model parameter variation: Topics by WorldWideScience.org

Sample records for model parameter variation

Temporal variation and scaling of parameters for a monthly hydrologic model

Science.gov (United States)

Deng, Chao; Liu, Pan; Wang, Dingbao; Wang, Weiguang

2018-03-01

The temporal variation of model parameters is affected by the catchment conditions and has a significant impact on hydrological simulation. This study aims to evaluate the seasonality and downscaling of model parameter across time scales based on monthly and mean annual water balance models with a common model framework. Two parameters of the monthly model, i.e., k and m, are assumed to be time-variant at different months. Based on the hydrological data set from 121 MOPEX catchments in the United States, we firstly analyzed the correlation between parameters (k and m) and catchment properties (NDVI and frequency of rainfall events, α). The results show that parameter k is positively correlated with NDVI or α, while the correlation is opposite for parameter m, indicating that precipitation and vegetation affect monthly water balance by controlling temporal variation of parameters k and m. The multiple linear regression is then used to fit the relationship between ε and the means and coefficient of variations of parameters k and m. Based on the empirical equation and the correlations between the time-variant parameters and NDVI, the mean annual parameter ε is downscaled to monthly k and m. The results show that it has lower NSEs than these from model with time-variant k and m being calibrated through SCE-UA, while for several study catchments, it has higher NSEs than that of the model with constant parameters. The proposed method is feasible and provides a useful tool for temporal scaling of model parameter.
Biosphere modelling for a HLW repository - scenario and parameter variations

International Nuclear Information System (INIS)

Grogan, H.

1985-03-01

In Switzerland high-level radioactive wastes have been considered for disposal in deep-lying crystalline formations. The individual doses to man resulting from radionuclides entering the biosphere via groundwater transport are calculated. The main recipient area modelled, which constitutes the base case, is a broad gravel terrace sited along the south bank of the river Rhine. An alternative recipient region, a small valley with a well, is also modelled. A number of parameter variations are performed in order to ascertain their impact on the doses. Finally two scenario changes are modelled somewhat simplistically, these consider different prevailing climates, namely tundra and a warmer climate than present. In the base case negligibly low doses to man in the long term, resulting from the existence of a HLW repository have been calculated. Cs-135 results in the largest dose (8.4E-7 mrem/y at 6.1E+6 y) while Np-237 gives the largest dose from the actinides (3.6E-8 mrem/y). The response of the model to parameter variations cannot be easily predicted due to non-linear coupling of many of the parameters. However, the calculated doses were negligibly low in all cases as were those resulting from the two scenario variations. (author)
Seasonal and spatial variation in broadleaf forest model parameters

Science.gov (United States)

Groenendijk, M.; van der Molen, M. K.; Dolman, A. J.

2009-04-01

Process based, coupled ecosystem carbon, energy and water cycle models are used with the ultimate goal to project the effect of future climate change on the terrestrial carbon cycle. A typical dilemma in such exercises is how much detail the model must be given to describe the observations reasonably realistic while also be general. We use a simple vegetation model (5PM) with five model parameters to study the variability of the parameters. These parameters are derived from the observed carbon and water fluxes from the FLUXNET database. For 15 broadleaf forests the model parameters were derived for different time resolutions. It appears that in general for all forests, the correlation coefficient between observed and simulated carbon and water fluxes improves with a higher parameter time resolution. The quality of the simulations is thus always better when a higher time resolution is used. These results show that annual parameters are not capable of properly describing weather effects on ecosystem fluxes, and that two day time resolution yields the best results. A first indication of the climate constraints can be found by the seasonal variation of the covariance between Jm, which describes the maximum electron transport for photosynthesis, and climate variables. A general seasonality we found is that during winter the covariance with all climate variables is zero. Jm increases rapidly after initial spring warming, resulting in a large covariance with air temperature and global radiation. During summer Jm is less variable, but co-varies negatively with air temperature and vapour pressure deficit and positively with soil water content. A temperature response appears during spring and autumn for broadleaf forests. This shows that an annual model parameter cannot be representative for the entire year. And relations with mean annual temperature are not possible. During summer the photosynthesis parameters are constrained by water availability, soil water content and
Inter-temporal variation in the travel time and travel cost parameters of transport models

OpenAIRE

Börjesson, Maria

2012-01-01

The parameters for travel time and travel cost are central in travel demand forecasting models. Since valuation of infrastructure investments requires prediction of travel demand for future evaluation years, inter-temporal variation of the travel time and travel cost parameters is a key issue in forecasting. Using two identical stated choice experiments conducted among Swedish drivers with an interval of 13 years, 1994 and 2007, this paper estimates the inter-temporal variation in travel time...
Multi-parameter variational calculations for the (2+1)-dimensional U(1) lattice gauge theory and the XY model

International Nuclear Information System (INIS)

Heys, D.W.; Stump, D.R.

1987-01-01

Variational calculations are described that use multi-parameter trial wave functions for the U(1) lattice gauge theory in two space dimensions, and for the XY model. The trial functions are constructed as the exponential of a linear combination of states from the strong-coupling basis of the model, with the coefficients treated as variational parameters. The expectation of the hamiltonian is computed by the Monte Carlo method, using a reweighting technique to evaluate expectation values in finite patches of the parameter space. The trial function for the U(1) gauge theory involves six variational parameters, and its weak-coupling behaviour is in reasonable agreement with theoretical expectations. (orig.)
Sensitivity analysis and parameter estimation for distributed hydrological modeling: potential of variational methods

Directory of Open Access Journals (Sweden)

W. Castaings

2009-04-01

Full Text Available Variational methods are widely used for the analysis and control of computationally intensive spatially distributed systems. In particular, the adjoint state method enables a very efficient calculation of the derivatives of an objective function (response function to be analysed or cost function to be optimised with respect to model inputs.

In this contribution, it is shown that the potential of variational methods for distributed catchment scale hydrology should be considered. A distributed flash flood model, coupling kinematic wave overland flow and Green Ampt infiltration, is applied to a small catchment of the Thoré basin and used as a relatively simple (synthetic observations but didactic application case.

It is shown that forward and adjoint sensitivity analysis provide a local but extensive insight on the relation between the assigned model parameters and the simulated hydrological response. Spatially distributed parameter sensitivities can be obtained for a very modest calculation effort (~6 times the computing time of a single model run and the singular value decomposition (SVD of the Jacobian matrix provides an interesting perspective for the analysis of the rainfall-runoff relation.

For the estimation of model parameters, adjoint-based derivatives were found exceedingly efficient in driving a bound-constrained quasi-Newton algorithm. The reference parameter set is retrieved independently from the optimization initial condition when the very common dimension reduction strategy (i.e. scalar multipliers is adopted.

Furthermore, the sensitivity analysis results suggest that most of the variability in this high-dimensional parameter space can be captured with a few orthogonal directions. A parametrization based on the SVD leading singular vectors was found very promising but should be combined with another regularization strategy in order to prevent overfitting.
Variational estimation of process parameters in a simplified atmospheric general circulation model

Science.gov (United States)

Lv, Guokun; Koehl, Armin; Stammer, Detlef

2016-04-01

Parameterizations are used to simulate effects of unresolved sub-grid-scale processes in current state-of-the-art climate model. The values of the process parameters, which determine the model's climatology, are usually manually adjusted to reduce the difference of model mean state to the observed climatology. This process requires detailed knowledge of the model and its parameterizations. In this work, a variational method was used to estimate process parameters in the Planet Simulator (PlaSim). The adjoint code was generated using automatic differentiation of the source code. Some hydrological processes were switched off to remove the influence of zero-order discontinuities. In addition, the nonlinearity of the model limits the feasible assimilation window to about 1day, which is too short to tune the model's climatology. To extend the feasible assimilation window, nudging terms for all state variables were added to the model's equations, which essentially suppress all unstable directions. In identical twin experiments, we found that the feasible assimilation window could be extended to over 1-year and accurate parameters could be retrieved. Although the nudging terms transform to a damping of the adjoint variables and therefore tend to erases the information of the data over time, assimilating climatological information is shown to provide sufficient information on the parameters. Moreover, the mechanism of this regularization is discussed.
Seasonal variation of photosynthetic model parameters and leaf area index from global Fluxnet eddy covariance data

Science.gov (United States)

Groenendijk, M.; Dolman, A. J.; Ammann, C.; Arneth, A.; Cescatti, A.; Dragoni, D.; Gash, J. H. C.; Gianelle, D.; Gioli, B.; Kiely, G.; Knohl, A.; Law, B. E.; Lund, M.; Marcolla, B.; van der Molen, M. K.; Montagnani, L.; Moors, E.; Richardson, A. D.; Roupsard, O.; Verbeeck, H.; Wohlfahrt, G.

2011-12-01

Global vegetation models require the photosynthetic parameters, maximum carboxylation capacity (Vcm), and quantum yield (α) to parameterize their plant functional types (PFTs). The purpose of this work is to determine how much the scaling of the parameters from leaf to ecosystem level through a seasonally varying leaf area index (LAI) explains the parameter variation within and between PFTs. Using Fluxnet data, we simulate a seasonally variable LAIF for a large range of sites, comparable to the LAIM derived from MODIS. There are discrepancies when LAIF reach zero levels and LAIM still provides a small positive value. We find that temperature is the most common constraint for LAIF in 55% of the simulations, while global radiation and vapor pressure deficit are the key constraints for 18% and 27% of the simulations, respectively, while large differences in this forcing still exist when looking at specific PFTs. Despite these differences, the annual photosynthesis simulations are comparable when using LAIF or LAIM (r2 = 0.89). We investigated further the seasonal variation of ecosystem-scale parameters derived with LAIF. Vcm has the largest seasonal variation. This holds for all vegetation types and climates. The parameter α is less variable. By including ecosystem-scale parameter seasonality we can explain a considerable part of the ecosystem-scale parameter variation between PFTs. The remaining unexplained leaf-scale PFT variation still needs further work, including elucidating the precise role of leaf and soil level nitrogen.
Numerical simulation of electro-osmotic consolidation coupling non-linear variation of soil parameters

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Wu, Hui; Hu, Liming; Wen, Qingbo

2017-06-01

Electro-osmotic consolidation is an effective method for soft ground improvement. A main limitation of previous numerical models on this technique is the ignorance of the non-linear variation of soil parameters. In the present study, a multi-field numerical model is developed with the consideration of the non-linear variation of soil parameters during electro-osmotic consolidation process. The numerical simulations on an axisymmetric model indicated that the non-linear variation of soil parameters showed remarkable impact on the development of the excess pore water pressure and degree of consolidation. A field experiment with complex geometry, boundary conditions, electrode configuration and voltage application was further simulated with the developed numerical model. The comparison between field and numerical data indicated that the numerical model coupling of the non-linear variation of soil parameters gave more reasonable results. The developed numerical model is capable to analyze engineering cases with complex operating conditions.
Parameter estimation for a cohesive sediment transport model by assimilating satellite observations in the Hangzhou Bay: Temporal variations and spatial distributions

Science.gov (United States)

Wang, Daosheng; Zhang, Jicai; He, Xianqiang; Chu, Dongdong; Lv, Xianqing; Wang, Ya Ping; Yang, Yang; Fan, Daidu; Gao, Shu

2018-01-01

Model parameters in the suspended cohesive sediment transport models are critical for the accurate simulation of suspended sediment concentrations (SSCs). Difficulties in estimating the model parameters still prevent numerical modeling of the sediment transport from achieving a high level of predictability. Based on a three-dimensional cohesive sediment transport model and its adjoint model, the satellite remote sensing data of SSCs during both spring tide and neap tide, retrieved from Geostationary Ocean Color Imager (GOCI), are assimilated to synchronously estimate four spatially and temporally varying parameters in the Hangzhou Bay in China, including settling velocity, resuspension rate, inflow open boundary conditions and initial conditions. After data assimilation, the model performance is significantly improved. Through several sensitivity experiments, the spatial and temporal variation tendencies of the estimated model parameters are verified to be robust and not affected by model settings. The pattern for the variations of the estimated parameters is analyzed and summarized. The temporal variations and spatial distributions of the estimated settling velocity are negatively correlated with current speed, which can be explained using the combination of flocculation process and Stokes' law. The temporal variations and spatial distributions of the estimated resuspension rate are also negatively correlated with current speed, which are related to the grain size of the seabed sediments under different current velocities. Besides, the estimated inflow open boundary conditions reach the local maximum values near the low water slack conditions and the estimated initial conditions are negatively correlated with water depth, which is consistent with the general understanding. The relationships between the estimated parameters and the hydrodynamic fields can be suggestive for improving the parameterization in cohesive sediment transport models.
Sensitivity of the model error parameter specification in weak-constraint four-dimensional variational data assimilation

Science.gov (United States)

Shaw, Jeremy A.; Daescu, Dacian N.

2017-08-01

This article presents the mathematical framework to evaluate the sensitivity of a forecast error aspect to the input parameters of a weak-constraint four-dimensional variational data assimilation system (w4D-Var DAS), extending the established theory from strong-constraint 4D-Var. Emphasis is placed on the derivation of the equations for evaluating the forecast sensitivity to parameters in the DAS representation of the model error statistics, including bias, standard deviation, and correlation structure. A novel adjoint-based procedure for adaptive tuning of the specified model error covariance matrix is introduced. Results from numerical convergence tests establish the validity of the model error sensitivity equations. Preliminary experiments providing a proof-of-concept are performed using the Lorenz multi-scale model to illustrate the theoretical concepts and potential benefits for practical applications.
Total Variation Based Parameter-Free Model for Impulse Noise Removal

DEFF Research Database (Denmark)

Sciacchitano, Federica; Dong, Yiqiu; Andersen, Martin Skovgaard

2017-01-01

We propose a new two-phase method for reconstruction of blurred images corrupted by impulse noise. In the first phase, we use a noise detector to identify the pixels that are contaminated by noise, and then, in the second phase, we reconstruct the noisy pixels by solving an equality constrained...... total variation minimization problem that preserves the exact values of the noise-free pixels. For images that are only corrupted by impulse noise (i. e., not blurred) we apply the semismooth Newton's method to a reduced problem, and if the images are also blurred, we solve the equality constrained...... reconstruction problem using a first-order primal-dual algorithm. The proposed model improves the computational efficiency (in the denoising case) and has the advantage of being regularization parameter-free. Our numerical results suggest that the method is competitive in terms of its restoration capabilities...
Variation of Parameters in Differential Equations (A Variation in Making Sense of Variation of Parameters)

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Quinn, Terry; Rai, Sanjay

2012-01-01

The method of variation of parameters can be found in most undergraduate textbooks on differential equations. The method leads to solutions of the non-homogeneous equation of the form y = u[subscript 1]y[subscript 1] + u[subscript 2]y[subscript 2], a sum of function products using solutions to the homogeneous equation y[subscript 1] and…
Analysis of the spatial variation in the parameters of the SWAT model with application in Flanders, Northern Belgium

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G. Heuvelmans

2004-01-01

Full Text Available Operational applications of a hydrological model often require the prediction of stream flow in (future time periods without stream flow observations or in ungauged catchments. Data for a case-specific optimisation of model parameters are not available for such applications, so parameters have to be derived from other catchments or time periods. It has been demonstrated that for applications of the SWAT in Northern Belgium, temporal transfers of the parameters have less influence than spatial transfers on the performance of the model. This study examines the spatial variation in parameter optima in more detail. The aim was to delineate zones wherein model parameters can be transferred without a significant loss of model performance. SWAT was calibrated for 25 catchments that are part of eight larger sub-basins of the Scheldt river basin. Two approaches are discussed for grouping these units in zones with a uniform set of parameters: a single parameter approach considering each parameter separately and a parameter set approach evaluating the parameterisation as a whole. For every catchment, the SWAT model was run with the local parameter optima, with the average parameter values for the entire study region (Flanders, with the zones delineated with the single parameter approach and with the zones obtained by the parameter set approach. Comparison of the model performances of these four parameterisation strategies indicates that both the single parameter and the parameter set zones lead to stream flow predictions that are more accurate than if the entire study region were treated as one single zone. On the other hand, the use of zonal average parameter values results in a considerably worse model fit compared to local parameter optima. Clustering of parameter sets gives a more accurate result than the single parameter approach and is, therefore, the preferred technique for use in the parameterisation of ungauged sub-catchments as part of the
Variational estimates of point-kinetics parameters

International Nuclear Information System (INIS)

Favorite, J.A.; Stacey, W.M. Jr.

1995-01-01

Variational estimates of the effect of flux shifts on the integral reactivity parameter of the point-kinetics equations and on regional power fractions were calculated for a variety of localized perturbations in two light water reactor (LWR) model problems representing a small, tightly coupled core and a large, loosely coupled core. For the small core, the flux shifts resulting from even relatively large localized reactivity changes (∼600 pcm) were small, and the standard point-kinetics approximation estimates of reactivity were in error by only ∼10% or less, while the variational estimates were accurate to within ∼1%. For the larger core, significant (>50%) flux shifts occurred in response to local perturbations, leading to errors of the same magnitude in the standard point-kinetics approximation of the reactivity worth. For positive reactivity, the error in the variational estimate of reactivity was only a few percent in the larger core, and the resulting transient power prediction was 1 to 2 orders of magnitude more accurate than with the standard point-kinetics approximation. For a large, local negative reactivity insertion resulting in a large flux shift, the accuracy of the variational estimate broke down. The variational estimate of the effect of flux shifts on reactivity in point-kinetics calculations of transients in LWR cores was found to generally result in greatly improved accuracy, relative to the standard point-kinetics approximation, the exception being for large negative reactivity insertions with large flux shifts in large, loosely coupled cores
Sensitivity analysis in oxidation ditch modelling: the effect of variations in stoichiometric, kinetic and operating parameters on the performance indices

NARCIS (Netherlands)

Abusam, A.A.A.; Keesman, K.J.; Straten, van G.; Spanjers, H.; Meinema, K.

2001-01-01

This paper demonstrates the application of the factorial sensitivity analysis methodology in studying the influence of variations in stoichiometric, kinetic and operating parameters on the performance indices of an oxidation ditch simulation model (benchmark). Factorial sensitivity analysis
The Social Network of Tracer Variations and O(100) Uncertain Photochemical Parameters in the Community Atmosphere Model

Science.gov (United States)

Lucas, D. D.; Labute, M.; Chowdhary, K.; Debusschere, B.; Cameron-Smith, P. J.

2014-12-01

Simulating the atmospheric cycles of ozone, methane, and other radiatively important trace gases in global climate models is computationally demanding and requires the use of 100's of photochemical parameters with uncertain values. Quantitative analysis of the effects of these uncertainties on tracer distributions, radiative forcing, and other model responses is hindered by the "curse of dimensionality." We describe efforts to overcome this curse using ensemble simulations and advanced statistical methods. Uncertainties from 95 photochemical parameters in the trop-MOZART scheme were sampled using a Monte Carlo method and propagated through 10,000 simulations of the single column version of the Community Atmosphere Model (CAM). The variance of the ensemble was represented as a network with nodes and edges, and the topology and connections in the network were analyzed using lasso regression, Bayesian compressive sensing, and centrality measures from the field of social network theory. Despite the limited sample size for this high dimensional problem, our methods determined the key sources of variation and co-variation in the ensemble and identified important clusters in the network topology. Our results can be used to better understand the flow of photochemical uncertainty in simulations using CAM and other climate models. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and supported by the DOE Office of Science through the Scientific Discovery Through Advanced Computing (SciDAC).
A variational approach to parameter estimation in ordinary differential equations

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Kaschek Daniel

2012-08-01

Full Text Available Abstract Background Ordinary differential equations are widely-used in the field of systems biology and chemical engineering to model chemical reaction networks. Numerous techniques have been developed to estimate parameters like rate constants, initial conditions or steady state concentrations from time-resolved data. In contrast to this countable set of parameters, the estimation of entire courses of network components corresponds to an innumerable set of parameters. Results The approach presented in this work is able to deal with course estimation for extrinsic system inputs or intrinsic reactants, both not being constrained by the reaction network itself. Our method is based on variational calculus which is carried out analytically to derive an augmented system of differential equations including the unconstrained components as ordinary state variables. Finally, conventional parameter estimation is applied to the augmented system resulting in a combined estimation of courses and parameters. Conclusions The combined estimation approach takes the uncertainty in input courses correctly into account. This leads to precise parameter estimates and correct confidence intervals. In particular this implies that small motifs of large reaction networks can be analysed independently of the rest. By the use of variational methods, elements from control theory and statistics are combined allowing for future transfer of methods between the two fields.
A variational approach to parameter estimation in ordinary differential equations.

Science.gov (United States)

Kaschek, Daniel; Timmer, Jens

2012-08-14

Ordinary differential equations are widely-used in the field of systems biology and chemical engineering to model chemical reaction networks. Numerous techniques have been developed to estimate parameters like rate constants, initial conditions or steady state concentrations from time-resolved data. In contrast to this countable set of parameters, the estimation of entire courses of network components corresponds to an innumerable set of parameters. The approach presented in this work is able to deal with course estimation for extrinsic system inputs or intrinsic reactants, both not being constrained by the reaction network itself. Our method is based on variational calculus which is carried out analytically to derive an augmented system of differential equations including the unconstrained components as ordinary state variables. Finally, conventional parameter estimation is applied to the augmented system resulting in a combined estimation of courses and parameters. The combined estimation approach takes the uncertainty in input courses correctly into account. This leads to precise parameter estimates and correct confidence intervals. In particular this implies that small motifs of large reaction networks can be analysed independently of the rest. By the use of variational methods, elements from control theory and statistics are combined allowing for future transfer of methods between the two fields.
Parameters in dynamic models of complex traits are containers of missing heritability.

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Yunpeng Wang

Full Text Available Polymorphisms identified in genome-wide association studies of human traits rarely explain more than a small proportion of the heritable variation, and improving this situation within the current paradigm appears daunting. Given a well-validated dynamic model of a complex physiological trait, a substantial part of the underlying genetic variation must manifest as variation in model parameters. These parameters are themselves phenotypic traits. By linking whole-cell phenotypic variation to genetic variation in a computational model of a single heart cell, incorporating genotype-to-parameter maps, we show that genome-wide association studies on parameters reveal much more genetic variation than when using higher-level cellular phenotypes. The results suggest that letting such studies be guided by computational physiology may facilitate a causal understanding of the genotype-to-phenotype map of complex traits, with strong implications for the development of phenomics technology.

Variation of the Moyer Model Parameter, H0, with primary proton energy

International Nuclear Information System (INIS)

Liu, K.L.; Stevenson, G.R.; Thomas, R.H.; Thomas, S.V.

1982-08-01

Experimental values of the Moyer Model Parameter H 0 were summarized and presented as a function of proton energy, E/sub p/. The variation of H 0 (E/sup p/) with E/sup p/ was studied by regression analysis. Regression Analysis of the data under log-log transformation gave a best value for the exponent m of 0.77 +- 0.26, but a t-test did not reject m = 1 (p +- 20%). Since m = 1 was not excluded, and a Fisher's F-test did not exclude linearity, a linear regression analysis was performed. A line passing through the origin was not rejected (Student's t-test, p = 30%) and has the equation: H 0 (E/sup p/ = (1.61 +- 0.19) x 10 -13 Sv.m 2 /GeV to be compared with a value of (1.65 +- 0.21) x 10 -13 Sv.m 2 /GeV published by Stevenson et al
Employment of single-diode model to elucidate the variations in photovoltaic parameters under different electrical and thermal conditions.

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Fahmi F Muhammad

Full Text Available In this research work, numerical simulations are performed to correlate the photovoltaic parameters with various internal and external factors influencing the performance of solar cells. Single-diode modeling approach is utilized for this purpose and theoretical investigations are compared with the reported experimental evidences for organic and inorganic solar cells at various electrical and thermal conditions. Electrical parameters include parasitic resistances (Rs and Rp and ideality factor (n, while thermal parameters can be defined by the cells temperature (T. A comprehensive analysis concerning broad spectral variations in the short circuit current (Isc, open circuit voltage (Voc, fill factor (FF and efficiency (η is presented and discussed. It was generally concluded that there exists a good agreement between the simulated results and experimental findings. Nevertheless, the controversial consequence of temperature impact on the performance of organic solar cells necessitates the development of a complementary model which is capable of well simulating the temperature impact on these devices performance.
MR angiography of stenosis and aneurysm models in the pulsatile flow: variation with imaging parameters and concentration of contrast media

International Nuclear Information System (INIS)

Park, Kyung Joo; Park, Jae Hyung; Lee, Hak Jong; Won, Hyung Jin; Lee, Dong Hyuk; Min, Byung Goo; Chang, Kee Hyun

1997-01-01

The image quality of magnetic resonance angiography (MRA) varies according to the imaging techniques applied and the parameters affected by blood flow patterns, as well as by the shape of the blood vessels. This study was designed to assess the influence on signal intensity and its distribution of the geometry of these vessels, the imaging parameters, and the concentration of contrast media in MRA of stenosis and aneurysm models. MRA was performed in stenosis and aneurysm models made of glass tubes, using pulsatile flow with viscosity and flow profile similar to those of blood. Slice and maximum intensity projection (MIP) images were obtained using various imaging techniques and parameters;there was variation in repetition time, flip angle, imaging planes, and concentrations of contrast media. On slice images of three-dimensional (3D) time-of-flight (TOF) techniques, flow signal intensity was measured at five locations in the models, and contrast ratio was calculated as the difference between flow signal intensity (SI) and background signal intensity (SIb) divided by background signal intensity or (SI-SIb)/SIb. MIP images obtained by various techniques and using various parameters were also analyzed, with emphasis in the stenosis model on demonstrated degree of stenosis, severity of signal void and image distortion, and in the aneurysm model, on degree of visualization, distortion of contour and distribution of signals. In 3D TOF, the shortest TR (36 msec) and the largest FA (50 deg ) resulted in the highest contrast ratio, but larger flip angles did not effectively demonstrate the demonstration of the peripheral part of the aneurysm. Loss of signal was most prominent in images of the stenosis model obtained with parallel or oblique planes to the flow direction. The two-dimensional TOF technique also caused signal void in stenosis, but precisely demonstrated the aneurysm, with dense opacification of the peripheral part. The phase contrast technique showed some
High frequency variations of Earth Rotation Parameters from GPS and GLONASS observations.

Science.gov (United States)

Wei, Erhu; Jin, Shuanggen; Wan, Lihua; Liu, Wenjie; Yang, Yali; Hu, Zhenghong

2015-01-28

The Earth's rotation undergoes changes with the influence of geophysical factors, such as Earth's surface fluid mass redistribution of the atmosphere, ocean and hydrology. However, variations of Earth Rotation Parameters (ERP) are still not well understood, particularly the short-period variations (e.g., diurnal and semi-diurnal variations) and their causes. In this paper, the hourly time series of Earth Rotation Parameters are estimated using Global Positioning System (GPS), Global Navigation Satellite System (GLONASS), and combining GPS and GLONASS data collected from nearly 80 sites from 1 November 2012 to 10 April 2014. These new observations with combining different satellite systems can help to decorrelate orbit biases and ERP, which improve estimation of ERP. The high frequency variations of ERP are analyzed using a de-trending method. The maximum of total diurnal and semidiurnal variations are within one milli-arcseconds (mas) in Polar Motion (PM) and 0.5 milli-seconds (ms) in UT1-UTC. The semidiurnal and diurnal variations are mainly related to the ocean tides. Furthermore, the impacts of satellite orbit and time interval used to determinate ERP on the amplitudes of tidal terms are analyzed. We obtain some small terms that are not described in the ocean tide model of the IERS Conventions 2010, which may be caused by the strategies and models we used or the signal noises as well as artifacts. In addition, there are also small differences on the amplitudes between our results and IERS convention. This might be a result of other geophysical excitations, such as the high-frequency variations in atmospheric angular momentum (AAM) and hydrological angular momentum (HAM), which needs more detailed analysis with more geophysical data in the future.
The effects of parameter variation on MSET models of the Crystal River-3 feedwater flow system

International Nuclear Information System (INIS)

Miron, A.

1998-01-01

In this paper we develop further the results reported in Reference 1 to include a systematic study of the effects of varying MSET models and model parameters for the Crystal River-3 (CR) feedwater flow system The study used archived CR process computer files from November 1-December 15, 1993 that were provided by Florida Power Corporation engineers Fairman Bockhorst and Brook Julias. The results support the conclusion that an optimal MSET model, properly trained and deriving its inputs in real-time from no more than 25 of the sensor signals normally provided to a PWR plant process computer, should be able to reliably detect anomalous variations in the feedwater flow venturis of less than 0.1% and in the absence of a venturi sensor signal should be able to generate a virtual signal that will be within 0.1% of the correct value of the missing signal
Analysis of variation in calibration curves for Kodak XV radiographic film using model-based parameters.

Science.gov (United States)

Hsu, Shu-Hui; Kulasekere, Ravi; Roberson, Peter L

2010-08-05

Film calibration is time-consuming work when dose accuracy is essential while working in a range of photon scatter environments. This study uses the single-target single-hit model of film response to fit the calibration curves as a function of calibration method, processor condition, field size and depth. Kodak XV film was irradiated perpendicular to the beam axis in a solid water phantom. Standard calibration films (one dose point per film) were irradiated at 90 cm source-to-surface distance (SSD) for various doses (16-128 cGy), depths (0.2, 0.5, 1.5, 5, 10 cm) and field sizes (5 × 5, 10 × 10 and 20 × 20 cm²). The 8-field calibration method (eight dose points per film) was used as a reference for each experiment, taken at 95 cm SSD and 5 cm depth. The delivered doses were measured using an Attix parallel plate chamber for improved accuracy of dose estimation in the buildup region. Three fitting methods with one to three dose points per calibration curve were investigated for the field sizes of 5 × 5, 10 × 10 and 20 × 20 cm². The inter-day variation of model parameters (background, saturation and slope) were 1.8%, 5.7%, and 7.7% (1 σ) using the 8-field method. The saturation parameter ratio of standard to 8-field curves was 1.083 ± 0.005. The slope parameter ratio of standard to 8-field curves ranged from 0.99 to 1.05, depending on field size and depth. The slope parameter ratio decreases with increasing depth below 0.5 cm for the three field sizes. It increases with increasing depths above 0.5 cm. A calibration curve with one to three dose points fitted with the model is possible with 2% accuracy in film dosimetry for various irradiation conditions. The proposed fitting methods may reduce workload while providing energy dependence correction in radiographic film dosimetry. This study is limited to radiographic XV film with a Lumisys scanner.
High Frequency Variations of Earth Rotation Parameters from GPS and GLONASS Observations

Directory of Open Access Journals (Sweden)

Erhu Wei

2015-01-01

Full Text Available The Earth’s rotation undergoes changes with the influence of geophysical factors, such as Earth’s surface fluid mass redistribution of the atmosphere, ocean and hydrology. However, variations of Earth Rotation Parameters (ERP are still not well understood, particularly the short-period variations (e.g., diurnal and semi-diurnal variations and their causes. In this paper, the hourly time series of Earth Rotation Parameters are estimated using Global Positioning System (GPS, Global Navigation Satellite System (GLONASS, and combining GPS and GLONASS data collected from nearly 80 sites from 1 November 2012 to 10 April 2014. These new observations with combining different satellite systems can help to decorrelate orbit biases and ERP, which improve estimation of ERP. The high frequency variations of ERP are analyzed using a de-trending method. The maximum of total diurnal and semidiurnal variations are within one milli-arcseconds (mas in Polar Motion (PM and 0.5 milli-seconds (ms in UT1-UTC. The semidiurnal and diurnal variations are mainly related to the ocean tides. Furthermore, the impacts of satellite orbit and time interval used to determinate ERP on the amplitudes of tidal terms are analyzed. We obtain some small terms that are not described in the ocean tide model of the IERS Conventions 2010, which may be caused by the strategies and models we used or the signal noises as well as artifacts. In addition, there are also small differences on the amplitudes between our results and IERS convention. This might be a result of other geophysical excitations, such as the high-frequency variations in atmospheric angular momentum (AAM and hydrological angular momentum (HAM, which needs more detailed analysis with more geophysical data in the future.
A Toolkit to Study Sensitivity of the Geant4 Predictions to the Variations of the Physics Model Parameters

Energy Technology Data Exchange (ETDEWEB)

Fields, Laura [Fermilab; Genser, Krzysztof [Fermilab; Hatcher, Robert [Fermilab; Kelsey, Michael [SLAC; Perdue, Gabriel [Fermilab; Wenzel, Hans [Fermilab; Wright, Dennis H. [SLAC; Yarba, Julia [Fermilab

2017-08-21

Geant4 is the leading detector simulation toolkit used in high energy physics to design detectors and to optimize calibration and reconstruction software. It employs a set of carefully validated physics models to simulate interactions of particles with matter across a wide range of interaction energies. These models, especially the hadronic ones, rely largely on directly measured cross-sections and phenomenological predictions with physically motivated parameters estimated by theoretical calculation or measurement. Because these models are tuned to cover a very wide range of possible simulation tasks, they may not always be optimized for a given process or a given material. This raises several critical questions, e.g. how sensitive Geant4 predictions are to the variations of the model parameters, or what uncertainties are associated with a particular tune of a Geant4 physics model, or a group of models, or how to consistently derive guidance for Geant4 model development and improvement from a wide range of available experimental data. We have designed and implemented a comprehensive, modular, user-friendly software toolkit to study and address such questions. It allows one to easily modify parameters of one or several Geant4 physics models involved in the simulation, and to perform collective analysis of multiple variants of the resulting physics observables of interest and comparison against a variety of corresponding experimental data. Based on modern event-processing infrastructure software, the toolkit offers a variety of attractive features, e.g. flexible run-time configurable workflow, comprehensive bookkeeping, easy to expand collection of analytical components. Design, implementation technology, and key functionalities of the toolkit are presented and illustrated with results obtained with Geant4 key hadronic models.
Influence of Population Variation of Physiological Parameters in Computational Models of Space Physiology

Science.gov (United States)

Myers, J. G.; Feola, A.; Werner, C.; Nelson, E. S.; Raykin, J.; Samuels, B.; Ethier, C. R.

2016-01-01

The earliest manifestations of Visual Impairment and Intracranial Pressure (VIIP) syndrome become evident after months of spaceflight and include a variety of ophthalmic changes, including posterior globe flattening and distension of the optic nerve sheath. Prevailing evidence links the occurrence of VIIP to the cephalic fluid shift induced by microgravity and the subsequent pressure changes around the optic nerve and eye. Deducing the etiology of VIIP is challenging due to the wide range of physiological parameters that may be influenced by spaceflight and are required to address a realistic spectrum of physiological responses. Here, we report on the application of an efficient approach to interrogating physiological parameter space through computational modeling. Specifically, we assess the influence of uncertainty in input parameters for two models of VIIP syndrome: a lumped-parameter model (LPM) of the cardiovascular and central nervous systems, and a finite-element model (FEM) of the posterior eye, optic nerve head (ONH) and optic nerve sheath. Methods: To investigate the parameter space in each model, we employed Latin hypercube sampling partial rank correlation coefficient (LHSPRCC) strategies. LHS techniques outperform Monte Carlo approaches by enforcing efficient sampling across the entire range of all parameters. The PRCC method estimates the sensitivity of model outputs to these parameters while adjusting for the linear effects of all other inputs. The LPM analysis addressed uncertainties in 42 physiological parameters, such as initial compartmental volume and nominal compartment percentage of total cardiac output in the supine state, while the FEM evaluated the effects on biomechanical strain from uncertainties in 23 material and pressure parameters for the ocular anatomy. Results and Conclusion: The LPM analysis identified several key factors including high sensitivity to the initial fluid distribution. The FEM study found that intraocular pressure and
Effect of variation of geometric parameters on the flow within a synthetic models of lower human airways

Science.gov (United States)

Espinosa Moreno, Andres Santiago; Duque Daza, Carlos Alberto

2017-11-01

The effects of variation of two geometric parameters, such as bifurcation angle and carina rounding radius, during the respiratory inhalation process, are studied numerically using two synthetic models of lower human airways. Laminar flow simulations were performed for six angles and three rounding radius, for 500, 1000, 1500 and 2000 for Reynolds numbers. Numerical results showed the existence of a direct relationship between the deformation of the velocity profiles (effect produced by the bifurcation) and the vortical structures observed through the secondary flow patterns. It is observed that the location of the vortices (and their related saddle point) is associated with the displacement of the velocity peak. On the other hand, increasing the angle and the rounding radius seems to bring about a growth of the pressure drop, which in turn displaces the distribution and peaks of the maximum shear stresses of the carina, that is, of the bifurcation point. Some physiological effects associated with the phenomena produced by these geometric variations are also discussed.
Parameter choice in Banach space regularization under variational inequalities

International Nuclear Information System (INIS)

Hofmann, Bernd; Mathé, Peter

2012-01-01

The authors study parameter choice strategies for the Tikhonov regularization of nonlinear ill-posed problems in Banach spaces. The effectiveness of any parameter choice for obtaining convergence rates depends on the interplay of the solution smoothness and the nonlinearity structure, and it can be expressed concisely in terms of variational inequalities. Such inequalities are link conditions between the penalty term, the norm misfit and the corresponding error measure. The parameter choices under consideration include an a priori choice, the discrepancy principle as well as the Lepskii principle. For the convenience of the reader, the authors review in an appendix a few instances where the validity of a variational inequality can be established. (paper)
Complexity, parameter sensitivity and parameter transferability in the modelling of floodplain inundation

Science.gov (United States)

Bates, P. D.; Neal, J. C.; Fewtrell, T. J.

2012-12-01

inferences regarding appropriate model complexity can only be achieved if such effects are rigorously controlled for. In terms of the second question we show evidence that leads us to posit a general rule of parameter sensitivity for hydraulic, and perhaps other, models. This is that as models become more physically complex (and hence better represent the underlying physical system) their sensitivity to parameter variation reduces. We hypothesize that with increasing model complexity the friction parameter in hydraulic model becomes less 'effective' and needs to compensate for fewer unrepresented processes. By 'unrepresented' we here mean both processes that are simply not represented by the model controlling equations and processes which are permitted by the model physics but which occur at sub-grid scales and therefore cannot in practice be simulated. This reducing sensitivity to parameter variation with increasing complexity is also shown to have important implications for the transferability of optimum calibrated parameters between events. We show that whilst simpler models may often be calibrated to achieve the same level of simulation performance as more complex codes, they may sometimes be less adept at prediction due to their greater parameter sensitivity.
Performance analysis of pin fins with temperature dependent thermal parameters using the variation of parameters method

Directory of Open Access Journals (Sweden)

Cihat Arslantürk

2016-08-01

Full Text Available The performance of pin fins transferring heat by convection and radiation and having variable thermal conductivity, variable emissivity and variable heat transfer coefficient was investigated in the present paper. Nondimensionalizing the fin equation, the problem parameters which affect the fin performance were obtained. Dimensionless nonlinear fin equation was solved with the variation of parameters method, which is quite new in the solution of nonlinear heat transfer problems. The solution of variation of parameters method was compared with known analytical solutions and some numerical solution. The comparisons showed that the solutions are seen to be perfectly compatible. The effects of problem parameters were investigated on the heat transfer rate and fin efficiency and results were presented graphically.
Real-time simulation of response to load variation for a ship reactor based on point-reactor double regions and lumped parameter model

Energy Technology Data Exchange (ETDEWEB)

Wang Qiao; Zhang De [Department of Nuclear Energy Science and Engineering, Naval University of Engineering, Wuhan 430033 (China); Chen Wenzhen, E-mail: Cwz2@21cn.com [Department of Nuclear Energy Science and Engineering, Naval University of Engineering, Wuhan 430033 (China); Chen Zhiyun [Department of Nuclear Energy Science and Engineering, Naval University of Engineering, Wuhan 430033 (China)

2011-05-15

Research highlights: > We calculate the variation of main parameters of the reactor core by the Simulink. > The Simulink calculation software (SCS) can deal well with the stiff problem. > The high calculation precision is reached with less time, and the results can be easily displayed. > The quick calculation of ship reactor transient can be achieved by this method. - Abstract: Based on the point-reactor double regions and lumped parameter model, while the nuclear power plant second loop load is increased or decreased quickly, the Simulink calculation software (SCS) is adopted to calculate the variation of main physical and thermal-hydraulic parameters of the reactor core. The calculation results are compared with those of three-dimensional simulation program. It is indicated that the SCS can deal well with the stiff problem of the point-reactor kinetics equations and the coupled problem of neutronics and thermal-hydraulics. The high calculation precision can be reached with less time, and the quick calculation of parameters of response to load disturbance for the ship reactor can be achieved. The clear image of the calculation results can also be displayed quickly by the SCS, which is very significant and important to guarantee the reactor safety operation.
Comparison of earthquake source parameters and interseismic plate coupling variations in global subduction zones (Invited)

Science.gov (United States)

Bilek, S. L.; Moyer, P. A.; Stankova-Pursley, J.

2010-12-01

Geodetically determined interseismic coupling variations have been found in subduction zones worldwide. These coupling variations have been linked to heterogeneities in interplate fault frictional conditions. These connections to fault friction imply that observed coupling variations are also important in influencing details in earthquake rupture behavior. Because of the wealth of newly available geodetic models along many subduction zones, it is now possible to examine detailed variations in coupling and compare to seismicity characteristics. Here we use a large catalog of earthquake source time functions and slip models for moderate to large magnitude earthquakes to explore these connections, comparing earthquake source parameters with available models of geodetic coupling along segments of the Japan, Kurile, Kamchatka, Peru, Chile, and Alaska subduction zones. In addition, we use published geodetic results along the Costa Rica margin to compare with source parameters of small magnitude earthquakes recorded with an onshore-offshore network of seismometers. For the moderate to large magnitude earthquakes, preliminary results suggest a complex relationship between earthquake parameters and estimates of strongly and weakly coupled segments of the plate interface. For example, along the Kamchatka subduction zone, these earthquakes occur primarily along the transition between strong and weak coupling, with significant heterogeneity in the pattern of moment scaled duration with respect to the coupling estimates. The longest scaled duration event in this catalog occurred in a region of strong coupling. Earthquakes along the transition between strong and weakly coupled exhibited the most complexity in the source time functions. Use of small magnitude (0.5 earthquake spectra, with higher corner frequencies and higher mean apparent stress for earthquakes that occur in along the Osa Peninsula relative to the Nicoya Peninsula, mimicking the along-strike variations in
Optimal parameters for the FFA-Beddoes dynamic stall model

Energy Technology Data Exchange (ETDEWEB)

Bjoerck, A; Mert, M [FFA, The Aeronautical Research Institute of Sweden, Bromma (Sweden); Madsen, H A [Risoe National Lab., Roskilde (Denmark)

1999-03-01

Unsteady aerodynamic effects, like dynamic stall, must be considered in calculation of dynamic forces for wind turbines. Models incorporated in aero-elastic programs are of semi-empirical nature. Resulting aerodynamic forces therefore depend on values used for the semi-empiricial parameters. In this paper a study of finding appropriate parameters to use with the Beddoes-Leishman model is discussed. Minimisation of the `tracking error` between results from 2D wind tunnel tests and simulation with the model is used to find optimum values for the parameters. The resulting optimum parameters show a large variation from case to case. Using these different sets of optimum parameters in the calculation of blade vibrations, give rise to quite different predictions of aerodynamic damping which is discussed. (au)
Uncertainty Quantification and Global Sensitivity Analysis of Subsurface Flow Parameters to Gravimetric Variations During Pumping Tests in Unconfined Aquifers

Science.gov (United States)

Maina, Fadji Zaouna; Guadagnini, Alberto

2018-01-01

We study the contribution of typically uncertain subsurface flow parameters to gravity changes that can be recorded during pumping tests in unconfined aquifers. We do so in the framework of a Global Sensitivity Analysis and quantify the effects of uncertainty of such parameters on the first four statistical moments of the probability distribution of gravimetric variations induced by the operation of the well. System parameters are grouped into two main categories, respectively, governing groundwater flow in the unsaturated and saturated portions of the domain. We ground our work on the three-dimensional analytical model proposed by Mishra and Neuman (2011), which fully takes into account the richness of the physical process taking place across the unsaturated and saturated zones and storage effects in a finite radius pumping well. The relative influence of model parameter uncertainties on drawdown, moisture content, and gravity changes are quantified through (a) the Sobol' indices, derived from a classical decomposition of variance and (b) recently developed indices quantifying the relative contribution of each uncertain model parameter to the (ensemble) mean, skewness, and kurtosis of the model output. Our results document (i) the importance of the effects of the parameters governing the unsaturated flow dynamics on the mean and variance of local drawdown and gravity changes; (ii) the marked sensitivity (as expressed in terms of the statistical moments analyzed) of gravity changes to the employed water retention curve model parameter, specific yield, and storage, and (iii) the influential role of hydraulic conductivity of the unsaturated and saturated zones to the skewness and kurtosis of gravimetric variation distributions. The observed temporal dynamics of the strength of the relative contribution of system parameters to gravimetric variations suggest that gravity data have a clear potential to provide useful information for estimating the key hydraulic
Reactor thermal behaviors under kinetics parameters variations in fast reactivity insertion

Energy Technology Data Exchange (ETDEWEB)

Abou-El-Maaty, Talal [Reactors Department, Atomic Energy Authority, Cairo 13759 (Egypt)], E-mail: talal22969@yahoo.com; Abdelhady, Amr [Reactors Department, Atomic Energy Authority, Cairo 13759 (Egypt)

2009-03-15

The influences of variations in some of the kinetics parameters affecting the reactivity insertion are considered in this study, it has been accomplished in order to acquire knowledge about the role that kinetic parameters play in prompt critical transients from the safety point of view. The kinetics parameters variations are limited to the effective delayed neutron fraction ({beta}{sub eff}) and the prompt neutron generation time ({lambda}). The reactor thermal behaviors under the variations in effective delayed neutron fraction and prompt neutron generation time included, the reactor power, maximum fuel temperature, maximum clad temperature, maximum coolant temperature and the mass flux variations at the hot channel. The analysis is done for a typical swimming pool, plate type research reactor with low enriched uranium. The scram system is disabled during the accidents simulations. Calculations were done using PARET code. As a result of simulations, it is concluded that, the reactor (ETRR2) thermal behavior is considerably more sensitive to the variation in the effective delayed neutron fraction than to the variation in prompt neutron generation time and the fast reactivity insertion in both cases causes a flow expansion and contraction at the hot channel exit. The amplitude of the oscillated flow is a qualitatively increases with the decrease in both {beta}{sub eff} and {lambda}.
A variational void coalescence model for ductile metals

KAUST Repository

Siddiq, Amir

2011-08-17

We present a variational void coalescence model that includes all the essential ingredients of failure in ductile porous metals. The model is an extension of the variational void growth model by Weinberg et al. (Comput Mech 37:142-152, 2006). The extended model contains all the deformation phases in ductile porous materials, i.e. elastic deformation, plastic deformation including deviatoric and volumetric (void growth) plasticity followed by damage initiation and evolution due to void coalescence. Parametric studies have been performed to assess the model\\'s dependence on the different input parameters. The model is then validated against uniaxial loading experiments for different materials. We finally show the model\\'s ability to predict the damage mechanisms and fracture surface profile of a notched round bar under tension as observed in experiments. © Springer-Verlag 2011.
Variations of little Higgs models and their electroweak constraints

International Nuclear Information System (INIS)

Csaki, Csaba; Hubisz, Jay; Meade, Patrick; Kribs, Graham D.; Terning, John

2003-01-01

We calculate the tree-level electroweak precision constraints on a wide class of little Higgs models including variations of the littlest Higgs SU(5)/SO(5), SU(6)/Sp(6), and SU(4) 4 /SU(3) 4 models. By performing a global fit to the precision data we find that for generic regions of the parameter space the bound on the symmetry breaking scale f is several TeV, where we have kept the normalization of f constant in the different models. For example, the 'minimal' implementation of SU(6)/Sp(6) is bounded by f>3.0 TeV throughout most of the parameter space, and SU(4) 4 /SU(3) 4 is bounded by f 2 ≡f 1 2 +f 2 2 >(4.2 TeV) 2 . In certain models, such as SU(4) 4 /SU(3) 4 , a large f does not directly imply a large amount of fine-tuning since the heavy-fermion masses that contribute to the Higgs boson mass can be lowered below f for a carefully chosen set of parameters. We also find that for certain models (or variations) there exist regions of parameter space in which the bound on f can be lowered into the range 1-2 TeV. These regions are typically characterized by a small mixing between heavy and standard model gauge bosons and a small (or vanishing) coupling between heavy U(1) gauge bosons and light fermions. Whether such a region of parameter space is natural or not is ultimately contingent on the UV completion

Revealing the physical insight of a length-scale parameter in metamaterials by exploiting the variational formulation

Science.gov (United States)

Abali, B. Emek

2018-04-01

For micro-architectured materials with a substructure, called metamaterials, we can realize a direct numerical simulation in the microscale by using classical mechanics. This method is accurate, however, computationally costly. Instead, a solution of the same problem in the macroscale is possible by means of the generalized mechanics. In this case, no detailed modeling of the substructure is necessary; however, new parameters emerge. A physical interpretation of these metamaterial parameters is challenging leading to a lack of experimental strategies for their determination. In this work, we exploit the variational formulation based on action principles and obtain a direct relation between a parameter used in the kinetic energy and a metamaterial parameter in the case of a viscoelastic model.
Estimation of Staphylococcus aureus growth parameters from turbidity data: characterization of strain variation and comparison of methods.

Science.gov (United States)

Lindqvist, R

2006-07-01

Turbidity methods offer possibilities for generating data required for addressing microorganism variability in risk modeling given that the results of these methods correspond to those of viable count methods. The objectives of this study were to identify the best approach for determining growth parameters based on turbidity data and use of a Bioscreen instrument and to characterize variability in growth parameters of 34 Staphylococcus aureus strains of different biotypes isolated from broiler carcasses. Growth parameters were estimated by fitting primary growth models to turbidity growth curves or to detection times of serially diluted cultures either directly or by using an analysis of variance (ANOVA) approach. The maximum specific growth rates in chicken broth at 17 degrees C estimated by time to detection methods were in good agreement with viable count estimates, whereas growth models (exponential and Richards) underestimated growth rates. Time to detection methods were selected for strain characterization. The variation of growth parameters among strains was best described by either the logistic or lognormal distribution, but definitive conclusions require a larger data set. The distribution of the physiological state parameter ranged from 0.01 to 0.92 and was not significantly different from a normal distribution. Strain variability was important, and the coefficient of variation of growth parameters was up to six times larger among strains than within strains. It is suggested to apply a time to detection (ANOVA) approach using turbidity measurements for convenient and accurate estimation of growth parameters. The results emphasize the need to consider implications of strain variability for predictive modeling and risk assessment.
Sensitivity analysis with respect to observations in variational data assimilation for parameter estimation

Directory of Open Access Journals (Sweden)

V. Shutyaev

2018-06-01

Full Text Available The problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem to find unknown parameters of the model. The observation data, and hence the optimal solution, may contain uncertainties. A response function is considered as a functional of the optimal solution after assimilation. Based on the second-order adjoint techniques, the sensitivity of the response function to the observation data is studied. The gradient of the response function is related to the solution of a nonstandard problem involving the coupled system of direct and adjoint equations. The nonstandard problem is studied, based on the Hessian of the original cost function. An algorithm to compute the gradient of the response function with respect to observations is presented. A numerical example is given for the variational data assimilation problem related to sea surface temperature for the Baltic Sea thermodynamics model.
Vibration control of an MR vehicle suspension system considering both hysteretic behavior and parameter variation

International Nuclear Information System (INIS)

Choi, Seung-Bok; Seong, Min-Sang; Ha, Sung-Hoon

2009-01-01

This paper presents vibration control responses of a controllable magnetorheological (MR) suspension system considering the two most important characteristics of the system; the field-dependent hysteretic behavior of the MR damper and the parameter variation of the suspension. In order to achieve this goal, a cylindrical MR damper which is applicable to a middle-sized passenger car is designed and manufactured. After verifying the damping force controllability, the field-dependent hysteretic behavior of the MR damper is identified using the Preisach hysteresis model. The full-vehicle suspension model is then derived by considering vertical, pitch and roll motions. An H ∞ controller is designed by treating the sprung mass of the vehicle as a parameter variation and integrating it with the hysteretic compensator which produces additional control input. In order to demonstrate the effectiveness and robustness of the proposed control system, the hardware-in-the-loop simulation (HILS) methodology is adopted by integrating the suspension model with the proposed MR damper. Vibration control responses of the vehicle suspension system such as vertical acceleration are evaluated under both bump and random road conditions
Source term modelling parameters for Project-90

International Nuclear Information System (INIS)

Shaw, W.; Smith, G.; Worgan, K.; Hodgkinson, D.; Andersson, K.

1992-04-01

This document summarises the input parameters for the source term modelling within Project-90. In the first place, the parameters relate to the CALIBRE near-field code which was developed for the Swedish Nuclear Power Inspectorate's (SKI) Project-90 reference repository safety assessment exercise. An attempt has been made to give best estimate values and, where appropriate, a range which is related to variations around base cases. It should be noted that the data sets contain amendments to those considered by KBS-3. In particular, a completely new set of inventory data has been incorporated. The information given here does not constitute a complete set of parameter values for all parts of the CALIBRE code. Rather, it gives the key parameter values which are used in the constituent models within CALIBRE and the associated studies. For example, the inventory data acts as an input to the calculation of the oxidant production rates, which influence the generation of a redox front. The same data is also an initial value data set for the radionuclide migration component of CALIBRE. Similarly, the geometrical parameters of the near-field are common to both sub-models. The principal common parameters are gathered here for ease of reference and avoidance of unnecessary duplication and transcription errors. (au)
Variations of the bacterial foraging algorithm for the extraction of PV module parameters from nameplate data

International Nuclear Information System (INIS)

Awadallah, Mohamed A.

2016-01-01

Highlights: • Bacterial foraging algorithm is used to extract PV model parameters from nameplate data. • Five variations of the bacterial foraging algorithm are compared on a simple objective function. • Best results obtained when swarming is neglected, step size is varied, and global best is preserved. • The technique is successfully applied on single- and double-diode models. • Matching between computation and measurements validates the obtained set of parameters. - Abstract: The paper introduces the task of parameter extraction of photovoltaic (PV) modules as a nonlinear optimization problem. The concerned parameters are the series resistance, shunt resistance, diode ideality factor, and diode reverse saturation current for both the single- and double-diode models. An error function representing the mismatch between computed and targeted performance is minimized using different versions of the bacterial foraging (BF) algorithm of global search and heuristic optimization. The targeted performance is obtained from the nameplate data of the PV module. Five distinct variations of the BF algorithm are used to solve the problem independently for the single- and double-diode models. The best optimization results are obtained when swarming is eliminated, chemotactic step size is dynamically varied, and global best is preserved, all acting together. Under such conditions, the best global minimum of 0.0028 is reached in an average best time of 94.4 sec for the single-diode model. However, it takes an average of 153 sec to reach the best global minimum of 0.0021 in case of double-diode model. An experimental verification study involves the comparison of computed performance to measurements on an Eclipsall PV module. It is shown that all variants of the BF algorithm could reach equivalent-circuit parameters with accepted accuracy by solving the optimization problem. The good matching between analytical and experimental results indicates the effectiveness of the
diurnal variation in blood parameters in the chicken in the hot

African Journals Online (AJOL)

Dr Olaleye

Twelve adult male chicken of the Nigerian local strain were bled every 3 Hours for 24 hours. Haematological and serum biochemical parameters were measured in the samples collected. Variations in the levels of these parameters throughout the 24 hours were determined. Thirteen out of the parameters measured showed.
Modeling of mouse eye and errors in ocular parameters affecting refractive state

Science.gov (United States)

Bawa, Gurinder

Rodents eye are particularly used to study refractive error state of an eye and development of refractive eye. Genetic organization of rodents is similar to that of humans, which makes them interesting candidates to be researched upon. From rodents family mice models are encouraged over rats because of availability of genetically engineered models. Despite of extensive work that has been performed on mice and rat models, still no one is able to quantify an optical model, due to variability in the reported ocular parameters. In this Dissertation, we have extracted ocular parameters and generated schematics of eye from the raw data from School of Medicine, Detroit. In order to see how the rays would travel through an eye and the defects associated with an eye; ray tracing has been performed using ocular parameters. Finally we have systematically evaluated the contribution of various ocular parameters, such as radii of curvature of ocular surfaces, thicknesses of ocular components, and refractive indices of ocular refractive media, using variational analysis and a computational model of the rodent eye. Variational analysis revealed that variation in all the ocular parameters does affect the refractive status of the eye, but depending upon the magnitude of the impact those parameters are listed as critical or non critical. Variation in the depth of the vitreous chamber, thickness of the lens, radius of the anterior surface of the cornea, radius of the anterior surface of the lens, as well as refractive indices for the lens and vitreous, appears to have the largest impact on the refractive error and thus are categorized as critical ocular parameters. The radii of the posterior surfaces of the cornea and lens have much smaller contributions to the refractive state, while the radii of the anterior and posterior surfaces of the retina have no effect on the refractive error. These data provide the framework for further refinement of the optical models of the rat and mouse
Insights into pre-reversal paleosecular variation from stochastic models

Directory of Open Access Journals (Sweden)

Klaudio ePeqini

2015-09-01

Full Text Available To provide insights on the paleosecular variation of the geomagnetic field and the mechanism of reversals, long time series of the dipolar magnetic moment are generated by two different stochastic models, known as the domino model and the inhomogeneous Lebovitz disk dynamo model, with initial values taken from the from paleomagnetic data. The former model considers mutual interactions of N macrospins embedded in a uniformly rotating medium, where random forcing and dissipation act on each macrospin. With an appropriate set of the model’s parameters values, the series generated by this model have similar statistical behaviour to the time series of the SHA.DIF.14K model. The latter model is an extension of the classical two-disk Rikitake model, considering N dynamo elements with appropriate interactions between them.We varied the parameters set of both models aiming at generating suitable time series with behaviour similar to the long time series of recent secular variation (SV. Such series are then extended to the near future, obtaining reversals in both cases of models. The analysis of the time series generated by simulating the models show that the reversals appears after a persistent period of low intensity geomagnetic field, as it is occurring in the present times.
Continuous radon measurements in schools: time variations and related parameters

International Nuclear Information System (INIS)

Giovani, C.; Cappelletto, C.; Garavaglia, M.; Pividore, S.; Villalta, R.

2004-01-01

Some results are reported of observations made within a four-year survey, during different seasons and in different conditions of school building use. Natural radon variations (day-night cycles, seasonal and temperature dependent variations etc..) and artificial ones (opening of windows, weekends and vacations, deployment of air conditioning or heating systems. etc.) were investigated as parameters affecting time dependent radon concentrations. (P.A.)
Assimilation of Earth rotation parameters into a global ocean model (FESOM)

Science.gov (United States)

Androsov, A.; Schröter, J.; Brunnabend, S.; Saynisch, J.

2012-04-01

Earth Rotation Parameters (ERP) are used to improve estimates of the ocean circulation and mass budget. GRACE data can be used for verification or for further improvements. The Finite Element Sea-ice Ocean Model (FESOM) is used to simulate weekly ocean circulation and mass variations. The FESOM model is a hydrostatic ocean circulation model with a fully non-linear free surface. It solves the hydrostatic primitive equations with volume (Boussinesq approximation) and mass (Greatbatch correction) conservation. Fresh water exchange with the atmosphere and land is modelled as mass flux. This flux is the weakest part of the mass budget as it is the difference of large and uncertain quantities: evaporation, precipitation and river runoff. All uncertainties included in these parameters are directly reflected in the model results. ERP help in closing the budget in a realistic manner. Our strategy is designed for testing parametric estimation on a weekly basis. First, Oceanographic Earth rotation parameters (OERP) are calculated by subtracting atmospheric and hydrologic estimates from observed ERP. They are compared to OERP derived from a global ocean circulation model. The difference can be inverted to diagnose a correction of the oceanic mass budget. Additionally mass variations measured by GRACE are used for verification. In a second step, the global mass correction parameter, derived by the inversion, is used to improve the fresh water budget of FESOM.
Iterative method of the parameter variation for solution of nonlinear functional equations

International Nuclear Information System (INIS)

Davidenko, D.F.

1975-01-01

The iteration method of parameter variation is used for solving nonlinear functional equations in Banach spaces. The authors consider some methods for numerical integration of ordinary first-order differential equations and construct the relevant iteration methods of parameter variation, both one- and multifactor. They also discuss problems of mathematical substantiation of the method, study the conditions and rate of convergence, estimate the error. The paper considers the application of the method to specific functional equations
Parameterization of aquatic ecosystem functioning and its natural variation: Hierarchical Bayesian modelling of plankton food web dynamics

Science.gov (United States)

Norros, Veera; Laine, Marko; Lignell, Risto; Thingstad, Frede

2017-10-01

Methods for extracting empirically and theoretically sound parameter values are urgently needed in aquatic ecosystem modelling to describe key flows and their variation in the system. Here, we compare three Bayesian formulations for mechanistic model parameterization that differ in their assumptions about the variation in parameter values between various datasets: 1) global analysis - no variation, 2) separate analysis - independent variation and 3) hierarchical analysis - variation arising from a shared distribution defined by hyperparameters. We tested these methods, using computer-generated and empirical data, coupled with simplified and reasonably realistic plankton food web models, respectively. While all methods were adequate, the simulated example demonstrated that a well-designed hierarchical analysis can result in the most accurate and precise parameter estimates and predictions, due to its ability to combine information across datasets. However, our results also highlighted sensitivity to hyperparameter prior distributions as an important caveat of hierarchical analysis. In the more complex empirical example, hierarchical analysis was able to combine precise identification of parameter values with reasonably good predictive performance, although the ranking of the methods was less straightforward. We conclude that hierarchical Bayesian analysis is a promising tool for identifying key ecosystem-functioning parameters and their variation from empirical datasets.
Lumped-parameter models

Energy Technology Data Exchange (ETDEWEB)

Ibsen, Lars Bo; Liingaard, M.

2006-12-15

A lumped-parameter model represents the frequency dependent soil-structure interaction of a massless foundation placed on or embedded into an unbounded soil domain. In this technical report the steps of establishing a lumped-parameter model are presented. Following sections are included in this report: Static and dynamic formulation, Simple lumped-parameter models and Advanced lumped-parameter models. (au)
Four-parameter model for polarization-resolved rough-surface BRDF.

Science.gov (United States)

Renhorn, Ingmar G E; Hallberg, Tomas; Bergström, David; Boreman, Glenn D

2011-01-17

A modeling procedure is demonstrated, which allows representation of polarization-resolved BRDF data using only four parameters: the real and imaginary parts of an effective refractive index with an added parameter taking grazing incidence absorption into account and an angular-scattering parameter determined from the BRDF measurement of a chosen angle of incidence, preferably close to normal incidence. These parameters allow accurate predictions of s- and p-polarized BRDF for a painted rough surface, over three decades of variation in BRDF magnitude. To characterize any particular surface of interest, the measurements required to determine these four parameters are the directional hemispherical reflectance (DHR) for s- and p-polarized input radiation and the BRDF at a selected angle of incidence. The DHR data describes the angular and polarization dependence, as well as providing the overall normalization constraint. The resulting model conserves energy and fulfills the reciprocity criteria.
Analysis of spin and gauge models with variational methods

International Nuclear Information System (INIS)

Dagotto, E.; Masperi, L.; Moreo, A.; Della Selva, A.; Fiore, R.

1985-01-01

Since independent-site (link) or independent-link (plaquette) variational states enhance the order or the disorder, respectively, in the treatment of spin (gauge) models, we prove that mixed states are able to improve the critical coupling while giving the qualitatively correct behavior of the relevant parameters
Storm surge model based on variational data assimilation method

Directory of Open Access Journals (Sweden)

Shi-li Huang

2010-06-01

Full Text Available By combining computation and observation information, the variational data assimilation method has the ability to eliminate errors caused by the uncertainty of parameters in practical forecasting. It was applied to a storm surge model based on unstructured grids with high spatial resolution meant for improving the forecasting accuracy of the storm surge. By controlling the wind stress drag coefficient, the variation-based model was developed and validated through data assimilation tests in an actual storm surge induced by a typhoon. In the data assimilation tests, the model accurately identified the wind stress drag coefficient and obtained results close to the true state. Then, the actual storm surge induced by Typhoon 0515 was forecast by the developed model, and the results demonstrate its efficiency in practical application.
A practical approach to parameter estimation applied to model predicting heart rate regulation

DEFF Research Database (Denmark)

Olufsen, Mette; Ottesen, Johnny T.

2013-01-01

Mathematical models have long been used for prediction of dynamics in biological systems. Recently, several efforts have been made to render these models patient specific. One way to do so is to employ techniques to estimate parameters that enable model based prediction of observed quantities....... Knowledge of variation in parameters within and between groups of subjects have potential to provide insight into biological function. Often it is not possible to estimate all parameters in a given model, in particular if the model is complex and the data is sparse. However, it may be possible to estimate...... a subset of model parameters reducing the complexity of the problem. In this study, we compare three methods that allow identification of parameter subsets that can be estimated given a model and a set of data. These methods will be used to estimate patient specific parameters in a model predicting...
Impacts of meteorological parameters and emissions on decadal, interannual, and seasonal variations of atmospheric black carbon in the Tibetan Plateau

Directory of Open Access Journals (Sweden)

Yu-Hao Mao

2016-09-01

Full Text Available We quantified the impacts of variations in meteorological parameters and emissions on decadal, interannual, and seasonal variations of atmospheric black carbon (BC in the Tibetan Plateau for 1980–2010 using a global 3-dimensional chemical transport model driven by the Modern Era Retrospective-analysis for Research and Applications (MERRA meteorological fields. From 1980 to 2010, simulated surface BC concentrations and all-sky direct radiative forcing at the top of the atmosphere due to atmospheric BC increased by 0.15 μg m−3 (63% and by 0.23 W m−2 (62%, respectively, averaged over the Tibetan Plateau (75–105°E, 25–40°N. Simulated annual mean surface BC concentrations were in the range of 0.24–0.40 μg m−3 averaged over the plateau for 1980–2010, with the decadal trends of 0.13 μg m−3 per decade in the 1980s and 0.08 in the 2000s. The interannual variations were −5.4% to 7.0% for deviation from the mean, 0.0062 μg m−3 for mean absolute deviation, and 2.5% for absolute percent departure from the mean. Model sensitivity simulations indicated that the decadal trends of surface BC concentrations were mainly driven by changes in emissions, while the interannual variations were dependent on variations of both meteorological parameters and emissions. Meteorological parameters played a crucial role in driving the interannual variations of BC especially in the monsoon season.
Comparison of ionospheric profile parameters with IRI-2012 model over Jicamarca

Science.gov (United States)

Bello, S. A.; Abdullah, M.; Hamid, N. S. A.; Reinisch, B. W.

2017-05-01

We used the hourly ionogram data obtained from Jicamarca station (12° S, 76.9° W, dip latitude: 1.0° N) an equatorial region to study the variation of the electron density profile parameters: maximum height of F2-layer (hmF2), bottomside thickness (B0) and shape (B1) parameter of F-layer. The period of study is for the year 2010 (solar minimum period).The diurnal monthly averages of these parameters are compared with the updated IRI-2012 model. The results show that hmF2 is highest during the daytime than nighttime. The variation in hmF2 was observed to modulate the thickness of the bottomside F2-layer. The observed hmF2 and B0 post-sunset peak is as result of the upward drift velocity of ionospheric plasma. We found a close agreement between IRI-CCIR hmF2 model and observed hmF2 during 0000-0700 LT while outside this period the model predictions deviate significantly with the observational values. Significant discrepancies are observed between the IRI model options for B0 and the observed B0 values. Specifically, the modeled values do not show B0 post-sunset peak. A fairly good agreement was observed between the observed B1 and IRI model options (ABT-2009 and Bill 2000) for B1.

Comparison of ionospheric profile parameters with IRI-2012 model over Jicamarca

International Nuclear Information System (INIS)

Bello, S A; Abdullah, M; Hamid, N S A; Reinisch, B W

2017-01-01

We used the hourly ionogram data obtained from Jicamarca station (12° S, 76.9° W, dip latitude: 1.0° N) an equatorial region to study the variation of the electron density profile parameters: maximum height of F2-layer ( hm F2), bottomside thickness ( B0 ) and shape ( B1 ) parameter of F-layer. The period of study is for the year 2010 (solar minimum period).The diurnal monthly averages of these parameters are compared with the updated IRI-2012 model. The results show that hm F2 is highest during the daytime than nighttime. The variation in hmF2 was observed to modulate the thickness of the bottomside F2-layer. The observed hm F2 and B0 post-sunset peak is as result of the upward drift velocity of ionospheric plasma. We found a close agreement between IRI-CCIR hm F2 model and observed hm F2 during 0000-0700 LT while outside this period the model predictions deviate significantly with the observational values. Significant discrepancies are observed between the IRI model options for B0 and the observed B0 values. Specifically, the modeled values do not show B0 post-sunset peak. A fairly good agreement was observed between the observed B1 and IRI model options (ABT-2009 and Bill 2000) for B1 . (paper)
Post-BEMUSE Reflood Model Input Uncertainty Methods (PREMIUM) Benchmark Phase II: Identification of Influential Parameters

International Nuclear Information System (INIS)

Kovtonyuk, A.; Petruzzi, A.; D'Auria, F.

2015-01-01

The objective of the Post-BEMUSE Reflood Model Input Uncertainty Methods (PREMIUM) benchmark is to progress on the issue of the quantification of the uncertainty of the physical models in system thermal-hydraulic codes by considering a concrete case: the physical models involved in the prediction of core reflooding. The PREMIUM benchmark consists of five phases. This report presents the results of Phase II dedicated to the identification of the uncertain code parameters associated with physical models used in the simulation of reflooding conditions. This identification is made on the basis of the Test 216 of the FEBA/SEFLEX programme according to the following steps: - identification of influential phenomena; - identification of the associated physical models and parameters, depending on the used code; - quantification of the variation range of identified input parameters through a series of sensitivity calculations. A procedure for the identification of potentially influential code input parameters has been set up in the Specifications of Phase II of PREMIUM benchmark. A set of quantitative criteria has been as well proposed for the identification of influential IP and their respective variation range. Thirteen participating organisations, using 8 different codes (7 system thermal-hydraulic codes and 1 sub-channel module of a system thermal-hydraulic code) submitted Phase II results. The base case calculations show spread in predicted cladding temperatures and quench front propagation that has been characterized. All the participants, except one, predict a too fast quench front progression. Besides, the cladding temperature time trends obtained by almost all the participants show oscillatory behaviour which may have numeric origins. Adopted criteria for identification of influential input parameters differ between the participants: some organisations used the set of criteria proposed in Specifications 'as is', some modified the quantitative thresholds
Rules of parameter variation in homotype series of birdsong can indicate a 'sollwert' significance.

Science.gov (United States)

Hultsch, H; Todt, D

1996-11-01

Various bird species produce songs which include homotype pattern series, i.e. segments composed of a number of repeated vocal units. We compared such units and analyzed the variation of their parameters, especially in the time and the frequency domain. In addition, we examined whether and how serial changes of both the range and the trend of variation were related to song constituents following the repetitions. Data evaluation showed that variation of specific serial parameters (e.g., unit pitch or unit duration) occurring in the whistle song-types of nightingales (Luscinia megarhynchos) were converging towards a distinct terminal value. Although song-types differed in this terminal value, it was found to play the role of a key cue ('sollwert'). The continuation of a song depended on a preceding attainment of its specific 'sollwert'. Our results suggest that the study of signal parameters and rules of their variations make a useful tool for the behavioral access to the properties of the control systems mediating serial signal performances.
A lumped parameter, low dimension model of heat exchanger

International Nuclear Information System (INIS)

Kanoh, Hideaki; Furushoo, Junji; Masubuchi, Masami

1980-01-01

This paper reports on the results of investigation of the distributed parameter model, the difference model, and the model of the method of weighted residuals for heat exchangers. By the method of weighted residuals (MWR), the opposite flow heat exchanger system is approximated by low dimension, lumped parameter model. By assuming constant specific heat, constant density, the same form of tube cross-section, the same form of the surface of heat exchange, uniform flow velocity, the linear relation of heat transfer to flow velocity, liquid heat carrier, and the thermal insulation of liquid from outside, fundamental equations are obtained. The experimental apparatus was made of acrylic resin. The response of the temperature at the exit of first liquid to the variation of the flow rate of second liquid was measured and compared with the models. The MWR model shows good approximation for the low frequency region, and as the number of division increases, good approximation spreads to higher frequency region. (Kato, T.)
Constraining spatial variations of the fine-structure constant in symmetron models

Directory of Open Access Journals (Sweden)

A.M.M. Pinho

2017-06-01

Full Text Available We introduce a methodology to test models with spatial variations of the fine-structure constant α, based on the calculation of the angular power spectrum of these measurements. This methodology enables comparisons of observations and theoretical models through their predictions on the statistics of the α variation. Here we apply it to the case of symmetron models. We find no indications of deviations from the standard behavior, with current data providing an upper limit to the strength of the symmetron coupling to gravity (log⁡β2<−0.9 when this is the only free parameter, and not able to constrain the model when also the symmetry breaking scale factor aSSB is free to vary.
Investigation of Spatial Variation of Sea States Offshore of Humboldt Bay CA Using a Hindcast Model.

Energy Technology Data Exchange (ETDEWEB)

Dallman, Ann Renee; Neary, Vincent Sinclair

2014-10-01

Spatial variability of sea states is an important consideration when performing wave resource assessments and wave resource characterization studies for wave energy converter (WEC) test sites and commercial WEC deployments. This report examines the spatial variation of sea states offshore of Humboldt Bay, CA, using the wave model SWAN . The effect of depth and shoaling on bulk wave parameters is well resolved using the model SWAN with a 200 m grid. At this site, the degree of spatial variation of these bulk wave parameters, with shoaling generally perpendicular to the depth contours, is found to depend on the season. The variation in wave height , for example, was higher in the summer due to the wind and wave sheltering from the protruding land on the coastline north of the model domain. Ho wever, the spatial variation within an area of a potential Tier 1 WEC test site at 45 m depth and 1 square nautical mile is almost negligible; at most about 0.1 m in both winter and summer. The six wave characterization parameters recommended by the IEC 6 2600 - 101 TS were compared at several points along a line perpendicular to shore from the WEC test site . As expected, these parameters varied based on depth , but showed very similar seasonal trends.
Bilinear models for inter- and intra-patient variation of the prostate

International Nuclear Information System (INIS)

Jeong, Y; Radke, R J; Lovelock, D M

2010-01-01

We propose bilinear models for capturing and effectively decoupling the expected shape variations of an organ both across the patient population and within a specific patient. Bilinear models have been successfully introduced in other areas of computer vision, but they have rarely been used in medical imaging applications. Our particular interest is in modeling the shape variation of the prostate for potential use in radiation therapy treatment planning. Using a dataset of 204 prostate shapes contoured from CT imagery of 12 different patients, we build bilinear models and show that they can fit both training and testing shapes accurately. We also show how the bilinear model can adapt to a new patient using only a few example shapes, producing a patient-specific model that also reflects expected content variation learnt from a broader population. Finally, we evaluate the training and testing projection error, adaptation performance and image segmentation accuracy of the bilinear model compared to linear principal component analysis and hierarchical point distribution models with the same number of parameters.
Tumor response parameters for head and neck cancer derived from tumor-volume variation during radiation therapy

International Nuclear Information System (INIS)

Chvetsov, Alexei V.

2013-01-01

-and-neck squamous cell carcinoma (SCC) is equal to 3.8 mean potential doubling times, which agrees with 4.0 mean potential doubling times obtained previously for lung SCC. Conclusions: The distribution of cell survival fractions obtained in this study support the hypothesis that the tumor-volume variation during radiotherapy treatment for head and neck cancer can be described by the two-level cell population tumor-volume model. This model can be used for in vivo evaluation of patient-specific radiobiological parameters that are needed for tumor-control probability evaluation.
Global parameter estimation for thermodynamic models of transcriptional regulation.

Science.gov (United States)

Suleimenov, Yerzhan; Ay, Ahmet; Samee, Md Abul Hassan; Dresch, Jacqueline M; Sinha, Saurabh; Arnosti, David N

2013-07-15

Deciphering the mechanisms involved in gene regulation holds the key to understanding the control of central biological processes, including human disease, population variation, and the evolution of morphological innovations. New experimental techniques including whole genome sequencing and transcriptome analysis have enabled comprehensive modeling approaches to study gene regulation. In many cases, it is useful to be able to assign biological significance to the inferred model parameters, but such interpretation should take into account features that affect these parameters, including model construction and sensitivity, the type of fitness calculation, and the effectiveness of parameter estimation. This last point is often neglected, as estimation methods are often selected for historical reasons or for computational ease. Here, we compare the performance of two parameter estimation techniques broadly representative of local and global approaches, namely, a quasi-Newton/Nelder-Mead simplex (QN/NMS) method and a covariance matrix adaptation-evolutionary strategy (CMA-ES) method. The estimation methods were applied to a set of thermodynamic models of gene transcription applied to regulatory elements active in the Drosophila embryo. Measuring overall fit, the global CMA-ES method performed significantly better than the local QN/NMS method on high quality data sets, but this difference was negligible on lower quality data sets with increased noise or on data sets simplified by stringent thresholding. Our results suggest that the choice of parameter estimation technique for evaluation of gene expression models depends both on quality of data, the nature of the models [again, remains to be established] and the aims of the modeling effort. Copyright © 2013 Elsevier Inc. All rights reserved.
Haematology and Serum Biochemistry Parameters and Variations in the Eurasian Beaver (Castor fiber).

Science.gov (United States)

Girling, Simon J; Campbell-Palmer, Roisin; Pizzi, Romain; Fraser, Mary A; Cracknell, Jonathan; Arnemo, Jon; Rosell, Frank

2015-01-01

Haematology parameters (N = 24) and serum biochemistry parameters (N = 35) were determined for wild Eurasian beavers (Castor fiber), between 6 months - 12 years old. Of the population tested in this study, N = 18 Eurasian beavers were from Norway and N = 17 originating from Bavaria but now living extensively in a reserve in England. All blood samples were collected from beavers via the ventral tail vein. All beavers were chemically restrained using inhalant isoflurane in 100% oxygen prior to blood sampling. Results were determined for haematological and serum biochemical parameters for the species and were compared between the two different populations with differences in means estimated and significant differences being noted. Standard blood parameters for the Eurasian beaver were determined and their ranges characterised using percentiles. Whilst the majority of blood parameters between the two populations showed no significant variation, haemoglobin, packed cell volume, mean cell haemoglobin and white blood cell counts showed significantly greater values (pbeavers or between sexually immature (beavers in the animals sampled. With Eurasian beaver reintroduction encouraged by legislation throughout Europe, knowledge of baseline blood values for the species and any variations therein is essential when assessing their health and welfare and the success or failure of any reintroduction program. This is the first study to produce base-line blood values and their variations for the Eurasian beaver.
Physicochemical parameters and seasonal variation of coastal water from Balochistan coast, Pakistan

Directory of Open Access Journals (Sweden)

Naeema Elahi

2015-03-01

Full Text Available Objective: To determine common physico-chemical parameters of coastal water. Methods: Physicochemical properties of water were determined according to the standards of the American Public Health Association. Generally, all those parameters were recorded a small variation between stations. The variation in physico-chemical parameters like salinity, temperature, dissolved oxygen and pH at Gwadar (Coastal water of Balochistan were recorded. Results: The range of air temperature of coastal water of Balochistan during 2004 and 2006 varies from 25 ºC to 37 ºC, water temperature ranged from 15.00 ºC to 33.00 ºC, pH ranged from 7.08 to 8.95, salinity ranged from 37.4‰ to 41.3‰ and dissolved oxygen ranged from 5.32 to 8.67 mg/L. Conclusions: Results showed that these parameters of Balochistan coast of Pakistan is not dangerous for marine habitat and the use of these parameters in monitoring programs to assess ecosystem health has the potential to inform the general public and decision-makers about the state of the coastal ecosystems. To save this vital important habitat, the government agencies and scientists should work with proper attention.
Geostatistical analysis of space variation in underground water various quality parameters in Kłodzko water intake area (SW part of Poland

Directory of Open Access Journals (Sweden)

Namysłowska-Wilczyńska Barbara

2016-09-01

Full Text Available This paper presents selected results of research connected with the development of a (3D geostatistical hydrogeochemical model of the Kłodzko Drainage Basin, dedicated to the spatial variation in the different quality parameters of underground water in the water intake area (SW part of Poland. The research covers the period 2011-2012. Spatial analyses of the variation in various quality parameters, i.e., contents of: iron, manganese, ammonium ion, nitrate ion, phosphate ion, total organic carbon, pH redox potential and temperature, were carried out on the basis of the chemical determinations of the quality parameters of underground water samples taken from the wells in the water intake area. Spatial variation in the parameters was analyzed on the basis of data obtained (November 2011 from tests of water taken from 14 existing wells with a depth ranging from 9.5 to 38.0 m b.g.l. The latest data (January 2012 were obtained (gained from 3 new piezometers, made in other locations in the relevant area. A depth of these piezometers amounts to 9-10 m.
How Sensitive Are Transdermal Transport Predictions by Microscopic Stratum Corneum Models to Geometric and Transport Parameter Input?

Science.gov (United States)

Wen, Jessica; Koo, Soh Myoung; Lape, Nancy

2018-02-01

While predictive models of transdermal transport have the potential to reduce human and animal testing, microscopic stratum corneum (SC) model output is highly dependent on idealized SC geometry, transport pathway (transcellular vs. intercellular), and penetrant transport parameters (e.g., compound diffusivity in lipids). Most microscopic models are limited to a simple rectangular brick-and-mortar SC geometry and do not account for variability across delivery sites, hydration levels, and populations. In addition, these models rely on transport parameters obtained from pure theory, parameter fitting to match in vivo experiments, and time-intensive diffusion experiments for each compound. In this work, we develop a microscopic finite element model that allows us to probe model sensitivity to variations in geometry, transport pathway, and hydration level. Given the dearth of experimentally-validated transport data and the wide range in theoretically-predicted transport parameters, we examine the model's response to a variety of transport parameters reported in the literature. Results show that model predictions are strongly dependent on all aforementioned variations, resulting in order-of-magnitude differences in lag times and permeabilities for distinct structure, hydration, and parameter combinations. This work demonstrates that universally predictive models cannot fully succeed without employing experimentally verified transport parameters and individualized SC structures. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.
Ultrasonic-assisted manufacturing processes: Variational model and numerical simulations

KAUST Repository

Siddiq, Amir

2012-04-01

We present a computational study of ultrasonic assisted manufacturing processes including sheet metal forming, upsetting, and wire drawing. A fully variational porous plasticity model is modified to include ultrasonic softening effects and then utilized to account for instantaneous softening when ultrasonic energy is applied during deformation. Material model parameters are identified via inverse modeling, i.e. by using experimental data. The versatility and predictive ability of the model are demonstrated and the effect of ultrasonic intensity on the manufacturing process at hand is investigated and compared qualitatively with experimental results reported in the literature. © 2011 Elsevier B.V. All rights reserved.
Model parameters for representative wetland plant functional groups

Science.gov (United States)

Williams, Amber S.; Kiniry, James R.; Mushet, David M.; Smith, Loren M.; McMurry, Scott T.; Attebury, Kelly; Lang, Megan; McCarty, Gregory W.; Shaffer, Jill A.; Effland, William R.; Johnson, Mari-Vaughn V.

2017-01-01

Wetlands provide a wide variety of ecosystem services including water quality remediation, biodiversity refugia, groundwater recharge, and floodwater storage. Realistic estimation of ecosystem service benefits associated with wetlands requires reasonable simulation of the hydrology of each site and realistic simulation of the upland and wetland plant growth cycles. Objectives of this study were to quantify leaf area index (LAI), light extinction coefficient (k), and plant nitrogen (N), phosphorus (P), and potassium (K) concentrations in natural stands of representative plant species for some major plant functional groups in the United States. Functional groups in this study were based on these parameters and plant growth types to enable process-based modeling. We collected data at four locations representing some of the main wetland regions of the United States. At each site, we collected on-the-ground measurements of fraction of light intercepted, LAI, and dry matter within the 2013–2015 growing seasons. Maximum LAI and k variables showed noticeable variations among sites and years, while overall averages and functional group averages give useful estimates for multisite simulation modeling. Variation within each species gives an indication of what can be expected in such natural ecosystems. For P and K, the concentrations from highest to lowest were spikerush (Eleocharis macrostachya), reed canary grass (Phalaris arundinacea), smartweed (Polygonum spp.), cattail (Typha spp.), and hardstem bulrush (Schoenoplectus acutus). Spikerush had the highest N concentration, followed by smartweed, bulrush, reed canary grass, and then cattail. These parameters will be useful for the actual wetland species measured and for the wetland plant functional groups they represent. These parameters and the associated process-based models offer promise as valuable tools for evaluating environmental benefits of wetlands and for evaluating impacts of various agronomic practices in
Sensitivity analysis of specific activity model parameters for environmental transport of 3H and dose assessment

International Nuclear Information System (INIS)

Rout, S.; Mishra, D.G.; Ravi, P.M.; Tripathi, R.M.

2016-01-01

Tritium is one of the radionuclides likely to get released to the environment from Pressurized Heavy Water Reactors. Environmental models are extensively used to quantify the complex environmental transport processes of radionuclides and also to assess the impact to the environment. Model parameters exerting the significant influence on model results are identified through a sensitivity analysis (SA). SA is the study of how the variation (uncertainty) in the output of a mathematical model can be apportioned, qualitatively or quantitatively, to different sources of variation in the input parameters. This study was designed to identify the sensitive model parameters of specific activity model (TRS 1616, IAEA) for environmental transfer of 3 H following release to air and then to vegetation and animal products. Model includes parameters such as air to soil transfer factor (CRs), Tissue Free Water 3 H to Organically Bound 3 H ratio (Rp), Relative humidity (RH), WCP (fractional water content) and WEQp (water equivalent factor) any change in these parameters leads to change in 3 H level in vegetation and animal products consequently change in dose due to ingestion. All these parameters are function of climate and/or plant which change with time, space and species. Estimation of these parameters at every time is a time consuming and also required sophisticated instrumentation. Therefore it is necessary to identify the sensitive parameters and freeze the values of least sensitive parameters at constant values for more accurate estimation of 3 H dose in short time for routine assessment
Long Memory of Financial Time Series and Hidden Markov Models with Time-Varying Parameters

DEFF Research Database (Denmark)

Nystrup, Peter; Madsen, Henrik; Lindström, Erik

2016-01-01

Hidden Markov models are often used to model daily returns and to infer the hidden state of financial markets. Previous studies have found that the estimated models change over time, but the implications of the time-varying behavior have not been thoroughly examined. This paper presents an adaptive...... to reproduce with a hidden Markov model. Capturing the time-varying behavior of the parameters also leads to improved one-step density forecasts. Finally, it is shown that the forecasting performance of the estimated models can be further improved using local smoothing to forecast the parameter variations....
Parameter optimization for surface flux transport models

Science.gov (United States)

Whitbread, T.; Yeates, A. R.; Muñoz-Jaramillo, A.; Petrie, G. J. D.

2017-11-01

Accurate prediction of solar activity calls for precise calibration of solar cycle models. Consequently we aim to find optimal parameters for models which describe the physical processes on the solar surface, which in turn act as proxies for what occurs in the interior and provide source terms for coronal models. We use a genetic algorithm to optimize surface flux transport models using National Solar Observatory (NSO) magnetogram data for Solar Cycle 23. This is applied to both a 1D model that inserts new magnetic flux in the form of idealized bipolar magnetic regions, and also to a 2D model that assimilates specific shapes of real active regions. The genetic algorithm searches for parameter sets (meridional flow speed and profile, supergranular diffusivity, initial magnetic field, and radial decay time) that produce the best fit between observed and simulated butterfly diagrams, weighted by a latitude-dependent error structure which reflects uncertainty in observations. Due to the easily adaptable nature of the 2D model, the optimization process is repeated for Cycles 21, 22, and 24 in order to analyse cycle-to-cycle variation of the optimal solution. We find that the ranges and optimal solutions for the various regimes are in reasonable agreement with results from the literature, both theoretical and observational. The optimal meridional flow profiles for each regime are almost entirely within observational bounds determined by magnetic feature tracking, with the 2D model being able to accommodate the mean observed profile more successfully. Differences between models appear to be important in deciding values for the diffusive and decay terms. In like fashion, differences in the behaviours of different solar cycles lead to contrasts in parameters defining the meridional flow and initial field strength.
The lumped parameter model for fuel pins

Energy Technology Data Exchange (ETDEWEB)

Liu, W S [Ontario Hydro, Toronto, ON (Canada)

1996-12-31

The use of a lumped fuel-pin model in a thermal-hydraulic code is advantageous because of computational simplicity and efficiency. The model uses an averaging approach over the fuel cross section and makes some simplifying assumptions to describe the transient equations for the averaged fuel, fuel centerline and sheath temperatures. It is shown that by introducing a factor in the effective fuel conductivity, the analytical solution of the mean fuel temperature can be modified to simulate the effects of the flux depression in the heat generation rate and the variation in fuel thermal conductivity. The simplified analytical method used in the transient equation is presented. The accuracy of the lumped parameter model has been compared with the results from the finite difference method. (author). 4 refs., 2 tabs., 4 figs.
Variational Wavefunction for the Periodic Anderson Model with Onsite Correlation Factors

Science.gov (United States)

Kubo, Katsunori; Onishi, Hiroaki

2017-01-01

We propose a variational wavefunction containing parameters to tune the probabilities of all the possible onsite configurations for the periodic Anderson model. We call it the full onsite-correlation wavefunction (FOWF). This is a simple extension of the Gutzwiller wavefunction (GWF), in which one parameter is included to tune the double occupancy of the f electrons at the same site. We compare the energy of the GWF and the FOWF evaluated by the variational Monte Carlo method and that obtained with the density-matrix renormalization group method. We find that the energy is considerably improved in the FOWF. On the other hand, the physical quantities do not change significantly between these two wavefunctions as long as they describe the same phase, such as the paramagnetic phase. From these results, we not only demonstrate the improvement by the FOWF, but we also gain insights on the applicability and limitation of the GWF to the periodic Anderson model.

Variational wavefunction for the periodic anderson model with onsite correlation factors

International Nuclear Information System (INIS)

Kubo, Katsunori; Onishi, Hiroaki

2017-01-01

We propose a variational wavefunction containing parameters to tune the probabilities of all the possible onsite configurations for the periodic Anderson model. We call it the full onsite-correlation wavefunction (FOWF). This is a simple extension of the Gutzwiller wavefunction (GWF), in which one parameter is included to tune the double occupancy of the f electrons at the same site. We compare the energy of the GWF and the FOWF evaluated by the variational Monte Carlo method and that obtained with the density-matrix renormalization group method. We find that the energy is considerably improved in the FOWF. On the other hand, the physical quantities do not change significantly between these two wavefunctions as long as they describe the same phase, such as the paramagnetic phase. From these results, we not only demonstrate the improvement by the FOWF, but we also gain insights on the applicability and limitation of the GWF to the periodic Anderson model. (author)
ANALYSIS THE DIURNAL VARIATIONS ON SELECTED PHYSICAL AND PHYSIOLOGICAL PARAMETERS

Directory of Open Access Journals (Sweden)

A. MAHABOOBJAN

2010-12-01

Full Text Available The purpose of the study was to analyze the diurnal variations on selected physical and physiological parameters such as speed, explosive power, resting heart rate and breath holding time among college students. To achieve the purpose of this study, a total of twenty players (n=20 from Government Arts College, Salem were selected as subjects To study the diurnal variation of the players on selected physiological and performance variables, the data were collected 4 times a day with every four hours in between the times it from 6.00 to 18.00 hours were selected as another categorical variable. One way repeated measures (ANOVA was used to analyze the data. If the obtained F-ratio was significant, Seheffe’s post-hoc test was used to find out the significant difference if anyamong the paired means. The level of significance was fixed at.05 level. It has concluded that both physical and physiological parameters were significantly deferred with reference to change of temperature in a day
Seasonal variation of photosynthetic model parameters and leaf area index from global Fluxnet eddy covariance data

NARCIS (Netherlands)

Groenendijk, M.; Dolman, A.J.; Ammann, C.; Arneth, A.; Cescatti, A.; Molen, van der M.K.; Moors, E.J.

2011-01-01

Global vegetation models require the photosynthetic parameters, maximum carboxylation capacity (Vcm), and quantum yield (a) to parameterize their plant functional types (PFTs). The purpose of this work is to determine how much the scaling of the parameters from leaf to ecosystem level through a
An improved state-parameter analysis of ecosystem models using data assimilation

Science.gov (United States)

Chen, M.; Liu, S.; Tieszen, L.L.; Hollinger, D.Y.

2008-01-01

Much of the effort spent in developing data assimilation methods for carbon dynamics analysis has focused on estimating optimal values for either model parameters or state variables. The main weakness of estimating parameter values alone (i.e., without considering state variables) is that all errors from input, output, and model structure are attributed to model parameter uncertainties. On the other hand, the accuracy of estimating state variables may be lowered if the temporal evolution of parameter values is not incorporated. This research develops a smoothed ensemble Kalman filter (SEnKF) by combining ensemble Kalman filter with kernel smoothing technique. SEnKF has following characteristics: (1) to estimate simultaneously the model states and parameters through concatenating unknown parameters and state variables into a joint state vector; (2) to mitigate dramatic, sudden changes of parameter values in parameter sampling and parameter evolution process, and control narrowing of parameter variance which results in filter divergence through adjusting smoothing factor in kernel smoothing algorithm; (3) to assimilate recursively data into the model and thus detect possible time variation of parameters; and (4) to address properly various sources of uncertainties stemming from input, output and parameter uncertainties. The SEnKF is tested by assimilating observed fluxes of carbon dioxide and environmental driving factor data from an AmeriFlux forest station located near Howland, Maine, USA, into a partition eddy flux model. Our analysis demonstrates that model parameters, such as light use efficiency, respiration coefficients, minimum and optimum temperatures for photosynthetic activity, and others, are highly constrained by eddy flux data at daily-to-seasonal time scales. The SEnKF stabilizes parameter values quickly regardless of the initial values of the parameters. Potential ecosystem light use efficiency demonstrates a strong seasonality. Results show that the
Parameters-related uncertainty in modeling sugar cane yield with an agro-Land Surface Model

Science.gov (United States)

Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Ruget, F.; Gabrielle, B.

2012-12-01

uptake of water (root profile), and transpiration and respiration (stomatal conductance, growth and maintenance respiration coefficients). We find that the optimal carboxylation rate and optimal photosynthesis temperature parameters contribute most to the uncertainty in NPP and GPP simulations whereas stomatal conductance is the most sensitive parameter controlling SH, followed by optimal photosynthesis temperature and optimal carboxylation rate. The spatial variation of the ranked correlation between input parameters and output variables is well explained by rain and temperature drivers, suggesting that climate mediated regionally different sensitivities of modeled sugarcane yield to the model parameters, for Australia and Brazil.
Variation of equation of state parameters in the Mg2(Si 1-xSnx) alloys

KAUST Repository

Pulikkotil, Jiji Thomas Joseph

2010-08-03

Thermoelectric performance peaks up for intermediate Mg2(Si 1-x:Snx) alloys, but not for isomorphic and isoelectronic Mg2(Si1-xGex) alloys. A comparative study of the equation of state parameters is performed using density functional theory, Green\\'s function technique, and the coherent potential approximation. Anomalous variation of the bulk modulus is found in Mg2(Si1-xSn x) but not in the Mg2(Si1-xGex) analogs. Assuming a Debye model, linear variations of the unit cell volume and pressure derivative of the bulk modulus suggest that lattice effects are important for the thermoelectric response. From the electronic structure perspective, Mg2(Si1-xSnx) is distinguished by a strong renormalization of the anion-anion hybridization. © 2010 IOP Publishing Ltd.
Geostatistical Characteristic of Space -Time Variation in Underground Water Selected Quality Parameters in Klodzko Water Intake Area (SW Part of Poland)

Science.gov (United States)

Namysłowska-Wilczyńska, Barbara

2016-04-01

This paper presents selected results of research connected with the development of a (3D) geostatistical hydrogeochemical model of the Klodzko Drainage Basin, dedicated to the spatial and time variation in the selected quality parameters of underground water in the Klodzko water intake area (SW part of Poland). The research covers the period 2011÷2012. Spatial analyses of the variation in various quality parameters, i.e, contents of: ammonium ion [gNH4+/m3], NO3- (nitrate ion) [gNO3/m3], PO4-3 (phosphate ion) [gPO4-3/m3], total organic carbon C (TOC) [gC/m3], pH redox potential and temperature C [degrees], were carried out on the basis of the chemical determinations of the quality parameters of underground water samples taken from the wells in the water intake area. Spatial and time variation in the quality parameters was analyzed on the basis of archival data (period 1977÷1999) for 22 (pump and siphon) wells with a depth ranging from 9.5 to 38.0 m b.g.l., later data obtained (November 2011) from tests of water taken from 14 existing wells. The wells were built in the years 1954÷1998. The water abstraction depth (difference between the terrain elevation and the dynamic water table level) is ranged from 276÷286 m a.s.l., with an average of 282.05 m a.s.l. Dynamic water table level is contained between 6.22 m÷16.44 m b.g.l., with a mean value of 9.64 m b.g.l. The latest data (January 2012) acquired from 3 new piezometers, with a depth of 9÷10m, which were made in other locations in the relevant area. Thematic databases, containing original data on coordinates X, Y (latitude, longitude) and Z (terrain elevation and time - years) and on regionalized variables, i.e. the underground water quality parameters in the Klodzko water intake area determined for different analytical configurations (22 wells, 14 wells, 14 wells + 3 piezometers), were created. Both archival data (acquired in the years 1977÷1999) and the latest data (collected in 2011÷2012) were analyzed
Coarse graining from variationally enhanced sampling applied to the Ginzburg-Landau model

Science.gov (United States)

Invernizzi, Michele; Valsson, Omar; Parrinello, Michele

2017-03-01

A powerful way to deal with a complex system is to build a coarse-grained model capable of catching its main physical features, while being computationally affordable. Inevitably, such coarse-grained models introduce a set of phenomenological parameters, which are often not easily deducible from the underlying atomistic system. We present a unique approach to the calculation of these parameters, based on the recently introduced variationally enhanced sampling method. It allows us to obtain the parameters from atomistic simulations, providing thus a direct connection between the microscopic and the mesoscopic scale. The coarse-grained model we consider is that of Ginzburg-Landau, valid around a second-order critical point. In particular, we use it to describe a Lennard-Jones fluid in the region close to the liquid-vapor critical point. The procedure is general and can be adapted to other coarse-grained models.
Prediction of interest rate using CKLS model with stochastic parameters

International Nuclear Information System (INIS)

Ying, Khor Chia; Hin, Pooi Ah

2014-01-01

The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector φ (j) of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j′-th time point where j≤j′≤j+n. To model the variation of φ (j) , we assume that φ (j) depends on φ (j−m) , φ (j−m+1) ,…, φ (j−1) and the interest rate r j+n at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r j+n+1 of the interest rate at the next time point when the value r j+n of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r j+n+d at the next d-th (d≥2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters
Prediction of interest rate using CKLS model with stochastic parameters

Energy Technology Data Exchange (ETDEWEB)

Ying, Khor Chia [Faculty of Computing and Informatics, Multimedia University, Jalan Multimedia, 63100 Cyberjaya, Selangor (Malaysia); Hin, Pooi Ah [Sunway University Business School, No. 5, Jalan Universiti, Bandar Sunway, 47500 Subang Jaya, Selangor (Malaysia)

2014-06-19

The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector φ{sup (j)} of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j′-th time point where j≤j′≤j+n. To model the variation of φ{sup (j)}, we assume that φ{sup (j)} depends on φ{sup (j−m)}, φ{sup (j−m+1)},…, φ{sup (j−1)} and the interest rate r{sub j+n} at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r{sub j+n+1} of the interest rate at the next time point when the value r{sub j+n} of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r{sub j+n+d} at the next d-th (d≥2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters.
Variations in environmental tritium doses due to meteorological data averaging and uncertainties in pathway model parameters

Energy Technology Data Exchange (ETDEWEB)

Kock, A.

1996-05-01

The objectives of this research are: (1) to calculate and compare off site doses from atmospheric tritium releases at the Savannah River Site using monthly versus 5 year meteorological data and annual source terms, including additional seasonal and site specific parameters not included in present annual assessments; and (2) to calculate the range of the above dose estimates based on distributions in model parameters given by uncertainty estimates found in the literature. Consideration will be given to the sensitivity of parameters given in former studies.
Variations in environmental tritium doses due to meteorological data averaging and uncertainties in pathway model parameters

International Nuclear Information System (INIS)

Kock, A.

1996-05-01

The objectives of this research are: (1) to calculate and compare off site doses from atmospheric tritium releases at the Savannah River Site using monthly versus 5 year meteorological data and annual source terms, including additional seasonal and site specific parameters not included in present annual assessments; and (2) to calculate the range of the above dose estimates based on distributions in model parameters given by uncertainty estimates found in the literature. Consideration will be given to the sensitivity of parameters given in former studies
Exploring gravitational lensing model variations in the Frontier Fields galaxy clusters

Science.gov (United States)

Harris James, Nicholas John; Raney, Catie; Brennan, Sean; Keeton, Charles

2018-01-01

Multiple groups have been working on modeling the mass distributions of the six lensing galaxy clusters in the Hubble Space Telescope Frontier Fields data set. The magnification maps produced from these mass models will be important for the future study of the lensed background galaxies, but there exists significant variation in the different groups’ models and magnification maps. We explore the use of two-dimensional histograms as a tool for visualizing these magnification map variations. Using a number of simple, one- or two-halo singular isothermal sphere models, we explore the features that are produced in 2D histogram model comparisons when parameters such as halo mass, ellipticity, and location are allowed to vary. Our analysis demonstrates the potential of 2D histograms as a means of observing the full range of differences between the Frontier Fields groups’ models.This work has been supported by funding from National Science Foundation grants PHY-1560077 and AST-1211385, and from the Space Telescope Science Institute.
Coarse graining from variationally enhanced sampling applied to the Ginzburg–Landau model

Science.gov (United States)

Invernizzi, Michele; Valsson, Omar; Parrinello, Michele

2017-01-01

A powerful way to deal with a complex system is to build a coarse-grained model capable of catching its main physical features, while being computationally affordable. Inevitably, such coarse-grained models introduce a set of phenomenological parameters, which are often not easily deducible from the underlying atomistic system. We present a unique approach to the calculation of these parameters, based on the recently introduced variationally enhanced sampling method. It allows us to obtain the parameters from atomistic simulations, providing thus a direct connection between the microscopic and the mesoscopic scale. The coarse-grained model we consider is that of Ginzburg–Landau, valid around a second-order critical point. In particular, we use it to describe a Lennard–Jones fluid in the region close to the liquid–vapor critical point. The procedure is general and can be adapted to other coarse-grained models. PMID:28292890
Stable exponential cosmological solutions with zero variation of G and three different Hubble-like parameters in the Einstein-Gauss-Bonnet model with a Λ-term

Energy Technology Data Exchange (ETDEWEB)

Ernazarov, K.K. [RUDN University, Institute of Gravitation and Cosmology, Moscow (Russian Federation); Ivashchuk, V.D. [RUDN University, Institute of Gravitation and Cosmology, Moscow (Russian Federation); VNIIMS, Center for Gravitation and Fundamental Metrology, Moscow (Russian Federation)

2017-06-15

We consider a D-dimensional gravitational model with a Gauss-Bonnet term and the cosmological term Λ. We restrict the metrics to diagonal cosmological ones and find for certain Λ a class of solutions with exponential time dependence of three scale factors, governed by three non-coinciding Hubble-like parameters H > 0, h{sub 1} and h{sub 2}, corresponding to factor spaces of dimensions m > 2, k{sub 1} > 1 and k{sub 2} > 1, respectively, with k{sub 1} ≠ k{sub 2} and D = 1 + m + k{sub 1} + k{sub 2}. Any of these solutions describes an exponential expansion of 3d subspace with Hubble parameter H and zero variation of the effective gravitational constant G. We prove the stability of these solutions in a class of cosmological solutions with diagonal metrics. (orig.)
Utilising temperature differences as constraints for estimating parameters in a simple climate model

International Nuclear Information System (INIS)

Bodman, Roger W; Karoly, David J; Enting, Ian G

2010-01-01

Simple climate models can be used to estimate the global temperature response to increasing greenhouse gases. Changes in the energy balance of the global climate system are represented by equations that necessitate the use of uncertain parameters. The values of these parameters can be estimated from historical observations, model testing, and tuning to more complex models. Efforts have been made at estimating the possible ranges for these parameters. This study continues this process, but demonstrates two new constraints. Previous studies have shown that land-ocean temperature differences are only weakly correlated with global mean temperature for natural internal climate variations. Hence, these temperature differences provide additional information that can be used to help constrain model parameters. In addition, an ocean heat content ratio can also provide a further constraint. A pulse response technique was used to identify relative parameter sensitivity which confirmed the importance of climate sensitivity and ocean vertical diffusivity, but the land-ocean warming ratio and the land-ocean heat exchange coefficient were also found to be important. Experiments demonstrate the utility of the land-ocean temperature difference and ocean heat content ratio for setting parameter values. This work is based on investigations with MAGICC (Model for the Assessment of Greenhouse-gas Induced Climate Change) as the simple climate model.
Assessment of structural model and parameter uncertainty with a multi-model system for soil water balance models

Science.gov (United States)

Michalik, Thomas; Multsch, Sebastian; Frede, Hans-Georg; Breuer, Lutz

2016-04-01

Water for agriculture is strongly limited in arid and semi-arid regions and often of low quality in terms of salinity. The application of saline waters for irrigation increases the salt load in the rooting zone and has to be managed by leaching to maintain a healthy soil, i.e. to wash out salts by additional irrigation. Dynamic simulation models are helpful tools to calculate the root zone water fluxes and soil salinity content in order to investigate best management practices. However, there is little information on structural and parameter uncertainty for simulations regarding the water and salt balance of saline irrigation. Hence, we established a multi-model system with four different models (AquaCrop, RZWQM, SWAP, Hydrus1D/UNSATCHEM) to analyze the structural and parameter uncertainty by using the Global Likelihood and Uncertainty Estimation (GLUE) method. Hydrus1D/UNSATCHEM and SWAP were set up with multiple sets of different implemented functions (e.g. matric and osmotic stress for root water uptake) which results in a broad range of different model structures. The simulations were evaluated against soil water and salinity content observations. The posterior distribution of the GLUE analysis gives behavioral parameters sets and reveals uncertainty intervals for parameter uncertainty. Throughout all of the model sets, most parameters accounting for the soil water balance show a low uncertainty, only one or two out of five to six parameters in each model set displays a high uncertainty (e.g. pore-size distribution index in SWAP and Hydrus1D/UNSATCHEM). The differences between the models and model setups reveal the structural uncertainty. The highest structural uncertainty is observed for deep percolation fluxes between the model sets of Hydrus1D/UNSATCHEM (~200 mm) and RZWQM (~500 mm) that are more than twice as high for the latter. The model sets show a high variation in uncertainty intervals for deep percolation as well, with an interquartile range (IQR) of
Statistical Analysis of Input Parameters Impact on the Modelling of Underground Structures

Directory of Open Access Journals (Sweden)

M. Hilar

2008-01-01

Full Text Available The behaviour of a geomechanical model and its final results are strongly affected by the input parameters. As the inherent variability of rock mass is difficult to model, engineers are frequently forced to face the question “Which input values should be used for analyses?” The correct answer to such a question requires a probabilistic approach, considering the uncertainty of site investigations and variation in the ground. This paper describes the statistical analysis of input parameters for FEM calculations of traffic tunnels in the city of Prague. At the beginning of the paper, the inaccuracy in the geotechnical modelling is discussed. In the following part the Fuzzy techniques are summarized, including information about an application of the Fuzzy arithmetic on the shotcrete parameters. The next part of the paper is focused on the stochastic simulation – Monte Carlo Simulation is briefly described, Latin Hypercubes method is described more in details. At the end several practical examples are described: statistical analysis of the input parameters on the numerical modelling of the completed Mrázovka tunnel (profile West Tunnel Tube km 5.160 and modelling of the constructed tunnel Špejchar – Pelc Tyrolka.
Haematology and Serum Biochemistry Parameters and Variations in the Eurasian Beaver (Castor fiber.

Directory of Open Access Journals (Sweden)

Simon J Girling

Full Text Available Haematology parameters (N = 24 and serum biochemistry parameters (N = 35 were determined for wild Eurasian beavers (Castor fiber, between 6 months - 12 years old. Of the population tested in this study, N = 18 Eurasian beavers were from Norway and N = 17 originating from Bavaria but now living extensively in a reserve in England. All blood samples were collected from beavers via the ventral tail vein. All beavers were chemically restrained using inhalant isoflurane in 100% oxygen prior to blood sampling. Results were determined for haematological and serum biochemical parameters for the species and were compared between the two different populations with differences in means estimated and significant differences being noted. Standard blood parameters for the Eurasian beaver were determined and their ranges characterised using percentiles. Whilst the majority of blood parameters between the two populations showed no significant variation, haemoglobin, packed cell volume, mean cell haemoglobin and white blood cell counts showed significantly greater values (p<0.01 in the Bavarian origin population than the Norwegian; neutrophil counts, alpha 2 globulins, cholesterol, sodium: potassium ratios and phosphorus levels showed significantly (p<0.05 greater values in Bavarian versus Norwegian; and potassium, bile acids, gamma globulins, urea, creatinine and total calcium values levels showed significantly (p<0.05 greater values in Norwegian versus Bavarian relict populations. No significant differences were noted between male and female beavers or between sexually immature (<3 years old and sexually mature (≥3 years old beavers in the animals sampled. With Eurasian beaver reintroduction encouraged by legislation throughout Europe, knowledge of baseline blood values for the species and any variations therein is essential when assessing their health and welfare and the success or failure of any reintroduction program. This is the first study to produce
Mathematical modelling of nonstationary processes in a regenerator with dissociating coolant at supercritical parameters

International Nuclear Information System (INIS)

Tashchilova, Eh.M.; Sharovarov, G.A.

1985-01-01

The mathematical model of nonstationary processes in heat exchangers with dissociating coolant at supercritical parameters is given. Its dimensionless criteria are deveped. The effect of NPP regenerator parameters on criteria variation is determined. The proceeding nonstationary processes are estimated qualitatively using the dimensionless parameters. Dynamics of the processes in heat exchangers is described by the energy, mass and moment-of-momentum equations for heating and heated medium taking into account heat accumulation in the heat-transfer wall and distribution of parameters along the length of a heat exchanger

Variational cluster perturbation theory for Bose-Hubbard models

International Nuclear Information System (INIS)

Koller, W; Dupuis, N

2006-01-01

We discuss the application of the variational cluster perturbation theory (VCPT) to the Mott-insulator-to-superfluid transition in the Bose-Hubbard model. We show how the VCPT can be formulated in such a way that it gives a translation invariant excitation spectrum-free of spurious gaps-despite the fact that it formally breaks translation invariance. The phase diagram and the single-particle Green function in the insulating phase are obtained for one-dimensional systems. When the chemical potential of the cluster is taken as a variational parameter, the VCPT reproduces the dimensional dependence of the phase diagram even for one-site clusters. We find a good quantitative agreement with the results of the density-matrix renormalization group when the number of sites in the cluster becomes of order 10. The extension of the method to the superfluid phase is discussed
Variational study of the pair hopping model

International Nuclear Information System (INIS)

Fazekas, P.

1990-01-01

We study the ground state of a Hamiltonian introduced by Kolb and Penson for modelling situations in which small electron pairs are formed. The Hamiltonian consists of a tight binding band term, and a term describing the nearest neighbour hopping of electron pairs. We give a Gutzwiller-type variational treatment, first with a single-parameter Ansatz treated in the single site Gutzwiller approximation, and then with more complicated trial wave functions, and an improved Gutzwiller approximation. The calculation yields a transition from a partially paired normal state, in which the spin susceptibility has a diminished value, into a fully paired state. (author). 16 refs, 2 figs
Long-period and short-period variations of ionospheric parameters studied from complex observations performed on Cuba

Energy Technology Data Exchange (ETDEWEB)

Laso, B; Lobachevskii, L A; Potapova, N I; Freizon, I A; Shapiro, B S

1980-09-01

Cuban data from 1978 are used to study long-period (i.e., diurnal) variations of Doppler shift on a 3000 km path at frequencies of 10 and 15 MHz these variations are related to variations of parameters on the ionospheric path. Short-period variations were also studied on the basis of Doppler shift data and vertical sounding data in the 0.000111-0.00113 Hz frequency range. The relation between the observed variations and internal gravity waves are discussed.
GRACE gravity field modeling with an investigation on correlation between nuisance parameters and gravity field coefficients

Science.gov (United States)

Zhao, Qile; Guo, Jing; Hu, Zhigang; Shi, Chuang; Liu, Jingnan; Cai, Hua; Liu, Xianglin

2011-05-01

The GRACE (Gravity Recovery And Climate Experiment) monthly gravity models have been independently produced and published by several research institutions, such as Center for Space Research (CSR), GeoForschungsZentrum (GFZ), Jet Propulsion Laboratory (JPL), Centre National d’Etudes Spatiales (CNES) and Delft Institute of Earth Observation and Space Systems (DEOS). According to their processing standards, above institutions use the traditional variational approach except that the DEOS exploits the acceleration approach. The background force models employed are rather similar. The produced gravity field models generally agree with one another in the spatial pattern. However, there are some discrepancies in the gravity signal amplitude between solutions produced by different institutions. In particular, 10%-30% signal amplitude differences in some river basins can be observed. In this paper, we implemented a variant of the traditional variational approach and computed two sets of monthly gravity field solutions using the data from January 2005 to December 2006. The input data are K-band range-rates (KBRR) and kinematic orbits of GRACE satellites. The main difference in the production of our two types of models is how to deal with nuisance parameters. This type of parameters is necessary to absorb low-frequency errors in the data, which are mainly the aliasing and instrument errors. One way is to remove the nuisance parameters before estimating the geopotential coefficients, called NPARB approach in the paper. The other way is to estimate the nuisance parameters and geopotential coefficients simultaneously, called NPESS approach. These two types of solutions mainly differ in geopotential coefficients from degree 2 to 5. This can be explained by the fact that the nuisance parameters and the gravity field coefficients are highly correlated, particularly at low degrees. We compare these solutions with the official and published ones by means of spectral analysis. It is
Novel Complete Probabilistic Models of Random Variation in High Frequency Performance of Nanoscale MOSFET

Directory of Open Access Journals (Sweden)

Rawid Banchuin

2013-01-01

Full Text Available The novel probabilistic models of the random variations in nanoscale MOSFET's high frequency performance defined in terms of gate capacitance and transition frequency have been proposed. As the transition frequency variation has also been considered, the proposed models are considered as complete unlike the previous one which take only the gate capacitance variation into account. The proposed models have been found to be both analytic and physical level oriented as they are the precise mathematical expressions in terms of physical parameters. Since the up-to-date model of variation in MOSFET's characteristic induced by physical level fluctuation has been used, part of the proposed models for gate capacitance is more accurate and physical level oriented than its predecessor. The proposed models have been verified based on the 65 nm CMOS technology by using the Monte-Carlo SPICE simulations of benchmark circuits and Kolmogorov-Smirnov tests as highly accurate since they fit the Monte-Carlo-based analysis results with 99% confidence. Hence, these novel models have been found to be versatile for the statistical/variability aware analysis/design of nanoscale MOSFET-based analog/mixed signal circuits and systems.
Ground Motion Prediction for Great Interplate Earthquakes in Kanto Basin Considering Variation of Source Parameters

Science.gov (United States)

Sekiguchi, H.; Yoshimi, M.; Horikawa, H.

2011-12-01

Broadband ground motions are estimated in the Kanto sedimentary basin which holds Tokyo metropolitan area inside for anticipated great interplate earthquakes along surrounding plate boundaries. Possible scenarios of great earthquakes along Sagami trough are modeled combining characteristic properties of the source area and adequate variation in source parameters in order to evaluate possible ground motion variation due to next Kanto earthquake. South to the rupture area of the 2011 Tohoku earthquake along the Japan trench, we consider possible M8 earthquake. The ground motions are computed with a four-step hybrid technique. We first calculate low-frequency ground motions at the engineering basement. We then calculate higher-frequency ground motions at the same position, and combine the lower- and higher-frequency motions using a matched filter. We finally calculate ground motions at the surface by computing the response of the alluvium-diluvium layers to the combined motions at the engineering basement.
Lithium-ion Battery Electrothermal Model, Parameter Estimation, and Simulation Environment

Directory of Open Access Journals (Sweden)

Simone Orcioni

2017-03-01

Full Text Available The market for lithium-ion batteries is growing exponentially. The performance of battery cells is growing due to improving production technology, but market request is growing even more rapidly. Modeling and characterization of single cells and an efficient simulation environment is fundamental for the development of an efficient battery management system. The present work is devoted to defining a novel lumped electrothermal circuit of a single battery cell, the extraction procedure of the parameters of the single cell from experiments, and a simulation environment in SystemC-WMS for the simulation of a battery pack. The electrothermal model of the cell was validated against experimental measurements obtained in a climatic chamber. The model is then used to simulate a 48-cell battery, allowing statistical variations among parameters. The different behaviors of the cells in terms of state of charge, current, voltage, or heat flow rate can be observed in the results of the simulation environment.
Variations of thermospheric composition according to AE-C data and CTIP modelling

Directory of Open Access Journals (Sweden)

H. Rishbeth

2004-01-01

Full Text Available Data from the Atmospheric Explorer C satellite, taken at middle and low latitudes in 1975-1978, are used to study latitudinal and month-by-month variations of thermospheric composition. The parameter used is the "compositional Ρ-parameter", related to the neutral atomic oxygen/molecular nitrogen concentration ratio. The midlatitude data show strong winter maxima of the atomic/molecular ratio, which account for the "seasonal anomaly" of the ionospheric F2-layer. When the AE-C data are compared with the empirical MSIS model and the computational CTIP ionosphere-thermosphere model, broadly similar features are found, but the AE-C data give a more molecular thermosphere than do the models, especially CTIP. In particular, CTIP badly overestimates the winter/summer change of composition, more so in the south than in the north. The semiannual variations at the equator and in southern latitudes, shown by CTIP and MSIS, appear more weakly in the AE-C data. Magnetic activity produces a more molecular thermosphere at high latitudes, and at mid-latitudes in summer. Key words. Atmospheric composition and structure (thermosphere – composition and chemistry
Variations of thermospheric composition according to AE-C data and CTIP modelling

Directory of Open Access Journals (Sweden)

H. Rishbeth

2004-01-01

Full Text Available Data from the Atmospheric Explorer C satellite, taken at middle and low latitudes in 1975-1978, are used to study latitudinal and month-by-month variations of thermospheric composition. The parameter used is the "compositional Ρ-parameter", related to the neutral atomic oxygen/molecular nitrogen concentration ratio. The midlatitude data show strong winter maxima of the atomic/molecular ratio, which account for the "seasonal anomaly" of the ionospheric F2-layer. When the AE-C data are compared with the empirical MSIS model and the computational CTIP ionosphere-thermosphere model, broadly similar features are found, but the AE-C data give a more molecular thermosphere than do the models, especially CTIP. In particular, CTIP badly overestimates the winter/summer change of composition, more so in the south than in the north. The semiannual variations at the equator and in southern latitudes, shown by CTIP and MSIS, appear more weakly in the AE-C data. Magnetic activity produces a more molecular thermosphere at high latitudes, and at mid-latitudes in summer.

Key words. Atmospheric composition and structure (thermosphere – composition and chemistry
Analysis and Comprehensive Analytical Modeling of Statistical Variations in Subthreshold MOSFET's High Frequency Characteristics

Directory of Open Access Journals (Sweden)

Rawid Banchuin

2014-01-01

Full Text Available In this research, the analysis of statistical variations in subthreshold MOSFET's high frequency characteristics defined in terms of gate capacitance and transition frequency, have been shown and the resulting comprehensive analytical models of such variations in terms of their variances have been proposed. Major imperfection in the physical level properties including random dopant fluctuation and effects of variations in MOSFET's manufacturing process, have been taken into account in the proposed analysis and modeling. The up to dated comprehensive analytical model of statistical variation in MOSFET's parameter has been used as the basis of analysis and modeling. The resulting models have been found to be both analytic and comprehensive as they are the precise mathematical expressions in terms of physical level variables of MOSFET. Furthermore, they have been verified at the nanometer level by using 65~nm level BSIM4 based benchmarks and have been found to be very accurate with smaller than 5 % average percentages of errors. Hence, the performed analysis gives the resulting models which have been found to be the potential mathematical tool for the statistical and variability aware analysis and design of subthreshold MOSFET based VHF circuits, systems and applications.
Intelligent Controller Design for Quad-Rotor Stabilization in Presence of Parameter Variations

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Oualid Doukhi

2017-01-01

Full Text Available The paper presents the mathematical model of a quadrotor unmanned aerial vehicle (UAV and the design of robust Self-Tuning PID controller based on fuzzy logic, which offers several advantages over certain types of conventional control methods, specifically in dealing with highly nonlinear systems and parameter uncertainty. The proposed controller is applied to the inner and outer loop for heading and position trajectory tracking control to handle the external disturbances caused by the variation in the payload weight during the flight period. The results of the numerical simulation using gazebo physics engine simulator and real-time experiment using AR drone 2.0 test bed demonstrate the effectiveness of this intelligent control strategy which can improve the robustness of the whole system and achieve accurate trajectory tracking control, comparing it with the conventional proportional integral derivative (PID.
Statistical study of interplanetary condition effect on geomagnetic storms: 2. Variations of parameters

Science.gov (United States)

Yermolaev, Yu. I.; Lodkina, I. G.; Nikolaeva, N. S.; Yermolaev, M. Yu.

2011-02-01

We investigate the behavior of mean values of the solar wind’s and interplanetary magnetic field’s (IMF) parameters and their absolute and relative variations during the magnetic storms generated by various types of the solar wind. In this paper, which is a continuation of paper [1], we, on the basis of the OMNI data archive for the period of 1976-2000, have analyzed 798 geomagnetic storms with D st ≤ -50 nT and their interplanetary sources: corotating interaction regions CIR, compression regions Sheath before the interplanetary CMEs; magnetic clouds MC; “Pistons” Ejecta, and an uncertain type of a source. For the analysis the double superposed epoch analysis method was used, in which the instants of the magnetic storm onset and the minimum of the D st index were taken as reference times. It is shown that the set of interplanetary sources of magnetic storms can be sub-divided into two basic groups according to their slowly and fast varying characteristics: (1) ICME (MC and Ejecta) and (2) CIR and Sheath. The mean values, the absolute and relative variations in MC and Ejecta for all parameters appeared to be either mean or lower than the mean value (the mean values of the electric field E y and of the B z component of IMF are higher in absolute value), while in CIR and Sheath they are higher than the mean value. High values of the relative density variation sN/ are observed in MC. At the same time, the high values for relative variations of the velocity, B z component, and IMF magnitude are observed in Sheath and CIR. No noticeable distinctions in the relationships between considered parameters for moderate and strong magnetic storms were observed.
Solar cooling. Dynamic computer simulations and parameter variations; Solare Kuehlung. Dynamische Rechnersimulationen und Parametervariationen

Energy Technology Data Exchange (ETDEWEB)

Adam, Mario; Lohmann, Sandra [Fachhochschule Duesseldorf (Germany). E2 - Erneuerbare Energien und Energieeffizienz

2011-05-15

The research project 'Solar cooling in the Hardware-in-the-Loop-Test' is funded by the BMBF and deals with the modeling of a pilot plant for solar cooling with the 17.5 kW absorption chiller of Yazaki in the simulation environment of MATLAB/ Simulink with the toolboxes Stateflow and CARNOT. Dynamic simulations and parameter variations according to the work-efficient methodology of design of experiments are used to select meaningful system configurations, control strategies and dimensioning of the components. The results of these simulations will be presented and a view of the use of acquired knowledge for the planned laboratory field tests on a hardware-in-the-loop test stand will be given. (orig.)
Variations of interplanetary parameters and cosmic-ray intensities

International Nuclear Information System (INIS)

Geranios, A.

1980-01-01

Observations of cosmic ray intensity depressions by earth bound neutron monitors and measurements of interplanetary parameter's variations aboard geocentric satellites in the period January 1972-July 1974 are analysed and grouped according to their correlation among them. From this analysis of about 30 cases it came out that the majority of the depressions correlates with the average propagation speed of interplanetary shocks as well as with the amplitude of the interplanetary magnetic field after the eruption of a solar flare. About one fourth of the events correlates with corotating fast solar wind streams. As the recovery time of the shock-related depressions depends strongly on the heliographic longitude of the causitive solar flare, it seems that the cosmic ray modulation region has a corotative-like feature. (Auth.)
Variational methods in molecular modeling

CERN Document Server

2017-01-01

This book presents tutorial overviews for many applications of variational methods to molecular modeling. Topics discussed include the Gibbs-Bogoliubov-Feynman variational principle, square-gradient models, classical density functional theories, self-consistent-field theories, phase-field methods, Ginzburg-Landau and Helfrich-type phenomenological models, dynamical density functional theory, and variational Monte Carlo methods. Illustrative examples are given to facilitate understanding of the basic concepts and quantitative prediction of the properties and rich behavior of diverse many-body systems ranging from inhomogeneous fluids, electrolytes and ionic liquids in micropores, colloidal dispersions, liquid crystals, polymer blends, lipid membranes, microemulsions, magnetic materials and high-temperature superconductors. All chapters are written by leading experts in the field and illustrated with tutorial examples for their practical applications to specific subjects. With emphasis placed on physical unders...
Spatial variations of order parameter around Kondo impurity for T<=Tsub(c)

International Nuclear Information System (INIS)

Yoksan, S.

1980-04-01

Analytic expressions for the spatial variations of the order parameter around a Kondo impurity are obtained. The oscillatory contribution due to the impurity scattering is calculated using the t matrix of Matsuura which conveniently yields the general results below Tsub(c). Differences between our values and those of Schlottmann are reported. (author)
Models for setting ATM parameter values

DEFF Research Database (Denmark)

Blaabjerg, Søren; Gravey, A.; Romæuf, L.

1996-01-01

essential to set traffic characteristic values that are relevant to the considered cell stream, and that ensure that the amount of non-conforming traffic is small. Using a queueing model representation for the GCRA formalism, several methods are available for choosing the traffic characteristics. This paper......In ATM networks, a user should negotiate at connection set-up a traffic contract which includes traffic characteristics and requested QoS. The traffic characteristics currently considered are the Peak Cell Rate, the Sustainable Cell Rate, the Intrinsic Burst Tolerance and the Cell Delay Variation...... (CDV) tolerance(s). The values taken by these traffic parameters characterize the so-called ''Worst Case Traffic'' that is used by CAC procedures for accepting a new connection and allocating resources to it. Conformance to the negotiated traffic characteristics is defined, at the ingress User...
Model parameter updating using Bayesian networks

International Nuclear Information System (INIS)

Treml, C.A.; Ross, Timothy J.

2004-01-01

This paper outlines a model parameter updating technique for a new method of model validation using a modified model reference adaptive control (MRAC) framework with Bayesian Networks (BNs). The model parameter updating within this method is generic in the sense that the model/simulation to be validated is treated as a black box. It must have updateable parameters to which its outputs are sensitive, and those outputs must have metrics that can be compared to that of the model reference, i.e., experimental data. Furthermore, no assumptions are made about the statistics of the model parameter uncertainty, only upper and lower bounds need to be specified. This method is designed for situations where a model is not intended to predict a complete point-by-point time domain description of the item/system behavior; rather, there are specific points, features, or events of interest that need to be predicted. These specific points are compared to the model reference derived from actual experimental data. The logic for updating the model parameters to match the model reference is formed via a BN. The nodes of this BN consist of updateable model input parameters and the specific output values or features of interest. Each time the model is executed, the input/output pairs are used to adapt the conditional probabilities of the BN. Each iteration further refines the inferred model parameters to produce the desired model output. After parameter updating is complete and model inputs are inferred, reliabilities for the model output are supplied. Finally, this method is applied to a simulation of a resonance control cooling system for a prototype coupled cavity linac. The results are compared to experimental data.
Uncertainty analysis of flexible rotors considering fuzzy parameters and fuzzy-random parameters

Directory of Open Access Journals (Sweden)

Fabian Andres Lara-Molina

Full Text Available Abstract The components of flexible rotors are subjected to uncertainties. The main sources of uncertainties include the variation of mechanical properties. This contribution aims at analyzing the dynamics of flexible rotors under uncertain parameters modeled as fuzzy and fuzzy random variables. The uncertainty analysis encompasses the modeling of uncertain parameters and the numerical simulation of the corresponding flexible rotor model by using an approach based on fuzzy dynamic analysis. The numerical simulation is accomplished by mapping the fuzzy parameters of the deterministic flexible rotor model. Thereby, the flexible rotor is modeled by using both the Fuzzy Finite Element Method and the Fuzzy Stochastic Finite Element Method. Numerical simulations illustrate the methodology conveyed in terms of orbits and frequency response functions subject to uncertain parameters.
Variational model for one-dimensional quantum magnets

Science.gov (United States)

Kudasov, Yu. B.; Kozabaranov, R. V.

2018-04-01

A new variational technique for investigation of the ground state and correlation functions in 1D quantum magnets is proposed. A spin Hamiltonian is reduced to a fermionic representation by the Jordan-Wigner transformation. The ground state is described by a new non-local trial wave function, and the total energy is calculated in an analytic form as a function of two variational parameters. This approach is demonstrated with an example of the XXZ-chain of spin-1/2 under a staggered magnetic field. Generalizations and applications of the variational technique for low-dimensional magnetic systems are discussed.

Long-Term Evaluation of Ocean Tidal Variation Models of Polar Motion and UT1

Science.gov (United States)

Karbon, Maria; Balidakis, Kyriakos; Belda, Santiago; Nilsson, Tobias; Hagedoorn, Jan; Schuh, Harald

2018-04-01

Recent improvements in the development of VLBI (very long baseline interferometry) and other space geodetic techniques such as the global navigation satellite systems (GNSS) require very precise a-priori information of short-period (daily and sub-daily) Earth rotation variations. One significant contribution to Earth rotation is caused by the diurnal and semi-diurnal ocean tides. Within this work, we developed a new model for the short-period ocean tidal variations in Earth rotation, where the ocean tidal angular momentum model and the Earth rotation variation have been setup jointly. Besides the model of the short-period variation of the Earth's rotation parameters (ERP), based on the empirical ocean tide model EOT11a, we developed also ERP models, that are based on the hydrodynamic ocean tide models FES2012 and HAMTIDE. Furthermore, we have assessed the effect of uncertainties in the elastic Earth model on the resulting ERP models. Our proposed alternative ERP model to the IERS 2010 conventional model considers the elastic model PREM and 260 partial tides. The choice of the ocean tide model and the determination of the tidal velocities have been identified as the main uncertainties. However, in the VLBI analysis all models perform on the same level of accuracy. From these findings, we conclude that the models presented here, which are based on a re-examined theoretical description and long-term satellite altimetry observation only, are an alternative for the IERS conventional model but do not improve the geodetic results.
PARAMETER ESTIMATION IN BREAD BAKING MODEL

Directory of Open Access Journals (Sweden)

Hadiyanto Hadiyanto

2012-05-01

Full Text Available Bread product quality is highly dependent to the baking process. A model for the development of product quality, which was obtained by using quantitative and qualitative relationships, was calibrated by experiments at a fixed baking temperature of 200°C alone and in combination with 100 W microwave powers. The model parameters were estimated in a stepwise procedure i.e. first, heat and mass transfer related parameters, then the parameters related to product transformations and finally product quality parameters. There was a fair agreement between the calibrated model results and the experimental data. The results showed that the applied simple qualitative relationships for quality performed above expectation. Furthermore, it was confirmed that the microwave input is most meaningful for the internal product properties and not for the surface properties as crispness and color. The model with adjusted parameters was applied in a quality driven food process design procedure to derive a dynamic operation pattern, which was subsequently tested experimentally to calibrate the model. Despite the limited calibration with fixed operation settings, the model predicted well on the behavior under dynamic convective operation and on combined convective and microwave operation. It was expected that the suitability between model and baking system could be improved further by performing calibration experiments at higher temperature and various microwave power levels. Abstrak PERKIRAAN PARAMETER DALAM MODEL UNTUK PROSES BAKING ROTI. Kualitas produk roti sangat tergantung pada proses baking yang digunakan. Suatu model yang telah dikembangkan dengan metode kualitatif dan kuantitaif telah dikalibrasi dengan percobaan pada temperatur 200oC dan dengan kombinasi dengan mikrowave pada 100 Watt. Parameter-parameter model diestimasi dengan prosedur bertahap yaitu pertama, parameter pada model perpindahan masa dan panas, parameter pada model transformasi, dan
Uncertainty analyses of the calibrated parameter values of a water quality model

Science.gov (United States)

Rode, M.; Suhr, U.; Lindenschmidt, K.-E.

2003-04-01

For river basin management water quality models are increasingly used for the analysis and evaluation of different management measures. However substantial uncertainties exist in parameter values depending on the available calibration data. In this paper an uncertainty analysis for a water quality model is presented, which considers the impact of available model calibration data and the variance of input variables. The investigation was conducted based on four extensive flowtime related longitudinal surveys in the River Elbe in the years 1996 to 1999 with varying discharges and seasonal conditions. For the model calculations the deterministic model QSIM of the BfG (Germany) was used. QSIM is a one dimensional water quality model and uses standard algorithms for hydrodynamics and phytoplankton dynamics in running waters, e.g. Michaelis Menten/Monod kinetics, which are used in a wide range of models. The multi-objective calibration of the model was carried out with the nonlinear parameter estimator PEST. The results show that for individual flow time related measuring surveys very good agreements between model calculation and measured values can be obtained. If these parameters are applied to deviating boundary conditions, substantial errors in model calculation can occur. These uncertainties can be decreased with an increased calibration database. More reliable model parameters can be identified, which supply reasonable results for broader boundary conditions. The extension of the application of the parameter set on a wider range of water quality conditions leads to a slight reduction of the model precision for the specific water quality situation. Moreover the investigations show that highly variable water quality variables like the algal biomass always allow a smaller forecast accuracy than variables with lower coefficients of variation like e.g. nitrate.
Mass balance model parameter transferability on a tropical glacier

Science.gov (United States)

Gurgiser, Wolfgang; Mölg, Thomas; Nicholson, Lindsey; Kaser, Georg

2013-04-01

The mass balance and melt water production of glaciers is of particular interest in the Peruvian Andes where glacier melt water has markedly increased water supply during the pronounced dry seasons in recent decades. However, the melt water contribution from glaciers is projected to decrease with appreciable negative impacts on the local society within the coming decades. Understanding mass balance processes on tropical glaciers is a prerequisite for modeling present and future glacier runoff. As a first step towards this aim we applied a process-based surface mass balance model in order to calculate observed ablation at two stakes in the ablation zone of Shallap Glacier (4800 m a.s.l., 9°S) in the Cordillera Blanca, Peru. Under the tropical climate, the snow line migrates very frequently across most of the ablation zone all year round causing large temporal and spatial variations of glacier surface conditions and related ablation. Consequently, pronounced differences between the two chosen stakes and the two years were observed. Hourly records of temperature, humidity, wind speed, short wave incoming radiation, and precipitation are available from an automatic weather station (AWS) on the moraine near the glacier for the hydrological years 2006/07 and 2007/08 while stake readings are available at intervals of between 14 to 64 days. To optimize model parameters, we used 1000 model simulations in which the most sensitive model parameters were varied randomly within their physically meaningful ranges. The modeled surface height change was evaluated against the two stake locations in the lower ablation zone (SH11, 4760m) and in the upper ablation zone (SH22, 4816m), respectively. The optimal parameter set for each point achieved good model skill but if we transfer the best parameter combination from one stake site to the other stake site model errors increases significantly. The same happens if we optimize the model parameters for each year individually and transfer
INFLUENCE OF TECHNOLOGICAL PARAMETERS ON AGROTEXTILES WATER ABSORBENCY USING ANOVA MODEL

Directory of Open Access Journals (Sweden)

LUPU Iuliana G.

2016-05-01

Full Text Available Agrotextiles are now days extensively being used in horticulture, farming and other agricultural activities. Agriculture and textiles are the largest industries in the world providing basic needs such as food and clothing. Agrotextiles plays a significant role to help control environment for crop protection, eliminate variations in climate, weather change and generate optimum condition for plant growth. Water absorptive capacity is a very important property of needle-punched nonwovens used as irrigation substrate in horticulture. Nonwovens used as watering substrate distribute water uniformly and act as slight water buffer owing to the absorbent capacity. The paper analyzes the influence of needling process parameters on water absorptive capacity of needle-punched nonwovens by using ANOVA model. The model allows the identification of optimal action parameters in a shorter time and with less material expenses than by experimental research. The frequency of needle board and needle depth penetration has been used as independent variables while the water absorptive capacity as dependent variable for ANOVA regression model. Based on employed ANOVA model we have established that there is a significant influence of needling parameters on water absorbent capacity. The higher of depth needle penetration and needle board frequency, the higher is the compactness of fabric. A less porous structure has a lower water absorptive capacity.
Variations of some parameters of enzyme induction in chemical workers

Energy Technology Data Exchange (ETDEWEB)

Dolara, P. (Univ. of Florence, Italy); Lodovici, M.; Buffoni, F.; Buiatti, E.; Baccetti, S.; Ciofini, O.; Bavazzano, P.; Barchielli, S.; Vannucci, V.

1982-01-01

Several parameters related to mono-oxygenase activity were followed in a population of chemical workers and controls. Workers exposed to toluene and xylene had a significant increase of urinary glucaric acid, that was correlated with hippuric acid excretion. On the other hand, workers exposed to pigments showed a marked increase of antipyrine half-life. A dose-related decrease of liver N-demethylase was induced in rats by the administration of a mixture of three of the pigments in use in the plant. Serum gamma-glutamyltranspeptidase was decreased in the workers exposed to pigments, but this variation was not statistically significant. The exposure to different chemicals in the workplace seemed to induce a complicated variation of mono-oxygenase levels, some enzyme being inhibited and others induced in the same group of workers. The sensitivity of these workers to toxic effects of chemicals, carcinogenic compounds and drugs seems to differ markedly from the control population.
Assessing the accuracy of subject-specific, muscle-model parameters determined by optimizing to match isometric strength.

Science.gov (United States)

DeSmitt, Holly J; Domire, Zachary J

2016-12-01

Biomechanical models are sensitive to the choice of model parameters. Therefore, determination of accurate subject specific model parameters is important. One approach to generate these parameters is to optimize the values such that the model output will match experimentally measured strength curves. This approach is attractive as it is inexpensive and should provide an excellent match to experimentally measured strength. However, given the problem of muscle redundancy, it is not clear that this approach generates accurate individual muscle forces. The purpose of this investigation is to evaluate this approach using simulated data to enable a direct comparison. It is hypothesized that the optimization approach will be able to recreate accurate muscle model parameters when information from measurable parameters is given. A model of isometric knee extension was developed to simulate a strength curve across a range of knee angles. In order to realistically recreate experimentally measured strength, random noise was added to the modeled strength. Parameters were solved for using a genetic search algorithm. When noise was added to the measurements the strength curve was reasonably recreated. However, the individual muscle model parameters and force curves were far less accurate. Based upon this examination, it is clear that very different sets of model parameters can recreate similar strength curves. Therefore, experimental variation in strength measurements has a significant influence on the results. Given the difficulty in accurately recreating individual muscle parameters, it may be more appropriate to perform simulations with lumped actuators representing similar muscles.
Robust estimation of hydrological model parameters

Directory of Open Access Journals (Sweden)

A. Bárdossy

2008-11-01

Full Text Available The estimation of hydrological model parameters is a challenging task. With increasing capacity of computational power several complex optimization algorithms have emerged, but none of the algorithms gives a unique and very best parameter vector. The parameters of fitted hydrological models depend upon the input data. The quality of input data cannot be assured as there may be measurement errors for both input and state variables. In this study a methodology has been developed to find a set of robust parameter vectors for a hydrological model. To see the effect of observational error on parameters, stochastically generated synthetic measurement errors were applied to observed discharge and temperature data. With this modified data, the model was calibrated and the effect of measurement errors on parameters was analysed. It was found that the measurement errors have a significant effect on the best performing parameter vector. The erroneous data led to very different optimal parameter vectors. To overcome this problem and to find a set of robust parameter vectors, a geometrical approach based on Tukey's half space depth was used. The depth of the set of N randomly generated parameters was calculated with respect to the set with the best model performance (Nash-Sutclife efficiency was used for this study for each parameter vector. Based on the depth of parameter vectors, one can find a set of robust parameter vectors. The results show that the parameters chosen according to the above criteria have low sensitivity and perform well when transfered to a different time period. The method is demonstrated on the upper Neckar catchment in Germany. The conceptual HBV model was used for this study.
Photovoltaic module parameters acquisition model

Energy Technology Data Exchange (ETDEWEB)

Cibira, Gabriel, E-mail: cibira@lm.uniza.sk; Koščová, Marcela, E-mail: mkoscova@lm.uniza.sk

2014-09-01

Highlights: • Photovoltaic five-parameter model is proposed using Matlab{sup ®} and Simulink. • The model acquisits input sparse data matrix from stigmatic measurement. • Computer simulations lead to continuous I–V and P–V characteristics. • Extrapolated I–V and P–V characteristics are in hand. • The model allows us to predict photovoltaics exploitation in different conditions. - Abstract: This paper presents basic procedures for photovoltaic (PV) module parameters acquisition using MATLAB and Simulink modelling. In first step, MATLAB and Simulink theoretical model are set to calculate I–V and P–V characteristics for PV module based on equivalent electrical circuit. Then, limited I–V data string is obtained from examined PV module using standard measurement equipment at standard irradiation and temperature conditions and stated into MATLAB data matrix as a reference model. Next, the theoretical model is optimized to keep-up with the reference model and to learn its basic parameters relations, over sparse data matrix. Finally, PV module parameters are deliverable for acquisition at different realistic irradiation, temperature conditions as well as series resistance. Besides of output power characteristics and efficiency calculation for PV module or system, proposed model validates computing statistical deviation compared to reference model.
Photovoltaic module parameters acquisition model

International Nuclear Information System (INIS)

Cibira, Gabriel; Koščová, Marcela

2014-01-01

Highlights: • Photovoltaic five-parameter model is proposed using Matlab ® and Simulink. • The model acquisits input sparse data matrix from stigmatic measurement. • Computer simulations lead to continuous I–V and P–V characteristics. • Extrapolated I–V and P–V characteristics are in hand. • The model allows us to predict photovoltaics exploitation in different conditions. - Abstract: This paper presents basic procedures for photovoltaic (PV) module parameters acquisition using MATLAB and Simulink modelling. In first step, MATLAB and Simulink theoretical model are set to calculate I–V and P–V characteristics for PV module based on equivalent electrical circuit. Then, limited I–V data string is obtained from examined PV module using standard measurement equipment at standard irradiation and temperature conditions and stated into MATLAB data matrix as a reference model. Next, the theoretical model is optimized to keep-up with the reference model and to learn its basic parameters relations, over sparse data matrix. Finally, PV module parameters are deliverable for acquisition at different realistic irradiation, temperature conditions as well as series resistance. Besides of output power characteristics and efficiency calculation for PV module or system, proposed model validates computing statistical deviation compared to reference model
Variations in embodied energy and carbon emission intensities of construction materials

Energy Technology Data Exchange (ETDEWEB)

Wan Omar, Wan-Mohd-Sabki [Griffith School of Engineering, Griffith University, Gold Coast Campus, Queensland 4222 (Australia); School of Environmental Engineering, Universiti Malaysia Perlis, 02600 Arau, Perlis (Malaysia); Doh, Jeung-Hwan, E-mail: j.doh@griffith.edu.au [Griffith School of Engineering, Griffith University, Gold Coast Campus, Queensland 4222 (Australia); Panuwatwanich, Kriengsak [Griffith School of Engineering, Griffith University, Gold Coast Campus, Queensland 4222 (Australia)

2014-11-15

Identification of parameter variation allows us to conduct more detailed life cycle assessment (LCA) of energy and carbon emission material over their lifecycle. Previous research studies have demonstrated that hybrid LCA (HLCA) can generally overcome the problems of incompleteness and accuracy of embodied energy (EE) and carbon (EC) emission assessment. Unfortunately, the current interpretation and quantification procedure has not been extensively and empirically studied in a qualitative manner, especially in hybridising between the process LCA and I-O LCA. To determine this weakness, this study empirically demonstrates the changes in EE and EC intensities caused by variations to key parameters in material production. Using Australia and Malaysia as a case study, the results are compared with previous hybrid models to identify key parameters and issues. The parameters considered in this study are technological changes, energy tariffs, primary energy factors, disaggregation constant, emission factors, and material price fluctuation. It was found that changes in technological efficiency, energy tariffs and material prices caused significant variations in the model. Finally, the comparison of hybrid models revealed that non-energy intensive materials greatly influence the variations due to high indirect energy and carbon emission in upstream boundary of material production, and as such, any decision related to these materials should be considered carefully. - Highlights: • We investigate the EE and EC intensity variation in Australia and Malaysia. • The influences of parameter variations on hybrid LCA model were evaluated. • Key significant contribution to the EE and EC intensity variation were identified. • High indirect EE and EC content caused significant variation in hybrid LCA models. • Non-energy intensive material caused variation between hybrid LCA models.
Variations in embodied energy and carbon emission intensities of construction materials

International Nuclear Information System (INIS)

Wan Omar, Wan-Mohd-Sabki; Doh, Jeung-Hwan; Panuwatwanich, Kriengsak

2014-01-01

Identification of parameter variation allows us to conduct more detailed life cycle assessment (LCA) of energy and carbon emission material over their lifecycle. Previous research studies have demonstrated that hybrid LCA (HLCA) can generally overcome the problems of incompleteness and accuracy of embodied energy (EE) and carbon (EC) emission assessment. Unfortunately, the current interpretation and quantification procedure has not been extensively and empirically studied in a qualitative manner, especially in hybridising between the process LCA and I-O LCA. To determine this weakness, this study empirically demonstrates the changes in EE and EC intensities caused by variations to key parameters in material production. Using Australia and Malaysia as a case study, the results are compared with previous hybrid models to identify key parameters and issues. The parameters considered in this study are technological changes, energy tariffs, primary energy factors, disaggregation constant, emission factors, and material price fluctuation. It was found that changes in technological efficiency, energy tariffs and material prices caused significant variations in the model. Finally, the comparison of hybrid models revealed that non-energy intensive materials greatly influence the variations due to high indirect energy and carbon emission in upstream boundary of material production, and as such, any decision related to these materials should be considered carefully. - Highlights: • We investigate the EE and EC intensity variation in Australia and Malaysia. • The influences of parameter variations on hybrid LCA model were evaluated. • Key significant contribution to the EE and EC intensity variation were identified. • High indirect EE and EC content caused significant variation in hybrid LCA models. • Non-energy intensive material caused variation between hybrid LCA models
Earth rotation parameter and variation during 2005–2010 solved with LAGEOS SLR data

Directory of Open Access Journals (Sweden)

Yi Shen

2015-01-01

Full Text Available Time series of Earth rotation parameters were estimated from range data measured by the satellite laser ranging technique to the Laser Geodynamics Satellites (LAGEOS-1/2 through 2005 to 2010 using the dynamic method. Compared with Earth orientation parameter (EOP C04, released by the International Earth Rotation and Reference Systems Service, the root mean square errors for the measured X and Y of polar motion (PM and length of day (LOD were 0.24 and 0.25 milliarcseconds (mas, and 0.068 milliseconds (ms, respectively. Compared with ILRSA EOP, the X and Y of PM and LOD were 0.27 and 0.30 mas, and 0.054 ms, respectively. The time series were analyzed using the wavelet transformation and least squares methods. Wavelet analysis showed obvious seasonal and interannual variations of LOD, and both annual and Chandler variations of PM; however, the annual variation could not be distinguished from the Chandler variation because the two frequencies were very close. The trends and periodic variations of LOD and PM were obtained in the least squares sense, and PM showed semi-annual, annual, and Chandler periods. Semi-annual, annual, and quasi-biennial cycles for LOD were also detected. The trend rates of PM in the X and Y directions were 3.17 and −1.60 mas per year, respectively, and the North Pole moved to 26.8°E relative to the crust during 2005–2010. The trend rate of the LOD change was 0.028 ms per year.
CCP Sensitivity Analysis by Variation of Thermal-Hydraulic Parameters of Wolsong-3, 4

Energy Technology Data Exchange (ETDEWEB)

You, Sung Chang [KHNP, Daejeon (Korea, Republic of)

2016-10-15

The PHWRs are tendency that ROPT(Regional Overpower Protection Trip) setpoint is decreased with reduction of CCP(Critical Channel Power) due to aging effects. For this reason, Wolsong unit 3 and 4 has been operated less than 100% power due to the result of ROPT setpoint evaluation. Typically CCP for ROPT evaluation is derived at 100% PHTS(Primary Heat Transport System) boundary conditions - inlet header temperature, header to header different pressure and outlet header pressure. Therefore boundary conditions at 100% power were estimated to calculate the thermal-hydraulic model at 100% power condition. Actually thermal-hydraulic boundary condition data for Wolsong-3 and 4 cannot be taken at 100% power condition at aged reactor condition. Therefore, to create a single-phase thermal-hydraulic model with 80% data, the validity of the model was confirmed at 93.8%(W3), 94.2%(W4, in the two-phase). And thermal-hydraulic boundary conditions at 100% power were calculated to use this model. For this reason, the sensitivities by varying thermal-hydraulic parameters for CCP calculation were evaluated for Wolsong unit 3 and 4. For confirming the uncertainties by variation PHTS model, sensitivity calculations were performed by varying of pressure tube roughness, orifice degradation factor and SG fouling factor, etc. In conclusion, sensitivity calculation results were very similar and the linearity was constant.
Variation of physicochemical parameters during a composting process

International Nuclear Information System (INIS)

Faria C, D.M.; Ballesteros, M.I.; Bendeck, M.

1999-01-01

Two composting processes were carried out; they lasted for about 165 days. In one of the processes the decomposition of the material was performed only by microorganisms only (direct composting) and in the other one, by microorganisms and earthworms -Eisenla foetida- (indirect composting). The first one was carried out in a composting system called c amas a nd the indirect one was carried out in its initial phase in a system of p anelas , then the wastes were transferred to a c ama . The materials were treated in both processes with lime, ammonium nitrate and microorganisms. Periodical samples were taken from different places of the pile and a temperature control was made weekly. The following physicochemical parameters were analyzed in each sample: Humidity, color, pH soil : water in ratios of 1:5 and 1:10, ash, organic matter, CIC, contents of carbon and nitrogen and C/N ratio. In the aqueous extract, C/N ratio and percentage of hydro solubles were analyzed. It was also made a germination assay taking measurements of the percentage of garden cress seeds (Lepidium sativum) that germinated in the aqueous extract. The parameters variation in each process let us to establish that the greatest changes in the material happened in the initial phases of the process (thermophilic and mesophilic phases); the presence of microorganisms was the limiting factor in the dynamic of the process; on the other hand, the earthworm addition did not accelerate the mineralization of organic matter. The results let us to establish that the color determination is not an effective parameter in order to evaluate the degree of maturity of the compost. Other parameters such as temperature and germination percentage can be made as routine test to determine the process rate. Determination of CIC, ash and hydro solubles content are recommended to evaluate the optimal maturity degree in the material. It is proposed changes such as to reduce the composting time to a maximum of 100 days and to
2-D Modelling of Long Period Variations of Galactic Cosmic Ray Intensity

International Nuclear Information System (INIS)

Siluszyk, M; Iskra, K; Alania, M

2015-01-01

A new two-dimensional (2-D) time dependent model describing long-period variations of the Galactic Cosmic Ray (GCR) intensity has been developed. New approximations for the changes of the magnitude B of the Interplanetary Magnetic Field (IMF), the tilt angle δ of the Heliospheric Neutral Sheet (HNS) and drift effects of the GCR particles have been included into the model. Moreover, temporal changes of the exponent γ expressing the power law - rigidity dependence of the amplitudes of the 11-year variation of the GCR intensity have been added. We show that changes of the expected GCR particle density precedes changes of the GCR intensity measured by the Moscow Neutron (MN) monitor by about 18 months. So ∼18 months can be taken as an effective delay time between the expected intensity caused by the combined influence of the changes of the parameters implemented in the time-dependent 2-D model and the GCR intensity measured by neutron monitors during the 21 cycle of solar activity. (paper)
Accounting for parameter uncertainty in the definition of parametric distributions used to describe individual patient variation in health economic models

OpenAIRE

Degeling, Koen; IJzerman, Maarten J.; Koopman, Miriam; Koffijberg, Hendrik

2017-01-01

Background Parametric distributions based on individual patient data can be used to represent both stochastic and parameter uncertainty. Although general guidance is available on how parameter uncertainty should be accounted for in probabilistic sensitivity analysis, there is no comprehensive guidance on reflecting parameter uncertainty in the (correlated) parameters of distributions used to represent stochastic uncertainty in patient-level models. This study aims to provide this guidance by ...
Convergence of surface diffusion parameters with model crystal size

Science.gov (United States)

Cohen, Jennifer M.; Voter, Arthur F.

1994-07-01

A study of the variation in the calculated quantities for adatom diffusion with respect to the size of the model crystal is presented. The reported quantities include surface diffusion barrier heights, pre-exponential factors, and dynamical correction factors. Embedded atom method (EAM) potentials were used throughout this effort. Both the layer size and the depth of the crystal were found to influence the values of the Arrhenius factors significantly. In particular, exchange type mechanisms required a significantly larger model than standard hopping mechanisms to determine adatom diffusion barriers of equivalent accuracy. The dynamical events that govern the corrections to transition state theory (TST) did not appear to be as sensitive to crystal depth. Suitable criteria for the convergence of the diffusion parameters with regard to the rate properties are illustrated.
Increase in winter haze over eastern China in recent decades: Roles of variations in meteorological parameters and anthropogenic emissions: INCREASE IN WINTER HAZE IN EASTERN CHINA

Energy Technology Data Exchange (ETDEWEB)

Yang, Yang [Atmospheric Science and Global Change Division, Pacific Northwest National Laboratory, Richland Washington USA; Liao, Hong [School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing China; Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing China; Lou, Sijia [Atmospheric Science and Global Change Division, Pacific Northwest National Laboratory, Richland Washington USA

2016-11-05

The increase in winter haze over eastern China in recent decades due to variations in meteorological parameters and anthropogenic emissions was quantified using observed atmospheric visibility from the National Climatic Data Center Global Summary of Day database for 1980–2014 and simulated PM2.5 concentrations for 1985–2005 from the Goddard Earth Observing System (GEOS) chemical transport model (GEOS-Chem). Observed winter haze days averaged over eastern China (105–122.5°E, 20–45°N) increased from 21 d in 1980 to 42 d in 2014, and from 22 to 30 d between 1985 and 2005. The GEOS-Chem model captured the increasing trend of winter PM2.5 concentrations for 1985–2005, with concentrations averaged over eastern China increasing from 16.1 μg m^-3 in 1985 to 38.4 μg m^-3 in 2005. Considering variations in both anthropogenic emissions and meteorological parameters, the model simulated an increase in winter surface-layer PM2.5 concentrations of 10.5 (±6.2) μg m^-3 decade^-1 over eastern China. The increasing trend was only 1.8 (±1.5) μg m^-3 decade^-1 when variations in meteorological parameters alone were considered. Among the meteorological parameters, the weakening of winds by -0.09 m s^-1 decade^-1 over 1985–2005 was found to be the dominant factor leading to the decadal increase in winter aerosol concentrations and haze days over eastern China during recent decades.
Nonlinear Variation of Parameters Formula for Impulsive Differential Equations with Initial Time Difference and Application

Directory of Open Access Journals (Sweden)

Peiguang Wang

2014-01-01

Full Text Available This paper establishes variation of parameters formula for impulsive differential equations with initial time difference. As an application, one of the results is used to investigate stability properties of solutions.

Two-dimensional strain gradient damage modeling: a variational approach

Science.gov (United States)

Placidi, Luca; Misra, Anil; Barchiesi, Emilio

2018-06-01

In this paper, we formulate a linear elastic second gradient isotropic two-dimensional continuum model accounting for irreversible damage. The failure is defined as the condition in which the damage parameter reaches 1, at least in one point of the domain. The quasi-static approximation is done, i.e., the kinetic energy is assumed to be negligible. In order to deal with dissipation, a damage dissipation term is considered in the deformation energy functional. The key goal of this paper is to apply a non-standard variational procedure to exploit the damage irreversibility argument. As a result, we derive not only the equilibrium equations but, notably, also the Karush-Kuhn-Tucker conditions. Finally, numerical simulations for exemplary problems are discussed as some constitutive parameters are varying, with the inclusion of a mesh-independence evidence. Element-free Galerkin method and moving least square shape functions have been employed.
Modelling lamb carcase pH and temperature decline parameters: relationship to shear force and abattoir variation.

Science.gov (United States)

Hopkins, David L; Holman, Benjamin W B; van de Ven, Remy J

2015-02-01

Carcase pH and temperature decline rates influence lamb tenderness; therefore pH decline parameters are beneficial when modelling tenderness. These include pH at temperature 18 °C (pH@Temp18), temperature when pH is 6 (Temp@pH6), and pH at 24 h post-mortem (pH24). This study aimed to establish a relationship between shear force (SF) as a proxy for tenderness and carcase pH decline parameters estimated using both linear and spline estimation models for the m. longissimus lumborum (LL). The study also compared abattoirs regarding their achievement of ideal pH decline, indicative of optimal tenderness. Based on SF measurements of LL and m. semimembranosus collected as part of the Information Nucleus slaughter programme (CRC for Sheep Industry Innovation) this study found significant relationships between tenderness and pH24LL, consistent across the meat cuts and ageing periods examined. Achievement of ideal pH decline was shown not to have significantly differed across abattoirs, although rates of pH decline varied significantly across years within abattoirs.
Application of a PID controller based on fuzzy logic to reduce variations in the control parameters in PWR reactors

International Nuclear Information System (INIS)

Vasconcelos, Wagner Eustaquio de; Lira, Carlos Alberto Brayner de Oliveira; Brito, Thiago Souza Pereira de; Afonso, Antonio Claudio Marques; Cruz Filho, Antonio Jose da; Marques, Jose Antonio; Teixeira, Marcello Goulart

2013-01-01

Nuclear reactors are in nature nonlinear systems and their parameters vary with time as a function of power level. These characteristics must be considered if large power variations occur in power plant operational regimes, such as in load-following conditions. A PWR reactor has a component called pressurizer, whose function is to supply the necessary high pressure for its operation and to contain pressure variations in the primary cooling system. The use of control systems capable of reducing fast variations of the operation variables and to maintain the stability of this system is of fundamental importance. The best-known controllers used in industrial control processes are proportional-integral-derivative (PID) controllers due to their simple structure and robust performance in a wide range of operating conditions. However, designing a fuzzy controller is seen to be a much less difficult task. Once a Fuzzy Logic controller is designed for a particular set of parameters of the nonlinear element, it yields satisfactory performance for a range of these parameters. The objective of this work is to develop fuzzy proportional-integral-derivative (fuzzy-PID) control strategies to control the level of water in the reactor. In the study of the pressurizer, several computer codes are used to simulate its dynamic behavior. At the fuzzy-PID control strategy, the fuzzy logic controller is exploited to extend the finite sets of PID gains to the possible combinations of PID gains in stable region. Thus the fuzzy logic controller tunes the gain of PID controller to adapt the model with changes in the water level of reactor. The simulation results showed a favorable performance with the use to fuzzy-PID controllers. (author)
Parameter Estimation of Partial Differential Equation Models.

Science.gov (United States)

Xun, Xiaolei; Cao, Jiguo; Mallick, Bani; Carroll, Raymond J; Maity, Arnab

2013-01-01

Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown, and need to be estimated from the measurements of the dynamic system in the present of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE, and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from LIDAR data.
Physically-based slope stability modelling and parameter sensitivity: a case study in the Quitite and Papagaio catchments, Rio de Janeiro, Brazil

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de Lima Neves Seefelder, Carolina; Mergili, Martin

2016-04-01

We use the software tools r.slope.stability and TRIGRS to produce factor of safety and slope failure susceptibility maps for the Quitite and Papagaio catchments, Rio de Janeiro, Brazil. The key objective of the work consists in exploring the sensitivity of the geotechnical (r.slope.stability) and geohydraulic (TRIGRS) parameterization on the model outcomes in order to define suitable parameterization strategies for future slope stability modelling. The two landslide-prone catchments Quitite and Papagaio together cover an area of 4.4 km², extending between 12 and 995 m a.s.l. The study area is dominated by granitic bedrock and soil depths of 1-3 m. Ranges of geotechnical and geohydraulic parameters are derived from literature values. A landslide inventory related to a rainfall event in 1996 (250 mm in 48 hours) is used for model evaluation. We attempt to identify those combinations of effective cohesion and effective internal friction angle yielding the best correspondence with the observed landslide release areas in terms of the area under the ROC Curve (AUCROC), and in terms of the fraction of the area affected by the release of landslides. Thereby we test multiple parameter combinations within defined ranges to derive the slope failure susceptibility (fraction of tested parameter combinations yielding a factor of safety smaller than 1). We use the tool r.slope.stability (comparing the infinite slope stability model and an ellipsoid-based sliding surface model) to test and to optimize the geotechnical parameters, and TRIGRS (a coupled hydraulic-infinite slope stability model) to explore the sensitivity of the model results to the geohydraulic parameters. The model performance in terms of AUCROC is insensitive to the variation of the geotechnical parameterization within much of the tested ranges. Assuming fully saturated soils, r.slope.stability produces rather conservative predictions, whereby the results yielded with the sliding surface model are more
Parameter sensitivity analysis of a lumped-parameter model of a chain of lymphangions in series.

Science.gov (United States)

Jamalian, Samira; Bertram, Christopher D; Richardson, William J; Moore, James E

2013-12-01

Any disruption of the lymphatic system due to trauma or injury can lead to edema. There is no effective cure for lymphedema, partly because predictive knowledge of lymphatic system reactions to interventions is lacking. A well-developed model of the system could greatly improve our understanding of its function. Lymphangions, defined as the vessel segment between two valves, are the individual pumping units. Based on our previous lumped-parameter model of a chain of lymphangions, this study aimed to identify the parameters that affect the system output the most using a sensitivity analysis. The system was highly sensitive to minimum valve resistance, such that variations in this parameter caused an order-of-magnitude change in time-average flow rate for certain values of imposed pressure difference. Average flow rate doubled when contraction frequency was increased within its physiological range. Optimum lymphangion length was found to be some 13-14.5 diameters. A peak of time-average flow rate occurred when transmural pressure was such that the pressure-diameter loop for active contractions was centered near maximum passive vessel compliance. Increasing the number of lymphangions in the chain improved the pumping in the presence of larger adverse pressure differences. For a given pressure difference, the optimal number of lymphangions increased with the total vessel length. These results indicate that further experiments to estimate valve resistance more accurately are necessary. The existence of an optimal value of transmural pressure may provide additional guidelines for increasing pumping in areas affected by edema.
Accounting for parameter uncertainty in the definition of parametric distributions used to describe individual patient variation in health economic models

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Koen Degeling

2017-12-01

Full Text Available Abstract Background Parametric distributions based on individual patient data can be used to represent both stochastic and parameter uncertainty. Although general guidance is available on how parameter uncertainty should be accounted for in probabilistic sensitivity analysis, there is no comprehensive guidance on reflecting parameter uncertainty in the (correlated parameters of distributions used to represent stochastic uncertainty in patient-level models. This study aims to provide this guidance by proposing appropriate methods and illustrating the impact of this uncertainty on modeling outcomes. Methods Two approaches, 1 using non-parametric bootstrapping and 2 using multivariate Normal distributions, were applied in a simulation and case study. The approaches were compared based on point-estimates and distributions of time-to-event and health economic outcomes. To assess sample size impact on the uncertainty in these outcomes, sample size was varied in the simulation study and subgroup analyses were performed for the case-study. Results Accounting for parameter uncertainty in distributions that reflect stochastic uncertainty substantially increased the uncertainty surrounding health economic outcomes, illustrated by larger confidence ellipses surrounding the cost-effectiveness point-estimates and different cost-effectiveness acceptability curves. Although both approaches performed similar for larger sample sizes (i.e. n = 500, the second approach was more sensitive to extreme values for small sample sizes (i.e. n = 25, yielding infeasible modeling outcomes. Conclusions Modelers should be aware that parameter uncertainty in distributions used to describe stochastic uncertainty needs to be reflected in probabilistic sensitivity analysis, as it could substantially impact the total amount of uncertainty surrounding health economic outcomes. If feasible, the bootstrap approach is recommended to account for this uncertainty.
Accounting for parameter uncertainty in the definition of parametric distributions used to describe individual patient variation in health economic models.

Science.gov (United States)

Degeling, Koen; IJzerman, Maarten J; Koopman, Miriam; Koffijberg, Hendrik

2017-12-15

Parametric distributions based on individual patient data can be used to represent both stochastic and parameter uncertainty. Although general guidance is available on how parameter uncertainty should be accounted for in probabilistic sensitivity analysis, there is no comprehensive guidance on reflecting parameter uncertainty in the (correlated) parameters of distributions used to represent stochastic uncertainty in patient-level models. This study aims to provide this guidance by proposing appropriate methods and illustrating the impact of this uncertainty on modeling outcomes. Two approaches, 1) using non-parametric bootstrapping and 2) using multivariate Normal distributions, were applied in a simulation and case study. The approaches were compared based on point-estimates and distributions of time-to-event and health economic outcomes. To assess sample size impact on the uncertainty in these outcomes, sample size was varied in the simulation study and subgroup analyses were performed for the case-study. Accounting for parameter uncertainty in distributions that reflect stochastic uncertainty substantially increased the uncertainty surrounding health economic outcomes, illustrated by larger confidence ellipses surrounding the cost-effectiveness point-estimates and different cost-effectiveness acceptability curves. Although both approaches performed similar for larger sample sizes (i.e. n = 500), the second approach was more sensitive to extreme values for small sample sizes (i.e. n = 25), yielding infeasible modeling outcomes. Modelers should be aware that parameter uncertainty in distributions used to describe stochastic uncertainty needs to be reflected in probabilistic sensitivity analysis, as it could substantially impact the total amount of uncertainty surrounding health economic outcomes. If feasible, the bootstrap approach is recommended to account for this uncertainty.
Impact of the calibration period on the conceptual rainfall-runoff model parameter estimates

Science.gov (United States)

Todorovic, Andrijana; Plavsic, Jasna

2015-04-01

. Correlation coefficients among optimised model parameters and total precipitation P, mean temperature T and mean flow Q are calculated to give an insight into parameter dependence on the hydrometeorological drivers. The results reveal high sensitivity of almost all model parameters towards calibration period. The highest variability is displayed by the refreezing coefficient, water holding capacity, and temperature gradient. The only statistically significant (decreasing) trend is detected in the evapotranspiration reduction threshold. Statistically significant correlation is detected between the precipitation gradient and precipitation depth, and between the time-area histogram base and flows. All other correlations are not statistically significant, implying that changes in optimised parameters cannot generally be linked to the changes in P, T or Q. As for the model performance, the model reproduces the observed runoff satisfactorily, though the runoff is slightly overestimated in wet periods. The Nash-Sutcliffe efficiency coefficient (NSE) ranges from 0.44 to 0.79. Higher NSE values are obtained over wetter periods, what is supported by statistically significant correlation between NSE and flows. Overall, no systematic variations in parameters or in model performance are detected. Parameter variability may therefore rather be attributed to errors in data or inadequacies in the model structure. Further research is required to examine the impact of the calibration strategy or model structure on the variability in optimised parameters in time.
Parameter sensitivity analysis of a 1-D cold region lake model for land-surface schemes

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Guerrero, José-Luis; Pernica, Patricia; Wheater, Howard; Mackay, Murray; Spence, Chris

2017-12-01

Lakes might be sentinels of climate change, but the uncertainty in their main feedback to the atmosphere - heat-exchange fluxes - is often not considered within climate models. Additionally, these fluxes are seldom measured, hindering critical evaluation of model output. Analysis of the Canadian Small Lake Model (CSLM), a one-dimensional integral lake model, was performed to assess its ability to reproduce diurnal and seasonal variations in heat fluxes and the sensitivity of simulated fluxes to changes in model parameters, i.e., turbulent transport parameters and the light extinction coefficient (Kd). A C++ open-source software package, Problem Solving environment for Uncertainty Analysis and Design Exploration (PSUADE), was used to perform sensitivity analysis (SA) and identify the parameters that dominate model behavior. The generalized likelihood uncertainty estimation (GLUE) was applied to quantify the fluxes' uncertainty, comparing daily-averaged eddy-covariance observations to the output of CSLM. Seven qualitative and two quantitative SA methods were tested, and the posterior likelihoods of the modeled parameters, obtained from the GLUE analysis, were used to determine the dominant parameters and the uncertainty in the modeled fluxes. Despite the ubiquity of the equifinality issue - different parameter-value combinations yielding equivalent results - the answer to the question was unequivocal: Kd, a measure of how much light penetrates the lake, dominates sensible and latent heat fluxes, and the uncertainty in their estimates is strongly related to the accuracy with which Kd is determined. This is important since accurate and continuous measurements of Kd could reduce modeling uncertainty.
A Total Variation Model Based on the Strictly Convex Modification for Image Denoising

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Boying Wu

2014-01-01

Full Text Available We propose a strictly convex functional in which the regular term consists of the total variation term and an adaptive logarithm based convex modification term. We prove the existence and uniqueness of the minimizer for the proposed variational problem. The existence, uniqueness, and long-time behavior of the solution of the associated evolution system is also established. Finally, we present experimental results to illustrate the effectiveness of the model in noise reduction, and a comparison is made in relation to the more classical methods of the traditional total variation (TV, the Perona-Malik (PM, and the more recent D-α-PM method. Additional distinction from the other methods is that the parameters, for manual manipulation, in the proposed algorithm are reduced to basically only one.
Quality assessment for radiological model parameters

International Nuclear Information System (INIS)

Funtowicz, S.O.

1989-01-01

A prototype framework for representing uncertainties in radiological model parameters is introduced. This follows earlier development in this journal of a corresponding framework for representing uncertainties in radiological data. Refinements and extensions to the earlier framework are needed in order to take account of the additional contextual factors consequent on using data entries to quantify model parameters. The parameter coding can in turn feed in to methods for evaluating uncertainties in calculated model outputs. (author)
Seismo-Geochemical Variations in SW Taiwan: Multi-Parameter Automatic Gas Monitoring Results

Science.gov (United States)

Yang, T. F.; Fu, C.-C.; Walia, V.; Chen, C.-H.; Chyi, L. L.; Liu, T.-K.; Song, S.-R.; Lee, M.; Lin, C.-W.; Lin, C.-C.

2006-04-01

Gas variations of many mud volcanoes and hot springs distributed along the tectonic sutures in southwestern Taiwan are considered to be sensitive to the earthquake activity. Therefore, a multi-parameter automatic gas station was built on the bank of one of the largest mud-pools at an active fault zone of southwestern Taiwan, for continuous monitoring of CO2, CH4, N2 and H2O, the major constituents of its bubbling gases. During the year round monitoring from October 2001 to October 2002, the gas composition, especially, CH4 and CO2, of the mud pool showed significant variations. Taking the CO2/CH4 ratio as the main indicator, anomalous variations can be recognized from a few days to a few weeks before earthquakes and correlated well with those with a local magnitude >4.0 and local intensities >2. It is concluded that the gas composition in the area is sensitive to the local crustal stress/strain and is worthy to conduct real-time monitoring for the seismo-geochemical precursors.
Modeling the impact of drought on canopy carbon and water fluxes for a subtropical evergreen coniferous plantation in southern China through parameter optimization using an ensemble Kalman filter

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W. Ju

2010-03-01

Full Text Available Soil and atmospheric water deficits have significant influences on CO₂ and energy exchanges between the atmosphere and terrestrial ecosystems. Model parameterization significantly affects the ability of a model to simulate carbon, water, and energy fluxes. In this study, an ensemble Kalman filter (EnKF and observations of gross primary productivity (GPP and latent heat (LE fluxes were used to optimize model parameters significantly affecting the calculation of these fluxes for a subtropical coniferous plantation in southeastern China. The optimized parameters include the maximum carboxylation rate (Vc_max, the slope in the modified Ball-Berry model (M and the coefficient determining the sensitivity of stomatal conductance to atmospheric water vapor deficit (D₀. Optimized Vc_max and M showed larger variations than D₀. Seasonal variations of Vc_max and M were more pronounced than the variations between the two years. Vc_max and M were associated with soil water content (SWC. During dry periods, SWC at the 20 cm depth explained 61% and 64% of variations of Vc_max and M, respectively. EnKF parameter optimization improved the simulations of GPP, LE and SH, mainly during dry periods. After parameter optimization using EnKF, the variations of GPP, LE and SH explained by the model increased by 1% to 4% at half-hourly steps and by 3% to 5% at daily time steps. Further efforts are needed to differentiate the real causes of parameter variations and improve the ability of models to describe the change of stomatal conductance with net photosynthesis rate and the sensitivity of photosynthesis capacity to soil water stress under different environmental conditions.
Stability Analysis for Li-Ion Battery Model Parameters and State of Charge Estimation by Measurement Uncertainty Consideration

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Shifei Yuan

2015-07-01

Full Text Available Accurate estimation of model parameters and state of charge (SoC is crucial for the lithium-ion battery management system (BMS. In this paper, the stability of the model parameters and SoC estimation under measurement uncertainty is evaluated by three different factors: (i sampling periods of 1/0.5/0.1 s; (ii current sensor precisions of ±5/±50/±500 mA; and (iii voltage sensor precisions of ±1/±2.5/±5 mV. Firstly, the numerical model stability analysis and parametric sensitivity analysis for battery model parameters are conducted under sampling frequency of 1–50 Hz. The perturbation analysis is theoretically performed of current/voltage measurement uncertainty on model parameter variation. Secondly, the impact of three different factors on the model parameters and SoC estimation was evaluated with the federal urban driving sequence (FUDS profile. The bias correction recursive least square (CRLS and adaptive extended Kalman filter (AEKF algorithm were adopted to estimate the model parameters and SoC jointly. Finally, the simulation results were compared and some insightful findings were concluded. For the given battery model and parameter estimation algorithm, the sampling period, and current/voltage sampling accuracy presented a non-negligible effect on the estimation results of model parameters. This research revealed the influence of the measurement uncertainty on the model parameter estimation, which will provide the guidelines to select a reasonable sampling period and the current/voltage sensor sampling precisions in engineering applications.
SU-F-R-32: Evaluation of MRI Acquisition Parameter Variations On Texture Feature Extraction Using ACR Phantom

International Nuclear Information System (INIS)

Xie, Y; Wang, J; Wang, C; Chang, Z

2016-01-01

Purpose: To investigate the sensitivity of classic texture features to variations of MRI acquisition parameters. Methods: This study was performed on American College of Radiology (ACR) MRI Accreditation Program Phantom. MR imaging was acquired on a GE 750 3T scanner with XRM explain gradient, employing a T1-weighted images (TR/TE=500/20ms) with the following parameters as the reference standard: number of signal average (NEX) = 1, matrix size = 256×256, flip angle = 90°, slice thickness = 5mm. The effect of the acquisition parameters on texture features with and without non-uniformity correction were investigated respectively, while all the other parameters were kept as reference standard. Protocol parameters were set as follows: (a). NEX = 0.5, 2 and 4; (b).Phase encoding steps = 128, 160 and 192; (c). Matrix size = 128×128, 192×192 and 512×512. 32 classic texture features were generated using the classic gray level run length matrix (GLRLM) and gray level co-occurrence matrix (GLCOM) from each image data set. Normalized range ((maximum-minimum)/mean) was calculated to determine variation among the scans with different protocol parameters. Results: For different NEX, 31 out of 32 texture features’ range are within 10%. For different phase encoding steps, 31 out of 32 texture features’ range are within 10%. For different acquisition matrix size without non-uniformity correction, 14 out of 32 texture features’ range are within 10%; for different acquisition matrix size with non-uniformity correction, 16 out of 32 texture features’ range are within 10%. Conclusion: Initial results indicated that those texture features that range within 10% are less sensitive to variations in T1-weighted MRI acquisition parameters. This might suggest that certain texture features might be more reliable to be used as potential biomarkers in MR quantitative image analysis.
A variational void coalescence model for ductile metals

KAUST Repository

Siddiq, Amir; Arciniega, Roman; El Sayed, Tamer

2011-01-01

We present a variational void coalescence model that includes all the essential ingredients of failure in ductile porous metals. The model is an extension of the variational void growth model by Weinberg et al. (Comput Mech 37:142-152, 2006
Variations in Modeled Dengue Transmission over Puerto Rico Using a Climate Driven Dynamic Model

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Morin, Cory; Monaghan, Andrew; Crosson, William; Quattrochi, Dale; Luvall, Jeffrey

2014-01-01

Dengue fever is a mosquito-borne viral disease reemerging throughout much of the tropical Americas. Dengue virus transmission is explicitly influenced by climate and the environment through its primary vector, Aedes aegypti. Temperature regulates Ae. aegypti development, survival, and replication rates as well as the incubation period of the virus within the mosquito. Precipitation provides water for many of the preferred breeding habitats of the mosquito, including buckets, old tires, and other places water can collect. Because of variations in topography, ocean influences and atmospheric processes, temperature and rainfall patterns vary across Puerto Rico and so do dengue virus transmission rates. Using NASA's TRMM (Tropical Rainfall Measuring Mission) satellite for precipitation input, ground-based observations for temperature input, and laboratory confirmed dengue cases reported by the Centers for Disease Control and Prevention for parameter calibration, we modeled dengue transmission at the county level across Puerto Rico from 2010-2013 using a dynamic dengue transmission model that includes interacting vector ecology and epidemiological components. Employing a Monte Carlo approach, we performed ensembles of several thousands of model simulations for each county in order to resolve the model uncertainty arising from using different combinations of parameter values that are not well known. The top 1% of model simulations that best reproduced the reported dengue case data were then analyzed to determine the most important parameters for dengue virus transmission in each county, as well as the relative influence of climate variability on transmission. These results can be used by public health workers to implement dengue control methods that are targeted for specific locations and climate conditions.
The variation of health effects based on the scenarios considering release parameters and meteorological data

International Nuclear Information System (INIS)

Jeong, Jong Tae; Ha, Jae Joo

2000-01-01

The variation of health effects resulting from the severe accidents of the YGN 3 and 4 nuclear power plants was examined based on scenarios considering the release parameters and meteorological data. The release parameters and meteorological data considered in making basic scenarios are release height, heat content, release time, warning time, wind speed, rainfall rate, and atmospheric stability class. The seasonal scenarios were also made in order to estimate the seasonal variation of health effects by considering seasonal characteristics of Korea. According to the results, there are large differences in consequence analysis from scenario to although an equal amount of radioactive materials is released to the atmosphere. Also, there are large differences in health effects from season to season due to distinct seasonal characteristics of Korea. Therefore, it is necessary to consider seasonal characteristics in developing optimum emergency response strategies
Parameter Estimation of Partial Differential Equation Models

KAUST Repository

Xun, Xiaolei

2013-09-01

Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown and need to be estimated from the measurements of the dynamic system in the presence of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from long-range infrared light detection and ranging data. Supplementary materials for this article are available online. © 2013 American Statistical Association.

Parameter Estimation for Thurstone Choice Models

Energy Technology Data Exchange (ETDEWEB)

Vojnovic, Milan [London School of Economics (United Kingdom); Yun, Seyoung [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-04-24

We consider the estimation accuracy of individual strength parameters of a Thurstone choice model when each input observation consists of a choice of one item from a set of two or more items (so called top-1 lists). This model accommodates the well-known choice models such as the Luce choice model for comparison sets of two or more items and the Bradley-Terry model for pair comparisons. We provide a tight characterization of the mean squared error of the maximum likelihood parameter estimator. We also provide similar characterizations for parameter estimators defined by a rank-breaking method, which amounts to deducing one or more pair comparisons from a comparison of two or more items, assuming independence of these pair comparisons, and maximizing a likelihood function derived under these assumptions. We also consider a related binary classification problem where each individual parameter takes value from a set of two possible values and the goal is to correctly classify all items within a prescribed classification error. The results of this paper shed light on how the parameter estimation accuracy depends on given Thurstone choice model and the structure of comparison sets. In particular, we found that for unbiased input comparison sets of a given cardinality, when in expectation each comparison set of given cardinality occurs the same number of times, for a broad class of Thurstone choice models, the mean squared error decreases with the cardinality of comparison sets, but only marginally according to a diminishing returns relation. On the other hand, we found that there exist Thurstone choice models for which the mean squared error of the maximum likelihood parameter estimator can decrease much faster with the cardinality of comparison sets. We report empirical evaluation of some claims and key parameters revealed by theory using both synthetic and real-world input data from some popular sport competitions and online labor platforms.
Modeling sugarcane yield with a process-based model from site to continental scale: uncertainties arising from model structure and parameter values

Science.gov (United States)

Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Caubel, A.; Huth, N.; Marin, F.; Martiné, J.-F.

2014-06-01

parameters on a continental scale across the large regions of intensive sugarcane cultivation in Australia and Brazil. The ten parameters driving most of the uncertainty in the ORCHIDEE-STICS modeled biomass at the 7 sites are identified by the screening procedure. We found that the 10 most sensitive parameters control phenology (maximum rate of increase of LAI) and root uptake of water and nitrogen (root profile and root growth rate, nitrogen stress threshold) in STICS, and photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), and transpiration and respiration (stomatal conductance, growth and maintenance respiration coefficients) in ORCHIDEE. We find that the optimal carboxylation rate and photosynthesis temperature parameters contribute most to the uncertainty in harvested biomass simulations at site scale. The spatial variation of the ranked correlation between input parameters and modeled biomass at harvest is well explained by rain and temperature drivers, suggesting different climate-mediated sensitivities of modeled sugarcane yield to the model parameters, for Australia and Brazil. This study reveals the spatial and temporal patterns of uncertainty variability for a highly parameterized agro-LSM and calls for more systematic uncertainty analyses of such models.
Predicting Variation of DNA Shape Preferences in Protein-DNA Interaction in Cancer Cells with a New Biophysical Model.

Science.gov (United States)

Batmanov, Kirill; Wang, Junbai

2017-09-18

DNA shape readout is an important mechanism of transcription factor target site recognition, in addition to the sequence readout. Several machine learning-based models of transcription factor-DNA interactions, considering DNA shape features, have been developed in recent years. Here, we present a new biophysical model of protein-DNA interactions by integrating the DNA shape properties. It is based on the neighbor dinucleotide dependency model BayesPI2, where new parameters are restricted to a subspace spanned by the dinucleotide form of DNA shape features. This allows a biophysical interpretation of the new parameters as a position-dependent preference towards specific DNA shape features. Using the new model, we explore the variation of DNA shape preferences in several transcription factors across various cancer cell lines and cellular conditions. The results reveal that there are DNA shape variations at FOXA1 (Forkhead Box Protein A1) binding sites in steroid-treated MCF7 cells. The new biophysical model is useful for elucidating the finer details of transcription factor-DNA interaction, as well as for predicting cancer mutation effects in the future.
Nycthemeral variations of 99Tcsup(m)-labelled heparin pharmacokinetic parameters

International Nuclear Information System (INIS)

Decousus, M.; Gremillet, E.; Decousus, H.; Champailler, A.; Houzard, C.; Perpoint, B.; Jaubert, J.

1985-01-01

Six healthy volunteers received four i.v.boluses of 99 Tcsup(m)-heparin at 8.00, 14.00, 20.00 and 02.00 hours at seven-day intervals. Nine blood samples were taken covering a period of 2 h after administration. Simultaneously urine was collected and diuresis not noted. Plasma and urinary radioactivity were measured and standard pharmacokinetic parameters were calculated. Nycthemeral variations of these kinetic parameters were detected by means of distribution-free tests. Circadian rhythms were analysed by means of the cosinor method and the Gauss-Marquardt method. The mean raw value of the following parameters: apparent volume of distribution, plasmatic clearance and extra-renal metabolic clearance, increased significantly between 8.00 and 14.00 and decreased between 14.00 and 20.00. A circadian rhythm was found for the plasmatic clearance only. On the other hand the elimination half-lives and the renal clearance were unaffected by the time of the injections. These results obtained for low doses of 99 Tcsup(m)-heparin suggest a circadian rhythm of the bio-availability of heparin in man. This fact should be taken into account for the use of 99 Tcsup(m)-heparin in the diagnosis of deep-vein thrombosis and for the safe adjustment of the heparin dosages in the treatment of severe thromboembolism. (author)
Effects of normal and extreme turbulence spectral parameters on wind turbine loads

DEFF Research Database (Denmark)

Dimitrov, Nikolay Krasimirov; Natarajan, Anand; Mann, Jakob

2017-01-01

the recommended values in the IEC 61400-1 Ed.3 that is used for wind turbine design. The present paper investigates the impact of Mann turbulence model parameter variations on the design loads envelope for 5 MW and 10 MW reference wind turbines. Specific focus is made on the blade root loads, tower top moments...... of design loads is investigated with a focus on the commonly used Mann turbulence model. Quantification of the Mann model parameters is made through wind measurements acquired from the Høvsøre site. The parameters of the Mann model fitted to site specific observations can differ significantly from...... and tower base loads under normal turbulence and extreme turbulence, whereby the change in operating extreme and fatigue design loads obtained through turbulence model parameter variations is compared with corresponding variations obtained from random seeds of turbulence. The investigations quantify...
Quantifying the performance of in vivo portal dosimetry in detecting four types of treatment parameter variations

International Nuclear Information System (INIS)

Bojechko, C.; Ford, E. C.

2015-01-01

Purpose: To quantify the ability of electronic portal imaging device (EPID) dosimetry used during treatment (in vivo) in detecting variations that can occur in the course of patient treatment. Methods: Images of transmitted radiation from in vivo EPID measurements were converted to a 2D planar dose at isocenter and compared to the treatment planning dose using a prototype software system. Using the treatment planning system (TPS), four different types of variability were modeled: overall dose scaling, shifting the positions of the multileaf collimator (MLC) leaves, shifting of the patient position, and changes in the patient body contour. The gamma pass rate was calculated for the modified and unmodified plans and used to construct a receiver operator characteristic (ROC) curve to assess the detectability of the different parameter variations. The detectability is given by the area under the ROC curve (AUC). The TPS was also used to calculate the impact of the variations on the target dose–volume histogram. Results: Nine intensity modulation radiation therapy plans were measured for four different anatomical sites consisting of 70 separate fields. Results show that in vivo EPID dosimetry was most sensitive to variations in the machine output, AUC = 0.70 − 0.94, changes in patient body habitus, AUC = 0.67 − 0.88, and systematic shifts in the MLC bank positions, AUC = 0.59 − 0.82. These deviations are expected to have a relatively small clinical impact [planning target volume (PTV) D 99 change <7%]. Larger variations have even higher detectability. Displacements in the patient’s position and random variations in MLC leaf positions were not readily detectable, AUC < 0.64. The D 99 of the PTV changed by up to 57% for the patient position shifts considered here. Conclusions: In vivo EPID dosimetry is able to detect relatively small variations in overall dose, systematic shifts of the MLC’s, and changes in the patient habitus. Shifts in the patient�
Quantifying the performance of in vivo portal dosimetry in detecting four types of treatment parameter variations

Energy Technology Data Exchange (ETDEWEB)

Bojechko, C.; Ford, E. C., E-mail: eford@uw.edu [Department of Radiation Oncology, University of Washington, 1959 NE Pacific Street, Seattle, Washington 98195 (United States)

2015-12-15

Purpose: To quantify the ability of electronic portal imaging device (EPID) dosimetry used during treatment (in vivo) in detecting variations that can occur in the course of patient treatment. Methods: Images of transmitted radiation from in vivo EPID measurements were converted to a 2D planar dose at isocenter and compared to the treatment planning dose using a prototype software system. Using the treatment planning system (TPS), four different types of variability were modeled: overall dose scaling, shifting the positions of the multileaf collimator (MLC) leaves, shifting of the patient position, and changes in the patient body contour. The gamma pass rate was calculated for the modified and unmodified plans and used to construct a receiver operator characteristic (ROC) curve to assess the detectability of the different parameter variations. The detectability is given by the area under the ROC curve (AUC). The TPS was also used to calculate the impact of the variations on the target dose–volume histogram. Results: Nine intensity modulation radiation therapy plans were measured for four different anatomical sites consisting of 70 separate fields. Results show that in vivo EPID dosimetry was most sensitive to variations in the machine output, AUC = 0.70 − 0.94, changes in patient body habitus, AUC = 0.67 − 0.88, and systematic shifts in the MLC bank positions, AUC = 0.59 − 0.82. These deviations are expected to have a relatively small clinical impact [planning target volume (PTV) D{sub 99} change <7%]. Larger variations have even higher detectability. Displacements in the patient’s position and random variations in MLC leaf positions were not readily detectable, AUC < 0.64. The D{sub 99} of the PTV changed by up to 57% for the patient position shifts considered here. Conclusions: In vivo EPID dosimetry is able to detect relatively small variations in overall dose, systematic shifts of the MLC’s, and changes in the patient habitus. Shifts in the
Optimization of Experimental Model Parameter Identification for Energy Storage Systems

Directory of Open Access Journals (Sweden)

Rosario Morello

2013-09-01

Full Text Available The smart grid approach is envisioned to take advantage of all available modern technologies in transforming the current power system to provide benefits to all stakeholders in the fields of efficient energy utilisation and of wide integration of renewable sources. Energy storage systems could help to solve some issues that stem from renewable energy usage in terms of stabilizing the intermittent energy production, power quality and power peak mitigation. With the integration of energy storage systems into the smart grids, their accurate modeling becomes a necessity, in order to gain robust real-time control on the network, in terms of stability and energy supply forecasting. In this framework, this paper proposes a procedure to identify the values of the battery model parameters in order to best fit experimental data and integrate it, along with models of energy sources and electrical loads, in a complete framework which represents a real time smart grid management system. The proposed method is based on a hybrid optimisation technique, which makes combined use of a stochastic and a deterministic algorithm, with low computational burden and can therefore be repeated over time in order to account for parameter variations due to the battery’s age and usage.
Modelling basin-wide variations in Amazon forest photosynthesis

Science.gov (United States)

Mercado, Lina; Lloyd, Jon; Domingues, Tomas; Fyllas, Nikolaos; Patino, Sandra; Dolman, Han; Sitch, Stephen

2010-05-01

Given the importance of Amazon rainforest in the global carbon and hydrological cycles, there is a need to use parameterized and validated ecosystem gas exchange and vegetation models for this region in order to adequately simulate present and future carbon and water balances. Recent research has found major differences in above-ground net primary productivity (ANPP), above ground biomass and tree dynamics across Amazonia. West Amazonia is more dynamic, with younger trees, higher stem growth rates and lower biomass than central and eastern Amazon (Baker et al. 2004; Malhi et al. 2004; Phillips et al. 2004). A factor of three variation in above-ground net primary productivity has been estimated across Amazonia by Malhi et al. (2004). Different hypotheses have been proposed to explain the observed spatial variability in ANPP (Malhi et al. 2004). First, due to the proximity to the Andes, sites from western Amazonia tend to have richer soils than central and eastern Amazon and therefore soil fertility could possibly be highly related to the high wood productivity found in western sites. Second, if GPP does not vary across the Amazon basin then different patterns of carbon allocation to respiration could also explain the observed ANPP gradient. However since plant growth depends on the interaction between photosynthesis, transport of assimilates, plant respiration, water relations and mineral nutrition, variations in plant gross photosynthesis (GPP) could also explain the observed variations in ANPP. In this study we investigate whether Amazon GPP can explain variations of observed ANPP. We use a sun and shade canopy gas exchange model that has been calibrated and evaluated at five rainforest sites (Mercado et al. 2009) to simulate gross primary productivity of 50 sites across the Amazon basin during the period 1980-2001. Such simulation differs from the ones performed with global vegetation models (Cox et al. 1998; Sitch et al. 2003) where i) single plant functional
Dynamic optimization of a biped model: Energetic walking gaits with different mechanical and gait parameters

Directory of Open Access Journals (Sweden)

Kang An

2015-05-01

Full Text Available Energy consumption is one of the problems for bipedal robots walking. For the purpose of studying the parameter effects on the design of energetic walking bipeds with strong adaptability, we use a dynamic optimization method on our new walking model to first investigate the effects of the mechanical parameters, including mass and length distribution, on the walking efficiency. Then, we study the energetic walking gait features with the combinations of walking speed and step length. Our walking model is designed upon Srinivasan’s model. Dynamic optimization is used for a free search with minimal constraints. The results show that the cost of transport of a certain gait increases with the increase in the mass and length distribution parameters, except for that the cost of transport decreases with big length distribution parameter and long step length. We can also find a corresponding range of walking speed and step length, in which the variation in one of the two parameters has no obvious effect on the cost of transport. With fixed mechanical parameters, the cost of transport increases with the increase in the walking speed. There is a speed–step length relationship for walking with minimal cost of transport. The hip torque output strategy is adjusted in two situations to meet the walking requirements.
GSTAR-SUR Modeling With Calendar Variations And Intervention To Forecast Outflow Of Currencies In Java Indonesia

Science.gov (United States)

Akbar, M. S.; Setiawan; Suhartono; Ruchjana, B. N.; Riyadi, M. A. A.

2018-03-01

Ordinary Least Squares (OLS) is general method to estimates Generalized Space Time Autoregressive (GSTAR) parameters. But in some cases, the residuals of GSTAR are correlated between location. If OLS is applied to this case, then the estimators are inefficient. Generalized Least Squares (GLS) is a method used in Seemingly Unrelated Regression (SUR) model. This method estimated parameters of some models with residuals between equations are correlated. Simulation study shows that GSTAR with GLS method for estimating parameters (GSTAR-SUR) is more efficient than GSTAR-OLS method. The purpose of this research is to apply GSTAR-SUR with calendar variation and intervention as exogenous variable (GSTARX-SUR) for forecast outflow of currency in Java, Indonesia. As a result, GSTARX-SUR provides better performance than GSTARX-OLS.
Nictemeral Variation of Physical Chemical and Biological Parameters of Ribeirão das Cruzes, Araraquara-SP

Directory of Open Access Journals (Sweden)

Vitor Rocha Santos

2015-12-01

Full Text Available Improper use of water, its degradation and irregular distribution can affect the quantity and quality needed for future generations, as well as create conflicts of interest between the industrial, urban and agricultural segments. In this context, it is of great importance the realization of studies on the quality of the hydric resources based on the analysis of temporal variation of limnological parameters. This study was conducted in the sub-basin of Ribeirão das Cruzes, which contributes to the water supply of the city of Araraquara (SP around 30% of all water captured and offered to the population. The objective of this research was to compare the water quality of river upstream and downstream of effluent discharge from a local treatment station in a 24 hour period (diurnal cycle variation. Data collection, comprising the period of one day, was done in order to observe the dynamics of operation and range of variation of the ecological processes in the studied system. The parameters analyzed showed significant variations in the sections of the upstream and downstream from the effluent discharge. With the nictemeral analysis it is evident the influence of effluents on the the waters of Ribeirão das Cruzes, especially during certain periods of the day.
Can Simple Soil Parameters Explain Field-Scale Variations in Glyphosate-, Bromoxyniloctanoate-, Diflufenican-, and Bentazone Mineralization?

DEFF Research Database (Denmark)

Norgaard, Trine; de Jonge, Lis Wollesen; Møldrup, Per

2015-01-01

The large spatial heterogeneity in soil physico-chemical and microbial parameters challenges our ability to predict and model pesticide leaching from agricultural land. Microbial mineralization of pesticides is an important process with respect to pesticide leaching since mineralization...... is the major process for the complete degradation of pesticides without generation of metabolites. The aim of our study was to determine field-scale variation in the potential for mineralization of the herbicides glyphosate, bromoxyniloctanoate, diflufenican, and bentazone and to investigate whether....... The mineralization potentials for glyphosate and bentazone were compared with 9-years leaching data from two horizontal wells 3.5 m below the field. The field-scale leaching patterns, however, could not be explained by the pesticide mineralization data. Instead, field-scale pesticide leaching may have been governed...
Automated parameter estimation for biological models using Bayesian statistical model checking.

Science.gov (United States)

Hussain, Faraz; Langmead, Christopher J; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram; Jha, Sumit K

2015-01-01

Probabilistic models have gained widespread acceptance in the systems biology community as a useful way to represent complex biological systems. Such models are developed using existing knowledge of the structure and dynamics of the system, experimental observations, and inferences drawn from statistical analysis of empirical data. A key bottleneck in building such models is that some system variables cannot be measured experimentally. These variables are incorporated into the model as numerical parameters. Determining values of these parameters that justify existing experiments and provide reliable predictions when model simulations are performed is a key research problem. Using an agent-based model of the dynamics of acute inflammation, we demonstrate a novel parameter estimation algorithm by discovering the amount and schedule of doses of bacterial lipopolysaccharide that guarantee a set of observed clinical outcomes with high probability. We synthesized values of twenty-eight unknown parameters such that the parameterized model instantiated with these parameter values satisfies four specifications describing the dynamic behavior of the model. We have developed a new algorithmic technique for discovering parameters in complex stochastic models of biological systems given behavioral specifications written in a formal mathematical logic. Our algorithm uses Bayesian model checking, sequential hypothesis testing, and stochastic optimization to automatically synthesize parameters of probabilistic biological models.
The influence of model parameters on catchment-response

International Nuclear Information System (INIS)

Shah, S.M.S.; Gabriel, H.F.; Khan, A.A.

2002-01-01

This paper deals with the study of influence of influence of conceptual rainfall-runoff model parameters on catchment response (runoff). A conceptual modified watershed yield model is employed to study the effects of model-parameters on catchment-response, i.e. runoff. The model is calibrated, using manual parameter-fitting approach, also known as trial and error parameter-fitting. In all, there are twenty one (21) parameters that control the functioning of the model. A lumped parametric approach is used. The detailed analysis was performed on Ling River near Kahuta, having catchment area of 56 sq. miles. The model includes physical parameters like GWSM, PETS, PGWRO, etc. fitting coefficients like CINF, CGWS, etc. and initial estimates of the surface-water and groundwater storages i.e. srosp and gwsp. Sensitivity analysis offers a good way, without repetititious computations, the proper weight and consideration that must be taken when each of the influencing factor is evaluated. Sensitivity-analysis was performed to evaluate the influence of model-parameters on runoff. The sensitivity and relative contributions of model parameters influencing catchment-response are studied. (author)
Study of gain variation as a function of physical parameters of GEM foil

CERN Document Server

Das, Supriya

2015-01-01

The ALICE experiment at LHC has planned to upgrade the TPC by replacing the MWPC with GEM based detecting elements to restrict the IBF to a tolerable value. However the variation of the gain as a function of physical parameters of industrially produced large size GEM foils is needed to be studied as a part of the QA procedure for the detector. The size of the electron avalanche and consequently the gain for GEM based detectors depend on the electric field distribution inside the holes. Geometry of a hole plays an important role in defining the electric field inside it. In this work we have studied the variation of the gain as a function of the hole diameters using Garfield++ simulation package.
Determination of remodeling parameters for a strain-adaptive finite element model of the distal ulna.

Science.gov (United States)

Neuert, Mark A C; Dunning, Cynthia E

2013-09-01

Strain energy-based adaptive material models are used to predict bone resorption resulting from stress shielding induced by prosthetic joint implants. Generally, such models are governed by two key parameters: a homeostatic strain-energy state (K) and a threshold deviation from this state required to initiate bone reformation (s). A refinement procedure has been performed to estimate these parameters in the femur and glenoid; this study investigates the specific influences of these parameters on resulting density distributions in the distal ulna. A finite element model of a human ulna was created using micro-computed tomography (µCT) data, initialized to a homogeneous density distribution, and subjected to approximate in vivo loading. Values for K and s were tested, and the resulting steady-state density distribution compared with values derived from µCT images. The sensitivity of these parameters to initial conditions was examined by altering the initial homogeneous density value. The refined model parameters selected were then applied to six additional human ulnae to determine their performance across individuals. Model accuracy using the refined parameters was found to be comparable with that found in previous studies of the glenoid and femur, and gross bone structures, such as the cortical shell and medullary canal, were reproduced. The model was found to be insensitive to initial conditions; however, a fair degree of variation was observed between the six specimens. This work represents an important contribution to the study of changes in load transfer in the distal ulna following the implementation of commercial orthopedic implants.
On parameter estimation in deformable models

DEFF Research Database (Denmark)

Fisker, Rune; Carstensen, Jens Michael

1998-01-01

Deformable templates have been intensively studied in image analysis through the last decade, but despite its significance the estimation of model parameters has received little attention. We present a method for supervised and unsupervised model parameter estimation using a general Bayesian form...
Determination of parameters of microstructural inhomogeneity of metal deformation by the method of modelling

International Nuclear Information System (INIS)

Kornienko, V.T.

1991-01-01

A method is suggested to estimate microstructural non-uniformity of deformation in metals by means of modelling. This method includes measurement of deformation in metals by small-dimensioned dividing grid cells as well as calculation of parameters by means of model representation of microdeformation distribution. It is shown that the method of modelling gives an opportunity to objectively estimate deformation non-uniformity in metals irrespective of the selected dimension of a dividing grid cells. New structural characteristics: base and wave of variations, reflecting a degree of dividing or uniting grains in metals according to the non-uniformity of deformation are introduced
Soil structure interaction model and variability of parameters in seismic analysis of nuclear island connected building

International Nuclear Information System (INIS)

Subramanian, K.V.; Palekar, S.M.; Bavare, M.S.; Mapari, H.A.; Patel, S.C.; Pillai, C.S.

2005-01-01

This paper provides salient features of the Soil Structure Interaction analysis of Nuclear Island Connected Building (NICB). The dynamic analysis of NICB is performed on a full 3D model accounting for the probable variation in the stiffness of the founding medium. A range analyses was performed to establish the effect of variability of subgrade parameters on the results of seismic analyses of NICB. This paper presents details of various analyses with respect to the subgrade model, uncertainties in subgrade properties, results of seismic analyses and a study of effect of the variability of parameters on the results of these analyses. The results of this study indicate that the variability of soil parameters beyond a certain value of shear wave velocity does not influence the response and in fact the response marginally diminishes. (authors)

Variational Dropout and the Local Reparameterization Trick

NARCIS (Netherlands)

Kingma, D.P.; Salimans, T.; Welling, M.; Cortes, C.; Lawrence, N.D.; Lee, D.D.; Sugiyama, M.; Garnett, R.

2015-01-01

We investigate a local reparameterizaton technique for greatly reducing the variance of stochastic gradients for variational Bayesian inference (SGVB) of a posterior over model parameters, while retaining parallelizability. This local reparameterization translates uncertainty about global parameters
Variation of 137Cs migration parameters in soils

International Nuclear Information System (INIS)

Silant'ev, A.N.; Shkuratova, I.G.

1988-01-01

Quasidiffusion model accounting the oriented migration is used to describe the observed profiles of 137 Cs distribution in soil. A way of model use in case of real soil, the quasidiffusion migration factor being varied, is suggested. It is shown that in the upper thin soil layer the quasidiffusion migration factor and oriented migration rate values are constant. With further increase of depth the quasidiffusion coefficient grows, the oriented migration rate is unchanged. On the basis of location data characteristic values of migration parameters for different soils of the USSR European territory depending on the soil texture, vegetative cover and moistening are determined
Parameter Estimation of Dynamic Multi-zone Models for Livestock Indoor Climate Control

DEFF Research Database (Denmark)

Wu, Zhuang; Stoustrup, Jakob; Heiselberg, Per

2008-01-01

, the livestock, the ventilation system and the building on the dynamic performance of indoor climate. Some significant parameters employed in the climate model as well as the airflow interaction between each conceptual zone are identified with the use of experimental time series data collected during spring......In this paper, a multi-zone modeling concept is proposed based on a simplified energy balance formulation to provide a better prediction of the indoor horizontal temperature variation inside the livestock building. The developed mathematical models reflect the influences from the weather...... and winter at a real scale livestock building in Denmark. The obtained comparative results between the measured data and the simulated output confirm that a very simple multi-zone model can capture the salient dynamical features of the climate dynamics which are needed for control purposes....
Parameter estimation of variable-parameter nonlinear Muskingum model using excel solver

Science.gov (United States)

Kang, Ling; Zhou, Liwei

2018-02-01

Abstract . The Muskingum model is an effective flood routing technology in hydrology and water resources Engineering. With the development of optimization technology, more and more variable-parameter Muskingum models were presented to improve effectiveness of the Muskingum model in recent decades. A variable-parameter nonlinear Muskingum model (NVPNLMM) was proposed in this paper. According to the results of two real and frequently-used case studies by various models, the NVPNLMM could obtain better values of evaluation criteria, which are used to describe the superiority of the estimated outflows and compare the accuracies of flood routing using various models, and the optimal estimated outflows by the NVPNLMM were closer to the observed outflows than the ones by other models.
Diffusion tensor imaging of the human calf : Variation of inter- and intramuscle-specific diffusion parameters

NARCIS (Netherlands)

Schlaffke, Lara; Rehmann, Robert; Froeling, Martijn; Kley, Rudolf; Tegenthoff, Martin; Vorgerd, Matthias; Schmidt-Wilcke, Tobias

2017-01-01

Purpose: To investigate to what extent inter- and intramuscular variations of diffusion parameters of human calf muscles can be explained by age, gender, muscle location, and body mass index (BMI) in a specific age group (20-35 years). Materials and Methods: Whole calf muscles of 18 healthy
Impact of seasonal variation, age and smoking status on human semen parameters: The Massachusetts General Hospital experience

Science.gov (United States)

Chen, Zuying; Godfrey-Bailey, Linda; Schiff, Isaac; Hauser, Russ

2004-01-01

Background To investigate the relationship of human semen parameters with season, age and smoking status. Methods The present study used data from subjects recruited into an ongoing cross-sectional study on the relationship between environmental agents and semen characteristics. Our population consisted of 306 patients who presented to the Vincent Memorial Andrology Laboratory of Massachusetts General Hospital for semen evaluation. Sperm concentration and motility were measured with computer aided sperm analysis (CASA). Sperm morphology was scored using Tygerberg Kruger strict criteria. Regression analyses were used to investigate the relationships between semen parameters and season, age and smoking status, adjusting for abstinence interval. Results Sperm concentration in the spring was significantly higher than in winter, fall and summer (p seasons. There were no statistically significant relationships between semen parameters and smoking status, though current smokers tended to have lower sperm concentration. We also did not find a statistically significant relationship between age and semen parameters. Conclusions We found seasonal variations in sperm concentration and suggestive evidence of seasonal variation in sperm motility and percent sperm with normal morphology. Although smoking status was not a significant predictor of semen parameters, this may have been due to the small number of current smokers in the study. PMID:15507127
Different atmospheric parameters influence on spectral UV radiation (measurements and modelling)

Energy Technology Data Exchange (ETDEWEB)

Chubarova, N Y [Moscow State Univ. (Russian Federation). Meteorological Observatory; Krotkov, N A [Maryland Univ., MD (United States). JCESS/Meteorology Dept.; Geogdzhaev, I V; Bushnev, S V; Kondranin, T V [SUMGF/MIPT, Dolgoprudny (Russian Federation); Khattatov, V U [Central Aerological Observatory, Dolgoprudny (Russian Federation)

1996-12-31

The ultraviolet (UV) radiation plays a vital role in the biophysical processes despite its small portion in the total solar flux. UV radiation is subject to large variations at the Earth surface depending greatly on solar elevation, ozone and cloud amount, aerosols and surface albedo. The analysis of atmospheric parameters influence is based on the spectral archive data of three spectral instruments: NSF spectroradiometer (Barrow network) (NSF Polar Programs UV Spectroradiometer Network 1991-1992,1992), spectrophotometer (SUVS-M) of Central Aerological Observatory CAO, spectroradiometer of Meteorological Observatory of the Moscow State University (MO MSU) and model simulations based on delta-Eddington approximation
Different atmospheric parameters influence on spectral UV radiation (measurements and modelling)

Energy Technology Data Exchange (ETDEWEB)

Chubarova, N.Y. [Moscow State Univ. (Russian Federation). Meteorological Observatory; Krotkov, N.A. [Maryland Univ., MD (United States). JCESS/Meteorology Dept.; Geogdzhaev, I.V.; Bushnev, S.V.; Kondranin, T.V. [SUMGF/MIPT, Dolgoprudny (Russian Federation); Khattatov, V.U. [Central Aerological Observatory, Dolgoprudny (Russian Federation)

1995-12-31

The ultraviolet (UV) radiation plays a vital role in the biophysical processes despite its small portion in the total solar flux. UV radiation is subject to large variations at the Earth surface depending greatly on solar elevation, ozone and cloud amount, aerosols and surface albedo. The analysis of atmospheric parameters influence is based on the spectral archive data of three spectral instruments: NSF spectroradiometer (Barrow network) (NSF Polar Programs UV Spectroradiometer Network 1991-1992,1992), spectrophotometer (SUVS-M) of Central Aerological Observatory CAO, spectroradiometer of Meteorological Observatory of the Moscow State University (MO MSU) and model simulations based on delta-Eddington approximation
Short-Term Solar Irradiance Forecasting Model Based on Artificial Neural Network Using Statistical Feature Parameters

Directory of Open Access Journals (Sweden)

Hongshan Zhao

2012-05-01

Full Text Available Short-term solar irradiance forecasting (STSIF is of great significance for the optimal operation and power predication of grid-connected photovoltaic (PV plants. However, STSIF is very complex to handle due to the random and nonlinear characteristics of solar irradiance under changeable weather conditions. Artificial Neural Network (ANN is suitable for STSIF modeling and many research works on this topic are presented, but the conciseness and robustness of the existing models still need to be improved. After discussing the relation between weather variations and irradiance, the characteristics of the statistical feature parameters of irradiance under different weather conditions are figured out. A novel ANN model using statistical feature parameters (ANN-SFP for STSIF is proposed in this paper. The input vector is reconstructed with several statistical feature parameters of irradiance and ambient temperature. Thus sufficient information can be effectively extracted from relatively few inputs and the model complexity is reduced. The model structure is determined by cross-validation (CV, and the Levenberg-Marquardt algorithm (LMA is used for the network training. Simulations are carried out to validate and compare the proposed model with the conventional ANN model using historical data series (ANN-HDS, and the results indicated that the forecast accuracy is obviously improved under variable weather conditions.
VARIATIONS IN ELECTROPHYSICAL PARAMETERS ESTIMATED FROM ELECTROMAGNETIC MONITORING DATA AS AN INDICATOR OF FAULT ACTIVITY

Directory of Open Access Journals (Sweden)

A. E. Shalaginov

2018-01-01

Full Text Available In the regions of high seismic activity, investigations of fault zones are of paramount importance as such zones can generate seismicity. A top task in the regional studies is determining the rates of activity from the data obtained by geoelectrical methods, especially considering the data on the faults covered by sediments. From a practical standpoint, the results of these studies are important for seismic zoning and forecasting of natural and anthropogenic geodynamic phenomena that may potentially occur in the populated areas and zones allocated for construction of industrial and civil objects, pipelines, roads, bridges, etc. Seismic activity in Gorny Altai is regularly monitored after the destructive 2003 Chuya earthquake (M=7.3 by the non-stationary electromagnetic sounding with galvanic and inductive sources of three modifications. From the long-term measurements that started in 2007 and continue in the present, electrical resistivity and electrical anisotropy are determined. Our study aimed to estimate the variations of these electrophysical parameters in the zone influenced by the fault, consider the intensity of the variations in comparison with seismicity indicators, and attempt at determining the degree of activity of the faults. Based on the results of our research, we propose a technique for measuring and interpreting the data sets obtained by a complex of non-stationary sounding modifications. The technique ensures a more precise evaluation of the electrophysical parameters. It is concluded that the electric anisotropy coefficient can be effectively used to characterize the current seismicity, and its maximum variations, being observed in the zone influenced by the fault, are characteristic of the fault activity. The use of two electrophysical parameters enhances the informativeness of the study.
Universally sloppy parameter sensitivities in systems biology models.

Directory of Open Access Journals (Sweden)

Ryan N Gutenkunst

2007-10-01

Full Text Available Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.
Universally sloppy parameter sensitivities in systems biology models.

Science.gov (United States)

Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P

2007-10-01

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.
Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models.

Directory of Open Access Journals (Sweden)

Jonathan R Karr

2015-05-01

Full Text Available Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.
Multi-subject atlas-based auto-segmentation reduces interobserver variation and improves dosimetric parameter consistency for organs at risk in nasopharyngeal carcinoma: A multi-institution clinical study

International Nuclear Information System (INIS)

Tao, Chang-Juan; Yi, Jun-Lin; Chen, Nian-Yong; Ren, Wei; Cheng, Jason; Tung, Stewart; Kong, Lin; Lin, Shao-Jun; Pan, Jian-Ji; Zhang, Guang-Shun; Hu, Jiang; Qi, Zhen-Yu; Ma, Jun; Lu, Jia-De; Yan, Di; Sun, Ying

2015-01-01

Background and purpose: To assess whether consensus guideline-based atlas-based auto-segmentation (ABAS) reduces interobserver variation and improves dosimetric parameter consistency for organs at risk (OARs) in nasopharyngeal carcinoma (NPC). Materials and methods: Eight radiation oncologists from 8 institutes contoured 20 OARs on planning CT images of 16 patients via manual contouring and manually-edited ABAS contouring. Interobserver variation [volume coefficient of variation (CV), Dice similarity coefficient (DSC), three-dimensional isocenter difference (3D-ICD)] and dosimetric parameters were compared between the two methods of contouring for each OAR. Results: Interobserver variation was significant for all OARs in manual contouring, resulting in significant dosimetric parameter variation (P < 0.05). Edited ABAS significantly improved multiple metrics and reduced dosimetric parameter variation for most OARs; brainstem, spinal cord, cochleae, temporomandibular joint (TMJ), larynx and pharyngeal constrictor muscle (PCM) obtained most benefit (range of mean DSC, volume CV and main ICD values was 0.36–0.83, 12.1–84.3%, 2.2–5.0 mm for manual contouring and 0.42–0.86, 7.2–70.6%, 1.2–3.5 mm for edited ABAS contouring, respectively; range of dose CV reduction: 1.0–3.0%). Conclusion: Substantial objective interobserver differences occur during manual contouring, resulting in significant dosimetric parameter variation. Edited ABAS reduced interobserver variation and improved dosimetric parameter consistency, particularly for brainstem, spinal cord, cochleae, TMJ, larynx and PCM
Systematic parameter inference in stochastic mesoscopic modeling

Energy Technology Data Exchange (ETDEWEB)

Lei, Huan; Yang, Xiu [Pacific Northwest National Laboratory, Richland, WA 99352 (United States); Li, Zhen [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States); Karniadakis, George Em, E-mail: george_karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States)

2017-02-01

We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are “sparse”. The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space. Fully access to the response surfaces within the confidence range enables us to infer the optimal force parameters given the desirable values of target properties at the macroscopic scale. Moreover, it enables us to investigate the intrinsic relationship between the model parameters, identify possible degeneracies in the parameter space, and optimize the model by eliminating model redundancies. The proposed method provides an efficient alternative approach for constructing mesoscopic models by inferring model parameters to recover target properties of the physics systems (e.g., from experimental measurements), where those force field parameters and formulation cannot be derived from the microscopic level in a straight forward way.
Assessing FPAR Source and Parameter Optimization Scheme in Application of a Diagnostic Carbon Flux Model

Energy Technology Data Exchange (ETDEWEB)

Turner, D P; Ritts, W D; Wharton, S; Thomas, C; Monson, R; Black, T A

2009-02-26

The combination of satellite remote sensing and carbon cycle models provides an opportunity for regional to global scale monitoring of terrestrial gross primary production, ecosystem respiration, and net ecosystem production. FPAR (the fraction of photosynthetically active radiation absorbed by the plant canopy) is a critical input to diagnostic models, however little is known about the relative effectiveness of FPAR products from different satellite sensors nor about the sensitivity of flux estimates to different parameterization approaches. In this study, we used multiyear observations of carbon flux at four eddy covariance flux tower sites within the conifer biome to evaluate these factors. FPAR products from the MODIS and SeaWiFS sensors, and the effects of single site vs. cross-site parameter optimization were tested with the CFLUX model. The SeaWiFs FPAR product showed greater dynamic range across sites and resulted in slightly reduced flux estimation errors relative to the MODIS product when using cross-site optimization. With site-specific parameter optimization, the flux model was effective in capturing seasonal and interannual variation in the carbon fluxes at these sites. The cross-site prediction errors were lower when using parameters from a cross-site optimization compared to parameter sets from optimization at single sites. These results support the practice of multisite optimization within a biome for parameterization of diagnostic carbon flux models.
Variational multiscale models for charge transport.

Science.gov (United States)

Wei, Guo-Wei; Zheng, Qiong; Chen, Zhan; Xia, Kelin

2012-01-01

This work presents a few variational multiscale models for charge transport in complex physical, chemical and biological systems and engineering devices, such as fuel cells, solar cells, battery cells, nanofluidics, transistors and ion channels. An essential ingredient of the present models, introduced in an earlier paper (Bulletin of Mathematical Biology, 72, 1562-1622, 2010), is the use of differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain from the microscopic domain, meanwhile, dynamically couple discrete and continuum descriptions. Our main strategy is to construct the total energy functional of a charge transport system to encompass the polar and nonpolar free energies of solvation, and chemical potential related energy. By using the Euler-Lagrange variation, coupled Laplace-Beltrami and Poisson-Nernst-Planck (LB-PNP) equations are derived. The solution of the LB-PNP equations leads to the minimization of the total free energy, and explicit profiles of electrostatic potential and densities of charge species. To further reduce the computational complexity, the Boltzmann distribution obtained from the Poisson-Boltzmann (PB) equation is utilized to represent the densities of certain charge species so as to avoid the computationally expensive solution of some Nernst-Planck (NP) equations. Consequently, the coupled Laplace-Beltrami and Poisson-Boltzmann-Nernst-Planck (LB-PBNP) equations are proposed for charge transport in heterogeneous systems. A major emphasis of the present formulation is the consistency between equilibrium LB-PB theory and non-equilibrium LB-PNP theory at equilibrium. Another major emphasis is the capability of the reduced LB-PBNP model to fully recover the prediction of the LB-PNP model at non-equilibrium settings. To account for the fluid impact on the charge transport, we derive coupled Laplace-Beltrami, Poisson-Nernst-Planck and Navier-Stokes equations from the variational principle
Variational multiscale models for charge transport

Science.gov (United States)

Wei, Guo-Wei; Zheng, Qiong; Chen, Zhan; Xia, Kelin

2012-01-01

This work presents a few variational multiscale models for charge transport in complex physical, chemical and biological systems and engineering devices, such as fuel cells, solar cells, battery cells, nanofluidics, transistors and ion channels. An essential ingredient of the present models, introduced in an earlier paper (Bulletin of Mathematical Biology, 72, 1562-1622, 2010), is the use of differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain from the microscopic domain, meanwhile, dynamically couple discrete and continuum descriptions. Our main strategy is to construct the total energy functional of a charge transport system to encompass the polar and nonpolar free energies of solvation, and chemical potential related energy. By using the Euler-Lagrange variation, coupled Laplace-Beltrami and Poisson-Nernst-Planck (LB-PNP) equations are derived. The solution of the LB-PNP equations leads to the minimization of the total free energy, and explicit profiles of electrostatic potential and densities of charge species. To further reduce the computational complexity, the Boltzmann distribution obtained from the Poisson-Boltzmann (PB) equation is utilized to represent the densities of certain charge species so as to avoid the computationally expensive solution of some Nernst-Planck (NP) equations. Consequently, the coupled Laplace-Beltrami and Poisson-Boltzmann-Nernst-Planck (LB-PBNP) equations are proposed for charge transport in heterogeneous systems. A major emphasis of the present formulation is the consistency between equilibrium LB-PB theory and non-equilibrium LB-PNP theory at equilibrium. Another major emphasis is the capability of the reduced LB-PBNP model to fully recover the prediction of the LB-PNP model at non-equilibrium settings. To account for the fluid impact on the charge transport, we derive coupled Laplace-Beltrami, Poisson-Nernst-Planck and Navier-Stokes equations from the variational principle
4D RECONSTRUCTIONS FROM LOW-COUNT SPECT DATA USING DEFORMABLE MODELS WITH SMOOTH INTERIOR INTENSITY VARIATIONS

International Nuclear Information System (INIS)

Cunningham, G. S.; Lehovich, A.

2000-01-01

The Bayes Inference Engine (BIE) has been used to perform a 4D reconstruction of a first-pass radiotracer bolus distribution inside a CardioWest Total Artificial Heart, imaged with the University of Arizona's FastSPECT system. The BIE estimates parameter values that define the 3D model of the radiotracer distribution at each of 41 times spanning about two seconds. The 3D models have two components: a closed surface, composed of hi-quadratic Bezier triangular surface patches, that defines the interface between the part of the blood pool that contains radiotracer and the part that contains no radiotracer, and smooth voxel-to-voxel variations in intensity within the closed surface. Ideally, the surface estimates the ventricular wall location where the bolus is infused throughout the part of the blood pool contained by the right ventricle. The voxel-to-voxel variations are needed to model an inhomogeneously-mixed bolus. Maximum a posterior (MAP) estimates of the Bezier control points and voxel values are obtained for each time frame. We show new reconstructions using the Bezier surface models, and discuss estimates of ventricular volume as a function of time, ejection fraction, and wall motion. The computation time for our reconstruction process, which directly estimates complex 3D model parameters from the raw data, is performed in a time that is competitive with more traditional voxel-based methods (ML-EM, e.g.)
Test models for improving filtering with model errors through stochastic parameter estimation

International Nuclear Information System (INIS)

Gershgorin, B.; Harlim, J.; Majda, A.J.

2010-01-01

The filtering skill for turbulent signals from nature is often limited by model errors created by utilizing an imperfect model for filtering. Updating the parameters in the imperfect model through stochastic parameter estimation is one way to increase filtering skill and model performance. Here a suite of stringent test models for filtering with stochastic parameter estimation is developed based on the Stochastic Parameterization Extended Kalman Filter (SPEKF). These new SPEKF-algorithms systematically correct both multiplicative and additive biases and involve exact formulas for propagating the mean and covariance including the parameters in the test model. A comprehensive study is presented of robust parameter regimes for increasing filtering skill through stochastic parameter estimation for turbulent signals as the observation time and observation noise are varied and even when the forcing is incorrectly specified. The results here provide useful guidelines for filtering turbulent signals in more complex systems with significant model errors.

Estimation and upscaling of dual-permeability model parameters for the transport of E.coli D21g in soils with preferential flow

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Dual-permeability models are increasingly used to quantify the transport of solutes and microorganisms in soils with preferential flow. An ability to accurately determine the model parameters and their variation with preferential pathway characteristics is crucial for predicting the transport of mi...
Comparing models of the periodic variations in spin-down and beamwidth for PSR B1828-11

Science.gov (United States)

Ashton, G.; Jones, D. I.; Prix, R.

2016-05-01

We build a framework using tools from Bayesian data analysis to evaluate models explaining the periodic variations in spin-down and beamwidth of PSR B1828-11. The available data consist of the time-averaged spin-down rate, which displays a distinctive double-peaked modulation, and measurements of the beamwidth. Two concepts exist in the literature that are capable of explaining these variations; we formulate predictive models from these and quantitatively compare them. The first concept is phenomenological and stipulates that the magnetosphere undergoes periodic switching between two metastable states as first suggested by Lyne et al. The second concept, precession, was first considered as a candidate for the modulation of B1828-11 by Stairs et al. We quantitatively compare models built from these concepts using a Bayesian odds ratio. Because the phenomenological switching model itself was informed by these data in the first place, it is difficult to specify appropriate parameter-space priors that can be trusted for an unbiased model comparison. Therefore, we first perform a parameter estimation using the spin-down data, and then use the resulting posterior distributions as priors for model comparison on the beamwidth data. We find that a precession model with a simple circular Gaussian beam geometry fails to appropriately describe the data, while allowing for a more general beam geometry provides a good fit to the data. The resulting odds between the precession model (with a general beam geometry) and the switching model are estimated as 102.7±0.5 in favour of the precession model.
Coupled variations of fundamental couplings and primordial nucleosynthesis

International Nuclear Information System (INIS)

Coc, Alain; Nunes, Nelson J.; Olive, Keith A.; Uzan, Jean-Philippe; Vangioni, Elisabeth

2006-10-01

The effect of variations of the fundamental nuclear parameters on big-bang nucleosynthesis are modeled and discussed in detail taking into account the interrelations between the fundamental parameters arising in unified theories. Considering only 4 He, strong constraints on the variation of the neutron lifetime, neutron-proton mass difference are set. These constraints are then translated into constraints on the time variation of the Yukawa couplings and the fine structure constant. Furthermore, we show that a variation of the deuterium binding energy is able to reconcile the 7 Li abundance deduced from the WMAP analysis with its spectroscopically determined value while maintaining concordance with D and 4 He. (authors)
Size and shape dependent lattice parameters of metallic nanoparticles

International Nuclear Information System (INIS)

Qi, W. H.; Wang, M. P.

2005-01-01

A model is developed to account for the size and shape dependent lattice parameters of metallic nanoparticles, where the particle shape difference is considered by introducing a shape factor. It is predicted that the lattice parameters of nanoparticles in several nanometers decrease with decreasing of the particle size, which is consistent with the corresponding experimental results. Furthermore, it is found that the particle shape can lead to 10% of the total lattice variation. The model is a continuous media model and can deal with the nanoparticles larger than 1 nm. Since the shape factor approaches to infinity for nanowires and nanofilms, therefore, the model cannot be generalized to the systems of nanowires and nanofilms. For the input parameters are physical constants of bulk materials, therefore, the present model may be used to predict the lattice variation of different metallic nanoparticles with different lattice structures
Local overfishing may be avoided by examining parameters of a spatio-temporal model.

Science.gov (United States)

Carson, Stuart; Shackell, Nancy; Mills Flemming, Joanna

2017-01-01

Spatial erosion of stock structure through local overfishing can lead to stock collapse because fish often prefer certain locations, and fisheries tend to focus on those locations. Fishery managers are challenged to maintain the integrity of the entire stock and require scientific approaches that provide them with sound advice. Here we propose a Bayesian hierarchical spatio-temporal modelling framework for fish abundance data to estimate key parameters that define spatial stock structure: persistence (similarity of spatial structure over time), connectivity (coherence of temporal pattern over space), and spatial variance (variation across the seascape). The consideration of these spatial parameters in the stock assessment process can help identify the erosion of structure and assist in preventing local overfishing. We use Atlantic cod (Gadus morhua) in eastern Canada as a case study an examine the behaviour of these parameters from the height of the fishery through its collapse. We identify clear signals in parameter behaviour under circumstances of destructive stock erosion as well as for recovery of spatial structure even when combined with a non-recovery in abundance. Further, our model reveals the spatial pattern of areas of high and low density persists over the 41 years of available data and identifies the remnant patches. Models of this sort are crucial to recovery plans if we are to identify and protect remaining sources of recolonization for Atlantic cod. Our method is immediately applicable to other exploited species.
Local overfishing may be avoided by examining parameters of a spatio-temporal model.

Directory of Open Access Journals (Sweden)

Stuart Carson

Full Text Available Spatial erosion of stock structure through local overfishing can lead to stock collapse because fish often prefer certain locations, and fisheries tend to focus on those locations. Fishery managers are challenged to maintain the integrity of the entire stock and require scientific approaches that provide them with sound advice. Here we propose a Bayesian hierarchical spatio-temporal modelling framework for fish abundance data to estimate key parameters that define spatial stock structure: persistence (similarity of spatial structure over time, connectivity (coherence of temporal pattern over space, and spatial variance (variation across the seascape. The consideration of these spatial parameters in the stock assessment process can help identify the erosion of structure and assist in preventing local overfishing. We use Atlantic cod (Gadus morhua in eastern Canada as a case study an examine the behaviour of these parameters from the height of the fishery through its collapse. We identify clear signals in parameter behaviour under circumstances of destructive stock erosion as well as for recovery of spatial structure even when combined with a non-recovery in abundance. Further, our model reveals the spatial pattern of areas of high and low density persists over the 41 years of available data and identifies the remnant patches. Models of this sort are crucial to recovery plans if we are to identify and protect remaining sources of recolonization for Atlantic cod. Our method is immediately applicable to other exploited species.
Exploiting intrinsic fluctuations to identify model parameters.

Science.gov (United States)

Zimmer, Christoph; Sahle, Sven; Pahle, Jürgen

2015-04-01

Parameterisation of kinetic models plays a central role in computational systems biology. Besides the lack of experimental data of high enough quality, some of the biggest challenges here are identification issues. Model parameters can be structurally non-identifiable because of functional relationships. Noise in measured data is usually considered to be a nuisance for parameter estimation. However, it turns out that intrinsic fluctuations in particle numbers can make parameters identifiable that were previously non-identifiable. The authors present a method to identify model parameters that are structurally non-identifiable in a deterministic framework. The method takes time course recordings of biochemical systems in steady state or transient state as input. Often a functional relationship between parameters presents itself by a one-dimensional manifold in parameter space containing parameter sets of optimal goodness. Although the system's behaviour cannot be distinguished on this manifold in a deterministic framework it might be distinguishable in a stochastic modelling framework. Their method exploits this by using an objective function that includes a measure for fluctuations in particle numbers. They show on three example models, immigration-death, gene expression and Epo-EpoReceptor interaction, that this resolves the non-identifiability even in the case of measurement noise with known amplitude. The method is applied to partially observed recordings of biochemical systems with measurement noise. It is simple to implement and it is usually very fast to compute. This optimisation can be realised in a classical or Bayesian fashion.
Inter-fraction variations in respiratory motion models

Energy Technology Data Exchange (ETDEWEB)

McClelland, J R; Modat, M; Ourselin, S; Hawkes, D J [Centre for Medical Image Computing, University College London (United Kingdom); Hughes, S; Qureshi, A; Ahmad, S; Landau, D B, E-mail: j.mcclelland@cs.ucl.ac.uk [Department of Oncology, Guy' s and St Thomas' s Hospitals NHS Trust, London (United Kingdom)

2011-01-07

Respiratory motion can vary dramatically between the planning stage and the different fractions of radiotherapy treatment. Motion predictions used when constructing the radiotherapy plan may be unsuitable for later fractions of treatment. This paper presents a methodology for constructing patient-specific respiratory motion models and uses these models to evaluate and analyse the inter-fraction variations in the respiratory motion. The internal respiratory motion is determined from the deformable registration of Cine CT data and related to a respiratory surrogate signal derived from 3D skin surface data. Three different models for relating the internal motion to the surrogate signal have been investigated in this work. Data were acquired from six lung cancer patients. Two full datasets were acquired for each patient, one before the course of radiotherapy treatment and one at the end (approximately 6 weeks later). Separate models were built for each dataset. All models could accurately predict the respiratory motion in the same dataset, but had large errors when predicting the motion in the other dataset. Analysis of the inter-fraction variations revealed that most variations were spatially varying base-line shifts, but changes to the anatomy and the motion trajectories were also observed.
Estimating model parameters for an impact-produced shock-wave simulation: Optimal use of partial data with the extended Kalman filter

International Nuclear Information System (INIS)

Kao, Jim; Flicker, Dawn; Ide, Kayo; Ghil, Michael

2006-01-01

This paper builds upon our recent data assimilation work with the extended Kalman filter (EKF) method [J. Kao, D. Flicker, R. Henninger, S. Frey, M. Ghil, K. Ide, Data assimilation with an extended Kalman filter for an impact-produced shock-wave study, J. Comp. Phys. 196 (2004) 705-723.]. The purpose is to test the capability of EKF in optimizing a model's physical parameters. The problem is to simulate the evolution of a shock produced through a high-speed flyer plate. In the earlier work, we have showed that the EKF allows one to estimate the evolving state of the shock wave from a single pressure measurement, assuming that all model parameters are known. In the present paper, we show that imperfectly known model parameters can also be estimated accordingly, along with the evolving model state, from the same single measurement. The model parameter optimization using the EKF can be achieved through a simple modification of the original EKF formalism by including the model parameters into an augmented state variable vector. While the regular state variables are governed by both deterministic and stochastic forcing mechanisms, the parameters are only subject to the latter. The optimally estimated model parameters are thus obtained through a unified assimilation operation. We show that improving the accuracy of the model parameters also improves the state estimate. The time variation of the optimized model parameters results from blending the data and the corresponding values generated from the model and lies within a small range, of less than 2%, from the parameter values of the original model. The solution computed with the optimized parameters performs considerably better and has a smaller total variance than its counterpart using the original time-constant parameters. These results indicate that the model parameters play a dominant role in the performance of the shock-wave hydrodynamic code at hand
Application of physiological parameters of a sample of the Brazilian population in different levels of exercise, on the deposition model of the ICRP Publication 66

International Nuclear Information System (INIS)

Reis, Arlene A. dos; Cardoso, Joaquim C.S.; Lourenco, Maria C.

2005-01-01

The Human Respiratory Tract Model (HRTM) proposed by the ICRP Publication 66 accounts for the morphology and physiology of the respiratory tract. The characteristics of air drawn into the lungs and exhaled are greatly influenced by the morphology of the respiratory tract, which causes numerous changes in pressure, flow rate, direction and humidity as air moves into and out of the lungs. The model uses morphological and physiological parameters from the Caucasian man to establish deposition fractions in the respiratory tract regions. The ICRP recommends, for a reliable evaluation of the regional deposition, the use of parameters from a local population when information is available. The main purpose of this study is to verify the influence in using the morphology and physiology parameters representative of a sample of the Brazilian population, in different levels of exercise, on the deposition model of the ICRP Publication 66. The deposition model was implemented using software Excel for Windows (version 2000). The results suggest a significant variation in fractional deposition when Brazilian parameters are applied in the model. The variations are not the same for all regions of the respiratory tract and depend on levels of exercise. (author)
Diffusion tensor imaging of the human calf: Variation of inter- and intramuscle-specific diffusion parameters.

Science.gov (United States)

Schlaffke, Lara; Rehmann, Robert; Froeling, Martijn; Kley, Rudolf; Tegenthoff, Martin; Vorgerd, Matthias; Schmidt-Wilcke, Tobias

2017-10-01

To investigate to what extent inter- and intramuscular variations of diffusion parameters of human calf muscles can be explained by age, gender, muscle location, and body mass index (BMI) in a specific age group (20-35 years). Whole calf muscles of 18 healthy volunteers were evaluated. Magnetic resonance imaging (MRI) was performed using a 3T scanner and a 16-channel Torso XL coil. Diffusion-weighted images were acquired to perform fiber tractography and diffusion tensor imaging (DTI) analysis for each muscle of both legs. Fiber tractography was used to separate seven lower leg muscles. Associations between DTI parameters and confounds were evaluated. All muscles were additionally separated in seven identical segments along the z-axis to evaluate intramuscular differences in diffusion parameters. Fractional anisotropy (FA) and mean diffusivity (MD) were obtained for each muscle with low standard deviations (SDs) (SD FA : 0.01-0.02; SD MD : 0.07-0.14(10 -3 )). We found significant differences in FA values of the tibialis anterior muscle (AT) and extensor digitorum longus (EDL) muscles between men and women for whole muscle FA (two-sample t-tests; AT: P = 0.0014; EDL: P = 0.0004). We showed significant intramuscular differences in diffusion parameters between adjacent segments in most calf muscles (P < 0.001). Whereas muscle insertions showed higher (SD 0.03-0.06) than muscle bellies (SD 0.01-0.03), no relationships between FA or MD with age or BMI were found. Inter- and intramuscular variations in diffusion parameters of the calf were shown, which are not related to age or BMI in this age group. Differences between muscle belly and insertion should be considered when interpreting datasets not including whole muscles. 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1137-1148. © 2017 International Society for Magnetic Resonance in Medicine.
Incorporating model parameter uncertainty into inverse treatment planning

International Nuclear Information System (INIS)

Lian Jun; Xing Lei

2004-01-01

Radiobiological treatment planning depends not only on the accuracy of the models describing the dose-response relation of different tumors and normal tissues but also on the accuracy of tissue specific radiobiological parameters in these models. Whereas the general formalism remains the same, different sets of model parameters lead to different solutions and thus critically determine the final plan. Here we describe an inverse planning formalism with inclusion of model parameter uncertainties. This is made possible by using a statistical analysis-based frameset developed by our group. In this formalism, the uncertainties of model parameters, such as the parameter a that describes tissue-specific effect in the equivalent uniform dose (EUD) model, are expressed by probability density function and are included in the dose optimization process. We found that the final solution strongly depends on distribution functions of the model parameters. Considering that currently available models for computing biological effects of radiation are simplistic, and the clinical data used to derive the models are sparse and of questionable quality, the proposed technique provides us with an effective tool to minimize the effect caused by the uncertainties in a statistical sense. With the incorporation of the uncertainties, the technique has potential for us to maximally utilize the available radiobiology knowledge for better IMRT treatment
Parameter selection in limited data cone-beam CT reconstruction using edge-preserving total variation algorithms

Science.gov (United States)

Lohvithee, Manasavee; Biguri, Ander; Soleimani, Manuchehr

2017-12-01

There are a number of powerful total variation (TV) regularization methods that have great promise in limited data cone-beam CT reconstruction with an enhancement of image quality. These promising TV methods require careful selection of the image reconstruction parameters, for which there are no well-established criteria. This paper presents a comprehensive evaluation of parameter selection in a number of major TV-based reconstruction algorithms. An appropriate way of selecting the values for each individual parameter has been suggested. Finally, a new adaptive-weighted projection-controlled steepest descent (AwPCSD) algorithm is presented, which implements the edge-preserving function for CBCT reconstruction with limited data. The proposed algorithm shows significant robustness compared to three other existing algorithms: ASD-POCS, AwASD-POCS and PCSD. The proposed AwPCSD algorithm is able to preserve the edges of the reconstructed images better with fewer sensitive parameters to tune.
Model-based diagnosis of large diesel engines based on angular speed variations of the crankshaft

Science.gov (United States)

Desbazeille, M.; Randall, R. B.; Guillet, F.; El Badaoui, M.; Hoisnard, C.

2010-07-01

This work aims at monitoring large diesel engines by analyzing the crankshaft angular speed variations. It focuses on a powerful 20-cylinder diesel engine with crankshaft natural frequencies within the operating speed range. First, the angular speed variations are modeled at the crankshaft free end. This includes modeling both the crankshaft dynamical behavior and the excitation torques. As the engine is very large, the first crankshaft torsional modes are in the low frequency range. A model with the assumption of a flexible crankshaft is required. The excitation torques depend on the in-cylinder pressure curve. The latter is modeled with a phenomenological model. Mechanical and combustion parameters of the model are optimized with the help of actual data. Then, an automated diagnosis based on an artificially intelligent system is proposed. Neural networks are used for pattern recognition of the angular speed waveforms in normal and faulty conditions. Reference patterns required in the training phase are computed with the model, calibrated using a small number of actual measurements. Promising results are obtained. An experimental fuel leakage fault is successfully diagnosed, including detection and localization of the faulty cylinder, as well as the approximation of the fault severity.
Parameter discovery in stochastic biological models using simulated annealing and statistical model checking.

Science.gov (United States)

Hussain, Faraz; Jha, Sumit K; Jha, Susmit; Langmead, Christopher J

2014-01-01

Stochastic models are increasingly used to study the behaviour of biochemical systems. While the structure of such models is often readily available from first principles, unknown quantitative features of the model are incorporated into the model as parameters. Algorithmic discovery of parameter values from experimentally observed facts remains a challenge for the computational systems biology community. We present a new parameter discovery algorithm that uses simulated annealing, sequential hypothesis testing, and statistical model checking to learn the parameters in a stochastic model. We apply our technique to a model of glucose and insulin metabolism used for in-silico validation of artificial pancreata and demonstrate its effectiveness by developing parallel CUDA-based implementation for parameter synthesis in this model.
Establishing statistical models of manufacturing parameters

International Nuclear Information System (INIS)

Senevat, J.; Pape, J.L.; Deshayes, J.F.

1991-01-01

This paper reports on the effect of pilgering and cold-work parameters on contractile strain ratio and mechanical properties that were investigated using a large population of Zircaloy tubes. Statistical models were established between: contractile strain ratio and tooling parameters, mechanical properties (tensile test, creep test) and cold-work parameters, and mechanical properties and stress-relieving temperature
Optimizing Photosynthetic and Respiratory Parameters Based on the Seasonal Variation Pattern in Regional Net Ecosystem Productivity Obtained from Atmospheric Inversion

Science.gov (United States)

Chen, Z.; Chen, J.; Zheng, X.; Jiang, F.; Zhang, S.; Ju, W.; Yuan, W.; Mo, G.

2014-12-01

In this study, we explore the feasibility of optimizing ecosystem photosynthetic and respiratory parameters from the seasonal variation pattern of the net carbon flux. An optimization scheme is proposed to estimate two key parameters (Vcmax and Q10) by exploiting the seasonal variation in the net ecosystem carbon flux retrieved by an atmospheric inversion system. This scheme is implemented to estimate Vcmax and Q10 of the Boreal Ecosystem Productivity Simulator (BEPS) to improve its NEP simulation in the Boreal North America (BNA) region. Simultaneously, in-situ NEE observations at six eddy covariance sites are used to evaluate the NEE simulations. The results show that the performance of the optimized BEPS is superior to that of the BEPS with the default parameter values. These results have the implication on using atmospheric CO2 data for optimizing ecosystem parameters through atmospheric inversion or data assimilation techniques.
Some tests for parameter constancy in cointegrated VAR-models

DEFF Research Database (Denmark)

Hansen, Henrik; Johansen, Søren

1999-01-01

Some methods for the evaluation of parameter constancy in vector autoregressive (VAR) models are discussed. Two different ways of re-estimating the VAR model are proposed; one in which all parameters are estimated recursively based upon the likelihood function for the first observations, and anot...... be applied to test the constancy of the long-run parameters in the cointegrated VAR-model. All results are illustrated using a model for the term structure of interest rates on US Treasury securities. ......Some methods for the evaluation of parameter constancy in vector autoregressive (VAR) models are discussed. Two different ways of re-estimating the VAR model are proposed; one in which all parameters are estimated recursively based upon the likelihood function for the first observations......, and another in which the cointegrating relations are estimated recursively from a likelihood function, where the short-run parameters have been concentrated out. We suggest graphical procedures based on recursively estimated eigenvalues to evaluate the constancy of the long-run parameters in the model...
Edge Modeling by Two Blur Parameters in Varying Contrasts.

Science.gov (United States)

Seo, Suyoung

2018-06-01

This paper presents a method of modeling edge profiles with two blur parameters, and estimating and predicting those edge parameters with varying brightness combinations and camera-to-object distances (COD). First, the validity of the edge model is proven mathematically. Then, it is proven experimentally with edges from a set of images captured for specifically designed target sheets and with edges from natural images. Estimation of the two blur parameters for each observed edge profile is performed with a brute-force method to find parameters that produce global minimum errors. Then, using the estimated blur parameters, actual blur parameters of edges with arbitrary brightness combinations are predicted using a surface interpolation method (i.e., kriging). The predicted surfaces show that the two blur parameters of the proposed edge model depend on both dark-side edge brightness and light-side edge brightness following a certain global trend. This is similar across varying CODs. The proposed edge model is compared with a one-blur parameter edge model using experiments of the root mean squared error for fitting the edge models to each observed edge profile. The comparison results suggest that the proposed edge model has superiority over the one-blur parameter edge model in most cases where edges have varying brightness combinations.
Estimating spatial and temporal components of variation in count data using negative binomial mixed models

Science.gov (United States)

Irwin, Brian J.; Wagner, Tyler; Bence, James R.; Kepler, Megan V.; Liu, Weihai; Hayes, Daniel B.

2013-01-01

Partitioning total variability into its component temporal and spatial sources is a powerful way to better understand time series and elucidate trends. The data available for such analyses of fish and other populations are usually nonnegative integer counts of the number of organisms, often dominated by many low values with few observations of relatively high abundance. These characteristics are not well approximated by the Gaussian distribution. We present a detailed description of a negative binomial mixed-model framework that can be used to model count data and quantify temporal and spatial variability. We applied these models to data from four fishery-independent surveys of Walleyes Sander vitreus across the Great Lakes basin. Specifically, we fitted models to gill-net catches from Wisconsin waters of Lake Superior; Oneida Lake, New York; Saginaw Bay in Lake Huron, Michigan; and Ohio waters of Lake Erie. These long-term monitoring surveys varied in overall sampling intensity, the total catch of Walleyes, and the proportion of zero catches. Parameter estimation included the negative binomial scaling parameter, and we quantified the random effects as the variations among gill-net sampling sites, the variations among sampled years, and site × year interactions. This framework (i.e., the application of a mixed model appropriate for count data in a variance-partitioning context) represents a flexible approach that has implications for monitoring programs (e.g., trend detection) and for examining the potential of individual variance components to serve as response metrics to large-scale anthropogenic perturbations or ecological changes.

Identification and Modelling of the In-Plane Reinforcement Orientation Variations in a CFRP Laminate Produced by Manual Lay-Up

Science.gov (United States)

Davila, Yves; Crouzeix, Laurent; Douchin, Bernard; Collombet, Francis; Grunevald, Yves-Henri

2017-08-01

Reinforcement angle orientation has a significant effect on the mechanical properties of composite materials. This work presents a methodology to introduce variable reinforcement angles into finite element (FE) models of composite structures. The study of reinforcement orientation variations uses meta-models to identify and control a continuous variation across the composite ply. First, the reinforcement angle is measured through image analysis techniques of the composite plies during the lay-up phase. Image analysis results show that variations in the mean ply orientations are between -0.5 and 0.5° with standard deviations ranging between 0.34 and 0.41°. An automatic post-treatment of the images determines the global and local angle variations yielding good agreements visually and numerically between the analysed images and the identified parameters. A composite plate analysed at the end of the cooling phase is presented as a case of study. Here, the variation in residual strains induced by the variability in the reinforcement orientation are up to 28% of the strain field of the homogeneous FE model. The proposed methodology has shown its capabilities to introduce material and geometrical variability into FE analysis of layered composite structures.
Identification and Modelling of the In-Plane Reinforcement Orientation Variations in a CFRP Laminate Produced by Manual Lay-Up

Science.gov (United States)

Davila, Yves; Crouzeix, Laurent; Douchin, Bernard; Collombet, Francis; Grunevald, Yves-Henri

2018-06-01

Reinforcement angle orientation has a significant effect on the mechanical properties of composite materials. This work presents a methodology to introduce variable reinforcement angles into finite element (FE) models of composite structures. The study of reinforcement orientation variations uses meta-models to identify and control a continuous variation across the composite ply. First, the reinforcement angle is measured through image analysis techniques of the composite plies during the lay-up phase. Image analysis results show that variations in the mean ply orientations are between -0.5 and 0.5° with standard deviations ranging between 0.34 and 0.41°. An automatic post-treatment of the images determines the global and local angle variations yielding good agreements visually and numerically between the analysed images and the identified parameters. A composite plate analysed at the end of the cooling phase is presented as a case of study. Here, the variation in residual strains induced by the variability in the reinforcement orientation are up to 28% of the strain field of the homogeneous FE model. The proposed methodology has shown its capabilities to introduce material and geometrical variability into FE analysis of layered composite structures.
Identifyability measures to select the parameters to be estimated in a solid-state fermentation distributed parameter model.

Science.gov (United States)

da Silveira, Christian L; Mazutti, Marcio A; Salau, Nina P G

2016-07-08

Process modeling can lead to of advantages such as helping in process control, reducing process costs and product quality improvement. This work proposes a solid-state fermentation distributed parameter model composed by seven differential equations with seventeen parameters to represent the process. Also, parameters estimation with a parameters identifyability analysis (PIA) is performed to build an accurate model with optimum parameters. Statistical tests were made to verify the model accuracy with the estimated parameters considering different assumptions. The results have shown that the model assuming substrate inhibition better represents the process. It was also shown that eight from the seventeen original model parameters were nonidentifiable and better results were obtained with the removal of these parameters from the estimation procedure. Therefore, PIA can be useful to estimation procedure, since it may reduce the number of parameters that can be evaluated. Further, PIA improved the model results, showing to be an important procedure to be taken. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:905-917, 2016. © 2016 American Institute of Chemical Engineers.
Variations in the Parameters of Background Seismic Noise during the Preparation Stages of Strong Earthquakes in the Kamchatka Region

Science.gov (United States)

Kasimova, V. A.; Kopylova, G. N.; Lyubushin, A. A.

2018-03-01

The results of the long (2011-2016) investigation of background seismic noise (BSN) in Kamchatka by the method suggested by Doct. Sci. (Phys.-Math.) A.A. Lyubushin with the use of the data from the network of broadband seismic stations of the Geophysical Survey of the Russian Academy of Sciences are presented. For characterizing the BSN field and its variability, continuous time series of the statistical parameters of the multifractal singularity spectra and wavelet expansion calculated from the records at each station are used. These parameters include the generalized Hurst exponent α*, singularity spectrum support width Δα, wavelet spectral exponent β, minimal normalized entropy of wavelet coefficients En, and spectral measure of their coherent behavior. The peculiarities in the spatiotemporal distribution of the BSN parameters as a probable response to the earthquakes with M w = 6.8-8.3 that occurred in Kamchatka in 2013 and 2016 are considered. It is established that these seismic events were preceded by regular variations in the BSN parameters, which lasted for a few months and consisted in the reduction of the median and mean α*, Δα, and β values estimated over all the stations and in the increase of the En values. Based on the increase in the spectral measure of the coherent behavior of the four-variate time series of the median and mean values of the considered statistics, the effect of the enhancement of the synchronism in the joint (collective) behavior of these parameters during a certain period prior to the mantle earthquake in the Sea of Okhotsk (May 24, 2013, M w = 8.3) is diagnosed. The procedures for revealing the precursory effects in the variations of the BSN parameters are described and the examples of these effects are presented.
Environmental Transport Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

M. A. Wasiolek

2003-06-27

This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (TWP) (BSC 2003 [163602]). Some documents in Figure 1-1 may be under development and not available when this report is issued. This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA), but access to the listed documents is not required to understand the contents of this report. This report is one of the reports that develops input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2003 [160699]) describes the conceptual model, the mathematical model, and the input parameters. The purpose of this analysis is to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or volcanic ash). The analysis was performed in accordance with the TWP (BSC 2003 [163602]). This analysis develops values of parameters associated with many features, events, and processes (FEPs) applicable to the reference biosphere (DTN: M00303SEPFEPS2.000 [162452]), which are addressed in the biosphere model (BSC 2003 [160699]). The treatment of these FEPs is described in BSC (2003 [160699
Environmental Transport Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

Wasiolek, M. A.

2003-01-01

This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (TWP) (BSC 2003 [163602]). Some documents in Figure 1-1 may be under development and not available when this report is issued. This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA), but access to the listed documents is not required to understand the contents of this report. This report is one of the reports that develops input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2003 [160699]) describes the conceptual model, the mathematical model, and the input parameters. The purpose of this analysis is to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or volcanic ash). The analysis was performed in accordance with the TWP (BSC 2003 [163602]). This analysis develops values of parameters associated with many features, events, and processes (FEPs) applicable to the reference biosphere (DTN: M00303SEPFEPS2.000 [162452]), which are addressed in the biosphere model (BSC 2003 [160699]). The treatment of these FEPs is described in BSC (2003 [160699], Section 6.2). Parameter values
Estimation of the location parameter of distributions with known coefficient of variation by record values

Directory of Open Access Journals (Sweden)

N. K. Sajeevkumar

2014-09-01

Full Text Available In this article, we derived the Best Linear Unbiased Estimator (BLUE of the location parameter of certain distributions with known coefficient of variation by record values. Efficiency comparisons are also made on the proposed estimator with some of the usual estimators. Finally we give a real life data to explain the utility of results developed in this article.
The use of multilevel models to evaluate sources of variation in reproductive performance in dairy cattle in Reunion Island

DEFF Research Database (Denmark)

Dohoo, I.R.; Tillard, E.; Stryhn, H.

2001-01-01

%, respectively) - but for the other two parameters (first-service-conception risk and first-service-to-conception interval), >90% of the variation resided at the lactation level. For the three continuous dependent variables, comparison of results between models based on log-transformed data and Box-Cox-transformed...
Parameter estimation in stochastic rainfall-runoff models

DEFF Research Database (Denmark)

Jonsdottir, Harpa; Madsen, Henrik; Palsson, Olafur Petur

2006-01-01

A parameter estimation method for stochastic rainfall-runoff models is presented. The model considered in the paper is a conceptual stochastic model, formulated in continuous-discrete state space form. The model is small and a fully automatic optimization is, therefore, possible for estimating all...... the parameter values are optimal for simulation or prediction. The data originates from Iceland and the model is designed for Icelandic conditions, including a snow routine for mountainous areas. The model demands only two input data series, precipitation and temperature and one output data series...
A method for model identification and parameter estimation

International Nuclear Information System (INIS)

Bambach, M; Heinkenschloss, M; Herty, M

2013-01-01

We propose and analyze a new method for the identification of a parameter-dependent model that best describes a given system. This problem arises, for example, in the mathematical modeling of material behavior where several competing constitutive equations are available to describe a given material. In this case, the models are differential equations that arise from the different constitutive equations, and the unknown parameters are coefficients in the constitutive equations. One has to determine the best-suited constitutive equations for a given material and application from experiments. We assume that the true model is one of the N possible parameter-dependent models. To identify the correct model and the corresponding parameters, we can perform experiments, where for each experiment we prescribe an input to the system and observe a part of the system state. Our approach consists of two stages. In the first stage, for each pair of models we determine the experiment, i.e. system input and observation, that best differentiates between the two models, and measure the distance between the two models. Then we conduct N(N − 1) or, depending on the approach taken, N(N − 1)/2 experiments and use the result of the experiments as well as the previously computed model distances to determine the true model. We provide sufficient conditions on the model distances and measurement errors which guarantee that our approach identifies the correct model. Given the model, we identify the corresponding model parameters in the second stage. The problem in the second stage is a standard parameter estimation problem and we use a method suitable for the given application. We illustrate our approach on three examples, including one where the models are elliptic partial differential equations with different parameterized right-hand sides and an example where we identify the constitutive equation in a problem from computational viscoplasticity. (paper)
Simulation, identification and statistical variation in cardiovascular analysis (SISCA) - A software framework for multi-compartment lumped modeling.

Science.gov (United States)

Huttary, Rudolf; Goubergrits, Leonid; Schütte, Christof; Bernhard, Stefan

2017-08-01

It has not yet been possible to obtain modeling approaches suitable for covering a wide range of real world scenarios in cardiovascular physiology because many of the system parameters are uncertain or even unknown. Natural variability and statistical variation of cardiovascular system parameters in healthy and diseased conditions are characteristic features for understanding cardiovascular diseases in more detail. This paper presents SISCA, a novel software framework for cardiovascular system modeling and its MATLAB implementation. The framework defines a multi-model statistical ensemble approach for dimension reduced, multi-compartment models and focuses on statistical variation, system identification and patient-specific simulation based on clinical data. We also discuss a data-driven modeling scenario as a use case example. The regarded dataset originated from routine clinical examinations and comprised typical pre and post surgery clinical data from a patient diagnosed with coarctation of aorta. We conducted patient and disease specific pre/post surgery modeling by adapting a validated nominal multi-compartment model with respect to structure and parametrization using metadata and MRI geometry. In both models, the simulation reproduced measured pressures and flows fairly well with respect to stenosis and stent treatment and by pre-treatment cross stenosis phase shift of the pulse wave. However, with post-treatment data showing unrealistic phase shifts and other more obvious inconsistencies within the dataset, the methods and results we present suggest that conditioning and uncertainty management of routine clinical data sets needs significantly more attention to obtain reasonable results in patient-specific cardiovascular modeling. Copyright © 2017 Elsevier Ltd. All rights reserved.
Bending analysis of agglomerated carbon nanotube-reinforced beam resting on two parameters modified Vlasov model foundation

Science.gov (United States)

Ghorbanpour Arani, A.; Zamani, M. H.

2018-06-01

The present work deals with bending behavior of nanocomposite beam resting on two parameters modified Vlasov model foundation (MVMF), with consideration of agglomeration and distribution of carbon nanotubes (CNTs) in beam matrix. Equivalent fiber based on Eshelby-Mori-Tanaka approach is employed to determine influence of CNTs aggregation on elastic properties of CNT-reinforced beam. The governing equations are deduced using the principle of minimum potential energy under assumption of the Euler-Bernoulli beam theory. The MVMF required the estimation of γ parameter; to this purpose, unique iterative technique based on variational principles is utilized to compute value of the γ and subsequently fourth-order differential equation is solved analytically. Eventually, the transverse displacements and bending stresses are obtained and compared for different agglomeration parameters, various boundary conditions simultaneously and variant elastic foundation without requirement to instate values for foundation parameters.
Daily variation of the radon concentration indoors and outdoors and the influence of meteorological parameters

International Nuclear Information System (INIS)

Porstendoerfer, J.; Butterweck, G.; Reineking, A.

1994-01-01

Series of continuous radon measurements in the open atmosphere and in a dwelling, including the parallel measurement of meteorological parameters, were performed over a period of several weeks. The radon concentration in indoor and outdoor air depends on meteorological conditions. In the open atmosphere the radon concentration varies between 1 and 100 Bq m -3 , depending on weather conditions and time of day. During time periods of low turbulent air exchange (high pressure weather with clear night sky), especially in the night and early morning hours (night inversion layer), the diurnal variation of the radon concentration showed a pronounced maximum. Cloudy and windy weather conditions yield a small diurnal variation of the radon concentration. Indoors, the average level and the diurnal variation of the indoor radon concentration is also influenced by meteorological conditions. The measurements are consistent with a dependence of indoor radon concentrations on indoor-outdoor pressure differences. 11 refs., 4 figs
Long-period variations of wind parameters in the mesopause region and the solar cycle dependence

International Nuclear Information System (INIS)

Greisiger, K.M.; Schminder, R.; Kuerschner, D.

1987-01-01

A solar dependence of wind parameters below 100 km was found by Sprenger and Schminder on the basis of long-term continuous ionospheric drift measurements. For winter they obtained for the prevailing wind a positive correlation with solar activity and for the amplitude of the semi-diurnal tidal wind a negative correlation. However, after the years 1973-1974 we found a significant negative correlation with solar activity with an indication of a new change after 1983. We conclude that this long-term behaviour points rather to a climatic variation with an internal atmospheric cause than to a direct solar control. Recent satellite data of the solar u.v. radiation and the upper stratospheric ozone have shown that the possible variation of the thermal tidal excitation during the solar cycle amounts to only a few per cent. This is, therefore, insufficient to account for the 40-70% variation of the tidal amplitudes. Some other possibilities of explaining this result are discussed. (author)
New trends in parameter identification for mathematical models

CERN Document Server

Leitão, Antonio; Zubelli, Jorge

2018-01-01

The Proceedings volume contains 16 contributions to the IMPA conference “New Trends in Parameter Identification for Mathematical Models”, Rio de Janeiro, Oct 30 – Nov 3, 2017, integrating the “Chemnitz Symposium on Inverse Problems on Tour”. This conference is part of the “Thematic Program on Parameter Identification in Mathematical Models” organized at IMPA in October and November 2017. One goal is to foster the scientific collaboration between mathematicians and engineers from the Brazialian, European and Asian communities. Main topics are iterative and variational regularization methods in Hilbert and Banach spaces for the stable approximate solution of ill-posed inverse problems, novel methods for parameter identification in partial differential equations, problems of tomography , solution of coupled conduction-radiation problems at high temperatures, and the statistical solution of inverse problems with applications in physics.
Application of lumped-parameter models

DEFF Research Database (Denmark)

Ibsen, Lars Bo; Liingaard, Morten

This technical report concerns the lumped-parameter models for a suction caisson with a ratio between skirt length and foundation diameter equal to 1/2, embedded into an viscoelastic soil. The models are presented for three different values of the shear modulus of the subsoil (section 1.1). Subse...
Predictive Distribution of the Dirichlet Mixture Model by the Local Variational Inference Method

DEFF Research Database (Denmark)

Ma, Zhanyu; Leijon, Arne; Tan, Zheng-Hua

2014-01-01

the predictive likelihood of the new upcoming data, especially when the amount of training data is small. The Bayesian estimation of a Dirichlet mixture model (DMM) is, in general, not analytically tractable. In our previous work, we have proposed a global variational inference-based method for approximately...... calculating the posterior distributions of the parameters in the DMM analytically. In this paper, we extend our previous study for the DMM and propose an algorithm to calculate the predictive distribution of the DMM with the local variational inference (LVI) method. The true predictive distribution of the DMM...... is analytically intractable. By considering the concave property of the multivariate inverse beta function, we introduce an upper-bound to the true predictive distribution. As the global minimum of this upper-bound exists, the problem is reduced to seek an approximation to the true predictive distribution...
A simulation of water pollution model parameter estimation

Science.gov (United States)

Kibler, J. F.

1976-01-01

A parameter estimation procedure for a water pollution transport model is elaborated. A two-dimensional instantaneous-release shear-diffusion model serves as representative of a simple transport process. Pollution concentration levels are arrived at via modeling of a remote-sensing system. The remote-sensed data are simulated by adding Gaussian noise to the concentration level values generated via the transport model. Model parameters are estimated from the simulated data using a least-squares batch processor. Resolution, sensor array size, and number and location of sensor readings can be found from the accuracies of the parameter estimates.
Identification of ecosystem parameters by SDE-modelling

DEFF Research Database (Denmark)

Stochastic differential equations (SDEs) for ecosystem modelling have attracted increasing attention during recent years. The modelling has mostly been through simulation experiments in order to analyse how system noise propagates through the ordinary differential equation formulation of ecosystem...... models. Estimation of parameters in SDEs is, however, possible by combining Kalman filter techniques and likelihood estimation. By modelling parameters as random walks it is possible to identify linear as well as non-linear interactions between ecosystem components. By formulating a simple linear SDE...
Experimental investigation on the effect of intake air temperature and air-fuel ratio on cycle-to-cycle variations of HCCI combustion and performance parameters

Energy Technology Data Exchange (ETDEWEB)

Maurya, Rakesh Kumar; Agarwal, Avinash Kumar [Engine Research Laboratory, Department of Mechanical Engineering, Indian Institute of Technology Kanpur, Kanpur 208016 (India)

2011-04-15

Combustion in HCCI engines is a controlled auto ignition of well-mixed fuel, air and residual gas. Since onset of HCCI combustion depends on the auto ignition of fuel/air mixture, there is no direct control on the start of combustion process. Therefore, HCCI combustion becomes unstable rather easily, especially at lower and higher engine loads. In this study, cycle-to-cycle variations of a HCCI combustion engine fuelled with ethanol were investigated on a modified two-cylinder engine. Port injection technique is used for preparing homogeneous charge for HCCI combustion. The experiments were conducted at varying intake air temperatures and air-fuel ratios at constant engine speed of 1500 rpm and P-{theta} diagram of 100 consecutive combustion cycles for each test conditions at steady state operation were recorded. Consequently, cycle-to-cycle variations of the main combustion parameters and performance parameters were analyzed. To evaluate the cycle-to-cycle variations of HCCI combustion parameters, coefficient of variation (COV) of every parameter were calculated for every engine operating condition. The critical optimum parameters that can be used to define HCCI operating ranges are 'maximum rate of pressure rise' and 'COV of indicated mean effective pressure (IMEP)'. (author)

Classification of the coefficients of variation of parameters evaluated in Japanese quail experiments

Directory of Open Access Journals (Sweden)

DHV Leal

2014-06-01

Full Text Available The objective of this study was to design a classification range of the coefficients of variation (CV of traits used in experiments with eggtype Japanese quails (Coturnix coturnix japonica. The journal Revista Brasileira de Zootecnia was systematically reviewed, using the key word 'quail' during the period of January, 2000 to 2010. The CV of feed intake (g/bird/d, egg production (%/bird/d, egg weight (g, egg mass (g/bird/d, feed conversion ratio per dozen eggs (g/dozen, feed conversion ratio per egg mass (g/g, and egg specific gravity (g/mL were collected. For each parameter, CV were classified using the following median (MD and pseudo-sigma (PS ratio as follows: low (CV MD + 2PS. According to the results, it was concluded that each parameter has a specific classification range that should be taken into account when evaluating experimental precision.
Influence of the "surface effect" on the segregation parameters of S in Fe(100): A multi-scale modelling and Auger Electron Spectroscopy study

Science.gov (United States)

Barnard, P. E.; Terblans, J. J.; Swart, H. C.

2015-12-01

The article takes a new look at the process of atomic segregation by considering the influence of surface relaxation on the segregation parameters; the activation energy (Q), segregation energy (ΔG), interaction parameter (Ω) and the pre-exponential factor (D0). Computational modelling, namely Density Functional Theory (DFT) and the Modified Darken Model (MDM) in conjunction with Auger Electron Spectroscopy (AES) was utilized to study the variation of the segregation parameters for S in the surface region of Fe(100). Results indicate a variation in each of the segregation parameters as a function of the atomic layer under consideration. Values of the segregation parameters varied more dramatically as the surface layer is approached, with atomic layer 2 having the largest deviations in comparison to the bulk values. This atomic layer had the highest Q value and formed the rate limiting step for the segregation of S towards the Fe(100) surface. It was found that the segregation process is influenced by two sets of segregation parameters, those of the surface region formed by atomic layer 2, and those in the bulk material. This article is the first to conduct a full scale investigation on the influence of surface relaxation on segregation and labelled it the "surface effect".
Prediction of interindividual variation in drug plasma levels in vivo from individual enzyme kinetic data and physiologically based pharmacokinetic modeling

NARCIS (Netherlands)

Bogaards, J.J.P.; Hissink, E.M.; Briggs, M.; Weaver, R.; Jochemsen, R.; Jackson, P.; Bertrand, M.; Bladeren, P. van

2000-01-01

A strategy is presented to predict interindividual variation in drug plasma levels in vivo by the use of physiologically based pharmacokinetic modeling and human in vitro metabolic parameters, obtained through the combined use of microsomes containing single cytochrome P450 enzymes and a human liver
Spatio-temporal modeling of nonlinear distributed parameter systems

CERN Document Server

Li, Han-Xiong

2011-01-01

The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein s
Models for estimating photosynthesis parameters from in situ production profiles

Science.gov (United States)

Kovač, Žarko; Platt, Trevor; Sathyendranath, Shubha; Antunović, Suzana

2017-12-01

The rate of carbon assimilation in phytoplankton primary production models is mathematically prescribed with photosynthesis irradiance functions, which convert a light flux (energy) into a material flux (carbon). Information on this rate is contained in photosynthesis parameters: the initial slope and the assimilation number. The exactness of parameter values is crucial for precise calculation of primary production. Here we use a model of the daily production profile based on a suite of photosynthesis irradiance functions and extract photosynthesis parameters from in situ measured daily production profiles at the Hawaii Ocean Time-series station Aloha. For each function we recover parameter values, establish parameter distributions and quantify model skill. We observe that the choice of the photosynthesis irradiance function to estimate the photosynthesis parameters affects the magnitudes of parameter values as recovered from in situ profiles. We also tackle the problem of parameter exchange amongst the models and the effect it has on model performance. All models displayed little or no bias prior to parameter exchange, but significant bias following parameter exchange. The best model performance resulted from using optimal parameter values. Model formulation was extended further by accounting for spectral effects and deriving a spectral analytical solution for the daily production profile. The daily production profile was also formulated with time dependent growing biomass governed by a growth equation. The work on parameter recovery was further extended by exploring how to extract photosynthesis parameters from information on watercolumn production. It was demonstrated how to estimate parameter values based on a linearization of the full analytical solution for normalized watercolumn production and from the solution itself, without linearization. The paper complements previous works on photosynthesis irradiance models by analysing the skill and consistency of
Delay Variation Model with Two Service Queues

Directory of Open Access Journals (Sweden)

Filip Rezac

2010-01-01

Full Text Available Delay in VoIP technology is very unpleasant issue and therefore a voice packets prioritization must be ensured. To maintain the high call quality a maximum information delivery time from the sender to the recipient is set to 150 ms. This paper focuses on the design of a mathematical model of end-to-end delay of a VoIP connection, in particular on a delay variation. It describes all partial delay components and mechanisms, their generation, facilities and mathematical formulations. A new approach to the delay variation model is presented and its validation has been done by experimention.
GEMSFITS: Code package for optimization of geochemical model parameters and inverse modeling

International Nuclear Information System (INIS)

Miron, George D.; Kulik, Dmitrii A.; Dmytrieva, Svitlana V.; Wagner, Thomas

2015-01-01

Highlights: • Tool for generating consistent parameters against various types of experiments. • Handles a large number of experimental data and parameters (is parallelized). • Has a graphical interface and can perform statistical analysis on the parameters. • Tested on fitting the standard state Gibbs free energies of aqueous Al species. • Example on fitting interaction parameters of mixing models and thermobarometry. - Abstract: GEMSFITS is a new code package for fitting internally consistent input parameters of GEM (Gibbs Energy Minimization) geochemical–thermodynamic models against various types of experimental or geochemical data, and for performing inverse modeling tasks. It consists of the gemsfit2 (parameter optimizer) and gfshell2 (graphical user interface) programs both accessing a NoSQL database, all developed with flexibility, generality, efficiency, and user friendliness in mind. The parameter optimizer gemsfit2 includes the GEMS3K chemical speciation solver ( (http://gems.web.psi.ch/GEMS3K)), which features a comprehensive suite of non-ideal activity- and equation-of-state models of solution phases (aqueous electrolyte, gas and fluid mixtures, solid solutions, (ad)sorption. The gemsfit2 code uses the robust open-source NLopt library for parameter fitting, which provides a selection between several nonlinear optimization algorithms (global, local, gradient-based), and supports large-scale parallelization. The gemsfit2 code can also perform comprehensive statistical analysis of the fitted parameters (basic statistics, sensitivity, Monte Carlo confidence intervals), thus supporting the user with powerful tools for evaluating the quality of the fits and the physical significance of the model parameters. The gfshell2 code provides menu-driven setup of optimization options (data selection, properties to fit and their constraints, measured properties to compare with computed counterparts, and statistics). The practical utility, efficiency, and
Identification of parameters of discrete-continuous models

International Nuclear Information System (INIS)

Cekus, Dawid; Warys, Pawel

2015-01-01

In the paper, the parameters of a discrete-continuous model have been identified on the basis of experimental investigations and formulation of optimization problem. The discrete-continuous model represents a cantilever stepped Timoshenko beam. The mathematical model has been formulated and solved according to the Lagrange multiplier formalism. Optimization has been based on the genetic algorithm. The presented proceeding’s stages make the identification of any parameters of discrete-continuous systems possible
Identification of parameters of discrete-continuous models

Energy Technology Data Exchange (ETDEWEB)

Cekus, Dawid, E-mail: cekus@imipkm.pcz.pl; Warys, Pawel, E-mail: warys@imipkm.pcz.pl [Institute of Mechanics and Machine Design Foundations, Czestochowa University of Technology, Dabrowskiego 73, 42-201 Czestochowa (Poland)

2015-03-10

In the paper, the parameters of a discrete-continuous model have been identified on the basis of experimental investigations and formulation of optimization problem. The discrete-continuous model represents a cantilever stepped Timoshenko beam. The mathematical model has been formulated and solved according to the Lagrange multiplier formalism. Optimization has been based on the genetic algorithm. The presented proceeding’s stages make the identification of any parameters of discrete-continuous systems possible.
Identifying the connective strength between model parameters and performance criteria

Directory of Open Access Journals (Sweden)

B. Guse

2017-11-01

Full Text Available In hydrological models, parameters are used to represent the time-invariant characteristics of catchments and to capture different aspects of hydrological response. Hence, model parameters need to be identified based on their role in controlling the hydrological behaviour. For the identification of meaningful parameter values, multiple and complementary performance criteria are used that compare modelled and measured discharge time series. The reliability of the identification of hydrologically meaningful model parameter values depends on how distinctly a model parameter can be assigned to one of the performance criteria. To investigate this, we introduce the new concept of connective strength between model parameters and performance criteria. The connective strength assesses the intensity in the interrelationship between model parameters and performance criteria in a bijective way. In our analysis of connective strength, model simulations are carried out based on a latin hypercube sampling. Ten performance criteria including Nash–Sutcliffe efficiency (NSE, Kling–Gupta efficiency (KGE and its three components (alpha, beta and r as well as RSR (the ratio of the root mean square error to the standard deviation for different segments of the flow duration curve (FDC are calculated. With a joint analysis of two regression tree (RT approaches, we derive how a model parameter is connected to different performance criteria. At first, RTs are constructed using each performance criterion as the target variable to detect the most relevant model parameters for each performance criterion. Secondly, RTs are constructed using each parameter as the target variable to detect which performance criteria are impacted by changes in the values of one distinct model parameter. Based on this, appropriate performance criteria are identified for each model parameter. In this study, a high bijective connective strength between model parameters and performance criteria
Agricultural and Environmental Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

Kaylie Rasmuson; Kurt Rautenstrauch

2003-01-01

This analysis is one of nine technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. It documents input parameters for the biosphere model, and supports the use of the model to develop Biosphere Dose Conversion Factors (BDCF). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in the biosphere Technical Work Plan (TWP, BSC 2003a). It should be noted that some documents identified in Figure 1-1 may be under development and therefore not available at the time this document is issued. The ''Biosphere Model Report'' (BSC 2003b) describes the ERMYN and its input parameters. This analysis report, ANL-MGR-MD-000006, ''Agricultural and Environmental Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. This report defines and justifies values for twelve parameters required in the biosphere model. These parameters are related to use of contaminated groundwater to grow crops. The parameter values recommended in this report are used in the soil, plant, and carbon-14 submodels of the ERMYN
Verification Techniques for Parameter Selection and Bayesian Model Calibration Presented for an HIV Model

Science.gov (United States)

Wentworth, Mami Tonoe

Uncertainty quantification plays an important role when making predictive estimates of model responses. In this context, uncertainty quantification is defined as quantifying and reducing uncertainties, and the objective is to quantify uncertainties in parameter, model and measurements, and propagate the uncertainties through the model, so that one can make a predictive estimate with quantified uncertainties. Two of the aspects of uncertainty quantification that must be performed prior to propagating uncertainties are model calibration and parameter selection. There are several efficient techniques for these processes; however, the accuracy of these methods are often not verified. This is the motivation for our work, and in this dissertation, we present and illustrate verification frameworks for model calibration and parameter selection in the context of biological and physical models. First, HIV models, developed and improved by [2, 3, 8], describe the viral infection dynamics of an HIV disease. These are also used to make predictive estimates of viral loads and T-cell counts and to construct an optimal control for drug therapy. Estimating input parameters is an essential step prior to uncertainty quantification. However, not all the parameters are identifiable, implying that they cannot be uniquely determined by the observations. These unidentifiable parameters can be partially removed by performing parameter selection, a process in which parameters that have minimal impacts on the model response are determined. We provide verification techniques for Bayesian model calibration and parameter selection for an HIV model. As an example of a physical model, we employ a heat model with experimental measurements presented in [10]. A steady-state heat model represents a prototypical behavior for heat conduction and diffusion process involved in a thermal-hydraulic model, which is a part of nuclear reactor models. We employ this simple heat model to illustrate verification
Zener Diode Compact Model Parameter Extraction Using Xyce-Dakota Optimization.

Energy Technology Data Exchange (ETDEWEB)

Buchheit, Thomas E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wilcox, Ian Zachary [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sandoval, Andrew J [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Reza, Shahed [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-12-01

This report presents a detailed process for compact model parameter extraction for DC circuit Zener diodes. Following the traditional approach of Zener diode parameter extraction, circuit model representation is defined and then used to capture the different operational regions of a real diode's electrical behavior. The circuit model contains 9 parameters represented by resistors and characteristic diodes as circuit model elements. The process of initial parameter extraction, the identification of parameter values for the circuit model elements, is presented in a way that isolates the dependencies between certain electrical parameters and highlights both the empirical nature of the extraction and portions of the real diode physical behavior which of the parameters are intended to represent. Optimization of the parameters, a necessary part of a robost parameter extraction process, is demonstrated using a 'Xyce-Dakota' workflow, discussed in more detail in the report. Among other realizations during this systematic approach of electrical model parameter extraction, non-physical solutions are possible and can be difficult to avoid because of the interdependencies between the different parameters. The process steps described are fairly general and can be leveraged for other types of semiconductor device model extractions. Also included in the report are recommendations for experiment setups for generating optimum dataset for model extraction and the Parameter Identification and Ranking Table (PIRT) for Zener diodes.
Brownian motion model with stochastic parameters for asset prices

Science.gov (United States)

Ching, Soo Huei; Hin, Pooi Ah

2013-09-01

The Brownian motion model may not be a completely realistic model for asset prices because in real asset prices the drift μ and volatility σ may change over time. Presently we consider a model in which the parameter x = (μ,σ) is such that its value x (t + Δt) at a short time Δt ahead of the present time t depends on the value of the asset price at time t + Δt as well as the present parameter value x(t) and m-1 other parameter values before time t via a conditional distribution. The Malaysian stock prices are used to compare the performance of the Brownian motion model with fixed parameter with that of the model with stochastic parameter.
Study on Parameters Modeling of Wind Turbines Using SCADA Data

Directory of Open Access Journals (Sweden)

Yonglong YAN

2014-08-01

Full Text Available Taking the advantage of the current massive monitoring data from Supervisory Control and Data Acquisition (SCADA system of wind farm, it is of important significance for anomaly detection, early warning and fault diagnosis to build the data model of state parameters of wind turbines (WTs. The operational conditions and the relationships between the state parameters of wind turbines are complex. It is difficult to establish the model of state parameter accurately, and the modeling method of state parameters of wind turbines considering parameter selection is proposed. Firstly, by analyzing the characteristic of SCADA data, a reasonable range of data and monitoring parameters are chosen. Secondly, neural network algorithm is adapted, and the selection method of input parameters in the model is presented. Generator bearing temperature and cooling air temperature are regarded as target parameters, and the two models are built and input parameters of the models are selected, respectively. Finally, the parameter selection method in this paper and the method using genetic algorithm-partial least square (GA-PLS are analyzed comparatively, and the results show that the proposed methods are correct and effective. Furthermore, the modeling of two parameters illustrate that the method in this paper can applied to other state parameters of wind turbines.
A practical method to assess model sensitivity and parameter uncertainty in C cycle models

Science.gov (United States)

Delahaies, Sylvain; Roulstone, Ian; Nichols, Nancy

2015-04-01

data streams or by considering longer observation windows no systematic analysis has been carried out so far to explain the large differences among results. We consider adjoint based methods to investigate inverse problems using DALEC and various data streams. Using resolution matrices we study the nature of the inverse problems (solution existence, uniqueness and stability) and show how standard regularization techniques affect resolution and stability properties. Instead of using standard prior information as a penalty term in the cost function to regularize the problems we constraint the parameter space using ecological balance conditions and inequality constraints. The efficiency and rapidity of this approach allows us to compute ensembles of solutions to the inverse problems from which we can establish the robustness of the variational method and obtain non Gaussian posterior distributions for the model parameters and initial carbon stocks.
Seven-parameter statistical model for BRDF in the UV band.

Science.gov (United States)

Bai, Lu; Wu, Zhensen; Zou, Xiren; Cao, Yunhua

2012-05-21

A new semi-empirical seven-parameter BRDF model is developed in the UV band using experimentally measured data. The model is based on the five-parameter model of Wu and the fourteen-parameter model of Renhorn and Boreman. Surface scatter, bulk scatter and retro-reflection scatter are considered. An optimizing modeling method, the artificial immune network genetic algorithm, is used to fit the BRDF measurement data over a wide range of incident angles. The calculation time and accuracy of the five- and seven-parameter models are compared. After fixing the seven parameters, the model can well describe scattering data in the UV band.
Modeling the dependency of radon concentration levels inside ancient Egyptian tombs on the ambient temperature variations

International Nuclear Information System (INIS)

Metwally, S.M.; Abo-Elmagdb, M.; Salamaa, E.

2007-01-01

Radon concentration inside partially closed places like dwellings, caves and tombs, depends on many parameters. Some parameters are known quantitatively as radon exhalation rate for walls, decay constant, surface to volume ratio and outdoor concentration while other parameters as ventilation rate is in common known qualitatively due to useless of traditional methods (tracer gases) in many places as ancient Egyptian tombs. This work introduces a derived mathematical model to evaluate the sensitivity of radon concentration levels inside single sided opening places as ancient Egyptian tombs on the ambient temperature differences. The obtained formula for the natural ventilation rate depends on the indoor and outdoor temperature difference and the geometrical dimensions of the doorway. The effects of in and out flow mixing, air viscosity, streamline contraction, swirling flow and turbulence, were taken into consideration in terms of an empirical correction factor. According UNSCEAR reports, the exhalation rate Φ=C ra λ rn fρ s (1-ε)L; C ra the effective radium content, λ rn decay constant, f emanation fraction, ρ s soil grain density, ε porosity and L diffusion length, these are approximately static parameters but the variability of ambient temperature introduces a source of energy of fluctuating strength to radon atoms in rocks which controls the flow rate and the ambient content of radon. Therefore, the change of outdoor and indoor temperature difference causes fluctuation of value and direction of volume flow rate in such places consequently causes the daily variation and on average the seasonal variation of radon concentration. Therefore according to the present model, the daily accurate expectation of radon concentrations inside ancient Egyptian tombs, require precise measurements of indoor and outdoor temperatures
Lumped-parameter Model of a Bucket Foundation

DEFF Research Database (Denmark)

Andersen, Lars; Ibsen, Lars Bo; Liingaard, Morten

2009-01-01

efficient model that can be applied in aero-elastic codes for fast evaluation of the dynamic structural response of wind turbines. The target solutions, utilised for calibration of the lumped-parameter models, are obtained by a coupled finite-element/boundaryelement scheme in the frequency domain......, and the quality of the models are tested in the time and frequency domains. It is found that precise results are achieved by lumped-parameter models with two to four internal degrees of freedom per displacement or rotation of the foundation. Further, coupling between the horizontal sliding and rocking cannot...
Variational Assimilation of Sparse and Uncertain Satellite Data For 1D Saint-Venant River Models

Science.gov (United States)

Garambois, P. A.; Brisset, P.; Monnier, J.; Roux, H.

2016-12-01

Profusion of satellites are providing increasingly accurate measurements of continental water cyle, and water bodies variations while in situ observability is declining. The future Surface Water and Ocean Topography (SWOT) mission will provide maps of river surface elevations widths and slopes with an almost global coverage and temporal revisits. This will offer the possibility to address a larger variety of inverse problems in surface hydrology. Data assimilation techniques, that are broadly used in several scientific fields, aim to optimally combine models, system observations and prior information. Variational assimilation consists in iterative minimization of a discrepency measure between model outputs and observations, here for retrieving boundary conditions and parameters of a 1D Saint Venant model. Nevertheless, inferring river discharge and hydraulic parameters thanks to the observation of river surface is not straightforward. This is particularly true in the case of sparse and uncertain observations of flow state variables since they are governed by nonlinear physical processes. This paper investigates the identifiability of hydraulic controls given sparse and uncertain satellite observations of a river. The identifiability of river discharge alone and with roughness is tested for several spatio temporal patterns of river observations, including SWOT like observations. A new 1D Shallow water model with variational data assimilation, within the DassFlow chain is presented as well as postprocessing and observation operator dedicated to the future SWOT and SWOT simulator data. In view to decrease inverse problem dimensionality discharge is represented in a reduced basis. Moreover we introduce an original and reduced parametrization of the flow resistance that can account for various flow regimes along with a cross section design dedicated to remote sensing. We show which discharge temporal frequencies can be identified w.r.t observation ones and at which

Problems of phenomenological simulation of the Dst variation

International Nuclear Information System (INIS)

Gul'el'mi, A.V.

1988-01-01

Stochastic generalization of RBM model, describing the D st -variation is suggested. The corresponding Fokker-Planck equation contains a new phenomenological parameter enabling to obtain the interval estimation of D st forecast. The structure of sources and sinks forming the D st -variation is considered from the viewpoint of critical phenomenon theory
Agricultural and Environmental Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

Kaylie Rasmuson; Kurt Rautenstrauch

2003-06-20

This analysis is one of nine technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. It documents input parameters for the biosphere model, and supports the use of the model to develop Biosphere Dose Conversion Factors (BDCF). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in the biosphere Technical Work Plan (TWP, BSC 2003a). It should be noted that some documents identified in Figure 1-1 may be under development and therefore not available at the time this document is issued. The ''Biosphere Model Report'' (BSC 2003b) describes the ERMYN and its input parameters. This analysis report, ANL-MGR-MD-000006, ''Agricultural and Environmental Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. This report defines and justifies values for twelve parameters required in the biosphere model. These parameters are related to use of contaminated groundwater to grow crops. The parameter values recommended in this report are used in the soil, plant, and carbon-14 submodels of the ERMYN.
Variation of parasite load and immune parameters in two species of New Zealand shore crabs.

Science.gov (United States)

Dittmer, Jessica; Koehler, Anson V; Richard, Freddie-Jeanne; Poulin, Robert; Sicard, Mathieu

2011-09-01

While parasites are likely to encounter several potential intermediate hosts in natural communities, a parasite's actual range of compatible hosts is limited by numerous biological factors ranging from behaviour to immunology. In crustaceans, two major components of immunity are haemocytes and the prophenoloxidase system involved in the melanisation of foreign particles. Here, we analysed metazoan parasite prevalence and loads in the two sympatric crab species Hemigrapsus crenulatus and Macrophthalmus hirtipes at two sites. In parallel, we analysed the variation in haemocyte concentration and amount of circulating phenoloxidase (PO) in the haemolymph of the same individuals in an attempt to (a) explain differences in parasite prevalence and loads in the two species at two sites and (b) assess the impact of parasites on these immune parameters. M. hirtipes harboured more parasites but also exhibited higher haemocyte concentrations than H. crenulatus independent of the study site. Thus, higher investment in haemocyte production for M. hirtipes does not seem to result in higher resistance to parasites. Analyses of variation in immune parameters for the two crab species between the two sites that differed in parasite prevalence showed common trends. (a) In general, haemocyte concentrations were higher at the site experiencing higher parasitic pressure while circulating PO activity was lower and (b) haemocyte concentrations were influenced by microphallid trematode metacercariae in individuals from the site with higher parasitic pressure. We suggest that the higher haemocyte concentrations observed in both crab species exposed to higher parasitic pressure may represent an adaptive response to the impact of parasites on this immune parameter.
A phenomenological variational multiscale constitutive model for intergranular failure in nanocrystalline materials

KAUST Repository

Siddiq, A.

2013-09-01

We present a variational multiscale constitutive model that accounts for intergranular failure in nanocrystalline fcc metals due to void growth and coalescence in the grain boundary region. Following previous work by the authors, a nanocrystalline material is modeled as a two-phase material consisting of a grain interior phase and a grain boundary affected zone (GBAZ). A crystal plasticity model that accounts for the transition from partial dislocation to full dislocation mediated plasticity is used for the grain interior. Isotropic porous plasticity model with further extension to account for failure due to the void coalescence was used for the GBAZ. The extended model contains all the deformation phases, i.e. elastic deformation, plastic deformation including deviatoric and volumetric plasticity (void growth) followed by damage initiation and evolution due to void coalescence. Parametric studies have been performed to assess the model\\'s dependence on the different input parameters. The model is then validated against uniaxial loading experiments for different materials. Lastly we show the model\\'s ability to predict the damage and fracture of a dog-bone shaped specimen as observed experimentally. © 2013 Elsevier B.V.
The mobilisation model and parameter sensitivity

International Nuclear Information System (INIS)

Blok, B.M.

1993-12-01

In the PRObabillistic Safety Assessment (PROSA) of radioactive waste in a salt repository one of the nuclide release scenario's is the subrosion scenario. A new subrosion model SUBRECN has been developed. In this model the combined effect of a depth-dependent subrosion, glass dissolution, and salt rise has been taken into account. The subrosion model SUBRECN and the implementation of this model in the German computer program EMOS4 is presented. A new computer program PANTER is derived from EMOS4. PANTER models releases of radionuclides via subrosion from a disposal site in a salt pillar into the biosphere. For uncertainty and sensitivity analyses the new subrosion model Latin Hypercube Sampling has been used for determine the different values for the uncertain parameters. The influence of the uncertainty in the parameters on the dose calculations has been investigated by the following sensitivity techniques: Spearman Rank Correlation Coefficients, Partial Rank Correlation Coefficients, Standardised Rank Regression Coefficients, and the Smirnov Test. (orig./HP)
Characterization of PV panel and global optimization of its model parameters using genetic algorithm

International Nuclear Information System (INIS)

Ismail, M.S.; Moghavvemi, M.; Mahlia, T.M.I.

2013-01-01

Highlights: • Genetic Algorithm optimization ability had been utilized to extract parameters of PV panel model. • Effect of solar radiation and temperature variations was taken into account in fitness function evaluation. • We used Matlab-Simulink to simulate operation of the PV-panel to validate results. • Different cases were analyzed to ascertain which of them gives more accurate results. • Accuracy and applicability of this approach to be used as a valuable tool for PV modeling were clearly validated. - Abstract: This paper details an improved modeling technique for a photovoltaic (PV) module; utilizing the optimization ability of a genetic algorithm, with different parameters of the PV module being computed via this approach. The accurate modeling of any PV module is incumbent upon the values of these parameters, as it is imperative in the context of any further studies concerning different PV applications. Simulation, optimization and the design of the hybrid systems that include PV are examples of these applications. The global optimization of the parameters and the applicability for the entire range of the solar radiation and a wide range of temperatures are achievable via this approach. The Manufacturer’s Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module. The results of single-diode and two-diode models are evaluated in order to ascertain which of them are more accurate. Other cases are also analyzed in this paper for the purpose of comparison. The Matlab–Simulink environment is used to simulate the operation of the PV module, depending on the extracted parameters. The results of the simulation are compared with the Data Sheet information, which is obtained via experimentation in order to validate the reliability of the approach. Three types of PV modules
Bayesian estimation of parameters in a regional hydrological model

Directory of Open Access Journals (Sweden)

K. Engeland

2002-01-01

Full Text Available This study evaluates the applicability of the distributed, process-oriented Ecomag model for prediction of daily streamflow in ungauged basins. The Ecomag model is applied as a regional model to nine catchments in the NOPEX area, using Bayesian statistics to estimate the posterior distribution of the model parameters conditioned on the observed streamflow. The distribution is calculated by Markov Chain Monte Carlo (MCMC analysis. The Bayesian method requires formulation of a likelihood function for the parameters and three alternative formulations are used. The first is a subjectively chosen objective function that describes the goodness of fit between the simulated and observed streamflow, as defined in the GLUE framework. The second and third formulations are more statistically correct likelihood models that describe the simulation errors. The full statistical likelihood model describes the simulation errors as an AR(1 process, whereas the simple model excludes the auto-regressive part. The statistical parameters depend on the catchments and the hydrological processes and the statistical and the hydrological parameters are estimated simultaneously. The results show that the simple likelihood model gives the most robust parameter estimates. The simulation error may be explained to a large extent by the catchment characteristics and climatic conditions, so it is possible to transfer knowledge about them to ungauged catchments. The statistical models for the simulation errors indicate that structural errors in the model are more important than parameter uncertainties. Keywords: regional hydrological model, model uncertainty, Bayesian analysis, Markov Chain Monte Carlo analysis
Constraints on geomagnetic secular variation modeling from electromagnetism and fluid dynamics of the Earth's core

Science.gov (United States)

Benton, E. R.

1986-01-01

A spherical harmonic representation of the geomagnetic field and its secular variation for epoch 1980, designated GSFC(9/84), is derived and evaluated. At three epochs (1977.5, 1980.0, 1982.5) this model incorporates conservation of magnetic flux through five selected patches of area on the core/mantle boundary bounded by the zero contours of vertical magnetic field. These fifteen nonlinear constraints are included like data in an iterative least squares parameter estimation procedure that starts with the recently derived unconstrained field model GSFC (12/83). Convergence is approached within three iterations. The constrained model is evaluated by comparing its predictive capability outside the time span of its data, in terms of residuals at magnetic observatories, with that for the unconstrained model.
Models and parameters for environmental radiological assessments

International Nuclear Information System (INIS)

Miller, C.W.

1983-01-01

This article reviews the forthcoming book Models and Parameters for Environmental Radiological Assessments, which presents a unified compilation of models and parameters for assessing the impact on man of radioactive discharges, both routine and accidental, into the environment. Models presented in this book include those developed for the prediction of atmospheric and hydrologic transport and deposition, for terrestrial and aquatic food-chain bioaccumulation, and for internal and external dosimetry. Summaries are presented for each of the transport and dosimetry areas previously for each of the transport and dosimetry areas previously mentioned, and details are available in the literature cited. A chapter of example problems illustrates many of the methodologies presented throughout the text. Models and parameters presented are based on the results of extensive literature reviews and evaluations performed primarily by the staff of the Health and Safety Research Division of Oak Ridge National Laboratory
Modeling of temporal variation of very low frequency radio waves over long paths as observed from Indian Antarctic stations

Science.gov (United States)

Sasmal, Sudipta; Basak, Tamal; Chakraborty, Suman; Palit, Sourav; Chakrabarti, Sandip K.

2017-07-01

Characteristics of very low frequency (VLF) signal depends on solar illumination across the propagation path. For a long path, solar zenith angle varies widely over the path and this has a significant influence on the propagation characteristics. To study the effect, Indian Centre for Space Physics participated in the 27th and 35th Scientific Expedition to Antarctica. VLF signals transmitted from the transmitters, namely, VTX (18.2 kHz), Vijayanarayanam, India, and NWC (19.8 kHz), North West Cape, Australia, were recorded simultaneously at Indian permanent stations Maitri and Bharati having respective geographic coordinates 70.75°S, 11.67°E, and 69.4°S, 76.17°E. A very stable diurnal variation of the signal has been obtained from both the stations. We reproduced the signal variations of VLF signal using solar zenith angle model coupled with long wavelength propagation capability (LWPC) code. We divided the whole path into several segments and computed the solar zenith angle (χ) profile. We assumed a linear relationship between the Wait's exponential model parameters effective reflection height (h'), steepness parameter (β), and solar zenith angle. The h' and β values were later used in the LWPC code to obtain the VLF signal amplitude at a particular time. The same procedure was repeated to obtain the whole day signal. Nature of the whole day signal variation from the theoretical modeling is also found to match with our observation to some extent.
Biological variation of platelet parameters determined by the Sysmex XN hematology analyzer.

Science.gov (United States)

Buoro, Sabrina; Seghezzi, Michela; Manenti, Barbara; Pacioni, Aurelio; Carobene, Anna; Ceriotti, Ferruccio; Ottomano, Cosimo; Lippi, Giuseppe

2017-07-01

This study was aimed to define the short- and medium-term biological variation (BV) estimates, the index of individuality and the reference change value (RCV) of platelet count, platelet distribution width, mean platelet volume, platelet larger cell ratio, plateletcrit and immature platelet fraction. The study population consisted of 43 health subjects, who participated to the assessment of medium-term (21 subjects; blood sampling once a week for 5 consecutive weeks) and short-term (22 subjects; blood sampling once a day for 5 consecutive days) BV study, using Sysmex XN-module. Eight subjects were also scheduled to participate to both phases. The data were subject to outlier analysis prior to CV-ANOVA, to determine the BV estimates with the relative confidence intervals. The medium-term and short-term within-subject BV (CV I ) was comprised between 2.3 and 7.0% and 1.1-8.6%, whereas the medium-term and short-term between-subjects BV (CV G ) was comprised between 7.1 and 20.7% and 6.8-48.6%. The index of individuality and index of heterogeneity were always respectively 0.63 for all the parameters, in both arms of the study. The RCVs were similar for all parameters, in both arms of the study. This study allowed to define the BV estimates of many platelet parameters, some of them unavailable in literature. The kinetics of platelet turnover suggests the use of short-term BV data for calculating analytical goals and RCV. The correct clinical interpretation of platelet parameters also necessitates that each laboratory estimates local RCV values. Copyright © 2017 Elsevier B.V. All rights reserved.
Parameter Estimation of Nonlinear Models in Forestry.

OpenAIRE

Fekedulegn, Desta; Mac Siúrtáin, Máirtín Pádraig; Colbert, Jim J.

1999-01-01

Partial derivatives of the negative exponential, monomolecular, Mitcherlich, Gompertz, logistic, Chapman-Richards, von Bertalanffy, Weibull and the Richard’s nonlinear growth models are presented. The application of these partial derivatives in estimating the model parameters is illustrated. The parameters are estimated using the Marquardt iterative method of nonlinear regression relating top height to age of Norway spruce (Picea abies L.) from the Bowmont Norway Spruce Thinnin...
Learning about physical parameters: the importance of model discrepancy

International Nuclear Information System (INIS)

Brynjarsdóttir, Jenný; O'Hagan, Anthony

2014-01-01

Science-based simulation models are widely used to predict the behavior of complex physical systems. It is also common to use observations of the physical system to solve the inverse problem, that is, to learn about the values of parameters within the model, a process which is often called calibration. The main goal of calibration is usually to improve the predictive performance of the simulator but the values of the parameters in the model may also be of intrinsic scientific interest in their own right. In order to make appropriate use of observations of the physical system it is important to recognize model discrepancy, the difference between reality and the simulator output. We illustrate through a simple example that an analysis that does not account for model discrepancy may lead to biased and over-confident parameter estimates and predictions. The challenge with incorporating model discrepancy in statistical inverse problems is being confounded with calibration parameters, which will only be resolved with meaningful priors. For our simple example, we model the model-discrepancy via a Gaussian process and demonstrate that through accounting for model discrepancy our prediction within the range of data is correct. However, only with realistic priors on the model discrepancy do we uncover the true parameter values. Through theoretical arguments we show that these findings are typical of the general problem of learning about physical parameters and the underlying physical system using science-based mechanistic models. (paper)
Introductory Biology Students’ Conceptual Models and Explanations of the Origin of Variation

Science.gov (United States)

Shaw, Neil; Momsen, Jennifer; Reinagel, Adam; Le, Paul; Taqieddin, Ranya; Long, Tammy

2014-01-01

Mutation is the key molecular mechanism generating phenotypic variation, which is the basis for evolution. In an introductory biology course, we used a model-based pedagogy that enabled students to integrate their understanding of genetics and evolution within multiple case studies. We used student-generated conceptual models to assess understanding of the origin of variation. By midterm, only a small percentage of students articulated complete and accurate representations of the origin of variation in their models. Targeted feedback was offered through activities requiring students to critically evaluate peers’ models. At semester's end, a substantial proportion of students significantly improved their representation of how variation arises (though one-third still did not include mutation in their models). Students’ written explanations of the origin of variation were mostly consistent with their models, although less effective than models in conveying mechanistic reasoning. This study contributes evidence that articulating the genetic origin of variation is particularly challenging for learners and may require multiple cycles of instruction, assessment, and feedback. To support meaningful learning of the origin of variation, we advocate instruction that explicitly integrates multiple scales of biological organization, assessment that promotes and reveals mechanistic and causal reasoning, and practice with explanatory models with formative feedback. PMID:25185235
Modelling of Impulsional pH Variations Using ChemFET-Based Microdevices: Application to Hydrogen Peroxide Detection

Directory of Open Access Journals (Sweden)

Abdou Karim Diallo

2014-02-01

Full Text Available This work presents the modelling of impulsional pH variations in microvolume related to water-based electrolysis and hydrogen peroxide electrochemical oxidation using an Electrochemical Field Effect Transistor (ElecFET microdevice. This ElecFET device consists of a pH-Chemical FET (pH-ChemFET with an integrated microelectrode around the dielectric gate area in order to trigger electrochemical reactions. Combining oxidation/reduction reactions on the microelectrode, water self-ionization and diffusion properties of associated chemical species, the model shows that the sensor response depends on the main influential parameters such as: (i polarization parameters on the microelectrode, i.e., voltage (Vp and time (tp; (ii distance between the gate sensitive area and the microelectrode (d; and (iii hydrogen peroxide concentration ([H2O2]. The model developed can predict the ElecFET response behaviour and creates new opportunities for H2O2-based enzymatic detection of biomolecules.
Wind Farm Decentralized Dynamic Modeling With Parameters

DEFF Research Database (Denmark)

Soltani, Mohsen; Shakeri, Sayyed Mojtaba; Grunnet, Jacob Deleuran

2010-01-01

Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...... local models. The results of this report are especially useful, but not limited, to design a decentralized wind farm controller, since in centralized controller design one can also use the model and update it in a central computing node.......Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...
Optimizing incomplete sample designs for item response model parameters

NARCIS (Netherlands)

van der Linden, Willem J.

Several models for optimizing incomplete sample designs with respect to information on the item parameters are presented. The following cases are considered: (1) known ability parameters; (2) unknown ability parameters; (3) item sets with multiple ability scales; and (4) response models with
Diurnal variations of tritium uptake by plants

International Nuclear Information System (INIS)

Hettinger, M.; Diabate, S.; Strack, S.

1991-02-01

The influence of the diurnal cycle is important for the behaviour of environmental tritium in the vegetation. A mathematical model has been used to calculate the deposition of tritium in plants as a function of diurnal variations of climatic parameters. The necessary physiological parameters (relationship of net photosynthesis and growth) were derived from growth experiments for tomatoes and maize. In chamber experiments, tomato and maize plants were exposed to tritium with natural diurnal variations of the climatic conditions. Within the range of standard deviations the measured concentrations of tritium in tissue free water of tomatoes correspond well to the estimated values. Furthermore, the incorporation into non-exchangeable organically bound tritium (OBT nx) can be sufficiently modelled and explained. There are deviations from the estimated concentrations in some parts of maize leaves. (orig.) [de
Variation of Magnetic Field (By , Bz) Polarity and Statistical Analysis of Solar Wind Parameters during the Magnetic Storm Period

OpenAIRE

Ga-Hee Moon

2011-01-01

It is generally believed that the occurrence of a magnetic storm depends upon the solar wind conditions, particularly the southward interplanetary magnetic field (IMF) component. To understand the relationship between solar wind parameters and magnetic storms, variations in magnetic field polarity and solar wind parameters during magnetic storms are examined. A total of 156 storms during the period of 1997~2003 are used. According to the interplanetary driver, magnetic storms are ...
Assessment of input function distortions on kinetic model parameters in simulated dynamic 82Rb PET perfusion studies

International Nuclear Information System (INIS)

Meyer, Carsten; Peligrad, Dragos-Nicolae; Weibrecht, Martin

2007-01-01

Cardiac 82 rubidium dynamic PET studies allow quantifying absolute myocardial perfusion by using tracer kinetic modeling. Here, the accurate measurement of the input function, i.e. the tracer concentration in blood plasma, is a major challenge. This measurement is deteriorated by inappropriate temporal sampling, spillover, etc. Such effects may influence the measured input peak value and the measured blood pool clearance. The aim of our study is to evaluate the effect of input function distortions on the myocardial perfusion as estimated by the model. To this end, we simulate noise-free myocardium time activity curves (TACs) with a two-compartment kinetic model. The input function to the model is a generic analytical function. Distortions of this function have been introduced by varying its parameters. Using the distorted input function, the compartment model has been fitted to the simulated myocardium TAC. This analysis has been performed for various sets of model parameters covering a physiologically relevant range. The evaluation shows that ±10% error in the input peak value can easily lead to ±10-25% error in the model parameter K 1 , which relates to myocardial perfusion. Variations in the input function tail are generally less relevant. We conclude that an accurate estimation especially of the plasma input peak is crucial for a reliable kinetic analysis and blood flow estimation

Variation of inflammatory parameters after sibutramine treatment compared to placebo in type 2 diabetic patients.

Science.gov (United States)

Derosa, G; Maffioli, P; Ferrari, I; Palumbo, I; Randazzo, S; D'Angelo, A; Cicero, A F G

2011-10-01

The efficacy of sibutramine has been demonstrated in randomized trials in obese/overweight patients including those with type 2 diabetes mellitus (T2DM). Our objective was to evaluate the effects of 1-year treatment with sibutramine compared to placebo on body weight, glycaemic control, lipid profile, and inflammatory parameters in type 2 diabetic patients. Two hundred and forty-six patients with uncontrolled T2DM [glycated haemoglobin (HbA(1c) ) > 8·0%] in therapy with different oral hypoglycaemic agents or insulin were randomized to take 10 mg of sibutramine or placebo for 12 months. We evaluated at baseline, and after 3, 6, 9, and 12 months these parameters: body weight, body mass index (BMI), HbA(1c) , fasting plasma glucose (FPG), post-prandial plasma glucose (PPG), fasting plasma insulin (FPI), homeostasis model assessment insulin resistance index (HOMA-IR), total cholesterol (TC), low density lipoprotein-cholesterol (LDL-C), high density lipoprotein-cholesterol (HDL-C), triglycerides (Tg), leptin, tumour necrosis factor-α (TNF-α), adiponectin (ADN), vaspin, high sensitivity C-reactive protein (Hs-CRP). We observed a decrease of body weight after 9 and 12 months in the group treated with sibutramine, but not in the control group. Regarding glycaemic and lipid profile, although there are differences seen over time within each of the groups, we did not obtain any significant differences between the two groups. Both placebo and sibutramine gave a similar improvement of HOMA-IR, leptin, TNF-α, ADN, and Hs-CRP. No vaspin variations were observed in either group. Sibutramine resulted in a decrease in body weight at 9 months and at 12 months that was not observed with placebo. Although there were differences seen over time within each of the groups, there were no significant differences between groups for any other parameter that we measured. © 2010 The Authors. JCPT © 2010 Blackwell Publishing Ltd.
Environmental Transport Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

M. Wasiolek

2004-01-01

This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment for the license application (TSPA-LA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA-LA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]) (TWP). This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA). This report is one of the five reports that develop input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the conceptual model and the mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed description of the model input parameters. The output of this report is used as direct input in the ''Nominal Performance Biosphere Dose Conversion Factor Analysis'' and in the ''Disruptive Event Biosphere Dose Conversion Factor Analysis'' that calculate the values of biosphere dose conversion factors (BDCFs) for the groundwater and volcanic ash exposure scenarios, respectively. The purpose of this analysis was to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or in volcanic ash). The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573])
Environmental Transport Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

M. Wasiolek

2004-09-10

This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment for the license application (TSPA-LA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA-LA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]) (TWP). This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA). This report is one of the five reports that develop input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the conceptual model and the mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed description of the model input parameters. The output of this report is used as direct input in the ''Nominal Performance Biosphere Dose Conversion Factor Analysis'' and in the ''Disruptive Event Biosphere Dose Conversion Factor Analysis'' that calculate the values of biosphere dose conversion factors (BDCFs) for the groundwater and volcanic ash exposure scenarios, respectively. The purpose of this analysis was to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or in volcanic ash). The analysis
Parameters and error of a theoretical model

International Nuclear Information System (INIS)

Moeller, P.; Nix, J.R.; Swiatecki, W.

1986-09-01

We propose a definition for the error of a theoretical model of the type whose parameters are determined from adjustment to experimental data. By applying a standard statistical method, the maximum-likelihoodlmethod, we derive expressions for both the parameters of the theoretical model and its error. We investigate the derived equations by solving them for simulated experimental and theoretical quantities generated by use of random number generators. 2 refs., 4 tabs
ANALYSIS OF THE INTRA-CITY VARIATION OF URBAN HEAT ISLAND AND ITS RELATION TO LAND SURFACE/COVER PARAMETERS

Directory of Open Access Journals (Sweden)

D. Gerçek

2016-06-01

Full Text Available Along with urbanization, sealing of vegetated land and evaporation surfaces by impermeable materials, lead to changes in urban climate. This phenomenon is observed as temperatures several degrees higher in densely urbanized areas compared to the rural land at the urban fringe particularly at nights, so-called Urban Heat Island. Urban Heat Island (UHI effect is related with urban form, pattern and building materials so far as it is associated with meteorological conditions, air pollution, excess heat from cooling. UHI effect has negative influences on human health, as well as other environmental problems such as higher energy demand, air pollution, and water shortage. Urban Heat Island (UHI effect has long been studied by observations of air temperature from thermometers. However, with the advent and proliferation of remote sensing technology, synoptic coverage and better representations of spatial variation of surface temperature became possible. This has opened new avenues for the observation capabilities and research of UHIs. In this study, "UHI effect and its relation to factors that cause it" is explored for İzmit city which has been subject to excess urbanization and industrialization during the past decades. Spatial distribution and variation of UHI effect in İzmit is analysed using Landsat 8 and ASTER day & night images of 2015 summer. Surface temperature data derived from thermal bands of the images were analysed for UHI effect. Higher temperatures were classified into 4 grades of UHIs and mapped both for day and night. Inadequate urban form, pattern, density, high buildings and paved surfaces at the expanse of soil ground and vegetation cover are the main factors that cause microclimates giving rise to spatial variations in temperatures across cities. These factors quantified as land surface/cover parameters for the study include vegetation index (NDVI, imperviousness (NDISI, albedo, solar insolation, Sky View Factor (SVF, building
Analysis of the Intra-City Variation of Urban Heat Island and its Relation to Land Surface/cover Parameters

Science.gov (United States)

Gerçek, D.; Güven, İ. T.; Oktay, İ. Ç.

2016-06-01

Along with urbanization, sealing of vegetated land and evaporation surfaces by impermeable materials, lead to changes in urban climate. This phenomenon is observed as temperatures several degrees higher in densely urbanized areas compared to the rural land at the urban fringe particularly at nights, so-called Urban Heat Island. Urban Heat Island (UHI) effect is related with urban form, pattern and building materials so far as it is associated with meteorological conditions, air pollution, excess heat from cooling. UHI effect has negative influences on human health, as well as other environmental problems such as higher energy demand, air pollution, and water shortage. Urban Heat Island (UHI) effect has long been studied by observations of air temperature from thermometers. However, with the advent and proliferation of remote sensing technology, synoptic coverage and better representations of spatial variation of surface temperature became possible. This has opened new avenues for the observation capabilities and research of UHIs. In this study, "UHI effect and its relation to factors that cause it" is explored for İzmit city which has been subject to excess urbanization and industrialization during the past decades. Spatial distribution and variation of UHI effect in İzmit is analysed using Landsat 8 and ASTER day & night images of 2015 summer. Surface temperature data derived from thermal bands of the images were analysed for UHI effect. Higher temperatures were classified into 4 grades of UHIs and mapped both for day and night. Inadequate urban form, pattern, density, high buildings and paved surfaces at the expanse of soil ground and vegetation cover are the main factors that cause microclimates giving rise to spatial variations in temperatures across cities. These factors quantified as land surface/cover parameters for the study include vegetation index (NDVI), imperviousness (NDISI), albedo, solar insolation, Sky View Factor (SVF), building envelope
SAT-MAP-CLIMATE project results[SATellite base bio-geophysical parameter MAPping and aggregation modelling for CLIMATE models

Energy Technology Data Exchange (ETDEWEB)

Bay Hasager, C.; Woetmann Nielsen, N.; Soegaard, H.; Boegh, E.; Hesselbjerg Christensen, J.; Jensen, N.O.; Schultz Rasmussen, M.; Astrup, P.; Dellwik, E.

2002-08-01

Earth Observation (EO) data from imaging satellites are analysed with respect to albedo, land and sea surface temperatures, land cover types and vegetation parameters such as the Normalized Difference Vegetation Index (NDVI) and the leaf area index (LAI). The observed parameters are used in the DMI-HIRLAM-D05 weather prediction model in order to improve the forecasting. The effect of introducing actual sea surface temperatures from NOAA AVHHR compared to climatological mean values, shows a more pronounced land-sea breeze effect which is also observable in field observations. The albedo maps from NOAA AVHRR are rather similar to the climatological mean values so for the HIRLAM model this is insignicant, yet most likely of some importance in the HIRHAM regional climate model. Land cover type maps are assigned local roughness values determined from meteorological field observations. Only maps with a spatial resolution around 25 m can adequately map the roughness variations of the typical patch size distribution in Denmark. A roughness map covering Denmark is aggregated (ie area-average non-linearly) by a microscale aggregation model that takes the non-linear turbulent responses of each roughness step change between patches in an arbitrary pattern into account. The effective roughnesses are calculated into a 15 km by 15 km grid for the HIRLAM model. The effect of hedgerows is included as an added roughness effect as a function of hedge density mapped from a digital vector map. Introducing the new effective roughness maps into the HIRLAM model appears to remedy on the seasonal wind speed bias over land and sea in spring. A new parameterisation on the effective roughness for scalar surface fluxes is developed and tested on synthetic data. Further is a method for the estimation the evapotranspiration from albedo, surface temperatures and NDVI succesfully compared to field observations. The HIRLAM predictions of water vapour at 12 GMT are used for atmospheric correction of
Application of multi-parameter chorus and plasmaspheric hiss wave models in radiation belt modeling

Science.gov (United States)

Aryan, H.; Kang, S. B.; Balikhin, M. A.; Fok, M. C. H.; Agapitov, O. V.; Komar, C. M.; Kanekal, S. G.; Nagai, T.; Sibeck, D. G.

2017-12-01

Numerical simulation studies of the Earth's radiation belts are important to understand the acceleration and loss of energetic electrons. The Comprehensive Inner Magnetosphere-Ionosphere (CIMI) model along with many other radiation belt models require inputs for pitch angle, energy, and cross diffusion of electrons, due to chorus and plasmaspheric hiss waves. These parameters are calculated using statistical wave distribution models of chorus and plasmaspheric hiss amplitudes. In this study we incorporate recently developed multi-parameter chorus and plasmaspheric hiss wave models based on geomagnetic index and solar wind parameters. We perform CIMI simulations for two geomagnetic storms and compare the flux enhancement of MeV electrons with data from the Van Allen Probes and Akebono satellites. We show that the relativistic electron fluxes calculated with multi-parameter wave models resembles the observations more accurately than the relativistic electron fluxes calculated with single-parameter wave models. This indicates that wave models based on a combination of geomagnetic index and solar wind parameters are more effective as inputs to radiation belt models.
Modelling hydrodynamic parameters to predict flow assisted corrosion

International Nuclear Information System (INIS)

Poulson, B.; Greenwell, B.; Chexal, B.; Horowitz, J.

1992-01-01

During the past 15 years, flow assisted corrosion has been a worldwide problem in the power generating industry. The phenomena is complex and depends on environment, material composition, and hydrodynamic factors. Recently, modeling of flow assisted corrosion has become a subject of great importance. A key part of this effort is modeling the hydrodynamic aspects of this issue. This paper examines which hydrodynamic parameter should be used to correlate the occurrence and rate of flow assisted corrosion with physically meaningful parameters, discusses ways of measuring the relevant hydrodynamic parameter, and describes how the hydrodynamic data is incorporated into the predictive model
Helicopter model rotor-blade vortex interaction impulsive noise: Scalability and parametric variations

Science.gov (United States)

Splettstoesser, W. R.; Schultz, K. J.; Boxwell, D. A.; Schmitz, F. H.

1984-01-01

Acoustic data taken in the anechoic Deutsch-Niederlaendischer Windkanal (DNW) have documented the blade vortex interaction (BVI) impulsive noise radiated from a 1/7-scale model main rotor of the AH-1 series helicopter. Averaged model scale data were compared with averaged full scale, inflight acoustic data under similar nondimensional test conditions. At low advance ratios (mu = 0.164 to 0.194), the data scale remarkable well in level and waveform shape, and also duplicate the directivity pattern of BVI impulsive noise. At moderate advance ratios (mu = 0.224 to 0.270), the scaling deteriorates, suggesting that the model scale rotor is not adequately simulating the full scale BVI noise; presently, no proved explanation of this discrepancy exists. Carefully performed parametric variations over a complete matrix of testing conditions have shown that all of the four governing nondimensional parameters - tip Mach number at hover, advance ratio, local inflow ratio, and thrust coefficient - are highly sensitive to BVI noise radiation.
Modeling response variation for radiometric calorimeters

International Nuclear Information System (INIS)

Mayer, R.L. II.

1986-01-01

Radiometric calorimeters are widely used in the DOE complex for accountability measurements of plutonium and tritium. Proper characterization of response variation for these instruments is, therefore, vital for accurate assessment of measurement control as well as for propagation of error calculations. This is not difficult for instruments used to measure items within a narrow range of power values; however, when a single instrument is used to measure items over a wide range of power values, improper estimates of uncertainty can result since traditional error models for radiometric calorimeters assume that uncertainty is not a function of sample power. This paper describes methods which can be used to accurately estimate random response variation for calorimeters used to measure items over a wide range of sample powers. The model is applicable to the two most common modes of calorimeter operation: heater replacement and servo control. 5 refs., 4 figs., 1 tab
Modelling regional variation of first-time births in Denmark 1980-1994 by an age-period-cohort model

Directory of Open Access Journals (Sweden)

Lisbeth B. Knudsen

2005-12-01

Full Text Available Despite the small size of Denmark, there have traditionally been rather consistent regional differences in fertility rates. We apply the statistical age-period-cohort model to include the effect of these three time-related factors thereby concisely illuminating the regional differences of first-time births in Denmark. From the Fertility of Women and Couples Dataset we obtain data on number of births by nulliparous women by year (1980-1994, age (15-45 and county of residence. We show that the APC-model describes the fertility rates of nulliparous women satisfactorily. To catch the regional variation an interaction parameter between age and county is necessary, which provides a surprisingly good description suggesting that the county-specific age-distributions of first-time fertility rates differ. Our results are in general agreement with the 'moral geography' concepts of Tonboe (2001.
Modelling regional variation of first-time births in Denmark 1980-1994 by an age-period-cohort model

DEFF Research Database (Denmark)

Thygesen, Lau Caspar; Knudsen, Lisbeth B.; Keiding, Niels

2005-01-01

Despite the small size of Denmark, there have traditionally been rather consistent regional differences in fertility rates. We apply the statistical age-period-cohort model to include the effect of these three time-related factors thereby concisely illuminating the regional differences of first......-time births in Denmark. From the Fertility of Women and Couples Dataset we obtain data on number of births by nulliparous women by year (1980-1994), age (15-45) and county of residence. We show that the APC-model describes the fertility rates of nulliparous women satisfactorily. To catch the regional...... variation an interaction parameter between age and county is necessary, which provides a surprisingly good description suggesting that the county-specific age-distributions of first-time fertility rates differ. Our results are in general agreement with the 'moral geography' concepts of Tonboe (2001)....
Long-term solar wind electron variations between 1971 and 1978

International Nuclear Information System (INIS)

Feldman, W.C.; Asbridge, J.R.; Bame, S.J.; Gosling, J.T.

1979-01-01

Imp solar wind electron data measured between 1971 and 1978 were studied with the aim of determining long-term variations near the earth. Two separate sets of parameter variations were observed: (1) in 1976--1977 the solar wind density, the electron temperature, and the interplanetary electrostatic potential were all enhanced, and (2) the halo density and associated electron parameters were all depressed during a 1 1/2-year period centered on the last 6 months of 1976. Although interpretation of these results in terms of corresponding coronal and interplanetary variations is not unique, it may be significant that measured solar wind parameters near the minimum of solar cycle 20 agree better with the Hartle-Sturrock model of the coronal expansion than they do during other epochs
Modeling the dependency of radon concentration levels inside ancient Egyptian tombs on the ambient temperature variations

Energy Technology Data Exchange (ETDEWEB)

Metwally, S M; Abo-Elmagdb, M [Faculty of Science, Department of Physics, Ain Shams University, P. O. Box 11566, Cairo (Egypt); Salamaa, E [National Institute for Standard, Radiation Measurements Department, Cairo (Egypt)

2007-06-15

Radon concentration inside partially closed places like dwellings, caves and tombs, depends on many parameters. Some parameters are known quantitatively as radon exhalation rate for walls, decay constant, surface to volume ratio and outdoor concentration while other parameters as ventilation rate is in common known qualitatively due to useless of traditional methods (tracer gases) in many places as ancient Egyptian tombs. This work introduces a derived mathematical model to evaluate the sensitivity of radon concentration levels inside single sided opening places as ancient Egyptian tombs on the ambient temperature differences. The obtained formula for the natural ventilation rate depends on the indoor and outdoor temperature difference and the geometrical dimensions of the doorway. The effects of in and out flow mixing, air viscosity, streamline contraction, swirling flow and turbulence, were taken into consideration in terms of an empirical correction factor. According UNSCEAR reports, the exhalation rate {phi}=C{sub ra}{lambda}{sub rn} f{rho}{sub s}(1-{epsilon})L; C{sub ra} the effective radium content, {lambda}{sub rn} decay constant, f emanation fraction, {rho}{sub s} soil grain density, {epsilon} porosity and L diffusion length, these are approximately static parameters but the variability of ambient temperature introduces a source of energy of fluctuating strength to radon atoms in rocks which controls the flow rate and the ambient content of radon. Therefore, the change of outdoor and indoor temperature difference causes fluctuation of value and direction of volume flow rate in such places consequently causes the daily variation and on average the seasonal variation of radon concentration. Therefore according to the present model, the daily accurate expectation of radon concentrations inside ancient Egyptian tombs, require precise measurements of indoor and outdoor temperatures.
EEJ and EIA variations during modeling substorms with different onset moments

Science.gov (United States)

Klimenko, V. V.; Klimenko, M. V.

2015-11-01

This paper presents the simulations of four modeling substorms with different moment of substorm onset at 00:00 UT, 06:00 UT, 12:00 UT, and 18:00 UT for spring equinoctial conditions in solar activity minimum. Such investigation provides opportunity to examine the longitudinal dependence of ionospheric response to geomagnetic substorms. Model runs were performed using modified Global Self-consistent Model of the Thermosphere, Ionosphere and Protonosphere (GSM TIP). We analyzed GSM TIP simulated global distributions of foF2, low latitude electric field and ionospheric currents at geomagnetic equator and their disturbances at different UT moments substorms. We considered in more detail the variations in equatorial ionization anomaly, equatorial electrojet and counter equatorial electrojet during substorms. It is shown that: (1) the effects in EIA, EEJ and CEJ strongly depend on the substorm onset moment; (2) disturbances in equatorial zonal current density during substorm has significant longitudinal dependence; (3) the observed controversy on the equatorial ionospheric electric field signature of substorms can depend on the substorm onset moments, i.e., on the longitudinal variability in parameters of the thermosphere-ionosphere system.
Multivariate-parameter optimization of aroma compound release from carbohydrate-oil-protein model emulsions.

Science.gov (United States)

Samavati, Vahid; D-jomeh, Zahra Emam

2013-11-06

Optimization for retention and partition coefficient of ethyl acetate in emulsion model systems was investigated using response surface methodology in this paper. The effects of emulsion model ingredients, tragacanth gum (TG) (0.5-1 wt%), whey protein isolate (WPI) (2-4 wt%) and oleic acid (5-10%, v/v) on retention and partition coefficient of ethyl acetate were studied using a five-level three-factor central composite rotatable design (CCRD). Results showed that the regression models generated adequately explained the data variation and significantly represented the actual relationships between the independent and response parameters. The results showed that the highest retention (97.20±0.51%) and lowest partition coefficient (4.51±0.13%) of ethyl acetate were reached at the TG concentration 1 wt%, WPI concentration 4 wt% and oleic acid volume fraction 10% (v/v). Copyright © 2013 Elsevier Ltd. All rights reserved.
Variations of 57Fe hyperfine parameters in medicaments containing ferrous fumarate and ferrous sulfate

International Nuclear Information System (INIS)

Oshtrakh, M. I.; Novikov, E. G.; Dubiel, S. M.; Semionkin, V. A.

2010-01-01

Several commercially available medicaments containing ferrous fumarate (FeC 4 H 2 O 4 ) and ferrous sulfate (FeSO 4 ), as a source of ferrous iron, were studied using a high velocity resolution Mössbauer spectroscopy. A comparison of the 57 Fe hyperfine parameters revealed small variations for the main components in both medicaments indicating some differences in the ferrous fumarates and ferrous sulfates. It was also found that all spectra contained additional minor components probably related to ferrous and ferric impurities or to partially modified main components.
WINKLER'S SINGLE-PARAMETER SUBGRADE MODEL FROM ...

African Journals Online (AJOL)

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Page 1 ... corresponding single-parameter Winkler model presented in this work. Keywords: Heterogeneous subgrade, Reissner's simplified continuum, Shear interaction, Simplified continuum, Winkler ... model in practical applications and its long time familiarity among practical engineers, its usage has endured to this date ...
Insight into model mechanisms through automatic parameter fitting: a new methodological framework for model development.

Science.gov (United States)

Tøndel, Kristin; Niederer, Steven A; Land, Sander; Smith, Nicolas P

2014-05-20

Striking a balance between the degree of model complexity and parameter identifiability, while still producing biologically feasible simulations using modelling is a major challenge in computational biology. While these two elements of model development are closely coupled, parameter fitting from measured data and analysis of model mechanisms have traditionally been performed separately and sequentially. This process produces potential mismatches between model and data complexities that can compromise the ability of computational frameworks to reveal mechanistic insights or predict new behaviour. In this study we address this issue by presenting a generic framework for combined model parameterisation, comparison of model alternatives and analysis of model mechanisms. The presented methodology is based on a combination of multivariate metamodelling (statistical approximation of the input-output relationships of deterministic models) and a systematic zooming into biologically feasible regions of the parameter space by iterative generation of new experimental designs and look-up of simulations in the proximity of the measured data. The parameter fitting pipeline includes an implicit sensitivity analysis and analysis of parameter identifiability, making it suitable for testing hypotheses for model reduction. Using this approach, under-constrained model parameters, as well as the coupling between parameters within the model are identified. The methodology is demonstrated by refitting the parameters of a published model of cardiac cellular mechanics using a combination of measured data and synthetic data from an alternative model of the same system. Using this approach, reduced models with simplified expressions for the tropomyosin/crossbridge kinetics were found by identification of model components that can be omitted without affecting the fit to the parameterising data. Our analysis revealed that model parameters could be constrained to a standard deviation of on

Modelling of intermittent microwave convective drying: parameter sensitivity

Directory of Open Access Journals (Sweden)

Zhang Zhijun

2017-06-01

Full Text Available The reliability of the predictions of a mathematical model is a prerequisite to its utilization. A multiphase porous media model of intermittent microwave convective drying is developed based on the literature. The model considers the liquid water, gas and solid matrix inside of food. The model is simulated by COMSOL software. Its sensitivity parameter is analysed by changing the parameter values by ±20%, with the exception of several parameters. The sensitivity analysis of the process of the microwave power level shows that each parameter: ambient temperature, effective gas diffusivity, and evaporation rate constant, has significant effects on the process. However, the surface mass, heat transfer coefficient, relative and intrinsic permeability of the gas, and capillary diffusivity of water do not have a considerable effect. The evaporation rate constant has minimal parameter sensitivity with a ±20% value change, until it is changed 10-fold. In all results, the temperature and vapour pressure curves show the same trends as the moisture content curve. However, the water saturation at the medium surface and in the centre show different results. Vapour transfer is the major mass transfer phenomenon that affects the drying process.
Long-period variations of wind parameters in the mesopause region and the solar cycle dependence

International Nuclear Information System (INIS)

Greisiger, K.M.; Schminder, R.; Kuerschner, D.

1987-01-01

The solar cycle dependence of wind parameters below 100 km on the basis of long term continuous ionospheric drift measurements in the low frequency range is discussed. For the meridional prevailing wind no significant variation was found. The same comparison as for winter was done for summer where the previous investigations gave no correlation. Now the radar meteor wind measurement values, too, showed a significant negative correlation of the zonal prevailing wind with solar activity for the years 1976 to 1983. The ionospheric drift measurement results of Collm have the same tendency but a larger dispersion due to the lower accuracy of the harmonic analysis because of the shorter daily measuring interval in summer. Continuous wind observations in the upper mesopause region over more than 20 years revealed distinct long term variations, the origin of which cannot be explained with the present knowledge
Retrospective forecast of ETAS model with daily parameters estimate

Science.gov (United States)

Falcone, Giuseppe; Murru, Maura; Console, Rodolfo; Marzocchi, Warner; Zhuang, Jiancang

2016-04-01

We present a retrospective ETAS (Epidemic Type of Aftershock Sequence) model based on the daily updating of free parameters during the background, the learning and the test phase of a seismic sequence. The idea was born after the 2011 Tohoku-Oki earthquake. The CSEP (Collaboratory for the Study of Earthquake Predictability) Center in Japan provided an appropriate testing benchmark for the five 1-day submitted models. Of all the models, only one was able to successfully predict the number of events that really happened. This result was verified using both the real time and the revised catalogs. The main cause of the failure was in the underestimation of the forecasted events, due to model parameters maintained fixed during the test. Moreover, the absence in the learning catalog of an event similar to the magnitude of the mainshock (M9.0), which drastically changed the seismicity in the area, made the learning parameters not suitable to describe the real seismicity. As an example of this methodological development we show the evolution of the model parameters during the last two strong seismic sequences in Italy: the 2009 L'Aquila and the 2012 Reggio Emilia episodes. The achievement of the model with daily updated parameters is compared with that of same model where the parameters remain fixed during the test time.
Parameter identification in multinomial processing tree models

NARCIS (Netherlands)

Schmittmann, V.D.; Dolan, C.V.; Raijmakers, M.E.J.; Batchelder, W.H.

2010-01-01

Multinomial processing tree models form a popular class of statistical models for categorical data that have applications in various areas of psychological research. As in all statistical models, establishing which parameters are identified is necessary for model inference and selection on the basis
Variation of different humification parameters during two composting types with lignicellulosics residual of roses

International Nuclear Information System (INIS)

Farias Camero, Diana Maria; Ballesteros G, Maria Ines; Bendeck L, Myriam

2000-01-01

Two composting processes were carried out; they lasted for about 165 days. In one of the processes only microorganisms performed the decomposition of the material only (direct composting) and in the other one by microorganisms and earthworms -Eisenia foetida- (indirect composting) Periodical samples were taken from different places of the pile and a temperature control was made weekly. Organic total carbon was analyzed in each sample, an organic matter extraction and fractionation was carried out with a mixture 1 M sodium hydroxide and 1M-sodium pyrophosphate in each sample too. Organic total carbon was quantified in the separated fractions, humic extract, humic acids, fulvic acids and humines; different humification parameters were calculated as of those results: Humification ratio, humification index, polymerization ratio, percentage of humic acids and no extractable organic carbon -extractable carbon ratio. E4/E6 ratio, oxygen, hydrogen, nitrogen and carbon content, C/H, C/O and C/N ratios were analyzed on humic acids. Humification parameters variation allows us to analyze the humic substances transformation and formation dynamics are limited by composting system and temperature generated and maintained. It was established that extractable carbon percent and CNoExt/Cext ratio cannot be considered as satisfactory parameters in order to evaluate the stabilization compost degree; polymerization ratio and humification index are the most adequate parameters to determinate the material humification degree
Prediction of the working parameters of a wood waste gasifier through an equilibrium model

Energy Technology Data Exchange (ETDEWEB)

Altafini, Carlos R.; Baretto, Ronaldo M. [Caxias do Sul Univ., Dept. of Mechanical Engineering, Caxias do Sul, RS (Brazil); Wander, Paulo R. [Caxias do Sul Univ., Dept. of Mechanical Engineering, Caxias do Sul, RS (Brazil); Federal Univ. of Rio Grande do Sul State (UFRGS), Mechanical Engineering Postgraduation Program (PROMEC), RS (Brazil)

2003-10-01

This paper deals with the computational simulation of a wood waste (sawdust) gasifier using an equilibrium model based on minimization of the Gibbs free energy. The gasifier has been tested with Pinus Elliotis sawdust, an exotic specie largely cultivated in the South of Brazil. The biomass used in the tests presented a moisture of nearly 10% (wt% on wet basis), and the average composition results of the gas produced (without tar) are compared with the equilibrium models used. Sensitivity studies to verify the influence of the moisture sawdust content on the fuel gas composition and on its heating value were made. More complex models to reproduce with better accuracy the gasifier studied were elaborated. Although the equilibrium models do not represent the reactions that occur at relatively high temperatures ( {approx_equal} 800 deg C) very well, these models can be useful to show some tendencies on the working parameter variations of a gasifier. (Author)
Modeling Per Capita State Health Expenditure Variat...

Data.gov (United States)

U.S. Department of Health & Human Services — Modeling Per Capita State Health Expenditure Variation State-Level Characteristics Matter, published in Volume 3, Issue 4, of the Medicare and Medicaid Research...
The Prediction of Length-of-day Variations Based on Gaussian Processes

Science.gov (United States)

Lei, Y.; Zhao, D. N.; Gao, Y. P.; Cai, H. B.

2015-01-01

Due to the complicated time-varying characteristics of the length-of-day (LOD) variations, the accuracies of traditional strategies for the prediction of the LOD variations such as the least squares extrapolation model, the time-series analysis model, and so on, have not met the requirements for real-time and high-precision applications. In this paper, a new machine learning algorithm --- the Gaussian process (GP) model is employed to forecast the LOD variations. Its prediction precisions are analyzed and compared with those of the back propagation neural networks (BPNN), general regression neural networks (GRNN) models, and the Earth Orientation Parameters Prediction Comparison Campaign (EOP PCC). The results demonstrate that the application of the GP model to the prediction of the LOD variations is efficient and feasible.
Equilibrium models and variational inequalities

CERN Document Server

Konnov, Igor

2007-01-01

The concept of equilibrium plays a central role in various applied sciences, such as physics (especially, mechanics), economics, engineering, transportation, sociology, chemistry, biology and other fields. If one can formulate the equilibrium problem in the form of a mathematical model, solutions of the corresponding problem can be used for forecasting the future behavior of very complex systems and, also, for correcting the the current state of the system under control. This book presents a unifying look on different equilibrium concepts in economics, including several models from related sciences.- Presents a unifying look on different equilibrium concepts and also the present state of investigations in this field- Describes static and dynamic input-output models, Walras, Cassel-Wald, spatial price, auction market, oligopolistic equilibrium models, transportation and migration equilibrium models- Covers the basics of theory and solution methods both for the complementarity and variational inequality probl...
Modelling the Probability Density Function of IPTV Traffic Packet Delay Variation

Directory of Open Access Journals (Sweden)

Michal Halas

2012-01-01

Full Text Available This article deals with modelling the Probability density function of IPTV traffic packet delay variation. The use of this modelling is in an efficient de-jitter buffer estimation. When an IP packet travels across a network, it experiences delay and its variation. This variation is caused by routing, queueing systems and other influences like the processing delay of the network nodes. When we try to separate these at least three types of delay variation, we need a way to measure these types separately. This work is aimed to the delay variation caused by queueing systems which has the main implications to the form of the Probability density function.
Phase diagram of the Shastry-Sutherland Kondo lattice model with classical localized spins: a variational calculation study

Science.gov (United States)

Shahzad, Munir; Sengupta, Pinaki

2017-08-01

We study the Shastry-Sutherland Kondo lattice model with additional Dzyaloshinskii-Moriya (DM) interactions, exploring the possible magnetic phases in its multi-dimensional parameter space. Treating the local moments as classical spins and using a variational ansatz, we identify the parameter ranges over which various common magnetic orderings are potentially stabilized. Our results reveal that the competing interactions result in a heightened susceptibility towards a wide range of spin configurations including longitudinal ferromagnetic and antiferromagnetic order, coplanar flux configurations and most interestingly, multiple non-coplanar configurations including a novel canted-flux state as the different Hamiltonian parameters like electron density, interaction strengths and degree of frustration are varied. The non-coplanar and non-collinear magnetic ordering of localized spins behave like emergent electromagnetic fields and drive unusual transport and electronic phenomena.
The "covariation method" for estimating the parameters of the standard Dynamic Energy Budget model II: Properties and preliminary patterns

Science.gov (United States)

Lika, Konstadia; Kearney, Michael R.; Kooijman, Sebastiaan A. L. M.

2011-11-01

The covariation method for estimating the parameters of the standard Dynamic Energy Budget (DEB) model provides a single-step method of accessing all the core DEB parameters from commonly available empirical data. In this study, we assess the robustness of this parameter estimation procedure and analyse the role of pseudo-data using elasticity coefficients. In particular, we compare the performance of Maximum Likelihood (ML) vs. Weighted Least Squares (WLS) approaches and find that the two approaches tend to converge in performance as the number of uni-variate data sets increases, but that WLS is more robust when data sets comprise single points (zero-variate data). The efficiency of the approach is shown to be high, and the prior parameter estimates (pseudo-data) have very little influence if the real data contain information about the parameter values. For instance, the effects of the pseudo-value for the allocation fraction κ is reduced when there is information for both growth and reproduction, that for the energy conductance is reduced when information on age at birth and puberty is given, and the effects of the pseudo-value for the maturity maintenance rate coefficient are insignificant. The estimation of some parameters (e.g., the zoom factor and the shape coefficient) requires little information, while that of others (e.g., maturity maintenance rate, puberty threshold and reproduction efficiency) require data at several food levels. The generality of the standard DEB model, in combination with the estimation of all of its parameters, allows comparison of species on the basis of parameter values. We discuss a number of preliminary patterns emerging from the present collection of parameter estimates across a wide variety of taxa. We make the observation that the estimated value of the fraction κ of mobilised reserve that is allocated to soma is far away from the value that maximises reproduction. We recognise this as the reason why two very different
Analysis of Electrical Coupling Parameters in Superconducting Cables

CERN Document Server

Bottura, L; Rosso, C

2003-01-01

The analysis of current distribution and redistribution in superconducting cables requires the knowledge of the electric coupling among strands, and in particular the interstrand resistance and inductance values. In practice both parameters can have wide variations in cables commonly used such as Rutherford cables for accelerators or Cable-in-Conduits for fusion and SMES magnets. In this paper we describe a model of a multi-stage twisted cable with arbitrary geometry that can be used to study the range of interstrand resistances and inductances that is associated with variations of geometry. These variations can be due to cabling or compaction effects. To describe the variations from the nominal geometry we have adopted a cable model that resembles to the physical process of cabling and compaction. The inductance calculation part of the model is validated by comparison to semi-analytical results, showing excellent accuracy and execution speed.
Lumped-parameters equivalent circuit for condenser microphones modeling.

Science.gov (United States)

Esteves, Josué; Rufer, Libor; Ekeom, Didace; Basrour, Skandar

2017-10-01

This work presents a lumped parameters equivalent model of condenser microphone based on analogies between acoustic, mechanical, fluidic, and electrical domains. Parameters of the model were determined mainly through analytical relations and/or finite element method (FEM) simulations. Special attention was paid to the air gap modeling and to the use of proper boundary condition. Corresponding lumped-parameters were obtained as results of FEM simulations. Because of its simplicity, the model allows a fast simulation and is readily usable for microphone design. This work shows the validation of the equivalent circuit on three real cases of capacitive microphones, including both traditional and Micro-Electro-Mechanical Systems structures. In all cases, it has been demonstrated that the sensitivity and other related data obtained from the equivalent circuit are in very good agreement with available measurement data.
Analysis of Modeling Parameters on Threaded Screws.

Energy Technology Data Exchange (ETDEWEB)

Vigil, Miquela S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brake, Matthew Robert [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vangoethem, Douglas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-06-01

Assembled mechanical systems often contain a large number of bolted connections. These bolted connections (joints) are integral aspects of the load path for structural dynamics, and, consequently, are paramount for calculating a structure's stiffness and energy dissipation prop- erties. However, analysts have not found the optimal method to model appropriately these bolted joints. The complexity of the screw geometry cause issues when generating a mesh of the model. This paper will explore different approaches to model a screw-substrate connec- tion. Model parameters such as mesh continuity, node alignment, wedge angles, and thread to body element size ratios are examined. The results of this study will give analysts a better understanding of the influences of these parameters and will aide in finding the optimal method to model bolted connections.
Parameter Estimates in Differential Equation Models for Chemical Kinetics

Science.gov (United States)

Winkel, Brian

2011-01-01

We discuss the need for devoting time in differential equations courses to modelling and the completion of the modelling process with efforts to estimate the parameters in the models using data. We estimate the parameters present in several differential equation models of chemical reactions of order n, where n = 0, 1, 2, and apply more general…
Simultaneous inference for model averaging of derived parameters

DEFF Research Database (Denmark)

Jensen, Signe Marie; Ritz, Christian

2015-01-01

Model averaging is a useful approach for capturing uncertainty due to model selection. Currently, this uncertainty is often quantified by means of approximations that do not easily extend to simultaneous inference. Moreover, in practice there is a need for both model averaging and simultaneous...... inference for derived parameters calculated in an after-fitting step. We propose a method for obtaining asymptotically correct standard errors for one or several model-averaged estimates of derived parameters and for obtaining simultaneous confidence intervals that asymptotically control the family...
Parameter identification in the logistic STAR model

DEFF Research Database (Denmark)

Ekner, Line Elvstrøm; Nejstgaard, Emil

We propose a new and simple parametrization of the so-called speed of transition parameter of the logistic smooth transition autoregressive (LSTAR) model. The new parametrization highlights that a consequence of the well-known identification problem of the speed of transition parameter is that th...
Regionalization of SWAT Model Parameters for Use in Ungauged Watersheds

Directory of Open Access Journals (Sweden)

Indrajeet Chaubey

2010-11-01

Full Text Available There has been a steady shift towards modeling and model-based approaches as primary methods of assessing watershed response to hydrologic inputs and land management, and of quantifying watershed-wide best management practice (BMP effectiveness. Watershed models often require some degree of calibration and validation to achieve adequate watershed and therefore BMP representation. This is, however, only possible for gauged watersheds. There are many watersheds for which there are very little or no monitoring data available, thus the question as to whether it would be possible to extend and/or generalize model parameters obtained through calibration of gauged watersheds to ungauged watersheds within the same region. This study explored the possibility of developing regionalized model parameter sets for use in ungauged watersheds. The study evaluated two regionalization methods: global averaging, and regression-based parameters, on the SWAT model using data from priority watersheds in Arkansas. Resulting parameters were tested and model performance determined on three gauged watersheds. Nash-Sutcliffe efficiencies (NS for stream flow obtained using regression-based parameters (0.53–0.83 compared well with corresponding values obtained through model calibration (0.45–0.90. Model performance obtained using global averaged parameter values was also generally acceptable (0.4 ≤ NS ≤ 0.75. Results from this study indicate that regionalized parameter sets for the SWAT model can be obtained and used for making satisfactory hydrologic response predictions in ungauged watersheds.
Soil-related Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

A. J. Smith

2003-01-01

This analysis is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the geologic repository at Yucca Mountain. The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A graphical representation of the documentation hierarchy for the ERMYN biosphere model is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003 [163602]). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. ''The Biosphere Model Report'' (BSC 2003 [160699]) describes in detail the conceptual model as well as the mathematical model and its input parameters. The purpose of this analysis was to develop the biosphere model parameters needed to evaluate doses from pathways associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation and ash

Multiwavelength light curve parameters of Cepheid variables

Directory of Open Access Journals (Sweden)

Bhardwaj Anupam

2017-01-01

Full Text Available We present a comparative analysis of theoretical and observed light curves of Cepheid variables using Fourier decomposition. The theoretical light curves at multiple wavelengths are generated using stellar pulsation models for chemical compositions representative of Cepheids in the Galaxy and Magellanic Clouds. The observed light curves at optical (VI, near-infrared (JHKs and mid-infrared (3.6 & 4.5-μm bands are compiled from the literature. We discuss the variation of light curve parameters as a function of period, wavelength and metallicity. Theoretical and observed Fourier amplitude parameters decrease with increase in wavelength while the phase parameters increase with wavelength. We find that theoretical amplitude parameters obtained using canonical mass-luminosity levels exhibit a greater offset with respect to observations when compared to non-canonical relations. We also discuss the impact of variation in convective efficiency on the light curve structure of Cepheid variables. The increase in mixing length parameter results in a zero-point offset in bolometric mean magnitudes and reduces the systematic large difference in theoretical amplitudes with respect to observations.
Inhalation Exposure Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

K. Rautenstrauch

2004-09-10

This analysis is one of 10 reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. Inhalation Exposure Input Parameters for the Biosphere Model is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the Technical Work Plan for Biosphere Modeling and Expert Support (BSC 2004 [DIRS 169573]). This analysis report defines and justifies values of mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception.
Inhalation Exposure Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

K. Rautenstrauch

2004-01-01

This analysis is one of 10 reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. Inhalation Exposure Input Parameters for the Biosphere Model is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the Technical Work Plan for Biosphere Modeling and Expert Support (BSC 2004 [DIRS 169573]). This analysis report defines and justifies values of mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception
Modeling and Parameter Estimation of a Small Wind Generation System

Directory of Open Access Journals (Sweden)

Carlos A. Ramírez Gómez

2013-11-01

Full Text Available The modeling and parameter estimation of a small wind generation system is presented in this paper. The system consists of a wind turbine, a permanent magnet synchronous generator, a three phase rectifier, and a direct current load. In order to estimate the parameters wind speed data are registered in a weather station located in the Fraternidad Campus at ITM. Wind speed data were applied to a reference model programed with PSIM software. From that simulation, variables were registered to estimate the parameters. The wind generation system model together with the estimated parameters is an excellent representation of the detailed model, but the estimated model offers a higher flexibility than the programed model in PSIM software.
Improving weather predictability by including land-surface model parameter uncertainty

Science.gov (United States)

Orth, Rene; Dutra, Emanuel; Pappenberger, Florian

2016-04-01

The land surface forms an important component of Earth system models and interacts nonlinearly with other parts such as ocean and atmosphere. To capture the complex and heterogenous hydrology of the land surface, land surface models include a large number of parameters impacting the coupling to other components of the Earth system model. Focusing on ECMWF's land-surface model HTESSEL we present in this study a comprehensive parameter sensitivity evaluation using multiple observational datasets in Europe. We select 6 poorly constrained effective parameters (surface runoff effective depth, skin conductivity, minimum stomatal resistance, maximum interception, soil moisture stress function shape, total soil depth) and explore their sensitivity to model outputs such as soil moisture, evapotranspiration and runoff using uncoupled simulations and coupled seasonal forecasts. Additionally we investigate the possibility to construct ensembles from the multiple land surface parameters. In the uncoupled runs we find that minimum stomatal resistance and total soil depth have the most influence on model performance. Forecast skill scores are moreover sensitive to the same parameters as HTESSEL performance in the uncoupled analysis. We demonstrate the robustness of our findings by comparing multiple best performing parameter sets and multiple randomly chosen parameter sets. We find better temperature and precipitation forecast skill with the best-performing parameter perturbations demonstrating representativeness of model performance across uncoupled (and hence less computationally demanding) and coupled settings. Finally, we construct ensemble forecasts from ensemble members derived with different best-performing parameterizations of HTESSEL. This incorporation of parameter uncertainty in the ensemble generation yields an increase in forecast skill, even beyond the skill of the default system. Orth, R., E. Dutra, and F. Pappenberger, 2016: Improving weather predictability by
Variational approach to chiral quark models

Energy Technology Data Exchange (ETDEWEB)

Futami, Yasuhiko; Odajima, Yasuhiko; Suzuki, Akira

1987-03-01

A variational approach is applied to a chiral quark model to test the validity of the perturbative treatment of the pion-quark interaction based on the chiral symmetry principle. It is indispensably related to the chiral symmetry breaking radius if the pion-quark interaction can be regarded as a perturbation.
Hybrid artificial bee colony algorithm for parameter optimization of five-parameter bidirectional reflectance distribution function model.

Science.gov (United States)

Wang, Qianqian; Zhao, Jing; Gong, Yong; Hao, Qun; Peng, Zhong

2017-11-20

A hybrid artificial bee colony (ABC) algorithm inspired by the best-so-far solution and bacterial chemotaxis was introduced to optimize the parameters of the five-parameter bidirectional reflectance distribution function (BRDF) model. To verify the performance of the hybrid ABC algorithm, we measured BRDF of three kinds of samples and simulated the undetermined parameters of the five-parameter BRDF model using the hybrid ABC algorithm and the genetic algorithm, respectively. The experimental results demonstrate that the hybrid ABC algorithm outperforms the genetic algorithm in convergence speed, accuracy, and time efficiency under the same conditions.
SPOTting Model Parameters Using a Ready-Made Python Package.

Directory of Open Access Journals (Sweden)

Tobias Houska

Full Text Available The choice for specific parameter estimation methods is often more dependent on its availability than its performance. We developed SPOTPY (Statistical Parameter Optimization Tool, an open source python package containing a comprehensive set of methods typically used to calibrate, analyze and optimize parameters for a wide range of ecological models. SPOTPY currently contains eight widely used algorithms, 11 objective functions, and can sample from eight parameter distributions. SPOTPY has a model-independent structure and can be run in parallel from the workstation to large computation clusters using the Message Passing Interface (MPI. We tested SPOTPY in five different case studies to parameterize the Rosenbrock, Griewank and Ackley functions, a one-dimensional physically based soil moisture routine, where we searched for parameters of the van Genuchten-Mualem function and a calibration of a biogeochemistry model with different objective functions. The case studies reveal that the implemented SPOTPY methods can be used for any model with just a minimal amount of code for maximal power of parameter optimization. They further show the benefit of having one package at hand that includes number of well performing parameter search methods, since not every case study can be solved sufficiently with every algorithm or every objective function.
Hydrological model parameter dimensionality is a weak measure of prediction uncertainty

Science.gov (United States)

Pande, S.; Arkesteijn, L.; Savenije, H.; Bastidas, L. A.

2015-04-01

This paper shows that instability of hydrological system representation in response to different pieces of information and associated prediction uncertainty is a function of model complexity. After demonstrating the connection between unstable model representation and model complexity, complexity is analyzed in a step by step manner. This is done measuring differences between simulations of a model under different realizations of input forcings. Algorithms are then suggested to estimate model complexity. Model complexities of the two model structures, SAC-SMA (Sacramento Soil Moisture Accounting) and its simplified version SIXPAR (Six Parameter Model), are computed on resampled input data sets from basins that span across the continental US. The model complexities for SIXPAR are estimated for various parameter ranges. It is shown that complexity of SIXPAR increases with lower storage capacity and/or higher recession coefficients. Thus it is argued that a conceptually simple model structure, such as SIXPAR, can be more complex than an intuitively more complex model structure, such as SAC-SMA for certain parameter ranges. We therefore contend that magnitudes of feasible model parameters influence the complexity of the model selection problem just as parameter dimensionality (number of parameters) does and that parameter dimensionality is an incomplete indicator of stability of hydrological model selection and prediction problems.
Parameter identification and global sensitivity analysis of Xin'anjiang model using meta-modeling approach

Directory of Open Access Journals (Sweden)

Xiao-meng Song

2013-01-01

Full Text Available Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on (1 a screening method (Morris for qualitative ranking of parameters, and (2 a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model (RSMSobol. First, the Morris screening method was used to qualitatively identify the parameters' sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model (RSM were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.
Estimation of Parameters in Mean-Reverting Stochastic Systems

Directory of Open Access Journals (Sweden)

Tianhai Tian

2014-01-01

Full Text Available Stochastic differential equation (SDE is a very important mathematical tool to describe complex systems in which noise plays an important role. SDE models have been widely used to study the dynamic properties of various nonlinear systems in biology, engineering, finance, and economics, as well as physical sciences. Since a SDE can generate unlimited numbers of trajectories, it is difficult to estimate model parameters based on experimental observations which may represent only one trajectory of the stochastic model. Although substantial research efforts have been made to develop effective methods, it is still a challenge to infer unknown parameters in SDE models from observations that may have large variations. Using an interest rate model as a test problem, in this work we use the Bayesian inference and Markov Chain Monte Carlo method to estimate unknown parameters in SDE models.
Iterative choice of the optimal regularization parameter in TV image deconvolution

International Nuclear Information System (INIS)

Sixou, B; Toma, A; Peyrin, F; Denis, L

2013-01-01

We present an iterative method for choosing the optimal regularization parameter for the linear inverse problem of Total Variation image deconvolution. This approach is based on the Morozov discrepancy principle and on an exponential model function for the data term. The Total Variation image deconvolution is performed with the Alternating Direction Method of Multipliers (ADMM). With a smoothed l 2 norm, the differentiability of the value of the Lagrangian at the saddle point can be shown and an approximate model function obtained. The choice of the optimal parameter can be refined with a Newton method. The efficiency of the method is demonstrated on a blurred and noisy bone CT cross section
Updating parameters of the chicken processing line model

DEFF Research Database (Denmark)

Kurowicka, Dorota; Nauta, Maarten; Jozwiak, Katarzyna

2010-01-01

A mathematical model of chicken processing that quantitatively describes the transmission of Campylobacter on chicken carcasses from slaughter to chicken meat product has been developed in Nauta et al. (2005). This model was quantified with expert judgment. Recent availability of data allows...... updating parameters of the model to better describe processes observed in slaughterhouses. We propose Bayesian updating as a suitable technique to update expert judgment with microbiological data. Berrang and Dickens’s data are used to demonstrate performance of this method in updating parameters...... of the chicken processing line model....
Role of deceleration parameter and interacting dark energy in singularity avoidance

Science.gov (United States)

Abdussattar; Prajapati, S. R.

2011-02-01

A class of non-singular bouncing FRW models are obtained by constraining the deceleration parameter in the presence of an interacting dark energy represented by a time-varying cosmological constant. The models being geometrically closed, initially accelerate for a certain period of time and decelerate thereafter and are also free from the entropy and cosmological constant problems. Taking a constant of integration equal to zero one particular model is discussed in some detail and the variation of different cosmological parameters are shown graphically for specific values of the parameters of the model. For some specific choice of the parameters of the model the ever expanding models of Ozer & Taha and Abdel-Rahman and the decelerating models of Berman and also the Einstein de-Sitter model may be obtained as special cases of this particular model.
Variation of thermophysical parameters of PCM CaCl2.6H2O with dopant from T-history data analysis

Science.gov (United States)

Sutjahja, I. M.; Silalahi, Alfriska O.; Sukmawati, Nissa; Kurnia, D.; Wonorahardjo, S.

2018-03-01

T-history is a powerful method for deriving the thermophysical parameters of a phase change material (PCM), which consists of solid and liquid specific heats as well as latent heat enthalpy. The performance of a PCM for thermal energy storage could be altered by chemical dopants added directly to the PCM in order to form a stable suspension. We described in this paper the role of chemical dopants in the variation of thermophysical parameters for CaCl2 · 6H2O inorganic PCM with 1 wt% and 2 wt% dopant concentration and BaSO4 (1 wt%) as a nucleator using the T-history method. The dopant consists graphite and CuO nanoparticles. The data analysis follows the original method proposed by (Zhang et al 1999 Meas. Sci. Technol. 10 201–205) and its modification by (Hong et al 2004 Int. J. Refrig. 27 360–366). In addition, the enthalpy-temperature curve is obtained by adopting a method proposed by (Marín et al 2003 Meas. Sci. Technol. 14 184–189). We found that the solid specific heat tends to increase non-linearly with increased dopant concentration for all dopants. The increased liquid specific heat, however, indicates the optimum value for 1 wt% graphite dopant. In contrast, the CuO dopant shows a smaller increase in dopant concentration. The specific heat data are analyzed based on the interacting mesolayer model for a nanofluid. The heat of fusion show strong variation with dopant type, in agreement with other experimental data for various PCMs and dopant particles.
Classical algorithms for automated parameter-search methods in compartmental neural models - A critical survey based on simulations using neuron

International Nuclear Information System (INIS)

Mutihac, R.; Mutihac, R.C.; Cicuttin, A.

2001-09-01

Parameter-search methods are problem-sensitive. All methods depend on some meta-parameters of their own, which must be determined experimentally in advance. A better choice of these intrinsic parameters for a certain parameter-search method may improve its performance. Moreover, there are various implementations of the same method, which may also affect its performance. The choice of the matching (error) function has a great impact on the search process in terms of finding the optimal parameter set and minimizing the computational cost. An initial assessment of the matching function ability to distinguish between good and bad models is recommended, before launching exhaustive computations. However, different runs of a parameter search method may result in the same optimal parameter set or in different parameter sets (the model is insufficiently constrained to accurately characterize the real system). Robustness of the parameter set is expressed by the extent to which small perturbations in the parameter values are not affecting the best solution. A parameter set that is not robust is unlikely to be physiologically relevant. Robustness can also be defined as the stability of the optimal parameter set to small variations of the inputs. When trying to estimate things like the minimum, or the least-squares optimal parameters of a nonlinear system, the existence of multiple local minima can cause problems with the determination of the global optimum. Techniques such as Newton's method, the Simplex method and Least-squares Linear Taylor Differential correction technique can be useful provided that one is lucky enough to start sufficiently close to the global minimum. All these methods suffer from the inability to distinguish a local minimum from a global one because they follow the local gradients towards the minimum, even if some methods are resetting the search direction when it is likely to get stuck in presumably a local minimum. Deterministic methods based on
Parameter identification of civil engineering structures

Science.gov (United States)

Juang, J. N.; Sun, C. T.

1980-01-01

This paper concerns the development of an identification method required in determining structural parameter variations for systems subjected to an extended exposure to the environment. The concept of structural identifiability of a large scale structural system in the absence of damping is presented. Three criteria are established indicating that a large number of system parameters (the coefficient parameters of the differential equations) can be identified by a few actuators and sensors. An eight-bay-fifteen-story frame structure is used as example. A simple model is employed for analyzing the dynamic response of the frame structure.
Genetic Parameter Estimates for Metabolizing Two Common Pharmaceuticals in Swine

Directory of Open Access Journals (Sweden)

Jeremy T. Howard

2018-02-01

Full Text Available In livestock, the regulation of drugs used to treat livestock has received increased attention and it is currently unknown how much of the phenotypic variation in drug metabolism is due to the genetics of an animal. Therefore, the objective of the study was to determine the amount of phenotypic variation in fenbendazole and flunixin meglumine drug metabolism due to genetics. The population consisted of crossbred female and castrated male nursery pigs (n = 198 that were sired by boars represented by four breeds. The animals were spread across nine batches. Drugs were administered intravenously and blood collected a minimum of 10 times over a 48 h period. Genetic parameters for the parent drug and metabolite concentration within each drug were estimated based on pharmacokinetics (PK parameters or concentrations across time utilizing a random regression model. The PK parameters were estimated using a non-compartmental analysis. The PK model included fixed effects of sex and breed of sire along with random sire and batch effects. The random regression model utilized Legendre polynomials and included a fixed population concentration curve, sex, and breed of sire effects along with a random sire deviation from the population curve and batch effect. The sire effect included the intercept for all models except for the fenbendazole metabolite (i.e., intercept and slope. The mean heritability across PK parameters for the fenbendazole and flunixin meglumine parent drug (metabolite was 0.15 (0.18 and 0.31 (0.40, respectively. For the parent drug (metabolite, the mean heritability across time was 0.27 (0.60 and 0.14 (0.44 for fenbendazole and flunixin meglumine, respectively. The errors surrounding the heritability estimates for the random regression model were smaller compared to estimates obtained from PK parameters. Across both the PK and plasma drug concentration across model, a moderate heritability was estimated. The model that utilized the plasma drug
Genetic Parameter Estimates for Metabolizing Two Common Pharmaceuticals in Swine

Science.gov (United States)

Howard, Jeremy T.; Ashwell, Melissa S.; Baynes, Ronald E.; Brooks, James D.; Yeatts, James L.; Maltecca, Christian

2018-01-01

In livestock, the regulation of drugs used to treat livestock has received increased attention and it is currently unknown how much of the phenotypic variation in drug metabolism is due to the genetics of an animal. Therefore, the objective of the study was to determine the amount of phenotypic variation in fenbendazole and flunixin meglumine drug metabolism due to genetics. The population consisted of crossbred female and castrated male nursery pigs (n = 198) that were sired by boars represented by four breeds. The animals were spread across nine batches. Drugs were administered intravenously and blood collected a minimum of 10 times over a 48 h period. Genetic parameters for the parent drug and metabolite concentration within each drug were estimated based on pharmacokinetics (PK) parameters or concentrations across time utilizing a random regression model. The PK parameters were estimated using a non-compartmental analysis. The PK model included fixed effects of sex and breed of sire along with random sire and batch effects. The random regression model utilized Legendre polynomials and included a fixed population concentration curve, sex, and breed of sire effects along with a random sire deviation from the population curve and batch effect. The sire effect included the intercept for all models except for the fenbendazole metabolite (i.e., intercept and slope). The mean heritability across PK parameters for the fenbendazole and flunixin meglumine parent drug (metabolite) was 0.15 (0.18) and 0.31 (0.40), respectively. For the parent drug (metabolite), the mean heritability across time was 0.27 (0.60) and 0.14 (0.44) for fenbendazole and flunixin meglumine, respectively. The errors surrounding the heritability estimates for the random regression model were smaller compared to estimates obtained from PK parameters. Across both the PK and plasma drug concentration across model, a moderate heritability was estimated. The model that utilized the plasma drug
THE EVIL-MC MODEL FOR ELLIPSOIDAL VARIATIONS OF PLANET-HOSTING STARS AND APPLICATIONS TO THE HAT-P-7 SYSTEM

Energy Technology Data Exchange (ETDEWEB)

Jackson, Brian K. [Carnegie Institution for Science, Washington, DC 20015 (United States); Lewis, Nikole K.; Showman, Adam P. [Lunar and Planetary Laboratory, University of Arizona, Kuiper Space Sciences Building, Tucson, AZ 85721 (United States); Barnes, Jason W. [Department of Physics, University of Idaho, Engineering-Physics Building, Moscow, ID 83844 (United States); Deming, L. Drake [Department of Astronomy, University of Maryland, College Park, MD 20742 (United States); Fortney, Jonathan J., E-mail: bjackson@dtm.ciw.edu [Department of Astronomy and Astrophysics, UCO/Lick Observatory, University of California, Santa Cruz, CA 95064 (United States)

2012-06-01

We present a new model for Ellipsoidal Variations Induced by a Low-Mass Companion, the EVIL-MC model. We employ several approximations appropriate for planetary systems to substantially increase the computational efficiency of our model relative to more general ellipsoidal variation models and improve upon the accuracy of simpler models. This new approach gives us a unique ability to rapidly and accurately determine planetary system parameters. We use the EVIL-MC model to analyze Kepler Quarter 0-2 (Q0-2) observations of the HAT-P-7 system, an F-type star orbited by a {approx} Jupiter-mass companion. Our analysis corroborates previous estimates of the planet-star mass ratio q = (1.10 {+-} 0.06) Multiplication-Sign 10{sup -3}, and we have revised the planet's dayside brightness temperature to 2680{sup +10}{sub -20} K. We also find a large difference between the day- and nightside planetary flux, with little nightside emission. Preliminary dynamical+radiative modeling of the atmosphere indicates that this result is qualitatively consistent with high altitude absorption of stellar heating. Similar analyses of Kepler and CoRoT photometry of other planets using EVIL-MC will play a key role in providing constraints on the properties of many extrasolar systems, especially given the limited resources for follow-up and characterization of these systems. However, as we highlight, there are important degeneracies between the contributions from ellipsoidal variations and planetary emission and reflection. Consequently, for many of the hottest and brightest Kepler and CoRoT planets, accurate estimates of the planetary emission and reflection, diagnostic of atmospheric heat budgets, will require accurate modeling of the photometric contribution from the stellar ellipsoidal variation.

Setting Parameters for Biological Models With ANIMO

NARCIS (Netherlands)

Schivo, Stefano; Scholma, Jetse; Karperien, Hermanus Bernardus Johannes; Post, Janine Nicole; van de Pol, Jan Cornelis; Langerak, Romanus; André, Étienne; Frehse, Goran

2014-01-01

ANIMO (Analysis of Networks with Interactive MOdeling) is a software for modeling biological networks, such as e.g. signaling, metabolic or gene networks. An ANIMO model is essentially the sum of a network topology and a number of interaction parameters. The topology describes the interactions
Constant-parameter capture-recapture models

Science.gov (United States)

Brownie, C.; Hines, J.E.; Nichols, J.D.

1986-01-01

Jolly (1982, Biometrics 38, 301-321) presented modifications of the Jolly-Seber model for capture-recapture data, which assume constant survival and/or capture rates. Where appropriate, because of the reduced number of parameters, these models lead to more efficient estimators than the Jolly-Seber model. The tests to compare models given by Jolly do not make complete use of the data, and we present here the appropriate modifications, and also indicate how to carry out goodness-of-fit tests which utilize individual capture history information. We also describe analogous models for the case where young and adult animals are tagged. The availability of computer programs to perform the analysis is noted, and examples are given using output from these programs.
Cilengitide-induced temporal variations in transvascular transfer parameters of tumor vasculature in a rat glioma model: identifying potential MRI biomarkers of acute effects.

Directory of Open Access Journals (Sweden)

Tavarekere N Nagaraja

Full Text Available Increased efficacy of radiotherapy (RT 4-8 h after Cilengitide treatment has been reported. We hypothesized that the effects of Cilengitide on tumor transvascular transfer parameters might underlie, and thus predict, this potentiation. Athymic rats with orthotopic U251 glioma were studied at ~21 days after implantation using dynamic contrast-enhanced (DCE-MRI. Vascular parameters, viz: plasma volume fraction (v(p, forward volume transfer constant (K(trans and interstitial volume fraction (v(e of a contrast agent, were determined in tumor vasculature once before, and again in cohorts 2, 4, 8, 12 and 24 h after Cilengitide administration (4 mg/kg; N = 31; 6-7 per cohort. Perfusion-fixed brain sections were stained for von Willebrand factor to visualize vascular segments. A comparison of pre- and post-treatment parameters showed that the differences between MR indices before and after Cilengitide treatment pivoted around the 8 h time point, with 2 and 4 h groups showing increases, 12 and 24 h groups showing decreases, and values at the 8 h time point close to the baseline. The vascular parameter differences between group of 2 and 4 h and group of 12 and 24 h were significant for K(trans (p = 0.0001 and v(e (p = 0,0271. Vascular staining showed little variation with time after Cilengitide. The vascular normalization occurring 8 h after Cilengitide treatment coincided with similar previous reports of increased treatment efficacy when RT followed Cilengitide by 8 h. Pharmacological normalization of vasculature has the potential to increase sensitivity to RT. Evaluating acute temporal responses of tumor vasculature to putative anti-angiogenic drugs may help in optimizing their combination with other treatment modalities.
On conditions and parameters important to model sensitivity for unsaturated flow through layered, fractured tuff

International Nuclear Information System (INIS)

Prindle, R.W.; Hopkins, P.L.

1990-10-01

The Hydrologic Code Intercomparison Project (HYDROCOIN) was formed to evaluate hydrogeologic models and computer codes and their use in performance assessment for high-level radioactive-waste repositories. This report describes the results of a study for HYDROCOIN of model sensitivity for isothermal, unsaturated flow through layered, fractured tuffs. We investigated both the types of flow behavior that dominate the performance measures and the conditions and model parameters that control flow behavior. We also examined the effect of different conceptual models and modeling approaches on our understanding of system behavior. The analyses included single- and multiple-parameter variations about base cases in one-dimensional steady and transient flow and in two-dimensional steady flow. The flow behavior is complex even for the highly simplified and constrained system modeled here. The response of the performance measures is both nonlinear and nonmonotonic. System behavior is dominated by abrupt transitions from matrix to fracture flow and by lateral diversion of flow. The observed behaviors are strongly influenced by the imposed boundary conditions and model constraints. Applied flux plays a critical role in determining the flow type but interacts strongly with the composite-conductivity curves of individual hydrologic units and with the stratigraphy. One-dimensional modeling yields conservative estimates of distributions of groundwater travel time only under very limited conditions. This study demonstrates that it is wrong to equate the shortest possible water-travel path with the fastest path from the repository to the water table. 20 refs., 234 figs., 10 tabs
Ground level enhancement (GLE) energy spectrum parameters model

Science.gov (United States)

Qin, G.; Wu, S.

2017-12-01

We study the ground level enhancement (GLE) events in solar cycle 23 with the four energy spectra parameters, the normalization parameter C, low-energy power-law slope γ 1, high-energy power-law slope γ 2, and break energy E0, obtained by Mewaldt et al. 2012 who fit the observations to the double power-law equation. we divide the GLEs into two groups, one with strong acceleration by interplanetary (IP) shocks and another one without strong acceleration according to the condition of solar eruptions. We next fit the four parameters with solar event conditions to get models of the parameters for the two groups of GLEs separately. So that we would establish a model of energy spectrum for GLEs for the future space weather prediction.
Introductory biology students' conceptual models and explanations of the origin of variation.

Science.gov (United States)

Speth, Elena Bray; Shaw, Neil; Momsen, Jennifer; Reinagel, Adam; Le, Paul; Taqieddin, Ranya; Long, Tammy

2014-01-01

Mutation is the key molecular mechanism generating phenotypic variation, which is the basis for evolution. In an introductory biology course, we used a model-based pedagogy that enabled students to integrate their understanding of genetics and evolution within multiple case studies. We used student-generated conceptual models to assess understanding of the origin of variation. By midterm, only a small percentage of students articulated complete and accurate representations of the origin of variation in their models. Targeted feedback was offered through activities requiring students to critically evaluate peers' models. At semester's end, a substantial proportion of students significantly improved their representation of how variation arises (though one-third still did not include mutation in their models). Students' written explanations of the origin of variation were mostly consistent with their models, although less effective than models in conveying mechanistic reasoning. This study contributes evidence that articulating the genetic origin of variation is particularly challenging for learners and may require multiple cycles of instruction, assessment, and feedback. To support meaningful learning of the origin of variation, we advocate instruction that explicitly integrates multiple scales of biological organization, assessment that promotes and reveals mechanistic and causal reasoning, and practice with explanatory models with formative feedback. © 2014 E. Bray Speth et al. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
I. Nuclear and neutron matter calculations with isobars. II. A model calculation of Fermi liquid parameters for liquid 3He

International Nuclear Information System (INIS)

Ainsworth, T.L.

1983-01-01

The Δ(1232) plays an important role in determining the properties of nuclear and neutron matter. The effects of the Δ resonance are incorporated explicitly by using a coupled channel formalism. A method for constraining a lowest order variational calculation, appropriate when nucleon internal degrees of freedom are made explicity, is presented. Different N-N potentials were calculated and fit to phase shift data and deuteron properties. The potentials were constructed to test the relative importance of the Δ resonance on nuclear properties. The symmetry energy and incompressibility of nuclear matter are generally reproduced by this calculation. Neutron matter results lead to appealing neutron star models. Fermi liquid parameters for 3 He are calculated with a model that includes both direct and induced terms. A convenient form of the direct interaction is obtained in terms of the parameters. The form of the direct interaction ensures that the forward scattering sum rule (Pauli principle) is obeyed. The parameters are adjusted to fit the experimentally determined F 0 /sup s/, F 0 /sup a/, and F 1 /sup s/ Landau parameters. Higher order Landau parameters are calculated by the self-consistent solution of the equations; comparison to experiment is good. The model also leads to a preferred value for the effective mass of 3 He. Of the three parameters only one shows any dependence on pressure. An exact sum rule is derived relating this parameter to a specific summation of Landau parameters
Variational theory of valence fluctuations: Ground states and quasiparticle excitations of the Anderson lattice model

Science.gov (United States)

Brandow, B. H.

1986-01-01

A variational study of ground states of the orbitally nondegenerate Anderson lattice model, using a wave function with one variational parameter per Bloch state k, has been extended to deal with essentially metallic systems having a nonintegral number of electrons per site. Quasiparticle excitations are obtained by direct appeal to Landau's original definition for interacting Fermi liquids, scrEqp(k,σ)=δEtotal/δn qp(k,σ). This approach provides a simple and explicit realization of the Luttinger picture of a periodic Fermi liquid. A close correspondence is maintained between the ``interacting'' (U=∞) system and the corresponding ``noninteracting'' (U=0) case, i.e., ordinary band theory; the result can be described as a renormalized band or renormalized hybridization theory. The occupation-number distribution for the conduction orbitals displays a finite discontinuity at the Fermi surface. If the d-f hybridization is nonzero throughout the Brillouin zone, the quasiparticle spectrum will always exhibit a gap, although this gap becomes exponentially small (i.e., of order TK) in the Kondo-lattice regime. In the ``ionic'' case with precisely two electrons per site, such a system may therefore exhibit an insulating (semiconducting) gap. The quasiparticle state density exhibits a prominent spike on each side of the spectral gap, just as in the elementary hybridization model (the U=0 case). For the metallic case, with a nonintegral number of electrons per site, the Fermi level falls within one of the two sharp density peaks. The effective mass at the Fermi surface tends to be very large; enhancements by a factor >~102 are quite feasible. The foregoing variational theory has also been refined by means of a trial wave function having two variational parameters per Bloch state k. The above qualitative features are all retained, with some quantitative differences, but there are also some qualitatively new features. The most interesting of these is the appearance, within
Parameter Estimation of Spacecraft Fuel Slosh Model

Science.gov (United States)

Gangadharan, Sathya; Sudermann, James; Marlowe, Andrea; Njengam Charles

2004-01-01

Fuel slosh in the upper stages of a spinning spacecraft during launch has been a long standing concern for the success of a space mission. Energy loss through the movement of the liquid fuel in the fuel tank affects the gyroscopic stability of the spacecraft and leads to nutation (wobble) which can cause devastating control issues. The rate at which nutation develops (defined by Nutation Time Constant (NTC can be tedious to calculate and largely inaccurate if done during the early stages of spacecraft design. Pure analytical means of predicting the influence of onboard liquids have generally failed. A strong need exists to identify and model the conditions of resonance between nutation motion and liquid modes and to understand the general characteristics of the liquid motion that causes the problem in spinning spacecraft. A 3-D computerized model of the fuel slosh that accounts for any resonant modes found in the experimental testing will allow for increased accuracy in the overall modeling process. Development of a more accurate model of the fuel slosh currently lies in a more generalized 3-D computerized model incorporating masses, springs and dampers. Parameters describing the model include the inertia tensor of the fuel, spring constants, and damper coefficients. Refinement and understanding the effects of these parameters allow for a more accurate simulation of fuel slosh. The current research will focus on developing models of different complexity and estimating the model parameters that will ultimately provide a more realistic prediction of Nutation Time Constant obtained through simulation.
MVP: A Simple and Effective Model to Simulate the Mean and Variation of Photosynthetically Active Radiation Under Discrete Forest Canopies

Science.gov (United States)

Song, C.; Band, L. E.

2003-12-01

The spatial patterns of Photosynthetically Active Radiation (PAR) under forest canopies, including both its mean and spatial variation, are critical factors that determine numerous ecophysiological processes in plant ecosystems. Though numerous models have been developed that can accurately simulate PAR transmission through plant canopies, Beer's law remains the primary model used in ecological models to describe PAR transmission through plant canopies due to the fact that the more accurate models are too complicated to be used operationally. This study developed a simple and computationally efficient model to simulate both the Mean and Variation of PAR (MVP) under the forest canopy. The model provides a careful description of the effects of gaps on the variable light environment under forest canopy, while it simplifies the simulation of multiple scattering of photons. The model assumes that a forest canopy is composed of individual crowns distributed within upper and lower boundaries with two types of gaps: the between- and within-crown gaps. The inputs to the model are canopy structural parameters, including canopy depth, tree count density, tree crown shape, and foliage area volume density (m2/m3, leaf areas per unit crown volume). The between-crown gaps are simulated with geometric optics, and the within-crown gaps are described by Beer's law. The model accounts for the covariance of PAR in space through time, making it possible to simulate both instantaneous variation of PAR and variation of daily accumulated PAR. Validation with observed PAR using ten quantum sensors under the Old Black Spruce stand at the Southern Study Area of the BOREAS project indicates the model captures the mean and variation of PAR under forest canopy reasonably well. The model is simple enough that it can be used by other ecological models, such as ecosystem dynamics and carbon budget models. Further validation and testing of the model with other types forest are needed in the future.
Soil-Related Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

Smith, A. J.

2004-01-01

This report presents one of the analyses that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the details of the conceptual model as well as the mathematical model and the required input parameters. The biosphere model is one of a series of process models supporting the postclosure Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A schematic representation of the documentation flow for the Biosphere input to TSPA is presented in Figure 1-1. This figure shows the evolutionary relationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (TWP) (BSC 2004 [DIRS 169573]). This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil-Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. The purpose of this analysis was to develop the biosphere model parameters associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation or ash deposition and, as a direct consequence, radionuclide concentration in other environmental media that are affected by radionuclide concentrations in soil. The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573]) where the governing procedure was defined as AP-SIII.9Q, ''Scientific Analyses''. This
The SSI TOOLBOX Source Term Model SOSIM - Screening for important radionuclides and parameter sensitivity analysis

Energy Technology Data Exchange (ETDEWEB)

Avila Moreno, R.; Barrdahl, R.; Haegg, C.

1995-05-01

The main objective of the present study was to carry out a screening and a sensitivity analysis of the SSI TOOLBOX source term model SOSIM. This model is a part of the SSI TOOLBOX for radiological impact assessment of the Swedish disposal concept for high-level waste KBS-3. The outputs of interest for this purpose were: the total released fraction, the time of total release, the time and value of maximum release rate, the dose rates after direct releases of the biosphere. The source term equations were derived and simple equations and methods were proposed for calculation of these. A literature survey has been performed in order to determine a characteristic variation range and a nominal value for each model parameter. In order to reduce the model uncertainties the authors recommend a change in the initial boundary condition for solution of the diffusion equation for highly soluble nuclides. 13 refs.
Variations of {sup 57}Fe hyperfine parameters in medicaments containing ferrous fumarate and ferrous sulfate

Energy Technology Data Exchange (ETDEWEB)

Oshtrakh, M. I., E-mail: oshtrakh@mail.utnet.ru; Novikov, E. G. [Ural Federal University (The former Ural State Technical University-UPI), Faculty of Physical Techniques and Devices for Quality Control (Russian Federation); Dubiel, S. M. [AGH University of Science and Technology, Faculty of Physics and Computer Science (Poland); Semionkin, V. A. [Ural Federal University (The former Ural State Technical University-UPI), Faculty of Physical Techniques and Devices for Quality Control (Russian Federation)

2010-04-15

Several commercially available medicaments containing ferrous fumarate (FeC{sub 4}H{sub 2}O{sub 4}) and ferrous sulfate (FeSO{sub 4}), as a source of ferrous iron, were studied using a high velocity resolution Moessbauer spectroscopy. A comparison of the {sup 57}Fe hyperfine parameters revealed small variations for the main components in both medicaments indicating some differences in the ferrous fumarates and ferrous sulfates. It was also found that all spectra contained additional minor components probably related to ferrous and ferric impurities or to partially modified main components.
Improving filtering and prediction of spatially extended turbulent systems with model errors through stochastic parameter estimation

International Nuclear Information System (INIS)

Gershgorin, B.; Harlim, J.; Majda, A.J.

2010-01-01

The filtering and predictive skill for turbulent signals is often limited by the lack of information about the true dynamics of the system and by our inability to resolve the assumed dynamics with sufficiently high resolution using the current computing power. The standard approach is to use a simple yet rich family of constant parameters to account for model errors through parameterization. This approach can have significant skill by fitting the parameters to some statistical feature of the true signal; however in the context of real-time prediction, such a strategy performs poorly when intermittent transitions to instability occur. Alternatively, we need a set of dynamic parameters. One strategy for estimating parameters on the fly is a stochastic parameter estimation through partial observations of the true signal. In this paper, we extend our newly developed stochastic parameter estimation strategy, the Stochastic Parameterization Extended Kalman Filter (SPEKF), to filtering sparsely observed spatially extended turbulent systems which exhibit abrupt stability transition from time to time despite a stable average behavior. For our primary numerical example, we consider a turbulent system of externally forced barotropic Rossby waves with instability introduced through intermittent negative damping. We find high filtering skill of SPEKF applied to this toy model even in the case of very sparse observations (with only 15 out of the 105 grid points observed) and with unspecified external forcing and damping. Additive and multiplicative bias corrections are used to learn the unknown features of the true dynamics from observations. We also present a comprehensive study of predictive skill in the one-mode context including the robustness toward variation of stochastic parameters, imperfect initial conditions and finite ensemble effect. Furthermore, the proposed stochastic parameter estimation scheme applied to the same spatially extended Rossby wave system demonstrates
Analysis of groundwater discharge with a lumped-parameter model, using a case study from Tajikistan

Science.gov (United States)

Pozdniakov, S. P.; Shestakov, V. M.

A lumped-parameter model of groundwater balance is proposed that permits an estimate of discharge variability in comparison with the variability of recharge, by taking into account the influence of aquifer parameters. Recharge-discharge relationships are analysed with the model for cases of deterministic and stochastic recharge time-series variations. The model is applied to study the temporal variability of groundwater discharge in a river valley in the territory of Tajikistan, an independent republic in Central Asia. Résumé Un modèle global de bilan d'eau souterraine a été développé pour estimer la variabilité de l'écoulement par rapport à celle de la recharge, en prenant en compte l'influence des paramètres de l'aquifère. Les relations entre recharge et écoulement sont analysées à l'aide du modèle pour des variations des chroniques de recharge soit déterministes, soit stochastiques. Le modèle est appliquéà l'étude de la variabilité temporelle de l'écoulement souterrain vers une rivière, dans le Tadjikistan, une république indépendante d'Asie centrale. Resumen Se propone un modelo de parámetros concentrados para realizar el balance de aguas subterráneas, el cual permite estimar la variabilidad en la descarga con respecto a la variabilidad en la recarga, en función de los parámetros que caracterizan el acuífero. Las relaciones entre recarga y descarga se analizan con el modelo para distintos casos de series temporales de recarga, tanto deterministas como estocásticas. El modelo se aplica al estudio de la variabilidad temporal de la descarga en un valle aluvial de Tadyikistán, una república independiente del Asia Central.
Modeling stimulus variation in three common implicit attitude tasks.

Science.gov (United States)

Wolsiefer, Katie; Westfall, Jacob; Judd, Charles M

2017-08-01

We explored the consequences of ignoring the sampling variation due to stimuli in the domain of implicit attitudes. A large literature in psycholinguistics has examined the statistical treatment of random stimulus materials, but the recommendations from this literature have not been applied to the social psychological literature on implicit attitudes. This is partly because of inherent complications in applying crossed random-effect models to some of the most common implicit attitude tasks, and partly because no work to date has demonstrated that random stimulus variation is in fact consequential in implicit attitude measurement. We addressed this problem by laying out statistically appropriate and practically feasible crossed random-effect models for three of the most commonly used implicit attitude measures-the Implicit Association Test, affect misattribution procedure, and evaluative priming task-and then applying these models to large datasets (average N = 3,206) that assess participants' implicit attitudes toward race, politics, and self-esteem. We showed that the test statistics from the traditional analyses are substantially (about 60 %) inflated relative to the more-appropriate analyses that incorporate stimulus variation. Because all three tasks used the same stimulus words and faces, we could also meaningfully compare the relative contributions of stimulus variation across the tasks. In an appendix, we give syntax in R, SAS, and SPSS for fitting the recommended crossed random-effects models to data from all three tasks, as well as instructions on how to structure the data file.
A possible model of growth and production of durum wheat (Triticum durum Desf.) in relation to meteorological parameters in Mediterranean environment

International Nuclear Information System (INIS)

Tuttobene, R.; Cosentino, S.; Cavallaro, V.

1993-01-01

This research aimed at studying a simulation model to describe the growth and yield of durum wheat in relation to meterological parameters in Mediterranean environment, using data of trials carried out by the Institute of Agronomy and filed crops of the University of Catania in two years and three localities of the Eastern Sicily. The model is divided into four modules which determine separately main phenological phases, leaf area index, total biomass and yield and soil water balance. The model uses air maximum and minimum temperature, photoperiod, solar radiation, rainfall and evaporation from a class A pan. Simulation carried out on the data of the trials showed a good interpretation of the variability of the actual data in relation to meteorological parameters. The model could simulate the variation due to plant density and sowing date. The model should be verified using independent data [it
A model reduction approach for the variational estimation of vascular compliance by solving an inverse fluid–structure interaction problem

International Nuclear Information System (INIS)

Bertagna, Luca; Veneziani, Alessandro

2014-01-01

Scientific computing has progressively become an important tool for research in cardiovascular diseases. The role of quantitative analyses based on numerical simulations has moved from ‘proofs of concept’ to patient-specific investigations, thanks to a strong integration between imaging and computational tools. However, beyond individual geometries, numerical models require the knowledge of parameters that are barely retrieved from measurements, especially in vivo. For this reason, recently cardiovascular mathematics considered data assimilation procedures for extracting the knowledge of patient-specific parameters from measures and images. In this paper, we consider specifically the quantification of vascular compliance, i.e. the parameter quantifying the tendency of arterial walls to deform under blood stress. Following up a previous paper, where a variational data assimilation procedure was proposed, based on solving an inverse fluid–structure interaction problem, here we consider model reduction techniques based on a proper orthogonal decomposition approach to accomplish the solution of the inverse problem in a computationally efficient way. (paper)
Variation in plasmonic (electronic) spectral parameters of Pr (III) and Nd (III) with varied concentration of moderators

Energy Technology Data Exchange (ETDEWEB)

Mishra, Shubha, E-mail: shubhamishra03@gmail.com [School of Studies in Physics, Vikram University, Ujjain (M. P.) (India); Limaye, S. N., E-mail: snl222@yahoo.co.in [Department of Chemistry, Dr. H.S. Gour University, A Central University, Sagar (M.P.) (India)

2015-07-31

It is said that the -4f shells behave as core and are least perturbed by changes around metal ion surrounding. However, there are evidences that-4f shells partially involved in direct moderator interaction. A systematic investigation on the plasmonic (electronic) spectral studies of some Rare Earths[RE(III).Mod] where, RE(III) = Pr(III),Nd(III) and Mod(moderator) = Y(III),La(III),Gd(III) and Lu(III), increased moderator concentration from 0.01 mol dm{sup −3} to 0.025 mol dm{sup −3} keeping the metal ion concentration at 0.01mol dm{sup −3} have been carried out. Variations in oscillator strengths (f), Judd-Ofelt parameters (T{sub λ}),inter-electronic repulsion Racah parameters (δE{sup k}),nephelauxetic ratio (β), radiative parameters (S{sub ED},A{sub T},β{sub R},T{sub R}). The values of oscillator strengths and Judd-Ofelt parameters have been discussed in the light of coordination number of RE(III) metal ions, denticity and basicity of the moderators. The [RE(III).Mod] bonding pattern has been studies in the light of the change in Racah parameters and nephelauxetic ratio.
Localization of the dynamic two-parameter subgrid-scale model and application to near-wall turbulent flows

International Nuclear Information System (INIS)

Wang, B.; Bergstrom, D.J.

2002-01-01

The dynamic two-parameter mixed model (DTPMM) has been recently introduced in the large eddy simulation (LES). However, current approaches in the literatures are mathematically inconsistent. In this paper, the DTPMM has been optimized using the functional variational method. The mathematical inconsistency has been removed and a governing system of two integral equations for the model coefficients of the DTPMM and some significant features have been obtained. Coherent structures relating to the vortex motion of large vortices have been investigated, using the vortex λ 2 -definition of Jeong and Hussain (1995). The numerical results agrees with the classical wall law of von Karman (1939) and experimental correlation of Aydin and Leutheusser (1991). (author)

Parameter estimation in nonlinear models for pesticide degradation

International Nuclear Information System (INIS)

Richter, O.; Pestemer, W.; Bunte, D.; Diekkrueger, B.

1991-01-01

A wide class of environmental transfer models is formulated as ordinary or partial differential equations. With the availability of fast computers, the numerical solution of large systems became feasible. The main difficulty in performing a realistic and convincing simulation of the fate of a substance in the biosphere is not the implementation of numerical techniques but rather the incomplete data basis for parameter estimation. Parameter estimation is a synonym for statistical and numerical procedures to derive reasonable numerical values for model parameters from data. The classical method is the familiar linear regression technique which dates back to the 18th century. Because it is easy to handle, linear regression has long been established as a convenient tool for analysing relationships. However, the wide use of linear regression has led to an overemphasis of linear relationships. In nature, most relationships are nonlinear and linearization often gives a poor approximation of reality. Furthermore, pure regression models are not capable to map the dynamics of a process. Therefore, realistic models involve the evolution in time (and space). This leads in a natural way to the formulation of differential equations. To establish the link between data and dynamical models, numerical advanced parameter identification methods have been developed in recent years. This paper demonstrates the application of these techniques to estimation problems in the field of pesticide dynamics. (7 refs., 5 figs., 2 tabs.)
Studies on seasonal variation in water quality parameters of Rana Pratap Sagar lake (1996-99)

International Nuclear Information System (INIS)

Verma, R.; Rout, D.; Purohit, K.C.

2000-01-01

Water- chemistry monitoring identifies the concentration and patterns of fluctuation in chemical constituents. This information is essential to project future trends monitoring in Lake Water chemistry to identify any potential for affecting plant operation through scaling or corrosion of the circulating and service-water system equipment. Regular water chemistry monitoring provides a useful record of past. This record helps in identification of conditions that would impair station operations before their onset, allowing remedial action to be undertaken before plant performance is significantly affected. Preventive action to control the parameters influencing the corrosion, scaling and bio-fouling in the cooling system, in turn, eliminates excessive maintenance and premature replacement that otherwise would result from damage caused by unforeseen changes in the cooling water. This paper highlights the systematic monitoring approach for the variation of chemical parameters influenced by the seasonal changes in a total period of four years. (author)
Biological parameters for lung cancer in mathematical models of carcinogenesis

International Nuclear Information System (INIS)

Jacob, P.; Jacob, V.

2003-01-01

Applications of the two-step model of carcinogenesis with clonal expansion (TSCE) to lung cancer data are reviewed, including those on atomic bomb survivors from Hiroshima and Nagasaki, British doctors, Colorado Plateau miners, and Chinese tin miners. Different sets of identifiable model parameters are used in the literature. The parameter set which could be determined with the lowest uncertainty consists of the net proliferation rate gamma of intermediate cells, the hazard h 55 at an intermediate age, and the hazard H? at an asymptotically large age. Also, the values of these three parameters obtained in the various studies are more consistent than other identifiable combinations of the biological parameters. Based on representative results for these three parameters, implications for the biological parameters in the TSCE model are derived. (author)
Variation in immune parameters and disease prevalence among Lesser Black-backed Gulls (Larus fuscus sp. with different migratory strategies.

Directory of Open Access Journals (Sweden)

Elena Arriero

Full Text Available The ability to control infections is a key trait for migrants that must be balanced against other costly features of the migratory life. In this study we explored the links between migration and disease ecology by examining natural variation in parasite exposure and immunity in several populations of Lesser Black-backed Gulls (Larus fuscus with different migratory strategies. We found higher activity of natural antibodies in long distance migrants from the nominate subspecies L.f.fuscus. Circulating levels of IgY showed large variation at the population level, while immune parameters associated with antimicrobial activity showed extensive variation at the individual level irrespective of population or migratory strategy. Pathogen prevalence showed large geographical variation. However, the seroprevalence of one of the gull-specific subtypes of avian influenza (H16 was associated to the migratory strategy, with lower prevalence among the long-distance migrants, suggesting that migration may play a role in disease dynamics of certain pathogens at the population level.
Parameter sensitivity and uncertainty analysis for a storm surge and wave model

Directory of Open Access Journals (Sweden)

L. A. Bastidas

2016-09-01

Full Text Available Development and simulation of synthetic hurricane tracks is a common methodology used to estimate hurricane hazards in the absence of empirical coastal surge and wave observations. Such methods typically rely on numerical models to translate stochastically generated hurricane wind and pressure forcing into coastal surge and wave estimates. The model output uncertainty associated with selection of appropriate model parameters must therefore be addressed. The computational overburden of probabilistic surge hazard estimates is exacerbated by the high dimensionality of numerical surge and wave models. We present a model parameter sensitivity analysis of the Delft3D model for the simulation of hazards posed by Hurricane Bob (1991 utilizing three theoretical wind distributions (NWS23, modified Rankine, and Holland. The sensitive model parameters (of 11 total considered include wind drag, the depth-induced breaking γB, and the bottom roughness. Several parameters show no sensitivity (threshold depth, eddy viscosity, wave triad parameters, and depth-induced breaking αB and can therefore be excluded to reduce the computational overburden of probabilistic surge hazard estimates. The sensitive model parameters also demonstrate a large number of interactions between parameters and a nonlinear model response. While model outputs showed sensitivity to several parameters, the ability of these parameters to act as tuning parameters for calibration is somewhat limited as proper model calibration is strongly reliant on accurate wind and pressure forcing data. A comparison of the model performance with forcings from the different wind models is also presented.
Calibration of discrete element model parameters: soybeans

Science.gov (United States)

Ghodki, Bhupendra M.; Patel, Manish; Namdeo, Rohit; Carpenter, Gopal

2018-05-01

Discrete element method (DEM) simulations are broadly used to get an insight of flow characteristics of granular materials in complex particulate systems. DEM input parameters for a model are the critical prerequisite for an efficient simulation. Thus, the present investigation aims to determine DEM input parameters for Hertz-Mindlin model using soybeans as a granular material. To achieve this aim, widely acceptable calibration approach was used having standard box-type apparatus. Further, qualitative and quantitative findings such as particle profile, height of kernels retaining the acrylic wall, and angle of repose of experiments and numerical simulations were compared to get the parameters. The calibrated set of DEM input parameters includes the following (a) material properties: particle geometric mean diameter (6.24 mm); spherical shape; particle density (1220 kg m^{-3} ), and (b) interaction parameters such as particle-particle: coefficient of restitution (0.17); coefficient of static friction (0.26); coefficient of rolling friction (0.08), and particle-wall: coefficient of restitution (0.35); coefficient of static friction (0.30); coefficient of rolling friction (0.08). The results may adequately be used to simulate particle scale mechanics (grain commingling, flow/motion, forces, etc) of soybeans in post-harvest machinery and devices.
A three-dimensional cohesive sediment transport model with data assimilation: Model development, sensitivity analysis and parameter estimation

Science.gov (United States)

Wang, Daosheng; Cao, Anzhou; Zhang, Jicai; Fan, Daidu; Liu, Yongzhi; Zhang, Yue

2018-06-01

Based on the theory of inverse problems, a three-dimensional sigma-coordinate cohesive sediment transport model with the adjoint data assimilation is developed. In this model, the physical processes of cohesive sediment transport, including deposition, erosion and advection-diffusion, are parameterized by corresponding model parameters. These parameters are usually poorly known and have traditionally been assigned empirically. By assimilating observations into the model, the model parameters can be estimated using the adjoint method; meanwhile, the data misfit between model results and observations can be decreased. The model developed in this work contains numerous parameters; therefore, it is necessary to investigate the parameter sensitivity of the model, which is assessed by calculating a relative sensitivity function and the gradient of the cost function with respect to each parameter. The results of parameter sensitivity analysis indicate that the model is sensitive to the initial conditions, inflow open boundary conditions, suspended sediment settling velocity and resuspension rate, while the model is insensitive to horizontal and vertical diffusivity coefficients. A detailed explanation of the pattern of sensitivity analysis is also given. In ideal twin experiments, constant parameters are estimated by assimilating 'pseudo' observations. The results show that the sensitive parameters are estimated more easily than the insensitive parameters. The conclusions of this work can provide guidance for the practical applications of this model to simulate sediment transport in the study area.
Fuel Cell Equivalent Electric Circuit Parameter Mapping

DEFF Research Database (Denmark)

Jeppesen, Christian; Zhou, Fan; Andreasen, Søren Juhl

In this work a simple model for a fuel cell is investigated for diagnostic purpose. The fuel cell is characterized, with respect to the electrical impedance of the fuel cell at non-faulty conditions and under variations in load current. Based on this the equivalent electrical circuit parameters can...
A variational calculation of 12C in the alpha-particle model

International Nuclear Information System (INIS)

Portilho, O.

1973-01-01

Some physical properties of three structureless alpha particles interacting through two-body potentials were discussed. Comparison between them and the corresponding experimental observations for the 12 C nucleus is done. The wave function is expanded in terms of translationally invariant harmonic-oscillator states, the coefficients being variational parameters
Uncertainty of Modal Parameters Estimated by ARMA Models

DEFF Research Database (Denmark)

Jensen, Jacob Laigaard; Brincker, Rune; Rytter, Anders

1990-01-01

In this paper the uncertainties of identified modal parameters such as eidenfrequencies and damping ratios are assed. From the measured response of dynamic excited structures the modal parameters may be identified and provide important structural knowledge. However the uncertainty of the parameters...... by simulation study of a lightly damped single degree of freedom system. Identification by ARMA models has been choosen as system identification method. It is concluded that both the sampling interval and number of sampled points may play a significant role with respect to the statistical errors. Furthermore......, it is shown that the model errors may also contribute significantly to the uncertainty....
Repeatability of derived parameters from histograms following non-Gaussian diffusion modelling of diffusion-weighted imaging in a paediatric oncological cohort

Energy Technology Data Exchange (ETDEWEB)

Jerome, Neil P.; Miyazaki, Keiko; Collins, David J.; Orton, Matthew R.; D' Arcy, James A.; Leach, Martin O. [Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London (United Kingdom); Wallace, Toni; Koh, Dow-Mu [Royal Marsden NHS Foundation Trust, Department of Radiology, Sutton, Surrey (United Kingdom); Moreno, Lucas [The Institute of Cancer Research, Paediatric Drug Development Team, Division of Cancer Therapeutics and Clinical Studies, London (United Kingdom); Hospital Nino Jesus, Madrid (Spain); Royal Marsden NHS Foundation Trust, Paediatric Drug Development Unit, Children and Young People' s Unit, Sutton, Surrey (United Kingdom); Pearson, Andrew D.J.; Marshall, Lynley V.; Carceller, Fernando; Zacharoulis, Stergios [The Institute of Cancer Research, Paediatric Drug Development Team, Division of Cancer Therapeutics and Clinical Studies, London (United Kingdom); Royal Marsden NHS Foundation Trust, Paediatric Drug Development Unit, Children and Young People' s Unit, Sutton, Surrey (United Kingdom)

2017-01-15

To examine repeatability of parameters derived from non-Gaussian diffusion models in data acquired in children with solid tumours. Paediatric patients (<16 years, n = 17) were scanned twice, 24 h apart, using DWI (6 b-values, 0-1000 mm{sup -2} s) at 1.5 T in a prospective study. Tumour ROIs were drawn (3 slices) and all data fitted using IVIM, stretched exponential, and kurtosis models; percentage coefficients of variation (CV) calculated for each parameter at all ROI histogram centiles, including the medians. The values for ADC, D, DDC{sub α}, α, and DDC{sub K} gave CV < 10 % down to the 5th centile, with sharp CV increases below 5th and above 95th centile. K, f, and D* showed increased CV (>30 %) over the histogram. ADC, D, DDC{sub α}, and DDC{sub K} were strongly correlated (ρ > 0.9), DDC{sub α} and α were not correlated (ρ = 0.083). Perfusion- and kurtosis-related parameters displayed larger, more variable CV across the histogram, indicating observed clinical changes outside of D/DDC in these models should be interpreted with caution. Centiles below 5th for all parameters show high CV and are unreliable as diffusion metrics. The stretched exponential model behaved well for both DDC{sub α} and α, making it a strong candidate for modelling multiple-b-value diffusion imaging data. (orig.)
Large-Ensemble modeling of past and future variations of the Antarctic Ice Sheet with a coupled ice-Earth-sea level model

Science.gov (United States)

Pollard, David; DeConto, Robert; Gomez, Natalya

2016-04-01

To date, most modeling of the Antarctic Ice Sheet's response to future warming has been calibrated using recent and modern observations. As an alternate approach, we apply a hybrid 3-D ice sheet-shelf model to the last deglacial retreat of Antarctica, making use of geologic data of the last ~20,000 years to test the model against the large-scale variations during this period. The ice model is coupled to a global Earth-sea level model to improve modeling of the bedrock response and to capture ocean-ice gravitational interactions. Following several recent ice-sheet studies, we use Large Ensemble (LE) statistical methods, performing sets of 625 runs from 30,000 years to present with systematically varying model parameters. Objective scores for each run are calculated using modern data and past reconstructed grounding lines, relative sea level records, cosmogenic elevation-age data and uplift rates. The LE results are analyzed to calibrate 4 particularly uncertain model parameters that concern marginal ice processes and interaction with the ocean. LE's are extended into the future with climates following RCP scenarios. An additional scoring criterion tests the model's ability to reproduce estimated sea-level high stands in the warm mid-Pliocene, for which drastic retreat mechanisms of hydrofracturing and ice-cliff failure are needed in the model. The LE analysis provides future sea-level-rise envelopes with well-defined parametric uncertainty bounds. Sensitivities of future LE results to Pliocene sea-level estimates, coupling to the Earth-sea level model, and vertical profiles of Earth properties, will be presented.
A RSSI-based parameter tracking strategy for constrained position localization

Science.gov (United States)

Du, Jinze; Diouris, Jean-François; Wang, Yide

2017-12-01

In this paper, a received signal strength indicator (RSSI)-based parameter tracking strategy for constrained position localization is proposed. To estimate channel model parameters, least mean squares method (LMS) is associated with the trilateration method. In the context of applications where the positions are constrained on a grid, a novel tracking strategy is proposed to determine the real position and obtain the actual parameters in the monitored region. Based on practical data acquired from a real localization system, an experimental channel model is constructed to provide RSSI values and verify the proposed tracking strategy. Quantitative criteria are given to guarantee the efficiency of the proposed tracking strategy by providing a trade-off between the grid resolution and parameter variation. The simulation results show a good behavior of the proposed tracking strategy in the presence of space-time variation of the propagation channel. Compared with the existing RSSI-based algorithms, the proposed tracking strategy exhibits better localization accuracy but consumes more calculation time. In addition, a tracking test is performed to validate the effectiveness of the proposed tracking strategy.
Consistent Stochastic Modelling of Meteocean Design Parameters

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Sterndorff, M. J.

2000-01-01

Consistent stochastic models of metocean design parameters and their directional dependencies are essential for reliability assessment of offshore structures. In this paper a stochastic model for the annual maximum values of the significant wave height, and the associated wind velocity, current...
Soil-Related Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

A. J. Smith

2004-09-09

This report presents one of the analyses that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the details of the conceptual model as well as the mathematical model and the required input parameters. The biosphere model is one of a series of process models supporting the postclosure Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A schematic representation of the documentation flow for the Biosphere input to TSPA is presented in Figure 1-1. This figure shows the evolutionary relationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (TWP) (BSC 2004 [DIRS 169573]). This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil-Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. The purpose of this analysis was to develop the biosphere model parameters associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation or ash deposition and, as a direct consequence, radionuclide concentration in other environmental media that are affected by radionuclide concentrations in soil. The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573]) where the governing procedure
Inhalation Exposure Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

M. Wasiolek

2006-06-05

This analysis is one of the technical reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), referred to in this report as the biosphere model. ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. ''Inhalation Exposure Input Parameters for the Biosphere Model'' is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the biosphere model is presented in Figure 1-1 (based on BSC 2006 [DIRS 176938]). This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and how this analysis report contributes to biosphere modeling. This analysis report defines and justifies values of atmospheric mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of the biosphere model to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception. This
Inhalation Exposure Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

M. Wasiolek

2006-01-01

This analysis is one of the technical reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), referred to in this report as the biosphere model. ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. ''Inhalation Exposure Input Parameters for the Biosphere Model'' is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the biosphere model is presented in Figure 1-1 (based on BSC 2006 [DIRS 176938]). This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and how this analysis report contributes to biosphere modeling. This analysis report defines and justifies values of atmospheric mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of the biosphere model to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception. This report is concerned primarily with the
Variational methods in the kinetic modeling of nuclear reactors: Recent advances

International Nuclear Information System (INIS)

Dulla, S.; Picca, P.; Ravetto, P.

2009-01-01

The variational approach can be very useful in the study of approximate methods, giving a sound mathematical background to numerical algorithms and computational techniques. The variational approach has been applied to nuclear reactor kinetic equations, to obtain a formulation of standard methods such as point kinetics and quasi-statics. more recently, the multipoint method has also been proposed for the efficient simulation of space-energy transients in nuclear reactors and in source-driven subcritical systems. The method is now founded on a variational basis that allows a consistent definition of integral parameters. The mathematical structure of multipoint and modal methods is also investigated, evidencing merits and shortcomings of both techniques. Some numerical results for simple systems are presented and the errors with respect to reference calculations are reported and discussed. (authors)
Estimation of Key Parameters of the Coupled Energy and Water Model by Assimilating Land Surface Data

Science.gov (United States)

Abdolghafoorian, A.; Farhadi, L.

2017-12-01

Accurate estimation of land surface heat and moisture fluxes, as well as root zone soil moisture, is crucial in various hydrological, meteorological, and agricultural applications. Field measurements of these fluxes are costly and cannot be readily scaled to large areas relevant to weather and climate studies. Therefore, there is a need for techniques to make quantitative estimates of heat and moisture fluxes using land surface state observations that are widely available from remote sensing across a range of scale. In this work, we applies the variational data assimilation approach to estimate land surface fluxes and soil moisture profile from the implicit information contained Land Surface Temperature (LST) and Soil Moisture (SM) (hereafter the VDA model). The VDA model is focused on the estimation of three key parameters: 1- neutral bulk heat transfer coefficient (CHN), 2- evaporative fraction from soil and canopy (EF), and 3- saturated hydraulic conductivity (Ksat). CHN and EF regulate the partitioning of available energy between sensible and latent heat fluxes. Ksat is one of the main parameters used in determining infiltration, runoff, groundwater recharge, and in simulating hydrological processes. In this study, a system of coupled parsimonious energy and water model will constrain the estimation of three unknown parameters in the VDA model. The profile of SM (LST) at multiple depths is estimated using moisture diffusion (heat diffusion) equation. In this study, the uncertainties of retrieved unknown parameters and fluxes are estimated from the inverse of Hesian matrix of cost function which is computed using the Lagrangian methodology. Analysis of uncertainty provides valuable information about the accuracy of estimated parameters and their correlation and guide the formulation of a well-posed estimation problem. The results of proposed algorithm are validated with a series of experiments using a synthetic data set generated by the simultaneous heat and
Characterization of PDMS samples with variation of its synthesis parameters for tunable optics applications

Science.gov (United States)

Marquez-Garcia, Josimar; Cruz-Félix, Angel S.; Santiago-Alvarado, Agustin; González-García, Jorge

2017-09-01

Nowadays the elastomer known as polydimethylsiloxane (PDMS, Sylgard 184), due to its physical properties, low cost and easy handle, have become a frequently used material for the elaboration of optical components such as: variable focal length liquid lenses, optical waveguides, solid elastic lenses, etc. In recent years, we have been working in the characterization of this material for applications in visual sciences; in this work, we describe the elaboration of PDMSmade samples, also, we present physical and optical properties of the samples by varying its synthesis parameters such as base: curing agent ratio, and both, curing time and temperature. In the case of mechanical properties, tensile and compression tests were carried out through a universal testing machine to obtain the respective stress-strain curves, and to obtain information regarding its optical properties, UV-vis spectroscopy is applied to the samples to obtain transmittance and absorbance curves. Index of refraction variation was obtained through an Abbe refractometer. Results from the characterization will determine the proper synthesis parameters for the elaboration of tunable refractive surfaces for potential applications in robotics.

Application of the physiological and morphological parameters of the brazilian population sample to the mathematical model of the human respiratory tract

International Nuclear Information System (INIS)

Reis, Arlene Alves dos

2005-01-01

The Human Respiratory Tract Model proposed by the ICRP Publication 66 accounts for the morphology and physiology of the respiratory tract. The characteristics of air drawn into the lungs and exhaled are greatly influenced by the morphology of the respiratory tract, which causes numerous changes in pressure, flow rate, direction and humidity as air moves into and out of the lungs. Concerning the respiratory physiological parameters the breathing characteristics influence the volume, the inhalation rate of air and the portion that enters through the nose and the mouth. These characteristics are important to determine the fractional deposition. The model uses morphological and physiological parameters from the Caucasian man to establish deposition fractions in the respiratory tract regions. It is known that the morphology and physiology are influenced by environmental, occupational and economic conditions. The ICRP recommends, for a reliable evaluation of the regional deposition, the use of parameters from a local population when information is available. The main purpose of this study is to verify the influence in using the morphology and physiology parameters representative of a sample of the Brazilian population on the deposition model of the ICRP Publication 66. The morphological and physiological data were obtained from the literature. The software EXCEL for Windows (version 2000) was used in order to implement the deposition model and also to allow the changes in parameters of interest. Initially, the implemented model was checked using the parameters defined by the ICRP and the results of the fraction deposition in the respiratory tract compartments were compared. Finally, morphological and physiological parameters from Brazilian adult male were applied and the fractional deposition calculated. The results suggest a significant variation in fractional deposition when Brazilian parameters are applied in the model. (author)
A distributed approach for parameters estimation in System Biology models

International Nuclear Information System (INIS)

Mosca, E.; Merelli, I.; Alfieri, R.; Milanesi, L.

2009-01-01

Due to the lack of experimental measurements, biological variability and experimental errors, the value of many parameters of the systems biology mathematical models is yet unknown or uncertain. A possible computational solution is the parameter estimation, that is the identification of the parameter values that determine the best model fitting respect to experimental data. We have developed an environment to distribute each run of the parameter estimation algorithm on a different computational resource. The key feature of the implementation is a relational database that allows the user to swap the candidate solutions among the working nodes during the computations. The comparison of the distributed implementation with the parallel one showed that the presented approach enables a faster and better parameter estimation of systems biology models.
Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model

Science.gov (United States)

Zuhdi, Shaifudin; Retno Sari Saputro, Dewi; Widyaningsih, Purnami

2017-06-01

A regression model is the representation of relationship between independent variable and dependent variable. The dependent variable has categories used in the logistic regression model to calculate odds on. The logistic regression model for dependent variable has levels in the logistics regression model is ordinal. GWOLR model is an ordinal logistic regression model influenced the geographical location of the observation site. Parameters estimation in the model needed to determine the value of a population based on sample. The purpose of this research is to parameters estimation of GWOLR model using R software. Parameter estimation uses the data amount of dengue fever patients in Semarang City. Observation units used are 144 villages in Semarang City. The results of research get GWOLR model locally for each village and to know probability of number dengue fever patient categories.
Reflector modelization for neutronic diffusion and parameters identification

International Nuclear Information System (INIS)

Argaud, J.P.

1993-04-01

Physical parameters of neutronic diffusion equations can be adjusted to decrease calculations-measurements errors. The reflector being always difficult to modelize, we choose to elaborate a new reflector model and to use the parameters of this model as adjustment coefficients in the identification procedure. Using theoretical results, and also the physical behaviour of neutronic flux solutions, the reflector model consists then in its replacement by boundary conditions for the diffusion equations on the core only. This theoretical result of non-local operator relations leads then to some discrete approximations by taking into account the multiscaled behaviour, on the core-reflector interface, of neutronic diffusion solutions. The resulting model of this approach is then compared with previous reflector modelizations, and first results indicate that this new model gives the same representation of reflector for the core than previous. (author). 12 refs
Transient dynamic and modeling parameter sensitivity analysis of 1D solid oxide fuel cell model

International Nuclear Information System (INIS)

Huangfu, Yigeng; Gao, Fei; Abbas-Turki, Abdeljalil; Bouquain, David; Miraoui, Abdellatif

2013-01-01

Highlights: • A multiphysics, 1D, dynamic SOFC model is developed. • The presented model is validated experimentally in eight different operating conditions. • Electrochemical and thermal dynamic transient time expressions are given in explicit forms. • Parameter sensitivity is discussed for different semi-empirical parameters in the model. - Abstract: In this paper, a multiphysics solid oxide fuel cell (SOFC) dynamic model is developed by using a one dimensional (1D) modeling approach. The dynamic effects of double layer capacitance on the electrochemical domain and the dynamic effect of thermal capacity on thermal domain are thoroughly considered. The 1D approach allows the model to predict the non-uniform distributions of current density, gas pressure and temperature in SOFC during its operation. The developed model has been experimentally validated, under different conditions of temperature and gas pressure. Based on the proposed model, the explicit time constant expressions for different dynamic phenomena in SOFC have been given and discussed in detail. A parameters sensitivity study has also been performed and discussed by using statistical Multi Parameter Sensitivity Analysis (MPSA) method, in order to investigate the impact of parameters on the modeling accuracy
Development of Row of Vibration Insulators and its Mathematical Models on a Base of Common Multi-parameter Scheme of Element Axial Line

Science.gov (United States)

Ponomarev, Yury K.

2018-01-01

The mathematical model of deformation of a cable (rope) vibration insulator consisting of two identical clips connected by means of elastic elements of a complex axial line is developed in detail. The axial line of the element is symmetric relatively to the horizontal axis of the shape and is made up of five rectilinear sections of arbitrary length a, b, c, conjugated to four radius sections with parameters R1 and R2 with angular extent 90°. On the basis of linear representations of the theory of bending and torsion of mechanics of materials, applied mechanics and linear algebra, a mathematical model of loading of an element and a vibration insulator as a whole in the direction of the vertical Y axis has been developed. Generalized characteristics of the friction and elastic forces for an elastic element with a complete set of the listed sections are obtained. Further, with the help of nullification in the generalized model of the characteristics of certain parameters, special cases of friction and elastic forces are obtained without taking into account the nullified parameters. Simultaneously, on the basis of the 3D computer-aided design system, volumetric models of simplified structures were created, given in the work. It is shown that, with the help of a variation of the five parameters of the axial scheme of the element, in combination with the variation of the moment of inertia of the rope section and the number of elements entering the ensemble, the load characteristics and stiffness of the vibration insulators can be changed tens and hundreds of times. This opens up unlimited possibilities for the optimal design of vibration protection systems in terms of weight characteristics, in cost, in terms of vibration intensity, in overall dimensions in different directions, which is very important for aerospace and transport engineering.
Challenges for modelling spatio-temporal variations of malaria risk in Malawi

Science.gov (United States)

Lowe, R.; Chirombo, J.; Tompkins, A. M.

2012-04-01

Malaria is the leading cause of morbidity and mortality in Malawi with more than 6 million episodes reported each year. Malaria poses a huge economic burden to Malawi in terms of the direct cost of treating malaria patients and also indirect costs resulting from workdays lost in agriculture and industry and absenteeism from school. Malawi implements malaria control activities within the Roll Back Malaria framework, with the objective to provide those most at risk (i.e. children under five years, pregnant woman and individuals with suppressed immune systems) access to personal and community protective measures. However, at present there is no mechanism by which to target the most 'at risk' populations ahead of an impending epidemic. Malaria transmission is influenced by variations in meteorological conditions, which impact the biology of the mosquito and the availability of breeding sites, but also socio-economic conditions such as levels of urbanisation, poverty and education, which influence human vulnerability and vector habitat. The many potential drivers of malaria, both extrinsic, such as climate, and intrinsic, such as population immunity are often difficult to disentangle. This presents a challenge for modelling of malaria risk in space and time. Using an age-stratified spatio-temporal dataset of malaria cases at the district level from July 2004 - June 2011, we use a spatio-temporal modelling framework to model variations in malaria risk in Malawi. Climatic and topographic variations are accounted for using an interpolation method to relate gridded products to administrative districts. District level data is tested in the model to account for confounding factors, including the proportion of the population living in urban areas; residing in traditional housing; with no toilet facilities; who do not attend school, etc, the number of health facilities per population and yearly estimates of insecticide-treated mosquito net distribution. In order to account for
Coupled 1D-2D hydrodynamic inundation model for sewer overflow: Influence of modeling parameters

Directory of Open Access Journals (Sweden)

Adeniyi Ganiyu Adeogun

2015-10-01

Full Text Available This paper presents outcome of our investigation on the influence of modeling parameters on 1D-2D hydrodynamic inundation model for sewer overflow, developed through coupling of an existing 1D sewer network model (SWMM and 2D inundation model (BREZO. The 1D-2D hydrodynamic model was developed for the purpose of examining flood incidence due to surcharged water on overland surface. The investigation was carried out by performing sensitivity analysis on the developed model. For the sensitivity analysis, modeling parameters, such as mesh resolution Digital Elevation Model (DEM resolution and roughness were considered. The outcome of the study shows the model is sensitive to changes in these parameters. The performance of the model is significantly influenced, by the Manning's friction value, the DEM resolution and the area of the triangular mesh. Also, changes in the aforementioned modeling parameters influence the Flood characteristics, such as the inundation extent, the flow depth and the velocity across the model domain. Keywords: Inundation, DEM, Sensitivity analysis, Model coupling, Flooding
On the validity of evolutionary models with site-specific parameters.

Directory of Open Access Journals (Sweden)

Konrad Scheffler

Full Text Available Evolutionary models that make use of site-specific parameters have recently been criticized on the grounds that parameter estimates obtained under such models can be unreliable and lack theoretical guarantees of convergence. We present a simulation study providing empirical evidence that a simple version of the models in question does exhibit sensible convergence behavior and that additional taxa, despite not being independent of each other, lead to improved parameter estimates. Although it would be desirable to have theoretical guarantees of this, we argue that such guarantees would not be sufficient to justify the use of these models in practice. Instead, we emphasize the importance of taking the variance of parameter estimates into account rather than blindly trusting point estimates - this is standardly done by using the models to construct statistical hypothesis tests, which are then validated empirically via simulation studies.
Climate change decision-making: Model & parameter uncertainties explored

Energy Technology Data Exchange (ETDEWEB)

Dowlatabadi, H.; Kandlikar, M.; Linville, C.

1995-12-31

A critical aspect of climate change decision-making is uncertainties in current understanding of the socioeconomic, climatic and biogeochemical processes involved. Decision-making processes are much better informed if these uncertainties are characterized and their implications understood. Quantitative analysis of these uncertainties serve to inform decision makers about the likely outcome of policy initiatives, and help set priorities for research so that outcome ambiguities faced by the decision-makers are reduced. A family of integrated assessment models of climate change have been developed at Carnegie Mellon. These models are distinguished from other integrated assessment efforts in that they were designed from the outset to characterize and propagate parameter, model, value, and decision-rule uncertainties. The most recent of these models is ICAM 2.1. This model includes representation of the processes of demographics, economic activity, emissions, atmospheric chemistry, climate and sea level change and impacts from these changes and policies for emissions mitigation, and adaptation to change. The model has over 800 objects of which about one half are used to represent uncertainty. In this paper we show, that when considering parameter uncertainties, the relative contribution of climatic uncertainties are most important, followed by uncertainties in damage calculations, economic uncertainties and direct aerosol forcing uncertainties. When considering model structure uncertainties we find that the choice of policy is often dominated by model structure choice, rather than parameter uncertainties.
A variational approach to the Gross-Neveu model

International Nuclear Information System (INIS)

Mishra, H.; Misra, P.; Mishra, A.

1988-01-01

The authors solve the instability of perturbative vacuum of Gross-Neveu model. They use a variational method. The analysis is nonperturbative as it uses only equal time commmutator/anticommutator algebra
Error propagation of partial least squares for parameters optimization in NIR modeling

Science.gov (United States)

Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng

2018-03-01

A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models.
Error propagation of partial least squares for parameters optimization in NIR modeling.

Science.gov (United States)

Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng

2018-03-05

A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models. Copyright © 2017. Published by Elsevier B.V.
Inhalation Exposure Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

M. A. Wasiolek

2003-01-01

This analysis is one of the nine reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2003a) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents a set of input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for a Yucca Mountain repository. This report, ''Inhalation Exposure Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003b). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available at that time. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this analysis report. This analysis report defines and justifies values of mass loading, which is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Measurements of mass loading are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air surrounding crops and concentrations in air inhaled by a receptor. Concentrations in air to which the
Parameter Optimisation for the Behaviour of Elastic Models over Time

DEFF Research Database (Denmark)

Mosegaard, Jesper

2004-01-01

Optimisation of parameters for elastic models is essential for comparison or finding equivalent behaviour of elastic models when parameters cannot simply be transferred or converted. This is the case with a large range of commonly used elastic models. In this paper we present a general method tha...
Integral Parameters of the Thermal Neutron Scattering Law

International Nuclear Information System (INIS)

Purohit, S.N.

1964-09-01

Integral parameters of the thermal neutron scattering law - the thermalization binding parameter (M 2 ), the Placzek's moments of the generalized frequency spectrum of dynamical modes and the energy transfer moments of the scattering law - are theoretically discussed. A detailed study of the variation of M 2 , the thermalization time constant and the effective temperature of the vibrating atoms, with the relative weight between intra-molecular vibrations and hindered rotations for H 2 O, is presented. Theoretical results for different scattering models of H 2 O are compared with the measurements of integral experiments. A set of integral parameters for D 2 O, using Butler's model, have been obtained. Importance of the structure of hindered rotations of H 2 O and D 2 O in the study of integral parameters has also been discussed
[Simulation of carbon cycle in Qianyanzhou artificial masson pine forest ecosystem and sensitivity analysis of model parameters].

Science.gov (United States)

Wang, Yuan; Zhang, Na; Yu, Gui-rui

2010-07-01

By using modified carbon-water cycle model EPPML (ecosystem productivity process model for landscape), the carbon absorption and respiration in Qianyanzhou artificial masson pine forest ecosystem in 2003 and 2004 were simulated, and the sensitivity of the model parameters was analyzed. The results showed that EPPML could effectively simulate the carbon cycle process of this ecosystem. The simulated annual values and the seasonal variations of gross primary productivity (GPP), net ecosystem productivity (NEP), and ecosystem respiration (Re) not only fitted well with the measured data, but also reflected the major impacts of extreme weather on carbon flows. The artificial masson pine forest ecosystem in Qianyanzhou was a strong carbon sink in both 2003 and 2004. Due to the coupling of high temperature and severe drought in the growth season in 2003, the carbon absorption in 2003 was lower than that in 2004. The annual NEP in 2003 and 2004 was 481.8 and 516.6 g C x m(-2) x a(-1), respectively. The key climatic factors giving important impacts on the seasonal variations of carbon cycle were solar radiation during early growth season, drought during peak growth season, and precipitation during post-peak growth season. Autotrophic respiration (Ra) and net primary productivity (NPP) had the similar seasonal variations. Soil heterotrophic respiration (Rh) was mainly affected by soil temperature at yearly scale, and by soil water content at monthly scale. During wet growth season, the higher the soil water content, the lower the Rh was; during dry growth season, the higher the precipitation during the earlier two months, the higher the Rh was. The maximum RuBP carboxylation rate at 25 degrees C (Vm25), specific leaf area (SLA), maximum leaf nitrogen content (LNm), average leaf nitrogen content (LN), and conversion coefficient of biomass to carbon (C/B) had the greatest influence on annual NEP. Different carbon cycle process could have different responses to sensitive
Multilevel models for multiple-baseline data: modeling across-participant variation in autocorrelation and residual variance.

Science.gov (United States)

Baek, Eun Kyeng; Ferron, John M

2013-03-01

Multilevel models (MLM) have been used as a method for analyzing multiple-baseline single-case data. However, some concerns can be raised because the models that have been used assume that the Level-1 error covariance matrix is the same for all participants. The purpose of this study was to extend the application of MLM of single-case data in order to accommodate across-participant variation in the Level-1 residual variance and autocorrelation. This more general model was then used in the analysis of single-case data sets to illustrate the method, to estimate the degree to which the autocorrelation and residual variances differed across participants, and to examine whether inferences about treatment effects were sensitive to whether or not the Level-1 error covariance matrix was allowed to vary across participants. The results from the analyses of five published studies showed that when the Level-1 error covariance matrix was allowed to vary across participants, some relatively large differences in autocorrelation estimates and error variance estimates emerged. The changes in modeling the variance structure did not change the conclusions about which fixed effects were statistically significant in most of the studies, but there was one exception. The fit indices did not consistently support selecting either the more complex covariance structure, which allowed the covariance parameters to vary across participants, or the simpler covariance structure. Given the uncertainty in model specification that may arise when modeling single-case data, researchers should consider conducting sensitivity analyses to examine the degree to which their conclusions are sensitive to modeling choices.
Modeling variations in the cedi/dollar exchange rate in Ghana: an autoregressive conditional heteroscedastic (ARCH) models.

Science.gov (United States)

Techie Quaicoe, Michael; Twenefour, Frank B K; Baah, Emmanuel M; Nortey, Ezekiel N N

2015-01-01

This research article aimed at modeling the variations in the dollar/cedi exchange rate. It examines the applicability of a range of ARCH/GARCH specifications for modeling volatility of the series. The variants considered include the ARMA, GARCH, IGARCH, EGARCH and M-GARCH specifications. The results show that the series was non stationary which resulted from the presence of a unit root in it. The ARMA (1, 1) was found to be the most suitable model for the conditional mean. From the Box-Ljung test statistics x-squared of 1476.338 with p value 0.00217 for squared returns and 16.918 with 0.0153 p values for squared residuals, the null hypothesis of no ARCH effect was rejected at 5% significance level indicating the presence of an ARCH effect in the series. ARMA (1, 1) + GARCH (1, 1) which has all parameters significant was found to be the most suitable model for the conditional mean with conditional variance, thus showing adequacy in describing the conditional mean with variance of the return series at 5% significant level. A 24 months forecast for the mean actual exchange rates and mean returns from January, 2013 to December, 2014 made also showed that the fitted model is appropriate for the data and a depreciating trend of the cedi against the dollar for forecasted period respectively.
Recommended direct simulation Monte Carlo collision model parameters for modeling ionized air transport processes

Energy Technology Data Exchange (ETDEWEB)

Swaminathan-Gopalan, Krishnan; Stephani, Kelly A., E-mail: ksteph@illinois.edu [Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States)

2016-02-15

A systematic approach for calibrating the direct simulation Monte Carlo (DSMC) collision model parameters to achieve consistency in the transport processes is presented. The DSMC collision cross section model parameters are calibrated for high temperature atmospheric conditions by matching the collision integrals from DSMC against ab initio based collision integrals that are currently employed in the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) and Data Parallel Line Relaxation (DPLR) high temperature computational fluid dynamics solvers. The DSMC parameter values are computed for the widely used Variable Hard Sphere (VHS) and the Variable Soft Sphere (VSS) models using the collision-specific pairing approach. The recommended best-fit VHS/VSS parameter values are provided over a temperature range of 1000-20 000 K for a thirteen-species ionized air mixture. Use of the VSS model is necessary to achieve consistency in transport processes of ionized gases. The agreement of the VSS model transport properties with the transport properties as determined by the ab initio collision integral fits was found to be within 6% in the entire temperature range, regardless of the composition of the mixture. The recommended model parameter values can be readily applied to any gas mixture involving binary collisional interactions between the chemical species presented for the specified temperature range.

Joint analysis of short-period variations of ionospheric parameters in Siberia and the Far East and processes of the tropical cyclogenesis

Science.gov (United States)

Chernigovskaya, M. A.; Kurkin, V. I.; Orlov, I. I.; Sharkov, E. A.; Pokrovskaya, I. V.

2009-04-01

In this work a possibility of manifestation of strong meteorological disturbances in the Earth lower atmosphere in variations of ionospheric parameters in the zone remote from the disturbance source has been studied. The spectral analysis of short-period variations (about ten minutes, hours) in maximum observed frequencies (MOF) of one-skip signals of oblique sounding has been carried out. These variations were induced by changes in the upper atmosphere parameters along the Magadan-Irkutsk oblique-incidence sounding path on the background of diurnal variations in the parameter under study. Data on MOF measurements with off-duty factor approximately 5 min in equinoxes (September, March) of 2005-2007 were used. The analysis was made using the improved ISTP-developed technique of determining periodicities in time series. The increase of signal spectrum energy at certain frequencies is interpreted as manifestation of traveling ionospheric disturbances (TID) associated with propagation of internal gravity waves in the atmosphere. The analysis revealed TIDs of temporal scales under consideration. The question concerning localization of possible sources of revealed disturbances is discussed. Troposphere meteorological disturbances giant in their energy (tropical cyclones, typhoon) are considered as potential sources of observable TIDs. The needed information on tropical cyclones that occurred in the north area of the Indian Ocean, south-west and central areas of the Pacific Ocean in 2005-2007 is taken from the electron base of satellite data on the global tropical cyclogenesis "Global-TC" (ISR RAS). In order to effectively separate disturbances associated with the magnetospheric-ionospheric interaction and disturbances induced by the lower atmosphere influence on the upper atmosphere, we analyze the tropical cyclogenesis events that occurred in quiet helio-geomagnetic conditions. The study was supported by the Program of RAS Presidium N 16 (Part 3) and the RFBR Grant N 08-05-00658.
Variation of thermal parameters in two different color morphs of a diurnal poison toad, Melanophryniscus rubriventris (Anura: Bufonidae).

Science.gov (United States)

Sanabria, Eduardo A; Vaira, Marcos; Quiroga, Lorena B; Akmentins, Mauricio S; Pereyra, Laura C

2014-04-01

We study the variation in thermal parameters in two contrasting populations Yungas Redbelly Toads (Melanophryniscus rubriventris) with different discrete color phenotypes comparing field body temperatures, critical thermal maximum and heating rates. We found significant differences in field body temperatures of the different morphs. Temperatures were higher in toads with a high extent of dorsal melanization. No variation was registered in operative temperatures between the study locations at the moment of capture and processing. Critical thermal maximum of toads was positively related with the extent of dorsal melanization. Furthermore, we founded significant differences in heating rates between morphs, where individuals with a high extent of dorsal melanization showed greater heating rates than toads with lower dorsal melanization. The color pattern-thermal parameter relationship observed may influence the activity patterns and body size of individuals. Body temperature is a modulator of physiological and behavioral functions in amphibians, influencing daily and seasonal activity, locomotor performance, digestion rate and growth rate. It is possible that some growth constraints may arise due to the relationship of color pattern-metabolism allowing different morphs to attain similar sizes at different locations instead of body-size clines. Copyright © 2014. Published by Elsevier Ltd.
The time-lapse AVO difference inversion for changes in reservoir parameters

Science.gov (United States)

Longxiao, Zhi; Hanming, Gu; Yan, Li

2016-12-01

The result of conventional time-lapse seismic processing is the difference between the amplitude and the post-stack seismic data. Although stack processing can improve the signal-to-noise ratio (SNR) of seismic data, it also causes a considerable loss of important information about the amplitude changes and only gives the qualitative interpretation. To predict the changes in reservoir fluid more precisely and accurately, we also need the quantitative information of the reservoir. To achieve this aim, we develop the method of time-lapse AVO (amplitude versus offset) difference inversion. For the inversion of reservoir changes in elastic parameters, we apply the Gardner equation as the constraint and convert the three-parameter inversion of elastic parameter changes into a two-parameter inversion to make the inversion more stable. For the inversion of variations in the reservoir parameters, we infer the relation between the difference of the reflection coefficient and variations in the reservoir parameters, and then invert reservoir parameter changes directly. The results of the theoretical modeling computation and practical application show that our method can estimate the relative variations in reservoir density, P-wave and S-wave velocity, calculate reservoir changes in water saturation and effective pressure accurately, and then provide reference for the rational exploitation of the reservoir.
Modelling tourists arrival using time varying parameter

Science.gov (United States)

Suciptawati, P.; Sukarsa, K. G.; Kencana, Eka N.

2017-06-01

The importance of tourism and its related sectors to support economic development and poverty reduction in many countries increase researchers’ attentions to study and model tourists’ arrival. This work is aimed to demonstrate time varying parameter (TVP) technique to model the arrival of Korean’s tourists to Bali. The number of Korean tourists whom visiting Bali for period January 2010 to December 2015 were used to model the number of Korean’s tourists to Bali (KOR) as dependent variable. The predictors are the exchange rate of Won to IDR (WON), the inflation rate in Korea (INFKR), and the inflation rate in Indonesia (INFID). Observing tourists visit to Bali tend to fluctuate by their nationality, then the model was built by applying TVP and its parameters were approximated using Kalman Filter algorithm. The results showed all of predictor variables (WON, INFKR, INFID) significantly affect KOR. For in-sample and out-of-sample forecast with ARIMA’s forecasted values for the predictors, TVP model gave mean absolute percentage error (MAPE) as much as 11.24 percent and 12.86 percent, respectively.
SPOTting model parameters using a ready-made Python package

Science.gov (United States)

Houska, Tobias; Kraft, Philipp; Breuer, Lutz

2015-04-01

The selection and parameterization of reliable process descriptions in ecological modelling is driven by several uncertainties. The procedure is highly dependent on various criteria, like the used algorithm, the likelihood function selected and the definition of the prior parameter distributions. A wide variety of tools have been developed in the past decades to optimize parameters. Some of the tools are closed source. Due to this, the choice for a specific parameter estimation method is sometimes more dependent on its availability than the performance. A toolbox with a large set of methods can support users in deciding about the most suitable method. Further, it enables to test and compare different methods. We developed the SPOT (Statistical Parameter Optimization Tool), an open source python package containing a comprehensive set of modules, to analyze and optimize parameters of (environmental) models. SPOT comes along with a selected set of algorithms for parameter optimization and uncertainty analyses (Monte Carlo, MC; Latin Hypercube Sampling, LHS; Maximum Likelihood, MLE; Markov Chain Monte Carlo, MCMC; Scuffled Complex Evolution, SCE-UA; Differential Evolution Markov Chain, DE-MCZ), together with several likelihood functions (Bias, (log-) Nash-Sutcliff model efficiency, Correlation Coefficient, Coefficient of Determination, Covariance, (Decomposed-, Relative-, Root-) Mean Squared Error, Mean Absolute Error, Agreement Index) and prior distributions (Binomial, Chi-Square, Dirichlet, Exponential, Laplace, (log-, multivariate-) Normal, Pareto, Poisson, Cauchy, Uniform, Weibull) to sample from. The model-independent structure makes it suitable to analyze a wide range of applications. We apply all algorithms of the SPOT package in three different case studies. Firstly, we investigate the response of the Rosenbrock function, where the MLE algorithm shows its strengths. Secondly, we study the Griewank function, which has a challenging response surface for
Model parameters estimation and sensitivity by genetic algorithms

International Nuclear Information System (INIS)

Marseguerra, Marzio; Zio, Enrico; Podofillini, Luca

2003-01-01

In this paper we illustrate the possibility of extracting qualitative information on the importance of the parameters of a model in the course of a Genetic Algorithms (GAs) optimization procedure for the estimation of such parameters. The Genetic Algorithms' search of the optimal solution is performed according to procedures that resemble those of natural selection and genetics: an initial population of alternative solutions evolves within the search space through the four fundamental operations of parent selection, crossover, replacement, and mutation. During the search, the algorithm examines a large amount of solution points which possibly carries relevant information on the underlying model characteristics. A possible utilization of this information amounts to create and update an archive with the set of best solutions found at each generation and then to analyze the evolution of the statistics of the archive along the successive generations. From this analysis one can retrieve information regarding the speed of convergence and stabilization of the different control (decision) variables of the optimization problem. In this work we analyze the evolution strategy followed by a GA in its search for the optimal solution with the aim of extracting information on the importance of the control (decision) variables of the optimization with respect to the sensitivity of the objective function. The study refers to a GA search for optimal estimates of the effective parameters in a lumped nuclear reactor model of literature. The supporting observation is that, as most optimization procedures do, the GA search evolves towards convergence in such a way to stabilize first the most important parameters of the model and later those which influence little the model outputs. In this sense, besides estimating efficiently the parameters values, the optimization approach also allows us to provide a qualitative ranking of their importance in contributing to the model output. The
WATGIS: A GIS-Based Lumped Parameter Water Quality Model

Science.gov (United States)

Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya

2002-01-01

A Geographic Information System (GIS)Âbased, lumped parameter water quality model was developed to estimate the spatial and temporal nitrogenÂloading patterns for lower coastal plain watersheds in eastern North Carolina. The model uses a spatially distributed delivery ratio (DR) parameter to account for nitrogen retention or loss along a drainage network. Delivery...
The effect of statistical analytical measurement variations on the plant control parameters and production costs in cement manufacturing – a case study

Directory of Open Access Journals (Sweden)

A. D. Love

2010-01-01

Full Text Available Raw materials used in cement manufacturing normally have varying chemical compositions and require regular analyses for plant control purposes. This is achieved by using several analytical instruments, such as XRF and ICP. The values obtained for the major elements Ca, Si, Fe and Al, are used to calculate the plant control parameters Lime Saturation Factor (LSF, Silica Ratio (SR and Alumina Modulus (AM. These plant control parameters are used to regulate the mixing and blending of various raw meal components and to operate the plant optimally. Any errors and large ﬂuctuations in these plant parameters not only inﬂuence the quality of the cement produced, but also have a major effect on the cost of production of cement clinker through their inﬂuence on the energy consumption and residence time in the kiln. This paper looks at the role that statistical variances in the analytical measurements of the major elements Ca, Si, Fe and Al can have on the ultimate LSF, SR and AM values calculated from these measurements. The inﬂuence of too high and too low values of the LSF, SR and AM on clinker quality and energy consumption is discussed, and acceptable variances in these three parameters, based on plant experiences, are established. The effect of variances in the LSF, SR and AM parameters on the production costs is then analysed, and it is shown that variations of as large as 30% and as little as 5% can potentially occur. The LSF calculation incorporates most chemical elements and therefore is prone to the largest number of variations due to statistical variances in the analytical determinations of the chemical elements. Despite all these variations in LSF values they actually produced the smallest inﬂuence on the production cost of the clinker. It is therefore concluded that the LSF value is the most practical parameter for plant control purposes.
Fusion strategies for selecting multiple tuning parameters for multivariate calibration and other penalty based processes: A model updating application for pharmaceutical analysis

Energy Technology Data Exchange (ETDEWEB)

Tencate, Alister J. [Department of Chemistry, Idaho State University, Pocatello, ID 83209 (United States); Kalivas, John H., E-mail: kalijohn@isu.edu [Department of Chemistry, Idaho State University, Pocatello, ID 83209 (United States); White, Alexander J. [Department of Physics and Optical Engineering, Rose-Hulman Institute of Technology, Terre Huate, IN 47803 (United States)

2016-05-19

New multivariate calibration methods and other processes are being developed that require selection of multiple tuning parameter (penalty) values to form the final model. With one or more tuning parameters, using only one measure of model quality to select final tuning parameter values is not sufficient. Optimization of several model quality measures is challenging. Thus, three fusion ranking methods are investigated for simultaneous assessment of multiple measures of model quality for selecting tuning parameter values. One is a supervised learning fusion rule named sum of ranking differences (SRD). The other two are non-supervised learning processes based on the sum and median operations. The effect of the number of models evaluated on the three fusion rules are also evaluated using three procedures. One procedure uses all models from all possible combinations of the tuning parameters. To reduce the number of models evaluated, an iterative process (only applicable to SRD) is applied and thresholding a model quality measure before applying the fusion rules is also used. A near infrared pharmaceutical data set requiring model updating is used to evaluate the three fusion rules. In this case, calibration of the primary conditions is for the active pharmaceutical ingredient (API) of tablets produced in a laboratory. The secondary conditions for calibration updating is for tablets produced in the full batch setting. Two model updating processes requiring selection of two unique tuning parameter values are studied. One is based on Tikhonov regularization (TR) and the other is a variation of partial least squares (PLS). The three fusion methods are shown to provide equivalent and acceptable results allowing automatic selection of the tuning parameter values. Best tuning parameter values are selected when model quality measures used with the fusion rules are for the small secondary sample set used to form the updated models. In this model updating situation, evaluation of
Fusion strategies for selecting multiple tuning parameters for multivariate calibration and other penalty based processes: A model updating application for pharmaceutical analysis

International Nuclear Information System (INIS)

Tencate, Alister J.; Kalivas, John H.; White, Alexander J.

2016-01-01

New multivariate calibration methods and other processes are being developed that require selection of multiple tuning parameter (penalty) values to form the final model. With one or more tuning parameters, using only one measure of model quality to select final tuning parameter values is not sufficient. Optimization of several model quality measures is challenging. Thus, three fusion ranking methods are investigated for simultaneous assessment of multiple measures of model quality for selecting tuning parameter values. One is a supervised learning fusion rule named sum of ranking differences (SRD). The other two are non-supervised learning processes based on the sum and median operations. The effect of the number of models evaluated on the three fusion rules are also evaluated using three procedures. One procedure uses all models from all possible combinations of the tuning parameters. To reduce the number of models evaluated, an iterative process (only applicable to SRD) is applied and thresholding a model quality measure before applying the fusion rules is also used. A near infrared pharmaceutical data set requiring model updating is used to evaluate the three fusion rules. In this case, calibration of the primary conditions is for the active pharmaceutical ingredient (API) of tablets produced in a laboratory. The secondary conditions for calibration updating is for tablets produced in the full batch setting. Two model updating processes requiring selection of two unique tuning parameter values are studied. One is based on Tikhonov regularization (TR) and the other is a variation of partial least squares (PLS). The three fusion methods are shown to provide equivalent and acceptable results allowing automatic selection of the tuning parameter values. Best tuning parameter values are selected when model quality measures used with the fusion rules are for the small secondary sample set used to form the updated models. In this model updating situation, evaluation of
Estimating resist parameters in optical lithography using the extended Nijboer-Zernike theory

NARCIS (Netherlands)

Dirksen, P.; Braat, J.J.M.; Janssen, A.J.E.M.

2006-01-01

This study presents an experimental method to determine the resist parameters at the origin of a general blurring of a projected aerial image. The resist model includes the effects of diffusion in the horizontal plane and image blur that originates from a stochastic variation of the focus parameter.
Contribution of long-term accounting for raindrop size distribution variations on quantitative precipitation estimation by weather radar: Disdrometers vs parameter optimization

Science.gov (United States)

Hazenberg, P.; Uijlenhoet, R.; Leijnse, H.

2015-12-01

Volumetric weather radars provide information on the characteristics of precipitation at high spatial and temporal resolution. Unfortunately, rainfall measurements by radar are affected by multiple error sources, which can be subdivided into two main groups: 1) errors affecting the volumetric reflectivity measurements (e.g. ground clutter, vertical profile of reflectivity, attenuation, etc.), and 2) errors related to the conversion of the observed reflectivity (Z) values into rainfall intensity (R) and specific attenuation (k). Until the recent wide-scale implementation of dual-polarimetric radar, this second group of errors received relatively little attention, focusing predominantly on precipitation type-dependent Z-R and Z-k relations. The current work accounts for the impact of variations of the drop size distribution (DSD) on the radar QPE performance. We propose to link the parameters of the Z-R and Z-k relations directly to those of the normalized gamma DSD. The benefit of this procedure is that it reduces the number of unknown parameters. In this work, the DSD parameters are obtained using 1) surface observations from a Parsivel and Thies LPM disdrometer, and 2) a Monte Carlo optimization procedure using surface rain gauge observations. The impact of both approaches for a given precipitation type is assessed for 45 days of summertime precipitation observed within The Netherlands. Accounting for DSD variations using disdrometer observations leads to an improved radar QPE product as compared to applying climatological Z-R and Z-k relations. However, overall precipitation intensities are still underestimated. This underestimation is expected to result from unaccounted errors (e.g. transmitter calibration, erroneous identification of precipitation as clutter, overshooting and small-scale variability). In case the DSD parameters are optimized, the performance of the radar is further improved, resulting in the best performance of the radar QPE product. However
NONLINEAR PLANT PIECEWISE-CONTINUOUS MODEL MATRIX PARAMETERS ESTIMATION

Directory of Open Access Journals (Sweden)

Roman L. Leibov

2017-09-01

Full Text Available This paper presents a nonlinear plant piecewise-continuous model matrix parameters estimation technique using nonlinear model time responses and random search method. One of piecewise-continuous model application areas is defined. The results of proposed approach application for aircraft turbofan engine piecewisecontinuous model formation are presented
27-day variation in solar-terrestrial parameters: Global characteristics and an origin based approach of the signals

Science.gov (United States)

Poblet, Facundo L.; Azpilicueta, Francisco

2018-05-01

The Earth and the near interplanetary medium are affected by the Sun in different ways. Those processes generated in the Sun that induce perturbations into the Magnetosphere-Ionosphere system are called geoeffective processes and show a wide range of temporal variations, like the 11-year solar cycle (long term variations), the variation of ∼27 days (recurrent variations), solar storms enduring for some days, particle acceleration events lasting for some hours, etc. In this article, the periodicity of ∼27 days associated with the solar synodic rotation period is investigated. The work is mainly focused on studying the resulting 27-day periodic signal in the magnetic activity, by the analysis of the horizontal component of the magnetic field registered on a set of 103 magnetic observatories distributed around the world. For this a new method to isolate the periodicity of interest has been developed consisting of two main steps: the first one consists of removing the linear trend corresponding to every calendar year from the data series, and the second one of removing from the resulting series a smoothed version of it obtained by applying a 30-day moving average. The result at the end of this process is a data series in which all the signal with periods larger than 30 days are canceled. The most important characteristics observed in the resulting signals are two main amplitude modulations: the first and most prominent related to the 11-year solar cycle and the second one with a semiannual pattern. In addition, the amplitude of the signal shows a dependence on the geomagnetic latitude of the observatory with a significant discontinuity at approx. ±60°. The processing scheme was also applied to other parameters that are widely used to characterize the energy transfer from the Sun to the Earth: F10.7 and Mg II indices and the ionospheric vertical total electron content (vTEC) were considered for radiative interactions; and the solar wind velocity for the non
Decision-case mix model for analyzing variation in cesarean rates.

Science.gov (United States)

Eldenburg, L; Waller, W S

2001-01-01

This article contributes a decision-case mix model for analyzing variation in c-section rates. Like recent contributions to the literature, the model systematically takes into account the effect of case mix. Going beyond past research, the model highlights differences in physician decision making in response to obstetric factors. Distinguishing the effects of physician decision making and case mix is important in understanding why c-section rates vary and in developing programs to effect change in physician behavior. The model was applied to a sample of deliveries at a hospital where physicians exhibited considerable variation in their c-section rates. Comparing groups with a low versus high rate, the authors' general conclusion is that the difference in physician decision tendencies (to perform a c-section), in response to specific obstetric factors, is at least as important as case mix in explaining variation in c-section rates. The exact effects of decision making versus case mix depend on how the model application defines the obstetric condition of interest and on the weighting of deliveries by their estimated "risk of Cesarean." The general conclusion is supported by an additional analysis that uses the model's elements to predict individual physicians' annual c-section rates.
Gamma-variate modeling of indicator dilution curves in electrical impedance tomography.

Science.gov (United States)

Hentze, Benjamin; Muders, Thomas; Luepschen, Henning; Leonhardt, Steffen; Putensen, Christian; Walter, Marian

2017-07-01

Electrical impedance tomography (EIT) is a non-invasive imaging technique, that can be used to monitor regional lung ventilation (V̇) in intensive care units (ICU) at bedside. This work introduces a method to extract regional lung perfusion (Q̇) from EIT image streams in order to quantify regional gas exchange in the lungs. EIT data from a single porcine animal trial, recorded during injection of a contrast agent (NaCl 10%) into a central venous catheter (CVC), are used for evaluation. Using semi-negative matrix factorization (Semi-NMF) a set of source signals is extracted from the data. A subsequent non-linear fit of a gamma-variate model to the source signals results in model signals, describing contrast agent flow through the cardio-pulmonary system. A linear fit of the model signals to the EIT image stream then yields functional images ofQ̇. Additionally, a pulmonary transit function (PTF) and parameters, such as mean transit time (MTT), time to peak (TTP) and area under curve (AUC) are derived. In result, EIT was used to track changes of regional lung ventilation to perfusion ratio (V̇/Q̇) during changes of positive end-expiratory pressure (PEEP). Furthermore, correlations of MTT and AUC with cardiac output (CO) indicate that CO measurement by EIT might be possible.
Size-density scaling in protists and the links between consumer-resource interaction parameters.

Science.gov (United States)

DeLong, John P; Vasseur, David A

2012-11-01

Recent work indicates that the interaction between body-size-dependent demographic processes can generate macroecological patterns such as the scaling of population density with body size. In this study, we evaluate this possibility for grazing protists and also test whether demographic parameters in these models are correlated after controlling for body size. We compiled data on the body-size dependence of consumer-resource interactions and population density for heterotrophic protists grazing algae in laboratory studies. We then used nested dynamic models to predict both the height and slope of the scaling relationship between population density and body size for these protists. We also controlled for consumer size and assessed links between model parameters. Finally, we used the models and the parameter estimates to assess the individual- and population-level dependence of resource use on body-size and prey-size selection. The predicted size-density scaling for all models matched closely to the observed scaling, and the simplest model was sufficient to predict the pattern. Variation around the mean size-density scaling relationship may be generated by variation in prey productivity and area of capture, but residuals are relatively insensitive to variation in prey size selection. After controlling for body size, many consumer-resource interaction parameters were correlated, and a positive correlation between residual prey size selection and conversion efficiency neutralizes the apparent fitness advantage of taking large prey. Our results indicate that widespread community-level patterns can be explained with simple population models that apply consistently across a range of sizes. They also indicate that the parameter space governing the dynamics and the steady states in these systems is structured such that some parts of the parameter space are unlikely to represent real systems. Finally, predator-prey size ratios represent a kind of conundrum, because they are
The rate-size trade-off structures intraspecific variation in Daphnia ambigua life history parameters.

Science.gov (United States)

DeLong, John P; Hanley, Torrance C

2013-01-01

The identification of trade-offs is necessary for understanding the evolution and maintenance of diversity. Here we employ the supply-demand (SD) body size optimization model to predict a trade-off between asymptotic body size and growth rate. We use the SD model to quantitatively predict the slope of the relationship between asymptotic body size and growth rate under high and low food regimes and then test the predictions against observations for Daphnia ambigua. Close quantitative agreement between observed and predicted slopes at both food levels lends support to the model and confirms that a 'rate-size' trade-off structures life history variation in this population. In contrast to classic life history expectations, growth and reproduction were positively correlated after controlling for the rate-size trade-off. We included 12 Daphnia clones in our study, but clone identity explained only some of the variation in life history traits. We also tested the hypothesis that growth rate would be positively related to intergenic spacer length (i.e. the growth rate hypothesis) across clones, but we found that clones with intermediate intergenic spacer lengths had larger asymptotic sizes and slower growth rates. Our results strongly support a resource-based optimization of body size following the SD model. Furthermore, because some resource allocation decisions necessarily precede others, understanding interdependent life history traits may require a more nested approach.
The rate-size trade-off structures intraspecific variation in Daphnia ambigua life history parameters.

Directory of Open Access Journals (Sweden)

John P DeLong

Full Text Available The identification of trade-offs is necessary for understanding the evolution and maintenance of diversity. Here we employ the supply-demand (SD body size optimization model to predict a trade-off between asymptotic body size and growth rate. We use the SD model to quantitatively predict the slope of the relationship between asymptotic body size and growth rate under high and low food regimes and then test the predictions against observations for Daphnia ambigua. Close quantitative agreement between observed and predicted slopes at both food levels lends support to the model and confirms that a 'rate-size' trade-off structures life history variation in this population. In contrast to classic life history expectations, growth and reproduction were positively correlated after controlling for the rate-size trade-off. We included 12 Daphnia clones in our study, but clone identity explained only some of the variation in life history traits. We also tested the hypothesis that growth rate would be positively related to intergenic spacer length (i.e. the growth rate hypothesis across clones, but we found that clones with intermediate intergenic spacer lengths had larger asymptotic sizes and slower growth rates. Our results strongly support a resource-based optimization of body size following the SD model. Furthermore, because some resource allocation decisions necessarily precede others, understanding interdependent life history traits may require a more nested approach.
A note on modeling of tumor regression for estimation of radiobiological parameters

International Nuclear Information System (INIS)

Zhong, Hualiang; Chetty, Indrin

2014-01-01

Purpose: Accurate calculation of radiobiological parameters is crucial to predicting radiation treatment response. Modeling differences may have a significant impact on derived parameters. In this study, the authors have integrated two existing models with kinetic differential equations to formulate a new tumor regression model for estimation of radiobiological parameters for individual patients. Methods: A system of differential equations that characterizes the birth-and-death process of tumor cells in radiation treatment was analytically solved. The solution of this system was used to construct an iterative model (Z-model). The model consists of three parameters: tumor doubling time T d , half-life of dead cells T r , and cell survival fraction SF D under dose D. The Jacobian determinant of this model was proposed as a constraint to optimize the three parameters for six head and neck cancer patients. The derived parameters were compared with those generated from the two existing models: Chvetsov's model (C-model) and Lim's model (L-model). The C-model and L-model were optimized with the parameter T d fixed. Results: With the Jacobian-constrained Z-model, the mean of the optimized cell survival fractions is 0.43 ± 0.08, and the half-life of dead cells averaged over the six patients is 17.5 ± 3.2 days. The parameters T r and SF D optimized with the Z-model differ by 1.2% and 20.3% from those optimized with the T d -fixed C-model, and by 32.1% and 112.3% from those optimized with the T d -fixed L-model, respectively. Conclusions: The Z-model was analytically constructed from the differential equations of cell populations that describe changes in the number of different tumor cells during the course of radiation treatment. The Jacobian constraints were proposed to optimize the three radiobiological parameters. The generated model and its optimization method may help develop high-quality treatment regimens for individual patients

On the effect of model parameters on forecast objects

Science.gov (United States)

Marzban, Caren; Jones, Corinne; Li, Ning; Sandgathe, Scott

2018-04-01

Many physics-based numerical models produce a gridded, spatial field of forecasts, e.g., a temperature map. The field for some quantities generally consists of spatially coherent and disconnected objects. Such objects arise in many problems, including precipitation forecasts in atmospheric models, eddy currents in ocean models, and models of forest fires. Certain features of these objects (e.g., location, size, intensity, and shape) are generally of interest. Here, a methodology is developed for assessing the impact of model parameters on the features of forecast objects. The main ingredients of the methodology include the use of (1) Latin hypercube sampling for varying the values of the model parameters, (2) statistical clustering algorithms for identifying objects, (3) multivariate multiple regression for assessing the impact of multiple model parameters on the distribution (across the forecast domain) of object features, and (4) methods for reducing the number of hypothesis tests and controlling the resulting errors. The final output of the methodology is a series of box plots and confidence intervals that visually display the sensitivities. The methodology is demonstrated on precipitation forecasts from a mesoscale numerical weather prediction model.
Variation in the Kozak sequence of WNT16 results in an increased translation and is associated with osteoporosis related parameters

DEFF Research Database (Denmark)

Hendrickx, Gretl; Boudin, Eveline; Fijałkowski, Igor

2014-01-01

on osteoporosis related parameters. Hereto, we performed a WNT16 candidate gene association study in a population of healthy Caucasian men from the Odense Androgen Study (OAS). Using HapMap, five tagSNPs and one multimarker test were selected for genotyping to cover most of the common genetic variation...
An automatic and effective parameter optimization method for model tuning

Directory of Open Access Journals (Sweden)

T. Zhang

2015-11-01

simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9 %. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameter tuning during the model development stage.
A variational approach to chiral quark models

International Nuclear Information System (INIS)

Futami, Yasuhiko; Odajima, Yasuhiko; Suzuki, Akira.

1987-01-01

A variational approach is applied to a chiral quark model to test the validity of the perturbative treatment of the pion-quark interaction based on the chiral symmetry principle. It is indispensably related to the chiral symmetry breaking radius if the pion-quark interaction can be regarded as a perturbation. (author)
Variational Bayesian Inference of Line Spectra

DEFF Research Database (Denmark)

Badiu, Mihai Alin; Hansen, Thomas Lundgaard; Fleury, Bernard Henri

2017-01-01

parameters. We propose an accurate representation of the pdfs of the frequencies by mixtures of von Mises pdfs, which yields closed-form expectations. We define the algorithm VALSE in which the estimates of the pdfs and parameters are iteratively updated. VALSE is a gridless, convergent method, does......; and the coefficients are governed by a Bernoulli-Gaussian prior model turning model order selection into binary sequence detection. Unlike earlier works which retain only point estimates of the frequencies, we undertake a more complete Bayesian treatment by estimating the posterior probability density functions (pdfs......) of the frequencies and computing expectations over them. Thus, we additionally capture and operate with the uncertainty of the frequency estimates. Aiming to maximize the model evidence, variational optimization provides analytic approximations of the posterior pdfs and also gives estimates of the additional...
A compact cyclic plasticity model with parameter evolution

DEFF Research Database (Denmark)

Krenk, Steen; Tidemann, L.

2017-01-01

The paper presents a compact model for cyclic plasticity based on energy in terms of external and internal variables, and plastic yielding described by kinematic hardening and a flow potential with an additive term controlling the nonlinear cyclic hardening. The model is basically described by five...... parameters: external and internal stiffness, a yield stress and a limiting ultimate stress, and finally a parameter controlling the gradual development of plastic deformation. Calibration against numerous experimental results indicates that typically larger plastic strains develop than predicted...
Luminescence model with quantum impact parameter for low energy ions

CERN Document Server

Cruz-Galindo, H S; Martínez-Davalos, A; Belmont-Moreno, E; Galindo, S

2002-01-01

We have modified an analytical model of induced light production by energetic ions interacting in scintillating materials. The original model is based on the distribution of energy deposited by secondary electrons produced along the ion's track. The range of scattered electrons, and thus the energy distribution, depends on a classical impact parameter between the electron and the ion's track. The only adjustable parameter of the model is the quenching density rho sub q. The modification here presented, consists in proposing a quantum impact parameter that leads to a better fit of the model to the experimental data at low incident ion energies. The light output response of CsI(Tl) detectors to low energy ions (<3 MeV/A) is fitted with the modified model and comparison is made to the original model.
Inhalation Exposure Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

M. A. Wasiolek

2003-09-24

This analysis is one of the nine reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2003a) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents a set of input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for a Yucca Mountain repository. This report, ''Inhalation Exposure Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003b). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available at that time. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this analysis report. This analysis report defines and justifies values of mass loading, which is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Measurements of mass loading are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air surrounding crops and concentrations in air
Repetitive Identification of Structural Systems Using a Nonlinear Model Parameter Refinement Approach

Directory of Open Access Journals (Sweden)

Jeng-Wen Lin

2009-01-01

Full Text Available This paper proposes a statistical confidence interval based nonlinear model parameter refinement approach for the health monitoring of structural systems subjected to seismic excitations. The developed model refinement approach uses the 95% confidence interval of the estimated structural parameters to determine their statistical significance in a least-squares regression setting. When the parameters' confidence interval covers the zero value, it is statistically sustainable to truncate such parameters. The remaining parameters will repetitively undergo such parameter sifting process for model refinement until all the parameters' statistical significance cannot be further improved. This newly developed model refinement approach is implemented for the series models of multivariable polynomial expansions: the linear, the Taylor series, and the power series model, leading to a more accurate identification as well as a more controllable design for system vibration control. Because the statistical regression based model refinement approach is intrinsically used to process a “batch” of data and obtain an ensemble average estimation such as the structural stiffness, the Kalman filter and one of its extended versions is introduced to the refined power series model for structural health monitoring.
Integral Parameters of the Thermal Neutron Scattering Law

Energy Technology Data Exchange (ETDEWEB)

Purohit, S N

1964-09-15

Integral parameters of the thermal neutron scattering law - the thermalization binding parameter (M{sub 2}), the Placzek's moments of the generalized frequency spectrum of dynamical modes and the energy transfer moments of the scattering law - are theoretically discussed. A detailed study of the variation of M{sub 2}, the thermalization time constant and the effective temperature of the vibrating atoms, with the relative weight between intra-molecular vibrations and hindered rotations for H{sub 2}O, is presented. Theoretical results for different scattering models of H{sub 2}O are compared with the measurements of integral experiments. A set of integral parameters for D{sub 2}O, using Butler's model, have been obtained. Importance of the structure of hindered rotations of H{sub 2}O and D{sub 2}O in the study of integral parameters has also been discussed.
Seasonal changes in climatic parameters and their relationship with the incidence of pneumococcal bacteraemia in Denmark

DEFF Research Database (Denmark)

Tvedebrink, Torben; Lundbye-Christensen, Søren; Thomsen, R.W.

2008-01-01

The seasonal variation in the incidence of invasive pneumococcal disease is well recognized, but little is known about its relationship with actual changes in climatic parameters. In this 8-year longitudinal population-based study in Denmark, a harmonic sinusoidal regression model was used...... to examine whether preceding changes in climatic parameters corresponded with subsequent variations in the incidence of pneumococcal bacteraemia, independently of seasonal variation. The study shows that changes in temperature can be used to closely predict peaks in the incidence of pneumococcal bacteraemia...
MODELING OF FUEL SPRAY CHARACTERISTICS AND DIESEL COMBUSTION CHAMBER PARAMETERS

Directory of Open Access Journals (Sweden)

G. M. Kukharonak

2011-01-01

Full Text Available The computer model for coordination of fuel spray characteristics with diesel combustion chamber parameters has been created in the paper. The model allows to observe fuel sprays develоpment in diesel cylinder at any moment of injection, to calculate characteristics of fuel sprays with due account of a shape and dimensions of a combustion chamber, timely to change fuel injection characteristics and supercharging parameters, shape and dimensions of a combustion chamber. Moreover the computer model permits to determine parameters of holes in an injector nozzle that provides the required fuel sprays characteristics at the stage of designing a diesel engine. Combustion chamber parameters for 4ЧН11/12.5 diesel engine have been determined in the paper.
Traveltime approximations and parameter estimation for orthorhombic media

KAUST Repository

Masmoudi, Nabil

2016-05-30

Building anisotropy models is necessary for seismic modeling and imaging. However, anisotropy estimation is challenging due to the trade-off between inhomogeneity and anisotropy. Luckily, we can estimate the anisotropy parameters Building anisotropy models is necessary for seismic modeling and imaging. However, anisotropy estimation is challenging due to the trade-off between inhomogeneity and anisotropy. Luckily, we can estimate the anisotropy parameters if we relate them analytically to traveltimes. Using perturbation theory, we have developed traveltime approximations for orthorhombic media as explicit functions of the anellipticity parameters η1, η2, and Δχ in inhomogeneous background media. The parameter Δχ is related to Tsvankin-Thomsen notation and ensures easier computation of traveltimes in the background model. Specifically, our expansion assumes an inhomogeneous ellipsoidal anisotropic background model, which can be obtained from well information and stacking velocity analysis. We have used the Shanks transform to enhance the accuracy of the formulas. A homogeneous medium simplification of the traveltime expansion provided a nonhyperbolic moveout description of the traveltime that was more accurate than other derived approximations. Moreover, the formulation provides a computationally efficient tool to solve the eikonal equation of an orthorhombic medium, without any constraints on the background model complexity. Although, the expansion is based on the factorized representation of the perturbation parameters, smooth variations of these parameters (represented as effective values) provides reasonable results. Thus, this formulation provides a mechanism to estimate the three effective parameters η1, η2, and Δχ. We have derived Dix-type formulas for orthorhombic medium to convert the effective parameters to their interval values.
Evolving Non-Dominated Parameter Sets for Computational Models from Multiple Experiments

Science.gov (United States)

Lane, Peter C. R.; Gobet, Fernand

2013-03-01

Creating robust, reproducible and optimal computational models is a key challenge for theorists in many sciences. Psychology and cognitive science face particular challenges as large amounts of data are collected and many models are not amenable to analytical techniques for calculating parameter sets. Particular problems are to locate the full range of acceptable model parameters for a given dataset, and to confirm the consistency of model parameters across different datasets. Resolving these problems will provide a better understanding of the behaviour of computational models, and so support the development of general and robust models. In this article, we address these problems using evolutionary algorithms to develop parameters for computational models against multiple sets of experimental data; in particular, we propose the `speciated non-dominated sorting genetic algorithm' for evolving models in several theories. We discuss the problem of developing a model of categorisation using twenty-nine sets of data and models drawn from four different theories. We find that the evolutionary algorithms generate high quality models, adapted to provide a good fit to all available data.
Variation of intrinsic magnetic parameters of single domain Co-N interstitial nitrides synthesized via hexa-ammine cobalt nitrate route

Energy Technology Data Exchange (ETDEWEB)

Ningthoujam, R.S. [Department of Chemistry, Indian Institute of Technology, Kanpur 208016 (India); Chemistry Division, Bhabha Atomic Research Centre, Mumbai 400085 (India); Panda, R.N., E-mail: rnp@bits-goa.ac.in [Chemistry Group, Birla Institute of Technology and Science-Pilani, Goa Campus, Zuari Nagar, Goa 403726 (India); Gajbhiye, N.S. [Department of Chemistry, Indian Institute of Technology, Kanpur 208016 (India)

2012-05-15

Highlights: Black-Right-Pointing-Pointer Variation of intrinsic magnetic parameters of Co-N. Black-Right-Pointing-Pointer Synthesis by hexa-ammine cobalt complex route. Black-Right-Pointing-Pointer Tuning of coercivity by variation of size. - Abstract: We report the variation of Curie temperature (T{sub c}) and coercivity (H{sub c}) of the single domain Co-N interstitial materials synthesized via nitridation of the hexa-ammine Cobalt(III) nitrate complex at 673 K. Co-N materials crystallize in the fcc cubic structure with unit cell parameter, a = 3.552 Angstrom-Sign . The X-ray diffraction (XRD) peaks are broader indicating the materials to be nano-structured with crystallite sizes of 5-14 nm. The scanning electron microscopy (SEM) and transmission electron microscopy (TEM) studies confirm the nanocrystalline nature of the materials. TEM images show chain-like clusters indicating dipolar interactions between the particles. Magnetic studies focus on the existence of giant magnetic Co atoms in the Co-N lattice that are not influenced by the thermal relaxation. The values of the H{sub c} could be tuned with the dimension of the particles. The values of T{sub c} of the nitride materials are masked by the onset of the ferromagnetic to superparamagnetic transition at higher temperatures. Thermomagnetic studies show an increasing trend in the Curie temperature, T{sub c}, with decrease in particle dimension. This result has been explained qualitatively on the basis of ferromagnetic to superparamagnetic transition and finite size scaling effects.
On the relationship between input parameters in two-mass vocal-fold model with acoustical coupling an signal parameters of the glottal flow

NARCIS (Netherlands)

van Hirtum, Annemie; Lopez, Ines; Hirschberg, Abraham; Pelorson, Xavier

2003-01-01

In this paper the sensitivity of the two-mass model with acoustical coupling to the model input-parameters is assessed. The model-output or the glottal volume air flow is characterised by signal-parameters in the time-domain. The influence of changing input-parameters on the signal-parameters is
Lumped-Parameter Models for Windturbine Footings on Layered Ground

DEFF Research Database (Denmark)

Andersen, Lars

The design of modern wind turbines is typically based on lifetime analyses using aeroelastic codes. In this regard, the impedance of the foundations must be described accurately without increasing the overall size of the computationalmodel significantly. This may be obtained by the fitting...... of a lumped-parameter model to the results of a rigorous model or experimental results. In this paper, guidelines are given for the formulation of such lumped-parameter models and examples are given in which the models are utilised for the analysis of a wind turbine supported by a surface footing on a layered...
Oyster Creek cycle 10 nodal model parameter optimization study using PSMS

International Nuclear Information System (INIS)

Dougher, J.D.

1987-01-01

The power shape monitoring system (PSMS) is an on-line core monitoring system that uses a three-dimensional nodal code (NODE-B) to perform nodal power calculations and compute thermal margins. The PSMS contains a parameter optimization function that improves the ability of NODE-B to accurately monitor core power distributions. This functions iterates on the model normalization parameters (albedos and mixing factors) to obtain the best agreement between predicted and measured traversing in-core probe (TIP) reading on a statepoint-by-statepoint basis. Following several statepoint optimization runs, an average set of optimized normalization parameters can be determined and can be implemented into the current or subsequent cycle core model for on-line core monitoring. A statistical analysis of 19 high-power steady-state state-points throughout Oyster Creek cycle 10 operation has shown a consistently poor virgin model performance. The normalization parameters used in the cycle 10 NODE-B model were based on a cycle 8 study, which evaluated only Exxon fuel types. The introduction of General Electric (GE) fuel into cycle 10 (172 assemblies) was a significant fuel/core design change that could have altered the optimum set of normalization parameters. Based on the need to evaluate a potential change in the model normalization parameters for cycle 11 and in an attempt to account for the poor cycle 10 model performance, a parameter optimization study was performed
Determining extreme parameter correlation in ground water models

DEFF Research Database (Denmark)

Hill, Mary Cole; Østerby, Ole

2003-01-01

can go undetected even by experienced modelers. Extreme parameter correlation can be detected using parameter correlation coefficients, but their utility depends on the presence of sufficient, but not excessive, numerical imprecision of the sensitivities, such as round-off error. This work...... investigates the information that can be obtained from parameter correlation coefficients in the presence of different levels of numerical imprecision, and compares it to the information provided by an alternative method called the singular value decomposition (SVD). Results suggest that (1) calculated...... correlation coefficients with absolute values that round to 1.00 were good indicators of extreme parameter correlation, but smaller values were not necessarily good indicators of lack of correlation and resulting unique parameter estimates; (2) the SVD may be more difficult to interpret than parameter...
Sensitivity of corneal biomechanical and optical behavior to material parameters using design of experiments method.

Science.gov (United States)

Xu, Mengchen; Lerner, Amy L; Funkenbusch, Paul D; Richhariya, Ashutosh; Yoon, Geunyoung

2018-02-01

The optical performance of the human cornea under intraocular pressure (IOP) is the result of complex material properties and their interactions. The measurement of the numerous material parameters that define this material behavior may be key in the refinement of patient-specific models. The goal of this study was to investigate the relative contribution of these parameters to the biomechanical and optical responses of human cornea predicted by a widely accepted anisotropic hyperelastic finite element model, with regional variations in the alignment of fibers. Design of experiments methods were used to quantify the relative importance of material properties including matrix stiffness, fiber stiffness, fiber nonlinearity and fiber dispersion under physiological IOP. Our sensitivity results showed that corneal apical displacement was influenced nearly evenly by matrix stiffness, fiber stiffness and nonlinearity. However, the variations in corneal optical aberrations (refractive power and spherical aberration) were primarily dependent on the value of the matrix stiffness. The optical aberrations predicted by variations in this material parameter were sufficiently large to predict clinically important changes in retinal image quality. Therefore, well-characterized individual variations in matrix stiffness could be critical in cornea modeling in order to reliably predict optical behavior under different IOPs or after corneal surgery.

Time-varying parameter models for catchments with land use change: the importance of model structure

Science.gov (United States)

Pathiraja, Sahani; Anghileri, Daniela; Burlando, Paolo; Sharma, Ashish; Marshall, Lucy; Moradkhani, Hamid

2018-05-01

Rapid population and economic growth in Southeast Asia has been accompanied by extensive land use change with consequent impacts on catchment hydrology. Modeling methodologies capable of handling changing land use conditions are therefore becoming ever more important and are receiving increasing attention from hydrologists. A recently developed data-assimilation-based framework that allows model parameters to vary through time in response to signals of change in observations is considered for a medium-sized catchment (2880 km2) in northern Vietnam experiencing substantial but gradual land cover change. We investigate the efficacy of the method as well as the importance of the chosen model structure in ensuring the success of a time-varying parameter method. The method was used with two lumped daily conceptual models (HBV and HyMOD) that gave good-quality streamflow predictions during pre-change conditions. Although both time-varying parameter models gave improved streamflow predictions under changed conditions compared to the time-invariant parameter model, persistent biases for low flows were apparent in the HyMOD case. It was found that HyMOD was not suited to representing the modified baseflow conditions, resulting in extreme and unrealistic time-varying parameter estimates. This work shows that the chosen model can be critical for ensuring the time-varying parameter framework successfully models streamflow under changing land cover conditions. It can also be used to determine whether land cover changes (and not just meteorological factors) contribute to the observed hydrologic changes in retrospective studies where the lack of a paired control catchment precludes such an assessment.
Time-varying parameter models for catchments with land use change: the importance of model structure

Directory of Open Access Journals (Sweden)

S. Pathiraja

2018-05-01

Full Text Available Rapid population and economic growth in Southeast Asia has been accompanied by extensive land use change with consequent impacts on catchment hydrology. Modeling methodologies capable of handling changing land use conditions are therefore becoming ever more important and are receiving increasing attention from hydrologists. A recently developed data-assimilation-based framework that allows model parameters to vary through time in response to signals of change in observations is considered for a medium-sized catchment (2880 km2 in northern Vietnam experiencing substantial but gradual land cover change. We investigate the efficacy of the method as well as the importance of the chosen model structure in ensuring the success of a time-varying parameter method. The method was used with two lumped daily conceptual models (HBV and HyMOD that gave good-quality streamflow predictions during pre-change conditions. Although both time-varying parameter models gave improved streamflow predictions under changed conditions compared to the time-invariant parameter model, persistent biases for low flows were apparent in the HyMOD case. It was found that HyMOD was not suited to representing the modified baseflow conditions, resulting in extreme and unrealistic time-varying parameter estimates. This work shows that the chosen model can be critical for ensuring the time-varying parameter framework successfully models streamflow under changing land cover conditions. It can also be used to determine whether land cover changes (and not just meteorological factors contribute to the observed hydrologic changes in retrospective studies where the lack of a paired control catchment precludes such an assessment.
Metamodel-based inverse method for parameter identification: elastic-plastic damage model

Science.gov (United States)

Huang, Changwu; El Hami, Abdelkhalak; Radi, Bouchaïb

2017-04-01

This article proposed a metamodel-based inverse method for material parameter identification and applies it to elastic-plastic damage model parameter identification. An elastic-plastic damage model is presented and implemented in numerical simulation. The metamodel-based inverse method is proposed in order to overcome the disadvantage in computational cost of the inverse method. In the metamodel-based inverse method, a Kriging metamodel is constructed based on the experimental design in order to model the relationship between material parameters and the objective function values in the inverse problem, and then the optimization procedure is executed by the use of a metamodel. The applications of the presented material model and proposed parameter identification method in the standard A 2017-T4 tensile test prove that the presented elastic-plastic damage model is adequate to describe the material's mechanical behaviour and that the proposed metamodel-based inverse method not only enhances the efficiency of parameter identification but also gives reliable results.
House thermal model parameter estimation method for Model Predictive Control applications

NARCIS (Netherlands)

van Leeuwen, Richard Pieter; de Wit, J.B.; Fink, J.; Smit, Gerardus Johannes Maria

In this paper we investigate thermal network models with different model orders applied to various Dutch low-energy house types with high and low interior thermal mass and containing floor heating. Parameter estimations are performed by using data from TRNSYS simulations. The paper discusses results
Time Variations of Observed H α Line Profiles and Precipitation Depths of Nonthermal Electrons in a Solar Flare

Energy Technology Data Exchange (ETDEWEB)

Falewicz, Robert; Radziszewski, Krzysztof; Rudawy, Paweł; Berlicki, Arkadiusz, E-mail: falewicz@astro.uni.wroc.pl, E-mail: radziszewski@astro.uni.wroc.pl, E-mail: rudawy@astro.uni.wroc.pl, E-mail: berlicki@astro.uni.wroc.pl [Astronomical Institute, University of Wrocław, 51-622 Wrocław, ul. Kopernika 11 (Poland)

2017-10-01

We compare time variations of the H α and X-ray emissions observed during the pre-impulsive and impulsive phases of the C1.1-class solar flare on 2013 June 21 with those of plasma parameters and synthesized X-ray emission from a 1D hydrodynamic numerical model of the flare. The numerical model was calculated assuming that the external energy is delivered to the flaring loop by nonthermal electrons (NTEs). The H α spectra and images were obtained using the Multi-channel Subtractive Double Pass spectrograph with a time resolution of 50 ms. The X-ray fluxes and spectra were recorded by RHESSI . Pre-flare geometric and thermodynamic parameters of the model and the delivered energy were estimated using RHESSI data. The time variations of the X-ray light curves in various energy bands and those of the H α intensities and line profiles were well correlated. The timescales of the observed variations agree with the calculated variations of the plasma parameters in the flaring loop footpoints, reflecting the time variations of the vertical extent of the energy deposition layer. Our result shows that the fast time variations of the H α emission of the flaring kernels can be explained by momentary changes of the deposited energy flux and the variations of the penetration depths of the NTEs.
Inverse modeling of hydrologic parameters using surface flux and runoff observations in the Community Land Model

Science.gov (United States)

Sun, Y.; Hou, Z.; Huang, M.; Tian, F.; Leung, L. Ruby

2013-12-01

This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4). Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Both deterministic least-square fitting and stochastic Markov-chain Monte Carlo (MCMC)-Bayesian inversion approaches are evaluated by applying them to CLM4 at selected sites with different climate and soil conditions. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find that using model parameters calibrated by the sampling-based stochastic inversion approaches provides significant improvements in the model simulations compared to using default CLM4 parameter values, and that as more information comes in, the predictive intervals (ranges of posterior distributions) of the calibrated parameters become narrower. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty bounds.
Lumped parameter models for the interpretation of environmental tracer data

Energy Technology Data Exchange (ETDEWEB)

Maloszewski, P [GSF-Inst. for Hydrology, Oberschleissheim (Germany); Zuber, A [Institute of Nuclear Physics, Cracow (Poland)

1996-10-01

Principles of the lumped-parameter approach to the interpretation of environmental tracer data are given. The following models are considered: the piston flow model (PFM), exponential flow model (EM), linear model (LM), combined piston flow and exponential flow model (EPM), combined linear flow and piston flow model (LPM), and dispersion model (DM). The applicability of these models for the interpretation of different tracer data is discussed for a steady state flow approximation. Case studies are given to exemplify the applicability of the lumped-parameter approach. Description of a user-friendly computer program is given. (author). 68 refs, 25 figs, 4 tabs.
Lumped parameter models for the interpretation of environmental tracer data

International Nuclear Information System (INIS)

Maloszewski, P.; Zuber, A.

1996-01-01

Principles of the lumped-parameter approach to the interpretation of environmental tracer data are given. The following models are considered: the piston flow model (PFM), exponential flow model (EM), linear model (LM), combined piston flow and exponential flow model (EPM), combined linear flow and piston flow model (LPM), and dispersion model (DM). The applicability of these models for the interpretation of different tracer data is discussed for a steady state flow approximation. Case studies are given to exemplify the applicability of the lumped-parameter approach. Description of a user-friendly computer program is given. (author). 68 refs, 25 figs, 4 tabs
Modelling spatial and temporal variations in the water quality of an artificial water reservoir in the semiarid Midwest of Argentina

Energy Technology Data Exchange (ETDEWEB)

Cid, Fabricio D., E-mail: fabricio.cid@gmail.com [Laboratory of Biology ' Prof. E. Caviedes Codelia' , Facultad de Ciencias Humanas, Universidad Nacional de San Luis, San Luis (Argentina); Laboratory of Integrative Biology, Institute for Multidisciplinary Research in Biology (IMIBIO-SL), Consejo Nacional de Investigaciones Cientificas y Tecnicas, San Luis (Argentina); Department of Biochemistry and Biological Sciences, Facultad de Quimica, Bioquimica y Farmacia, Universidad Nacional de San Luis, San Luis (Argentina); Anton, Rosa I. [Department of Analytical Chemistry, Facultad de Quimica, Bioquimica y Farmacia, Universidad Nacional de San Luis, San Luis (Argentina); Pardo, Rafael; Vega, Marisol [Department of Analytical Chemistry, Facultad de Ciencias, Universidad de Valladolid, Valladolid (Spain); Caviedes-Vidal, Enrique [Laboratory of Biology ' Prof. E. Caviedes Codelia' , Facultad de Ciencias Humanas, Universidad Nacional de San Luis, San Luis (Argentina); Laboratory of Integrative Biology, Institute for Multidisciplinary Research in Biology (IMIBIO-SL), Consejo Nacional de Investigaciones Cientificas y Tecnicas, San Luis (Argentina); Department of Biochemistry and Biological Sciences, Facultad de Quimica, Bioquimica y Farmacia, Universidad Nacional de San Luis, San Luis (Argentina)

2011-10-31

Highlights: {yields} Water quality of an Argentinean reservoir has been investigated by N-way PCA. {yields} PARAFAC mode modelled spatial and seasonal variations of water composition. {yields} Two factors related with organic and lead pollution have been identified. {yields} The most polluted areas of the reservoir were located, and polluting sources identified. - Abstract: Temporal and spatial patterns of water quality of an important artificial water reservoir located in the semiarid Midwest of Argentina were investigated using chemometric techniques. Surface water samples were collected at 38 points of the water reservoir during eleven sampling campaigns between October 1998 and June 2000, covering the warm wet season and the cold dry season, and analyzed for dissolved oxygen (DO), conductivity, pH, ammonium, nitrate, nitrite, total dissolved solids (TDS), alkalinity, hardness, bicarbonate, chloride, sulfate, calcium, magnesium, fluoride, sodium, potassium, iron, aluminum, silica, phosphate, sulfide, arsenic, chromium, lead, cadmium, chemical oxygen demand (COD), biochemical oxygen demand (BOD), viable aerobic bacteria (VAB) and total coliform bacteria (TC). Concentrations of lead, ammonium, nitrite and coliforms were higher than the maximum allowable limits for drinking water in a large proportion of the water samples. To obtain a general representation of the spatial and temporal trends of the water quality parameters at the reservoir, the three-dimensional dataset (sampling sites x parameters x sampling campaigns) has been analyzed by matrix augmentation principal component analysis (MA-PCA) and N-way principal component analysis (N-PCA) using Tucker3 and PARAFAC (Parallel Factor Analysis) models. MA-PCA produced a component accounting for the general behavior of parameters associated with organic pollution. The Tucker3 models were not appropriate for modelling the water quality dataset. The two-factor PARAFAC model provided the best picture to understand the
Modelling spatial and temporal variations in the water quality of an artificial water reservoir in the semiarid Midwest of Argentina

International Nuclear Information System (INIS)

Cid, Fabricio D.; Anton, Rosa I.; Pardo, Rafael; Vega, Marisol; Caviedes-Vidal, Enrique

2011-01-01

Highlights: → Water quality of an Argentinean reservoir has been investigated by N-way PCA. → PARAFAC mode modelled spatial and seasonal variations of water composition. → Two factors related with organic and lead pollution have been identified. → The most polluted areas of the reservoir were located, and polluting sources identified. - Abstract: Temporal and spatial patterns of water quality of an important artificial water reservoir located in the semiarid Midwest of Argentina were investigated using chemometric techniques. Surface water samples were collected at 38 points of the water reservoir during eleven sampling campaigns between October 1998 and June 2000, covering the warm wet season and the cold dry season, and analyzed for dissolved oxygen (DO), conductivity, pH, ammonium, nitrate, nitrite, total dissolved solids (TDS), alkalinity, hardness, bicarbonate, chloride, sulfate, calcium, magnesium, fluoride, sodium, potassium, iron, aluminum, silica, phosphate, sulfide, arsenic, chromium, lead, cadmium, chemical oxygen demand (COD), biochemical oxygen demand (BOD), viable aerobic bacteria (VAB) and total coliform bacteria (TC). Concentrations of lead, ammonium, nitrite and coliforms were higher than the maximum allowable limits for drinking water in a large proportion of the water samples. To obtain a general representation of the spatial and temporal trends of the water quality parameters at the reservoir, the three-dimensional dataset (sampling sites x parameters x sampling campaigns) has been analyzed by matrix augmentation principal component analysis (MA-PCA) and N-way principal component analysis (N-PCA) using Tucker3 and PARAFAC (Parallel Factor Analysis) models. MA-PCA produced a component accounting for the general behavior of parameters associated with organic pollution. The Tucker3 models were not appropriate for modelling the water quality dataset. The two-factor PARAFAC model provided the best picture to understand the spatial and
Modeling per capita state health expenditure variation: state-level characteristics matter.

Science.gov (United States)

Cuckler, Gigi; Sisko, Andrea

2013-01-01

In this paper, we describe the methods underlying the econometric model developed by the Office of the Actuary in the Centers for Medicare & Medicaid Services, to explain differences in per capita total personal health care spending by state, as described in Cuckler, et al. (2011). Additionally, we discuss many alternative model specifications to provide additional insights for valid interpretation of the model. We study per capita personal health care spending as measured by the State Health Expenditures, by State of Residence for 1991-2009, produced by the Centers for Medicare & Medicaid Services' Office of the Actuary. State-level demographic, health status, economic, and health economy characteristics were gathered from a variety of U.S. government sources, such as the Census Bureau, Bureau of Economic Analysis, the Centers for Disease Control, the American Hospital Association, and HealthLeaders-InterStudy. State-specific factors, such as income, health care capacity, and the share of elderly residents, are important factors in explaining the level of per capita personal health care spending variation among states over time. However, the slow-moving nature of health spending per capita and close relationships among state-level factors create inefficiencies in modeling this variation, likely resulting in incorrectly estimated standard errors. In addition, we find that both pooled and fixed effects models primarily capture cross-sectional variation rather than period-specific variation.
Modeling fish community dynamics in Florida Everglades: Role of temperature variation

Science.gov (United States)

Al-Rabai'ah, H. A.; Koh, H. L.; DeAngelis, Donald L.; Lee, Hooi-Ling

2002-01-01

Temperature variation is an important factor in Everglade wetlands ecology. A temperature fluctuation from 17°C to 32°C recorded in the Everglades may have significant impact on fish dynamics. The short life cycles of some of Everglade fishes has rendered this temperature variation to have even more impacts on the ecosystem. Fish population dynamic models, which do not explicitly consider seasonal oscillations in temperature, may fail to describe the details of such a population. Hence, a model for fish in freshwater marshes of the Florida Everglades that explicitly incorporates seasonal temperature variations is developed. The model's main objective is to assess the temporal pattern of fish population and densities through time subject to temperature variations. Fish population is divided into 2 functional groups (FGs) consisting of small fishes; each group is subdivided into 5-day age classes during their life cycles. Many governing sub-modules are set directly or indirectly to be temperature dependent. Growth, fecundity, prey availability, consumption rates and mortality are examples. Several mortality sub-modules are introduced in the model, of which starvation mortality is set to be proportional to the ratio of prey needed to prey available at that particular time step. As part of the calibration process, the model is run for 50 years to ensure that fish densities do not go to extinction, while the simulation period is about 8 years.
Is there any correlation between model-based perfusion parameters and model-free parameters of time-signal intensity curve on dynamic contrast enhanced MRI in breast cancer patients?

Energy Technology Data Exchange (ETDEWEB)

Yi, Boram; Kang, Doo Kyoung; Kim, Tae Hee [Ajou University School of Medicine, Department of Radiology, Suwon, Gyeonggi-do (Korea, Republic of); Yoon, Dukyong [Ajou University School of Medicine, Department of Biomedical Informatics, Suwon (Korea, Republic of); Jung, Yong Sik; Kim, Ku Sang [Ajou University School of Medicine, Department of Surgery, Suwon (Korea, Republic of); Yim, Hyunee [Ajou University School of Medicine, Department of Pathology, Suwon (Korea, Republic of)

2014-05-15

To find out any correlation between dynamic contrast-enhanced (DCE) model-based parameters and model-free parameters, and evaluate correlations between perfusion parameters with histologic prognostic factors. Model-based parameters (Ktrans, Kep and Ve) of 102 invasive ductal carcinomas were obtained using DCE-MRI and post-processing software. Correlations between model-based and model-free parameters and between perfusion parameters and histologic prognostic factors were analysed. Mean Kep was significantly higher in cancers showing initial rapid enhancement (P = 0.002) and a delayed washout pattern (P = 0.001). Ve was significantly lower in cancers showing a delayed washout pattern (P = 0.015). Kep significantly correlated with time to peak enhancement (TTP) (ρ = -0.33, P < 0.001) and washout slope (ρ = 0.39, P = 0.002). Ve was significantly correlated with TTP (ρ = 0.33, P = 0.002). Mean Kep was higher in tumours with high nuclear grade (P = 0.017). Mean Ve was lower in tumours with high histologic grade (P = 0.005) and in tumours with negative oestrogen receptor status (P = 0.047). TTP was shorter in tumours with negative oestrogen receptor status (P = 0.037). We could acquire general information about the tumour vascular physiology, interstitial space volume and pathologic prognostic factors by analyzing time-signal intensity curve without a complicated acquisition process for the model-based parameters. (orig.)
Dynamics in the Parameter Space of a Neuron Model

Science.gov (United States)

Paulo, C. Rech

2012-06-01

Some two-dimensional parameter-space diagrams are numerically obtained by considering the largest Lyapunov exponent for a four-dimensional thirteen-parameter Hindmarsh—Rose neuron model. Several different parameter planes are considered, and it is shown that depending on the combination of parameters, a typical scenario can be preserved: for some choice of two parameters, the parameter plane presents a comb-shaped chaotic region embedded in a large periodic region. It is also shown that there exist regions close to these comb-shaped chaotic regions, separated by the comb teeth, organizing themselves in period-adding bifurcation cascades.
Target Selection Models with Preference Variation Between Offenders

NARCIS (Netherlands)

Townsley, Michael; Birks, Daniel; Ruiter, Stijn; Bernasco, Wim; White, Gentry

2016-01-01

Objectives: This study explores preference variation in location choice strategies of residential burglars. Applying a model of offender target selection that is grounded in assertions of the routine activity approach, rational choice perspective, crime pattern and social disorganization theories,
The Impact of Three Factors on the Recovery of Item Parameters for the Three-Parameter Logistic Model

Science.gov (United States)

Kim, Kyung Yong; Lee, Won-Chan

2017-01-01

This article provides a detailed description of three factors (specification of the ability distribution, numerical integration, and frame of reference for the item parameter estimates) that might affect the item parameter estimation of the three-parameter logistic model, and compares five item calibration methods, which are combinations of the…
Condition Parameter Modeling for Anomaly Detection in Wind Turbines

Directory of Open Access Journals (Sweden)

Yonglong Yan

2014-05-01

Full Text Available Data collected from the supervisory control and data acquisition (SCADA system, used widely in wind farms to obtain operational and condition information about wind turbines (WTs, is of important significance for anomaly detection in wind turbines. The paper presents a novel model for wind turbine anomaly detection mainly based on SCADA data and a back-propagation neural network (BPNN for automatic selection of the condition parameters. The SCADA data sets are determined through analysis of the cumulative probability distribution of wind speed and the relationship between output power and wind speed. The automatic BPNN-based parameter selection is for reduction of redundant parameters for anomaly detection in wind turbines. Through investigation of cases of WT faults, the validity of the automatic parameter selection-based model for WT anomaly detection is verified.
Determination of appropriate models and parameters for premixing calculations

Energy Technology Data Exchange (ETDEWEB)

Park, Ik-Kyu; Kim, Jong-Hwan; Min, Beong-Tae; Hong, Seong-Wan

2008-03-15

The purpose of the present work is to use experiments that have been performed at Forschungszentrum Karlsruhe during about the last ten years for determining the most appropriate models and parameters for premixing calculations. The results of a QUEOS experiment are used to fix the parameters concerning heat transfer. The QUEOS experiments are especially suited for this purpose as they have been performed with small hot solid spheres. Therefore the area of heat exchange is known. With the heat transfer parameters fixed in this way, a PREMIX experiment is recalculated. These experiments have been performed with molten alumina (Al{sub 2}O{sub 3}) as a simulant of corium. Its initial temperature is 2600 K. With these experiments the models and parameters for jet and drop break-up are tested.
Determination of appropriate models and parameters for premixing calculations

International Nuclear Information System (INIS)

Park, Ik-Kyu; Kim, Jong-Hwan; Min, Beong-Tae; Hong, Seong-Wan

2008-03-01

The purpose of the present work is to use experiments that have been performed at Forschungszentrum Karlsruhe during about the last ten years for determining the most appropriate models and parameters for premixing calculations. The results of a QUEOS experiment are used to fix the parameters concerning heat transfer. The QUEOS experiments are especially suited for this purpose as they have been performed with small hot solid spheres. Therefore the area of heat exchange is known. With the heat transfer parameters fixed in this way, a PREMIX experiment is recalculated. These experiments have been performed with molten alumina (Al 2 O 3 ) as a simulant of corium. Its initial temperature is 2600 K. With these experiments the models and parameters for jet and drop break-up are tested
A parameter network and model pyramid for managing technical information flow

International Nuclear Information System (INIS)

Sinnock, S.; Hartman, H.A.

1994-01-01

Prototypes of information management tools have been developed that can help communicate the technical basis for nuclear waste disposal to a broad audience of program scientists and engineers, project managers, and informed observers from stakeholder organizations. These tools include system engineering concepts, parameter networks expressed as influence diagrams, associated model hierarchies, and a relational database. These tools are used to express relationships among data-collection parameters, model input parameters, model output parameters, systems requirements, physical elements of a system description, and functional analysis of the contribution of physical elements and their associated parameters in satisfying the system requirements. By organizing parameters, models, physical elements, functions, and requirements in a visually reviewable network and a relational database the severe communication challenges facing participants in the nuclear waste dialog can be addressed. The network identifies the influences that data collected in the field have on measures of repository suitability, providing a visual, traceable map that clarifies the role of data and models in supporting conclusions about repository suitability. The map allows conclusions to be traced directly to the underlying parameters and models. Uncertainty in these underlying elements can be exposed to open review in the context of the effects uncertainty has on judgements about suitability. A parameter network provides a stage upon which an informed social dialog about the technical merits of a nuclear waste repository can be conducted. The basis for such dialog must be that stage, if decisions about repository suitability are to be based on a repository's ability to meet requirements embodied in laws and regulations governing disposal of nuclear wastes

Surface texture generation during cylindrical milling in the aspect of cutting force variations

International Nuclear Information System (INIS)

Wojciechowski, S; Twardowski, P; Pelic, M

2014-01-01

The work presented here concentrates on surface texture analysis, after cylindrical milling of hardened steel. Cutting force variations occurring in the machining process have direct influence on the cutter displacements and thus on the generated surface texture. Therefore, in these experiments, the influence of active number of teeth (z c ) on the cutting force variations was investigated. Cutting forces and cutter displacements were measured during machining process (online) using, namely piezoelectric force dynamometer and 3D laser vibrometer. Surface roughness parameters were measured using stylus surface profiler. The surface roughness model including cutting parameters (f z , D) and cutting force variations was also developed. The research revealed that in cylindrical milling process, cutting force variations have immediate influence on surface texture generation
Models and parameters for environmental radiological assessments

Energy Technology Data Exchange (ETDEWEB)

Miller, C W [ed.

1984-01-01

This book presents a unified compilation of models and parameters appropriate for assessing the impact of radioactive discharges to the environment. Models examined include those developed for the prediction of atmospheric and hydrologic transport and deposition, for terrestrial and aquatic food-chain bioaccumulation, and for internal and external dosimetry. Chapters have been entered separately into the data base. (ACR)
Models and parameters for environmental radiological assessments

International Nuclear Information System (INIS)

Miller, C.W.

1984-01-01

This book presents a unified compilation of models and parameters appropriate for assessing the impact of radioactive discharges to the environment. Models examined include those developed for the prediction of atmospheric and hydrologic transport and deposition, for terrestrial and aquatic food-chain bioaccumulation, and for internal and external dosimetry. Chapters have been entered separately into the data base
Uncertainty in dual permeability model parameters for structured soils

Science.gov (United States)

Arora, B.; Mohanty, B. P.; McGuire, J. T.

2012-01-01

Successful application of dual permeability models (DPM) to predict contaminant transport is contingent upon measured or inversely estimated soil hydraulic and solute transport parameters. The difficulty in unique identification of parameters for the additional macropore- and matrix-macropore interface regions, and knowledge about requisite experimental data for DPM has not been resolved to date. Therefore, this study quantifies uncertainty in dual permeability model parameters of experimental soil columns with different macropore distributions (single macropore, and low- and high-density multiple macropores). Uncertainty evaluation is conducted using adaptive Markov chain Monte Carlo (AMCMC) and conventional Metropolis-Hastings (MH) algorithms while assuming 10 out of 17 parameters to be uncertain or random. Results indicate that AMCMC resolves parameter correlations and exhibits fast convergence for all DPM parameters while MH displays large posterior correlations for various parameters. This study demonstrates that the choice of parameter sampling algorithms is paramount in obtaining unique DPM parameters when information on covariance structure is lacking, or else additional information on parameter correlations must be supplied to resolve the problem of equifinality of DPM parameters. This study also highlights the placement and significance of matrix-macropore interface in flow experiments of soil columns with different macropore densities. Histograms for certain soil hydraulic parameters display tri-modal characteristics implying that macropores are drained first followed by the interface region and then by pores of the matrix domain in drainage experiments. Results indicate that hydraulic properties and behavior of the matrix-macropore interface is not only a function of saturated hydraulic conductivity of the macroporematrix interface (Ksa) and macropore tortuosity (lf) but also of other parameters of the matrix and macropore domains.
Optimization of Terrestrial Ecosystem Model Parameters Using Atmospheric CO2 Concentration Data With the Global Carbon Assimilation System (GCAS)

Science.gov (United States)

Chen, Zhuoqi; Chen, Jing M.; Zhang, Shupeng; Zheng, Xiaogu; Ju, Weiming; Mo, Gang; Lu, Xiaoliang

2017-12-01

The Global Carbon Assimilation System that assimilates ground-based atmospheric CO2 data is used to estimate several key parameters in a terrestrial ecosystem model for the purpose of improving carbon cycle simulation. The optimized parameters are the leaf maximum carboxylation rate at 25°C (Vmax25), the temperature sensitivity of ecosystem respiration (Q10), and the soil carbon pool size. The optimization is performed at the global scale at 1° resolution for the period from 2002 to 2008. The results indicate that vegetation from tropical zones has lower Vmax25 values than vegetation in temperate regions. Relatively high values of Q10 are derived over high/midlatitude regions. Both Vmax25 and Q10 exhibit pronounced seasonal variations at middle-high latitudes. The maxima in Vmax25 occur during growing seasons, while the minima appear during nongrowing seasons. Q10 values decrease with increasing temperature. The seasonal variabilities of Vmax25 and Q10 are larger at higher latitudes. Optimized Vmax25 and Q10 show little seasonal variabilities at tropical regions. The seasonal variabilities of Vmax25 are consistent with the variabilities of LAI for evergreen conifers and broadleaf evergreen forests. Variations in leaf nitrogen and leaf chlorophyll contents may partly explain the variations in Vmax25. The spatial distribution of the total soil carbon pool size after optimization is compared favorably with the gridded Global Soil Data Set for Earth System. The results also suggest that atmospheric CO2 data are a source of information that can be tapped to gain spatially and temporally meaningful information for key ecosystem parameters that are representative at the regional and global scales.
Simultaneous Parameters Identifiability and Estimation of an E. coli Metabolic Network Model

Directory of Open Access Journals (Sweden)

Kese Pontes Freitas Alberton

2015-01-01

Full Text Available This work proposes a procedure for simultaneous parameters identifiability and estimation in metabolic networks in order to overcome difficulties associated with lack of experimental data and large number of parameters, a common scenario in the modeling of such systems. As case study, the complex real problem of parameters identifiability of the Escherichia coli K-12 W3110 dynamic model was investigated, composed by 18 differential ordinary equations and 35 kinetic rates, containing 125 parameters. With the procedure, model fit was improved for most of the measured metabolites, achieving 58 parameters estimated, including 5 unknown initial conditions. The results indicate that simultaneous parameters identifiability and estimation approach in metabolic networks is appealing, since model fit to the most of measured metabolites was possible even when important measures of intracellular metabolites and good initial estimates of parameters are not available.
Periodic Anderson model with correlated conduction electrons: Variational and exact diagonalization study

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Hagymási, I.; Itai, K.; Sólyom, J.

2012-06-01

We investigate an extended version of the periodic Anderson model (the so-called periodic Anderson-Hubbard model) with the aim to understand the role of interaction between conduction electrons in the formation of the heavy-fermion and mixed-valence states. Two methods are used: (i) variational calculation with the Gutzwiller wave function optimizing numerically the ground-state energy and (ii) exact diagonalization of the Hamiltonian for short chains. The f-level occupancy and the renormalization factor of the quasiparticles are calculated as a function of the energy of the f orbital for a wide range of the interaction parameters. The results obtained by the two methods are in reasonably good agreement for the periodic Anderson model. The agreement is maintained even when the interaction between band electrons, Ud, is taken into account, except for the half-filled case. This discrepancy can be explained by the difference between the physics of the one- and higher-dimensional models. We find that this interaction shifts and widens the energy range of the bare f level, where heavy-fermion behavior can be observed. For large-enough Ud this range may lie even above the bare conduction band. The Gutzwiller method indicates a robust transition from Kondo insulator to Mott insulator in the half-filled model, while Ud enhances the quasiparticle mass when the filling is close to half filling.
Distribution-centric 3-parameter thermodynamic models of partition gas chromatography.

Science.gov (United States)

Blumberg, Leonid M

2017-03-31

If both parameters (the entropy, ΔS, and the enthalpy, ΔH) of the classic van't Hoff model of dependence of distribution coefficients (K) of analytes on temperature (T) are treated as the temperature-independent constants then the accuracy of the model is known to be insufficient for the needed accuracy of retention time prediction. A more accurate 3-parameter Clarke-Glew model offers a way to treat ΔS and ΔH as functions, ΔS(T) and ΔH(T), of T. A known T-centric construction of these functions is based on relating them to the reference values (ΔS ref and ΔH ref ) corresponding to a predetermined reference temperature (T ref ). Choosing a single T ref for all analytes in a complex sample or in a large database might lead to practically irrelevant values of ΔS ref and ΔH ref for those analytes that have too small or too large retention factors at T ref . Breaking all analytes in several subsets each with its own T ref leads to discontinuities in the analyte parameters. These problems are avoided in the K-centric modeling where ΔS(T) and ΔS(T) and other analyte parameters are described in relation to their values corresponding to a predetermined reference distribution coefficient (K Ref ) - the same for all analytes. In this report, the mathematics of the K-centric modeling are described and the properties of several types of K-centric parameters are discussed. It has been shown that the earlier introduced characteristic parameters of the analyte-column interaction (the characteristic temperature, T char , and the characteristic thermal constant, θ char ) are a special chromatographically convenient case of the K-centric parameters. Transformations of T-centric parameters into K-centric ones and vice-versa as well as the transformations of one set of K-centric parameters into another set and vice-versa are described. Copyright © 2017 Elsevier B.V. All rights reserved.
Patient-specific parameter estimation in single-ventricle lumped circulation models under uncertainty

Science.gov (United States)

Schiavazzi, Daniele E.; Baretta, Alessia; Pennati, Giancarlo; Hsia, Tain-Yen; Marsden, Alison L.

2017-01-01

Summary Computational models of cardiovascular physiology can inform clinical decision-making, providing a physically consistent framework to assess vascular pressures and flow distributions, and aiding in treatment planning. In particular, lumped parameter network (LPN) models that make an analogy to electrical circuits offer a fast and surprisingly realistic method to reproduce the circulatory physiology. The complexity of LPN models can vary significantly to account, for example, for cardiac and valve function, respiration, autoregulation, and time-dependent hemodynamics. More complex models provide insight into detailed physiological mechanisms, but their utility is maximized if one can quickly identify patient specific parameters. The clinical utility of LPN models with many parameters will be greatly enhanced by automated parameter identification, particularly if parameter tuning can match non-invasively obtained clinical data. We present a framework for automated tuning of 0D lumped model parameters to match clinical data. We demonstrate the utility of this framework through application to single ventricle pediatric patients with Norwood physiology. Through a combination of local identifiability, Bayesian estimation and maximum a posteriori simplex optimization, we show the ability to automatically determine physiologically consistent point estimates of the parameters and to quantify uncertainty induced by errors and assumptions in the collected clinical data. We show that multi-level estimation, that is, updating the parameter prior information through sub-model analysis, can lead to a significant reduction in the parameter marginal posterior variance. We first consider virtual patient conditions, with clinical targets generated through model solutions, and second application to a cohort of four single-ventricle patients with Norwood physiology. PMID:27155892
Adaptive Parameter Estimation of Person Recognition Model in a Stochastic Human Tracking Process

Science.gov (United States)

Nakanishi, W.; Fuse, T.; Ishikawa, T.

2015-05-01

This paper aims at an estimation of parameters of person recognition models using a sequential Bayesian filtering method. In many human tracking method, any parameters of models used for recognize the same person in successive frames are usually set in advance of human tracking process. In real situation these parameters may change according to situation of observation and difficulty level of human position prediction. Thus in this paper we formulate an adaptive parameter estimation using general state space model. Firstly we explain the way to formulate human tracking in general state space model with their components. Then referring to previous researches, we use Bhattacharyya coefficient to formulate observation model of general state space model, which is corresponding to person recognition model. The observation model in this paper is a function of Bhattacharyya coefficient with one unknown parameter. At last we sequentially estimate this parameter in real dataset with some settings. Results showed that sequential parameter estimation was succeeded and were consistent with observation situations such as occlusions.
Constraining statistical-model parameters using fusion and spallation reactions

Directory of Open Access Journals (Sweden)

Charity Robert J.

2011-10-01

Full Text Available The de-excitation of compound nuclei has been successfully described for several decades by means of statistical models. However, such models involve a large number of free parameters and ingredients that are often underconstrained by experimental data. We show how the degeneracy of the model ingredients can be partially lifted by studying different entrance channels for de-excitation, which populate different regions of the parameter space of the compound nucleus. Fusion reactions, in particular, play an important role in this strategy because they ﬁx three out of four of the compound-nucleus parameters (mass, charge and total excitation energy. The present work focuses on ﬁssion and intermediate-mass-fragment emission cross sections. We prove how equivalent parameter sets for fusion-ﬁssion reactions can be resolved using another entrance channel, namely spallation reactions. Intermediate-mass-fragment emission can be constrained in a similar way. An interpretation of the best-ﬁt IMF barriers in terms of the Wigner energies of the nascent fragments is discussed.
Modeling visual search using three-parameter probability functions in a hierarchical Bayesian framework.

Science.gov (United States)

Lin, Yi-Shin; Heinke, Dietmar; Humphreys, Glyn W

2015-04-01

In this study, we applied Bayesian-based distributional analyses to examine the shapes of response time (RT) distributions in three visual search paradigms, which varied in task difficulty. In further analyses we investigated two common observations in visual search-the effects of display size and of variations in search efficiency across different task conditions-following a design that had been used in previous studies (Palmer, Horowitz, Torralba, & Wolfe, Journal of Experimental Psychology: Human Perception and Performance, 37, 58-71, 2011; Wolfe, Palmer, & Horowitz, Vision Research, 50, 1304-1311, 2010) in which parameters of the response distributions were measured. Our study showed that the distributional parameters in an experimental condition can be reliably estimated by moderate sample sizes when Monte Carlo simulation techniques are applied. More importantly, by analyzing trial RTs, we were able to extract paradigm-dependent shape changes in the RT distributions that could be accounted for by using the EZ2 diffusion model. The study showed that Bayesian-based RT distribution analyses can provide an important means to investigate the underlying cognitive processes in search, including stimulus grouping and the bottom-up guidance of attention.
Model parameter learning using Kullback-Leibler divergence

Science.gov (United States)

Lin, Chungwei; Marks, Tim K.; Pajovic, Milutin; Watanabe, Shinji; Tung, Chih-kuan

2018-02-01

In this paper, we address the following problem: For a given set of spin configurations whose probability distribution is of the Boltzmann type, how do we determine the model coupling parameters? We demonstrate that directly minimizing the Kullback-Leibler divergence is an efficient method. We test this method against the Ising and XY models on the one-dimensional (1D) and two-dimensional (2D) lattices, and provide two estimators to quantify the model quality. We apply this method to two types of problems. First, we apply it to the real-space renormalization group (RG). We find that the obtained RG flow is sufficiently good for determining the phase boundary (within 1% of the exact result) and the critical point, but not accurate enough for critical exponents. The proposed method provides a simple way to numerically estimate amplitudes of the interactions typically truncated in the real-space RG procedure. Second, we apply this method to the dynamical system composed of self-propelled particles, where we extract the parameter of a statistical model (a generalized XY model) from a dynamical system described by the Viscek model. We are able to obtain reasonable coupling values corresponding to different noise strengths of the Viscek model. Our method is thus able to provide quantitative analysis of dynamical systems composed of self-propelled particles.
Good Models Gone Bad: Quantifying and Predicting Parameter-Induced Climate Model Simulation Failures

Science.gov (United States)

Lucas, D. D.; Klein, R.; Tannahill, J.; Brandon, S.; Covey, C. C.; Domyancic, D.; Ivanova, D. P.

2012-12-01

Simulations using IPCC-class climate models are subject to fail or crash for a variety of reasons. Statistical analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation failures of the Parallel Ocean Program (POP2). About 8.5% of our POP2 runs failed for numerical reasons at certain combinations of parameter values. We apply support vector machine (SVM) classification from the fields of pattern recognition and machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. The SVM classifiers readily predict POP2 failures in an independent validation ensemble, and are subsequently used to determine the causes of the failures via a global sensitivity analysis. Four parameters related to ocean mixing and viscosity are identified as the major sources of POP2 failures. Our method can be used to improve the robustness of complex scientific models to parameter perturbations and to better steer UQ ensembles. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and was funded by the Uncertainty Quantification Strategic Initiative Laboratory Directed Research and Development Project at LLNL under project tracking code 10-SI-013 (UCRL LLNL-ABS-569112).
Iterative integral parameter identification of a respiratory mechanics model.

Science.gov (United States)

Schranz, Christoph; Docherty, Paul D; Chiew, Yeong Shiong; Möller, Knut; Chase, J Geoffrey

2012-07-18

Patient-specific respiratory mechanics models can support the evaluation of optimal lung protective ventilator settings during ventilation therapy. Clinical application requires that the individual's model parameter values must be identified with information available at the bedside. Multiple linear regression or gradient-based parameter identification methods are highly sensitive to noise and initial parameter estimates. Thus, they are difficult to apply at the bedside to support therapeutic decisions. An iterative integral parameter identification method is applied to a second order respiratory mechanics model. The method is compared to the commonly used regression methods and error-mapping approaches using simulated and clinical data. The clinical potential of the method was evaluated on data from 13 Acute Respiratory Distress Syndrome (ARDS) patients. The iterative integral method converged to error minima 350 times faster than the Simplex Search Method using simulation data sets and 50 times faster using clinical data sets. Established regression methods reported erroneous results due to sensitivity to noise. In contrast, the iterative integral method was effective independent of initial parameter estimations, and converged successfully in each case tested. These investigations reveal that the iterative integral method is beneficial with respect to computing time, operator independence and robustness, and thus applicable at the bedside for this clinical application.
[Parameter optimization of BEPS model based on the flux data of the temperate deciduous broad-leaved forest in Northeast China.

Science.gov (United States)

Lu, Wei; Fan, Wen Yi; Tian, Tian

2016-05-01

Keeping other parameters as empirical constants, different numerical combinations of the main photosynthetic parameters V c max and J max were conducted to estimate daily GPP by using the iteration method in this paper. To optimize V c max and J max in BEPSHourly model at hourly time steps, simulated daily GPP using different numerical combinations of the parameters were compared with the flux tower data obtained from the temperate deciduous broad-leaved forest of the Maoershan Forest Farm in Northeast China. Comparing the simulated daily GPP with the observed flux data in 2011, the results showed that optimal V c max and J max for the deciduous broad-leaved forest in Northeast China were 41.1 μmol·m -2 ·s -1 and 82.8 μmol·m -2 ·s -1 respectively with the minimal RMSE and the maximum R 2 of 1.10 g C·m -2 ·d -1 and 0.95. After V c max and J max optimization, BEPSHourly model simulated the seasonal variation of GPP better.
GPI-repetitive control for linear systems with parameter uncertainty / variation

Directory of Open Access Journals (Sweden)

John A. Cortés-Romero

2015-01-01

Full Text Available Robust repetitive control problems for uncertain linear systems have been considered by different approaches. This article proposes the use of Repetitive Control and Generalized Proportional Integral (GPI Control in a complementary fashion. The conditioning and coupling of these techniques has been done in a time discrete context. Repetitive control is a control technique, based on the internal model principle, which yields perfect asymptotic tracking and rejection of periodic signals. On the other hand, GPI control is established as a robust linear control system design technique that is able to reject structured time polynomial additive perturbation, in particular, parameter uncertainty that can be locally approximated by time polynomial signal. GPI control provides a suitable stability and robustness conditions for the proper Repetitive Control operation. A stability analysis is presented under the frequency response framework using plant samples for different parameter uncertainty conditions. We carry out some comparative stability analysis with other complementary control approaches that has been effective for this kind of task, enhancing a better robustness and an improved performance for the GPI case. Illustrative simulation examples are presented which validate the proposed approach.
Failure analysis of parameter-induced simulation crashes in climate models

Science.gov (United States)

Lucas, D. D.; Klein, R.; Tannahill, J.; Ivanova, D.; Brandon, S.; Domyancic, D.; Zhang, Y.

2013-08-01

Simulations using IPCC (Intergovernmental Panel on Climate Change)-class climate models are subject to fail or crash for a variety of reasons. Quantitative analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation crashes within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). About 8.5% of our CCSM4 simulations failed for numerical reasons at combinations of POP2 parameter values. We applied support vector machine (SVM) classification from machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. A committee of SVM classifiers readily predicted model failures in an independent validation ensemble, as assessed by the area under the receiver operating characteristic (ROC) curve metric (AUC > 0.96). The causes of the simulation failures were determined through a global sensitivity analysis. Combinations of 8 parameters related to ocean mixing and viscosity from three different POP2 parameterizations were the major sources of the failures. This information can be used to improve POP2 and CCSM4 by incorporating correlations across the relevant parameters. Our method can also be used to quantify, predict, and understand simulation crashes in other complex geoscientific models.
Validity of covariance models for the analysis of geographical variation

DEFF Research Database (Denmark)

Guillot, Gilles; Schilling, Rene L.; Porcu, Emilio

2014-01-01

1. Due to the availability of large molecular data-sets, covariance models are increasingly used to describe the structure of genetic variation as an alternative to more heavily parametrised biological models. 2. We focus here on a class of parametric covariance models that received sustained att...
A stochastic optimization model under modeling uncertainty and parameter certainty for groundwater remediation design-Part I. Model development

Energy Technology Data Exchange (ETDEWEB)

He, L., E-mail: li.he@ryerson.ca [Department of Civil Engineering, Faculty of Engineering, Architecture and Science, Ryerson University, 350 Victoria Street, Toronto, Ontario, M5B 2K3 (Canada); Huang, G.H. [Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, Saskatchewan, S4S 0A2 (Canada); College of Urban Environmental Sciences, Peking University, Beijing 100871 (China); Lu, H.W. [Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, Saskatchewan, S4S 0A2 (Canada)

2010-04-15

Solving groundwater remediation optimization problems based on proxy simulators can usually yield optimal solutions differing from the 'true' ones of the problem. This study presents a new stochastic optimization model under modeling uncertainty and parameter certainty (SOMUM) and the associated solution method for simultaneously addressing modeling uncertainty associated with simulator residuals and optimizing groundwater remediation processes. This is a new attempt different from the previous modeling efforts. The previous ones focused on addressing uncertainty in physical parameters (i.e. soil porosity) while this one aims to deal with uncertainty in mathematical simulator (arising from model residuals). Compared to the existing modeling approaches (i.e. only parameter uncertainty is considered), the model has the advantages of providing mean-variance analysis for contaminant concentrations, mitigating the effects of modeling uncertainties on optimal remediation strategies, offering confidence level of optimal remediation strategies to system designers, and reducing computational cost in optimization processes.

The Impact on Individualizing Student Models on Necessary Practice Opportunities

Science.gov (United States)

Lee, Jung In; Brunskill, Emma

2012-01-01

When modeling student learning, tutors that use the Knowledge Tracing framework often assume that all students have the same set of model parameters. We find that when fitting parameters to individual students, there is significant variation among the individual's parameters. We examine if this variation is important in terms of instructional…
Variational Boussinesq model for strongly nonlinear dispersive waves

NARCIS (Netherlands)

Lawrence, C.; Adytia, D.; van Groesen, E.

2018-01-01

For wave tank, coastal and oceanic applications, a fully nonlinear Variational Boussinesq model with optimized dispersion is derived and a simple Finite Element implementation is described. Improving a previous weakly nonlinear version, high waves over flat and varying bottom are shown to be
Time series analyses of hydrological parameter variations and their correlations at a coastal area in Busan, South Korea

Science.gov (United States)

Chung, Sang Yong; Senapathi, Venkatramanan; Sekar, Selvam; Kim, Tae Hyung

2018-02-01

Monitoring and time-series analysis of the hydrological parameters electrical conductivity (EC), water pressure, precipitation and tide were carried out, to understand the characteristics of the parameter variations and their correlations at a coastal area in Busan, South Korea. The monitoring data were collected at a sharp interface between freshwater and saline water at the depth of 25 m below ground. Two well-logging profiles showed that seawater intrusion has largely expanded (progressed inland), and has greatly affected the groundwater quality in a coastal aquifer of tuffaceous sedimentary rock over a 9-year period. According to the time series analyses, the periodograms of the hydrological parameters present very similar trends to the power spectral densities (PSD) of the hydrological parameters. Autocorrelation functions (ACF) and partial autocorrelation functions (PACF) of the hydrological parameters were produced to evaluate their self-correlations. The ACFs of all hydrologic parameters showed very good correlation over the entire time lag, but the PACF revealed that the correlations were good only at time lag 1. Crosscorrelation functions (CCF) were used to evaluate the correlations between the hydrological parameters and the characteristics of seawater intrusion in the coastal aquifer system. The CCFs showed that EC had a close relationship with water pressure and precipitation rather than tide. The CCFs of water pressure with tide and precipitation were in inverse proportion, and the CCF of water pressure with precipitation was larger than that with tide.
Parameter resolution in two models for cell survival after radiation

International Nuclear Information System (INIS)

Di Cera, E.; Andreasi Bassi, F.; Arcovito, G.

1989-01-01

The resolvability of model parameters for the linear-quadratic and the repair-misrepair models for cell survival after radiation has been studied by Monte Carlo simulations as a function of the number of experimental data points collected in a given dose range and the experimental error. Statistical analysis of the results reveals the range of experimental conditions under which the model parameters can be resolved with sufficient accuracy, and points out some differences in the operational aspects of the two models. (orig.)
Modelling spatial and temporal variations of annual suspended sediment yields from small agricultural catchments.

Science.gov (United States)

Rymszewicz, A; Bruen, M; O'Sullivan, J J; Turner, J N; Lawler, D M; Harrington, J R; Conroy, E; Kelly-Quinn, M

2018-04-01

Estimates of sediment yield are important for ecological and geomorphological assessment of fluvial systems and for assessment of soil erosion within a catchment. Many regulatory frameworks, such as the Convention for the Protection of the Marine Environment of the North-East Atlantic, derived from the Oslo and Paris Commissions (OSPAR) require reporting of annual sediment fluxes. While they may be measured in large rivers, sediment flux is rarely measured in smaller rivers. Measurements of sediment transport at a national scale can be also challenging and therefore, sediment yield models are often utilised by water resource managers for the predictions of sediment yields in the ungauged catchments. Regression based models, calibrated to field measurements, can offer an advantage over complex and computational models due to their simplicity, easy access to input data and due to the additional insights into factors controlling sediment export in the study sites. While traditionally calibrated to long-term average values of sediment yields such predictions cannot represent temporal variations. This study addresses this issue in a novel way by taking account of the variation from year to year in hydrological variables in the developed models (using annual mean runoff, annual mean flow, flows exceeded in five percentage of the time (Q5) and seasonal rainfall estimated separately for each year of observations). Other parameters included in the models represent spatial differences influenced by factors such as soil properties (% poorly drained soils and % peaty soils), land-use (% pasture or % arable lands), channel slope (S1085) and drainage network properties (drainage density). Catchment descriptors together with year-specific hydrological variables can explain both spatial differences and inter-annual variability of suspended sediment yields. The methodology is demonstrated by deriving equations from Irish data-sets (compiled in this study) with the best model
PARAMETER ESTIMATION AND MODEL SELECTION FOR INDOOR ENVIRONMENTS BASED ON SPARSE OBSERVATIONS

Directory of Open Access Journals (Sweden)

Y. Dehbi

2017-09-01

Full Text Available This paper presents a novel method for the parameter estimation and model selection for the reconstruction of indoor environments based on sparse observations. While most approaches for the reconstruction of indoor models rely on dense observations, we predict scenes of the interior with high accuracy in the absence of indoor measurements. We use a model-based top-down approach and incorporate strong but profound prior knowledge. The latter includes probability density functions for model parameters and sparse observations such as room areas and the building footprint. The floorplan model is characterized by linear and bi-linear relations with discrete and continuous parameters. We focus on the stochastic estimation of model parameters based on a topological model derived by combinatorial reasoning in a first step. A Gauss-Markov model is applied for estimation and simulation of the model parameters. Symmetries are represented and exploited during the estimation process. Background knowledge as well as observations are incorporated in a maximum likelihood estimation and model selection is performed with AIC/BIC. The likelihood is also used for the detection and correction of potential errors in the topological model. Estimation results are presented and discussed.
Parameter Estimation and Model Selection for Indoor Environments Based on Sparse Observations

Science.gov (United States)

Dehbi, Y.; Loch-Dehbi, S.; Plümer, L.

2017-09-01

This paper presents a novel method for the parameter estimation and model selection for the reconstruction of indoor environments based on sparse observations. While most approaches for the reconstruction of indoor models rely on dense observations, we predict scenes of the interior with high accuracy in the absence of indoor measurements. We use a model-based top-down approach and incorporate strong but profound prior knowledge. The latter includes probability density functions for model parameters and sparse observations such as room areas and the building footprint. The floorplan model is characterized by linear and bi-linear relations with discrete and continuous parameters. We focus on the stochastic estimation of model parameters based on a topological model derived by combinatorial reasoning in a first step. A Gauss-Markov model is applied for estimation and simulation of the model parameters. Symmetries are represented and exploited during the estimation process. Background knowledge as well as observations are incorporated in a maximum likelihood estimation and model selection is performed with AIC/BIC. The likelihood is also used for the detection and correction of potential errors in the topological model. Estimation results are presented and discussed.
Influence of lung parameter values for the Brazilian population on inhalation dose

International Nuclear Information System (INIS)

Reis, Arlene A.; Lopes, Ricardo T.

2009-01-01

The Human Respiratory Tract Model (HRTM) proposed by the ICRP Publication 66 accounts for the morphology and physiology of the respiratory tract. The ICRP 66 presents deposition fraction in the respiratory tract regions considering reference values from Caucasian man. However, in order to obtain a more accurate assessment of intake and dose the ICRP recommends the use of specific information when they are available. The main objective of this study is to evaluate the influence in dose calculation to each region of the respiratory tract when physiological parameters from samples of Brazilian population, in different levels of exercise, are applied in the deposition model.The dosimetric model of HRTM was implemented in the software EXCEL for Windows and committed equivalent dose was determined for each respiratory tract region. First it was calculated the total number of nuclear transformations considering the fractional deposition of activity in each source tissue obtained by application of physiological and morphological Brazilian parameters in the deposition model and then it was calculated the total energy absorbed per unit mass in the target tissue.The variation in the fractional deposition in the compartments of the respiratory tract in changing the physiological parameters from Caucasian to Brazilian adult man causes variation in the number of total transformations and also in the equivalent dose in each region of the respiratory tract. The variations are not the same for all regions of the respiratory tract and depend on levels of exercise. (author)
Assessing of channel roughness and temperature variations on ...

African Journals Online (AJOL)

Assessing of channel roughness and temperature variations on wastewater quality parameters using numerical modeling. ... According to the obtained results, nitrate (NO3) has a decreasing trend when the Manning Roughness Coefficient (N) is higher than 0.04 along the channel, but is reduced when “N” is less than 0.04.
Dynamics of a neuron model in different two-dimensional parameter-spaces

International Nuclear Information System (INIS)

Rech, Paulo C.

2011-01-01

We report some two-dimensional parameter-space diagrams numerically obtained for the multi-parameter Hindmarsh-Rose neuron model. Several different parameter planes are considered, and we show that regardless of the combination of parameters, a typical scenario is preserved: for all choice of two parameters, the parameter-space presents a comb-shaped chaotic region immersed in a large periodic region. We also show that exist regions close these chaotic region, separated by the comb teeth, organized themselves in period-adding bifurcation cascades. - Research highlights: → We report parameter-spaces obtained for the Hindmarsh-Rose neuron model. → Regardless of the combination of parameters, a typical scenario is preserved. → The scenario presents a comb-shaped chaotic region immersed in a periodic region. → Periodic regions near the chaotic region are in period-adding bifurcation cascades.
Topography induced spatial variations in diurnal cycles of assimilation and latent heat of Mediterranean forest

Science.gov (United States)

van der Tol, C.; Dolman, A. J.; Waterloo, M. J.; Raspor, K.

2007-02-01

The aim of this study is to explain topography induced spatial variations in the diurnal cycles of assimilation and latent heat of Mediterranean forest. Spatial variations of the fluxes are caused by variations in weather conditions and in vegetation characteristics. Weather conditions reflect short-term effects of climate, whereas vegetation characteristics, through adaptation and acclimation, long-term effects of climate. In this study measurements of plant physiology and weather conditions are used to explain observed differences in the fluxes. A model is used to study which part of the differences in the fluxes is caused by weather conditions and which part by vegetation characteristics. Data were collected at four experimental sub-Mediterranean deciduous forest plots in a heterogeneous terrain with contrasting aspect, soil water availability, humidity and temperature. We used a sun-shade model to scale fluxes from leaf to canopy, and calculated the canopy energy balance. Parameter values were derived from measurements of light interception, leaf chamber photosynthesis, leaf nitrogen content and 13C isotope discrimination in leaf material. Leaf nitrogen content is a measure of photosynthetic capacity, and 13C isotope discrimination of water use efficiency. For validation, sap-flux based measurements of transpiration were used. The model predicted diurnal cycles of transpiration and stomatal conductance, both their magnitudes and differences in afternoon stomatal closure between slopes of different aspect within the confidence interval of the validation data. Weather conditions mainly responsible for the shape of the diurnal cycles, and vegetation parameters for the magnitude of the fluxes. Although the data do not allow for a quantification of the two effects, the differences in vegetation parameters and weather among the plots and the sensitivity of the fluxes to them suggest that the diurnal cycles were more strongly affected by spatial variations in
Topography induced spatial variations in diurnal cycles of assimilation and latent heat of Mediterranean forest

Directory of Open Access Journals (Sweden)

C. van der Tol

2007-01-01

Full Text Available The aim of this study is to explain topography induced spatial variations in the diurnal cycles of assimilation and latent heat of Mediterranean forest. Spatial variations of the fluxes are caused by variations in weather conditions and in vegetation characteristics. Weather conditions reflect short-term effects of climate, whereas vegetation characteristics, through adaptation and acclimation, long-term effects of climate. In this study measurements of plant physiology and weather conditions are used to explain observed differences in the fluxes. A model is used to study which part of the differences in the fluxes is caused by weather conditions and which part by vegetation characteristics. Data were collected at four experimental sub-Mediterranean deciduous forest plots in a heterogeneous terrain with contrasting aspect, soil water availability, humidity and temperature. We used a sun-shade model to scale fluxes from leaf to canopy, and calculated the canopy energy balance. Parameter values were derived from measurements of light interception, leaf chamber photosynthesis, leaf nitrogen content and 13C isotope discrimination in leaf material. Leaf nitrogen content is a measure of photosynthetic capacity, and 13C isotope discrimination of water use efficiency. For validation, sap-flux based measurements of transpiration were used. The model predicted diurnal cycles of transpiration and stomatal conductance, both their magnitudes and differences in afternoon stomatal closure between slopes of different aspect within the confidence interval of the validation data. Weather conditions mainly responsible for the shape of the diurnal cycles, and vegetation parameters for the magnitude of the fluxes. Although the data do not allow for a quantification of the two effects, the differences in vegetation parameters and weather among the plots and the sensitivity of the fluxes to them suggest that the diurnal cycles were more strongly affected by spatial
The sensitivity of flowline models of tidewater glaciers to parameter uncertainty

Directory of Open Access Journals (Sweden)

E. M. Enderlin

2013-10-01

Full Text Available Depth-integrated (1-D flowline models have been widely used to simulate fast-flowing tidewater glaciers and predict change because the continuous grounding line tracking, high horizontal resolution, and physically based calving criterion that are essential to realistic modeling of tidewater glaciers can easily be incorporated into the models while maintaining high computational efficiency. As with all models, the values for parameters describing ice rheology and basal friction must be assumed and/or tuned based on observations. For prognostic studies, these parameters are typically tuned so that the glacier matches observed thickness and speeds at an initial state, to which a perturbation is applied. While it is well know that ice flow models are sensitive to these parameters, the sensitivity of tidewater glacier models has not been systematically investigated. Here we investigate the sensitivity of such flowline models of outlet glacier dynamics to uncertainty in three key parameters that influence a glacier's resistive stress components. We find that, within typical observational uncertainty, similar initial (i.e., steady-state glacier configurations can be produced with substantially different combinations of parameter values, leading to differing transient responses after a perturbation is applied. In cases where the glacier is initially grounded near flotation across a basal over-deepening, as typically observed for rapidly changing glaciers, these differences can be dramatic owing to the threshold of stability imposed by the flotation criterion. The simulated transient response is particularly sensitive to the parameterization of ice rheology: differences in ice temperature of ~ 2 °C can determine whether the glaciers thin to flotation and retreat unstably or remain grounded on a marine shoal. Due to the highly non-linear dependence of tidewater glaciers on model parameters, we recommend that their predictions are accompanied by
A test for the parameters of multiple linear regression models ...

African Journals Online (AJOL)

A test for the parameters of multiple linear regression models is developed for conducting tests simultaneously on all the parameters of multiple linear regression models. The test is robust relative to the assumptions of homogeneity of variances and absence of serial correlation of the classical F-test. Under certain null and ...
Determination of the Corona model parameters with artificial neural networks

International Nuclear Information System (INIS)

Ahmet, Nayir; Bekir, Karlik; Arif, Hashimov

2005-01-01

Full text : The aim of this study is to calculate new model parameters taking into account the corona of electrical transmission line wires. For this purpose, a neural network modeling proposed for the corona frequent characteristics modeling. Then this model was compared with the other model developed at the Polytechnic Institute of Saint Petersburg. The results of development of the specified corona model for calculation of its influence on the wave processes in multi-wires line and determination of its parameters are submitted. Results of obtained calculation equations are brought for electrical transmission line with allowance for superficial effect in the ground and wires with reference to developed corona model
Influence of simulation assumptions and input parameters on energy balance calculations of residential buildings

International Nuclear Information System (INIS)

Dodoo, Ambrose; Tettey, Uniben Yao Ayikoe; Gustavsson, Leif

2017-01-01

In this study, we modelled the influence of different simulation assumptions on energy balances of two variants of a residential building, comprising the building in its existing state and with energy-efficient improvements. We explored how selected parameter combinations and variations affect the energy balances of the building configurations. The selected parameters encompass outdoor microclimate, building thermal envelope and household electrical equipment including technical installations. Our modelling takes into account hourly as well as seasonal profiles of different internal heat gains. The results suggest that the impact of parameter interactions on calculated space heating of buildings is somewhat small and relatively more noticeable for an energy-efficient building in contrast to a conventional building. We find that the influence of parameters combinations is more apparent as more individual parameters are varied. The simulations show that a building's calculated space heating demand is significantly influenced by how heat gains from electrical equipment are modelled. For the analyzed building versions, calculated final energy for space heating differs by 9–14 kWh/m"2 depending on the assumed energy efficiency level for electrical equipment. The influence of electrical equipment on calculated final space heating is proportionally more significant for an energy-efficient building compared to a conventional building. This study shows the influence of different simulation assumptions and parameter combinations when varied simultaneously. - Highlights: • Energy balances are modelled for conventional and efficient variants of a building. • Influence of assumptions and parameter combinations and variations are explored. • Parameter interactions influence is apparent as more single parameters are varied. • Calculated space heating demand is notably affected by how heat gains are modelled.
On the relationship between input parameters in the two-mass vocal-fold model with acoustical coupling and signal parameters of the glottal flow

NARCIS (Netherlands)

Hirtum, van A.; Lopez Arteaga, I.; Hirschberg, A.; Pelorson, X.

2003-01-01

In this paper the sensitivity of the two-mass model with acoustical coupling to the model input-parameters is assessed. The model-output or the glottal volume air flow is characterised by signal-parameters in the time-domain. The influence of changing input-parameters on the signal-parameters is
A termination criterion for parameter estimation in stochastic models in systems biology.

Science.gov (United States)

Zimmer, Christoph; Sahle, Sven

2015-11-01

Parameter estimation procedures are a central aspect of modeling approaches in systems biology. They are often computationally expensive, especially when the models take stochasticity into account. Typically parameter estimation involves the iterative optimization of an objective function that describes how well the model fits some measured data with a certain set of parameter values. In order to limit the computational expenses it is therefore important to apply an adequate stopping criterion for the optimization process, so that the optimization continues at least until a reasonable fit is obtained, but not much longer. In the case of stochastic modeling, at least some parameter estimation schemes involve an objective function that is itself a random variable. This means that plain convergence tests are not a priori suitable as stopping criteria. This article suggests a termination criterion suited to optimization problems in parameter estimation arising from stochastic models in systems biology. The termination criterion is developed for optimization algorithms that involve populations of parameter sets, such as particle swarm or evolutionary algorithms. It is based on comparing the variance of the objective function over the whole population of parameter sets with the variance of repeated evaluations of the objective function at the best parameter set. The performance is demonstrated for several different algorithms. To test the termination criterion we choose polynomial test functions as well as systems biology models such as an Immigration-Death model and a bistable genetic toggle switch. The genetic toggle switch is an especially challenging test case as it shows a stochastic switching between two steady states which is qualitatively different from the model behavior in a deterministic model. Copyright © 2015. Published by Elsevier Ireland Ltd.
A stochastic optimization model under modeling uncertainty and parameter certainty for groundwater remediation design--part I. Model development.

Science.gov (United States)

He, L; Huang, G H; Lu, H W

2010-04-15

Solving groundwater remediation optimization problems based on proxy simulators can usually yield optimal solutions differing from the "true" ones of the problem. This study presents a new stochastic optimization model under modeling uncertainty and parameter certainty (SOMUM) and the associated solution method for simultaneously addressing modeling uncertainty associated with simulator residuals and optimizing groundwater remediation processes. This is a new attempt different from the previous modeling efforts. The previous ones focused on addressing uncertainty in physical parameters (i.e. soil porosity) while this one aims to deal with uncertainty in mathematical simulator (arising from model residuals). Compared to the existing modeling approaches (i.e. only parameter uncertainty is considered), the model has the advantages of providing mean-variance analysis for contaminant concentrations, mitigating the effects of modeling uncertainties on optimal remediation strategies, offering confidence level of optimal remediation strategies to system designers, and reducing computational cost in optimization processes. 2009 Elsevier B.V. All rights reserved.
Assessment of parameter regionalization methods for modeling flash floods in China

Science.gov (United States)

Ragettli, Silvan; Zhou, Jian; Wang, Haijing

2017-04-01

Rainstorm flash floods are a common and serious phenomenon during the summer months in many hilly and mountainous regions of China. For this study, we develop a modeling strategy for simulating flood events in small river basins of four Chinese provinces (Shanxi, Henan, Beijing, Fujian). The presented research is part of preliminary investigations for the development of a national operational model for predicting and forecasting hydrological extremes in basins of size 10 - 2000 km2, whereas most of these basins are ungauged or poorly gauged. The project is supported by the China Institute of Water Resources and Hydropower Research within the framework of the national initiative for flood prediction and early warning system for mountainous regions in China (research project SHZH-IWHR-73). We use the USGS Precipitation-Runoff Modeling System (PRMS) as implemented in the Java modeling framework Object Modeling System (OMS). PRMS can operate at both daily and storm timescales, switching between the two using a precipitation threshold. This functionality allows the model to perform continuous simulations over several years and to switch to the storm mode to simulate storm response in greater detail. The model was set up for fifteen watersheds for which hourly precipitation and runoff data were available. First, automatic calibration based on the Shuffled Complex Evolution method was applied to different hydrological response unit (HRU) configurations. The Nash-Sutcliffe efficiency (NSE) was used as assessment criteria, whereas only runoff data from storm events were considered. HRU configurations reflect the drainage-basin characteristics and depend on assumptions regarding drainage density and minimum HRU size. We then assessed the sensitivity of optimal parameters to different HRU configurations. Finally, the transferability to other watersheds of optimal model parameters that were not sensitive to HRU configurations was evaluated. Model calibration for the 15

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