Identification of hydrological model parameter variation using ensemble Kalman filter
Deng, Chao; Liu, Pan; Guo, Shenglian; Li, Zejun; Wang, Dingbao
2016-12-01
Hydrological model parameters play an important role in the ability of model prediction. In a stationary context, parameters of hydrological models are treated as constants; however, model parameters may vary with time under climate change and anthropogenic activities. The technique of ensemble Kalman filter (EnKF) is proposed to identify the temporal variation of parameters for a two-parameter monthly water balance model (TWBM) by assimilating the runoff observations. Through a synthetic experiment, the proposed method is evaluated with time-invariant (i.e., constant) parameters and different types of parameter variations, including trend, abrupt change and periodicity. Various levels of observation uncertainty are designed to examine the performance of the EnKF. The results show that the EnKF can successfully capture the temporal variations of the model parameters. The application to the Wudinghe basin shows that the water storage capacity (SC) of the TWBM model has an apparent increasing trend during the period from 1958 to 2000. The identified temporal variation of SC is explained by land use and land cover changes due to soil and water conservation measures. In contrast, the application to the Tongtianhe basin shows that the estimated SC has no significant variation during the simulation period of 1982-2013, corresponding to the relatively stationary catchment properties. The evapotranspiration parameter (C) has temporal variations while no obvious change patterns exist. The proposed method provides an effective tool for quantifying the temporal variations of the model parameters, thereby improving the accuracy and reliability of model simulations and forecasts.
NWP model forecast skill optimization via closure parameter variations
Järvinen, H.; Ollinaho, P.; Laine, M.; Solonen, A.; Haario, H.
2012-04-01
We present results of a novel approach to tune predictive skill of numerical weather prediction (NWP) models. These models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. The current practice is to specify manually the numerical parameter values, based on expert knowledge. We developed recently a concept and method (QJRMS 2011) for on-line estimation of the NWP model parameters via closure parameter variations. The method called EPPES ("Ensemble prediction and parameter estimation system") utilizes ensemble prediction infra-structure for parameter estimation in a very cost-effective way: practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating an ensemble of predictions so that each member uses different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In this presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an ensemble prediction system emulator, based on the ECHAM5 atmospheric GCM show that the model tuning capability of EPPES scales up to realistic models and ensemble prediction systems. Finally, preliminary results of EPPES in the context of ECMWF forecasting system are presented.
Variational methods to estimate terrestrial ecosystem model parameters
Delahaies, Sylvain; Roulstone, Ian
2016-04-01
Carbon is at the basis of the chemistry of life. Its ubiquity in the Earth system is the result of complex recycling processes. Present in the atmosphere in the form of carbon dioxide it is adsorbed by marine and terrestrial ecosystems and stored within living biomass and decaying organic matter. Then soil chemistry and a non negligible amount of time transform the dead matter into fossil fuels. Throughout this cycle, carbon dioxide is released in the atmosphere through respiration and combustion of fossils fuels. Model-data fusion techniques allow us to combine our understanding of these complex processes with an ever-growing amount of observational data to help improving models and predictions. The data assimilation linked ecosystem carbon (DALEC) model is a simple box model simulating the carbon budget allocation for terrestrial ecosystems. Over the last decade several studies have demonstrated the relative merit of various inverse modelling strategies (MCMC, ENKF, 4DVAR) to estimate model parameters and initial carbon stocks for DALEC and to quantify the uncertainty in the predictions. Despite its simplicity, DALEC represents the basic processes at the heart of more sophisticated models of the carbon cycle. Using adjoint based methods we study inverse problems for DALEC with various data streams (8 days MODIS LAI, monthly MODIS LAI, NEE). The framework of constraint optimization allows us to incorporate ecological common sense into the variational framework. We use resolution matrices to study the nature of the inverse problems and to obtain data importance and information content for the different type of data. We study how varying the time step affect the solutions, and we show how "spin up" naturally improves the conditioning of the inverse problems.
Variations on tremor parameters
Boose, A.; Jentgens, Ch.; Spieker, S.; Dichgans, J.
1995-03-01
This paper describes our analysis procedure for long-term tremor EMG recordings, as well as three examples of applications. The description of the method focuses on how characteristics of the tremor (e.g. frequency, intensity, agonist-antagonist interaction) can be defined and calculated based on surface EMG data. The resulting quantitative characteristics are called ``tremor parameters.'' We discuss sinusoidally modulated, band-limited white noise as a model for pathological tremor-EMG, and show how the basic parameters can be extracted from this class of signals. The method is then applied to (1) estimate tremor severity in clinical studies, (2) quantify agonist-antagonist interaction, and (3) investigate the variations of the tremor parameters using simple methods from time-series analysis.
Marton, F. C.
2001-12-01
The thermal, mineralogical, and buoyancy structures of thermal-kinetic models of subducting slabs are highly dependent upon a number of parameters, especially if the metastable persistence of olivine in the transition zone is investigated. The choice of starting thermal model for the lithosphere, whether a cooling halfspace (HS) or plate model, can have a significant effect, resulting in metastable wedges of olivine that differ in size by up to two to three times for high values of the thermal parameter (ǎrphi). Moreover, as ǎrphi is the product of the age of the lithosphere at the trench, convergence rate, and dip angle, slabs with similar ǎrphis can show great variations in structures as these constituents change. This is especially true for old lithosphere, as the lithosphere continually cools and thickens with age for HS models, but plate models, with parameters from Parson and Sclater [1977] (PS) or Stein and Stein [1992] (GDH1), achieve a thermal steady-state and constant thickness in about 70 My. In addition, the latent heats (q) of the phase transformations of the Mg2SiO4 polymorphs can also have significant effects in the slabs. Including q feedback in models raises the temperature and reduces the extent of metastable olivine, causing the sizes of the metastable wedges to vary by factors of up to two times. The effects of the choice of thermal model, inclusion and non-inclusion of q feedback, and variations in the constituents of ǎrphi are investigated for several model slabs.
Hertog, Maarten L. A. T. M.; Scheerlinck, Nico; Nicolaï, Bart M.
2009-01-01
When modelling the behaviour of horticultural products, demonstrating large sources of biological variation, we often run into the issue of non-Gaussian distributed model parameters. This work presents an algorithm to reproduce such correlated non-Gaussian model parameters for use with Monte Carlo simulations. The algorithm works around the problem of non-Gaussian distributions by transforming the observed non-Gaussian probability distributions using a proposed SKN-distribution function before applying the covariance decomposition algorithm to generate Gaussian random co-varying parameter sets. The proposed SKN-distribution function is based on the standard Gaussian distribution function and can exhibit different degrees of both skewness and kurtosis. This technique is demonstrated using a case study on modelling the ripening of tomato fruit evaluating the propagation of biological variation with time.
Simulations of a epidemic model with parameters variation analysis for the dengue fever
Jardim, C. L. T. F.; Prates, D. B.; Silva, J. M.; Ferreira, L. A. F.; Kritz, M. V.
2015-09-01
Mathematical models can be widely found in the literature for describing and analyzing epidemics. The models that use differential equations to represent mathematically such description are specially sensible to parameters involved in the modelling. In this work, an already developed model, called SIR, is analyzed when applied to a scenario of a dengue fever epidemic. Such choice is powered by the existence of useful tools presented by a variation of this original model, which allow an inclusion of different aspects of the dengue fever disease, as its seasonal characteristics, the presence of more than one strain of the vector and of the biological factor of cross-immunity. The analysis and results interpretation are performed through numerical solutions of the model in question, and a special attention is given to the different solutions generated by the use of different values for the parameters present in this model. Slight variations are performed either dynamically or statically in those parameters, mimicking hypothesized changes in the biological scenario of this simulation and providing a source of evaluation of how those changes would affect the outcomes of the epidemic in a population.
Testing variational estimation of process parameters and initial conditions of an earth system model
Directory of Open Access Journals (Sweden)
Simon Blessing
2014-03-01
Full Text Available We present a variational assimilation system around a coarse resolution Earth System Model (ESM and apply it for estimating initial conditions and parameters of the model. The system is based on derivative information that is efficiently provided by the ESM's adjoint, which has been generated through automatic differentiation of the model's source code. In our variational approach, the length of the feasible assimilation window is limited by the size of the domain in control space over which the approximation by the derivative is valid. This validity domain is reduced by non-smooth process representations. We show that in this respect the ocean component is less critical than the atmospheric component. We demonstrate how the feasible assimilation window can be extended to several weeks by modifying the implementation of specific process representations and by switching off processes such as precipitation.
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.
Castaings, W.; Dartus, D.; Le Dimet, F.-X.; Saulnier, G.-M.
2009-04-01
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.
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 investig
Knight, Christopher G; Knight, Sylvia H E; Massey, Neil; Aina, Tolu; Christensen, Carl; Frame, Dave J; Kettleborough, Jamie A; Martin, Andrew; Pascoe, Stephen; Sanderson, Ben; Stainforth, David A; Allen, Myles R
2007-07-24
In complex spatial models, as used to predict the climate response to greenhouse gas emissions, parameter variation within plausible bounds has major effects on model behavior of interest. Here, we present an unprecedentedly large ensemble of >57,000 climate model runs in which 10 parameters, initial conditions, hardware, and software used to run the model all have been varied. We relate information about the model runs to large-scale model behavior (equilibrium sensitivity of global mean temperature to a doubling of carbon dioxide). We demonstrate that effects of parameter, hardware, and software variation are detectable, complex, and interacting. However, we find most of the effects of parameter variation are caused by a small subset of parameters. Notably, the entrainment coefficient in clouds is associated with 30% of the variation seen in climate sensitivity, although both low and high values can give high climate sensitivity. We demonstrate that the effect of hardware and software is small relative to the effect of parameter variation and, over the wide range of systems tested, may be treated as equivalent to that caused by changes in initial conditions. We discuss the significance of these results in relation to the design and interpretation of climate modeling experiments and large-scale modeling more generally.
Sarkar, Debraj; Roy, Debabrata; Choudhury, Amalendu Bikash; Yamada, Sotoshi
2016-08-01
In modern day power systems, fault current limiters (FCL) are used to provide protection from high fault currents in the event of electrical faults and thus help to deliver uninterrupted electric supply to the consumers. Several technologies of FCLs are available for practical usage. However, the saturated iron-core superconducting fault current limiter (SISFCL) has gained a lot of attention in recent years in view of its ability to offer very low impedance during normal operation and high impedance during faulted condition. Previous mathematical models defining the performance of the device employs a simple BH curve. But as the change in mathematical state of saturation and unsaturation is important for the operation of the device, the paper investigates the responses considering the effects of magnetic hysteresis utilising the Jiles Atherton hysteresis model. Further the performance of the device is analysed with the variations of different parameters viz., the fault resistance magnitude, DC bias current, number of turns of the AC winding and number of turns of the DC winding that portray the effectiveness of the parameters encouraging an optimal design of the limiter.
Bifurcations, chaos, and sensitivity to parameter variations in the Sato cardiac cell model
Otte, Stefan; Berg, Sebastian; Luther, Stefan; Parlitz, Ulrich
2016-08-01
The dynamics of a detailed ionic cardiac cell model proposed by Sato et al. (2009) is investigated in terms of periodic and chaotic action potentials, bifurcation scenarios, and coexistence of attractors. Starting from the model's standard parameter values bifurcation diagrams are computed to evaluate the model's robustness with respect to (small) parameter changes. While for some parameters the dynamics turns out to be practically independent from their values, even minor changes of other parameters have a very strong impact and cause qualitative changes due to bifurcations or transitions to coexisting attractors. Implications of this lack of robustness are discussed.
Variation of the Moyer Model Parameter, H/sub 0/, with primary proton energy
Energy Technology Data Exchange (ETDEWEB)
Liu, K.L.; Stevenson, G.R.; Thomas, R.H.; Thomas, S.V.
1982-08-01
Experimental values of the Moyer Model Parameter H/sub 0/ were summarized and presented as a function of proton energy, E/sub p/. The variation of H/sub 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/sub 0/(E/sup p/ = (1.61 +- 0.19) x 10/sup -13/ Sv.m/sup 2//GeV to be compared with a value of (1.65 +- 0.21) x 10/sup -13/ Sv.m/sup 2//GeV published by Stevenson et al. (St 82).
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 seas
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.
Blümel, Marcus; Guschlbauer, Christoph; Daun-Gruhn, Silvia; Hooper, Scott L; Büschges, Ansgar
2012-11-01
Models built using mean data can represent only a very small percentage, or none, of the population being modeled, and produce different activity than any member of it. Overcoming this "averaging" pitfall requires measuring, in single individuals in single experiments, all of the system's defining characteristics. We have developed protocols that allow all the parameters in the curves used in typical Hill-type models (passive and active force-length, series elasticity, force-activation, force-velocity) to be determined from experiments on individual stick insect muscles (Blümel et al. 2012a). A requirement for means to not well represent the population is that the population shows large variation in its defining characteristics. We therefore used these protocols to measure extensor muscle defining parameters in multiple animals. Across-animal variability in these parameters can be very large, ranging from 1.3- to 17-fold. This large variation is consistent with earlier data in which extensor muscle responses to identical motor neuron driving showed large animal-to-animal variability (Hooper et al. 2006), and suggests accurate modeling of extensor muscles requires modeling individual-by-individual. These complete characterizations of individual muscles also allowed us to test for parameter correlations. Two parameter pairs significantly co-varied, suggesting that a simpler model could as well reproduce muscle response.
Hameed, Shilan S.; Aziz, Fakhra; Sulaiman, Khaulah; Ahmad, Zubair
2017-01-01
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. PMID:28793325
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.
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).
On Non-Linear Sensitivity of Marine Biological Models to Parameter Variations
2007-01-01
M.B., 2002. Understanding uncertain enviromental systems. In: Grasman, J., van Straten, G. (Eds.), Predictability and Nonlinear Modelling in Natural...Lekien, F., 2006. Quantifying uncertainities in ocean predictions. In: Paluszkiewicz, T., Harper, S. (Eds.), Oceanography, special issue on Advances in
Variation of wave directional spread parameters along the Indian coast
Digital Repository Service at National Institute of Oceanography (India)
SanilKumar, V.
Directional spreading of wave energy is popularly modeled with the help of the Cosine Power model and it mainly depends on the spreading parameter. This paper describes the variation of the spreading parameter estimated based on the wave data...
Distributed Parameter Modelling Applications
DEFF Research Database (Denmark)
2011-01-01
Here the issue of distributed parameter models is addressed. Spatial variations as well as time are considered important. Several applications for both steady state and dynamic applications are given. These relate to the processing of oil shale, the granulation of industrial fertilizers and the d......Here the issue of distributed parameter models is addressed. Spatial variations as well as time are considered important. Several applications for both steady state and dynamic applications are given. These relate to the processing of oil shale, the granulation of industrial fertilizers...... sands processing. The fertilizer granulation model considers the dynamics of MAP-DAP (mono and diammonium phosphates) production within an industrial granulator, that involves complex crystallisation, chemical reaction and particle growth, captured through population balances. A final example considers...
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)
Guardiola-Albert, Carolina; Díez-Herrero, Andrés; Bodoque, José M.; Bermejo, Marcos; Rivero-Honegger, Carlos; Yagüe, Carlos; Monjo, Robert; Tapiador, Francisco J.
2016-04-01
The present study deals the rainfall spatial variability of a small mountainous catchment, which includes the spatial distribution and variability of convective and stratiform events. This work focuses on the precipitation events with hydrological response in Venero-Claro Basin (Avila, Spain). In this basin of 15 square kilometers, flood events of different magnitudes have been often registered. Therefore, any improvement in understanding rainfall characteristics in the area can be of special importance in rainfall estimation and hence to calibrate and validate hydrological models. These enhancements imply more objectivity of risk studies and more predictive and preventive capacity. To separate events by origin it has been used the dimensionless index defined by Monjo (2015), according to the relative temporal distribution of maximum intensities. The main advantages of this method are that it does not require thresholds, so it can be applied for each rain gauge. The geostatistical variogram tool is used to quantify the spatial characteristics of both kinds of events. Hourly rainfall accumulations over the area are computed with observations from one of the 5 existing X-band radar in Spain and 7 rain gauges located in the zone. For each hour the rainfall variogram model has been fitted with the aid of the X-band radar images. Valuable information is extracted from the stratiform and convective ensembles of variogram models. The variogram model parameters are analyzed to determine characteristics of spatial continuity that differentiates stratiform and convective events, and quartiles of sills and ranges in both ensembles are compared.
Directory of Open Access Journals (Sweden)
M. A. Volkov
Full Text Available We have used the global numerical model of the coupled ionosphere-thermosphere-protonosphere system to simulate the electric-field, ion- and electron-temperature and -concentration variations observed by EISCAT during the substorm event of 25 March 1987. In our previous studies we adopted the model input data for field-aligned currents and precipitating electron fluxes to obtain an agreement between observed and modelled ionospheric variations. Now, we have calculated the field-aligned currents needful to simulate the substrom variations of the electric field and other parameters observed by EISCAT. The calculations of the field-aligned currents have been performed by means of numerical integration of the time-dependent continuity equation for the cold magnetospheric electrons. This equation was added to the system of the modelling equations including the equation for the electric-field potential to be solved jointly. In this case the inputs of the model are the spatial and time variations of the electric-field potential at the polar-cap boundaries and those of the cold magnetospheric electron concentration which have been adopted to obtain the agreement between the observed and modelled ionospheric variations for the substorm event of 25 March 1987. By this means it has been found that during the active phase of the substorm the current wedge is formed. It is connected with the region of the decreased cold magnetospheric electron content travelling westwards with a velocity of about 1 km s^{–1} at ionospheric levels.
Energy Technology Data Exchange (ETDEWEB)
Kanezaki, Akio; Shirai, Hiroshi [Chuo University, 1-13-27 Kasuga, Bunkyo-ku, Tokyo 112-8551 (Japan); Hirata, Akimasa; Watanabe, Soichi, E-mail: ahirata@nitech.ac.j [National Institute of Information and Communications Technology, 4-2-1 Nukuikitamachi, Koganei-shi, Tokyo 184-8795 (Japan)
2010-08-21
The present study describes theoretical parametric analysis of the steady-state temperature elevation in one-dimensional three-layer (skin, fat and muscle) and one-layer (skin only) models due to millimeter-wave exposure. The motivation of this fundamental investigation is that some variability of warmth sensation in the human skin has been reported. An analytical solution for a bioheat equation was derived by using the Laplace transform for the one-dimensional human models. Approximate expressions were obtained to investigate the dependence of temperature elevation on different thermal and tissue thickness parameters. It was shown that the temperature elevation on the body surface decreases monotonically with the blood perfusion rate, heat conductivity and heat transfer from the body to air. Also revealed were the conditions where maximum and minimum surface temperature elevations were observed for different thermal and tissue thickness parameters. The surface temperature elevation in the three-layer model is 1.3-2.8 times greater than that in the one-layer model. The main reason for this difference is attributed to the adiabatic nature of the fat layer. By considering the variation range of thermal and tissue thickness parameters which causes the maximum and minimum temperature elevations, the dominant parameter influencing the surface temperature elevation was found to be the heat transfer coefficient between the body surface and air.
Storm surge variational assimilation model
Directory of Open Access Journals (Sweden)
Shi-li HUANG
2010-06-01
Full Text Available To eliminate errors caused by uncertainty of parameters and further improve capability of storm surge forecasting, the variational data assimilation method is applied to the storm surge model based on unstructured grid with high spatial resolution. The method can effectively improve the forecasting accuracy of storm surge induced by typhoon through controlling wind drag force coefficient parameter. The model is first theoretically validated with synthetic data. Then, the real storm surge process induced by the TC 0515 typhoon is forecasted by the variational data assimilation model, and results show the feasibility of practical application.
Kane, A.; Moulin, C.; Thiria, S.; Bopp, L.; Berrada, M.; Tagliabue, A.; CréPon, M.; Aumont, O.; Badran, F.
2011-06-01
The global ocean biogeochemical models that are used in order to assess the ocean role in the global carbon cycle and estimate the impact of the climate change on marine ecosystems are getting more and more sophisticated. They now often account for several phytoplankton functional types that play particular roles in marine food webs and the ocean carbon cycle. These phytoplankton functional types have specific physiological characteristics, which are usually poorly known and therefore add uncertainties to model results. Indeed, this evolution in model complexity is not accompanied by a similar increase in the number and diversity of in situ data sets necessary for model calibration and evaluation. Thus, it is of primary importance to develop new methods to improve model performance using existing biogeochemical data sets, despite their current limitations. In this paper, we have optimized 45 physiological parameters of the PISCES global model, using a variational optimal control method. In order to bypass a global 3-D ocean variational assimilation, which would require enormous computation and memory storage, we have simplified the estimation procedure by assimilating monthly climatological in situ observations at five contrasted oceanographic stations of the JGOFS program in a 1-D version of the PISCES model. We began by estimating the weight matrix in the cost function by using heuristic considerations. Then we used this matrix to estimate the 45 parameters of the 1-D version of the PISCES model by assimilating the different monthly profiles (observed profiles at the five stations) in the same variational procedure on a time window of 1 year. This set of optimized parameters was then used in the standard 3-D global PISCES version to perform a 500 year global simulation. The results of both the standard and the optimized versions of the model were compared to satellite-derived chlorophyll-a images, which are an independent and global data set, showing that our
Dathe, Margitta; Meyer, Jana; Beyermann, Michael; Maul, Björn; Hoischen, Christian; Bienert, Michael
2002-02-01
Model compounds of modified hydrophobicity (Eta), hydrophobic moment (mu) and angle subtended by charged residues (Phi) were synthesized to define the general roles of structural motifs of cationic helical peptides for membrane activity and selectivity. The peptide sets were based on a highly hydrophobic, non-selective KLA model peptide with high antimicrobial and hemolytic activity. Variation of the investigated parameters was found to be a suitable method for modifying peptide selectivity towards either neutral or highly negatively charged lipid bilayers. Eta and mu influenced selectivity preferentially via modification of activity on 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine (POPC) bilayers, while the size of the polar/hydrophobic angle affected the activity against 1-palmitoyl-2-oleoylphosphatidyl-DL-glycerol (POPG). The influence of the parameters on the activity determining step was modest in both lipid systems and the activity profiles were the result of the parameters' influence on the second less pronounced permeabilization step. Thus, the activity towards POPC vesicles was determined by the high permeabilizing efficiency, however, changes in the structural parameters preferentially influenced the relatively moderate affinity. In contrast, intensive peptide accumulation via electrostatic interactions was sufficient for the destabilization of highly negatively charged POPG lipid membranes, but changes in the activity profile, as revealed by the modification of Phi, seem to be preferentially caused by variation of the low permeabilizing efficiency. The parameters proved very effective also in modifying antimicrobial and hemolytic activity. However, their influence on cell selectivity was limited. A threshold value of hydrophobicity seems to exist which restricted the activity modifying potential of mu and Phi on both lipid bilayers and cell membranes.
DEFF Research Database (Denmark)
Ibsen, Lars Bo; Liingaard, Morten
A lumped-parameter model represents the frequency dependent soil-structure interaction of a massless foundation placed on or embedded into an unbounded soil domain. The lumped-parameter model development have been reported by (Wolf 1991b; Wolf 1991a; Wolf and Paronesso 1991; Wolf and Paronesso 19...
UPRE method for total variation parameter selection
Energy Technology Data Exchange (ETDEWEB)
Wohlberg, Brendt [Los Alamos National Laboratory; Lin, Youzuo [Los Alamos National Laboratory
2008-01-01
Total Variation (TV) Regularization is an important method for solving a wide variety of inverse problems in image processing. In order to optimize the reconstructed image, it is important to choose the optimal regularization parameter. The Unbiased Predictive Risk Estimator (UPRE) has been shown to give a very good estimate of this parameter for Tikhonov Regularization. In this paper we propose an approach to extend UPRE method to the TV problem. However, applying the extended UPRE is impractical in the case of inverse problems such as de blurring, due to the large scale of the associated linear problem. We also propose an approach to reducing the large scale problem to a small problem, significantly reducing computational requirements while providing a good approximation to the original problem.
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.)
Energy Technology Data Exchange (ETDEWEB)
Shankar, Ravi; Mondal, Prasenjit; Chand, Shri [Indian Institute of Technology Roorkee, Uttaranchal (India). Dept. of Chemical Engineering
2013-11-01
In the present paper steady state models of a double chamber glucose glutamic acid microbial fuel cell (GGA-MFC) under continuous operation have been developed and solved using Matlab 2007 software. The experimental data reported in a recent literature has been used for the validation of the models. The present models give prediction on the cell voltage and cell power density with 19-44% errors, which is less (up to 20%) than the errors on the prediction of cell voltage made in some recent literature for the same MFC where the effects of the difference in pH and ionic conductivity between anodic and cathodic solutions on cell voltage were not incorporated in model equations. It also describes the changes in anodic and cathodic chamber temperature due to the increase in substrate concentration and cell current density. Temperature profile across the membrane thickness has also been studied. (orig.)
Response model parameter linking
Barrett, Michelle Derbenwick
2015-01-01
With a few exceptions, the problem of linking item response model parameters from different item calibrations has been conceptualized as an instance of the problem of equating observed scores on different test forms. This thesis argues, however, that the use of item response models does not require
Volume variation of Gruneisen parameters of fcc transition metals
Indian Academy of Sciences (India)
C V Pandya; P R Vyas; T C Pandya; V B Gohel
2002-02-01
The volume variation of the Gruneisen parameters of ten fcc transition metals, up to 40% compression, has been studied on the basis of a model approach proposed by Antonov et al. The results are reasonably good for six metals except for Rh, Ag, Au and Ni when compared with available experimental and other theoretical values. The model requires an appropriate modification for Rh, Ag, Au and Ni.
Estimating parameters in stochastic systems: A variational Bayesian approach
Vrettas, Michail D.; Cornford, Dan; Opper, Manfred
2011-11-01
This work is concerned with approximate inference in dynamical systems, from a variational Bayesian perspective. When modelling real world dynamical systems, stochastic differential equations appear as a natural choice, mainly because of their ability to model the noise of the system by adding a variation of some stochastic process to the deterministic dynamics. Hence, inference in such processes has drawn much attention. Here a new extended framework is derived that is based on a local polynomial approximation of a recently proposed variational Bayesian algorithm. The paper begins by showing that the new extension of this variational algorithm can be used for state estimation (smoothing) and converges to the original algorithm. However, the main focus is on estimating the (hyper-) parameters of these systems (i.e. drift parameters and diffusion coefficients). The new approach is validated on a range of different systems which vary in dimensionality and non-linearity. These are the Ornstein-Uhlenbeck process, the exact likelihood of which can be computed analytically, the univariate and highly non-linear, stochastic double well and the multivariate chaotic stochastic Lorenz ’63 (3D model). As a special case the algorithm is also applied to the 40 dimensional stochastic Lorenz ’96 system. In our investigation we compare this new approach with a variety of other well known methods, such as the hybrid Monte Carlo, dual unscented Kalman filter, full weak-constraint 4D-Var algorithm and analyse empirically their asymptotic behaviour as a function of observation density or length of time window increases. In particular we show that we are able to estimate parameters in both the drift (deterministic) and the diffusion (stochastic) part of the model evolution equations using our new methods.
Cosmological models with constant deceleration parameter
Energy Technology Data Exchange (ETDEWEB)
Berman, M.S.; de Mello Gomide, F.
1988-02-01
Berman presented elsewhere a law of variation for Hubble's parameter that yields constant deceleration parameter models of the universe. By analyzing Einstein, Pryce-Hoyle and Brans-Dicke cosmologies, we derive here the necessary relations in each model, considering a perfect fluid.
Gain Variation with Raman Amplifier Parameters and Its Restoration
Institute of Scientific and Technical Information of China (English)
无
2003-01-01
We demonstrate that gain profile of a distributed Raman amplifier is sensitive to its parameter variation, such as loss/gain coefficients change or partial pump failure. Gain flatness can be restored by adjusting power of pump lasers.
Variation of semen parameters in healthy medical students due to ...
African Journals Online (AJOL)
Variation of semen parameters in healthy medical students due to exam ... period when compared to samples donated at the beginning of the semester. Conclusion Stress levels of donors might prove to be clinically relevant and important ...
Anisotropic parameter estimation using velocity variation with offset analysis
Energy Technology Data Exchange (ETDEWEB)
Herawati, I.; Saladin, M.; Pranowo, W.; Winardhie, S.; Priyono, A. [Faculty of Mining and Petroleum Engineering, Institut Teknologi Bandung, Jalan Ganesa 10, Bandung, 40132 (Indonesia)
2013-09-09
Seismic anisotropy is defined as velocity dependent upon angle or offset. Knowledge about anisotropy effect on seismic data is important in amplitude analysis, stacking process and time to depth conversion. Due to this anisotropic effect, reflector can not be flattened using single velocity based on hyperbolic moveout equation. Therefore, after normal moveout correction, there will still be residual moveout that relates to velocity information. This research aims to obtain anisotropic parameters, ε and δ, using two proposed methods. The first method is called velocity variation with offset (VVO) which is based on simplification of weak anisotropy equation. In VVO method, velocity at each offset is calculated and plotted to obtain vertical velocity and parameter δ. The second method is inversion method using linear approach where vertical velocity, δ, and ε is estimated simultaneously. Both methods are tested on synthetic models using ray-tracing forward modelling. Results show that δ value can be estimated appropriately using both methods. Meanwhile, inversion based method give better estimation for obtaining ε value. This study shows that estimation on anisotropic parameters rely on the accuracy of normal moveout velocity, residual moveout and offset to angle transformation.
Robust Active Suspension Design Subject to Vehicle Inertial Parameter Variations
Institute of Scientific and Technical Information of China (English)
Hai-Ping Du; Nong Zhang
2010-01-01
This paper presents an approach in designing a robust controller for vehicle suspensions considering changes in vehicle inertial properties. A four-degree-of-freedom half-car model with active suspension is studied in this paper, and three main performance requirements are considered. Among these requirements, the ride comfort performance is optimized by minimizing the H∞ norm of the transfer function from the road disturbance to the sprung mass acceleration, while the road holding performance and the suspension deflection limitation are guaranteed by constraining the generalized H2 (GH2) norms of the transfer functions from the road disturbance to the dynamic tyre load and the suspension deflection to be less than their hard limits, respectively. At the same time, the controller saturation problem is considered by constraining its peak response output to be less than a given limit using the GH2 norm as well. By solving the finite number of linear matrix inequalities (LMIs) with the minimization optimization procedure, the controller gains, which are dependent on the time-varying inertial parameters, can be obtained. Numerical simulations on both frequency and bump responses show that the designed parameter-dependent controller can achieve better active suspension performance compared with the passive suspension in spite of the variations of inertial parameters.
Krivolutsky, A. A.; Dement'eva, A. V.; Kukoleva, A. A.
2016-12-01
The results of a three-dimensional numerical simulation of changes in the temperature and wind within a height range of up to 100 km caused by changes in fluxes in the solar ultraviolet (UV) radiation in the 23rd solar activity cycle (which was characterized by unusually low values of UV-radiation fluxes) and also of global changes in the ozone content are presented. The simulation results showed that the response of the temperature to variations in the UV radiation are substantially of a nonzonal character, which is caused by the presence in the model of sources of quasi-stationary waves corresponding to the observational data.
Institute of Scientific and Technical Information of China (English)
胡晓红; 陈大卿
2012-01-01
给出了一种基于变分偏微分方程的双参数图像去噪模型.利用变分法的极大极小原理,证明了该双参数模型存在唯一的极小值,给出该模型的Euler-Lagrange方程,根据给出的偏微分方程的离散格式,对噪声图像进行去噪,与Rudin,Osher and Fatemi提出的模型(ROF模型)的结果比较,结果表明,双参数模型在视觉上及峰度信噪比上都比ROF模型的去噪效果好.%This paper presents an image denoising model based on Variational Partial differential equation with double parameters. Firstly,using the minimax principle of variational method,this paper proves that the double parameters model has an unique minimal value,then it gives the corresponding Euler-Lagrange equation. Secondly,According to the given discrete format of partial differential equation,it denoises some noise images. Comparing the results with Rudin,Osher and Fatemi model(ROF model) ,the results show that double parameters model in visual and kurtosis signal-to-noise ratio has better denoising effect.
Recent variations of fundamental parameters and their implications for gravitation
Dent, Thomas
2010-01-01
We compare the sensitivity of a recent bound on time variation of the fine structure constant from optical clocks with bounds on time varying fundamental constants from atomic clocks sensitive to the electron-to-proton mass ratio, from radioactive decay rates in meteorites, and from the Oklo natural reactor. Tests of the Weak Equivalence Principle also lead to comparable bounds on present time variations of constants, as well as putting the strongest limits on variations tracking the gravitational potential. For recent time variations, the "winner in sensitivity" depends on possible relations between the variations of different couplings in the standard model of particle physics. WEP tests are currently the most sensitive within scenarios with unification of gauge interactions. A detection of time variation in atomic clocks would favour dynamical dark energy and put strong constraints on the dynamics of a cosmological scalar field.
Photovoltaic module parameters acquisition model
Cibira, Gabriel; Koščová, Marcela
2014-09-01
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.
Mode choice model parameters estimation
Strnad, Irena
2010-01-01
The present work focuses on parameter estimation of two mode choice models: multinomial logit and EVA 2 model, where four different modes and five different trip purposes are taken into account. Mode choice model discusses the behavioral aspect of mode choice making and enables its application to a traffic model. Mode choice model includes mode choice affecting trip factors by using each mode and their relative importance to choice made. When trip factor values are known, it...
Solutions of fractional diffusion equations by variation of parameters method
Directory of Open Access Journals (Sweden)
Mohyud-Din Syed Tauseef
2015-01-01
Full Text Available This article is devoted to establish a novel analytical solution scheme for the fractional diffusion equations. Caputo’s formulation followed by the variation of parameters method has been employed to obtain the analytical solutions. Following the derived analytical scheme, solution of the fractional diffusion equation for several initial functions has been obtained. Graphs are plotted to see the physical behavior of obtained solutions.
Estimation of shape model parameters for 3D surfaces
DEFF Research Database (Denmark)
Erbou, Søren Gylling Hemmingsen; Darkner, Sune; Fripp, Jurgen;
2008-01-01
Statistical shape models are widely used as a compact way of representing shape variation. Fitting a shape model to unseen data enables characterizing the data in terms of the model parameters. In this paper a Gauss-Newton optimization scheme is proposed to estimate shape model parameters of 3D s...
Barber, Michael N.
1980-03-01
An algorithm for determining the sequence of variational parameters in a variational approximation to a real-space renormalization group is developed. Using this procedure, the Kadanoff one-hypercube approximation for the two-dimensional Ising model is investigated in some detail. We conclude that the apparent success of this method is somewhat fortuitous; a consistent and completely optimized treatment yielding considerably poorer estimates of the specific heat exponents. In addition, the variational parameter is found to be non-analytic at the fixed point. The nature of singularity agrees with the predictions of van Saarloos, van Leeuwen, and Pruisken.
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.
Variational methods in molecular modeling
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...
Parameter variations in prediction skill optimization at ECMWF
Ollinaho, P.; Bechtold, P.; Leutbecher, M.; Laine, M.; Solonen, A.; Haario, H.; Järvinen, H.
2013-11-01
Algorithmic numerical weather prediction (NWP) skill optimization has been tested using the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). We report the results of initial experimentation using importance sampling based on model parameter estimation methodology targeted for ensemble prediction systems, called the ensemble prediction and parameter estimation system (EPPES). The same methodology was earlier proven to be a viable concept in low-order ordinary differential equation systems, and in large-scale atmospheric general circulation models (ECHAM5). Here we show that prediction skill optimization is possible even in the context of a system that is (i) of very high dimensionality, and (ii) carefully tuned to very high skill. We concentrate on four closure parameters related to the parameterizations of sub-grid scale physical processes of convection and formation of convective precipitation. We launch standard ensembles of medium-range predictions such that each member uses different values of the four parameters, and make sequential statistical inferences about the parameter values. Our target criterion is the squared forecast error of the 500 hPa geopotential height at day three and day ten. The EPPES methodology is able to converge towards closure parameter values that optimize the target criterion. Therefore, we conclude that estimation and cost function-based tuning of low-dimensional static model parameters is possible despite the very high dimensional state space, as well as the presence of stochastic noise due to initial state and physical tendency perturbations. The remaining question before EPPES can be considered as a generally applicable tool in model development is the correct formulation of the target criterion. The one used here is, in our view, very selective. Considering the multi-faceted question of improving forecast model performance, a more general target criterion should be developed
Describing variations of the Fisher-matrix across parameter space
Schäfer, Björn Malte
2016-01-01
Forecasts in cosmology, both with Monte-Carlo Markov-chain methods and with the Fisher matrix formalism, depend on the choice of the fiducial model because both the signal strength of any observable as well as the model nonlinearities linking observables to cosmological parameters vary in the general case. In this paper we propose a method for extrapolating Fisher-forecasts across the space of cosmological parameters by constructing a suitable ba- sis. We demonstrate the validity of our method with constraints on a standard dark energy model extrapolated from a {\\Lambda}CDM-model, as can be expected from 2-bin weak lensing to- mography with a Euclid-like survey, in the parameter pairs $(\\Omega_\\text{m},\\sigma_8)$, $(\\Omega_\\text{m}, w_0)$ and $(w_0, w_\\text{a})$. Our numerical results include very accurate extrapolations across a wide range of cosmo- logical parameters in terms of shape, size and orientation of the parameter likelihood, and a decomposition of the change of the likelihood contours into modes, ...
Variational Methods for Biomolecular Modeling
Wei, Guo-Wei
2016-01-01
Structure, function and dynamics of many biomolecular systems can be characterized by the energetic variational principle and the corresponding systems of partial differential equations (PDEs). This principle allows us to focus on the identification of essential energetic components, the optimal parametrization of energies, and the efficient computational implementation of energy variation or minimization. Given the fact that complex biomolecular systems are structurally non-uniform and their interactions occur through contact interfaces, their free energies are associated with various interfaces as well, such as solute-solvent interface, molecular binding interface, lipid domain interface, and membrane surfaces. This fact motivates the inclusion of interface geometry, particular its curvatures, to the parametrization of free energies. Applications of such interface geometry based energetic variational principles are illustrated through three concrete topics: the multiscale modeling of biomolecular electrosta...
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
Roe, Byron
2013-01-01
The effect of correlations between model parameters and nuisance parameters is discussed, in the context of fitting model parameters to data. Modifications to the usual $\\chi^2$ method are required. Fake data studies, as used at present, will not be optimum. Problems will occur for applications of the Maltoni-Schwetz \\cite{ms} theorem. Neutrino oscillations are used as examples, but the problems discussed here are general ones, which are often not addressed.
Equilibrium models and variational inequalities
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...
The Degree Semantics Parameter and cross-linguistic variation
Directory of Open Access Journals (Sweden)
M. Ryan Bochnak
2015-03-01
Full Text Available The standard degree analysis of gradability in English holds that the function of degree morphology, such as the comparative, measure phrases, and degree adverbs, is to bind a degree variable located in the lexical semantics of gradable predicates. In this paper, I investigate gradation structures in Washo (isolate/Hokan, and claim that this language systematically lacks degree morphology of this sort. I propose that this gap in the functional inventory of Washo stems from a parameter on whether languages are able to introduce degree variables into the logical form that can be bound by such operators, providing further cross-linguistic support for a similar proposal made by Beck et al. (2009 for Motu (Austronesian. Specifically, I argue that gradable predicates in Washo do not introduce a degree variable. Consequently, if we assume that gradable predicates in English are type ⟨d, ⟨e, t⟩⟩, then Washo and English must differ in their lexical semantics for gradable predicates. Alternatively, if we want to maintain lexical uniformity between the two languages (i.e., that gradable predicates in English don’t themselves introduce degrees, then we must place variation at the level of a grammatical mechanism that introduces degrees in English for degree operators to bind, but which is lacking in Washo. The results of this investigation thus inform questions about the nature of cross-linguistic variation, specifically the division of labor between variation in functional categories and the lexicon. http://dx.doi.org/10.3765/sp.8.6 BibTeX info
Estimating winter wheat phenological parameters: Implications for crop modeling
Crop parameters, such as the timing of developmental events, are critical for accurate simulation results in crop simulation models, yet uncertainty often exists in determining the parameters. Factors contributing to the uncertainty include: a) sources of variation within a plant (i.e., within diffe...
A study on parameter variation effects on battery packs for electric vehicles
Zhou, Long; Zheng, Yuejiu; Ouyang, Minggao; Lu, Languang
2017-10-01
As one single cell cannot meet power and driving range requirement in an electric vehicle, the battery packs with hundreds of single cells connected in parallel and series should be constructed. The most significant difference between a single cell and a battery pack is cell variation. Not only does cell variation affect pack energy density and power density, but also it causes early degradation of battery and potential safety issues. The cell variation effects on battery packs are studied, which are of great significant to battery pack screening and management scheme. In this study, the description for the consistency characteristics of battery packs was first proposed and a pack model with 96 cells connected in series was established. A set of parameters are introduced to study the cell variation and their impacts on battery packs are analyzed through the battery pack capacity loss simulation and experiments. Meanwhile, the capacity loss composition of the battery pack is obtained and verified by the temperature variation experiment. The results from this research can demonstrate that the temperature, self-discharge rate and coulombic efficiency are the major affecting parameters of cell variation and indicate the dissipative cell equalization is sufficient for the battery pack.
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.
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 Osa Peninsula relative to the Nicoya Peninsula, mimicking the along-strike variations in calculated interplate coupling.
PARAMETER ESTIMATION OF ENGINEERING TURBULENCE MODEL
Institute of Scientific and Technical Information of China (English)
钱炜祺; 蔡金狮
2001-01-01
A parameter estimation algorithm is introduced and used to determine the parameters in the standard k-ε two equation turbulence model (SKE). It can be found from the estimation results that although the parameter estimation method is an effective method to determine model parameters, it is difficult to obtain a set of parameters for SKE to suit all kinds of separated flow and a modification of the turbulence model structure should be considered. So, a new nonlinear k-ε two-equation model (NNKE) is put forward in this paper and the corresponding parameter estimation technique is applied to determine the model parameters. By implementing the NNKE to solve some engineering turbulent flows, it is shown that NNKE is more accurate and versatile than SKE. Thus, the success of NNKE implies that the parameter estimation technique may have a bright prospect in engineering turbulence model research.
Solution of Seventh Order Boundary Value Problems by Variation of Parameters Method
Directory of Open Access Journals (Sweden)
Muzammal Iftikhar
2013-01-01
Full Text Available The induction motor behavior is represented by a fifth order differential equation model. Addition of a torque correction factor to this model accurately reproduces the transient torques and instantaneous real and reactive power flows of the full seventh order differential equation model. The aim of this study is to solve the seventh order boundary value problems and the variation of parameters method is used for this purpose. The approximate solutions of the problems are obtained in terms of rapidly convergent series. Two numerical examples have been given to illustrate the efficiency and implementation of the method.
GIS-Based Hydrogeological-Parameter Modeling
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
A regression model is proposed to relate the variation of water well depth with topographic properties (area and slope), the variation of hydraulic conductivity and vertical decay factor. The implementation of this model in GIS environment (ARC/TNFO) based on known water data and DEM is used to estimate the variation of hydraulic conductivity and decay factor of different lithoiogy units in watershed context.
Kocaturk, Huseyin; Kumral, Mustafa
2016-04-01
Plate tectonics is one of the most illustrated theory and biggest geo-dynamic incident on earth surface and sub-surface for the earth science. Tectonic settlement, rock forming minerals, form of stratigraphy, ore genesis processes, crystal structures and even rock textures are all related with plate tectonic. One of the most known region of Turkey is Southern part of Uludaǧ and has been defined with three main lithological union. Region is formed with metamorphics, ophiolites and magmatic intrusions which are generally I-type granodiorites. Also these intrusion related rocks has formed and altered by high grade hydrothermal activity. This study approaches to understand bigger to smaller frameworks of these processes which between plate tectonics and fluid pathways. Geodynamic related fuzzy logic modelling is present us compact conclusion report about structural associations for the economic generations. Deformation structures and fluid pathways which related with plate tectonics progressed on our forearc system and each steps of dynamic movements of subducting mechanism has been seemed affect both hydrothermal stages and mineral variations together. Types of each deformation structure and mineral assemblages has characterized for flux estimations which can be useful for subsurface mapping. Geoanalytical results showed us clear characteristic stories for mutual processes. Determined compression and release directions on our map explains not only hydrothermal stages but also how succesion of intrusions changes. Our fuzzy logic models intersect sections of physical and chemical interactions of study field. Researched parameters like mafic minerals and enclave ratios on different deformation structures, cross sections of structures and relative existing sequence are all changes with different time periods like geochemical environment and each vein. With the combined informations in one scene we can transact mineralization processes about region which occurs in
Quasi-sure Product Variation of Two-parameter Smooth Martingales on the Wiener Space
Institute of Scientific and Technical Information of China (English)
Ji Cheng LIU; Jia Gang REN
2006-01-01
In this paper, we prove that the process of product variation of a two-parameter smooth martingale admits an ∞ modification, which can be constructed as the quasi-sure limit of sum of the corresponding product variation.
Estimation of growth parameters using a nonlinear mixed Gompertz model.
Wang, Z; Zuidhof, M J
2004-06-01
In order to maximize the utility of simulation models for decision making, accurate estimation of growth parameters and associated variances is crucial. A mixed Gompertz growth model was used to account for between-bird variation and heterogeneous variance. The mixed model had several advantages over the fixed effects model. The mixed model partitioned BW variation into between- and within-bird variation, and the covariance structure assumed with the random effect accounted for part of the BW correlation across ages in the same individual. The amount of residual variance decreased by over 55% with the mixed model. The mixed model reduced estimation biases that resulted from selective sampling. For analysis of longitudinal growth data, the mixed effects growth model is recommended.
Uncertainty Quantification for Optical Model Parameters
Lovell, A E; Sarich, J; Wild, S M
2016-01-01
Although uncertainty quantification has been making its way into nuclear theory, these methods have yet to be explored in the context of reaction theory. For example, it is well known that different parameterizations of the optical potential can result in different cross sections, but these differences have not been systematically studied and quantified. The purpose of this work is to investigate the uncertainties in nuclear reactions that result from fitting a given model to elastic-scattering data, as well as to study how these uncertainties propagate to the inelastic and transfer channels. We use statistical methods to determine a best fit and create corresponding 95\\% confidence bands. A simple model of the process is fit to elastic-scattering data and used to predict either inelastic or transfer cross sections. In this initial work, we assume that our model is correct, and the only uncertainties come from the variation of the fit parameters. We study a number of reactions involving neutron and deuteron p...
Variation of semen parameters in healthy medical students due to ...
African Journals Online (AJOL)
that vary most in samples of healthy donors undergoing stressful examination period. ... Assessment of semen quality is based on an evaluation of several parameters ... having a very important impact on infertility in both males and females.
Cluster variation studies of the anisotropic exchange interaction model
King, T. C.; Chen, H. H.
The cluster variation method is applied to study critical properties of the Potts-like ferromagnetic anisotropic exchange interaction model. Phase transition temperatures, order parameter discontinuities and latent heats of the model on the triangular and the fcc lattices are determined by the triangle approximation; and those on the square and the sc lattices are determined by the square approximation.
Transformations among CE–CVM model parameters for multicomponent systems
Indian Academy of Sciences (India)
B Nageswara Sarma; Shrikant Lele
2005-06-01
In the development of thermodynamic databases for multicomponent systems using the cluster expansion–cluster variation methods, we need to have a consistent procedure for expressing the model parameters (CECs) of a higher order system in terms of those of the lower order subsystems and to an independent set of parameters which exclusively represent interactions of the higher order systems. Such a procedure is presented in detail in this communication. Furthermore, the details of transformations required to express the model parameters in one basis from those defined in another basis for the same system are also presented.
Variations in epidemic distribution with some characteristic parameters
Institute of Scientific and Technical Information of China (English)
Liu Zhen-Zhen; Wang Xing-Yuan; Wang Mao-Ji
2012-01-01
Considering the spread of an epidemic among a population of mobile agents that can get infected and maintain the infection for a period,we investigate the variation in the homogeneity of the distribution of the epidemic with the remaining time of infection τ,the velocity modulus of the agent υ,and the infection rate α.We find that the distribution of the infected cluster size is always exponential.By analyzing the variation of the characteristic infected cluster size coefficient,we show that the inhomogeneity of epidemic distribution increases with an increase in τ for very low υ,while it decreases with an increase in τ for moderate υ.The epidemic distribution also tends to a homogeneous state as both υ and α increase.
Dark energy equation of state parameter and its variation at low redshifts
Tripathi, Ashutosh; Jassal, H K
2016-01-01
In this paper, we constrain dark energy models using a compendium of observations at low redshifts. We consider the dark energy as a barotropic fluid, with the equation of state a constant as well the case where dark energy equation of state is a function of time. The observations considered here are Supernova Type Ia data, Baryonic Acoustic Oscillation data and Hubble parameter measurements. We compare constraints obtained from these data and also do a combined analysis. The combined observational constraints put strong limits on variation of dark energy energy density with redshift. For varying dark energy models, the range of parameters preferred by the supernova type Ia data is in tension with the other low redshift distance measurements.
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.
Variations of cosmic large-scale structure covariance matrices across parameter space
Reischke, Robert; Kiessling, Alina; Schäfer, Björn Malte
2017-03-01
The likelihood function for cosmological parameters, given by e.g. weak lensing shear measurements, depends on contributions to the covariance induced by the non-linear evolution of the cosmic web. As highly non-linear clustering to date has only been described by numerical N-body simulations in a reliable and sufficiently precise way, the necessary computational costs for estimating those covariances at different points in parameter space are tremendous. In this work, we describe the change of the matter covariance and the weak lensing covariance matrix as a function of cosmological parameters by constructing a suitable basis, where we model the contribution to the covariance from non-linear structure formation using Eulerian perturbation theory at third order. We show that our formalism is capable of dealing with large matrices and reproduces expected degeneracies and scaling with cosmological parameters in a reliable way. Comparing our analytical results to numerical simulations, we find that the method describes the variation of the covariance matrix found in the SUNGLASS weak lensing simulation pipeline within the errors at one-loop and tree-level for the spectrum and the trispectrum, respectively, for multipoles up to ℓ ≤ 1300. We show that it is possible to optimize the sampling of parameter space where numerical simulations should be carried out by minimizing interpolation errors and propose a corresponding method to distribute points in parameter space in an economical way.
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)
PARAMETER ESTIMATION IN BREAD BAKING MODEL
Hadiyanto Hadiyanto; AJB van Boxtel
2012-01-01
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 pro...
The effect of model errors in variational assimilation
Wergen, Werner
1992-08-01
A linearized, one-dimensional shallow water model is used to investigate the effect of model errors in four-dimensional variational assimilation. A suitable initialization scheme for variational assimilation is proposed. Introducing deliberate phase speed errors in the model, the results from variational assimilation are compared to standard analysis/forecast cycle experiments. While the latter draws to the data and reflects the model errors only in the datavoid areas, variational assimilation with the model used as strong constraint is shown to distribute the model errors over the entire analysis domain. The implications for verification and diagnostics are discussed. Temporal weighting of the observations can reduce the errors towards the end of the assimilation period, but may deteriorate the subsequent forecasts. An extension to variational assimilation is proposed, which seeks not only to determine the initial state from the observations but also some of the tunable parameters of the model. The potentional usefulness of this approach for parameterization studies and for a separation of forecast errors into model- and analysis errors is discussed. Finally, variational assimilations with the model used as weak constraint are presented. While showing a good performance in the assimilation, forecasts can suffer severely if the extra term in the equations up to which the model is enforced are unable to compensate for the real model error. In the discussion, an overall appraisal of both assimilation methods is given.
Parameter counting in models with global symmetries
Energy Technology Data Exchange (ETDEWEB)
Berger, Joshua [Institute for High Energy Phenomenology, Newman Laboratory of Elementary Particle Physics, Cornell University, Ithaca, NY 14853 (United States)], E-mail: jb454@cornell.edu; Grossman, Yuval [Institute for High Energy Phenomenology, Newman Laboratory of Elementary Particle Physics, Cornell University, Ithaca, NY 14853 (United States)], E-mail: yuvalg@lepp.cornell.edu
2009-05-18
We present rules for determining the number of physical parameters in models with exact flavor symmetries. In such models the total number of parameters (physical and unphysical) needed to described a matrix is less than in a model without the symmetries. Several toy examples are studied in order to demonstrate the rules. The use of global symmetries in studying the minimally supersymmetric standard model (MSSM) is examined.
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...... method is based on a modified version of the EM algorithm. Experimental results for a deformable template used for textile inspection are presented...
Numerical modeling of piezoelectric transducers using physical parameters.
Cappon, Hans; Keesman, Karel J
2012-05-01
Design of ultrasonic equipment is frequently facilitated with numerical models. These numerical models, however, need a calibration step, because usually not all characteristics of the materials used are known. Characterization of material properties combined with numerical simulations and experimental data can be used to acquire valid estimates of the material parameters. In our design application, a finite element (FE) model of an ultrasonic particle separator, driven by an ultrasonic transducer in thickness mode, is required. A limited set of material parameters for the piezoelectric transducer were obtained from the manufacturer, thus preserving prior physical knowledge to a large extent. The remaining unknown parameters were estimated from impedance analysis with a simple experimental setup combined with a numerical optimization routine using 2-D and 3-D FE models. Thus, a full set of physically interpretable material parameters was obtained for our specific purpose. The approach provides adequate accuracy of the estimates of the material parameters, near 1%. These parameter estimates will subsequently be applied in future design simulations, without the need to go through an entire series of characterization experiments. Finally, a sensitivity study showed that small variations of 1% in the main parameters caused changes near 1% in the eigenfrequency, but changes up to 7% in the admittance peak, thus influencing the efficiency of the system. Temperature will already cause these small variations in response; thus, a frequency control unit is required when actually manufacturing an efficient ultrasonic separation system.
Lattice parameter variations during aging in nickel-base superalloys
Nathal, M. V.; Mackay, R. A.; Garlick, R. G.
1988-01-01
The importance of the state of coherency on measurements of gamma/gamma-prime lattice mismatch has been experimentally demonstrated during aging at 1000 C of specimens of an alloy with composition Ni-(8.6)Cr-(5.3)Al-(10.1)Co-(11.7)W-(1.2)Ti-(0.7)Mo (wt pct). Lattice parameter measurements are given as a function of aging time, and the corresponding sample microstructures are presented. The results show that changes of the two phases during aging did not influence the lattice parameter measurements, indicating that aging specimens to produce a semicoherent gamma/gamma-prime structure provides a good approximation of the true, unconstrained lattice mismatch.
Variation of equation of state parameters in the Mg2(Si 1-xSnx) alloys
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.
Narrow-track wheeled agricultural tractor parameter variation.
Guzzomi, A; Rondelli, V
2013-10-01
Despite a general consensus among farmers, manufacturers, and researchers that wheeled agricultural tractor design has changed over time, there is little published evidence. There is debate as to whether the standardized rollover protective structure (ROPS) energy and force requirements, based on a tractor reference mass and pertaining to studies conducted more than 40 years ago, are appropriate for modern tractors. This article investigated the physical parameters of 326 modern narrow-track tractors, measured according to OECD Code 6 over 16 years (1993 to 2008 inclusive): 252 (-77%) were fixed-chassis tractors and 74 (-23%) were articulated. To understand the significance of design changes, the data were analyzed with respect to time and as a function of tractor mass. Articulated and fixed-chassis data were treated separately. The time data allowed qualitative analysis, while the mass data allowed quantitative analysis. The parameters show some changes over time and clearly indicate differences between articulated and fixed-chassis types. The parameter changes, along with the differences between types, may have important safety ramifications for ROPS energy absorption requirements, and these aspects are discussed. Regression lines with R2 values were fitted to the mass-related data for fixed-chassis and articulated tractors to determine the suitability of fit. The mass relations also displayed differences between fixed-chassis and articulated tractors. Thus, the most significant recommendation from this study is that the standardized testing procedure for narrow-track wheeled agricultural tractor category should be split into two groups: fixed-chassis and articulated.
Trait Characteristics of Diffusion Model Parameters
Directory of Open Access Journals (Sweden)
Anna-Lena Schubert
2016-07-01
Full Text Available Cognitive modeling of response time distributions has seen a huge rise in popularity in individual differences research. In particular, several studies have shown that individual differences in the drift rate parameter of the diffusion model, which reflects the speed of information uptake, are substantially related to individual differences in intelligence. However, if diffusion model parameters are to reflect trait-like properties of cognitive processes, they have to qualify as trait-like variables themselves, i.e., they have to be stable across time and consistent over different situations. To assess their trait characteristics, we conducted a latent state-trait analysis of diffusion model parameters estimated from three response time tasks that 114 participants completed at two laboratory sessions eight months apart. Drift rate, boundary separation, and non-decision time parameters showed a great temporal stability over a period of eight months. However, the coefficients of consistency and reliability were only low to moderate and highest for drift rate parameters. These results show that the consistent variance of diffusion model parameters across tasks can be regarded as temporally stable ability parameters. Moreover, they illustrate the need for using broader batteries of response time tasks in future studies on the relationship between diffusion model parameters and intelligence.
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......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...
Models of Solar Irradiance Variations: Current Status
Indian Academy of Sciences (India)
Natalie A. Krivova; Sami K. Solanki
2008-03-01
Regular monitoring of solar irradiance has been carried out since 1978 to show that solar total and spectral irradiance varies at different time scales. Whereas variations on time scales of minutes to hours are due to solar oscillations and granulation, variations on longer time scales are driven by the evolution of the solar surface magnetic field. Here the most recent advances in modelling of solar irradiance variations on time scales longer than a day are briefly reviewed.
Parameter Estimation of Partial Differential Equation Models
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.
Application of lumped-parameter models
Energy Technology Data Exchange (ETDEWEB)
Ibsen, Lars Bo; Liingaard, M.
2006-12-15
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. Subsequently, the assembly of the dynamic stiffness matrix for the foundation is considered, and the solution for obtaining the steady state response, when using lumped-parameter models is given. (au)
Analysis of the variation of range parameters of thermal cameras
Bareła, Jarosław; Kastek, Mariusz; Firmanty, Krzysztof; Krupiński, Michał
2016-10-01
Measured range characteristics may vary considerably (up to several dozen percent) between different samples of the same camera type. The question is whether the manufacturing process somehow lacks repeatability or the commonly used measurement procedures themselves need improvement. The presented paper attempts to deal with the aforementioned question. The measurement method has been thoroughly analyzed as well as the measurement test bed. Camera components (such as detector and optics) have also been analyzed and their key parameters have been measured, including noise figures of the entire system. Laboratory measurements are the most precise method used to determine range parameters of a thermal camera. However, in order to obtain reliable results several important conditions have to be fulfilled. One must have the test equipment capable of measurement accuracy (uncertainty) significantly better than the magnitudes of measured quantities. The measurements must be performed in a controlled environment thus excluding the influence of varying environmental conditions. The personnel must be well-trained, experienced in testing the thermal imaging devices and familiar with the applied measurement procedures. The measurement data recorded for several dozen of cooled thermal cameras (from one of leading camera manufacturers) have been the basis of the presented analysis. The measurements were conducted in the accredited research laboratory of Institute of Optoelectronics (Military University of Technology).
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
Zakharova, O.; Hainzl, S.; Lange, D.; Enescu, B.
2017-01-01
Recent development in analysis tools and deployments of the geodetic and seismic instruments give an opportunity to investigate aftershock sequences at local scales, which is important for the seismic hazard assessment. In particular, we study the dependencies between aftershock sequences properties and deformational/geological data on a scale of the rupture extension of megathrust earthquakes. For this goal we use, on one hand, published models of inter-, co- and postseismic slip and geological information and, on the other hand, aftershock parameters, obtained by fitting a modified Epidemic Type Aftershock Sequence (ETAS) model. The altered ETAS model takes into account the mainshock rupture extension and it distinguishes between primary and the secondary aftershock triggering involved in the total seismicity rate. We estimate the Spearman correlation coefficients between the spatially distributed aftershock parameters estimated by the modified ETAS model and crustal physical properties for the Maule 2010 Mw8.8 and the Tohoku-oki 2011 Mw9.0 aftershock sequences. We find that: (1) modified ETAS model outperforms the classical one, when the mainshock rupture extension cannot be neglected and represented as a point source; (2) anomalous aftershock parameters occur in the areas of the reactivated fault systems; (3) aftershocks, regardless of their generation, tend to occur in the areas of high coseismic slip gradient, afterslip and interseismic coupling; (4) aftershock seismic moment releases preferentially in regions of large coseismic slip, coseismic slip gradient and interseismically locked areas; (5) b value tends to be smaller in interseismically locked regions.
Modeling of microscale variations in methane fluxes
Energy Technology Data Exchange (ETDEWEB)
Kettunen, A.
2002-07-01
The current study analyzes the different modes of variation in methane fluxes from different microsites of a boreal mire. The results emphasize the importance of microsite characteristics, water table and vegetation cover for methane fluxes. Water level affects the moisture and oxygen profiles in peat matrix which are reflected to methane production and oxidation rates and the corresponding microbial populations. Vascular plants promote methane production by providing substrates in the form of root exudates and fine root litter, enhance methane oxidation by transporting oxygen to water saturated peat layers and accelerate methane transport by liberating methane from peat to the atmosphere via the aerenchymous tissue. The model presented in this study connects the methane fluxes to the seasonal photosynthetic cycle of plants at the microsite level while the thermal and hydrological conditions in peat are used as an operational framework. Overall, the model dynamically combines the microbial processes in peat to changing environmental factors in the level of peatland ecosystem. Sensitivity analysis of the model reveals the importance of substrate supply to methane fluxes. Furthermore, the model outcome is sensitive to increased capability of the vascular plants to transport oxygen downwards. Lack of oxygen and partly methane keep methane oxidation at a very low level. Any changes in model parameters or environmental conditions that compensate for these lacks have a remarkable decreasing effect on simulated flux. Simulated methane flux decreases considerably if the duration of simulated dry period increases, threshold for a dramatic change lying between 4 and 6 weeks of drought. Increase in air temperature enhances methane flux especially if the effect of increased temperature on gross primary production is taken into account. (orig.)
Statefinder parameters in two dark energy models
Panotopoulos, Grigoris
2007-01-01
The statefinder parameters ($r,s$) in two dark energy models are studied. In the first, we discuss in four-dimensional General Relativity a two fluid model, in which dark energy and dark matter are allowed to interact with each other. In the second model, we consider the DGP brane model generalized by taking a possible energy exchange between the brane and the bulk into account. We determine the values of the statefinder parameters that correspond to the unique attractor of the system at hand. Furthermore, we produce plots in which we show $s,r$ as functions of red-shift, and the ($s-r$) plane for each model.
Parameter Symmetry of the Interacting Boson Model
Shirokov, A M; Smirnov, Yu F; Shirokov, Andrey M.; Smirnov, Yu. F.
1998-01-01
We discuss the symmetry of the parameter space of the interacting boson model (IBM). It is shown that for any set of the IBM Hamiltonian parameters (with the only exception of the U(5) dynamical symmetry limit) one can always find another set that generates the equivalent spectrum. We discuss the origin of the symmetry and its relevance for physical applications.
Modeling Per Capita State Health Expenditure Variat...
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...
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...
Setting Parameters for Biological Models With ANIMO
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
Delineating Parameter Unidentifiabilities in Complex Models
Raman, Dhruva V; Papachristodoulou, Antonis
2016-01-01
Scientists use mathematical modelling to understand and predict the properties of complex physical systems. In highly parameterised models there often exist relationships between parameters over which model predictions are identical, or nearly so. These are known as structural or practical unidentifiabilities, respectively. They are hard to diagnose and make reliable parameter estimation from data impossible. They furthermore imply the existence of an underlying model simplification. We describe a scalable method for detecting unidentifiabilities, and the functional relations defining them, for generic models. This allows for model simplification, and appreciation of which parameters (or functions thereof) cannot be estimated from data. Our algorithm can identify features such as redundant mechanisms and fast timescale subsystems, as well as the regimes in which such approximations are valid. We base our algorithm on a novel quantification of regional parametric sensitivity: multiscale sloppiness. Traditional...
A variational void coalescence model for ductile metals
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.
Coastal zone simulations with variational Boussinesq modelling
Adytia, Didit
2012-01-01
The main challenge in deriving a Boussinesq model for water wave is to model accurately the dispersion and nonlinearity of waves. The dispersion is a depth-dependent relation between the wave speed and the wavelength. A Boussinesq-type model can be derived from the so-called variational principle
Energy Technology Data Exchange (ETDEWEB)
William K. Terry; A. M. Ougouag; Farzad Rahnema; Michael Scott McKinley
2003-04-01
The well-known spatial variation of packing fraction near the outer boundary of a pebble-bed reactor core is cited. The ramifications of this variation are explored with the MCNP computer code. It is found that the variation has negligible effects on the global reactor physics parameters extracted from the MCNP calculations for use in analysis by diffusion-theory codes, but for local reaction rates the effects of the variation are naturally important. Included is some preliminary work in using first-order perturbation theory for estimating the effect of the spatial variation of packing fraction on the core eigenvalue and the fision density distribution.
Parameter Estimation, Model Reduction and Quantum Filtering
Chase, Bradley A
2009-01-01
This dissertation explores the topics of parameter estimation and model reduction in the context of quantum filtering. Chapters 2 and 3 provide a review of classical and quantum probability theory, stochastic calculus and filtering. Chapter 4 studies the problem of quantum parameter estimation and introduces the quantum particle filter as a practical computational method for parameter estimation via continuous measurement. Chapter 5 applies these techniques in magnetometry and studies the estimator's uncertainty scalings in a double-pass atomic magnetometer. Chapter 6 presents an efficient feedback controller for continuous-time quantum error correction. Chapter 7 presents an exact model of symmetric processes of collective qubit systems.
V. D. Rusov; Glushkov, A. V.; Vaschenko, V. N.; Pavlovich, V. N.; Zelentsova, T. N.; Mihalus, O. T.; Tarasov, V. A.; Saranuk, D. N.
2004-01-01
The energy-balance model of global climate, which is taking into account a nontrivial role of solar and galactic protons, is presented. The model is described by the equation of fold catastrophe relative to increment of temperature, where the variation of a solar insolation and cosmic rays are control parameters. It is shown that the bifurcation equation of the model describes one of two stable states of the climate system. The solution of this equation exhibits the property of the determined...
DEFF Research Database (Denmark)
Sennels, Henriette P; Jørgensen, Henrik L; Gøtze, Jens Peter;
2012-01-01
Purpose. To evaluate the influence of time of day on the circulating concentrations of 14 frequently used clinical biochemical parameters in the Bispebjerg study of diurnal variations. Materials and methods. Venous blood samples were obtained under controlled environmental, activities and food...
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.
Ermakova, Elena; Kotik, Dmitry; Bösinger, Tilmann
2016-07-01
The dynamics of the amplitude spectra and polarization parameter (epsilon)[1] of magnetic ULF noise were investigated during different seasons and high geomagnetic activity time using the data on the horizontal magnetic components monitoring at mid-latitude (New Life, Russia, 56 N, 46 E) and low-latitude stations (Crete, 35.15 N, 25.20 E). It was found that abrupt changes in the spectral polarization parameters can be linked as with variation of height of maximum and the electron density of the F-layer, and with a change in ionospheric parameters profiles at lower altitudes, for example, with the appearance of sporadic Es-layers and intermediate layers, located between the E and F-layers. It was detected the peculiarities in the daily dynamics of the epsilon parameter at low latitudes: a) the appearance in some cases more complicated than in the mid-latitudes, epsilon structure of the spectrum associated with the presence of two different values of the boundary frequency fB [2]; b) a decreasing of fB near local midnight observed in 70% of cases; c) observation of typical for dark time epsilon spectra after sunrise in the winter season. The numerical calculations of epsilon parameter were made using the IRI-2012 model with setting the models of sporadic and intermediate layers. The results revealed the dependence of the polarization spectra of the intensity and height of such thin layers. The specific changes in the electron density at altitudes of 80-350 km during the recovery phase of strong magnetic storms were defined basing on a comparative analysis of the experimental spectra and the results of the numerical calculations. References. 1. E. N. Ermakova, D. S. Kotik, A. V.Ryabov, A. V.Pershin, T. B.osinger, and Q. Zhou, Studying the variation of the broadband spectral maximum parameters in the natural ULF fields, Radiophysics and Quantum Electronics, Vol. 55, No. 10-11, March, 2013 p. 605-615. 2. T. Bosinger, A. G. Demekhov, E. N. Ermakova, C. Haldoupis and Q
Estimating von Bertalanffy parameters with individual and environmental variations in growth.
Shelton, Andrew O; Mangel, Marc
2012-01-01
Variation among individuals is an ubiquitous feature of natural populations. However, the relative roles of intrinsic individual differences and stochastic processes in generating variation remain poorly understood. For somatic growth, identifying the contribution of individual and stochastic processes to observed variation in size has important implications both for basic and applied biology. Here we propose and develop methods for estimating individual variation in growth using size-at-age data. We modify the von Bertalanffy growth model to explicitly incorporate individual, environmental, and stochastic variation and provide analytic expressions for the mean and variance of length-at-age in populations. We use a Bayesian statistical model to estimate individual variation from length-at-age data and apply the model to simulated data to test its efficacy. Although a first step towards understanding individual variation, we demonstrate that estimating individual variation from observational samples is possible and provide a platform for future analytical and statistical developments.
Delineating parameter unidentifiabilities in complex models
Raman, Dhruva V.; Anderson, James; Papachristodoulou, Antonis
2017-03-01
Scientists use mathematical modeling as a tool for understanding and predicting the properties of complex physical systems. In highly parametrized models there often exist relationships between parameters over which model predictions are identical, or nearly identical. These are known as structural or practical unidentifiabilities, respectively. They are hard to diagnose and make reliable parameter estimation from data impossible. They furthermore imply the existence of an underlying model simplification. We describe a scalable method for detecting unidentifiabilities, as well as the functional relations defining them, for generic models. This allows for model simplification, and appreciation of which parameters (or functions thereof) cannot be estimated from data. Our algorithm can identify features such as redundant mechanisms and fast time-scale subsystems, as well as the regimes in parameter space over which such approximations are valid. We base our algorithm on a quantification of regional parametric sensitivity that we call `multiscale sloppiness'. Traditionally, the link between parametric sensitivity and the conditioning of the parameter estimation problem is made locally, through the Fisher information matrix. This is valid in the regime of infinitesimal measurement uncertainty. We demonstrate the duality between multiscale sloppiness and the geometry of confidence regions surrounding parameter estimates made where measurement uncertainty is non-negligible. Further theoretical relationships are provided linking multiscale sloppiness to the likelihood-ratio test. From this, we show that a local sensitivity analysis (as typically done) is insufficient for determining the reliability of parameter estimation, even with simple (non)linear systems. Our algorithm can provide a tractable alternative. We finally apply our methods to a large-scale, benchmark systems biology model of necrosis factor (NF)-κ B , uncovering unidentifiabilities.
Systematic parameter inference in stochastic mesoscopic modeling
Lei, Huan; Yang, Xiu; Li, Zhen; Karniadakis, George Em
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.
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...
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)
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
Parameters in dynamic models of complex traits are containers of missing heritability.
Directory of Open Access Journals (Sweden)
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.
On the total variation dictionary model.
Zeng, Tieyong; Ng, Michael K
2010-03-01
The goal of this paper is to provide a theoretical study of a total variation (TV) dictionary model. Based on the properties of convex analysis and bounded variation functions, the existence of solutions of the TV dictionary model is proved. We then show that the dual form of the model can be given by the minimization of the sum of the l(1) -norm of the dual solution and the Bregman distance between the curvature of the primal solution and the subdifferential of TV norm of the dual solution. This theoretical result suggests that the dictionary must represent sparsely the curvatures of solution image in order to obtain a better denoising performance.
Identification of slow molecular order parameters for Markov model construction
Perez-Hernandez, Guillermo; Giorgino, Toni; de Fabritiis, Gianni; Noé, Frank
2013-01-01
A goal in the kinetic characterization of a macromolecular system is the description of its slow relaxation processes, involving (i) identification of the structural changes involved in these processes, and (ii) estimation of the rates or timescales at which these slow processes occur. Most of the approaches to this task, including Markov models, Master-equation models, and kinetic network models, start by discretizing the high-dimensional state space and then characterize relaxation processes in terms of the eigenvectors and eigenvalues of a discrete transition matrix. The practical success of such an approach depends very much on the ability to finely discretize the slow order parameters. How can this task be achieved in a high-dimensional configuration space without relying on subjective guesses of the slow order parameters? In this paper, we use the variational principle of conformation dynamics to derive an optimal way of identifying the "slow subspace" of a large set of prior order parameters - either g...
Capturing Appearance Variation in Active Appearance Models
Van der Maaten, L.J.P.; Hendriks, E.A.
2010-01-01
The paper presents an extension of active appearance models (AAMs) that is better capable of dealing with the large variation in face appearance that is encountered in large multi-person face data sets. Instead of the traditional PCA-based texture model, our extended AAM employs a mixture of probabi
Variation ranges of motion parameters for space debris in the geosynchronous ring
Zhao, Chang-Yin; Zhang, Ming-Jiang; Yu, Sheng-Xian; Xiong, Jian-Ning; Zhang, Wei; Zhu, Ting-Lei
2016-06-01
We propose a method that uses only one set of known orbital elements to directly determine the motion state and variation ranges of motion parameters, including the inclination, right ascension of the ascending node (RAAN), evolution period of the orbital plane, maximum libration amplitude of the semi-major axis, commensurable angle, libration period and drift period, for space debris in the geosynchronous ring. These variation ranges of motion parameters characterize the evolution of debris quantitatively and illustrate the three-dimensional (3D) variations. Employing the proposed method, we study the motion state and variation ranges of motion parameters for catalogued and uncontrolled space debris with existing two-line element (TLE) data in the geosynchronous ring, and present specific results. We also compare our results with actual observational results derived from long-term TLE historical data, and find that, in the vast majority of cases, our proposed method of determining the motion state and variation ranges of motion parameters via only one set of known orbital elements is effective. In addition, before the elaboration of the variation ranges of motion parameters stated above, we obtain the statistical distribution of space debris in the orbital plane and the daily motion from the TLE historical data. We then derive two mathematical formulae that explain the statistical distribution and daily motion on the basis of the essence of dynamics, which contributes to the characterization of the evolution of debris.
Parameter estimation and model selection in computational biology.
Directory of Open Access Journals (Sweden)
Gabriele Lillacci
2010-03-01
Full Text Available A central challenge in computational modeling of biological systems is the determination of the model parameters. Typically, only a fraction of the parameters (such as kinetic rate constants are experimentally measured, while the rest are often fitted. The fitting process is usually based on experimental time course measurements of observables, which are used to assign parameter values that minimize some measure of the error between these measurements and the corresponding model prediction. The measurements, which can come from immunoblotting assays, fluorescent markers, etc., tend to be very noisy and taken at a limited number of time points. In this work we present a new approach to the problem of parameter selection of biological models. We show how one can use a dynamic recursive estimator, known as extended Kalman filter, to arrive at estimates of the model parameters. The proposed method follows. First, we use a variation of the Kalman filter that is particularly well suited to biological applications to obtain a first guess for the unknown parameters. Secondly, we employ an a posteriori identifiability test to check the reliability of the estimates. Finally, we solve an optimization problem to refine the first guess in case it should not be accurate enough. The final estimates are guaranteed to be statistically consistent with the measurements. Furthermore, we show how the same tools can be used to discriminate among alternate models of the same biological process. We demonstrate these ideas by applying our methods to two examples, namely a model of the heat shock response in E. coli, and a model of a synthetic gene regulation system. The methods presented are quite general and may be applied to a wide class of biological systems where noisy measurements are used for parameter estimation or model selection.
Estimation of Model Parameters for Steerable Needles
Park, Wooram; Reed, Kyle B.; Okamura, Allison M.; Chirikjian, Gregory S.
2010-01-01
Flexible needles with bevel tips are being developed as useful tools for minimally invasive surgery and percutaneous therapy. When such a needle is inserted into soft tissue, it bends due to the asymmetric geometry of the bevel tip. This insertion with bending is not completely repeatable. We characterize the deviations in needle tip pose (position and orientation) by performing repeated needle insertions into artificial tissue. The base of the needle is pushed at a constant speed without rotating, and the covariance of the distribution of the needle tip pose is computed from experimental data. We develop the closed-form equations to describe how the covariance varies with different model parameters. We estimate the model parameters by matching the closed-form covariance and the experimentally obtained covariance. In this work, we use a needle model modified from a previously developed model with two noise parameters. The modified needle model uses three noise parameters to better capture the stochastic behavior of the needle insertion. The modified needle model provides an improvement of the covariance error from 26.1% to 6.55%. PMID:21643451
Estimation of Model Parameters for Steerable Needles.
Park, Wooram; Reed, Kyle B; Okamura, Allison M; Chirikjian, Gregory S
2010-01-01
Flexible needles with bevel tips are being developed as useful tools for minimally invasive surgery and percutaneous therapy. When such a needle is inserted into soft tissue, it bends due to the asymmetric geometry of the bevel tip. This insertion with bending is not completely repeatable. We characterize the deviations in needle tip pose (position and orientation) by performing repeated needle insertions into artificial tissue. The base of the needle is pushed at a constant speed without rotating, and the covariance of the distribution of the needle tip pose is computed from experimental data. We develop the closed-form equations to describe how the covariance varies with different model parameters. We estimate the model parameters by matching the closed-form covariance and the experimentally obtained covariance. In this work, we use a needle model modified from a previously developed model with two noise parameters. The modified needle model uses three noise parameters to better capture the stochastic behavior of the needle insertion. The modified needle model provides an improvement of the covariance error from 26.1% to 6.55%.
An Optimization Model of Tunnel Support Parameters
Directory of Open Access Journals (Sweden)
Su Lijuan
2015-05-01
Full Text Available An optimization model was developed to obtain the ideal values of the primary support parameters of tunnels, which are wide-ranging in high-speed railway design codes when the surrounding rocks are at the III, IV, and V levels. First, several sets of experiments were designed and simulated using the FLAC3D software under an orthogonal experimental design. Six factors, namely, level of surrounding rock, buried depth of tunnel, lateral pressure coefficient, anchor spacing, anchor length, and shotcrete thickness, were considered. Second, a regression equation was generated by conducting a multiple linear regression analysis following the analysis of the simulation results. Finally, the optimization model of support parameters was obtained by solving the regression equation using the least squares method. In practical projects, the optimized values of support parameters could be obtained by integrating known parameters into the proposed model. In this work, the proposed model was verified on the basis of the Liuyang River Tunnel Project. Results show that the optimization model significantly reduces related costs. The proposed model can also be used as a reliable reference for other high-speed railway tunnels.
2013-08-01
saturation effects is cal- culated by substituting (6) and (7) into (1)-(5). After some algebraic manipulation, the modified machine model is given...2012. [10] T. Herold, D. Franck, E. Lange and K. Hameyer, “Extension of a d-q Model of a Permanent Magnet Excited Synchronous Machine by including
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.
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.
Intelligent Controller Design for Quad-Rotor Stabilization in Presence of Parameter Variations
Directory of Open Access Journals (Sweden)
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.
A variational approach for dissipative quantum transport in a wide parameter space
Energy Technology Data Exchange (ETDEWEB)
Zhang, Yu, E-mail: zhy@yangtze.hku.hk; Kwok, YanHo; Chen, GuanHua, E-mail: ghc@everest.hku.hk [Department of Chemistry, The University of Hong Kong, Pokfluam Road (Hong Kong); Yam, ChiYung [Department of Chemistry, The University of Hong Kong, Pokfluam Road (Hong Kong); Beijing Computational Science Research Center, Beijing 100094 (China)
2015-09-14
Recent development of theoretical method for dissipative quantum transport has achieved notable progresses in the weak or strong electron-phonon coupling regime. However, a generalized theory for dissipative quantum transport in a wide parameter space had not been established. In this work, a variational polaron theory for dissipative quantum transport in a wide range of electron-phonon coupling is developed. The optimal polaron transformation is determined by the optimization of the Feynman-Bogoliubov upper bound of free energy. The free energy minimization ends up with an optimal mean-field Hamiltonian and a minimal interaction Hamiltonian. Hence, second-order perturbation can be applied to the transformed system, resulting in an accurate and efficient method for the treatment of dissipative quantum transport with different electron-phonon coupling strength. Numerical benchmark calculation on a single site model coupled to one phonon mode is presented.
A variational approach for dissipative quantum transport in a wide parameter space.
Zhang, Yu; Yam, ChiYung; Chen, GuanHua
2015-09-14
Recent development of theoretical method for dissipative quantum transport has achieved notable progresses in the weak or strong electron-phonon coupling regime. However, a generalized theory for dissipative quantum transport in a wide parameter space had not been established. In this work, a variational polaron theory for dissipative quantum transport in a wide range of electron-phonon coupling is developed. The optimal polaron transformation is determined by the optimization of the Feynman-Bogoliubov upper bound of free energy. The free energy minimization ends up with an optimal mean-field Hamiltonian and a minimal interaction Hamiltonian. Hence, second-order perturbation can be applied to the transformed system, resulting in an accurate and efficient method for the treatment of dissipative quantum transport with different electron-phonon coupling strength. Numerical benchmark calculation on a single site model coupled to one phonon mode is presented.
Directory of Open Access Journals (Sweden)
Patarawan Sangnawakij
2017-02-01
Full Text Available The problem of estimating parameters in a gamma distribution has been widely studied with respect to both theories and applications. In special cases, when the parameter space is bounded, the construction of the confidence interval based on the classical Neyman procedure is unsatisfactory because the information regarding the restriction of the parameter is disregarded. In order to develop the estimator for this issue, the confidence intervals for the coefficient of variation for the case of a gamma distribution were proposed. Extending to two populations, the confidence intervals for the difference and the ratio of coefficients of variation with restricted parameters were presented. Monte Carlo simulations were used to investigate the performance of the proposed estimators. The results showed that the proposed confidence intervals performed better than the compared estimators in terms of expected length, especially when the coefficients of variation were close to the boundary. Additionally, two examples using real data were analyzed to illustrate the findings of the paper.
Energy Technology Data Exchange (ETDEWEB)
Meghna, K.K. [INO Graduate Training Programme and Saha Institute of Nuclear Physics, Kolkata 700064 (India); Homi Bhabha National Institute, Mumbai 400085 (India); Biswas, S. [School of Physical Sciences, National Institute of Science Education and Research, Bhubaneswar 751005 (India); Jash, A. [INO Graduate Training Programme and Saha Institute of Nuclear Physics, Kolkata 700064 (India); Homi Bhabha National Institute, Mumbai 400085 (India); Chattopadhyay, S. [Variable Energy Cyclotron Centre, Kolkata 700064 (India); Homi Bhabha National Institute, Mumbai 400085 (India); Saha, S., E-mail: satyajit.saha@saha.ac.in [Applied Nuclear Physics Division, Saha Institute of Nuclear Physics, Kolkata 700064 (India); Homi Bhabha National Institute, Mumbai 400085 (India)
2016-04-21
Performance of single gap Resistive Plate Chamber (RPC) detectors is investigated under variation of environmental parameters, such as temperature and relative humidity. Operational characteristics of the RPCs depend on both the environmental temperature and the relative humidity. Sensitivity to such dependence is found to be more on temperature rather than the relative humidity. Qualitative interpretation of some of the results obtained is given based on the known properties of the electrode materials and gases used in the detectors. - Highlights: • Performance of single gap bakelite Resistive Plate Chamber (RPC) detectors is investigated under independent variation of environmental temperature and relative humidity. • Parameters such as leakage currents, noise rates, efficiency and timing characteristics of RPCs are investigated. • Operational characteristics of the RPCs depend on both the environmental temperature and the relative humidity. • Sensitivity of the operational parameters to variation of environmental parameters is found to be more on temperature rather than the relative humidity.
Modeling the variation trends of glacier systems
Directory of Open Access Journals (Sweden)
Z. Xie
2013-01-01
Full Text Available The basic principles and methods for a functional glacier systems model are introduced and applied for glaciers of Northwest China. When running the model we assume that a glacier system is under steady state conditions in the initial year. The median size of a glacier system is used as representative for the system. The curve of glacier area distribution against elevation is used to compute the increase in equilibrium line altitude (ELA, and the annual glacier ablation is calculated using a global formula a = 1.33(9.66 + ts².⁸⁵ [4, p. 96]. The net mass balance near the ELA under steady state conditions represents the net mass balance of the whole glacier system, and the time required for glacier runoff to return to the initial year level is calculated according to the law of glacier runoff variation, and used to calculate the variation of glacier area. The variation of glacier runoff is modeled according to ablation at the ELA, and the variation of glacier volume is modeled according to the absolute value of the mass balance. The observed changes in surveyed glaciers in China over recent decades were broadly consistent with predictions of the glacier system model. The model therefore offers a reliable method for the prediction of changes in glacier systems in response to changing climate.
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.
The Impact of Gate-Driver Parameters Variation and Device Degradation in the PV-Inverter Lifetime
DEFF Research Database (Denmark)
Sintamarean, Nicolae Cristian; Wang, Huai; Blaabjerg, Frede;
2014-01-01
This paper introduces a reliability-oriented design tool for a new generation of grid connected PV-inverters. The proposed design tool consists of a real field Mission Profile (MP) model (for one year operation in USA-Arizona), a PV-panel model, a grid connected PV-inverter model, an Electro......-Thermal model and the lifetime model of the power semiconductor devices. A simulation model able to consider a one year real field operation conditions (solar irradiance and ambient temperature) is developed. Thus, one year estimation of the converter devices thermal loading distribution is achieved...... and is further used as an input to a lifetime model. The proposed reliability oriented design tool is used to study the impact of MP-variation, Gate-Driver (GD) parameters variation and device degradation in the PVinverter lifetime. The obtained results indicate that in order to improve the accuracy...
The Impact of Gate-Driver Parameters Variation and Device Degradation in the PV-Inverter Lifetime
DEFF Research Database (Denmark)
Sintamarean, Nicolae Cristian; Wang, Huai; Blaabjerg, Frede
2014-01-01
This paper introduces a reliability-oriented design tool for a new generation of grid connected PV-inverters. The proposed design tool consists of a real field Mission Profile (MP) model (for one year operation in USA-Arizona), a PV-panel model, a grid connected PV-inverter model, an Electro......-Thermal model and the lifetime model of the power semiconductor devices. A simulation model able to consider a one year real field operation conditions (solar irradiance and ambient temperature) is developed. Thus, one year estimation of the converter devices thermal loading distribution is achieved...... and is further used as an input to a lifetime model. The proposed reliability oriented design tool is used to study the impact of MP-variation, Gate-Driver (GD) parameters variation and device degradation in the PVinverter lifetime. The obtained results indicate that in order to improve the accuracy...
The Lund Model at Nonzero Impact Parameter
Janik, R A; Janik, Romuald A.; Peschanski, Robi
2003-01-01
We extend the formulation of the longitudinal 1+1 dimensional Lund model to nonzero impact parameter using the minimal area assumption. Complete formulae for the string breaking probability and the momenta of the produced mesons are derived using the string worldsheet Minkowskian helicoid geometry. For strings stretched into the transverse dimension, we find probability distribution with slope linear in m_T similar to the statistical models but without any thermalization assumptions.
IMPROVEMENT OF FLUID PIPE LUMPED PARAMETER MODEL
Institute of Scientific and Technical Information of China (English)
Kong Xiaowu; Wei Jianhua; Qiu Minxiu; Wu Genmao
2004-01-01
The traditional lumped parameter model of fluid pipe is introduced and its drawbacks are pointed out.Furthermore, two suggestions are put forward to remove these drawbacks.Firstly, the structure of equivalent circuit is modified, and then the evaluation of equivalent fluid resistance is change to take the frequency-dependent friction into account.Both simulation and experiment prove that this model is precise to characterize the dynamic behaviors of fluid in pipe.
Ultrasonic-assisted manufacturing processes: Variational model and numerical simulations
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.
Ultrasonic-assisted manufacturing processes: variational model and numerical simulations.
Siddiq, Amir; El Sayed, Tamer
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. Copyright © 2011 Elsevier B.V. All rights reserved.
Insights into pre-reversal paleosecular variation from stochastic models
Peqini, Klaudio; Duka, Bejo; De Santis, Angelo
2015-09-01
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.
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.
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...... velocity, and water level is presented. The stochastic model includes statistical uncertainty and dependency between the four stochastic variables. Further, a new stochastic model for annual maximum directional significant wave heights is presented. The model includes dependency between the maximum wave...... height from neighboring directional sectors. Numerical examples are presented where the models are calibrated using the Maximum Likelihood method to data from the central part of the North Sea. The calibration of the directional distributions is made such that the stochastic model for the omnidirectional...
2013-08-22
Shaft Surface PMSM Interior PMSM UNCLASSIFIED UNCLASSIFIED Three phase model 22 August 2013 abM ...transformation matrix: • To transform from 3 phase abc to 3 equivalent axes dq0: • Under balanced condition zero sequence quantities are...d qi i * *,d qi i regulator PI * *,d qv v Inverse Park’s * abcvabc dq dq abc DYNAMOMETER OR ENGINE Controller UNCLASSIFIED UNCLASSIFIED
Directory of Open Access Journals (Sweden)
Borchevkina Olga
2016-01-01
Full Text Available The paper presents observations of atmospheric and ionospheric parameters during strong meteorological disturbances (storms in the Kaliningrad region. The analysis of ionospheric observations has shown that during meteorological storms the amplitude of diurnal variations in TEC decreases to 50 %; and in foF2, to 15 % as compared to quiet days. The revealed changes in ionospheric conditions during meteorological storms are regularly registered and represent a characteristic feature of the meteorological effect on the ionosphere. Modeling studies of the vertical propagation of AGW from the Earth’s surface showed that such waves quickly (within ~15 min reach altitudes of the upper atmosphere (~300 km. The refraction and dissipation of waves in the upper atmosphere produces perturbations of the background state of the atmosphere and gives rise to the waveguide propagation of infrasonic wave components. The observed manifestations of TEC disturbances caused by AGW propagating from the lower atmosphere can be explained by the diurnal variation of the altitude of the ionosphere and the waveguide propagation of infrasonic waves.
Improvement of Continuous Hydrologic Models and HMS SMA Parameters Reduction
Rezaeian Zadeh, Mehdi; Zia Hosseinipour, E.; Abghari, Hirad; Nikian, Ashkan; Shaeri Karimi, Sara; Moradzadeh Azar, Foad
2010-05-01
Hydrological models can help us to predict stream flows and associated runoff volumes of rainfall events within a watershed. There are many different reasons why we need to model the rainfall-runoff processes of for a watershed. However, the main reason is the limitation of hydrological measurement techniques and the costs of data collection at a fine scale. Generally, we are not able to measure all that we would like to know about a given hydrological systems. This is very particularly the case for ungauged catchments. Since the ultimate aim of prediction using models is to improve decision-making about a hydrological problem, therefore, having a robust and efficient modeling tool becomes an important factor. Among several hydrologic modeling approaches, continuous simulation has the best predictions because it can model dry and wet conditions during a long-term period. Continuous hydrologic models, unlike event based models, account for a watershed's soil moisture balance over a long-term period and are suitable for simulating daily, monthly, and seasonal streamflows. In this paper, we describe a soil moisture accounting (SMA) algorithm added to the hydrologic modeling system (HEC-HMS) computer program. As is well known in the hydrologic modeling community one of the ways for improving a model utility is the reduction of input parameters. The enhanced model developed in this study is applied to Khosrow Shirin Watershed, located in the north-west part of Fars Province in Iran, a data limited watershed. The HMS SMA algorithm divides the potential path of rainfall onto a watershed into five zones. The results showed that the output of HMS SMA is insensitive with the variation of many parameters such as soil storage and soil percolation rate. The study's objective is to remove insensitive parameters from the model input using Multi-objective sensitivity analysis. Keywords: Continuous Hydrologic Modeling, HMS SMA, Multi-objective sensitivity analysis, SMA Parameters
Modeling the climatic response to orbital variations.
Imbrie, J; Imbrie, J Z
1980-02-29
According to the astronomical theory of climate, variations in the earth's orbit are the fundamental cause of the succession of Pleistocene ice ages. This article summarizes how the theory has evolved since the pioneer studies of James Croll and Milutin Milankovitch, reviews recent evidence that supports the theory, and argues that a major opportunity is at hand to investigate the physical mechanisms by which the climate system responds to orbital forcing. After a survey of the kinds of models that have been applied to this problem, a strategy is suggested for building simple, physically motivated models, and a time-dependent model is developed that simulates the history of planetary glaciation for the past 500,000 years. Ignoring anthropogenic and other possible sources of variation acting at frequencies higher than one cycle per 19,000 years, this model predicts that the long-term cooling trend which began some 6000 years ago will continue for the next 23,000 years.
Gutzwiller variational theory for the Hubbard model with attractive interaction.
Bünemann, Jörg; Gebhard, Florian; Radnóczi, Katalin; Fazekas, Patrik
2005-06-29
We investigate the electronic and superconducting properties of a negative-U Hubbard model. For this purpose we evaluate a recently introduced variational theory based on Gutzwiller-correlated BCS wavefunctions. We find significant differences between our approach and standard BCS theory, especially for the superconducting gap. For small values of |U|, we derive analytical expressions for the order parameter and the superconducting gap which we compare to exact results from perturbation theory.
Institute of Scientific and Technical Information of China (English)
陈水宣; 邹俊; 谢丹
2012-01-01
The heat transfer of steels in laminar cooling process of hot strip mill was analyzed and partial differential models were proposed with boundary conditions of thermal radiation and cooling water convective equations.Based on the functional variation principle,the models were solved and node temperature on discrete time was obtained.To further enhance the temperature model calculation precision,thermal material properties including density,specific heat capacity and thermal conductivity were experimentally measured in Baosteel Gleeble thermal simulation equipment for three different carbon steels and the method of least squares was used to statistically derive regression models for the properties.Furthermore,the heat transfer coefficients of water and air cooling were reversely calculated and optimized based on actual measured temperature to meet the long-term stability of the application of the models.The numerical simulation and experimental results show that the setup accuracy of temperature prediction system of ROT was effectively improved.%分析板材在层冷过程中的传热,建立以热辐射和冷却水对流换热方程为边界条件的偏微分热传导模型,并基于泛函变分原理进行离散求解,获得各离散时间节点上的温度。为进一步提高该温度模型计算精度,在宝钢Gleeble热模拟实验机上测定3种碳钢样本的密度、比热容和热导率等热物性参数随温度变化的函数关系,采用最小二乘法建立回归模型,线性插值后用于温度场定量计算。此外,采用层冷实测温度反算和优化水冷、空冷换热系数,以满足模型现场长期应用的稳定性要求。结果表明,改造后层冷温度设定系统的精度能较准确地反映板材在层冷过程的温度变化,温度模型计算值与实测值吻合良好。
Order Parameters of the Dilute A Models
Warnaar, S O; Seaton, K A; Nienhuis, B
1993-01-01
The free energy and local height probabilities of the dilute A models with broken $\\Integer_2$ symmetry are calculated analytically using inversion and corner transfer matrix methods. These models possess four critical branches. The first two branches provide new realisations of the unitary minimal series and the other two branches give a direct product of this series with an Ising model. We identify the integrable perturbations which move the dilute A models away from the critical limit. Generalised order parameters are defined and their critical exponents extracted. The associated conformal weights are found to occur on the diagonal of the relevant Kac table. In an appropriate regime the dilute A$_3$ model lies in the universality class of the Ising model in a magnetic field. In this case we obtain the magnetic exponent $\\delta=15$ directly, without the use of scaling relations.
Testing Linear Models for Ability Parameters in Item Response Models
Glas, Cees A.W.; Hendrawan, Irene
2005-01-01
Methods for testing hypotheses concerning the regression parameters in linear models for the latent person parameters in item response models are presented. Three tests are outlined: A likelihood ratio test, a Lagrange multiplier test and a Wald test. The tests are derived in a marginal maximum like
Geomagnetic Core Field Secular Variation Models
DEFF Research Database (Denmark)
Gillet, N.; Lesur, V.; Olsen, Nils
2010-01-01
We analyse models describing time changes of the Earth’s core magnetic field (secular variation) covering the historical period (several centuries) and the more recent satellite era (previous decade), and we illustrate how both the information contained in the data and the a priori information...... highlight the difficulty of resolving the time variability of the high degree secular variation coefficients (i.e. the secular acceleration), arising for instance from the challenge to properly separate sources of internal and of external origin. In addition, the regularisation process may also result...
Directory of Open Access Journals (Sweden)
Gang Lin
2015-01-01
Full Text Available Epidemiological studies around the world have reported that fine particulate matter (PM2.5 is closely associated with human health. The distribution of PM2.5 concentrations is influenced by multiple geographic and socioeconomic factors. Using a remote-sensing-derived PM2.5 dataset, this paper explores the relationship between PM2.5 concentrations and meteorological parameters and their spatial variance in China for the period 2001–2010. The spatial variations of the relationships between the annual average PM2.5, the annual average precipitation (AAP, and the annual average temperature (AAT were evaluated using the Geographically Weighted Regression (GWR model. The results indicated that PM2.5 had a strong and stable correlation with meteorological parameters. In particular, PM2.5 had a negative correlation with precipitation and a positive correlation with temperature. In addition, the relationship between the variables changed over space, and the strong negative correlation between PM2.5 and the AAP mainly appeared in the warm temperate semihumid region and northern subtropical humid region in 2001 and 2010, with some localized differences. The strong positive correlation between the PM2.5 and the AAT mainly occurred in the mid-temperate semiarid region, the humid, semihumid, and semiarid warm temperate regions, and the northern subtropical humid region in 2001 and 2010.
Toghi Eshghi, Amin; Lee, Soobum; Lee, Hanmin; Kim, Young-Cheol
2016-04-01
In this paper, we perform design parameter study and design optimization for a piezoelectric energy harvester considering vehicle speed variation. Initially, a FEM model using ANSYS is developed to appraise the performance of a piezoelectric harvester in a rotating tire. The energy harvester proposed here uses the vertical deformation at contact patch area from the car weight and centrifugal acceleration. This harvester is composed of a beam which is clamped at both ends and a piezoelectric material is attached on the top of that. The piezoelectric material possesses the 31 mode of transduction in which the direction of applied field is perpendicular to that of the electric field. To optimize the harvester performance, we would change the geometrical parameters of the harvester to obtain the maximum power. One of the main challenges in the design process is obtaining the required power while considering the constraints for harvester weight and volume. These two concerns are addressed in this paper. Since the final goal of this study is the development of an energy harvester with a wireless sensor system installed in a real car, the real time data for varied velocity of a vehicle are taken into account for power measurements. This study concludes that the proposed design is applicable to wireless tire sensor systems.
Storm surge model based on variational data assimilation method
Institute of Scientific and Technical Information of China (English)
Shi-li HUANG; Jian XU; De-guan WANG; Dong-yan LU
2010-01-01
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.
Modelling spin Hamiltonian parameters of molecular nanomagnets.
Gupta, Tulika; Rajaraman, Gopalan
2016-07-12
Molecular nanomagnets encompass a wide range of coordination complexes possessing several potential applications. A formidable challenge in realizing these potential applications lies in controlling the magnetic properties of these clusters. Microscopic spin Hamiltonian (SH) parameters describe the magnetic properties of these clusters, and viable ways to control these SH parameters are highly desirable. Computational tools play a proactive role in this area, where SH parameters such as isotropic exchange interaction (J), anisotropic exchange interaction (Jx, Jy, Jz), double exchange interaction (B), zero-field splitting parameters (D, E) and g-tensors can be computed reliably using X-ray structures. In this feature article, we have attempted to provide a holistic view of the modelling of these SH parameters of molecular magnets. The determination of J includes various class of molecules, from di- and polynuclear Mn complexes to the {3d-Gd}, {Gd-Gd} and {Gd-2p} class of complexes. The estimation of anisotropic exchange coupling includes the exchange between an isotropic metal ion and an orbitally degenerate 3d/4d/5d metal ion. The double-exchange section contains some illustrative examples of mixed valance systems, and the section on the estimation of zfs parameters covers some mononuclear transition metal complexes possessing very large axial zfs parameters. The section on the computation of g-anisotropy exclusively covers studies on mononuclear Dy(III) and Er(III) single-ion magnets. The examples depicted in this article clearly illustrate that computational tools not only aid in interpreting and rationalizing the observed magnetic properties but possess the potential to predict new generation MNMs.
Model of light variations of Be stars
Energy Technology Data Exchange (ETDEWEB)
Stepinski, T. (Polska Akademia Nauk, Warsaw. Centrum Astronomiczne)
1980-01-01
The following model of Be star is proposed: a star rotating rigidly with a ''break up'' velocity is surrounded with a flat, geometrically thin, optically thick gaseous disk rotating with a Keplerian velocity. The disk absorbs and reemits stellar light. Viscous heat dissipation in the disk is neglected. The emerging spectrum of the system is calculated in black body approximation with temperature being a function of a position on the star and on the disk. Variation of the inner and outer disk radii may give rise to monochromatic light variations of the whole system in the range of 0.1-0.7 magnitudes. The light variations observed in Be stars are in the same range.
Variational modelling of nonlinear water waves
Kalogirou, Anna; Bokhove, Onno
2015-11-01
Mathematical modelling of water waves is demonstrated by investigating variational methods. A potential flow water wave model is derived using variational techniques and extented to include explicit time-dependence, leading to non-autonomous dynamics. As a first example, we consider the problem of a soliton splash in a long wave channel with a contraction at its end, resulting after a sluice gate is removed at a finite time. The removal of the sluice gate is included in the variational principle through a time-dependent gravitational potential. A second example involving non-autonomous dynamics concerns the motion of a free surface in a vertical Hele-Shaw cell. Explicit time-dependence now enters the model through a linear damping term due to the effect of wall friction and a term representing the motion of an artificially driven wave pump. In both cases, the model is solved numerically using a Galerkin FEM and the numerical results are compared to wave structures observed in experiments. The water wave model is also adapted to accommodate nonlinear ship dynamics. The novelty is this case is the coupling between the water wave dynamics, the ship dynamics and water line dynamics on the ship. For simplicity, we consider a simple ship structure consisting of V-shaped cross-sections.
Variational Bayes for Regime-Switching Log-Normal Models
Directory of Open Access Journals (Sweden)
Hui Zhao
2014-07-01
Full Text Available The power of projection using divergence functions is a major theme in information geometry. One version of this is the variational Bayes (VB method. This paper looks at VB in the context of other projection-based methods in information geometry. It also describes how to apply VB to the regime-switching log-normal model and how it provides a computationally fast solution to quantify the uncertainty in the model specification. The results show that the method can recover exactly the model structure, gives the reasonable point estimates and is very computationally efficient. The potential problems of the method in quantifying the parameter uncertainty are discussed.
Systematic parameter inference in stochastic mesoscopic modeling
Lei, Huan; Li, Zhen; Karniadakis, George
2016-01-01
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....
A Variational Bayes Approach to the Analysis of Occupancy Models.
Directory of Open Access Journals (Sweden)
Allan E Clark
Full Text Available Detection-nondetection data are often used to investigate species range dynamics using Bayesian occupancy models which rely on the use of Markov chain Monte Carlo (MCMC methods to sample from the posterior distribution of the parameters of the model. In this article we develop two Variational Bayes (VB approximations to the posterior distribution of the parameters of a single-season site occupancy model which uses logistic link functions to model the probability of species occurrence at sites and of species detection probabilities. This task is accomplished through the development of iterative algorithms that do not use MCMC methods. Simulations and small practical examples demonstrate the effectiveness of the proposed technique. We specifically show that (under certain circumstances the variational distributions can provide accurate approximations to the true posterior distributions of the parameters of the model when the number of visits per site (K are as low as three and that the accuracy of the approximations improves as K increases. We also show that the methodology can be used to obtain the posterior distribution of the predictive distribution of the proportion of sites occupied (PAO.
Modelling tourists arrival using time varying parameter
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.
Variational multiscale models for charge transport.
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
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.
Variation in selected hematological parameters of captive red-tailed hawks.
Rehder, N B; Bird, D M; Laguë, P C; Mackay, C
1982-01-01
Diurnal and winter variations of four hematological parameters were examined in 10 red-tailed hawks (Buteo jamaicensis). The mean values obtained were: 39.4% packed cell volume (PCV); 2.45 X 10(6) erythrocytes (RBC) per mm3 of blood; 5.73 mg of calcium and 1.44 mg of magnesium per 100 ml of plasma. Only the PCV and RBC count showed significant diurnal variation. When the birds were sampled at a set time of day, from November through to February, no significant changes were detected in any of the four parameters. Variation among the birds in RBC count, PCV and calcium concentration was significant on a diurnal basis but over the four month period only the PCV varied significantly.
Parameter-invariant second-order variational problems in one variable
Muñoz Masqué, J.; Pozo Coronado, L. M.
1998-07-01
A projection is defined such that a second-order Lagrangian density factors through this projection modulo contact forms if and only if it is parameter invariant. In this way, a geometric interpretation of the parameter invariance conditions is obtained. The above projection is then used to prove the strict factorization of the Poincaré-Cartan form attached to a parameter-invariant variational problem thus leading us to state the Hamilton-Cartan formalism, the complete description of symmetries and regularity for such problems. The case of the squared curvature Lagrangian in the plane is analysed especially.
Araghy, Homaira P.; Peterson, Byron J.; Hayashi, Hiromi; Konoshima, Shigeru; Ashikawa, Naoko; Seo, Dongcheol; JT-60U Team
We obtained the local foil properties of the JT-60U imaging bolometer foil (a single graphite-coated gold foil with an effective area of 9 × 7 cm2 and a nominal thickness of 2.5 μm) such as the thermal diffusivity, κ, and the product of the thermal conductivity, k, and the thickness, tf , by calibrating some parts of the foil. Calibration of the foil was made in situ using a He-Ne laser (˜27 mW) as a known radiation source to heat the foil. The thermal images of the foil are provided by an infrared (IR) camera (microbolometer type). The parameters are determined by finite element modeling (FEM) of the foil temperature and comparing the solution to the experimental results. In this work we apply this calibration technique to investigate the spatial variation of the foil parameters. Significant variation in the local temperature rise of the foil due to local heating by the laser beam indicates a spatial variation of the foil parameters κ, k and tf. This variation is possibly due to nonuniformity in carbon coating and/or the thickness of the foil.
Owen-Smith, Norman
2011-07-01
1. There is a pressing need for population models that can reliably predict responses to changing environmental conditions and diagnose the causes of variation in abundance in space as well as through time. In this 'how to' article, it is outlined how standard population models can be modified to accommodate environmental variation in a heuristically conducive way. This approach is based on metaphysiological modelling concepts linking populations within food web contexts and underlying behaviour governing resource selection. Using population biomass as the currency, population changes can be considered at fine temporal scales taking into account seasonal variation. Density feedbacks are generated through the seasonal depression of resources even in the absence of interference competition. 2. Examples described include (i) metaphysiological modifications of Lotka-Volterra equations for coupled consumer-resource dynamics, accommodating seasonal variation in resource quality as well as availability, resource-dependent mortality and additive predation, (ii) spatial variation in habitat suitability evident from the population abundance attained, taking into account resource heterogeneity and consumer choice using empirical data, (iii) accommodating population structure through the variable sensitivity of life-history stages to resource deficiencies, affecting susceptibility to oscillatory dynamics and (iv) expansion of density-dependent equations to accommodate various biomass losses reducing population growth rate below its potential, including reductions in reproductive outputs. Supporting computational code and parameter values are provided. 3. The essential features of metaphysiological population models include (i) the biomass currency enabling within-year dynamics to be represented appropriately, (ii) distinguishing various processes reducing population growth below its potential, (iii) structural consistency in the representation of interacting populations and
Solar parameters for modeling interplanetary background
Bzowski, M; Tokumaru, M; Fujiki, K; Quemerais, E; Lallement, R; Ferron, S; Bochsler, P; McComas, D J
2011-01-01
The goal of the Fully Online Datacenter of Ultraviolet Emissions (FONDUE) Working Team of the International Space Science Institute in Bern, Switzerland, was to establish a common calibration of various UV and EUV heliospheric observations, both spectroscopic and photometric. Realization of this goal required an up-to-date model of spatial distribution of neutral interstellar hydrogen in the heliosphere, and to that end, a credible model of the radiation pressure and ionization processes was needed. This chapter describes the solar factors shaping the distribution of neutral interstellar H in the heliosphere. Presented are the solar Lyman-alpha flux and the solar Lyman-alpha resonant radiation pressure force acting on neutral H atoms in the heliosphere, solar EUV radiation and the photoionization of heliospheric hydrogen, and their evolution in time and the still hypothetical variation with heliolatitude. Further, solar wind and its evolution with solar activity is presented in the context of the charge excha...
Parameter estimation, model reduction and quantum filtering
Chase, Bradley A.
This thesis explores the topics of parameter estimation and model reduction in the context of quantum filtering. The last is a mathematically rigorous formulation of continuous quantum measurement, in which a stream of auxiliary quantum systems is used to infer the state of a target quantum system. Fundamental quantum uncertainties appear as noise which corrupts the probe observations and therefore must be filtered in order to extract information about the target system. This is analogous to the classical filtering problem in which techniques of inference are used to process noisy observations of a system in order to estimate its state. Given the clear similarities between the two filtering problems, I devote the beginning of this thesis to a review of classical and quantum probability theory, stochastic calculus and filtering. This allows for a mathematically rigorous and technically adroit presentation of the quantum filtering problem and solution. Given this foundation, I next consider the related problem of quantum parameter estimation, in which one seeks to infer the strength of a parameter that drives the evolution of a probe quantum system. By embedding this problem in the state estimation problem solved by the quantum filter, I present the optimal Bayesian estimator for a parameter when given continuous measurements of the probe system to which it couples. For cases when the probe takes on a finite number of values, I review a set of sufficient conditions for asymptotic convergence of the estimator. For a continuous-valued parameter, I present a computational method called quantum particle filtering for practical estimation of the parameter. Using these methods, I then study the particular problem of atomic magnetometry and review an experimental method for potentially reducing the uncertainty in the estimate of the magnetic field beyond the standard quantum limit. The technique involves double-passing a probe laser field through the atomic system, giving
On Variations Of Pre-supernova Model Properties
Farmer, R.; Fields, C. E.; Petermann, I.; Dessart, Luc; Cantiello, M.; Paxton, B.; Timmes, F. X.
2016-12-01
We explore the variation in single-star 15-30 {M}⊙ , nonrotating, solar metallicity, pre-supernova MESA models that is due to changes in the number of isotopes in a fully coupled nuclear reaction network and adjustments in the mass resolution. Within this two-dimensional plane, we quantitatively detail the range of core masses at various stages of evolution, mass locations of the main nuclear burning shells, electron fraction profiles, mass fraction profiles, burning lifetimes, stellar lifetimes, and compactness parameter at core collapse for models with and without mass-loss. Up to carbon burning, we generally find that mass resolution has a larger impact on the variations than the number of isotopes, while the number of isotopes plays a more significant role in determining the span of the variations for neon, oxygen, and silicon burning. Choice of mass resolution dominates the variations in the structure of the intermediate convection zone and secondary convection zone during core and shell hydrogen burning, respectively, where we find that a minimum mass resolution of ≈0.01 {M}⊙ is necessary to achieve convergence in the helium core mass at the ≈5% level. On the other hand, at the onset of core collapse, we find ≈30% variations in the central electron fraction and mass locations of the main nuclear burning shells, a minimum of ≈127 isotopes is needed to attain convergence of these values at the ≈10% level.
Institute of Scientific and Technical Information of China (English)
DONG Gui-Fang; LIU Qing-Di; WANG Li-Duo; QIU Yong
2008-01-01
By investigating the variation of different characteristic parameters of pentacene/poly(methyl methacrylate)transistors suffered from electric stress in an environment without O2, H2O and light, we deduce lifetimes of the transistors by different criterion parameters. Defined by the time for the parameters changing one half,the lifetime is different from the minimum of 7h (using on/off current ratio as the criterion parameter) to the maximum of 2.38 × 108h (using transconductance as the criterion parameter). We also find that, under our experimental conditions, the main reason that affects the stabilities of the device is the increase of shallow traps formed in the organic semiconductors.
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.
Single Plant Root System Modeling under Soil Moisture Variation
Yabusaki, S.; Fang, Y.; Chen, X.; Scheibe, T. D.
2016-12-01
A prognostic Virtual Plant-Atmosphere-Soil System (vPASS) model is being developed that integrates comprehensively detailed mechanistic single plant modeling with microbial, atmospheric, and soil system processes in its immediate environment. Three broad areas of process module development are targeted: Incorporating models for root growth and function, rhizosphere interactions with bacteria and other organisms, litter decomposition and soil respiration into established porous media flow and reactive transport models Incorporating root/shoot transport, growth, photosynthesis and carbon allocation process models into an integrated plant physiology model Incorporating transpiration, Volatile Organic Compounds (VOC) emission, particulate deposition and local atmospheric processes into a coupled plant/atmosphere model. The integrated plant ecosystem simulation capability is being developed as open source process modules and associated interfaces under a modeling framework. The initial focus addresses the coupling of root growth, vascular transport system, and soil under drought scenarios. Two types of root water uptake modeling approaches are tested: continuous root distribution and constitutive root system architecture. The continuous root distribution models are based on spatially averaged root development process parameters, which are relatively straightforward to accommodate in the continuum soil flow and reactive transport module. Conversely, the constitutive root system architecture models use root growth rates, root growth direction, and root branching to evolve explicit root geometries. The branching topologies require more complex data structures and additional input parameters. Preliminary results are presented for root model development and the vascular response to temporal and spatial variations in soil conditions.
Parameter optimization in S-system models
Directory of Open Access Journals (Sweden)
Vasconcelos Ana
2008-04-01
Full Text Available Abstract Background The inverse problem of identifying the topology of biological networks from their time series responses is a cornerstone challenge in systems biology. We tackle this challenge here through the parameterization of S-system models. It was previously shown that parameter identification can be performed as an optimization based on the decoupling of the differential S-system equations, which results in a set of algebraic equations. Results A novel parameterization solution is proposed for the identification of S-system models from time series when no information about the network topology is known. The method is based on eigenvector optimization of a matrix formed from multiple regression equations of the linearized decoupled S-system. Furthermore, the algorithm is extended to the optimization of network topologies with constraints on metabolites and fluxes. These constraints rejoin the system in cases where it had been fragmented by decoupling. We demonstrate with synthetic time series why the algorithm can be expected to converge in most cases. Conclusion A procedure was developed that facilitates automated reverse engineering tasks for biological networks using S-systems. The proposed method of eigenvector optimization constitutes an advancement over S-system parameter identification from time series using a recent method called Alternating Regression. The proposed method overcomes convergence issues encountered in alternate regression by identifying nonlinear constraints that restrict the search space to computationally feasible solutions. Because the parameter identification is still performed for each metabolite separately, the modularity and linear time characteristics of the alternating regression method are preserved. Simulation studies illustrate how the proposed algorithm identifies the correct network topology out of a collection of models which all fit the dynamical time series essentially equally well.
Modeling of Parameters of Subcritical Assembly SAD
Petrochenkov, S; Puzynin, I
2005-01-01
The accepted conceptual design of the experimental Subcritical Assembly in Dubna (SAD) is based on the MOX core with a nominal unit capacity of 25 kW (thermal). This corresponds to the multiplication coefficient $k_{\\rm eff} =0.95$ and accelerator beam power 1 kW. A subcritical assembly driven with the existing 660 MeV proton accelerator at the Joint Institute for Nuclear Research has been modelled in order to make choice of the optimal parameters for the future experiments. The Monte Carlo method was used to simulate neutron spectra, energy deposition and doses calculations. Some of the calculation results are presented in the paper.
Energy Technology Data Exchange (ETDEWEB)
Xu Longdao; Gao Yuliang
1985-09-01
Two variational parameters are included in the most probable constrained effective wave function with the accurate Hamiltonian remained. The third critical field which coincides with the result in paper (1) has been easily obtained through the variational principle.
Tsui, Po-Hsiang; Wan, Yung-Liang; Huang, Chih-Chung; Wang, Ming-Chen
2010-10-01
The Nakagami parameter is associated with the Nakagami distribution estimated from ultrasonic backscattered signals and closely reflects the scatterer concentrations in tissues. There is an interest in exploring the possibility of enhancing the ability of the Nakagami parameter to characterize tissues. In this paper, we explore the effect of adaptive thresholdfiltering based on the noise-assisted empirical mode decomposition of the ultrasonic backscattered signals on the Nakagami parameter as a function of scatterer concentration for improving the Nakagami parameter performance. We carried out phantom experiments using 5 MHz focused and nonfocused transducers. Before filtering, the dynamic ranges of the Nakagami parameter, estimated using focused and nonfocused transducers between the scatterer concentrations of 2 and 32 scatterers/mm3, were 0.44 and 0.1, respectively. After filtering, the dynamic ranges of the Nakagami parameter, using the focused and nonfocused transducers, were 0.71 and 0.79, respectively. The experimental results showed that the adaptive threshold filter makes the Nakagami parameter measured by a focused transducer more sensitive to the variation in the scatterer concentration. The proposed method also endows the Nakagami parameter measured by a nonfocused transducer with the ability to differentiate various scatterer concentrations. However, the Nakagami parameters estimated by focused and nonfocused transducers after adaptive threshold filtering have different physical meanings: the former represents the statistics of signals backscattered from unresolvable scatterers while the latter is associated with stronger resolvable scatterers or local inhomogeneity due to scatterer aggregation.
Ahmed, Naveed; Alahmari, Abdulrahman M.; Darwish, Saied; Naveed, Madiha
2016-12-01
Micro-channels are considered as the integral part of several engineering devices such as micro-channel heat exchangers, micro-coolers, micro-pulsating heat pipes and micro-channels used in gas turbine blades for aerospace applications. In such applications, a fluid flow is required to pass through certain micro-passages such as micro-grooves and micro-channels. The fluid flow characteristics (flow rate, turbulence, pressure drop and fluid dynamics) are mainly established based on the size and accuracy of micro-passages. Variations (oversizing and undersizing) in micro-passage's geometry directly affect the fluid flow characteristics. In this study, the micro-channels of several sizes are fabricated in well-known aerospace nickel alloy (Inconel 718) through laser beam micro-milling. The variations in geometrical characteristics of different-sized micro-channels are studied under the influences of different parameters of Nd:YAG laser. In order to have a minimum variation in the machined geometries of each size of micro-channel, the multi-objective optimization of laser parameters has been carried out utilizing the response surface methodology approach. The objective was set to achieve the targeted top widths and depths of micro-channels with minimum degree of taperness associated with the micro-channel's sidewalls. The optimized sets of laser parameters proposed for each size of micro-channel can be used to fabricate the micro-channels in Inconel 718 with minimum amount of geometrical variations.
Baker Syed; Poskar C; Junker Björn
2011-01-01
Abstract In systems biology, experimentally measured parameters are not always available, necessitating the use of computationally based parameter estimation. In order to rely on estimated parameters, it is critical to first determine which parameters can be estimated for a given model and measurement set. This is done with parameter identifiability analysis. A kinetic model of the sucrose accumulation in the sugar cane culm tissue developed by Rohwer et al. was taken as a test case model. Wh...
Moose models with vanishing $S$ parameter
Casalbuoni, R; Dominici, Daniele
2004-01-01
In the linear moose framework, which naturally emerges in deconstruction models, we show that there is a unique solution for the vanishing of the $S$ parameter at the lowest order in the weak interactions. We consider an effective gauge theory based on $K$ SU(2) gauge groups, $K+1$ chiral fields and electroweak groups $SU(2)_L$ and $U(1)_Y$ at the ends of the chain of the moose. $S$ vanishes when a link in the moose chain is cut. As a consequence one has to introduce a dynamical non local field connecting the two ends of the moose. Then the model acquires an additional custodial symmetry which protects this result. We examine also the possibility of a strong suppression of $S$ through an exponential behavior of the link couplings as suggested by Randall Sundrum metric.
Model parameters for simulation of physiological lipids
McGlinchey, Nicholas
2016-01-01
Coarse grain simulation of proteins in their physiological membrane environment can offer insight across timescales, but requires a comprehensive force field. Parameters are explored for multicomponent bilayers composed of unsaturated lipids DOPC and DOPE, mixed‐chain saturation POPC and POPE, and anionic lipids found in bacteria: POPG and cardiolipin. A nonbond representation obtained from multiscale force matching is adapted for these lipids and combined with an improved bonding description of cholesterol. Equilibrating the area per lipid yields robust bilayer simulations and properties for common lipid mixtures with the exception of pure DOPE, which has a known tendency to form nonlamellar phase. The models maintain consistency with an existing lipid–protein interaction model, making the force field of general utility for studying membrane proteins in physiologically representative bilayers. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. PMID:26864972
Exploring Factor Model Parameters across Continuous Variables with Local Structural Equation Models.
Hildebrandt, Andrea; Lüdtke, Oliver; Robitzsch, Alexander; Sommer, Christopher; Wilhelm, Oliver
2016-01-01
Using an empirical data set, we investigated variation in factor model parameters across a continuous moderator variable and demonstrated three modeling approaches: multiple-group mean and covariance structure (MGMCS) analyses, local structural equation modeling (LSEM), and moderated factor analysis (MFA). We focused on how to study variation in factor model parameters as a function of continuous variables such as age, socioeconomic status, ability levels, acculturation, and so forth. Specifically, we formalized the LSEM approach in detail as compared with previous work and investigated its statistical properties with an analytical derivation and a simulation study. We also provide code for the easy implementation of LSEM. The illustration of methods was based on cross-sectional cognitive ability data from individuals ranging in age from 4 to 23 years. Variations in factor loadings across age were examined with regard to the age differentiation hypothesis. LSEM and MFA converged with respect to the conclusions. When there was a broad age range within groups and varying relations between the indicator variables and the common factor across age, MGMCS produced distorted parameter estimates. We discuss the pros of LSEM compared with MFA and recommend using the two tools as complementary approaches for investigating moderation in factor model parameters.
Reconstructing the evolution of dark energy with variations of fundamental parameters
Nunes, N J; Martins, C J A P; Robbers, G
2009-01-01
Under the assumption that the variations of parameters of nature and the current acceleration of the universe are related and governed by the evolution of a single scalar field, we show how information can be obtained on the nature of dark energy from observational detection of (or constraints on) cosmological variations of the fine structure constant and the proton-to-electron mass ratio. We also comment on the current observational status, and on the prospects for improvements with future spectrographs such as ESPRESSO and CODEX.
Strong parameter renormalization from optimum lattice model orbitals
Brosco, Valentina; Ying, Zu-Jian; Lorenzana, José
2017-01-01
Which is the best single-particle basis to express a Hubbard-like lattice model? A rigorous variational answer to this question leads to equations the solution of which depends in a self-consistent manner on the lattice ground state. Contrary to naive expectations, for arbitrary small interactions, the optimized orbitals differ from the noninteracting ones, leading also to substantial changes in the model parameters as shown analytically and in an explicit numerical solution for a simple double-well one-dimensional case. At strong coupling, we obtain the direct exchange interaction with a very large renormalization with important consequences for the explanation of ferromagnetism with model Hamiltonians. Moreover, in the case of two atoms and two fermions we show that the optimization equations are closely related to reduced density-matrix functional theory, thus establishing an unsuspected correspondence between continuum and lattice approaches.
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.
Physicochemical parameters and seasonal variation of coastal water from Balochistan coast, Pakistan
Institute of Scientific and Technical Information of China (English)
Naeema Elahi; Quratulan Ahmed; Levent Bat; Farzana Yousuf
2015-01-01
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 25ºCto 37ºC, water temperature ranged from 15.00ºC to 33.00ºC, 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.
Energy Technology Data Exchange (ETDEWEB)
Galvez-Carrillo, Manuel; Kinnaert, Michel [Dept. of Control Engineering and System Analysis, Universite Libre de Bruxelles (ULB), 50 Av. F.D. Roosevelt, CP 165/55, B-1050 Brussels (Belgium)
2011-05-15
A fault detection and isolation (FDI) system for monitoring rotor current sensors in a doubly-fed induction generator (DFIG) for wind turbine applications is presented. The FDI system is designed so that the effect of parameter variations (resistances and inductances) is minimized. The residual generation is based on the generalized observer scheme (GOS) including parameter estimation. A decision system made of a combination of vector CUSUM (Cumulative sum) algorithms is used to process the residual vector and to achieve detection and isolation of incipient (small magnitude) faults. The approach is validated using signals obtained from a simulated vector-controlled DFIG. (author)
Indian Academy of Sciences (India)
T H Freeda; C Mahadevan
2001-10-01
Pure and impurity added (with NH4Cl, NH4NO3, NH4H2PO4, and (NH4)2SO4) KDP single crystals were grown by the gel method using silica gels. X-ray diffraction data were collected for powder samples and used for the estimation of lattice variation and thermal parameters like Debye–Waller factor, mean-square amplitude of vibration, Debye temperature and Debye frequency. The thermal parameters do not vary in a particular order with respect to impurity concentration. The results obtained are reported and discussed.
On Variations Of Pre-Supernova Model Properties
Farmer, R; Petermann, I; Dessart, Luc; Cantiello, M; Paxton, B; Timmes, F X
2016-01-01
We explore the variation in single star 15-30 $\\rm{M}_{\\odot}$, non-rotating, solar metallicity, pre-supernova MESA models due to changes in the number of isotopes in a fully-coupled nuclear reaction network and adjustments in the mass resolution. Within this two-dimensional plane we quantitatively detail the range of core masses at various stages of evolution, mass locations of the main nuclear burning shells, electron fraction profiles, mass fraction profiles, burning lifetimes, stellar lifetimes, and compactness parameter at core-collapse for models with and without mass loss. Up to carbon burning we generally find mass resolution has a larger impact on the variations than the number of isotopes, while the number of isotopes plays a more significant role in determining the span of the variations for neon, oxygen and silicon burning. Choice of mass resolution dominates the variations in the structure of the intermediate convection zone and secondary convection zone during core and shell hydrogen burning res...
Eibenberger, K; Schima, H; Trubel, W; Temel, T; Schmidt, C; Scherer, R; Windberger, U; Dock, W; Grabenwöger, F
1996-07-01
The aim of our study was to objectively compare the effectiveness of various Doppler parameters in the diagnosis of renal artery stenosis. In three sheep, variable degrees of renal artery stenosis were induced and renal segmental arteries were investigated using pulsed Doppler sonography. In each animal the standard deviation of the instantaneous peak velocity within one cardiac cycle normalized by the mean peak velocity (coefficient of variation) had significantly higher normalized regression coefficients (k* = -0.215, average of three animals) when compared to resistive index (k* = -0.090) and acceleration index (k* = -0.069). In each individual animal, coefficient of variation detected lower pressure gradients (6.3 mm Hg, average value) than did resistive index (13.4 mm Hg) or acceleration index (17.3 mm Hg). The coefficient of variation may detect the presence of pressure gradients in renal artery stenosis more accurately than acceleration index or resistive index.
Diurnal variation of B parameters over Havana at low and high solar activity
Lazo, B.; Savio, S.; Alazo, K.; Calzadilla, A.; Ojeda, A.
In support of the international effort of determining the best set of parameters to describe the electron density profile in the ionosphere we have analyzed the diurnal variation of B0 and B1 for Havana (23°N; 278°E; Dip 54.6°N; Modip 44.8°N) for low and high solar activity during winter and summertime.
The Method of Variation of Parameters for Solving a Dynamical System of Relative Motion
Institute of Scientific and Technical Information of China (English)
ZHANG Yi
2011-01-01
The integration method of a dynamical system of relative motion is studied,and the method of variation of parameters for the dynamical equations of relative motion is presented.First,the dynamic equations of relative motion are brought into the frame of generalized Birkhoffian systems and are expressed in the contravariant algebraic form.Second,an auxiliary system is constructed and its complete solution is found.Finally,the variation of parameters is given,and a complete solution of the problem is obtained by taking advantage of the properties of generalized canonical transformations.An example is given to illustrate the application of the results.An important direction in analytical dynamics is to present new and versatile integration methods for a complex mechanical system.The motion of a complex system may include the motion of a carrier,as well as the motion of a carried system relative to the carrier.Whittaker[1] studied the Lagrange equations of a holonomic system subject to uniform rotation constraints.Lur'e studied the dynamics of relative motion ofa holonomic system.[2] Mei took the dynamics of relative motion as a special topic to review and research in his monographs.[3-8] Over the past twenty years,research on the dynamics of relative motion has been fruitful.[3- 24]%The integration method of a dynamical system of relative motion is studied, and the method of variation of parameters for the dynamical equations of relative motion is presented. First, the dynamic equations of relative motion are brought into the frame of generalized Birkhoffan systems and are expressed in the contravariant algebraic form. Second, an auxiliary system is constructed and its complete solution is found. Finally, the variation of parameters is given, and a complete solution of the problem is obtained by taking advantage of the properties of generalized canonical transformations. An example is given to illustrate the application of the results.
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
estimation approach that allows for the parameters of the estimated models to be time varying. It is shown that a two-state Gaussian hidden Markov model with time-varying parameters is able to reproduce the long memory of squared daily returns that was previously believed to be the most difficult fact...... 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....
Numerical modeling of partial discharges parameters
Directory of Open Access Journals (Sweden)
Kartalović Nenad M.
2016-01-01
Full Text Available In recent testing of the partial discharges or the use for the diagnosis of insulation condition of high voltage generators, transformers, cables and high voltage equipment develops rapidly. It is a result of the development of electronics, as well as, the development of knowledge about the processes of partial discharges. The aim of this paper is to contribute the better understanding of this phenomenon of partial discharges by consideration of the relevant physical processes in isolation materials and isolation systems. Prebreakdown considers specific processes, and development processes at the local level and their impact on specific isolation material. This approach to the phenomenon of partial discharges needed to allow better take into account relevant discharge parameters as well as better numerical model of partial discharges.
Model parameters for representative wetland plant functional groups
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
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
Celeste: Variational inference for a generative model of astronomical images
Regier, Jeffrey; McAuliffe, Jon; Adams, Ryan; Hoffman, Matt; Lang, Dustin; Schlegel, David; Prabhat,
2015-01-01
We present a new, fully generative model of optical telescope image sets, along with a variational procedure for inference. Each pixel intensity is treated as a Poisson random variable, with a rate parameter dependent on latent properties of stars and galaxies. Key latent properties are themselves random, with scientific prior distributions constructed from large ancillary data sets. We check our approach on synthetic images. We also run it on images from a major sky survey, where it exceeds the performance of the current state-of-the-art method for locating celestial bodies and measuring their colors.
Global analysis of a class of HIV models with immune response and antigenic variation
Souza, Max O
2008-01-01
We study the global stability of two models for the HIV virus dynamics, that take into account the CTL immune response and antigenic variation. We show that both models are globally asymptotically stable, by using appropriate Lyapunov functions. For both models, we characterise the stable equilibrium points for the entire biologically relevant parameter range. In the model with antigenic variation, which can have a large number of equilibrium points, this allows us to determine what is the diversity of the persistent strains.
Directory of Open Access Journals (Sweden)
Datta N
2005-01-01
Full Text Available BACKGROUND: Tumor regression parameters and time factor during external radiotherapy (EXTRT are of paramount importance. AIMS: To quantify the parameters of tumor regression and time factor during EXTRT in cancer cervix. SETTINGS AND DESIGN: Patients, treated solely with radiotherapy and enrolled for other prospective studies having weekly tumor regressions recorded were considered. MATERIALS AND METHODS: Seventy-seven patients received 50Gy of EXTRT followed by intracavitary brachytherapy. Loco-regional regressions were assessed clinically and regression fraction (RF was represented as RF = c + a1D + a2D2- a3T, with c, D and T as constant, cumulative EXTRT dose and treatment time respectively. STATISTICAL ANALYSIS USED: Step wise linear regression was performed for RF. Scatter plots were fitted using linear-quadratic fit. RESULTS: Coefficients of parameters D, D2 and T were computed for various dose intervals, namely 0-20 Gy, 0-30 Gy, 0-40 Gy and 0-50 Gy. At 0-20 Gy and 0-30 Gy, only the coefficient of D2 was significant (P < 0.001, while both D2 and T turned significant (P < 0.001 at 0-40 Gy. For the entire range of 0-50 Gy, all the coefficients of D, D2 and T showed significance, leading to an estimate of 26 Gy for a1/a2 and 0.96 Gy/day for a3/a1. CONCLUSIONS: As with a/β and g/a of post-irradiation cell survival curves, a1/a2 and a3/a1 represents the cumulative effect of various radiobiological factors influencing clinical regression of tumor during the course of EXTRT. The dynamic changes in the coefficients of D, D2sub and T, indicate their relative importance during various phases of EXTRT.
Fast Total-Variation Image Deconvolution with Adaptive Parameter Estimation via Split Bregman Method
Directory of Open Access Journals (Sweden)
Chuan He
2014-01-01
Full Text Available The total-variation (TV regularization has been widely used in image restoration domain, due to its attractive edge preservation ability. However, the estimation of the regularization parameter, which balances the TV regularization term and the data-fidelity term, is a difficult problem. In this paper, based on the classical split Bregman method, a new fast algorithm is derived to simultaneously estimate the regularization parameter and to restore the blurred image. In each iteration, the regularization parameter is refreshed conveniently in a closed form according to Morozov’s discrepancy principle. Numerical experiments in image deconvolution show that the proposed algorithm outperforms some state-of-the-art methods both in accuracy and in speed.
Institute of Scientific and Technical Information of China (English)
LU Ting-kan; LIU Yu-zhou
2005-01-01
Described the outcomes of a comprehensive numerical modeling on the rock bolting performance for preventing the deformation of stratified, composite roof structure of drift in a coal mine. The investigation was undertaken in the adverse geological conditions, with variation of belt parameters, including length, density, distribution, pretension,as well as the geometry of opening, so as to determine the effect of bolting parameter variation on roof deformation and stability. The outcomes clearly demonstrated that a significant improvement of roof stability can be achieved associating with bolting parameters optimization, and indicated the importance of flexible geotechnical designation of rock mbolting reinforcement in mining practice.
2011-01-01
He was with RF Micro Devices, where he worked to develop gallium nitride technology. He has extensive experience in both growth and characterization...main heat source), it is observed in the model that the heat is radiating away such that the isothermal contours are nearly circular and centered about...some importance from a model perspective, because an accurate density of active traps is hard to quantitatively determine by experiment. In both of
The identifiability of parameters in a water quality model of the Biebrza River, Poland
Perk, van der M.; Bierkens, M.F.P.
1997-01-01
The identifiability of model parameters of a steady state water quality model of the Biebrza River and the resulting variation in model results was examined by applying the Monte Carlo method which combines calibration, identifiability analysis, uncertainty analysis, and sensitivity analysis. The wa
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...... that will optimise parameters based on the behaviour of the elastic models over time....
Model Identification of Linear Parameter Varying Aircraft Systems
Fujimore, Atsushi; Ljung, Lennart
2007-01-01
This article presents a parameter estimation of continuous-time polytopic models for a linear parameter varying (LPV) system. The prediction error method of linear time invariant (LTI) models is modified for polytopic models. The modified prediction error method is applied to an LPV aircraft system whose varying parameter is the flight velocity and model parameters are the stability and control derivatives (SCDs). In an identification simulation, the polytopic model is more suitable for expre...
Monte-Carlo Inversion of Travel-Time Data for the Estimation of Weld Model Parameters
Hunter, A. J.; Drinkwater, B. W.; Wilcox, P. D.
2011-06-01
The quality of ultrasonic array imagery is adversely affected by uncompensated variations in the medium properties. A method for estimating the parameters of a general model of an inhomogeneous anisotropic medium is described. The model is comprised of a number of homogeneous sub-regions with unknown anisotropy. Bayesian estimation of the unknown model parameters is performed via a Monte-Carlo Markov chain using the Metropolis-Hastings algorithm. Results are demonstrated using simulated weld data.
Kelley, Ken
2007-11-01
The accuracy in parameter estimation approach to sample size planning is developed for the coefficient of variation, where the goal of the method is to obtain an accurate parameter estimate by achieving a sufficiently narrow confidence interval. The first method allows researchers to plan sample size so that the expected width of the confidence interval for the population coefficient of variation is sufficiently narrow. A modification allows a desired degree of assurance to be incorporated into the method, so that the obtained confidence interval will be sufficiently narrow with some specified probability (e.g., 85% assurance that the 95 confidence interval width will be no wider than to units). Tables of necessary sample size are provided for a variety of scenarios that may help researchers planning a study where the coefficient of variation is of interest plan an appropriate sample size in order to have a sufficiently narrow confidence interval, optionally with somespecified assurance of the confidence interval being sufficiently narrow. Freely available computer routines have been developed that allow researchers to easily implement all of the methods discussed in the article.
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) (SDFA : 0.01-0.02; SDMD : 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 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.
[Calculation of parameters in forest evapotranspiration model].
Wang, Anzhi; Pei, Tiefan
2003-12-01
Forest evapotranspiration is an important component not only in water balance, but also in energy balance. It is a great demand for the development of forest hydrology and forest meteorology to simulate the forest evapotranspiration accurately, which is also a theoretical basis for the management and utilization of water resources and forest ecosystem. Taking the broadleaved Korean pine forest on Changbai Mountain as an example, this paper constructed a mechanism model for estimating forest evapotranspiration, based on the aerodynamic principle and energy balance equation. Using the data measured by the Routine Meteorological Measurement System and Open-Path Eddy Covariance Measurement System mounted on the tower in the broadleaved Korean pine forest, the parameters displacement height d, stability functions for momentum phi m, and stability functions for heat phi h were ascertained. The displacement height of the study site was equal to 17.8 m, near to the mean canopy height, and the functions of phi m and phi h changing with gradient Richarson number R i were constructed.
Study of gain variation as a function of physical parameters of GEM foil
Energy Technology Data Exchange (ETDEWEB)
Das, Supriya, E-mail: Supriya.Das@cern.ch
2016-07-11
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.
Parameter sensitivity in satellite-gravity-constrained geothermal modelling
Pastorutti, Alberto; Braitenberg, Carla
2017-04-01
The use of satellite gravity data in thermal structure estimates require identifying the factors that affect the gravity field and are related to the thermal characteristics of the lithosphere. We propose a set of forward-modelled synthetics, investigating the model response in terms of heat flow, temperature, and gravity effect at satellite altitude. The sensitivity analysis concerns the parameters involved, as heat production, thermal conductivity, density and their temperature dependence. We discuss the effect of the horizontal smoothing due to heat conduction, the superposition of the bulk thermal effect of near-surface processes (e.g. advection in ground-water and permeable faults, paleoclimatic effects, blanketing by sediments), and the out-of equilibrium conditions due to tectonic transients. All of them have the potential to distort the gravity-derived estimates.We find that the temperature-conductivity relationship has a small effect with respect to other parameter uncertainties on the modelled temperature depth variation, surface heat flow, thermal lithosphere thickness. We conclude that the global gravity is useful for geothermal studies.
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.
Parameter optimization in differential geometry based solvation models.
Wang, Bao; Wei, G W
2015-10-01
Differential geometry (DG) based solvation models are a new class of variational implicit solvent approaches that are able to avoid unphysical solvent-solute boundary definitions and associated geometric singularities, and dynamically couple polar and non-polar interactions in a self-consistent framework. Our earlier study indicates that DG based non-polar solvation model outperforms other methods in non-polar solvation energy predictions. However, the DG based full solvation model has not shown its superiority in solvation analysis, due to its difficulty in parametrization, which must ensure the stability of the solution of strongly coupled nonlinear Laplace-Beltrami and Poisson-Boltzmann equations. In this work, we introduce new parameter learning algorithms based on perturbation and convex optimization theories to stabilize the numerical solution and thus achieve an optimal parametrization of the DG based solvation models. An interesting feature of the present DG based solvation model is that it provides accurate solvation free energy predictions for both polar and non-polar molecules in a unified formulation. Extensive numerical experiment demonstrates that the present DG based solvation model delivers some of the most accurate predictions of the solvation free energies for a large number of molecules.
Parameters-related uncertainty in modeling sugar cane yield with an agro-Land Surface Model
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.
Transfer function modeling of damping mechanisms in distributed parameter models
Slater, J. C.; Inman, D. J.
1994-01-01
This work formulates a method for the modeling of material damping characteristics in distributed parameter models which may be easily applied to models such as rod, plate, and beam equations. The general linear boundary value vibration equation is modified to incorporate hysteresis effects represented by complex stiffness using the transfer function approach proposed by Golla and Hughes. The governing characteristic equations are decoupled through separation of variables yielding solutions similar to those of undamped classical theory, allowing solution of the steady state as well as transient response. Example problems and solutions are provided demonstrating the similarity of the solutions to those of the classical theories and transient responses of nonviscous systems.
Variation of photon interaction parameters with energy for some Cu-Pb alloys
Energy Technology Data Exchange (ETDEWEB)
Singh, Tejbir, E-mail: dr.tejbir@gmail.com; Kaur, Sarpreet; Kaur, Parminder; Kaur, Harvinder [Department of Physics, Sri Guru Granth Sahib World University, Fatehgarh Saheb-140406, Punjab (India); Singh, Parjit S. [Department of Physics, Punjabi University, Patiala-147002, Punjab (India)
2015-08-28
Various photon interaction parameters (mass attenuation coefficients, effective atomic numbers and effective electron numbers) have been computed for different compositions of Cu-Pb alloys in the wide energy regime of 1 keV to 100 GeV. The mass attenuation coefficients have been computed using mixture rule with the help of WinXCom (mass attenuation coefficient database for elements). The variation of mass attenuation coefficients, effective atomic numbers and electron density has been analysed and discussed in terms of dominance of different photon interaction processes viz. Compton scattering, photoelectric effect and pair production.
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.
Temporal variations analyses and predictive modeling of microbiological seawater quality.
Lušić, Darija Vukić; Kranjčević, Lado; Maćešić, Senka; Lušić, Dražen; Jozić, Slaven; Linšak, Željko; Bilajac, Lovorka; Grbčić, Luka; Bilajac, Neiro
2017-08-01
Bathing water quality is a major public health issue, especially for tourism-oriented regions. Currently used methods within EU allow at least a 2.2 day period for obtaining the analytical results, making outdated the information forwarded to the public. Obtained results and beach assessment are influenced by the temporal and spatial characteristics of sample collection, and numerous environmental parameters, as well as by differences of official water standards. This paper examines the temporal variation of microbiological parameters during the day, as well as the influence of the sampling hour, on decision processes in the management of the beach. Apart from the fecal indicators stipulated by the EU Bathing Water Directive (E. coli and enterococci), additional fecal (C. perfringens) and non-fecal (S. aureus and P. aeriginosa) parameters were analyzed. Moreover, the effects of applying different evaluation criteria (national, EU and U.S. EPA) to beach ranking were studied, and the most common reasons for exceeding water-quality standards were investigated. In order to upgrade routine monitoring, a predictive statistical model was developed. The highest concentrations of fecal indicators were recorded early in the morning (6 AM) due to the lack of solar radiation during the night period. When compared to enterococci, E. coli criteria appears to be more stringent for the detection of fecal pollution. In comparison to EU and U.S. EPA criteria, Croatian national evaluation criteria provide stricter public health standards. Solar radiation and precipitation were the predominant environmental parameters affecting beach water quality, and these parameters were included in the predictive model setup. Predictive models revealed great potential for the monitoring of recreational water bodies, and with further development can become a useful tool for the improvement of public health protection. Copyright © 2017 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Adedeji G. Abiodun
2011-01-01
Full Text Available Purpose. This study investigated the anthropometric indices associated with variations in cardiovascular parameters among primary school pupils in Ile-Ife. Method. One thousand and twenty-six pupils (age range 6–14 years, mean age 10.12 years from ten schools were recruited with parents' informed consent. Anthropometric (Height (Ht, Weight (Wt, Abdominal Circumference (AC and cardiovascular (Systolic Blood Pressure (SBP, Diastolic Blood Pressure (DBP, Heart Rate (HR parameters were measured using standard instruments and procedures. Blood pressure (BP was measured after ten minutes of quiet sitting. Body Mass Index (BMI, Rate Pressure Product (RPP and Pulse Pressure (PP were estimated. Results. Age, Ht, Wt, BMI, and AC correlated significantly (<.01 with BP and PP. AC and BMI were predictors of BP, HR, RPP, and PP. Conclusion. Significant correlations exist between age, Ht, Wt, BMI, AC, and BP with weight being a more viable predictor of SBP and age a more viable predictor of DBP.
Facial wiping in the rat fetus: variation of chemosensory stimulus parameters.
Brumley, Michele R; Robinson, Scott R
2004-05-01
Fetal rats reliably express a facial wiping response to novel chemosensory stimuli. Previous research has examined facial wiping as an early form of motor coordination and as a behavioral indicator of sensory responsiveness. The present study examined how variation in stimulus parameters of lemon odor infusion (concentration, volume, and infusion time) affected the wiping response of E20 rat fetuses. Infusions of higher concentration or greater volume generally elicited wiping responses of greater duration and more strokes. Most facial wipes involved strokes by single forelimbs; however, bilaterally synchronous wiping was expressed only in bouts of at least seven wipes, and was facilitated by stimuli of moderate intensity. These findings suggest that the total number of wiping strokes or bout duration are well suited as measures of overall sensory responsiveness in the fetus and that chemosensory stimulus parameters exert a permissive influence on interlimb coordination during a bout of facial wiping.
Abiodun, Adedeji G; Egwu, Michael O; Adedoyin, Rufus A
2011-01-01
Purpose. This study investigated the anthropometric indices associated with variations in cardiovascular parameters among primary school pupils in Ile-Ife. Method. One thousand and twenty-six pupils (age range 6-14 years, mean age 10.12 years) from ten schools were recruited with parents' informed consent. Anthropometric (Height (Ht), Weight (Wt), Abdominal Circumference (AC)) and cardiovascular (Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP), Heart Rate (HR)) parameters were measured using standard instruments and procedures. Blood pressure (BP) was measured after ten minutes of quiet sitting. Body Mass Index (BMI), Rate Pressure Product (RPP) and Pulse Pressure (PP) were estimated. Results. Age, Ht, Wt, BMI, and AC correlated significantly (P < .01) with BP and PP. AC and BMI were predictors of BP, HR, RPP, and PP. Conclusion. Significant correlations exist between age, Ht, Wt, BMI, AC, and BP with weight being a more viable predictor of SBP and age a more viable predictor of DBP.
Box-constrained Total-variation Image Restoration with Automatic Parameter Estimation
Institute of Scientific and Technical Information of China (English)
HE Chuan; HU Chang-Hua; ZHANG Wei; SHI Biao
2014-01-01
The box constraints in image restoration have been arousing great attention, since the pixels of a digital image can attain only a finite number of values in a given dynamic range. This paper studies the box-constrained total-variation (TV) image restoration problem with automatic regularization parameter estimation. By adopting the variable splitting technique and introducing some auxiliary variables, the box-constrained TV minimization problem is decomposed into a sequence of subproblems which are easier to solve. Then the alternating direction method (ADM) is adopted to solve the related subproblems. By means of Morozov0s discrepancy principle, the regularization parameter can be updated adaptively in a closed form in each iteration. Image restoration experiments indicate that with our strategies, more accurate solutions are achieved, especially for image with high percentage of pixel values lying on the boundary of the given dynamic range.
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.
On the modeling of internal parameters in hyperelastic biological materials
Giantesio, Giulia
2016-01-01
This paper concerns the behavior of hyperelastic energies depending on an internal parameter. First, the situation in which the internal parameter is a function of the gradient of the deformation is presented. Second, two models where the parameter describes the activation of skeletal muscle tissue are analyzed. In those models, the activation parameter depends on the strain and it is important to consider the derivative of the parameter with respect to the strain in order to capture the proper behavior of the stress.
Determining extreme parameter correlation in ground water models
DEFF Research Database (Denmark)
Hill, Mary Cole; Østerby, Ole
2003-01-01
In ground water flow system models with hydraulic-head observations but without significant imposed or observed flows, extreme parameter correlation generally exists. As a result, hydraulic conductivity and recharge parameters cannot be uniquely estimated. In complicated problems, such correlation...... correlation coefficients, but it required sensitivities that were one to two significant digits less accurate than those that required using parameter correlation coefficients; and (3) both the SVD and parameter correlation coefficients identified extremely correlated parameters better when the parameters...
An analytical method for Mathieu oscillator based on method of variation of parameter
Li, Xianghong; Hou, Jingyu; Chen, Jufeng
2016-08-01
A simple, but very accurate analytical method for forced Mathieu oscillator is proposed, the idea of which is based on the method of variation of parameter. Assuming that the time-varying parameter in Mathieu oscillator is constant, one could easily obtain its accurately analytical solution. Then the approximately analytical solution for Mathieu oscillator could be established after substituting periodical time-varying parameter for the constant one in the obtained accurate analytical solution. In order to certify the correctness and precision of the proposed analytical method, the first-order and ninth-order approximation solutions by harmonic balance method (HBM) are also presented. The comparisons between the results by the proposed method with those by the numerical simulation and HBM verify that the results by the proposed analytical method agree very well with those by the numerical simulation. Moreover, the precision of the proposed new analytical method is not only higher than the approximation solution by first-order HBM, but also better than the approximation solution by the ninth-order HBM in large ranges of system parameters.
Model comparisons and genetic and environmental parameter ...
African Journals Online (AJOL)
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South African Journal of Animal Science 2005, 35 (1) ... Genetic and environmental parameters were estimated for pre- and post-weaning average daily gain ..... and BWT (and medium maternal genetic correlations) indicates that these traits ...
Institute of Scientific and Technical Information of China (English)
MA Xue-min; LI Bao-lin; LIN Chang-wei
2015-01-01
The functions of bounded Φ-variation are development and generalization of bounded variation functions in the usual sense.Henstock-Kurzweil integral is a very useful tool for some discontinuous systems. In this paper, by using Henstock-Kurzweil integral, we establish theorems of continuous dependence of bounded Φ-variation solutions on parameter for a class of discontinuous systems on the base of Φ-function. These results are essential generalizations of continuous dependence of bounded variation solutions on parameter for the systems.
Surface ozone variation at Bhubaneswar and intra-corelationship study with various parameters
Indian Academy of Sciences (India)
P S Mahapatra; J Jena; S Moharana; H Srichandan; T Das; G Roy Chaudhury; S N Das
2012-10-01
This paper summarizes the results of year long (December 2009 to January 2011) continuous measurements of daytime (0700–1745) ozone (O3) in the ambient air and related meteorological parameters at Bhubaneswar (21° 15′N–85° 15′E), Odisha. The seasonal variation shows distinct daytime ozone maxima during winters with a peak in January (∼85 ppbv), a slight increase (∼38 ppbv) in June and lowest in August (∼20 ppbv). The backward trajectory analysis during winter months suggests long distance transport of airmass from mainly Indo-Gangetic Plains (IGP) and western part of Indian peninsula, a major industrial hub. In other seasons, wind reaches the observation site from less polluted landmasses and the Bay of Bengal, thereby considerably reducing the pollution load. On the contrary, ozone build-up was found to be maximum and minimum in pre-monsoon and monsoon, respectively. An anti-weekend ozone effect (∼5 ppbv) was observed in winter. Paired t-test and F-test along with principal component analysis (PCA) were done to determine significance between various components (ozone, precursors and meteorological parameters). The t- and F-test showed significant monthly variation of ozone mixing ratio. The PCA showed that three components explained 79.1% of variances.
NEW DOCTORAL DEGREE Parameter estimation problem in the Weibull model
Marković, Darija
2009-01-01
In this dissertation we consider the problem of the existence of best parameters in the Weibull model, one of the most widely used statistical models in reliability theory and life data theory. Particular attention is given to a 3-parameter Weibull model. We have listed some of the many applications of this model. We have described some of the classical methods for estimating parameters of the Weibull model, two graphical methods (Weibull probability plot and hazard plot), and two analyt...
Directory of Open Access Journals (Sweden)
Olfa Bel Hadj Brahim Kechiche
2014-06-01
Full Text Available This study highlights the impact of an universal Phase Locked Loop (PLL parameters variation on PMSM position estimation at low speeds. Indeed, the PLL parameters variation impact on the PMSM rotor position estimation performance and robustness cannot be neglected anymore. For this purpose, the study presents the theory and simulation results of a demodulation scheme applied to Sensorless PMSM control based on the Pulsating Voltage Injection (PVI technique. Comprehensive simulations, carried out under MATLAB/SIMULINK®, are discussed according to the variation of the PLL proportional and integral parameters.
Variations of cosmic large-scale structure covariance matrices across parameter space
Reischke, Robert; Schäfer, Björn Malte
2016-01-01
The likelihood function for cosmological parameters, given by e.g. weak lensing shear measurements, depends on contributions to the covariance induced by the nonlinear evolution of the cosmic web. As nonlinear clustering to date has only been described by numerical $N$-body simulations in a reliable and sufficiently precise way, the necessary computational costs for estimating those covariances at different points in parameter space are tremendous. In this work we describe the change of the matter covariance and of the weak lensing covariance matrix as a function of cosmological parameters by constructing a suitable basis, where we model the contribution to the covariance from nonlinear structure formation using Eulerian perturbation theory at third order. We show that our formalism is capable of dealing with large matrices and reproduces expected degeneracies and scaling with cosmological parameters in a reliable way. Comparing our analytical results to numerical simulations we find that the method describes...
Kadu, Caroline A C; Parich, Alexandra; Schueler, Silvio; Konrad, Heino; Muluvi, Geoffrey M; Eyog-Matig, Oscar; Muchugi, Alice; Williams, Vivienne L; Ramamonjisoa, Lolona; Kapinga, Consolatha; Foahom, Bernard; Katsvanga, Cuthbert; Hafashimana, David; Obama, Crisantos; Vinceti, Barbara; Schumacher, Rainer; Geburek, Thomas
2012-11-01
Prunus africana--an evergreen tree found in Afromontane forests--is used in traditional medicine to cure benign prostate hyperplasia. Different bioactive constituents derived from bark extracts from 20 tree populations sampled throughout the species' natural range in Africa were studied by means of GC-MSD. The average concentration [mg/kgw/w] in increasing order was: lauric acid (18), myristic acid (22), n-docosanol (25), ferulic acid (49), β-sitostenone (198), β-sitosterol (490), and ursolic acid (743). The concentrations of many bark constituents were significantly correlated and concentration of n-docosanol was highly significantly correlated with all other analytes. Estimates of variance components revealed the highest variation among populations for ursolic acid (66%) and the lowest for β-sitosterol (20%). In general, environmental parameters recorded (temperature, precipitation, altitude) for the samples sites were not correlated with the concentration of most constituents; however, concentration of ferulic acid was significantly correlated with annual precipitation. Because the concentration of compounds in bark extracts may be affected by tree size, the diameter of sampled plants at 1.3m tree height (as proxy of age) was recorded. The only relationship with tree diameter was a negative correlation with ursolic acid. Under the assumption that genetically less variable populations have less variable concentrations of bark compounds, correlations between variation parameters of the concentration and the respective genetic composition based on chloroplast and nuclear DNA markers were assessed. Only variation of β-sitosterol concentration was significantly correlated with haplotypic diversity. The fixation index (F(IS)) was positively correlated with the variation in concentration of ferulic acid. Principal Components Analysis (PCA) indicated a weak geographic pattern. Mantel tests, however, revealed associations between the geographic patterns of bioactive
Energy Technology Data Exchange (ETDEWEB)
Vasconcelos, Wagner Eustaquio de; Lira, Carlos Alberto Brayner de Oliveira; Brito, Thiago Souza Pereira de; Afonso, Antonio Claudio Marques, E-mail: wagner@unicap.br, E-mail: cabol@ufpe.br, E-mail: afonsofisica@gmail.com, E-mail: thiago.brito86@yahoo.com.br [Universidade Federal de Pernambuco (UFPE), Recife, PE (Brazil). Centro de Tecnologia e Geociencias. Departamento de Energia Nuclear; Cruz Filho, Antonio Jose da; Marques, Jose Antonio, E-mail: antonio.jscf@gmail.com, E-mail: jamarkss@uol.com.br [Universidade Catolica de Pernambuco (CCT/PUC-PE), Recife, PE (Brazil). Centro de Ciencias e Tecnologia; Teixeira, Marcello Goulart, E-mail: marcellogt@dcc.ufrj.br [Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, RJ (Brazil). Instituto de Matematica. Dept. de Matematica
2013-07-01
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 optimization model in electrical discharge machining process
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
Electrical discharge machining (EDM) process, at present is still an experience process, wherein selected parameters are often far from the optimum, and at the same time selecting optimization parameters is costly and time consuming. In this paper,artificial neural network (ANN) and genetic algorithm (GA) are used together to establish the parameter optimization model. An ANN model which adapts Levenberg-Marquardt algorithm has been set up to represent the relationship between material removal rate (MRR) and input parameters, and GA is used to optimize parameters, so that optimization results are obtained. The model is shown to be effective, and MRR is improved using optimized machining parameters.
Sensitivity of a Shallow-Water Model to Parameters
Kazantsev, Eugene
2011-01-01
An adjoint based technique is applied to a shallow water model in order to estimate the influence of the model's parameters on the solution. Among parameters the bottom topography, initial conditions, boundary conditions on rigid boundaries, viscosity coefficients Coriolis parameter and the amplitude of the wind stress tension are considered. Their influence is analyzed from three points of view: 1. flexibility of the model with respect to a parameter that is related to the lowest value of the cost function that can be obtained in the data assimilation experiment that controls this parameter; 2. possibility to improve the model by the parameter's control, i.e. whether the solution with the optimal parameter remains close to observations after the end of control; 3. sensitivity of the model solution to the parameter in a classical sense. That implies the analysis of the sensitivity estimates and their comparison with each other and with the local Lyapunov exponents that characterize the sensitivity of the mode...
Variations of immune parameters in terrestrial isopods: a matter of gender, aging and Wolbachia
Sicard, Mathieu; Chevalier, Frédéric; de Vlechouver, Mickaël; Bouchon, Didier; Grève, Pierre; Braquart-Varnier, Christine
2010-09-01
Ecological factors modulate animal immunocompetence and potentially shape the evolution of their immune systems. Not only environmental parameters impact on immunocompetence: Aging is one major cause of variability of immunocompetence between individuals, and sex-specific levels of immunocompetence have also been frequently described. Moreover, a growing core of data put in light that vertically transmitted symbionts can dramatically modulate the immunocompetence of their hosts. In this study, we addressed the influence of gender, age and the feminising endosymbiont Wolbachia ( wVulC) on variations in haemocyte density, total PO activity and bacterial load in the haemolymph of the terrestrial isopod Armadillidium vulgare. This host-symbiont system is of particular interest to address this question since: (1) wVulC was previously shown as immunosuppressive in middle-aged females and (2) wVulC influences sex determination. We show that age, gender and Wolbachia modulate together immune parameters in A. vulgare. However, wVulC, which interacts with aging, appears to be the prominent factor interfering with both PO activity and haemocyte density. This interference with immune parameters is not the only aspect of wVulC virulence on its host, as reproduction and survival are also altered.
Compositional modelling of distributed-parameter systems
Maschke, Bernhard; Schaft, van der Arjan; Lamnabhi-Lagarrigue, F.; Loría, A.; Panteley, E.
2005-01-01
The Hamiltonian formulation of distributed-parameter systems has been a challenging reserach area for quite some time. (A nice introduction, especially with respect to systems stemming from fluid dynamics, can be found in [26], where also a historical account is provided.) The identification of the
Parameter Estimation and Experimental Design in Groundwater Modeling
Institute of Scientific and Technical Information of China (English)
SUN Ne-zheng
2004-01-01
This paper reviews the latest developments on parameter estimation and experimental design in the field of groundwater modeling. Special considerations are given when the structure of the identified parameter is complex and unknown. A new methodology for constructing useful groundwater models is described, which is based on the quantitative relationships among the complexity of model structure, the identifiability of parameter, the sufficiency of data, and the reliability of model application.
Digital Repository Service at National Institute of Oceanography (India)
Fernandes, C.E.G.; Das, A.; Naik, S.S.; Sharma, R.; LokaBharathi, P.A.
The variation in bacterial parameters of coastal waters and sediments of Kalbadevi Bay, Ratnagiri, Maharashtra, India was examined for immediate response after simulated mining. Sampling was carried out at suction and disturbance points in the water...
Bayesian approach to decompression sickness model parameter estimation.
Howle, L E; Weber, P W; Nichols, J M
2017-03-01
We examine both maximum likelihood and Bayesian approaches for estimating probabilistic decompression sickness model parameters. Maximum likelihood estimation treats parameters as fixed values and determines the best estimate through repeated trials, whereas the Bayesian approach treats parameters as random variables and determines the parameter probability distributions. We would ultimately like to know the probability that a parameter lies in a certain range rather than simply make statements about the repeatability of our estimator. Although both represent powerful methods of inference, for models with complex or multi-peaked likelihoods, maximum likelihood parameter estimates can prove more difficult to interpret than the estimates of the parameter distributions provided by the Bayesian approach. For models of decompression sickness, we show that while these two estimation methods are complementary, the credible intervals generated by the Bayesian approach are more naturally suited to quantifying uncertainty in the model parameters.
Learning optimal spatially-dependent regularization parameters in total variation image denoising
Van Chung, Cao; De los Reyes, J. C.; Schönlieb, C. B.
2017-07-01
We consider a bilevel optimization approach in function space for the choice of spatially dependent regularization parameters in TV image denoising models. First- and second-order optimality conditions for the bilevel problem are studied when the spatially-dependent parameter belongs to the Sobolev space {{H}1}≤ft(Ω \\right) . A combined Schwarz domain decomposition-semismooth Newton method is proposed for the solution of the full optimality system and local superlinear convergence of the semismooth Newton method is verified. Exhaustive numerical computations are finally carried out to show the suitability of the approach.
Models for setting ATM parameter values
DEFF Research Database (Denmark)
Blaabjerg, Søren; Gravey, A.; Romæuf, L.
1996-01-01
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...... to Network Interface (UNI) and at subsequent Inter Carrier Interfaces (ICIs), by algorithmic rules based on the Generic Cell Rate Algorithm (GCRA) formalism. Conformance rules are implemented by policing mechanisms that control the traffic submitted by the user and discard excess traffic. It is therefore...
Huang, Jian; Yuen, Pong C; Chen, Wen-Sheng; Lai, Jian Huang
2007-08-01
This paper addresses the problem of automatically tuning multiple kernel parameters for the kernel-based linear discriminant analysis (LDA) method. The kernel approach has been proposed to solve face recognition problems under complex distribution by mapping the input space to a high-dimensional feature space. Some recognition algorithms such as the kernel principal components analysis, kernel Fisher discriminant, generalized discriminant analysis, and kernel direct LDA have been developed in the last five years. The experimental results show that the kernel-based method is a good and feasible approach to tackle the pose and illumination variations. One of the crucial factors in the kernel approach is the selection of kernel parameters, which highly affects the generalization capability and stability of the kernel-based learning methods. In view of this, we propose an eigenvalue-stability-bounded margin maximization (ESBMM) algorithm to automatically tune the multiple parameters of the Gaussian radial basis function kernel for the kernel subspace LDA (KSLDA) method, which is developed based on our previously developed subspace LDA method. The ESBMM algorithm improves the generalization capability of the kernel-based LDA method by maximizing the margin maximization criterion while maintaining the eigenvalue stability of the kernel-based LDA method. An in-depth investigation on the generalization performance on pose and illumination dimensions is performed using the YaleB and CMU PIE databases. The FERET database is also used for benchmark evaluation. Compared with the existing PCA-based and LDA-based methods, our proposed KSLDA method, with the ESBMM kernel parameter estimation algorithm, gives superior performance.
Hemmat, Maedeh; Kamal, Mehdi; Afzali-Kusha, Ali; Pedram, Massoud
2016-10-01
In this paper, the impact of physical parameter variations on the electrical characteristics of III-V TFETs is investigated. The study is performed on the operations of two optimized ultra-thin 20 nm double-gate transistors. The two device structures are InAs homojunction TFET and InAs-GaAs0.1Sb0.9 heterojunction TFET. The operation parameters are the ON-current, OFF-current, and threshold voltage. The investigation is performed at the device level, using a device simulator and the Monte-Carlo simulation approach is exploited to extract the distribution of electrical parameters in the presence of the process variation. The results reveal that the operation of the transistor is more sensitive to the doping of the source and gate work function compared to other physical parameters. Furthermore, the heterojunction TFETs show less sensitivity to physical parameter variations compared to the homojunction ones.
Variation of plasma parameters of vacuum arc column with gap distance
Han, Wen; Yuan, Zhao; He, Junjia
2016-07-01
On the basis of a two-dimensional (2D) magneto-hydrodynamic model, we studied long-gap-distance vacuum arcs in a uniform axial magnetic field and determined the effect of gap distance varying in a large range on plasma parameters. Simulation results showed that with increasing gap distance, the parameters of the plasma near the cathode are almost invariant, except for ion number density, but the parameters of the plasma in front of the anode clearly vary; meanwhile, joule heat gradually becomes the main source of energy for the arc column. In a short gap, a clear current constriction can be found in the entire arc column. Whereas when the gap distance exceeds a certain value, a sharp contraction of the current only arises in front of the anode.
DEFF Research Database (Denmark)
Norgaard, Trine; de Jonge, Lis Wollesen; Møldrup, Per
2015-01-01
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......-radiorespirometric method. Initial mineralization rates were determined using first-order kinetics for glyphosate and bromoxyniloctanoate and zeroorder kinetics for diflufenican and bentazone. The mineralization rates of the four pesticides varied between the different pesticides and the different soil samples, but we...... could not establish correlations between the pesticide mineralization rates and the measured soil parameters. Only the glyphosate mineralization rates showed slightly increasing mineralization potentials towards the northern area of the field, with increasing clay and decreasing OC contents...
An electroplating topography model based on layout-dependent variation of copper deposition rate
Institute of Scientific and Technical Information of China (English)
Wang Qiang; Chen Lan; Li Zhigang; Ruan Wenbiao
2011-01-01
A layout-pattern-dependent electroplating model is developed based on the physical mechanism of the electroplating process.Our proposed electroplating model has an advantage over former ones due to a consideration of the variation of copper deposition rate with different layout parameters during the process.The simulation results compared with silicon data demonstrate the improvement in accuracy.
Pindera, Marek-Jerzy; Salzar, Robert S.
1996-01-01
The objective of this work was the development of efficient, user-friendly computer codes for optimizing fabrication-induced residual stresses in metal matrix composites through the use of homogeneous and heterogeneous interfacial layer architectures and processing parameter variation. To satisfy this objective, three major computer codes have been developed and delivered to the NASA-Lewis Research Center, namely MCCM, OPTCOMP, and OPTCOMP2. MCCM is a general research-oriented code for investigating the effects of microstructural details, such as layered morphology of SCS-6 SiC fibers and multiple homogeneous interfacial layers, on the inelastic response of unidirectional metal matrix composites under axisymmetric thermomechanical loading. OPTCOMP and OPTCOMP2 combine the major analysis module resident in MCCM with a commercially-available optimization algorithm and are driven by user-friendly interfaces which facilitate input data construction and program execution. OPTCOMP enables the user to identify those dimensions, geometric arrangements and thermoelastoplastic properties of homogeneous interfacial layers that minimize thermal residual stresses for the specified set of constraints. OPTCOMP2 provides additional flexibility in the residual stress optimization through variation of the processing parameters (time, temperature, external pressure and axial load) as well as the microstructure of the interfacial region which is treated as a heterogeneous two-phase composite. Overviews of the capabilities of these codes are provided together with a summary of results that addresses the effects of various microstructural details of the fiber, interfacial layers and matrix region on the optimization of fabrication-induced residual stresses in metal matrix composites.
Parameter and Uncertainty Estimation in Groundwater Modelling
DEFF Research Database (Denmark)
Jensen, Jacob Birk
The data basis on which groundwater models are constructed is in general very incomplete, and this leads to uncertainty in model outcome. Groundwater models form the basis for many, often costly decisions and if these are to be made on solid grounds, the uncertainty attached to model results must...... be quantified. This study was motivated by the need to estimate the uncertainty involved in groundwater models.Chapter 2 presents an integrated surface/subsurface unstructured finite difference model that was developed and applied to a synthetic case study.The following two chapters concern calibration...... and uncertainty estimation. Essential issues relating to calibration are discussed. The classical regression methods are described; however, the main focus is on the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. The next two chapters describe case studies in which the GLUE methodology...
Energy Technology Data Exchange (ETDEWEB)
Doiron, H.H.; Deane, J.D.
1982-09-01
Effects of hydraulic cleaning parameter variations on rate of penetration response of 7 7/8 inch diameter soft formation insert bits have been measured in laboratory drilling tests. Tests were conducted in Mancos Shale rock samples at 700 psi and 4000 psi simulated overbalance pressure conditions using a 9.1 pound per gallon bentonite-barite water base drilling fluid. Bit hydraulic horsepower was varied from 0.72 to 9.5 HHP/in/sup 2/ using two or three nozzles in sizes ranging from 9/32 to 14/32 inches in diameter. Some improvements in ROP at constant bit hydraulic horsepower and impact force levels were obtained with two nozzle configurations vs. three nozzle configurations, but improvements were not consistently out of the range of normal test to test variations. Reduction in drilling costs due to the measured response of ROP to improved hydraulic cleaning is compared to increased operating costs required to provide additional hydraulics. Results indicate that bit hydraulic horsepower levels in excess of popular rules of thumb are cost effective in slow drilling due to high overbalance pressure.
Parameter redundancy in discrete state‐space and integrated models
McCrea, Rachel S.
2016-01-01
Discrete state‐space models are used in ecology to describe the dynamics of wild animal populations, with parameters, such as the probability of survival, being of ecological interest. For a particular parametrization of a model it is not always clear which parameters can be estimated. This inability to estimate all parameters is known as parameter redundancy or a model is described as nonidentifiable. In this paper we develop methods that can be used to detect parameter redundancy in discrete state‐space models. An exhaustive summary is a combination of parameters that fully specify a model. To use general methods for detecting parameter redundancy a suitable exhaustive summary is required. This paper proposes two methods for the derivation of an exhaustive summary for discrete state‐space models using discrete analogues of methods for continuous state‐space models. We also demonstrate that combining multiple data sets, through the use of an integrated population model, may result in a model in which all parameters are estimable, even though models fitted to the separate data sets may be parameter redundant. PMID:27362826
Parameter redundancy in discrete state-space and integrated models.
Cole, Diana J; McCrea, Rachel S
2016-09-01
Discrete state-space models are used in ecology to describe the dynamics of wild animal populations, with parameters, such as the probability of survival, being of ecological interest. For a particular parametrization of a model it is not always clear which parameters can be estimated. This inability to estimate all parameters is known as parameter redundancy or a model is described as nonidentifiable. In this paper we develop methods that can be used to detect parameter redundancy in discrete state-space models. An exhaustive summary is a combination of parameters that fully specify a model. To use general methods for detecting parameter redundancy a suitable exhaustive summary is required. This paper proposes two methods for the derivation of an exhaustive summary for discrete state-space models using discrete analogues of methods for continuous state-space models. We also demonstrate that combining multiple data sets, through the use of an integrated population model, may result in a model in which all parameters are estimable, even though models fitted to the separate data sets may be parameter redundant. © 2016 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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.
Ternary interaction parameters in calphad solution models
Energy Technology Data Exchange (ETDEWEB)
Eleno, Luiz T.F., E-mail: luizeleno@usp.br [Universidade de Sao Paulo (USP), SP (Brazil). Instituto de Fisica; Schön, Claudio G., E-mail: schoen@usp.br [Universidade de Sao Paulo (USP), SP (Brazil). Computational Materials Science Laboratory. Department of Metallurgical and Materials Engineering
2014-07-01
For random, diluted, multicomponent solutions, the excess chemical potentials can be expanded in power series of the composition, with coefficients that are pressure- and temperature-dependent. For a binary system, this approach is equivalent to using polynomial truncated expansions, such as the Redlich-Kister series for describing integral thermodynamic quantities. For ternary systems, an equivalent expansion of the excess chemical potentials clearly justifies the inclusion of ternary interaction parameters, which arise naturally in the form of correction terms in higher-order power expansions. To demonstrate this, we carry out truncated polynomial expansions of the excess chemical potential up to the sixth power of the composition variables. (author)
Parameter estimation and error analysis in environmental modeling and computation
Kalmaz, E. E.
1986-01-01
A method for the estimation of parameters and error analysis in the development of nonlinear modeling for environmental impact assessment studies is presented. The modular computer program can interactively fit different nonlinear models to the same set of data, dynamically changing the error structure associated with observed values. Parameter estimation techniques and sequential estimation algorithms employed in parameter identification and model selection are first discussed. Then, least-square parameter estimation procedures are formulated, utilizing differential or integrated equations, and are used to define a model for association of error with experimentally observed data.
Energy Technology Data Exchange (ETDEWEB)
Karantanas, A.H. [Department of CT-MRI, Larissa General Hospital (Greece); Zibis, A.H.; Papaliaga, M.; Georgiou, E.; Rousogiannis, S. [Larissa Medical School, University of Thessaly, Larissa (Greece)
1998-12-01
The aim of this study was to investigate the correlation of vertebral dimensions with somatometric parameters in patients without clinical symptoms and radiological signs of central lumbar spinal stenosis. One hundred patients presenting with low back pain or sciatica were studied with CT. In each of the L3, L4 and L5 vertebra three slices were taken with the following measurements: 1. Slice through the intervertebral disc: (a) spinal canal area; (b) interarticular diameter; (c) interligamentous diameter. 2. Slice below the vertebral arcus: (a) dural sac area; (b) vertebral body area. 3. Pediculolaminar level: (a) anteroposterior diameter and interpedicular diameter of the spinal canal; (b) spinal canal area; (c) width of the lateral recesses. The Jones-Thomson index was also estimated. The results of the present study showed that there is a statistically significant correlation of height, weight and age with various vertebral indices. The conventional, widely accepted, anteroposterior diameter of 11.5 mm of the lumbar spinal canal is independent of somatometric parameters, and it is the only constant measurement for the estimation of lumbar spinal stenosis with a single value. The present study suggests that there are variations of the dimensions of the lumbar spinal canal and correlations with height, weight and age of the patient. (orig.) With 1 fig., 6 tabs., 24 refs.
Madurga, Rodrigo; Plaza, Gustavo R.; Blackledge, Todd A.; Guinea, Gustavo. V.; Elices, Manuel; Pérez-Rigueiro, José
2016-01-01
Spider major ampullate gland silks (MAS) vary greatly in material properties among species but, this variation is shown here to be confined to evolutionary shifts along a single universal performance trajectory. This reveals an underlying design principle that is maintained across large changes in both spider ecology and silk chemistry. Persistence of this design principle becomes apparent after the material properties are defined relative to the true alignment parameter, which describes the orientation and stretching of the protein chains in the silk fiber. Our results show that the mechanical behavior of all Entelegynae major ampullate silk fibers, under any conditions, are described by this single parameter that connects the sequential action of three deformation micromechanisms during stretching: stressing of protein-protein hydrogen bonds, rotation of the β-nanocrystals and growth of the ordered fraction. Conservation of these traits for over 230 million years is an indication of the optimal design of the material and gives valuable clues for the production of biomimetic counterparts based on major ampullate spider silk.
Athira, P.; Sudheer, K.
2013-12-01
Parameter estimation is one of the major tasks in the application of any physics based distributed model. Generally the calibration does not consider the heterogeneity of the parameters across the basin, and as a result the model simulation conforms to the location for which it has been calibrated for. However, the major advantage of distributed hydrological models is to have reasonably good simulations on various locations in the watershed, including ungauged locations. While multi-site calibration can address this issue to some extent, the availability of more gauge sites in a watershed is always not guaranteed. When single site calibration is performed, generally a uniform variation of the parameters is considered across the basin which does not ensure the true heterogeneity of the parameters in the basin. The primary objective of this study is to compare the effect of uniform variation of the parameter with a procedure that identifies actual heterogeneity of the parameters across the basin, while performing calibration of distributed hydrological models. In order to demonstrate the objective, a case study of two watersheds in the USA using the model, Soil and Water Assessment Tool (SWAT) is presented and discussed. Initially, the SWAT model is calibrated for both the watersheds in the traditional way considering uniform variation of the sensitive parameters during the calibration. Further, the hydrological response units (HRU) delineated in the SWAT are classified into various clusters based the land use, soil type and slope. A random perturbation of the parameters is performed in these clusters during calibration. The rationale behind this approach was to identify plausible parameter values that simulate the hydrological process in these clusters appropriately. The proposed procedure is applied to both the basins. The results indicate that the simulations obtained for upstream ungauged locations (other than that used for calibration) are much better when a
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.
Parameter estimation of hydrologic models using data assimilation
Kaheil, Y. H.
2005-12-01
The uncertainties associated with the modeling of hydrologic systems sometimes demand that data should be incorporated in an on-line fashion in order to understand the behavior of the system. This paper represents a Bayesian strategy to estimate parameters for hydrologic models in an iterative mode. The paper presents a modified technique called localized Bayesian recursive estimation (LoBaRE) that efficiently identifies the optimum parameter region, avoiding convergence to a single best parameter set. The LoBaRE methodology is tested for parameter estimation for two different types of models: a support vector machine (SVM) model for predicting soil moisture, and the Sacramento Soil Moisture Accounting (SAC-SMA) model for estimating streamflow. The SAC-SMA model has 13 parameters that must be determined. The SVM model has three parameters. Bayesian inference is used to estimate the best parameter set in an iterative fashion. This is done by narrowing the sampling space by imposing uncertainty bounds on the posterior best parameter set and/or updating the "parent" bounds based on their fitness. The new approach results in fast convergence towards the optimal parameter set using minimum training/calibration data and evaluation of fewer parameter sets. The efficacy of the localized methodology is also compared with the previously used Bayesian recursive estimation (BaRE) algorithm.
Estimation of Kinetic Parameters in an Automotive SCR Catalyst Model
DEFF Research Database (Denmark)
Åberg, Andreas; Widd, Anders; Abildskov, Jens;
2016-01-01
A challenge during the development of models for simulation of the automotive Selective Catalytic Reduction catalyst is the parameter estimation of the kinetic parameters, which can be time consuming and problematic. The parameter estimation is often carried out on small-scale reactor tests, or p...
Mirror symmetry for two parameter models, 2
Candelas, Philip; Katz, S; Morrison, Douglas Robert Ogston; Philip Candelas; Anamaria Font; Sheldon Katz; David R Morrison
1994-01-01
We describe in detail the space of the two K\\"ahler parameters of the Calabi--Yau manifold \\P_4^{(1,1,1,6,9)}[18] by exploiting mirror symmetry. The large complex structure limit of the mirror, which corresponds to the classical large radius limit, is found by studying the monodromy of the periods about the discriminant locus, the boundary of the moduli space corresponding to singular Calabi--Yau manifolds. A symplectic basis of periods is found and the action of the Sp(6,\\Z) generators of the modular group is determined. From the mirror map we compute the instanton expansion of the Yukawa couplings and the generalized N=2 index, arriving at the numbers of instantons of genus zero and genus one of each degree. We also investigate an SL(2,\\Z) symmetry that acts on a boundary of the moduli space.
Accuracy of Parameter Estimation in Gibbs Sampling under the Two-Parameter Logistic Model.
Kim, Seock-Ho; Cohen, Allan S.
The accuracy of Gibbs sampling, a Markov chain Monte Carlo procedure, was considered for estimation of item and ability parameters under the two-parameter logistic model. Memory test data were analyzed to illustrate the Gibbs sampling procedure. Simulated data sets were analyzed using Gibbs sampling and the marginal Bayesian method. The marginal…
Basic relations for the period variation models of variable stars
Mikulášek, Zdeněk; Gráf, Tomáš; Zejda, Miloslav; Zhu, Liying; Qian, Shen-Bang
2012-01-01
Models of period variations are basic tools for period analyzes of variable stars. We introduce phase function and instant period and formulate basic relations and equations among them. Some simple period models are also presented.
On linear models and parameter identifiability in experimental biological systems.
Lamberton, Timothy O; Condon, Nicholas D; Stow, Jennifer L; Hamilton, Nicholas A
2014-10-07
A key problem in the biological sciences is to be able to reliably estimate model parameters from experimental data. This is the well-known problem of parameter identifiability. Here, methods are developed for biologists and other modelers to design optimal experiments to ensure parameter identifiability at a structural level. The main results of the paper are to provide a general methodology for extracting parameters of linear models from an experimentally measured scalar function - the transfer function - and a framework for the identifiability analysis of complex model structures using linked models. Linked models are composed by letting the output of one model become the input to another model which is then experimentally measured. The linked model framework is shown to be applicable to designing experiments to identify the measured sub-model and recover the input from the unmeasured sub-model, even in cases that the unmeasured sub-model is not identifiable. Applications for a set of common model features are demonstrated, and the results combined in an example application to a real-world experimental system. These applications emphasize the insight into answering "where to measure" and "which experimental scheme" questions provided by both the parameter extraction methodology and the linked model framework. The aim is to demonstrate the tools' usefulness in guiding experimental design to maximize parameter information obtained, based on the model structure.
Directory of Open Access Journals (Sweden)
Oksana V. Mandrikova
2015-11-01
Full Text Available The paper is devoted to new mathematical tools for ionospheric parameter analysis and anomaly discovery during ionospheric perturbations. The complex structure of processes under study, their a-priori uncertainty and therefore the complex structure of registered data require a set of techniques and technologies to perform mathematical modelling, data analysis, and to make final interpretations. We suggest a technique of ionospheric parameter modelling and analysis based on combining the wavelet transform with autoregressive integrated moving average models (ARIMA models. This technique makes it possible to study ionospheric parameter changes in the time domain, make predictions about variations, and discover anomalies caused by high solar activity and lithospheric processes prior to and during strong earthquakes. The technique was tested on critical frequency foF2 and total electron content (TEC datasets from Kamchatka (a region in the Russian Far East and Magadan (a town in the Russian Far East. The mathematical models introduced in the paper facilitated ionospheric dynamic mode analysis and proved to be efficient for making predictions with time advance equal to 5 hours. Ionospheric anomalies were found using model error estimates, those anomalies arising during increased solar activity and strong earthquakes in Kamchatka.
Energy Technology Data Exchange (ETDEWEB)
Downward, L.; Booth, C.H.; Lukens, W.W.; Bridges, F.
2006-07-25
A general problem when fitting EXAFS data is determining whether particular parameters are statistically significant. The F-test is an excellent way of determining relevancy in EXAFS because it only relies on the ratio of the fit residual of two possible models, and therefore the data errors approximately cancel. Although this test is widely used in crystallography (there, it is often called a 'Hamilton test') and has been properly applied to EXAFS data in the past, it is very rarely applied in EXAFS analysis. We have implemented a variation of the F-test adapted for EXAFS data analysis in the RSXAP analysis package, and demonstrate its applicability with a few examples, including determining whether a particular scattering shell is warranted, and differentiating between two possible species or two possible structures in a given shell.
Institute of Scientific and Technical Information of China (English)
孙健; 李维亮; 周秀骥
2001-01-01
Sensitivity experiment is an important method to study the effect on regional climate due to seasonal variation of land surface parameters. Using China Regional Climate Model (CRCM)nested in CCM1, we first simulate Chinese regional climate, then two numerical sensitivity experiments on the effect of vegetation and roughness length are made. The results show that:(1) If the vegetation is replaced with the monthly data of 1997, precipitation and land-surface temperature are both changed clearly, precipitation decreases and land surface temperature increases, but there is no regional correspondence between these changes. And the results are much better than the results when climate average vegetation was used in the CRCM. (2) If the roughness length is replaced with the monthly data of 1997, there is significant change on land surface temperature, and there is very good regional correspondence between these changes. But the effect on precipitation is very small.
CHAMP: Changepoint Detection Using Approximate Model Parameters
2014-06-01
positions as a Markov chain in which the transition probabilities are defined by the time since the last changepoint: p(τi+1 = t|τi = s) = g(t− s), (1...experimentally verified using artifi- cially generated data and are compared to those of Fearnhead and Liu [5]. 2 Related work Hidden Markov Models (HMMs) are...length α, and maximum number of particles M . Output: Viterbi path of changepoint times and models // Initialize data structures 1: max path, prev queue
Modeling of patient's blood pressure variation during ambulance transportation
Sakatani, Kenji; Ono, Takahiko; Kobayasi, Yasuhide; Hikita, Shinichi; Saito, Mitsuyuki
2007-12-01
In an emergency transportation by ambulance, a patient is transported in a supine position. In this position, a patient's blood pressure (BP) variation depending on an inertial force which occurs when an ambulance accelerates or decelerates. This BP variation causes a critical damage for a patent with brain disorder. In order to keep a patient stable during transportation, it is required to maintain small BP variation. To analyze the BP variation during transportation, a model of the BP variation has so far been made. But, it can estimate the BP variation only in braking. The purpose of this paper is to make a dynamical model of the BP variation which can simulate it in both braking and accelerating. First, to obtain the data to construct the model, we used a tilting bed to measure a head-to-foot acceleration and BP of fingertip. Based on this data, we build a mathematical model whose input is the head-to-foot acceleration and output is the Mean BP variation. It is a switched model which switches two models depending on the jerk. We add baroreceptor reflex to the model as a offset value.
WINKLER'S SINGLE-PARAMETER SUBGRADE MODEL FROM ...
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[3, 9]. However, mainly due to the simplicity of Winkler's model in practical applications and .... this case, the coefficient B takes the dimension of a ... In plane-strain problems, the assumption of ... loaded circular region; s is the radial coordinate.
Space-time variation of the electron-to-proton mass ratio in a Weyl model
Landau, Susana J; Bonder, Yuri; Sudarsky, Daniel
2010-01-01
We consider a phenomenological model where the effective fermion masses depend on the local value of Weyl tensor as a possible explanation for the recent data indicating a space-time variation of the electron-to-proton mass ratio ($\\Delta \\mu/\\mu$) within the Milky Way. We also contrast the required value of the model's parameters with the bounds obtained for the same quantity from modern tests on the violation of the Weak Equivalence Principle (WEP). We obtain the theoretical expression for the variation of $\\Delta \\mu/\\mu$ and for the violation of the WEP as a function of the model parameters. We perform a least square minimization in order to obtain constraints on the model parameters from bounds on the WEP. The bounds obtained on the model parameters from the variation of $\\Delta \\mu/\\mu$ are inconsistent with the bounds obtained from constraints on the violation of the WEP. The variation of nucleon and electron masses through the Weyl tensor is not a viable model.
Mass distributions in a variational model
Stevenson, P D
2009-01-01
The time-dependent Hartree-Fock approach may be derived from a variational principle and a Slater Determinant wavefunction Ansatz. It gives a good description of nuclear processes in which one-body collisions dominate and has been applied with success to giant resonances and collisions around the barrier. It is inherently unable to give a good description of two-body observables. A variational principle, due to Balian and Veneroni has been proposed which can be geared to good reproduction of two-body observables. Keeping the Slater Determinant Ansatz, and restricting the two-body observables to be the squares of one-body observables, the procedure can be implemented as a modification of the time-dependent Hartree-Fock procedure. Applications, using the Skyrme effective interaction, are presented for the mass distributions of fragments following de-excitation of the giant dipole resonance in S-32. An illustration of the method's use in collisions is given.
Infrared Observations Of Saturn's Rings : Azimuthal Variations And Thermal Modeling
Leyrat, C.; Spilker, L. J.; Altobelli, N.; Pilorz, S.; Ferrari, C.; Edgington, S. G.; Wallis, B. D.; Nugent, C.; Flasar, M.
2007-12-01
Saturn's rings represent a collection of icy centimeter to meter size particles with their local dynamic dictated by self gravity, mutual collisions, surface roughness and thickness of the rings themselves. The infrared observations obtained by the CIRS infrared spectrometer on board Cassini over the last 3.5 year contain informations on the local dynamic, as the thermal signature of planetary rings is influenced both by the ring structure and the particle properties. The ring temperature is very dependent on the solar phase angle (Spilker et al., this issue), and on the local hour angle around Saturn, depending on whether or not particles' visible hemispheres are heated by the Sun. The geometric filling factor, which can be estimated from CIRS spectra, is less dependent on the local hour angle, suggesting that the non isothermal behavior of particles' surfaces have low impact, but it is very dependent on the spacecraft elevation for the A and C rings. The ring small scale structure can be explored using CIRS data. Variations of the filling factor with the local hour angle relative to the spacecraft azimuth reveals self-gravity wakes. We derive morphological parameters of such wakes in both A and B rings assuming that wakes can be modeled either by regularly spaced bars with infinite or finite optical depth. Our results indicates that wakes in the A ring are almost flat, with a ratio height/width ≈ 0.44 ± 0.16 and with a pitch angle relative to the orbital motion direction of ≍ 27deg. This is consistent with UVIS (Colwell et al., 2006) and VIMS data (Hedman et al., 2007). Such models are more difficult to constrain in the B ring, but small variations of the filling factor indicate that the pitch angle decreases drastically in this ring. We also present a new thermal bar model to explain azimuthal variations of temperatures in the A ring. We compare results with previous ring thermal models of spherical particles. The Cassini/CIRS azimuthal scans data set is
Improved Methodology for Parameter Inference in Nonlinear, Hydrologic Regression Models
Bates, Bryson C.
1992-01-01
A new method is developed for the construction of reliable marginal confidence intervals and joint confidence regions for the parameters of nonlinear, hydrologic regression models. A parameter power transformation is combined with measures of the asymptotic bias and asymptotic skewness of maximum likelihood estimators to determine the transformation constants which cause the bias or skewness to vanish. These optimized constants are used to construct confidence intervals and regions for the transformed model parameters using linear regression theory. The resulting confidence intervals and regions can be easily mapped into the original parameter space to give close approximations to likelihood method confidence intervals and regions for the model parameters. Unlike many other approaches to parameter transformation, the procedure does not use a grid search to find the optimal transformation constants. An example involving the fitting of the Michaelis-Menten model to velocity-discharge data from an Australian gauging station is used to illustrate the usefulness of the methodology.
A simulation of water pollution model parameter estimation
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.
On retrial queueing model with fuzzy parameters
Ke, Jau-Chuan; Huang, Hsin-I.; Lin, Chuen-Horng
2007-01-01
This work constructs the membership functions of the system characteristics of a retrial queueing model with fuzzy customer arrival, retrial and service rates. The α-cut approach is used to transform a fuzzy retrial-queue into a family of conventional crisp retrial queues in this context. By means of the membership functions of the system characteristics, a set of parametric non-linear programs is developed to describe the family of crisp retrial queues. A numerical example is solved successfully to illustrate the validity of the proposed approach. Because the system characteristics are expressed and governed by the membership functions, more information is provided for use by management. By extending this model to the fuzzy environment, fuzzy retrial-queue is represented more accurately and analytic results are more useful for system designers and practitioners.
Mohamed, Mohamed M; Saleh, Nawal E; Sherif, Mohsen M
2010-04-01
Dissolved benzene was detected in the shallow unconfined Liwa aquifer (UAE). This aquifer represents the main freshwater source for a nearby residence camp area. A finite element model is used to simulate the fate, transport, and attenuation of the dissolved benzene plume to help decision makers assess natural attenuation as a viable remediation option. Sensitivity of benzene attenuation to uncertainties in the estimation of some of the kinetic and transport parameters is studied. It was found that natural attenuation is more sensitive to microbial growth rate and half saturation coefficients of both benzene and oxygen than initial biomass concentration and dispersivity coefficients. Increasing microbial growth rate by fourfold increased natural attenuation effectiveness after 40 years by 10%; while decreasing it by fourfold decreased natural attenuation effectiveness by 77%. On the other hand, increasing half saturation coefficient by fourfold decreased natural attenuation effectiveness by 46% in 40 years. Decreasing the same parameter fourfold caused natural attenuation effectiveness to increase by 9%.
Han, Zhong-Tao; Qian, Sheng-Bang; Voloshina, Irina; Metlov, Vladimir G.; Zhu, Li-Ying; Li, Lin-Jia
2016-10-01
GSC 4560–02157 is a new eclipsing cataclysmic variable with an orbital period of 0.265359 days. By using the published V ‑ and R ‑ band data together with our observations, we discovered that the O ‑ C curve of GSC 4560–02157 may show a cyclic variation with a period of 3.51 years and an amplitude of 1.40 min. If this variation is caused by a light travel-time effect via the existence of a third body, then its mass can be derived as M 3 sin i' ≈ 91.08 M Jup, and it should be a low-mass star. In addition, several physical parameters were measured. The color of the secondary star was determined to be V ‑ R = 0.77(±0.03) which corresponds to a spectral type of K2–3. The secondary star's mass was estimated as M 2 = 0.73(±0.02) M ⊙ by combing the derived V ‑ R value around phase 0 with the assumption that it obeys the mass-luminosity relation for main sequence stars. This mass is consistent with the mass—period relation for CV donor stars. For the white dwarf, the eclipse durations and contacts of the white dwarf yield an upper limit on the white dwarf's radius corresponding to a lower limit on mass of M 1 ≈ 0.501 M ⊙. The overestimated radius and previously published spectral data indicate that the boundary layer may have a very high temperature.
Linear Sigma Models With Strongly Coupled Phases -- One Parameter Models
Hori, Kentaro
2013-01-01
We systematically construct a class of two-dimensional $(2,2)$ supersymmetric gauged linear sigma models with phases in which a continuous subgroup of the gauge group is totally unbroken. We study some of their properties by employing a recently developed technique. The focus of the present work is on models with one K\\"ahler parameter. The models include those corresponding to Calabi-Yau threefolds, extending three examples found earlier by a few more, as well as Calabi-Yau manifolds of other dimensions and non-Calabi-Yau manifolds. The construction leads to predictions of equivalences of D-brane categories, systematically extending earlier examples. There is another type of surprise. Two distinct superconformal field theories corresponding to Calabi-Yau threefolds with different Hodge numbers, $h^{2,1}=23$ versus $h^{2,1}=59$, have exactly the same quantum K\\"ahler moduli space. The strong-weak duality plays a crucial r\\^ole in confirming this, and also is useful in the actual computation of the metric on t...
Namysłowska-Wilczyńska, Barbara
2016-09-01
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. Data derived from 14 wells (2011) and 14 wells + 3 piezometers (2012) were subjected to spatial analyses using geostatistical methods. The evaluation of basic statistics of the quality parameters, including their histograms of distributions, scatter diagrams and correlation coefficient values r were presented. The directional semivariogram function γ(h) and the ordinary (block) kriging procedure were used to build the 3D geostatistical model. The geostatistical parameters of the theoretical models of directional semivariograms of the water quality parameters under study, calculated along the wells depth (taking into account the terrain elevation), were used in the ordinary (block) kriging estimation. The obtained results of estimation, i.e., block diagrams allowed us to determine the levels of increased values of estimated averages Z* of underground water quality parameters.
Behmanesh, Iman; Moaveni, Babak
2016-07-01
This paper presents a Hierarchical Bayesian model updating framework to account for the effects of ambient temperature and excitation amplitude. The proposed approach is applied for model calibration, response prediction and damage identification of a footbridge under changing environmental/ambient conditions. The concrete Young's modulus of the footbridge deck is the considered updating structural parameter with its mean and variance modeled as functions of temperature and excitation amplitude. The identified modal parameters over 27 months of continuous monitoring of the footbridge are used to calibrate the updating parameters. One of the objectives of this study is to show that by increasing the levels of information in the updating process, the posterior variation of the updating structural parameter (concrete Young's modulus) is reduced. To this end, the calibration is performed at three information levels using (1) the identified modal parameters, (2) modal parameters and ambient temperatures, and (3) modal parameters, ambient temperatures, and excitation amplitudes. The calibrated model is then validated by comparing the model-predicted natural frequencies and those identified from measured data after deliberate change to the structural mass. It is shown that accounting for modeling error uncertainties is crucial for reliable response prediction, and accounting only the estimated variability of the updating structural parameter is not sufficient for accurate response predictions. Finally, the calibrated model is used for damage identification of the footbridge.
Parameter identification in tidal models with uncertain boundaries
Bagchi, Arunabha; ten Brummelhuis, P.G.J.; ten Brummelhuis, Paul
1994-01-01
In this paper we consider a simultaneous state and parameter estimation procedure for tidal models with random inputs, which is formulated as a minimization problem. It is assumed that some model parameters are unknown and that the random noise inputs only act upon the open boundaries. The
Exploring the interdependencies between parameters in a material model.
Energy Technology Data Exchange (ETDEWEB)
Silling, Stewart Andrew; Fermen-Coker, Muge
2014-01-01
A method is investigated to reduce the number of numerical parameters in a material model for a solid. The basis of the method is to detect interdependencies between parameters within a class of materials of interest. The method is demonstrated for a set of material property data for iron and steel using the Johnson-Cook plasticity model.
An Alternative Three-Parameter Logistic Item Response Model.
Pashley, Peter J.
Birnbaum's three-parameter logistic function has become a common basis for item response theory modeling, especially within situations where significant guessing behavior is evident. This model is formed through a linear transformation of the two-parameter logistic function in order to facilitate a lower asymptote. This paper discusses an…
Parameter identification in tidal models with uncertain boundaries
Bagchi, Arunabha; Brummelhuis, ten Paul
1994-01-01
In this paper we consider a simultaneous state and parameter estimation procedure for tidal models with random inputs, which is formulated as a minimization problem. It is assumed that some model parameters are unknown and that the random noise inputs only act upon the open boundaries. The hyperboli
A compact cyclic plasticity model with parameter evolution
DEFF Research Database (Denmark)
Krenk, Steen; Tidemann, L.
2017-01-01
, and it is demonstrated that this simple formulation enables very accurate representation of experimental results. An extension of the theory to account for model parameter evolution effects, e.g. in the form of changing yield level, is included in the form of extended evolution equations for the model parameters...
Regionalization of SWAT Model Parameters for Use in Ungauged Watersheds
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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.
Modeling of global variations and ring shadowing in Saturn's ionosphere
Moore, L. E.; Mendillo, M.; Müller-Wodarg, I. C. F.; Murr, D. L.
2004-12-01
A time-dependent one-dimensional model of Saturn's ionosphere has been developed as an intermediate step towards a fully coupled Saturn Thermosphere-Ionosphere Model (STIM). A global circulation model (GCM) of the thermosphere provides the latitude and local time dependent neutral atmosphere, from which a globally varying ionosphere is calculated. Four ion species are used (H +, H +2, H +3, and He +) with current cross-sections and reaction rates, and the SOLAR2000 model for the Sun's irradiance. Occultation data from the Voyager photopolarimeter system (PPS) are adapted to model the radial profile of the ultraviolet (UV) optical depth of the rings. Diurnal electron density peak values and heights are generated for all latitudes and two seasons under solar minimum and solar maximum conditions, both with and without shadowing from the rings. Saturn's lower ionosphere is shown to be in photochemical equilibrium, whereas diffusive processes are important in the topside. In agreement with previous 1-D models, the ionosphere is dominated by H + and H +3, with a peak electron density of ˜10 electrons cm -3. At low- and mid-latitudes, H + is the dominant ion, and the electron density exhibits a diurnal maximum during the mid-afternoon. At higher latitudes and shadowed latitudes (smaller ionizing fluxes), the diurnal maximum retreats towards noon, and the ratio of [H +]/[H +3] decreases, with H +3 becoming the dominant ion at altitudes near the peak (˜1200-1600 km) for noon-time hours. Shadowing from the rings leads to attenuation of solar flux, the magnitude and latitudinal structure of which is seasonal. During solstice, the season for the Cassini spacecraft's encounter with Saturn, attenuation has a maximum of two orders of magnitude, causing a reduction in modeled peak electron densities and total electron column contents by as much as a factor of three. Calculations are performed that explore the parameter space for charge-exchange reactions of H + with
Bayesian estimation of parameters in a regional hydrological model
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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
MHD modeling of dense plasma focus electrode shape variation
McLean, Harry; Hartman, Charles; Schmidt, Andrea; Tang, Vincent; Link, Anthony; Ellsworth, Jen; Reisman, David
2013-10-01
The dense plasma focus (DPF) is a very simple device physically, but results to date indicate that very extensive physics is needed to understand the details of operation, especially during the final pinch where kinetic effects become very important. Nevertheless, the overall effects of electrode geometry, electrode size, and drive circuit parameters can be informed efficiently using MHD fluid codes, especially in the run-down phase before the final pinch. These kinds of results can then guide subsequent, more detailed fully kinetic modeling efforts. We report on resistive 2-d MHD modeling results applying the TRAC-II code to the DPF with an emphasis on varying anode and cathode shape. Drive circuit variations are handled in the code using a self-consistent circuit model for the external capacitor bank since the device impedance is strongly coupled to the internal plasma physics. Electrode shape is characterized by the ratio of inner diameter to outer diameter, length to diameter, and various parameterizations for tapering. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
Plasticity in extended phenotypes: orb web architectural responses to variations in prey parameters.
Blamires, Sean J
2010-09-15
A spider orb web is an extended phenotype; it modifies and interacts with the environment, influencing spider physiology. Orb webs are plastic, responding to variations in prey parameters. Studies attempting to understand how nutrients influence spider orb-web plasticity have been hampered by the inability to decouple prey nutrients from other, highly correlated, prey factors and the intrinsic link between prey protein and prey energy concentration. I analyzed the nutrient concentrations of cockroaches, and adult and juvenile crickets to devise experiments that controlled prey protein concentration while varying prey size, ingested mass, energy concentration and feeding frequency of the orb web spider Argiope keyserlingi. I found that A. keyserlingi alters overall architecture according to feeding frequency. Decoration length was inversely related to ingested prey mass and/or energy density in one experiment but directly related to ingested prey mass in another. These contradictory results suggest that factors not examined in this study have a confounding influence on decoration plasticity. As decorations attract prey as well as predators decreasing decoration investment may, in some instances, be attributable to benefits no longer outweighing the risks. Web area was altered according to feeding frequency, and mesh size altered according to feeding frequency and prey length. The number of radii in orb webs was unaffected by prey parameters. A finite amount of silk can be invested in the orb web, so spiders trade-off smaller mesh size with larger web capture area, explaining why feeding frequency influenced both web area and mesh size. Mesh size is additionally responsive to prey size via sensory cues, with spiders constructing webs suitable for catching the most common or most profitable prey.
An empirical model of the quiet daily geomagnetic field variation
Yamazaki, Y.; Yumoto, K.; Cardinal, M.G.; Fraser, B.J.; Hattori, P.; Kakinami, Y.; Liu, J.Y.; Lynn, K.J.W.; Marshall, R.; McNamara, D.; Nagatsuma, T.; Nikiforov, V.M.; Otadoy, R.E.; Ruhimat, M.; Shevtsov, B.M.; Shiokawa, K.; Abe, S.; Uozumi, T.; Yoshikawa, A.
2011-01-01
An empirical model of the quiet daily geomagnetic field variation has been constructed based on geomagnetic data obtained from 21 stations along the 210 Magnetic Meridian of the Circum-pan Pacific Magnetometer Network (CPMN) from 1996 to 2007. Using the least squares fitting method for geomagnetically quiet days (Kp ??? 2+), the quiet daily geomagnetic field variation at each station was described as a function of solar activity SA, day of year DOY, lunar age LA, and local time LT. After interpolation in latitude, the model can describe solar-activity dependence and seasonal dependence of solar quiet daily variations (S) and lunar quiet daily variations (L). We performed a spherical harmonic analysis (SHA) on these S and L variations to examine average characteristics of the equivalent external current systems. We found three particularly noteworthy results. First, the total current intensity of the S current system is largely controlled by solar activity while its focus position is not significantly affected by solar activity. Second, we found that seasonal variations of the S current intensity exhibit north-south asymmetry; the current intensity of the northern vortex shows a prominent annual variation while the southern vortex shows a clear semi-annual variation as well as annual variation. Thirdly, we found that the total intensity of the L current system changes depending on solar activity and season; seasonal variations of the L current intensity show an enhancement during the December solstice, independent of the level of solar activity. Copyright 2011 by the American Geophysical Union.
Kuczera, George; Kavetski, Dmitri; Franks, Stewart; Thyer, Mark
2006-11-01
SummaryCalibration and prediction in conceptual rainfall-runoff (CRR) modelling is affected by the uncertainty in the observed forcing/response data and the structural error in the model. This study works towards the goal of developing a robust framework for dealing with these sources of error and focuses on model error. The characterisation of model error in CRR modelling has been thwarted by the convenient but indefensible treatment of CRR models as deterministic descriptions of catchment dynamics. This paper argues that the fluxes in CRR models should be treated as stochastic quantities because their estimation involves spatial and temporal averaging. Acceptance that CRR models are intrinsically stochastic paves the way for a more rational characterisation of model error. The hypothesis advanced in this paper is that CRR model error can be characterised by storm-dependent random variation of one or more CRR model parameters. A simple sensitivity analysis is used to identify the parameters most likely to behave stochastically, with variation in these parameters yielding the largest changes in model predictions as measured by the Nash-Sutcliffe criterion. A Bayesian hierarchical model is then formulated to explicitly differentiate between forcing, response and model error. It provides a very general framework for calibration and prediction, as well as for testing hypotheses regarding model structure and data uncertainty. A case study calibrating a six-parameter CRR model to daily data from the Abercrombie catchment (Australia) demonstrates the considerable potential of this approach. Allowing storm-dependent variation in just two model parameters (with one of the parameters characterising model error and the other reflecting input uncertainty) yields a substantially improved model fit raising the Nash-Sutcliffe statistic from 0.74 to 0.94. Of particular significance is the use of posterior diagnostics to test the key assumptions about the data and model errors
Parameter Estimation for an Electric Arc Furnace Model Using Maximum Likelihood
Directory of Open Access Journals (Sweden)
Jesser J. Marulanda-Durango
2012-12-01
Full Text Available In this paper, we present a methodology for estimating the parameters of a model for an electrical arc furnace, by using maximum likelihood estimation. Maximum likelihood estimation is one of the most employed methods for parameter estimation in practical settings. The model for the electrical arc furnace that we consider, takes into account the non-periodic and non-linear variations in the voltage-current characteristic. We use NETLAB, an open source MATLAB® toolbox, for solving a set of non-linear algebraic equations that relate all the parameters to be estimated. Results obtained through simulation of the model in PSCADTM, are contrasted against real measurements taken during the furnance's most critical operating point. We show how the model for the electrical arc furnace, with appropriate parameter tuning, captures with great detail the real voltage and current waveforms generated by the system. Results obtained show a maximum error of 5% for the current's root mean square error.
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. ...
Spatio-temporal modeling of nonlinear distributed parameter systems
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
Directory of Open Access Journals (Sweden)
Baker Syed
2011-01-01
Full Text Available Abstract In systems biology, experimentally measured parameters are not always available, necessitating the use of computationally based parameter estimation. In order to rely on estimated parameters, it is critical to first determine which parameters can be estimated for a given model and measurement set. This is done with parameter identifiability analysis. A kinetic model of the sucrose accumulation in the sugar cane culm tissue developed by Rohwer et al. was taken as a test case model. What differentiates this approach is the integration of an orthogonal-based local identifiability method into the unscented Kalman filter (UKF, rather than using the more common observability-based method which has inherent limitations. It also introduces a variable step size based on the system uncertainty of the UKF during the sensitivity calculation. This method identified 10 out of 12 parameters as identifiable. These ten parameters were estimated using the UKF, which was run 97 times. Throughout the repetitions the UKF proved to be more consistent than the estimation algorithms used for comparison.
Baker, Syed Murtuza; Poskar, C Hart; Junker, Björn H
2011-10-11
In systems biology, experimentally measured parameters are not always available, necessitating the use of computationally based parameter estimation. In order to rely on estimated parameters, it is critical to first determine which parameters can be estimated for a given model and measurement set. This is done with parameter identifiability analysis. A kinetic model of the sucrose accumulation in the sugar cane culm tissue developed by Rohwer et al. was taken as a test case model. What differentiates this approach is the integration of an orthogonal-based local identifiability method into the unscented Kalman filter (UKF), rather than using the more common observability-based method which has inherent limitations. It also introduces a variable step size based on the system uncertainty of the UKF during the sensitivity calculation. This method identified 10 out of 12 parameters as identifiable. These ten parameters were estimated using the UKF, which was run 97 times. Throughout the repetitions the UKF proved to be more consistent than the estimation algorithms used for comparison.
Geomagnetically induced currents in Uruguay: Sensitivity to modelling parameters
Caraballo, R.
2016-11-01
According to the traditional wisdom, geomagnetically induced currents (GIC) should occur rarely at mid-to-low latitudes, but in the last decades a growing number of reports have addressed their effects on high-voltage (HV) power grids at mid-to-low latitudes. The growing trend to interconnect national power grids to meet regional integration objectives, may lead to an increase in the size of the present energy transmission networks to form a sort of super-grid at continental scale. Such a broad and heterogeneous super-grid can be exposed to the effects of large GIC if appropriate mitigation actions are not taken into consideration. In the present study, we present GIC estimates for the Uruguayan HV power grid during severe magnetic storm conditions. The GIC intensities are strongly dependent on the rate of variation of the geomagnetic field, conductivity of the ground, power grid resistances and configuration. Calculated GIC are analysed as functions of these parameters. The results show a reasonable agreement with measured data in Brazil and Argentina, thus confirming the reliability of the model. The expansion of the grid leads to a strong increase in GIC intensities in almost all substations. The power grid response to changes in ground conductivity and resistances shows similar results in a minor extent. This leads us to consider GIC as a non-negligible phenomenon in South America. Consequently, GIC must be taken into account in mid-to-low latitude power grids as well.
Simple Penalties on Maximum-Likelihood Estimates of Genetic Parameters to Reduce Sampling Variation.
Meyer, Karin
2016-08-01
Multivariate estimates of genetic parameters are subject to substantial sampling variation, especially for smaller data sets and more than a few traits. A simple modification of standard, maximum-likelihood procedures for multivariate analyses to estimate genetic covariances is described, which can improve estimates by substantially reducing their sampling variances. This is achieved by maximizing the likelihood subject to a penalty. Borrowing from Bayesian principles, we propose a mild, default penalty-derived assuming a Beta distribution of scale-free functions of the covariance components to be estimated-rather than laboriously attempting to determine the stringency of penalization from the data. An extensive simulation study is presented, demonstrating that such penalties can yield very worthwhile reductions in loss, i.e., the difference from population values, for a wide range of scenarios and without distorting estimates of phenotypic covariances. Moreover, mild default penalties tend not to increase loss in difficult cases and, on average, achieve reductions in loss of similar magnitude to computationally demanding schemes to optimize the degree of penalization. Pertinent details required for the adaptation of standard algorithms to locate the maximum of the likelihood function are outlined.
Purves, R D
1994-02-01
Noncompartmental investigation of the distribution of residence times from concentration-time data requires estimation of the second noncentral moment (AUM2C) as well as the area under the curve (AUC) and the area under the moment curve (AUMC). The accuracy and precision of 12 numerical integration methods for AUM2C were tested on simulated noisy data sets representing bolus, oral, and infusion concentration-time profiles. The root-mean-squared errors given by the best methods were only slightly larger than the corresponding errors in the estimation of AUC and AUMC. AUM2C extrapolated "tail" areas as estimated from a log-linear fit are biased, but the bias is minimized by application of a simple correction factor. The precision of estimates of variance of residence times (VRT) can be severely impaired by the variance of the extrapolated tails. VRT is therefore not a useful parameter unless the tail areas are small or can be shown to be estimated with little error. Estimates of the coefficient of variation of residence times (CVRT) and its square (CV2) are robust in the sense of being little affected by errors in the concentration values. The accuracy of estimates of CVRT obtained by optimum numerical methods is equal to or better than that of AUC and mean residence time estimates, even in data sets with large tail areas.
Weigand, M.; Kemna, A.
2016-06-01
Spectral induced polarization (SIP) data are commonly analysed using phenomenological models. Among these models the Cole-Cole (CC) model is the most popular choice to describe the strength and frequency dependence of distinct polarization peaks in the data. More flexibility regarding the shape of the spectrum is provided by decomposition schemes. Here the spectral response is decomposed into individual responses of a chosen elementary relaxation model, mathematically acting as kernel in the involved integral, based on a broad range of relaxation times. A frequently used kernel function is the Debye model, but also the CC model with some other a priorly specified frequency dispersion (e.g. Warburg model) has been proposed as kernel in the decomposition. The different decomposition approaches in use, also including conductivity and resistivity formulations, pose the question to which degree the integral spectral parameters typically derived from the obtained relaxation time distribution are biased by the approach itself. Based on synthetic SIP data sampled from an ideal CC response, we here investigate how the two most important integral output parameters deviate from the corresponding CC input parameters. We find that the total chargeability may be underestimated by up to 80 per cent and the mean relaxation time may be off by up to three orders of magnitude relative to the original values, depending on the frequency dispersion of the analysed spectrum and the proximity of its peak to the frequency range limits considered in the decomposition. We conclude that a quantitative comparison of SIP parameters across different studies, or the adoption of parameter relationships from other studies, for example when transferring laboratory results to the field, is only possible on the basis of a consistent spectral analysis procedure. This is particularly important when comparing effective CC parameters with spectral parameters derived from decomposition results.
Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model
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.
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.
Tube-Load Model Parameter Estimation for Monitoring Arterial Hemodynamics
Directory of Open Access Journals (Sweden)
Guanqun eZhang
2011-11-01
Full Text Available A useful model of the arterial system is the uniform, lossless tube with parametric load. This tube-load model is able to account for wave propagation and reflection (unlike lumped-parameter models such as the Windkessel while being defined by only a few parameters (unlike comprehensive distributed-parameter models. As a result, the parameters may be readily estimated by accurate fitting of the model to available arterial pressure and flow waveforms so as to permit improved monitoring of arterial hemodynamics. In this paper, we review tube-load model parameter estimation techniques that have appeared in the literature for monitoring wave reflection, large artery compliance, pulse transit time, and central aortic pressure. We begin by motivating the use of the tube-load model for parameter estimation. We then describe the tube-load model, its assumptions and validity, and approaches for estimating its parameters. We next summarize the various techniques and their experimental results while highlighting their advantages over conventional techniques. We conclude the review by suggesting future research directions and describing potential applications.
Tube-Load Model Parameter Estimation for Monitoring Arterial Hemodynamics
Zhang, Guanqun; Hahn, Jin-Oh; Mukkamala, Ramakrishna
2011-01-01
A useful model of the arterial system is the uniform, lossless tube with parametric load. This tube-load model is able to account for wave propagation and reflection (unlike lumped-parameter models such as the Windkessel) while being defined by only a few parameters (unlike comprehensive distributed-parameter models). As a result, the parameters may be readily estimated by accurate fitting of the model to available arterial pressure and flow waveforms so as to permit improved monitoring of arterial hemodynamics. In this paper, we review tube-load model parameter estimation techniques that have appeared in the literature for monitoring wave reflection, large artery compliance, pulse transit time, and central aortic pressure. We begin by motivating the use of the tube-load model for parameter estimation. We then describe the tube-load model, its assumptions and validity, and approaches for estimating its parameters. We next summarize the various techniques and their experimental results while highlighting their advantages over conventional techniques. We conclude the review by suggesting future research directions and describing potential applications. PMID:22053157
Algorithm for Tree Growth Modeling Based on Random Parameters and ARMA
Directory of Open Access Journals (Sweden)
Lichun Jiang
2013-08-01
Full Text Available Chapman-Richards function is used to model growth data of dahurian larch (Larix gmelinii Rupr. from longitudinal measurements using nonlinear mixed-effects modeling approach. The parameter variation in the model was divided into random effects, fixed effects and variance-covariance structure. The values for fixed effects parameters and the variance-covariance matrix of random effects were estimated using NLME function in S-plus software. Autocorrelation structure was considered for explaining the dependency among multiple measurements within the individuals. Information criterion statistics (AIC, BIC and Likelihood ratio test are used for comparing different structures of the random effects components. These methods are illustrated using the nonlinear mixed-effects methods in S-Plus software. Results showed that the Chapman-Richards model with three random parameters could typically depict the dahurian larch tree growth in northeastern China. The mixed-effects model provided better performance and more precise estimations than the fixed-effects model.
Parameter estimation and investigation of a bolted joint model
Shiryayev, O. V.; Page, S. M.; Pettit, C. L.; Slater, J. C.
2007-11-01
Mechanical joints are a primary source of variability in the dynamics of built-up structures. Physical phenomena in the joint are quite complex and therefore too impractical to model at the micro-scale. This motivates the development of lumped parameter joint models with discrete interfaces so that they can be easily implemented in finite element codes. Among the most important considerations in choosing a model for dynamically excited systems is its ability to model energy dissipation. This translates into the need for accurate and reliable methods to measure model parameters and estimate their inherent variability from experiments. The adjusted Iwan model was identified as a promising candidate for representing joint dynamics. Recent research focused on this model has exclusively employed impulse excitation in conjunction with neural networks to identify the model parameters. This paper presents an investigation of an alternative parameter estimation approach for the adjusted Iwan model, which employs data from oscillatory forcing. This approach is shown to produce parameter estimates with precision similar to the impulse excitation method for a range of model parameters.
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.
Parameter estimation of hidden periodic model in random fields
Institute of Scientific and Technical Information of China (English)
何书元
1999-01-01
Two-dimensional hidden periodic model is an important model in random fields. The model is used in the field of two-dimensional signal processing, prediction and spectral analysis. A method of estimating the parameters for the model is designed. The strong consistency of the estimators is proved.
Nicastri, M; Chiarella, G; Gallo, L V; Catalano, M; Cassandro, E
2004-12-01
The introduction, in the late 70s, of the first digital spectrograph (DSP Sonograph) by Kay Elemetrics has improved the possibilities of spectroacoustic voice analysis in the clinical field. Thanks to the marketing, in 1993, of the Multi Dimensional Voice Program (MDVP) advanced system, it is now possible to analyse 33 quantitative voice parameters which, in turn, allow evaluation of fundamental frequency, amplitude and spectral energy balance and the presence of any sonority gap and diplophony. Despite its potentials, the above-mentioned system is not widely used yet, partly on account of the lack of a standard procedure. Indeed, there are still only a few case reports in the literature taking into consideration prescriptive aspects related both to procedure and analysis. This study aims to provide the results of amplitude perturbation parameter analysis in euphonic adult patients. In our opinion, these are the most significant parameters in determining the severity of a phonation disorder. The study has been carried out on 35 patients (24 female, 11 male, mean age 31.6 years, range 19-59). The voice signal has been recorded using a 4300 B Kay Computer Speech Lab (CSL) supported by a personal computer including a SM48 Shure-Prolog microphone located at a distance of 15 cm and angled at 45 degrees. Input microphone saturation has been adjusted to 6/9 of the CH1 channel. The voice sample consisted in a held /a/ and the analysis has been carried out on the central 3 seconds of the recording. The analysis has been carried out using a 5105 MDVP software version 2.3 and the signal digitalised at a 50 kHz sample rate. In order for the sample to be as free from intensity or frequency changes as possible, each patient underwent a training session (including at least 3 phonation tests) before the recording. The study included only emissions between 55 and 65 dB and with spectrum stability. Environmental noise has constantly been monitored and maintained below 30 dB. Data
Model-based reconstruction for illumination variation in face images
Boom, B.J.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.
2008-01-01
We propose a novel method to correct for arbitrary illumination variation in the face images. The main purpose is to improve recognition results of face images taken under uncontrolled illumination conditions. We correct the illumination variation in the face images using a face shape model, which
Modeling the effects of developmental variation on insect phenology.
Yurk, Brian P; Powell, James A
2010-08-01
Phenology, the timing of developmental events such as oviposition or pupation, is highly dependent on temperature; since insects are ectotherms, the time it takes them to complete a life stage (development time) depends on the temperatures they experience. This dependence varies within and between populations due to variation among individuals that is fixed within a life stage (giving rise to what we call persistent variation) and variation from random effects within a life stage (giving rise to what we call random variation). It is important to understand how both types of variation affect phenology if we are to predict the effects of climate change on insect populations.We present three nested phenology models incorporating increasing levels of variation. First, we derive an advection equation to describe the temperature-dependent development of a population with no variation in development time. This model is extended to incorporate persistent variation by introducing a developmental phenotype that varies within a population, yielding a phenotype-dependent advection equation. This is further extended by including a diffusion term describing random variation in a phenotype-dependent Fokker-Planck development equation. These models are also novel because they are formulated in terms of development time rather than developmental rate; development time can be measured directly in the laboratory, whereas developmental rate is calculated by transforming laboratory data. We fit the phenology models to development time data for mountain pine beetles (MPB) (Dendroctonus ponderosae Hopkins [Coleoptera: Scolytidae]) held at constant temperatures in laboratory experiments. The nested models are parameterized using a maximum likelihood approach. The results of the parameterization show that the phenotype-dependent advection model provides the best fit to laboratory data, suggesting that MPB phenology may be adequately described in terms of persistent variation alone. MPB
Parameters causing variation between soil screening values and the effect of harmonization
Provoost, J.; Reijnders, L.; Swartjes, F.; Bronders, J.; Carlon, C.; D'Alessandro, M.; Cornelis, C.
2008-01-01
Background, aim, and scope: This paper discusses the variation between generic soil screening values (SSV) from 17 countries for 11 volatile organic contaminants (VOC). The variation between SSV was one to four orders-of-magnitude (OOM) depending on the SSV and landuse type. What would be the variat
Modeling of Craniofacial Anatomy, Variation, and Growth
DEFF Research Database (Denmark)
Thorup, Signe Strann
The topic of this thesis is automatic analysis of craniofacial images with respect to changes due to growth and surgery, inter-subject variation and intracranial volume estimation. The methods proposed contribute to the knowledge about specific craniofacial anomalies, as well as provide a tool...... for detailed analyses for clinical and research purposes. Most of the applications in this thesis rely on non-rigid image registration by the means of warping one image into the coordinate system of another image. This warping results in a deformation field that describes the anatomical correspondence between...... the two images. To elaborate further: a computational atlas of the average anatomy was constructed. Using non-rigid registration, image data from a subject is automatically transformed into the coordinate space of the atlas. In this process, all knowledge built into the atlas is transferred to the subject...
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.
Estimating parameters for generalized mass action models with connectivity information
Directory of Open Access Journals (Sweden)
Voit Eberhard O
2009-05-01
Full Text Available Abstract Background Determining the parameters of a mathematical model from quantitative measurements is the main bottleneck of modelling biological systems. Parameter values can be estimated from steady-state data or from dynamic data. The nature of suitable data for these two types of estimation is rather different. For instance, estimations of parameter values in pathway models, such as kinetic orders, rate constants, flux control coefficients or elasticities, from steady-state data are generally based on experiments that measure how a biochemical system responds to small perturbations around the steady state. In contrast, parameter estimation from dynamic data requires time series measurements for all dependent variables. Almost no literature has so far discussed the combined use of both steady-state and transient data for estimating parameter values of biochemical systems. Results In this study we introduce a constrained optimization method for estimating parameter values of biochemical pathway models using steady-state information and transient measurements. The constraints are derived from the flux connectivity relationships of the system at the steady state. Two case studies demonstrate the estimation results with and without flux connectivity constraints. The unconstrained optimal estimates from dynamic data may fit the experiments well, but they do not necessarily maintain the connectivity relationships. As a consequence, individual fluxes may be misrepresented, which may cause problems in later extrapolations. By contrast, the constrained estimation accounting for flux connectivity information reduces this misrepresentation and thereby yields improved model parameters. Conclusion The method combines transient metabolic profiles and steady-state information and leads to the formulation of an inverse parameter estimation task as a constrained optimization problem. Parameter estimation and model selection are simultaneously carried out
An improved state-parameter analysis of ecosystem models using data assimilation
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
Pawar, D D; Mapari, R V
2016-01-01
The main purpose of the present paper is to investigate LRS Bianchi type I metric in the presence of perfect fluid and dark energy. In order to obtain a deterministic solution of the field equations we have assumed that, the two sources of the perfect fluid and dark energy interact minimally with separate conservation of their energy momentum tensors. The EoS parameter of the perfect fluid is also assumed to be constant. In addition to these we have used a special law of variation of Hubble parameter proposed by Berman that yields constant deceleration parameter. For two different values of the constant deceleration parameters we have obtained two different cosmological models. The physical behaviors of both the models have been discussed by using some physical parameters.
Analysis and modeling of solar irradiance variations
Yeo, K L
2014-01-01
A prominent manifestation of the solar dynamo is the 11-year activity cycle, evident in indicators of solar activity, including solar irradiance. Although a relationship between solar activity and the brightness of the Sun had long been suspected, it was only directly observed after regular satellite measurements became available with the launch of Nimbus-7 in 1978. The measurement of solar irradiance from space is accompanied by the development of models aimed at describing the apparent variability by the intensity excess/deficit effected by magnetic structures in the photosphere. The more sophisticated models, termed semi-empirical, rely on the intensity spectra of photospheric magnetic structures generated with radiative transfer codes from semi-empirical model atmospheres. An established example of such models is SATIRE-S (Spectral And Total Irradiance REconstruction for the Satellite era). One key limitation of current semi-empirical models is the fact that the radiant properties of network and faculae a...
A comprehensive parameter study of an active magnetic regenerator using a 2D numerical model
DEFF Research Database (Denmark)
Nielsen, Kaspar Kirstein; Bahl, Christian Robert Haffenden; Smith, Anders
2010-01-01
A two-dimensional numerical heat transfer model is used to investigate an active magnetic regenerator (AMR) based on parallel plates of magnetocaloric material. A large range of parameter variations are performed to study the optimal AMR. The parameters varied are the plate and channel thicknesses......, cycle frequency and fluid movement. These are cast into the non-dimensional units utilization, porosity and number of transfer units (NTU). The cooling capacity vs. temperature span is mapped as a function of these parameters and each configuration is evaluated through the maximum temperature span...
Towards predictive food process models: A protocol for parameter estimation.
Vilas, Carlos; Arias-Méndez, Ana; Garcia, Miriam R; Alonso, Antonio A; Balsa-Canto, E
2016-05-31
Mathematical models, in particular, physics-based models, are essential tools to food product and process design, optimization and control. The success of mathematical models relies on their predictive capabilities. However, describing physical, chemical and biological changes in food processing requires the values of some, typically unknown, parameters. Therefore, parameter estimation from experimental data is critical to achieving desired model predictive properties. This work takes a new look into the parameter estimation (or identification) problem in food process modeling. First, we examine common pitfalls such as lack of identifiability and multimodality. Second, we present the theoretical background of a parameter identification protocol intended to deal with those challenges. And, to finish, we illustrate the performance of the proposed protocol with an example related to the thermal processing of packaged foods.
Estimation of the input parameters in the Feller neuronal model
Ditlevsen, Susanne; Lansky, Petr
2006-06-01
The stochastic Feller neuronal model is studied, and estimators of the model input parameters, depending on the firing regime of the process, are derived. Closed expressions for the first two moments of functionals of the first-passage time (FTP) through a constant boundary in the suprathreshold regime are derived, which are used to calculate moment estimators. In the subthreshold regime, the exponentiality of the FTP is utilized to characterize the input parameters. The methods are illustrated on simulated data. Finally, approximations of the first-passage-time moments are suggested, and biological interpretations and comparisons of the parameters in the Feller and the Ornstein-Uhlenbeck models are discussed.
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.
A Model of Genetic Variation in Human Social Networks
Fowler, James H; Christakis, Nicholas A
2008-01-01
Social networks influence the evolution of cooperation and they exhibit strikingly systematic patterns across a wide range of human contexts. Both of these facts suggest that variation in the topological attributes of human social networks might have a genetic basis. While genetic variation accounts for a significant portion of the variation in many complex social behaviors, the heritability of egocentric social network attributes is unknown. Here we show that three of these attributes (in-degree, transitivity, and centrality) are heritable. We then develop a "mirror network" method to test extant network models and show that none accounts for observed genetic variation in human social networks. We propose an alternative "attract and introduce" model that generates significant heritability as well as other important network features, and we show that this model with two simple forms of heterogeneity is well suited to the modeling of real social networks in humans. These results suggest that natural selection ...
Modelling asteroid brightness variations. I - Numerical methods
Karttunen, H.
1989-01-01
A method for generating lightcurves of asteroid models is presented. The effects of the shape of the asteroid and the scattering law of a surface element are distinctly separable, being described by chosen functions that can easily be changed. The shape is specified by means of two functions that yield the length of the radius vector and the normal vector of the surface at a given point. The general shape must be convex, but spherical concavities producing macroscopic shadowing can also be modeled.
An automatic and effective parameter optimization method for model tuning
Directory of Open Access Journals (Sweden)
T. Zhang
2015-05-01
Full Text Available Physical parameterizations in General Circulation Models (GCMs, having various uncertain parameters, greatly impact model performance and model climate sensitivity. Traditional manual and empirical tuning of these parameters is time consuming and ineffective. In this study, a "three-step" methodology is proposed to automatically and effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. Different from the traditional optimization methods, two extra steps, one determines parameter sensitivity and the other chooses the optimum initial value of sensitive parameters, are introduced before the downhill simplex method to reduce the computational cost and improve the tuning performance. Atmospheric GCM 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 parameters tuning during the model development stage.
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
Bianchi type-V dark energy model with varying EoS parameter
Saha, Bijan
2012-01-01
Within the scope of an anisotropic Bianchi type-V cosmological model we have studied the evolution of the universe. The assumption of a diagonal energy-momentum tensor leads to some severe restriction on the metric functions, which on its part imposes restriction on the components of the energy momentum tensor. This model allows anisotropic matter distribution. Further using the proportionality condition that relates the shear scalar $(\\sigma)$ in the model is proportional to expansion scalar $(\\vartheta)$ and the variation law of Hubble parameter, connecting Hubble parameter with volume scale. Exact solution to the corresponding equations are obtained. The EoS parameter for dark energy as well as deceleration parameter is found to be the time varying functions. A qualitative picture of the evolution of the universe corresponding to different of its stages is given using the latest observational data.
Directory of Open Access Journals (Sweden)
Miholca CONSTANTIN
2008-07-01
Full Text Available The paper presents a method of mathematical modelling of a solar converter using the results of full-scale testing. The advantages of analytical modelling method applied to photovoltaic systems are also presented; this is because the model parameters are directly measurable by data acquisition from the photovoltaic field consisting of photovoltaic cells type Z - (mono-crystalline photovoltaic. The model parameter also includes both the photovoltaic cell characteristics as a device (forming the photovoltaic field and the temperature influence on the photovoltaic field performance. The results of the photovoltaic model numerical simulation (PV to the major parameters conversion variation can also be used to design and assess the performance of low and medium - power photovoltaic systems operating in single regime (to supply the home appliances.
Parameter variation and scenario analysis in impact assessments of emerging energy technologies
Breunig, Hanna Marie
There is a global need for energy technologies that reduce the adverse impacts of societal progress and that address today's challenges without creating tomorrow's problems. Life cycle impact assessment (LCIA) can support technology developers in achieving these prerequisites of sustainability by providing a systems perspective. However, modeling the early-stage scale up and impacts of technology systems may lead to unreliable or incomplete results due to a lack of representative technical, spatial, and temporal data. The goal of this dissertation is to support the acceleration of clean energy technology development by providing information about the regional variation of impacts and benefits resulting from plausible deployment scenarios. Three emerging energy technologies are selected as case studies: (1) brine management for carbon dioxide sequestration; (2) carbon dioxide capture, utilization, and sequestration; (3) stationary fuel cells for combined heat and power in commercial buildings. In all three case studies, priority areas are identified where more reliable data and models are necessary for reducing uncertainty, and vital information is revealed on how impacts vary spatially and temporally. Importantly, moving away from default technology and waste management hierarchies as a source of data fosters goal-driven systems thinking which in turn leads to the discovery of technology improvement potentials.
Do Lumped-Parameter Models Provide the Correct Geometrical Damping?
DEFF Research Database (Denmark)
Andersen, Lars
This paper concerns the formulation of lumped-parameter models for rigid footings on homogenous or stratified soil. Such models only contain a few degrees of freedom, which makes them ideal for inclusion in aero-elastic codes for wind turbines and other models applied to fast evaluation of struct......This paper concerns the formulation of lumped-parameter models for rigid footings on homogenous or stratified soil. Such models only contain a few degrees of freedom, which makes them ideal for inclusion in aero-elastic codes for wind turbines and other models applied to fast evaluation...... response during excitation and the geometrical damping related to free vibrations of a hexagonal footing. The optimal order of a lumped-parameter model is determined for each degree of freedom, i.e. horizontal and vertical translation as well as torsion and rocking. In particular, the necessity of coupling...... between horizontal sliding and rocking is discussed....
A New Approach for Parameter Optimization in Land Surface Model
Institute of Scientific and Technical Information of China (English)
LI Hongqi; GUO Weidong; SUN Guodong; ZHANG Yaocun; FU Congbin
2011-01-01
In this study,a new parameter optimization method was used to investigate the expansion of conditional nonlinear optimal perturbation (CNOP) in a land surface model (LSM) using long-term enhanced field observations at Tongyn station in Jilin Province,China,combined with a sophisticated LSM (common land model,CoLM).Tongyu station is a reference site of the international Coordinated Energy and Water Cycle Observations Project (CEOP) that has studied semiarid regions that have undergone desertification,salination,and degradation since late 1960s.In this study,three key land-surface parameters,namely,soil color,proportion of sand or clay in soil,and leaf-area index were chosen as parameters to be optimized.Our study comprised three experiments:First,a single-parameter optimization was performed,while the second and third experiments performed triple- and six-parameter optinizations,respectively.Notable improvements in simulating sensible heat flux (SH),latent heat flux (LH),soil temperature (TS),and moisture (MS) at shallow layers were achieved using the optimized parameters.The multiple-parameter optimization experiments performed better than the single-parameter experminent.All results demonstrate that the CNOP method can be used to optimize expanded parameters in an LSM.Moreover,clear mathematical meaning,simple design structure,and rapid computability give this method great potential for further application to parameter optimization in LSMs.
Seasonal variations in blood parameters of the Amazonian manatee, Trichechus inunguis
Directory of Open Access Journals (Sweden)
Elton P. Colares
2000-01-01
Full Text Available Seasonal variations in body weight, food consumption and blood glucose, total lipids, urea, total proteins, albumin and globulins of captive Amazonian manatees, Trichechus inunguis, were determined. Body weight changed significantly along the year, increasing from autumn to spring and decreasing in summer. The mean daily food intake of paragrass remained almost unchanged along the year. Paragrass administered to the manatees showed important variations in crude protein and lipid content along the year. No significant differences in blood parameters were registered between males and females in all seasons. Further, there were no significant differences in blood total proteins, albumin and globulins along the year. On the other hand, significant differences in the mean blood glucose, lipids and urea were registered. An increase in the blood glucose in the spring and summer was observed. Blood urea and lipids levels were positively related to paragrass protein and lipids content. These two correlations suggested that these blood parameters are good indicators of the animal nutritional status in the Amazonian manatee.Variações sasonais no peso do corpo, consumo de alimento e glicose, lípides totais, uréia, proteínas totais, albumina e globulinas do sangue de Peixes bois cativos, Trichechus inunguis, foram determinadas. Houve diferença significativa no peso dos animais ao longo do ano, sendo este aumento entre o outono e a primavera e decresce no verão. O consumo de capim colônia não variou ao longo do ano. A composição de proteína bruta e lipídeos totais de capim colônia dado aos animais mostrou importante variação ao longo do ano. Não foi verificado nenhuma variação nas concentrações dos parâmetros sagüíneos estudados entre os sexos em todas as estações. Também não foi verificado diferenças significativas nas concentrações sangüíneas de proteínas totais, albumina e globulinas ao longo do ano. Por outro lado
Parameter Estimation for a Computable General Equilibrium Model
DEFF Research Database (Denmark)
Arndt, Channing; Robinson, Sherman; Tarp, Finn
. Second, it permits incorporation of prior information on parameter values. Third, it can be applied in the absence of copious data. Finally, it supplies measures of the capacity of the model to reproduce the historical record and the statistical significance of parameter estimates. The method is applied...
Retrospective forecast of ETAS model with daily parameters estimate
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.
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.
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...
Parameter Estimates in Differential Equation Models for Population Growth
Winkel, Brian J.
2011-01-01
We estimate the parameters present in several differential equation models of population growth, specifically logistic growth models and two-species competition models. We discuss student-evolved strategies and offer "Mathematica" code for a gradient search approach. We use historical (1930s) data from microbial studies of the Russian biologist,…
Dynamic Modeling and Parameter Identification of Power Systems
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
@@ The generator, the excitation system, the steam turbine and speed governor, and the load are the so called four key models of power systems. Mathematical modeling and parameter identification for the four key models are of great importance as the basis for designing, operating, and analyzing power systems.
Dynamic Load Model using PSO-Based Parameter Estimation
Taoka, Hisao; Matsuki, Junya; Tomoda, Michiya; Hayashi, Yasuhiro; Yamagishi, Yoshio; Kanao, Norikazu
This paper presents a new method for estimating unknown parameters of dynamic load model as a parallel composite of a constant impedance load and an induction motor behind a series constant reactance. An adequate dynamic load model is essential for evaluating power system stability, and this model can represent the behavior of actual load by using appropriate parameters. However, the problem of this model is that a lot of parameters are necessary and it is not easy to estimate a lot of unknown parameters. We propose an estimating method based on Particle Swarm Optimization (PSO) which is a non-linear optimization method by using the data of voltage, active power and reactive power measured at voltage sag.
Parameter Estimation for the Thurstone Case III Model.
Mackay, David B.; Chaiy, Seoil
1982-01-01
The ability of three estimation criteria to recover parameters of the Thurstone Case V and Case III models from comparative judgment data was investigated via Monte Carlo techniques. Significant differences in recovery are shown to exist. (Author/JKS)
Xu, Xiao Bing; Zhan, Tony Liang Tong; Chen, Yun Min; Guo, Qi Gang
2015-02-01
The methods to determine the parameters of a one-dimensional compression model for landfilled municipal solid waste were investigated. In order to test the methods for parameter determination, long-term laboratory compression experiments were carried out under different surcharge loads (i.e. 100, 200 and 400 kPa). Based on the measured compression strain and the reported creep index, the modified primary compression indexes, pre-consolidation pressure and ultimate biodegradation-induced secondary compression strain were determined using the proposed methods. It was found that the simulated compression could not capture the measured secondary compression behavior when using a constant value of biodegradation-induced compression rate coefficient. The variation of the rate coefficient with the change of decomposition rate should be considered during modeling. Accordingly, the biodegradation-induced secondary compression strain in the compression model should be expressed in an incremental form in order to consider the variation of the rate coefficient.
Institute of Scientific and Technical Information of China (English)
Youlong XIA; Zong-Liang YANG; Paul L. STOFFA; Mrinal K. SEN
2005-01-01
Most previous land-surface model calibration studies have defined global ranges for their parameters to search for optimal parameter sets. Little work has been conducted to study the impacts of realistic versus global ranges as well as model complexities on the calibration and uncertainty estimates. The primary purpose of this paper is to investigate these impacts by employing Bayesian Stochastic Inversion (BSI)to the Chameleon Surface Model (CHASM). The CHASM was designed to explore the general aspects of land-surface energy balance representation within a common modeling framework that can be run from a simple energy balance formulation to a complex mosaic type structure. The BSI is an uncertainty estimation technique based on Bayes theorem, importance sampling, and very fast simulated annealing.The model forcing data and surface flux data were collected at seven sites representing a wide range of climate and vegetation conditions. For each site, four experiments were performed with simple and complex CHASM formulations as well as realistic and global parameter ranges. Twenty eight experiments were conducted and 50 000 parameter sets were used for each run. The results show that the use of global and realistic ranges gives similar simulations for both modes for most sites, but the global ranges tend to produce some unreasonable optimal parameter values. Comparison of simple and complex modes shows that the simple mode has more parameters with unreasonable optimal values. Use of parameter ranges and model complexities have significant impacts on frequency distribution of parameters, marginal posterior probability density functions, and estimates of uncertainty of simulated sensible and latent heat fluxes.Comparison between model complexity and parameter ranges shows that the former has more significant impacts on parameter and uncertainty estimations.
Variational Data Assimilation for Optimizing Boundary Conditions in Ocean Models
Kazantsev, Christine; Tolstykh, Mikhail
2016-01-01
The review describes the development of ideas Gury Ivanovich Marchuk in the field of variational data assimilation for ocean models applied in particular in coupled models for long-range weather forecasts. Particular attention is paid to the optimization of boundary conditions on rigid boundaries. As idealized and realistic model configurations are considered. It is shown that the optimization allows us to determine the most sensitive model operators and bring the model solution closer to the assimilated data.
Variations of Shape in Industrial Geometric Models
Veelo, Bastiaan Niels
2004-01-01
This thesis presents an approach to free-form surface manipulations, which conceptually improves an existing CAD system that constructs surfaces by smoothly interpolating a network of intersecting curves. There are no regularity requirements on the network, which already yields superior modelling capabilities compared to systems that are based on industry-standard NURBS surfaces. Originally, the shape of such a surface can be modified only locally by manipulating a curve in the network. In t...
Institute of Scientific and Technical Information of China (English)
HUANG; Sixun; HAN; Wei; WU; Rongsheng
2004-01-01
In the present work, the data assimilation problem in meteorology and physical oceanography is re-examined using the variational optimal control approaches in combination with regularization techniques in inverse problem. Here the estimations of the initial condition,boundary condition and model parameters are performed simultaneously in the framework of variational data assimilation. To overcome the difficulty of ill-posedness, especially for the model parameters distributed in space and time, an additional term is added into the cost functional as a stabilized functional. Numerical experiments show that even with noisy observations the initial conditions and model parameters are recovered to an acceptable degree of accuracy.
Comparing spatial and temporal transferability of hydrological model parameters
Patil, Sopan D.; Stieglitz, Marc
2015-06-01
Operational use of hydrological models requires the transfer of calibrated parameters either in time (for streamflow forecasting) or space (for prediction at ungauged catchments) or both. Although the effects of spatial and temporal parameter transfer on catchment streamflow predictions have been well studied individually, a direct comparison of these approaches is much less documented. Here, we compare three different schemes of parameter transfer, viz., temporal, spatial, and spatiotemporal, using a spatially lumped hydrological model called EXP-HYDRO at 294 catchments across the continental United States. Results show that the temporal parameter transfer scheme performs best, with lowest decline in prediction performance (median decline of 4.2%) as measured using the Kling-Gupta efficiency metric. More interestingly, negligible difference in prediction performance is observed between the spatial and spatiotemporal parameter transfer schemes (median decline of 12.4% and 13.9% respectively). We further demonstrate that the superiority of temporal parameter transfer scheme is preserved even when: (1) spatial distance between donor and receiver catchments is reduced, or (2) temporal lag between calibration and validation periods is increased. Nonetheless, increase in the temporal lag between calibration and validation periods reduces the overall performance gap between the three parameter transfer schemes. Results suggest that spatiotemporal transfer of hydrological model parameters has the potential to be a viable option for climate change related hydrological studies, as envisioned in the "trading space for time" framework. However, further research is still needed to explore the relationship between spatial and temporal aspects of catchment hydrological variability.
Combined Estimation of Hydrogeologic Conceptual Model and Parameter Uncertainty
Energy Technology Data Exchange (ETDEWEB)
Meyer, Philip D.; Ye, Ming; Neuman, Shlomo P.; Cantrell, Kirk J.
2004-03-01
The objective of the research described in this report is the development and application of a methodology for comprehensively assessing the hydrogeologic uncertainties involved in dose assessment, including uncertainties associated with conceptual models, parameters, and scenarios. This report describes and applies a statistical method to quantitatively estimate the combined uncertainty in model predictions arising from conceptual model and parameter uncertainties. The method relies on model averaging to combine the predictions of a set of alternative models. Implementation is driven by the available data. When there is minimal site-specific data the method can be carried out with prior parameter estimates based on generic data and subjective prior model probabilities. For sites with observations of system behavior (and optionally data characterizing model parameters), the method uses model calibration to update the prior parameter estimates and model probabilities based on the correspondence between model predictions and site observations. The set of model alternatives can contain both simplified and complex models, with the requirement that all models be based on the same set of data. The method was applied to the geostatistical modeling of air permeability at a fractured rock site. Seven alternative variogram models of log air permeability were considered to represent data from single-hole pneumatic injection tests in six boreholes at the site. Unbiased maximum likelihood estimates of variogram and drift parameters were obtained for each model. Standard information criteria provided an ambiguous ranking of the models, which would not justify selecting one of them and discarding all others as is commonly done in practice. Instead, some of the models were eliminated based on their negligibly small updated probabilities and the rest were used to project the measured log permeabilities by kriging onto a rock volume containing the six boreholes. These four
Parameter Estimation for Groundwater Models under Uncertain Irrigation Data.
Demissie, Yonas; Valocchi, Albert; Cai, Ximing; Brozovic, Nicholas; Senay, Gabriel; Gebremichael, Mekonnen
2015-01-01
The success of modeling groundwater is strongly influenced by the accuracy of the model parameters that are used to characterize the subsurface system. However, the presence of uncertainty and possibly bias in groundwater model source/sink terms may lead to biased estimates of model parameters and model predictions when the standard regression-based inverse modeling techniques are used. This study first quantifies the levels of bias in groundwater model parameters and predictions due to the presence of errors in irrigation data. Then, a new inverse modeling technique called input uncertainty weighted least-squares (IUWLS) is presented for unbiased estimation of the parameters when pumping and other source/sink data are uncertain. The approach uses the concept of generalized least-squares method with the weight of the objective function depending on the level of pumping uncertainty and iteratively adjusted during the parameter optimization process. We have conducted both analytical and numerical experiments, using irrigation pumping data from the Republican River Basin in Nebraska, to evaluate the performance of ordinary least-squares (OLS) and IUWLS calibration methods under different levels of uncertainty of irrigation data and calibration conditions. The result from the OLS method shows the presence of statistically significant (p irrigation pumping uncertainties during the calibration procedures, the proposed IUWLS is able to minimize the bias effectively without adding significant computational burden to the calibration processes.
Parameter estimation for groundwater models under uncertain irrigation data
Demissie, Yonas; Valocchi, Albert J.; Cai, Ximing; Brozovic, Nicholas; Senay, Gabriel; Gebremichael, Mekonnen
2015-01-01
The success of modeling groundwater is strongly influenced by the accuracy of the model parameters that are used to characterize the subsurface system. However, the presence of uncertainty and possibly bias in groundwater model source/sink terms may lead to biased estimates of model parameters and model predictions when the standard regression-based inverse modeling techniques are used. This study first quantifies the levels of bias in groundwater model parameters and predictions due to the presence of errors in irrigation data. Then, a new inverse modeling technique called input uncertainty weighted least-squares (IUWLS) is presented for unbiased estimation of the parameters when pumping and other source/sink data are uncertain. The approach uses the concept of generalized least-squares method with the weight of the objective function depending on the level of pumping uncertainty and iteratively adjusted during the parameter optimization process. We have conducted both analytical and numerical experiments, using irrigation pumping data from the Republican River Basin in Nebraska, to evaluate the performance of ordinary least-squares (OLS) and IUWLS calibration methods under different levels of uncertainty of irrigation data and calibration conditions. The result from the OLS method shows the presence of statistically significant (p irrigation pumping uncertainties during the calibration procedures, the proposed IUWLS is able to minimize the bias effectively without adding significant computational burden to the calibration processes.
Parameter estimation in stochastic rainfall-runoff models
DEFF Research Database (Denmark)
Jonsdottir, Harpa; Madsen, Henrik; Palsson, Olafur Petur
2006-01-01
the parameters, including the noise terms. The parameter estimation method is a maximum likelihood method (ML) where the likelihood function is evaluated using a Kalman filter technique. The ML method estimates the parameters in a prediction error settings, i.e. the sum of squared prediction error is minimized....... For a comparison the parameters are also estimated by an output error method, where the sum of squared simulation error is minimized. The former methodology is optimal for short-term prediction whereas the latter is optimal for simulations. Hence, depending on the purpose it is possible to select whether...... 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...
SPOTting Model Parameters Using a Ready-Made Python Package.
Houska, Tobias; Kraft, Philipp; Chamorro-Chavez, Alejandro; Breuer, Lutz
2015-01-01
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.
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.
Liu, M.; He, B.; Lü, A.; Zhou, L.; Wu, J.
2014-06-01
Parameters sensitivity analysis is a crucial step in effective model calibration. It quantitatively apportions the variation of model output to different sources of variation, and identifies how "sensitive" a model is to changes in the values of model parameters. Through calibration of parameters that are sensitive to model outputs, parameter estimation becomes more efficient. Due to uncertainties associated with yield estimates in a regional assessment, field-based models that perform well at field scale are not accurate enough to model at regional scale. Conducting parameters sensitivity analysis at the regional scale and analyzing the differences of parameter sensitivity between stations would make model calibration and validation in different sub-regions more efficient. Further, it would benefit the model applied to the regional scale. Through simulating 2000 × 22 samples for 10 stations in the Huanghuaihai Plain, this study discovered that TB (Optimal temperature), HI (Normal harvest index), WA (Potential radiation use efficiency), BN2 (Normal fraction of N in crop biomass at mid-season) and RWPC1 (Fraction of root weight at emergency) are more sensitive than other parameters. Parameters that determine nutrition supplement and LAI development have higher global sensitivity indices than first-order indices. For spatial application, soil diversity is crucial because soil is responsible for crop parameters sensitivity index differences between sites.
An Effective Parameter Screening Strategy for High Dimensional Watershed Models
Khare, Y. P.; Martinez, C. J.; Munoz-Carpena, R.
2014-12-01
Watershed simulation models can assess the impacts of natural and anthropogenic disturbances on natural systems. These models have become important tools for tackling a range of water resources problems through their implementation in the formulation and evaluation of Best Management Practices, Total Maximum Daily Loads, and Basin Management Action Plans. For accurate applications of watershed models they need to be thoroughly evaluated through global uncertainty and sensitivity analyses (UA/SA). However, due to the high dimensionality of these models such evaluation becomes extremely time- and resource-consuming. Parameter screening, the qualitative separation of important parameters, has been suggested as an essential step before applying rigorous evaluation techniques such as the Sobol' and Fourier Amplitude Sensitivity Test (FAST) methods in the UA/SA framework. The method of elementary effects (EE) (Morris, 1991) is one of the most widely used screening methodologies. Some of the common parameter sampling strategies for EE, e.g. Optimized Trajectories [OT] (Campolongo et al., 2007) and Modified Optimized Trajectories [MOT] (Ruano et al., 2012), suffer from inconsistencies in the generated parameter distributions, infeasible sample generation time, etc. In this work, we have formulated a new parameter sampling strategy - Sampling for Uniformity (SU) - for parameter screening which is based on the principles of the uniformity of the generated parameter distributions and the spread of the parameter sample. A rigorous multi-criteria evaluation (time, distribution, spread and screening efficiency) of OT, MOT, and SU indicated that SU is superior to other sampling strategies. Comparison of the EE-based parameter importance rankings with those of Sobol' helped to quantify the qualitativeness of the EE parameter screening approach, reinforcing the fact that one should use EE only to reduce the resource burden required by FAST/Sobol' analyses but not to replace it.
Seasonal Gravity Field Variations from GRACE and Hydrological Models
DEFF Research Database (Denmark)
Andersen, Ole Baltazar; Hinderer, Jacques; Lemoine, Frank G.
2004-01-01
This study present an investigation of the newly released 18 monthly gravity field solutions from the GRACE twin space-crafts with emphasis on the global scale annual gravity field variations observed from GRACE and modeled from hydrological models as annual changes in terrestrial water storage....... Four global hydrological models covering the same period in 2002–2003 as the GRACE observations were investigated to for their mutual consistency in estimates of annual variation in terrestrial water storage and related temporal changes in gravity field. The hydrological models differ by a maximum of 2...... variation in gravity from GRACE is around 0.4 µGal (0.9 cm water layer thickness) on 2000 km length scales. This makes the GRACE observations of terrestrial water storage on global annual scales more accurate than present-day hydrological models....
Uncertainties of optical-model parameters for the study of the threshold anomaly
Abriola, Daniel; Testoni, J; Gollan, F; Martí, G V
2015-01-01
In the analysis of elastic-scattering experimental data, optical-model parameters (usually, depths of real and imaginary potentials) are fitted and conclusions are drawn analyzing their variations at bombardment energies close to the Coulomb barrier (threshold anomaly). The judgement about the shape of this variation (related to the physical processes producing this anomaly) depends on these fitted values but the robustness of the conclusions strongly depends on the uncertainties with which these parameters are derived. We will show that previous published studies have not used a common criterium for the evaluation of the parameter uncertainties. In this work, a study of these uncertainties is presented, using conventional statistic tools as well as bootstrapping techniques. As case studies, these procedures are applied to re-analyze detailed elastic-scattering data for the $^{12}$C + $^{208}$Pb and the $^6$Li + $^{80}$Se systems.
Energy Technology Data Exchange (ETDEWEB)
Hamimid, M., E-mail: Hamimid_mourad@hotmail.com [Laboratoire de modelisation des systemes energetiques LMSE, Universite de Biskra, BP 145, 07000 Biskra (Algeria); Mimoune, S.M., E-mail: s.m.mimoune@mselab.org [Laboratoire de modelisation des systemes energetiques LMSE, Universite de Biskra, BP 145, 07000 Biskra (Algeria); Feliachi, M., E-mail: mouloud.feliachi@univ-nantes.fr [IREENA-IUT, CRTT, 37 Boulevard de l' Universite, BP 406, 44602 Saint Nazaire Cedex (France)
2012-07-01
In this present work, the minor hysteresis loops model based on parameters scaling of the modified Jiles-Atherton model is evaluated by using judicious expressions. These expressions give the minor hysteresis loops parameters as a function of the major hysteresis loop ones. They have exponential form and are obtained by parameters identification using the stochastic optimization method 'simulated annealing'. The main parameters influencing the data fitting are three parameters, the pinning parameter k, the mean filed parameter {alpha} and the parameter which characterizes the shape of anhysteretic magnetization curve a. To validate this model, calculated minor hysteresis loops are compared with measured ones and good agreements are obtained.
Synthesis of Polymerizable Amphiphiles with Systematic Variation of Critical Packing Parameters
Institute of Scientific and Technical Information of China (English)
M. H. Li; W. L. Yang; J. Qian; C. C. Wang; S. K. Fu
2005-01-01
@@ 1Introduction An amphiphile is a molecule composed of hydrophilic part and hydrophobic part, which are incompatible and tend to separate from each other. The tendency of separation is often promoted by addition of water and sometimes also oil. Under balanced conditions the mixtures form macroscopically homogeneous phases, including isotropic solution phases and liquid crystalline phases. Correlation of the amphiphile structure with its preferred phases could be understood with a simple geometric model[1], which defines a dimensionless Critical Packing Parameter (CPP) to describe the relative bulkiness of the hydrophobic part and the hydrophilic part in an amphiphile. With CPP increasing from a small value to a high value the amphiphile changes from hydrophilic to hydrophobic, its preferred phase structure from direct structures via lamellar structure to reverse structures. This model provides a basis for the molecular design of amphiphiles. To immobilize the microstructure of the phases formed by amphiphiles is a challenge for current material chemists. Techniques of both inorganic polymerization[2] and organic polymerization[3] have been developed. With organic polymerization the molecular design of polymerizable amphiphiles is critical for the successful immobilization of the vulnerable precursor microstructures.
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.
Mathematically Modeling Parameters Influencing Surface Roughness in CNC Milling
Directory of Open Access Journals (Sweden)
Engin Nas
2012-01-01
Full Text Available In this study, steel AISI 1050 is subjected to process of face milling in CNC milling machine and such parameters as cutting speed, feed rate, cutting tip, depth of cut influencing the surface roughness are investigated experimentally. Four different experiments are conducted by creating different combinations for parameters. In conducted experiments, cutting tools, which are coated by PVD method used in forcing steel and spheroidal graphite cast iron are used. Surface roughness values, which are obtained by using specified parameters with cutting tools, are measured and correlation between measured surface roughness values and parameters is modeled mathematically by using curve fitting algorithm. Mathematical models are evaluated according to coefficients of determination (R2 and the most ideal one is suggested for theoretical works. Mathematical models, which are proposed for each experiment, are estipulated.
Regionalization parameters of conceptual rainfall-runoff model
Osuch, M.
2003-04-01
Main goal of this study was to develop techniques for the a priori estimation parameters of hydrological model. Conceptual hydrological model CLIRUN was applied to around 50 catchment in Poland. The size of catchments range from 1 000 to 100 000 km2. The model was calibrated for a number of gauged catchments with different catchment characteristics. The parameters of model were related to different climatic and physical catchment characteristics (topography, land use, vegetation and soil type). The relationships were tested by comparing observed and simulated runoff series from the gauged catchment that were not used in the calibration. The model performance using regional parameters was promising for most of the calibration and validation catchments.
Santaren, D.; Peylin, P.; Viovy, N.; Ciais, P.
2003-04-01
Global model of Carbone, water, and energy exchanges between the biosphere and the atmosphere are usually validated and calibrated with intensive measurement made over specific ecosystem like those of the fluxnet networks.However the nonlinear dependance between fluxes and model parameters generally complicate the optimization of the major parameters.In this study, we estimate few key parameters of the ORCHIDEE french model,using diurnal variation measurements of latent heat,sensible heat and net CO2 fluxes for 3 weeks over pine forest (Landes, France).The model is forced with the observed climatic forcing: Temperature, income solar radiations,wind velocity norm, air humidity, pressure and precipitations. We will first present the inverse methodology and the problem linkedto the non linearity. The result of the optimization shows correlations within the initial ensemble of parameters which allow us to choose only five parameters determined independently from the observations. Directly related to the net CO2 flux, the maximum rate of carboxylation,Vcmax,and the stomatal conductance, gs, are significantly changed from their apriori estimate for that period. The aerodynamic resistance, the albedo and a parameter linked to maintenance respiration were also modified within their physical range.Overall the model fit to the data was largely improved. Note however that some discrepancies remain for sensible heat flux which would probably require some model improvements for the stocking of energy in the soil. Such work is currently extended in time to account for parameter variations between the season. The application to other ecosystems and with the supplementary data of the Leaf Area Index will be also discussed.
Calibrating corneal material model parameters using only inflation data: an ill-posed problem.
Kok, S; Botha, N; Inglis, H M
2014-12-01
Goldmann applanation tonometry (GAT) is a method used to estimate the intraocular pressure by measuring the indentation resistance of the cornea. A popular approach to investigate the sensitivity of GAT results to material and geometry variations is to perform numerical modelling using the finite element method, for which a calibrated material model is required. These material models are typically calibrated using experimental inflation data by solving an inverse problem. In the inverse problem, the underlying material constitutive behaviour is inferred from the measured macroscopic response (chamber pressure versus apical displacement). In this study, a biomechanically motivated elastic fibre-reinforced corneal material model is chosen. The inverse problem of calibrating the corneal material model parameters using only experimental inflation data is demonstrated to be ill-posed, with small variations in the experimental data leading to large differences in the calibrated model parameters. This can result in different groups of researchers, calibrating their material model with the same inflation test data, drawing vastly different conclusions about the effect of material parameters on GAT results. It is further demonstrated that multiple loading scenarios, such as inflation as well as bending, would be required to reliably calibrate such a corneal material model. Copyright © 2014 John Wiley & Sons, Ltd.
Weibull Parameters Estimation Based on Physics of Failure Model
DEFF Research Database (Denmark)
Kostandyan, Erik; Sørensen, John Dalsgaard
2012-01-01
Reliability estimation procedures are discussed for the example of fatigue development in solder joints using a physics of failure model. The accumulated damage is estimated based on a physics of failure model, the Rainflow counting algorithm and the Miner’s rule. A threshold model is used...... distribution. Methods from structural reliability analysis are used to model the uncertainties and to assess the reliability for fatigue failure. Maximum Likelihood and Least Square estimation techniques are used to estimate fatigue life distribution parameters....
Monitoring of oil palm plantations and growth variations with a dense vegetation model
DEFF Research Database (Denmark)
Teng, Khar Chun; Koay, Jun Yi; Tey, Seng Heng
2014-01-01
-PACT) and Fresnel Phase Corrections. The iterative solutions of the radiative transfer model are computed with input based on ground truth measurements of physical parameters of oil palm plantations in the state of Perak, Malaysia, and compared with the SAR images obtained from RADARSAT2. Preliminary results...... are analyzed for dominant scattering mechanisms as well as monitoring of growth variation of oil palm trees for further development of operation models for long term monitoring of oil palm plantations....
Modelling basin-wide variations in Amazon forest photosynthesis
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
MODELING PARAMETERS OF ARC OF ELECTRIC ARC FURNACE
Directory of Open Access Journals (Sweden)
R.N. Khrestin
2015-08-01
Full Text Available Purpose. The aim is to build a mathematical model of the electric arc of arc furnace (EAF. The model should clearly show the relationship between the main parameters of the arc. These parameters determine the properties of the arc and the possibility of optimization of melting mode. Methodology. We have built a fairly simple model of the arc, which satisfies the above requirements. The model is designed for the analysis of electromagnetic processes arc of varying length. We have compared the results obtained when testing the model with the results obtained on actual furnaces. Results. During melting in real chipboard under the influence of changes in temperature changes its properties arc plasma. The proposed model takes into account these changes. Adjusting the length of the arc is the main way to regulate the mode of smelting chipboard. The arc length is controlled by the movement of the drive electrode. The model reflects the dynamic changes in the parameters of the arc when changing her length. We got the dynamic current-voltage characteristics (CVC of the arc for the different stages of melting. We got the arc voltage waveform and identified criteria by which possible identified stage of smelting. Originality. In contrast to the previously known models, this model clearly shows the relationship between the main parameters of the arc EAF: arc voltage Ud, amperage arc id and length arc d. Comparison of the simulation results and experimental data obtained from real particleboard showed the adequacy of the constructed model. It was found that character of change of magnitude Md, helps determine the stage of melting. Practical value. It turned out that the model can be used to simulate smelting in EAF any capacity. Thus, when designing the system of control mechanism for moving the electrode, the model takes into account changes in the parameters of the arc and it can significantly reduce electrode material consumption and energy consumption
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
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.
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
Directory of Open Access Journals (Sweden)
N.Ramesh Raju
2015-10-01
Full Text Available PID controller is mostly used in process plants to control the system performance by properly choosing its parameters. The optimum PID parameters can be obtained in offline using genetic algorithm if the mathematical model of the system is exactly known. In all process plants the process parameters such as properties of materials like thermal conductivity, electrical conductivity, physical dimensions such as diameter, length of the pipes, parameters of valves and pumps will change as time runs. This happens due to corrosion, scaling, aging, repairs during the maintenance, wear and tear. When the system is robust these changes slightly affect the performance of the system. When the system is not robust they make the system performance worst. Due to above reasons the process plant parameters changes as time runs. It is not easy to measure the changes in system parameters while plant is running and could not be evaluated optimum PID parameters through mathematical model. In this paper a new approach using genetic algorithm and neural network is established for optimum self tuning of PID parameters by observing the time response of the system at any time while plant is running.
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
Construction of constant-Q viscoelastic model with three parameters
Institute of Scientific and Technical Information of China (English)
SUN Cheng-yu; YIN Xing-yao
2007-01-01
The popularly used viscoelastic models have some shortcomings in describing relationship between quality factor (Q) and frequency, which is not consistent with the observation data. Based on the theory of viscoelasticity, a new approach to construct constant-Q viscoelastic model in given frequency band with three parameters is developed. The designed model describes the frequency-independence feature of quality factor very well, and the effect of viscoelasticity on seismic wave field can be studied relatively accurate in theory with this model. Furthermore, the number of required parameters in this model has been reduced fewer than that of other constant-Q models, this can simplify the solution of the viscoelastic problems to some extent. At last, the accuracy and application range have been analyzed through numerical tests. The effect of viscoelasticity on wave propagation has been briefly illustrated through the change of frequency spectra and waveform in several different viscoelastic models.
Global-scale regionalization of hydrologic model parameters
Beck, Hylke E.; van Dijk, Albert I. J. M.; de Roo, Ad; Miralles, Diego G.; McVicar, Tim R.; Schellekens, Jaap; Bruijnzeel, L. Adrian
2016-05-01
Current state-of-the-art models typically applied at continental to global scales (hereafter called macroscale) tend to use a priori parameters, resulting in suboptimal streamflow (Q) simulation. For the first time, a scheme for regionalization of model parameters at the global scale was developed. We used data from a diverse set of 1787 small-to-medium sized catchments (10-10,000 km2) and the simple conceptual HBV model to set up and test the scheme. Each catchment was calibrated against observed daily Q, after which 674 catchments with high calibration and validation scores, and thus presumably good-quality observed Q and forcing data, were selected to serve as donor catchments. The calibrated parameter sets for the donors were subsequently transferred to 0.5° grid cells with similar climatic and physiographic characteristics, resulting in parameter maps for HBV with global coverage. For each grid cell, we used the 10 most similar donor catchments, rather than the single most similar donor, and averaged the resulting simulated Q, which enhanced model performance. The 1113 catchments not used as donors were used to independently evaluate the scheme. The regionalized parameters outperformed spatially uniform (i.e., averaged calibrated) parameters for 79% of the evaluation catchments. Substantial improvements were evident for all major Köppen-Geiger climate types and even for evaluation catchments > 5000 km distant from the donors. The median improvement was about half of the performance increase achieved through calibration. HBV with regionalized parameters outperformed nine state-of-the-art macroscale models, suggesting these might also benefit from the new regionalization scheme. The produced HBV parameter maps including ancillary data are available via www.gloh2o.org.
Bayesian parameter estimation for nonlinear modelling of biological pathways
Directory of Open Access Journals (Sweden)
Ghasemi Omid
2011-12-01
Full Text Available Abstract Background The availability of temporal measurements on biological experiments has significantly promoted research areas in systems biology. To gain insight into the interaction and regulation of biological systems, mathematical frameworks such as ordinary differential equations have been widely applied to model biological pathways and interpret the temporal data. Hill equations are the preferred formats to represent the reaction rate in differential equation frameworks, due to their simple structures and their capabilities for easy fitting to saturated experimental measurements. However, Hill equations are highly nonlinearly parameterized functions, and parameters in these functions cannot be measured easily. Additionally, because of its high nonlinearity, adaptive parameter estimation algorithms developed for linear parameterized differential equations cannot be applied. Therefore, parameter estimation in nonlinearly parameterized differential equation models for biological pathways is both challenging and rewarding. In this study, we propose a Bayesian parameter estimation algorithm to estimate parameters in nonlinear mathematical models for biological pathways using time series data. Results We used the Runge-Kutta method to transform differential equations to difference equations assuming a known structure of the differential equations. This transformation allowed us to generate predictions dependent on previous states and to apply a Bayesian approach, namely, the Markov chain Monte Carlo (MCMC method. We applied this approach to the biological pathways involved in the left ventricle (LV response to myocardial infarction (MI and verified our algorithm by estimating two parameters in a Hill equation embedded in the nonlinear model. We further evaluated our estimation performance with different parameter settings and signal to noise ratios. Our results demonstrated the effectiveness of the algorithm for both linearly and nonlinearly
Mirror symmetry for two-parameter models, 1
Candelas, Philip; Font, A; Katz, S; Morrison, Douglas Robert Ogston; Candelas, Philip; Ossa, Xenia de la; Font, Anamaria; Katz, Sheldon; Morrison, David R.
1994-01-01
We study, by means of mirror symmetry, the quantum geometry of the K\\"ahler-class parameters of a number of Calabi-Yau manifolds that have $b_{11}=2$. Our main interest lies in the structure of the moduli space and in the loci corresponding to singular models. This structure is considerably richer when there are two parameters than in the various one-parameter models that have been studied hitherto. We describe the intrinsic structure of the point in the (compactification of the) moduli space that corresponds to the large complex structure or classical limit. The instanton expansions are of interest owing to the fact that some of the instantons belong to families with continuous parameters. We compute the Yukawa couplings and their expansions in terms of instantons of genus zero. By making use of recent results of Bershadsky et al. we compute also the instanton numbers for instantons of genus one. For particular values of the parameters the models become birational to certain models with one parameter. The co...
A VARIATIONAL MODEL FOR 2-D MICROPOLAR BLOOD FLOW
Institute of Scientific and Technical Information of China (English)
He Ji-huan
2003-01-01
The micropolar fluid model is an essential generalization of the well-established Navier-Stokes model in the sense that it takes into account the microstructure of the fluid.This paper is devolted to establishing a variational principle for 2-D incompressible micropolar blood flow.
Reflection in variational models for linear water waves
Klopman, Gert; Dingemans, Maarten W.
2010-01-01
The reflection characteristics are analysed for a series of Hamiltonian water-wave models. These variational models have been derived by applying a Boussinesq-like approach to the vertical flow-structure. Both parabolic and hyperbolic-cosine approximations to the vertical structure are considered. M
Do Lumped-Parameter Models Provide the Correct Geometrical Damping?
DEFF Research Database (Denmark)
Andersen, Lars
2007-01-01
This paper concerns the formulation of lumped-parameter models for rigid footings on homogenous or stratified soil with focus on the horizontal sliding and rocking. Such models only contain a few degrees of freedom, which makes them ideal for inclusion in aero-elastic codes for wind turbines...
Muscle parameters for musculoskeletal modelling of the human neck
Borst, J.; Forbes, P.A.; Happee, R.; Veeger, H.E.J.
2011-01-01
Background: To study normal or pathological neuromuscular control, a musculoskeletal model of the neck has great potential but a complete and consistent anatomical dataset which comprises the muscle geometry parameters to construct such a model is not yet available. Methods: A dissection experiment
Do Lumped-Parameter Models Provide the Correct Geometrical Damping?
DEFF Research Database (Denmark)
Andersen, Lars
2007-01-01
This paper concerns the formulation of lumped-parameter models for rigid footings on homogenous or stratified soil with focus on the horizontal sliding and rocking. Such models only contain a few degrees of freedom, which makes them ideal for inclusion in aero-elastic codes for wind turbines...
Multiplicity Control in Structural Equation Modeling: Incorporating Parameter Dependencies
Smith, Carrie E.; Cribbie, Robert A.
2013-01-01
When structural equation modeling (SEM) analyses are conducted, significance tests for all important model relationships (parameters including factor loadings, covariances, etc.) are typically conducted at a specified nominal Type I error rate ([alpha]). Despite the fact that many significance tests are often conducted in SEM, rarely is…
Muscle parameters for musculoskeletal modelling of the human neck
Borst, J.; Forbes, P.A.; Happee, R.; Veeger, H.E.J.
2011-01-01
Background: To study normal or pathological neuromuscular control, a musculoskeletal model of the neck has great potential but a complete and consistent anatomical dataset which comprises the muscle geometry parameters to construct such a model is not yet available. Methods: A dissection experiment
Geometry parameters for musculoskeletal modelling of the shoulder system
Van der Helm, F C; Veeger, DirkJan (H. E. J.); Pronk, G M; Van der Woude, L H; Rozendal, R H
1992-01-01
A dynamical finite-element model of the shoulder mechanism consisting of thorax, clavicula, scapula and humerus is outlined. The parameters needed for the model are obtained in a cadaver experiment consisting of both shoulders of seven cadavers. In this paper, in particular, the derivation of geomet
Precise correction to parameter ρ in the littlest Higgs model
Institute of Scientific and Technical Information of China (English)
Farshid Tabbak; F.Farnoudi
2008-01-01
In this paper tree-level violation of weak isospin parameter,ρ in the flame of the littlest Higgs model is studied.The potentially large deviation from the standard model prediction for the ρ in terms of the littlest Higgs model parameters is calculated.The maximum value for ρ for f ＝ 1 TeV,c ＝ 0.05,c'＝ 0.05and v'= 1.5 GeV is ρ = 1.2973 which means a large enhancement than the SM.
Comparative Analysis of Visco-elastic Models with Variable Parameters
Directory of Open Access Journals (Sweden)
Silviu Nastac
2010-01-01
Full Text Available The paper presents a theoretical comparative study for computational behaviour analysis of vibration isolation elements based on viscous and elastic models with variable parameters. The changing of elastic and viscous parameters can be produced by natural timed evolution demo-tion or by heating developed into the elements during their working cycle. It was supposed both linear and non-linear numerical viscous and elastic models, and their combinations. The results show the impor-tance of numerical model tuning with the real behaviour, as such the characteristics linearity, and the essential parameters for damping and rigidity. Multiple comparisons between linear and non-linear simulation cases dignify the basis of numerical model optimization regarding mathematical complexity vs. results reliability.
Blümel, Marcus; Hooper, Scott L; Guschlbauerc, Christoph; White, William E; Büschges, Ansgar
2012-11-01
Characterizing muscle requires measuring such properties as force-length, force-activation, and force-velocity curves. These characterizations require large numbers of data points because both what type of function (e.g., linear, exponential, hyperbolic) best represents each property, and the values of the parameters in the relevant equations, need to be determined. Only a few properties are therefore generally measured in experiments on any one muscle, and complete characterizations are obtained by averaging data across a large number of muscles. Such averaging approaches can work well for muscles that are similar across individuals. However, considerable evidence indicates that large inter-individual variation exists, at least for some muscles. This variation poses difficulties for across-animal averaging approaches. Methods to fully describe all muscle's characteristics in experiments on individual muscles would therefore be useful. Prior work in stick insect extensor muscle has identified what functions describe each of this muscle's properties and shown that these equations apply across animals. Characterizing these muscles on an individual-by-individual basis therefore requires determining only the values of the parameters in these equations, not equation form. We present here techniques that allow determining all these parameter values in experiments on single muscles. This technique will allow us to compare parameter variation across individuals and to model muscles individually. Similar experiments can likely be performed on single muscles in other systems. This approach may thus provide a widely applicable method for characterizing and modeling muscles from single experiments.
A software for parameter estimation in dynamic models
Directory of Open Access Journals (Sweden)
M. Yuceer
2008-12-01
Full Text Available A common problem in dynamic systems is to determine parameters in an equation used to represent experimental data. The goal is to determine the values of model parameters that provide the best fit to measured data, generally based on some type of least squares or maximum likelihood criterion. In the most general case, this requires the solution of a nonlinear and frequently non-convex optimization problem. Some of the available software lack in generality, while others do not provide ease of use. A user-interactive parameter estimation software was needed for identifying kinetic parameters. In this work we developed an integration based optimization approach to provide a solution to such problems. For easy implementation of the technique, a parameter estimation software (PARES has been developed in MATLAB environment. When tested with extensive example problems from literature, the suggested approach is proven to provide good agreement between predicted and observed data within relatively less computing time and iterations.
Meta-analysis of magnitudes, differences and variation in evolutionary parameters.
Morrissey, M B
2016-10-01
Meta-analysis is increasingly used to synthesize major patterns in the large literatures within ecology and evolution. Meta-analytic methods that do not account for the process of observing data, which we may refer to as 'informal meta-analyses', may have undesirable properties. In some cases, informal meta-analyses may produce results that are unbiased, but do not necessarily make the best possible use of available data. In other cases, unbiased statistical noise in individual reports in the literature can potentially be converted into severe systematic biases in informal meta-analyses. I first present a general description of how failure to account for noise in individual inferences should be expected to lead to biases in some kinds of meta-analysis. In particular, informal meta-analyses of quantities that reflect the dispersion of parameters in nature, for example, the mean absolute value of a quantity, are likely to be generally highly misleading. I then re-analyse three previously published informal meta-analyses, where key inferences were of aspects of the dispersion of values in nature, for example, the mean absolute value of selection gradients. Major biological conclusions in each original informal meta-analysis closely match those that could arise as artefacts due to statistical noise. I present alternative mixed-model-based analyses that are specifically tailored to each situation, but where all analyses may be implemented with widely available open-source software. In each example meta-re-analysis, major conclusions change substantially.
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.
Parameter Estimation of Photovoltaic Models via Cuckoo Search
Directory of Open Access Journals (Sweden)
Jieming Ma
2013-01-01
Full Text Available Since conventional methods are incapable of estimating the parameters of Photovoltaic (PV models with high accuracy, bioinspired algorithms have attracted significant attention in the last decade. Cuckoo Search (CS is invented based on the inspiration of brood parasitic behavior of some cuckoo species in combination with the Lévy flight behavior. In this paper, a CS-based parameter estimation method is proposed to extract the parameters of single-diode models for commercial PV generators. Simulation results and experimental data show that the CS algorithm is capable of obtaining all the parameters with extremely high accuracy, depicted by a low Root-Mean-Squared-Error (RMSE value. The proposed method outperforms other algorithms applied in this study.
An Improved Lumped Parameter Model for a Piezoelectric Energy Harvester in Transverse Vibration
Directory of Open Access Journals (Sweden)
Guang-qing Wang
2014-01-01
Full Text Available An improved lumped parameter model (ILPM is proposed which predicts the output characteristics of a piezoelectric vibration energy harvester (PVEH. A correction factor is derived for improving the precisions of lumped parameter models for transverse vibration, by considering the dynamic mode shape and the strain distribution of the PVEH. For a tip mass, variations of the correction factor with PVEH length are presented with curve fitting from numerical solutions. The improved governing motion equations and exact analytical solution of the PVEH excited by persistent base motions are developed. Steady-state electrical and mechanical response expressions are derived for arbitrary frequency excitations. Effects of the structural parameters on the electromechanical outputs of the PVEH and important characteristics of the PVEH, such as short-circuit and open-circuit behaviors, are analyzed numerically in detail. Accuracy of the output performances of the ILPM is identified from the available lumped parameter models and the coupled distributed parameter model. Good agreement is found between the analytical results of the ILPM and the coupled distributed parameter model. The results demonstrate the feasibility of the ILPM as a simple and effective means for enhancing the predictions of the PVEH.
Parameter Estimation for Single Diode Models of Photovoltaic Modules
Energy Technology Data Exchange (ETDEWEB)
Hansen, Clifford [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Photovoltaic and Distributed Systems Integration Dept.
2015-03-01
Many popular models for photovoltaic system performance employ a single diode model to compute the I - V curve for a module or string of modules at given irradiance and temperature conditions. A single diode model requires a number of parameters to be estimated from measured I - V curves. Many available parameter estimation methods use only short circuit, o pen circuit and maximum power points for a single I - V curve at standard test conditions together with temperature coefficients determined separately for individual cells. In contrast, module testing frequently records I - V curves over a wide range of irradi ance and temperature conditions which, when available , should also be used to parameterize the performance model. We present a parameter estimation method that makes use of a fu ll range of available I - V curves. We verify the accuracy of the method by recov ering known parameter values from simulated I - V curves . We validate the method by estimating model parameters for a module using outdoor test data and predicting the outdoor performance of the module.
Automatic Determination of the Conic Coronal Mass Ejection Model Parameters
Pulkkinen, A.; Oates, T.; Taktakishvili, A.
2009-01-01
Characterization of the three-dimensional structure of solar transients using incomplete plane of sky data is a difficult problem whose solutions have potential for societal benefit in terms of space weather applications. In this paper transients are characterized in three dimensions by means of conic coronal mass ejection (CME) approximation. A novel method for the automatic determination of cone model parameters from observed halo CMEs is introduced. The method uses both standard image processing techniques to extract the CME mass from white-light coronagraph images and a novel inversion routine providing the final cone parameters. A bootstrap technique is used to provide model parameter distributions. When combined with heliospheric modeling, the cone model parameter distributions will provide direct means for ensemble predictions of transient propagation in the heliosphere. An initial validation of the automatic method is carried by comparison to manually determined cone model parameters. It is shown using 14 halo CME events that there is reasonable agreement, especially between the heliocentric locations of the cones derived with the two methods. It is argued that both the heliocentric locations and the opening half-angles of the automatically determined cones may be more realistic than those obtained from the manual analysis
García-Navas, Vicente; Sanz, Juan José
2012-01-01
Over a five-year period we monitored breeding parameters in a colony of Tree Sparrows Passer montanus in central Spain. This multi-brooded species can raise one to three broods per season. In this study, we analyzed inter-brood variation in reproductive success to infer the existence of seasonal patterns. We also explored inter-annual variation of life-history traits, which is of particular interest in a declining species like the Tree Sparrow. In agreement with our expectation of a multi-bro...
Estimation of the parameters of ETAS models by Simulated Annealing
Lombardi, Anna Maria
2015-01-01
This paper proposes a new algorithm to estimate the maximum likelihood parameters of an Epidemic Type Aftershock Sequences (ETAS) model. It is based on Simulated Annealing, a versatile method that solves problems of global optimization and ensures convergence to a global optimum. The procedure is tested on both simulated and real catalogs. The main conclusion is that the method performs poorly as the size of the catalog decreases because the effect of the correlation of the ETAS parameters is...
CADLIVE optimizer: web-based parameter estimation for dynamic models
Directory of Open Access Journals (Sweden)
Inoue Kentaro
2012-08-01
Full Text Available Abstract Computer simulation has been an important technique to capture the dynamics of biochemical networks. In most networks, however, few kinetic parameters have been measured in vivo because of experimental complexity. We develop a kinetic parameter estimation system, named the CADLIVE Optimizer, which comprises genetic algorithms-based solvers with a graphical user interface. This optimizer is integrated into the CADLIVE Dynamic Simulator to attain efficient simulation for dynamic models.
Reference physiological parameters for pharmacodynamic modeling of liver cancer
Energy Technology Data Exchange (ETDEWEB)
Travis, C.C.; Arms, A.D.
1988-01-01
This document presents a compilation of measured values for physiological parameters used in pharamacodynamic modeling of liver cancer. The physiological parameters include body weight, liver weight, the liver weight/body weight ratio, and number of hepatocytes. Reference values for use in risk assessment are given for each of the physiological parameters based on analyses of valid measurements taken from the literature and other reliable sources. The proposed reference values for rodents include sex-specific measurements for the B6C3F{sub 1}, mice and Fishcer 344/N, Sprague-Dawley, and Wistar rats. Reference values are also provided for humans. 102 refs., 65 tabs.
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...
X-Parameter Based Modelling of Polar Modulated Power Amplifiers
DEFF Research Database (Denmark)
Wang, Yelin; Nielsen, Troels Studsgaard; Sira, Daniel
2013-01-01
X-parameters are developed as an extension of S-parameters capable of modelling non-linear devices driven by large signals. They are suitable for devices having only radio frequency (RF) and DC ports. In a polar power amplifier (PA), phase and envelope of the input modulated signal are applied...... at separate ports and the envelope port is neither an RF nor a DC port. As a result, X-parameters may fail to characterise the effect of the envelope port excitation and consequently the polar PA. This study introduces a solution to the problem for a commercial polar PA. In this solution, the RF-phase path...
A practical method to assess model sensitivity and parameter uncertainty in C cycle models
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.
A Bayesian framework for parameter estimation in dynamical models.
Directory of Open Access Journals (Sweden)
Flávio Codeço Coelho
Full Text Available Mathematical models in biology are powerful tools for the study and exploration of complex dynamics. Nevertheless, bringing theoretical results to an agreement with experimental observations involves acknowledging a great deal of uncertainty intrinsic to our theoretical representation of a real system. Proper handling of such uncertainties is key to the successful usage of models to predict experimental or field observations. This problem has been addressed over the years by many tools for model calibration and parameter estimation. In this article we present a general framework for uncertainty analysis and parameter estimation that is designed to handle uncertainties associated with the modeling of dynamic biological systems while remaining agnostic as to the type of model used. We apply the framework to fit an SIR-like influenza transmission model to 7 years of incidence data in three European countries: Belgium, the Netherlands and Portugal.
Modelling of Water Turbidity Parameters in a Water Treatment Plant
Directory of Open Access Journals (Sweden)
A. S. KOVO
2005-01-01
Full Text Available The high cost of chemical analysis of water has necessitated various researches into finding alternative method of determining portable water quality. This paper is aimed at modelling the turbidity value as a water quality parameter. Mathematical models for turbidity removal were developed based on the relationships between water turbidity and other water criteria. Results showed that the turbidity of water is the cumulative effect of the individual parameters/factors affecting the system. A model equation for the evaluation and prediction of a clarifier’s performance was developed:Model: T = T0(-1.36729 + 0.037101∙10λpH + 0.048928t + 0.00741387∙alkThe developed model will aid the predictive assessment of water treatment plant performance. The limitations of the models are as a result of insufficient variable considered during the conceptualization.
Simultaneous estimation of parameters in the bivariate Emax model.
Magnusdottir, Bergrun T; Nyquist, Hans
2015-12-10
In this paper, we explore inference in multi-response, nonlinear models. By multi-response, we mean models with m > 1 response variables and accordingly m relations. Each parameter/explanatory variable may appear in one or more of the relations. We study a system estimation approach for simultaneous computation and inference of the model and (co)variance parameters. For illustration, we fit a bivariate Emax model to diabetes dose-response data. Further, the bivariate Emax model is used in a simulation study that compares the system estimation approach to equation-by-equation estimation. We conclude that overall, the system estimation approach performs better for the bivariate Emax model when there are dependencies among relations. The stronger the dependencies, the more we gain in precision by using system estimation rather than equation-by-equation estimation.
Impact of the calibration period on the conceptual rainfall-runoff model parameter estimates
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.
Modeling of mouse eye and errors in ocular parameters affecting refractive state
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
Shape parameter estimate for a glottal model without time position
Degottex, Gilles; Roebel, Axel; Rodet, Xavier
2009-01-01
cote interne IRCAM: Degottex09a; None / None; National audience; From a recorded speech signal, we propose to estimate a shape parameter of a glottal model without estimating his time position. Indeed, the literature usually propose to estimate the time position first (ex. by detecting Glottal Closure Instants). The vocal-tract filter estimate is expressed as a minimum-phase envelope estimation after removing the glottal model and a standard lips radiation model. Since this filter is mainly b...
Light-Front Spin-1 Model: Parameters Dependence
Mello, Clayton S; de Melo, J P B C; Frederico, T
2015-01-01
We study the structure of the $\\rho$-meson within a light-front model with constituent quark degrees of freedom. We calculate electroweak static observables: magnetic and quadrupole moments, decay constant and charge radius. The prescription used to compute the electroweak quantities is free of zero modes, which makes the calculation implicitly covariant. We compare the results of our model with other ones found in the literature. Our model parameters give a decay constant close to the experimental one.
Cosmological Models with Variable Deceleration Parameter in Lyra's Manifold
Pradhan, A; Singh, C B
2006-01-01
FRW models of the universe have been studied in the cosmological theory based on Lyra's manifold. A new class of exact solutions has been obtained by considering a time dependent displacement field for variable deceleration parameter from which three models of the universe are derived (i) exponential (ii) polynomial and (iii) sinusoidal form respectively. The behaviour of these models of the universe are also discussed. Finally some possibilities of further problems and their investigations have been pointed out.
Ridley, Victoria A.; Holme, Richard
2016-03-01
We present new models of Jupiter's internal magnetic field and secular variation from all available direct measurements from three decades of spacecraft observation. A regularized minimum norm approach allows the creation of smooth, numerically stable models displaying a high degree of structure. External field from the magnetodisk is modeled iteratively for each orbit. Jupiter's inner magnetosphere is highly stable with time, with no evidence for variation with solar activity. We compare two spherical harmonic models, one assuming a field constant in time and a second allowing for linear time variation. Including secular variation improves data fit with fewer additional parameters than increasing field complexity. Our favored solution indicates a ˜0.012% yr-1 increase in Jupiter's dipole magnetic moment from 1973 to 2003; this value is roughly one quarter of that for Earth. Inaccuracies in determination of the planetary reference frame cannot explain all the observed secular variation. Should more structure be allowed in the solutions, we find the northern hemispherical configuration resembles recent models based on satellite auroral footprint locations, and there is also evidence of a possible patch of reversed polar flux seen at the expected depth of the dynamo region, resembling that found at Earth and with implications for the Jovian interior. Finally, using our preferred model, we infer flow dynamics at the top of Jupiter's dynamo source. Though highly speculative, the results produce several gyres with some symmetry about the equator, similar to those seen at Earth's core-mantle boundary, suggesting motion on cylinders aligned with the rotation axis.
Variational Bayesian identification and prediction of stochastic nonlinear dynamic causal models
Daunizeau, J.; Friston, K. J.; Kiebel, S. J.
2009-11-01
In this paper, we describe a general variational Bayesian approach for approximate inference on nonlinear stochastic dynamic models. This scheme extends established approximate inference on hidden-states to cover: (i) nonlinear evolution and observation functions, (ii) unknown parameters and (precision) hyperparameters and (iii) model comparison and prediction under uncertainty. Model identification or inversion entails the estimation of the marginal likelihood or evidence of a model. This difficult integration problem can be finessed by optimising a free-energy bound on the evidence using results from variational calculus. This yields a deterministic update scheme that optimises an approximation to the posterior density on the unknown model variables. We derive such a variational Bayesian scheme in the context of nonlinear stochastic dynamic hierarchical models, for both model identification and time-series prediction. The computational complexity of the scheme is comparable to that of an extended Kalman filter, which is critical when inverting high dimensional models or long time-series. Using Monte-Carlo simulations, we assess the estimation efficiency of this variational Bayesian approach using three stochastic variants of chaotic dynamic systems. We also demonstrate the model comparison capabilities of the method, its self-consistency and its predictive power.
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
A model for random cyclic pressure variations in spark-ignition engines
Energy Technology Data Exchange (ETDEWEB)
Chandrashekar, T.K. [Sri Siddhartha Inst. of Technology, Karnataka (India); Antony, A.J. [Sahyadri Inst. of Technology, Mangalore, Karnataka (India)
2009-07-01
Cycle-by-cycle (CBC) variation of mean effective pressure in spark ignition engines is always greater than in compression ignition engines and needs to be reduced for better drivability, reduced emissions and increased power output. This study examined the parameters affecting CBC fluctuation and how to reduce the fluctuations. The paper presented two newly developed models designed to simulate the engine combustion process and CBC fluctuation. The mathematical model was outlined in detail with particular reference to model development; the statistical model for CBC fluctuation; and experimental setup. The model was found to be physically realistic and correctly predicted the cyclic variation of pressure to provide fundamental insight into the processes. The combustion model also took the effects of heat transfer and friction into consideration. 7 refs., 1 tab., 14 figs., 1 appendix.
Solar Model Parameters and Direct Measurements of Solar Neutrino Fluxes
Bandyopadhyay, A; Goswami, S; Petcov, S T; Bandyopadhyay, Abhijit; Choubey, Sandhya; Goswami, Srubabati
2006-01-01
We explore a novel possibility of determining the solar model parameters, which serve as input in the calculations of the solar neutrino fluxes, by exploiting the data from direct measurements of the fluxes. More specifically, we use the rather precise value of the $^8B$ neutrino flux, $\\phi_B$ obtained from the global analysis of the solar neutrino and KamLAND data, to derive constraints on each of the solar model parameters on which $\\phi_B$ depends. We also use more precise values of $^7Be$ and $pp$ fluxes as can be obtained from future prospective data and discuss whether such measurements can help in reducing the uncertainties of one or more input parameters of the Standard Solar Model.
IP-Sat: Impact-Parameter dependent Saturation model; revised
Rezaeian, Amir H; Van de Klundert, Merijn; Venugopalan, Raju
2013-01-01
In this talk, we present a global analysis of available small-x data on inclusive DIS and exclusive diffractive processes, including the latest data from the combined HERA analysis on reduced cross sections within the Impact-Parameter dependent Saturation (IP-Sat) Model. The impact-parameter dependence of dipole amplitude is crucial in order to have a unified description of both inclusive and exclusive diffractive processes. With the parameters of model fixed via a fit to the high-precision reduced cross-section, we compare model predictions to data for the structure functions, the longitudinal structure function, the charm structure function, exclusive vector mesons production and Deeply Virtual Compton Scattering (DVCS). Excellent agreement is obtained for the processes considered at small x in a wide range of Q^2.
QCD-inspired determination of NJL model parameters
Springer, Paul; Rechenberger, Stefan; Rennecke, Fabian
2016-01-01
The QCD phase diagram at finite temperature and density has attracted considerable interest over many decades now, not least because of its relevance for a better understanding of heavy-ion collision experiments. Models provide some insight into the QCD phase structure but usually rely on various parameters. Based on renormalization group arguments, we discuss how the parameters of QCD low-energy models can be determined from the fundamental theory of the strong interaction. We particularly focus on a determination of the temperature dependence of these parameters in this work and comment on the effect of a finite quark chemical potential. We present first results and argue that our findings can be used to improve the predictive power of future model calculations.
Note on the equivalence of hierarchical variational models and auxiliary deep generative models
Brümmer, Niko
2016-01-01
This note compares two recently published machine learning methods for constructing flexible, but tractable families of variational hidden-variable posteriors. The first method, called "hierarchical variational models" enriches the inference model with an extra variable, while the other, called "auxiliary deep generative models", enriches the generative model instead. We conclude that the two methods are mathematically equivalent.
SPOTting model parameters using a ready-made Python package
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
Synchronous Generator Model Parameter Estimation Based on Noisy Dynamic Waveforms
Berhausen, Sebastian; Paszek, Stefan
2016-01-01
In recent years, there have occurred system failures in many power systems all over the world. They have resulted in a lack of power supply to a large number of recipients. To minimize the risk of occurrence of power failures, it is necessary to perform multivariate investigations, including simulations, of power system operating conditions. To conduct reliable simulations, the current base of parameters of the models of generating units, containing the models of synchronous generators, is necessary. In the paper, there is presented a method for parameter estimation of a synchronous generator nonlinear model based on the analysis of selected transient waveforms caused by introducing a disturbance (in the form of a pseudorandom signal) in the generator voltage regulation channel. The parameter estimation was performed by minimizing the objective function defined as a mean square error for deviations between the measurement waveforms and the waveforms calculated based on the generator mathematical model. A hybrid algorithm was used for the minimization of the objective function. In the paper, there is described a filter system used for filtering the noisy measurement waveforms. The calculation results of the model of a 44 kW synchronous generator installed on a laboratory stand of the Institute of Electrical Engineering and Computer Science of the Silesian University of Technology are also given. The presented estimation method can be successfully applied to parameter estimation of different models of high-power synchronous generators operating in a power system.
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.
Optimizing Muscle Parameters in Musculoskeletal Modeling Using Monte Carlo Simulations
Hanson, Andrea; Reed, Erik; Cavanagh, Peter
2011-01-01
Astronauts assigned to long-duration missions experience bone and muscle atrophy in the lower limbs. The use of musculoskeletal simulation software has become a useful tool for modeling joint and muscle forces during human activity in reduced gravity as access to direct experimentation is limited. Knowledge of muscle and joint loads can better inform the design of exercise protocols and exercise countermeasure equipment. In this study, the LifeModeler(TM) (San Clemente, CA) biomechanics simulation software was used to model a squat exercise. The initial model using default parameters yielded physiologically reasonable hip-joint forces. However, no activation was predicted in some large muscles such as rectus femoris, which have been shown to be active in 1-g performance of the activity. Parametric testing was conducted using Monte Carlo methods and combinatorial reduction to find a muscle parameter set that more closely matched physiologically observed activation patterns during the squat exercise. Peak hip joint force using the default parameters was 2.96 times body weight (BW) and increased to 3.21 BW in an optimized, feature-selected test case. The rectus femoris was predicted to peak at 60.1% activation following muscle recruitment optimization, compared to 19.2% activation with default parameters. These results indicate the critical role that muscle parameters play in joint force estimation and the need for exploration of the solution space to achieve physiologically realistic muscle activation.
Modelling of intermittent microwave convective drying: parameter sensitivity
Zhang, Zhijun; Qin, Wenchao; Shi, Bin; Gao, Jingxin; Zhang, Shiwei
2017-06-01
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.
Hamilton City Board of Education (Ontario).
Suggestions for studying the topic of variation of individuals and objects (balls) to help develop elementary school students' measurement, comparison, classification, evaluation, and data collection and recording skills are made. General suggestions of variables that can be investigated are made for the study of human variation. Twelve specific…
Coarse graining from variationally enhanced sampling applied to the Ginzburg-Landau model.
Invernizzi, Michele; Valsson, Omar; Parrinello, Michele
2017-03-28
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.
Coarse graining from variationally enhanced sampling applied to the Ginzburg–Landau model
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
Models with hidden regular variation: Generation and detection
Directory of Open Access Journals (Sweden)
Bikramjit Das
2015-12-01
Full Text Available We review the notions of multivariate regular variation (MRV and hidden regular variation (HRV for distributions of random vectors and then discuss methods for generating models exhibiting both properties concentrating on the non-negative orthant in dimension two. Furthermore we suggest diagnostic techniques that detect these properties in multivariate data and indicate when models exhibiting both MRV and HRV are plausible fits for the data. We illustrate our techniques on simulated data, as well as two real Internet data sets.
Comparing spatial and temporal transferability of hydrological model parameters
Patil, Sopan; Stieglitz, Marc
2015-04-01
Operational use of hydrological models requires the transfer of calibrated parameters either in time (for streamflow forecasting) or space (for prediction at ungauged catchments) or both. Although the effects of spatial and temporal parameter transfer on catchment streamflow predictions have been well studied individually, a direct comparison of these approaches is much less documented. In our view, such comparison is especially pertinent in the context of increasing appeal and popularity of the "trading space for time" approaches that are proposed for assessing the hydrological implications of anthropogenic climate change. Here, we compare three different schemes of parameter transfer, viz., temporal, spatial, and spatiotemporal, using a spatially lumped hydrological model called EXP-HYDRO at 294 catchments across the continental United States. Results show that the temporal parameter transfer scheme performs best, with lowest decline in prediction performance (median decline of 4.2%) as measured using the Kling-Gupta efficiency metric. More interestingly, negligible difference in prediction performance is observed between the spatial and spatiotemporal parameter transfer schemes (median decline of 12.4% and 13.9% respectively). We further demonstrate that the superiority of temporal parameter transfer scheme is preserved even when: (1) spatial distance between donor and receiver catchments is reduced, or (2) temporal lag between calibration and validation periods is increased. Nonetheless, increase in the temporal lag between calibration and validation periods reduces the overall performance gap between the three parameter transfer schemes. Results suggest that spatiotemporal transfer of hydrological model parameters has the potential to be a viable option for climate change related hydrological studies, as envisioned in the "trading space for time" framework. However, further research is still needed to explore the relationship between spatial and temporal
Improving Langley calibrations by reducing diurnal variations of aerosol Ångström parameters
Directory of Open Access Journals (Sweden)
A. Kreuter
2013-01-01
Full Text Available Errors in the sun photometer calibration constant lead to artificial diurnal variations, symmetric around solar noon, of the retrieved aerosol optical depth (AOD and the associated Ångström exponent α and its curvature γ. We show in simulations that within the uncertainty of state-of-the-art Langley calibrations, these diurnal variations of α and γ can be significant in low AOD conditions, while those of AOD are negligible. We implement a weighted Monte Carlo method of finding an improved calibration constant by minimizing the diurnal variations in α and γ and apply the method to sun photometer data of a clear day in Innsbruck, Austria. The results show that our method can be used to improve the calibrations in two of the four wavelength channels by up to a factor of 3.6.
Improving Langley calibrations by reducing diurnal variations of aerosol Ångström parameters
Directory of Open Access Journals (Sweden)
A. Kreuter
2012-09-01
Full Text Available Errors in the sun photometer calibration constant lead to artificial diurnal variations, symmetric around solar noon, of the retrieved Aerosol Optical Depth (AOD and the associated Ångström exponent α and its curvature γ. We show in simulations that within the uncertainty of state-of-the-art Langley calibrations, these diurnal variations of α and γ can be significant in low AOD conditions, while those of AOD are negligible. We implement a weighted Monte-Carlo method of finding an improved calibration constant by minimizing the diurnal variations in α and γ and apply the method to sun photometer data of a clear day in Innsbruck, Austria. The results show that our method can be used to improve the calibrations in two of the four wavelength channels by up to a factor of 3.6.
Patterns of variation in reproductive parameters in Eurasian lynx (Lynx lynx).
Nilsen, Erlend B; Linnell, John D C; Odden, John; Samelius, Gustaf; Andrén, Henrik
2012-07-01
Detailed knowledge of the variation in demographic rates is central for our ability to understand the evolution of life history strategies and population dynamics, and to plan for the conservation of endangered species. We studied variation in reproductive output of 61 radio-collared Eurasian lynx females in four Scandinavian study sites spanning a total of 223 lynx-years. Specifically, we examined how the breeding proportion and litter size varied among study areas and age classes (2-year-old vs. >2-year-old females). In general, the breeding proportion varied between age classes and study sites, whereas we did not detect such variation in litter size. The lack of differences in litter sizes among age classes is at odds with most findings in large mammals, and we argue that this is because the level of prenatal investment is relatively low in felids compared to their substantial levels of postnatal care.
A simple physical model predicts small exon length variations.
Directory of Open Access Journals (Sweden)
2006-04-01
Full Text Available One of the most common splice variations are small exon length variations caused by the use of alternative donor or acceptor splice sites that are in very close proximity on the pre-mRNA. Among these, three-nucleotide variations at so-called NAGNAG tandem acceptor sites have recently attracted considerable attention, and it has been suggested that these variations are regulated and serve to fine-tune protein forms by the addition or removal of a single amino acid. In this paper we first show that in-frame exon length variations are generally overrepresented and that this overrepresentation can be quantitatively explained by the effect of nonsense-mediated decay. Our analysis allows us to estimate that about 50% of frame-shifted coding transcripts are targeted by nonsense-mediated decay. Second, we show that a simple physical model that assumes that the splicing machinery stochastically binds to nearby splice sites in proportion to the affinities of the sites correctly predicts the relative abundances of different small length variations at both boundaries. Finally, using the same simple physical model, we show that for NAGNAG sites, the difference in affinities of the neighboring sites for the splicing machinery accurately predicts whether splicing will occur only at the first site, splicing will occur only at the second site, or three-nucleotide splice variants are likely to occur. Our analysis thus suggests that small exon length variations are the result of stochastic binding of the spliceosome at neighboring splice sites. Small exon length variations occur when there are nearby alternative splice sites that have similar affinity for the splicing machinery.
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.
Lattice variation and thermal parameters of NiMg1–SO4 7H2O single crystals
Indian Academy of Sciences (India)
M Theivanayagom; C Mahadevan
2001-10-01
NiMg1–SO4.7H2O single crystals were grown by the slow evaporation method from aqueous solutions. Density was measured by the floatation method. X-ray diffraction data were collected for powder samples and used for the estimation of lattice variation and thermal parameters like Debye–Waller factor, mean-square amplitude of vibration and Debye temperature. Lattice volumes approximately obey a relation similar to Retger’s rule. Values of thermal parameters do not follow any particular order with composition. The results obtained are reported.
Neudeck, Philip G.; Chen, Liangyu; Spry, David J.; Beheim, Glenn M.; Chang, Carl W.
2014-01-01
This work reports DC electrical characterization of a 76 mm diameter 4H-SiC JFET test wafer fabricated as part of NASA's on-going efforts to realize medium-scale ICs with prolonged and stable circuit operation at temperatures as high as 500 degC. In particular, these measurements provide quantitative parameter ranges for use in JFET IC design and simulation. Larger than expected parameter variations were observed both as a function of position across the wafer as well as a function of ambient testing temperature from 23 degC to 500 degC.
Estimation of the parameters of ETAS models by Simulated Annealing
Lombardi, Anna Maria
2015-02-01
This paper proposes a new algorithm to estimate the maximum likelihood parameters of an Epidemic Type Aftershock Sequences (ETAS) model. It is based on Simulated Annealing, a versatile method that solves problems of global optimization and ensures convergence to a global optimum. The procedure is tested on both simulated and real catalogs. The main conclusion is that the method performs poorly as the size of the catalog decreases because the effect of the correlation of the ETAS parameters is more significant. These results give new insights into the ETAS model and the efficiency of the maximum-likelihood method within this context.
J-A Hysteresis Model Parameters Estimation using GA
Directory of Open Access Journals (Sweden)
Bogomir Zidaric
2005-01-01
Full Text Available This paper presents the Jiles and Atherton (J-A hysteresis model parameter estimation for soft magnetic composite (SMC material. The calculation of Jiles and Atherton hysteresis model parameters is based on experimental data and genetic algorithms (GA. Genetic algorithms operate in a given area of possible solutions. Finding the best solution of a problem in wide area of possible solutions is uncertain. A new approach in use of genetic algorithms is proposed to overcome this uncertainty. The basis of this approach is in genetic algorithm built in another genetic algorithm.
A new estimate of the parameters in linear mixed models
Institute of Scientific and Technical Information of China (English)
王松桂; 尹素菊
2002-01-01
In linear mixed models, there are two kinds of unknown parameters: one is the fixed effect, theother is the variance component. In this paper, new estimates of these parameters, called the spectral decom-position estimates, are proposed, Some important statistical properties of the new estimates are established,in particular the linearity of the estimates of the fixed effects with many statistical optimalities. A new methodis applied to two important models which are used in economics, finance, and mechanical fields. All estimatesobtained have good statistical and practical meaning.
Models wagging the dog: are circuits constructed with disparate parameters?
Nowotny, Thomas; Szücs, Attila; Levi, Rafael; Selverston, Allen I
2007-08-01
In a recent article, Prinz, Bucher, and Marder (2004) addressed the fundamental question of whether neural systems are built with a fixed blueprint of tightly controlled parameters or in a way in which properties can vary largely from one individual to another, using a database modeling approach. Here, we examine the main conclusion that neural circuits indeed are built with largely varying parameters in the light of our own experimental and modeling observations. We critically discuss the experimental and theoretical evidence, including the general adequacy of database approaches for questions of this kind, and come to the conclusion that the last word for this fundamental question has not yet been spoken.
Do land parameters matter in large-scale hydrological modelling?
Gudmundsson, Lukas; Seneviratne, Sonia I.
2013-04-01
Many of the most pending issues in large-scale hydrology are concerned with predicting hydrological variability at ungauged locations. However, current-generation hydrological and land surface models that are used for their estimation suffer from large uncertainties. These models rely on mathematical approximations of the physical system as well as on mapped values of land parameters (e.g. topography, soil types, land cover) to predict hydrological variables (e.g. evapotranspiration, soil moisture, stream flow) as a function of atmospheric forcing (e.g. precipitation, temperature, humidity). Despite considerable progress in recent years, it remains unclear whether better estimates of land parameters can improve predictions - or - if a refinement of model physics is necessary. To approach this question we suggest scrutinizing our perception of hydrological systems by confronting it with the radical assumption that hydrological variability at any location in space depends on past and present atmospheric forcing only, and not on location-specific land parameters. This so called "Constant Land Parameter Hypothesis (CLPH)" assumes that variables like runoff can be predicted without taking location specific factors such as topography or soil types into account. We demonstrate, using a modern statistical tool, that monthly runoff in Europe can be skilfully estimated using atmospheric forcing alone, without accounting for locally varying land parameters. The resulting runoff estimates are used to benchmark state-of-the-art process models. These are found to have inferior performance, despite their explicit process representation, which accounts for locally varying land parameters. This suggests that progress in the theory of hydrological systems is likely to yield larger improvements in model performance than more precise land parameter estimates. The results also question the current modelling paradigm that is dominated by the attempt to account for locally varying land
Parameter analysis for a mathematical model of the immune system in leukemia
Safta, Carmen Anca; Balea, Silvia; Halanay, Andrei; Neamtu, Mihaela
2014-12-01
Starting from a mathematical model which describes the dynamics of Chronic Myelogenous Leukemia (CML) when the action of different cell lines of the immune system is considered, the aim of the paper is to analyze the parameters influence in CML evolution. The model consists of seven delay differential equations with seven delays. The physiological processes are modeled using feedback functions so the variation of their coefficients changes the disease's evolution. Numerical simulations will be used to observe the evolution of the disease and to determine the possible treatment options.
Models for selecting GMA Welding Parameters for Improving Mechanical Properties of Weld Joints
Srinivasa Rao, P.; Ramachandran, Pragash; Jebaraj, S.
2016-02-01
During the process of Gas Metal Arc (GMAW) welding, the weld joints mechanical properties are influenced by the welding parameters such as welding current and arc voltage. These parameters directly will influence the quality of the weld in terms of mechanical properties. Even small variation in any of the cited parameters may have an important effect on depth of penetration and on joint strength. In this study, S45C Constructional Steel is taken as the base metal to be tested using the parameters wire feed rate, voltage and type of shielding gas. Physical properties considered in the present study are tensile strength and hardness. The testing of weld specimen is carried out as per ASTM Standards. Mathematical models to predict the tensile strength and depth of penetration of weld joint have been developed by regression analysis using the experimental results.
Seasonal Gravity Field Variations from GRACE and Hydrological Models
DEFF Research Database (Denmark)
Andersen, Ole Baltazar; Hinderer, Jacques; Lemoine, Frank G.
2004-01-01
This study present an investigation of the newly released 18 monthly gravity field solutions from the GRACE twin space-crafts with emphasis on the global scale annual gravity field variations observed from GRACE and modeled from hydrological models as annual changes in terrestrial water storage....... Four global hydrological models covering the same period in 2002–2003 as the GRACE observations were investigated to for their mutual consistency in estimates of annual variation in terrestrial water storage and related temporal changes in gravity field. The hydrological models differ by a maximum of 2...... µGal or nearly 5 cm equivalent water storage in selected regions. Integrated over all land masses the standard deviation among the annual signal from the four hydrological models are 0.6 µGal equivalent to around 1.4 cm in equivalent water layer thickness. The estimated accuracy of the annual...
Institute of Scientific and Technical Information of China (English)
Lukas Graber; Diomar Infante; Michael Steurer; William W. Brey
2011-01-01
Careful analysis of transients in shipboard power systems is important to achieve long life times of the com ponents in future all-electric ships. In order to accomplish results with high accuracy, it is recommended to validate cable models as they have significant influence on the amplitude and frequency spectrum of voltage transients. The authors propose comparison of model and measurement using scattering parameters. They can be easily obtained from measurement and simulation and deliver broadband information about the accuracy of the model. The measurement can be performed using a vector network analyzer. The process to extract scattering parameters from simulation models is explained in detail. Three different simulation models of a 5 kV XLPE power cable have been validated. The chosen approach delivers an efficient tool to quickly estimate the quality of a model.
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
Considerations for parameter optimization and sensitivity in climate models.
Neelin, J David; Bracco, Annalisa; Luo, Hao; McWilliams, James C; Meyerson, Joyce E
2010-12-14
Climate models exhibit high sensitivity in some respects, such as for differences in predicted precipitation changes under global warming. Despite successful large-scale simulations, regional climatology features prove difficult to constrain toward observations, with challenges including high-dimensionality, computationally expensive simulations, and ambiguity in the choice of objective function. In an atmospheric General Circulation Model forced by observed sea surface temperature or coupled to a mixed-layer ocean, many climatic variables yield rms-error objective functions that vary smoothly through the feasible parameter range. This smoothness occurs despite nonlinearity strong enough to reverse the curvature of the objective function in some parameters, and to imply limitations on multimodel ensemble means as an estimator of global warming precipitation changes. Low-order polynomial fits to the model output spatial fields as a function of parameter (quadratic in model field, fourth-order in objective function) yield surprisingly successful metamodels for many quantities and facilitate a multiobjective optimization approach. Tradeoffs arise as optima for different variables occur at different parameter values, but with agreement in certain directions. Optima often occur at the limit of the feasible parameter range, identifying key parameterization aspects warranting attention--here the interaction of convection with free tropospheric water vapor. Analytic results for spatial fields of leading contributions to the optimization help to visualize tradeoffs at a regional level, e.g., how mismatches between sensitivity and error spatial fields yield regional error under minimization of global objective functions. The approach is sufficiently simple to guide parameter choices and to aid intercomparison of sensitivity properties among climate models.
Latitudinal variations of aerosol optical parameters over South Africa based on MISR satellite data
CSIR Research Space (South Africa)
Tesfaye M
2010-09-01
Full Text Available The latitudunal variation of the relative weight size distribution and optical properties of aerosols over South Africa is presented here. The study uses 10-years of Multi-angle Imaging SpectroRadiometer (MISR) satellite data, collected over South...
Uncertainty of Modal Parameters Estimated by ARMA Models
DEFF Research Database (Denmark)
Jensen, Jakob Laigaard; Brincker, Rune; Rytter, Anders
In this paper the uncertainties of identified modal parameters such as eigenfrequencies and damping ratios are assessed. From the measured response of dynamic excited structures the modal parameters may be identified and provide important structural knowledge. However the uncertainty of the param......In this paper the uncertainties of identified modal parameters such as eigenfrequencies and damping ratios are assessed. From the measured response of dynamic excited structures the modal parameters may be identified and provide important structural knowledge. However the uncertainty...... by a simulation study of a lightly damped single degree of freedom system. Identification by ARMA models has been chosen 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...
Iterative integral parameter identification of a respiratory mechanics model
Directory of Open Access Journals (Sweden)
Schranz Christoph
2012-07-01
Full Text Available Abstract Background 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. Methods 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. Results 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. Conclusion 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.
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.
Placek, Ben; Angerhausen, Daniel
2013-01-01
EXONEST is an algorithm dedicated to detecting and characterizing the photometric signatures of exoplanets, which include reflection and thermal emission, Doppler boosting, and ellipsoidal variations. Using Bayesian Inference, we can test between competing models that describe the data as well as estimate model parameters. We demonstrate this approach by testing circular versus eccentric planetary orbital models, as well as testing for the presence or absence of four photometric effects. In addition to using Bayesian Model Selection, a unique aspect of EXONEST is the capability to distinguish between reflective and thermal contributions to the light curve. A case-study is presented using Kepler data recorded from the transiting planet KOI-13b. By considering only the non-transiting portions of the light curve, we demonstrate that it is possible to estimate the photometrically-relevant model parameters of KOI-13b. Furthermore, Bayesian model testing confirms that the orbit of KOI-13b has a detectable eccentric...
Placek, Ben; Knuth, Kevin H.; Angerhausen, Daniel
2014-11-01
EXONEST is an algorithm dedicated to detecting and characterizing the photometric signatures of exoplanets, which include reflection and thermal emission, Doppler boosting, and ellipsoidal variations. Using Bayesian inference, we can test between competing models that describe the data as well as estimate model parameters. We demonstrate this approach by testing circular versus eccentric planetary orbital models, as well as testing for the presence or absence of four photometric effects. In addition to using Bayesian model selection, a unique aspect of EXONEST is the potential capability to distinguish between reflective and thermal contributions to the light curve. A case study is presented using Kepler data recorded from the transiting planet KOI-13b. By considering only the nontransiting portions of the light curve, we demonstrate that it is possible to estimate the photometrically relevant model parameters of KOI-13b. Furthermore, Bayesian model testing confirms that the orbit of KOI-13b has a detectable eccentricity.
Energy Technology Data Exchange (ETDEWEB)
Placek, Ben; Knuth, Kevin H. [Physics Department, University at Albany (SUNY), Albany, NY 12222 (United States); Angerhausen, Daniel, E-mail: bplacek@albany.edu, E-mail: kknuth@albany.edu, E-mail: daniel.angerhausen@gmail.com [Department of Physics, Applied Physics, and Astronomy, Rensselear Polytechnic Institute, Troy, NY 12180 (United States)
2014-11-10
EXONEST is an algorithm dedicated to detecting and characterizing the photometric signatures of exoplanets, which include reflection and thermal emission, Doppler boosting, and ellipsoidal variations. Using Bayesian inference, we can test between competing models that describe the data as well as estimate model parameters. We demonstrate this approach by testing circular versus eccentric planetary orbital models, as well as testing for the presence or absence of four photometric effects. In addition to using Bayesian model selection, a unique aspect of EXONEST is the potential capability to distinguish between reflective and thermal contributions to the light curve. A case study is presented using Kepler data recorded from the transiting planet KOI-13b. By considering only the nontransiting portions of the light curve, we demonstrate that it is possible to estimate the photometrically relevant model parameters of KOI-13b. Furthermore, Bayesian model testing confirms that the orbit of KOI-13b has a detectable eccentricity.
A Variational Bayes Genomic-Enabled Prediction Model with Genotype × Environment Interaction
Directory of Open Access Journals (Sweden)
Osval A. Montesinos-López
2017-06-01
Full Text Available There are Bayesian and non-Bayesian genomic models that take into account G×E interactions. However, the computational cost of implementing Bayesian models is high, and becomes almost impossible when the number of genotypes, environments, and traits is very large, while, in non-Bayesian models, there are often important and unsolved convergence problems. The variational Bayes method is popular in machine learning, and, by approximating the probability distributions through optimization, it tends to be faster than Markov Chain Monte Carlo methods. For this reason, in this paper, we propose a new genomic variational Bayes version of the Bayesian genomic model with G×E using half-t priors on each standard deviation (SD term to guarantee highly noninformative and posterior inferences that are not sensitive to the choice of hyper-parameters. We show the complete theoretical derivation of the full conditional and the variational posterior distributions, and their implementations. We used eight experimental genomic maize and wheat data sets to illustrate the new proposed variational Bayes approximation, and compared its predictions and implementation time with a standard Bayesian genomic model with G×E. Results indicated that prediction accuracies are slightly higher in the standard Bayesian model with G×E than in its variational counterpart, but, in terms of computation time, the variational Bayes genomic model with G×E is, in general, 10 times faster than the conventional Bayesian genomic model with G×E. For this reason, the proposed model may be a useful tool for researchers who need to predict and select genotypes in several environments.
Variations in Modeled Dengue Transmission over Puerto Rico Using a Climate Driven Dynamic Model
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.
Modelling Biophysical Parameters of Maize Using Landsat 8 Time Series
Dahms, Thorsten; Seissiger, Sylvia; Conrad, Christopher; Borg, Erik
2016-06-01
Open and free access to multi-frequent high-resolution data (e.g. Sentinel - 2) will fortify agricultural applications based on satellite data. The temporal and spatial resolution of these remote sensing datasets directly affects the applicability of remote sensing methods, for instance a robust retrieving of biophysical parameters over the entire growing season with very high geometric resolution. In this study we use machine learning methods to predict biophysical parameters, namely the fraction of absorbed photosynthetic radiation (FPAR), the leaf area index (LAI) and the chlorophyll content, from high resolution remote sensing. 30 Landsat 8 OLI scenes were available in our study region in Mecklenburg-Western Pomerania, Germany. In-situ data were weekly to bi-weekly collected on 18 maize plots throughout the summer season 2015. The study aims at an optimized prediction of biophysical parameters and the identification of the best explaining spectral bands and vegetation indices. For this purpose, we used the entire in-situ dataset from 24.03.2015 to 15.10.2015. Random forest and conditional inference forests were used because of their explicit strong exploratory and predictive character. Variable importance measures allowed for analysing the relation between the biophysical parameters with respect to the spectral response, and the performance of the two approaches over the plant stock evolvement. Classical random forest regression outreached the performance of conditional inference forests, in particular when modelling the biophysical parameters over the entire growing period. For example, modelling biophysical parameters of maize for the entire vegetation period using random forests yielded: FPAR: R² = 0.85; RMSE = 0.11; LAI: R² = 0.64; RMSE = 0.9 and chlorophyll content (SPAD): R² = 0.80; RMSE=4.9. Our results demonstrate the great potential in using machine-learning methods for the interpretation of long-term multi-frequent remote sensing datasets to model
Magnetized anisotropic dark energy models with constant deceleration parameter
Indian Academy of Sciences (India)
A Y SHAIKH; S D KATORE
2016-12-01
In this paper, we have studied the solutions of plane-symmetric Universe with variable $\\omega$ in the presence and the absence of magnetic field of energy density $\\rho B$. A special law of variation for Hubble’s parameterproposed by Bermann in {\\it Nuovo Cimento} B 74, 182 (1983) has been utilized to solve the field equations. Some physical and kinematical properties of the models are also discussed.
Methane variations on orbital timescales: a transient modeling experiment
Directory of Open Access Journals (Sweden)
T. Y. M. Konijnendijk
2011-06-01
Full Text Available Methane (CH_{4} variations on orbital timescales are often associated with variations in wetland coverage, most notably in the summer monsoon areas of the Northern Hemisphere. Here we test this assumption by simulating orbitally forced variations in global wetland emissions, using a simple wetland distribution and CH_{4} emissions model that has been run on the output of a climate model (CLIMBER-2 containing atmosphere, ocean and vegetation components. The transient climate modeling simulation extends over the last 650 000 yr and includes variations in land-ice distribution and greenhouse gases. Tropical temperature and global vegetation are found to be the dominant controls for global CH_{4} emissions and therefore atmospheric concentrations. The relative importance of wetland coverage, vegetation coverage, and emission temperatures depends on the specific climatic zone (boreal, tropics and Indian/Asian monsoon area and timescale (precession, obliquity and glacial-interglacial timescales. Despite the low spatial resolution of the climate model and crude parameterizations for methane production and release, simulated variations in CH_{4} emissions agree well with those in measured concentrations, both in their time series and spectra. The simulated lags between emissions and orbital forcing also show close agreement with those found in measured data, both on the precession and obliquity timescale. We find causal links between atmospheric CH_{4} concentrations and tropical temperatures and global vegetation, but only covariance between monsoon precipitation and CH_{4} concentrations. The primary importance of the first two factors explains the lags found in the CH_{4} record from ice cores. Simulation of the dynamical vegetation response to climate variation on orbital timescales would be needed to reduce the uncertainty in these preliminary attributions.
High correlation of double Debye model parameters in skin cancer detection.
Truong, Bao C Q; Tuan, H D; Fitzgerald, Anthony J; Wallace, Vincent P; Nguyen, H T
2014-01-01
The double Debye model can be used to capture the dielectric response of human skin in terahertz regime due to high water content in the tissue. The increased water proportion is widely considered as a biomarker of carcinogenesis, which gives rise of using this model in skin cancer detection. Therefore, the goal of this paper is to provide a specific analysis of the double Debye parameters in terms of non-melanoma skin cancer classification. Pearson correlation is applied to investigate the sensitivity of these parameters and their combinations to the variation in tumor percentage of skin samples. The most sensitive parameters are then assessed by using the receiver operating characteristic (ROC) plot to confirm their potential of classifying tumor from normal skin. Our positive outcomes support further steps to clinical application of terahertz imaging in skin cancer delineation.
Joint Dynamics Modeling and Parameter Identification for Space Robot Applications
Directory of Open Access Journals (Sweden)
Adenilson R. da Silva
2007-01-01
Full Text Available Long-term mission identification and model validation for in-flight manipulator control system in almost zero gravity with hostile space environment are extremely important for robotic applications. In this paper, a robot joint mathematical model is developed where several nonlinearities have been taken into account. In order to identify all the required system parameters, an integrated identification strategy is derived. This strategy makes use of a robust version of least-squares procedure (LS for getting the initial conditions and a general nonlinear optimization method (MCS—multilevel coordinate search—algorithm to estimate the nonlinear parameters. The approach is applied to the intelligent robot joint (IRJ experiment that was developed at DLR for utilization opportunity on the International Space Station (ISS. The results using real and simulated measurements have shown that the developed algorithm and strategy have remarkable features in identifying all the parameters with good accuracy.
Mathematical Modelling and Parameter Optimization of Pulsating Heat Pipes
Yang, Xin-She; Luan, Tao; Koziel, Slawomir
2014-01-01
Proper heat transfer management is important to key electronic components in microelectronic applications. Pulsating heat pipes (PHP) can be an efficient solution to such heat transfer problems. However, mathematical modelling of a PHP system is still very challenging, due to the complexity and multiphysics nature of the system. In this work, we present a simplified, two-phase heat transfer model, and our analysis shows that it can make good predictions about startup characteristics. Furthermore, by considering parameter estimation as a nonlinear constrained optimization problem, we have used the firefly algorithm to find parameter estimates efficiently. We have also demonstrated that it is possible to obtain good estimates of key parameters using very limited experimental data.
The influences of model parameters on the characteristics of memristors
Institute of Scientific and Technical Information of China (English)
Zhou Jing; Huang Da
2012-01-01
As the fourth passive circuit component,a memristor is a nonlinear resistor that can "remember" the amount of charge passing through it.The characteristic of "remembering" the charge and non-volatility makes memristors great potential candidates in many fields.Nowadays,only a few groups have the ability to fabricate memristors,and most researchers study them by theoretic analysis and simulation.In this paper,we first analyse the theoretical base and characteristics of memristors,then use a simulation program with integrated circuit emphasis as our tool to simulate the theoretical model of memristors and change the parameters in the model to see the influence of each parameter on the characteristics.Our work supplies researchers engaged in memristor-based circuits with advice on how to choose the proper parameters.
Directory of Open Access Journals (Sweden)
Eugene Ruzagira
Full Text Available To investigate the effect of seasonal variation on adult clinical laboratory parameters in Rwanda, Zambia, and Uganda and determine its implications for HIV prevention and other clinical trials.Volunteers in a cross-sectional study to establish laboratory reference intervals were asked to return for a seasonal visit after the local season had changed from dry to rainy or vice versa. Volunteers had to be clinically healthy, not pregnant and negative for HIV, Hepatitis B and C, and syphilis infection at both visits. At each visit, blood was taken for measurement of hemoglobin, haematocrit, mean corpuscular volume, red blood cells, platelets, total white blood cells (WBC, neutrophils, lymphocytes, monocytes, eosinophils, basophils, CD4/CD8 T cells, aspartate aminotransferase, alanine aminotransferase, alkaline phosphatase, direct bilirubin, total bilirubin, total immunoglobulin gamma, total protein, creatinine, total amylase, creatine phosphokinase and lactate dehydrogenase (LDH. Consensus dry season reference intervals were applied to rainy season values (and vice versa and the proportion of 'out-of-range' values determined. Percentage differences between dry and rainy season parameter mean values were estimated.In this cohort of 903 volunteers, less than 10.0% of consensus parameter (except LDH values in one season were "out-of-range" in the other. Twenty-two (22 percent of rainy season LDH values fell outside of the consensus dry season interval with the higher values observed in the rainy season. Variability between consensus seasonal means ranged from 0.0% (total WBC, neutrophils, monocytes, basophils, and direct bilirubin to 40.0% (eosinophils. Within sites, the largest seasonal variations were observed for monocytes (Masaka, 11.5%, LDH (Lusaka, 21.7%, and basophils (Kigali, 22.2%.Seasonality had minimal impact on adult clinical laboratory parameter values in Rwanda, Zambia, and Uganda. Seasonal variation may not be an important factor in the
Estimation of parameters in a distributed precipitation-runoff model for Norway
Directory of Open Access Journals (Sweden)
S. Beldring
2003-01-01
Full Text Available A distributed version of the HBV-model using 1 km2 grid cells and daily time step was used to simulate runoff from the entire land surface of Norway for the period 1961-1990. The model was sensitive to changes in small scale properties of the land surface and the climatic input data, through explicit representation of differences between model elements, and by implicit consideration of sub-grid variations in moisture status. A geographically transferable set of model parameters was determined by a multi-criteria calibration strategy, which simultaneously minimised the residuals between model simulated and observed runoff from 141 Norwegian catchments located in areas with different runoff regimes and landscape characteristics. Model discretisation units with identical landscape classification were assigned similar parameter values. Model performance was evaluated by simulating discharge from 43 independent catchments. Finally, a river routing procedure using a kinematic wave approximation to open channel flow was introduced in the model, and discharges from three additional catchments were calculated and compared with observations. The model was used to produce a map of average annual runoff for Norway for the period 1961-1990. Keywords: distributed model, multi-criteria calibration, global parameters, ungauged catchments.
Revised Parameters for the AMOEBA Polarizable Atomic Multipole Water Model.
Laury, Marie L; Wang, Lee-Ping; Pande, Vijay S; Head-Gordon, Teresa; Ponder, Jay W
2015-07-23
A set of improved parameters for the AMOEBA polarizable atomic multipole water model is developed. An automated procedure, ForceBalance, is used to adjust model parameters to enforce agreement with ab initio-derived results for water clusters and experimental data for a variety of liquid phase properties across a broad temperature range. The values reported here for the new AMOEBA14 water model represent a substantial improvement over the previous AMOEBA03 model. The AMOEBA14 model accurately predicts the temperature of maximum density and qualitatively matches the experimental density curve across temperatures from 249 to 373 K. Excellent agreement is observed for the AMOEBA14 model in comparison to experimental properties as a function of temperature, including the second virial coefficient, enthalpy of vaporization, isothermal compressibility, thermal expansion coefficient, and dielectric constant. The viscosity, self-diffusion constant, and surface tension are also well reproduced. In comparison to high-level ab initio results for clusters of 2-20 water molecules, the AMOEBA14 model yields results similar to AMOEBA03 and the direct polarization iAMOEBA models. With advances in computing power, calibration data, and optimization techniques, we recommend the use of the AMOEBA14 water model for future studies employing a polarizable water model.
Online variational inference for state-space models with point-process observations.
Mangion, Andrew Zammit; Yuan, Ke; Kadirkamanathan, Visakan; Niranjan, Mahesan; Sanguinetti, Guido
2011-08-01
We present a variational Bayesian (VB) approach for the state and parameter inference of a state-space model with point-process observations, a physiologically plausible model for signal processing of spike data. We also give the derivation of a variational smoother, as well as an efficient online filtering algorithm, which can also be used to track changes in physiological parameters. The methods are assessed on simulated data, and results are compared to expectation-maximization, as well as Monte Carlo estimation techniques, in order to evaluate the accuracy of the proposed approach. The VB filter is further assessed on a data set of taste-response neural cells, showing that the proposed approach can effectively capture dynamical changes in neural responses in real time.
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
In Bayesian analysis of a statistical model, the predictive distribution is obtained by marginalizing over the parameters with their posterior distributions. Compared to the frequently used point estimate plug-in method, the predictive distribution leads to a more reliable result in calculating...... 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...
Comparison of Parameter Estimation Methods for Transformer Weibull Lifetime Modelling
Institute of Scientific and Technical Information of China (English)
ZHOU Dan; LI Chengrong; WANG Zhongdong
2013-01-01
Two-parameter Weibull distribution is the most widely adopted lifetime model for power transformers.An appropriate parameter estimation method is essential to guarantee the accuracy of a derived Weibull lifetime model.Six popular parameter estimation methods (i.e.the maximum likelihood estimation method,two median rank regression methods including the one regressing X on Y and the other one regressing Y on X,the Kaplan-Meier method,the method based on cumulative hazard plot,and the Li's method) are reviewed and compared in order to find the optimal one that suits transformer's Weibull lifetime modelling.The comparison took several different scenarios into consideration:10 000 sets of lifetime data,each of which had a sampling size of 40 ～ 1 000 and a censoring rate of 90％,were obtained by Monte-Carlo simulations for each scienario.Scale and shape parameters of Weibull distribution estimated by the six methods,as well as their mean value,median value and 90％ confidence band are obtained.The cross comparison of these results reveals that,among the six methods,the maximum likelihood method is the best one,since it could provide the most accurate Weibull parameters,i.e.parameters having the smallest bias in both mean and median values,as well as the shortest length of the 90％ confidence band.The maximum likelihood method is therefore recommended to be used over the other methods in transformer Weibull lifetime modelling.
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.
Variational Boussinesq model for simulation of coastal waves and tsunamis
Adytia, D.; Adytia, Didit; van Groesen, Embrecht W.C.; Tan, Soon Keat; Huang, Zhenhua
2009-01-01
In this paper we describe the basic ideas of a so-called Variational Boussinesq Model which is based on the Hamiltonian structure of gravity surface waves. By using a rather simple approach to prescribe the profile of vertical fluid potential in the expression for the kinetic energy, we obtain a set
Synaptic channel model including effects of spike width variation
2015-01-01
Synaptic Channel Model Including Effects of Spike Width Variation Hamideh Ramezani Next-generation and Wireless Communications Laboratory (NWCL) Department of Electrical and Electronics Engineering Koc University, Istanbul, Turkey Ozgur B. Akan Next-generation and Wireless Communications Laboratory (NWCL) Department of Electrical and Electronics Engineering Koc University, Istanbul, Turkey ABSTRACT An accu...
Variational Boussinesq model for simulations of coastal waves and tsunamis
Adytia, Didit; Groesen, van E.; Tan, Soon Keat; Huang, Zhenhua
2009-01-01
In this paper we describe the basic ideas of a so-called Variational Boussinesq Model which is based on the Hamiltonian structure of gravity surface waves. By using a rather simple approach to prescribe the profile of vertical fluid potential in the expression for the kinetic energy, we obtain a set
Calculation of Thermodynamic Parameters for Freundlich and Temkin Isotherm Models
Institute of Scientific and Technical Information of China (English)
ZHANGZENGQIANG; ZHANGYIPING; 等
1999-01-01
Derivation of the Freundlich and Temkin isotherm models from the kinetic adsorption/desorption equations was carried out to calculate their thermodynamic equilibrium constants.The calculation formulase of three thermodynamic parameters,the standard molar Gibbs free energy change,the standard molar enthalpy change and the standard molar entropy change,of isothermal adsorption processes for Freundlich and Temkin isotherm models were deduced according to the relationship between the thermodynamic equilibrium constants and the temperature.
Parameter Estimation for a Computable General Equilibrium Model
DEFF Research Database (Denmark)
Arndt, Channing; Robinson, Sherman; Tarp, Finn
2002-01-01
We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (CGE) models. The approach applies information theory to estimating a system of non-linear simultaneous equations. It has a number of advantages. First, it imposes all general equilibrium constraints...
Parabolic problems with parameters arising in evolution model for phytromediation
Sahmurova, Aida; Shakhmurov, Veli
2012-12-01
The past few decades, efforts have been made to clean sites polluted by heavy metals as chromium. One of the new innovative methods of eradicating metals from soil is phytoremediation. This uses plants to pull metals from the soil through the roots. This work develops a system of differential equations with parameters to model the plant metal interaction of phytoremediation (see [1]).
Lumped-parameter Model of a Bucket Foundation
DEFF Research Database (Denmark)
Andersen, Lars; Ibsen, Lars Bo; Liingaard, Morten
2009-01-01
As an alternative to gravity footings or pile foundations, offshore wind turbines at shallow water can be placed on a bucket foundation. The present analysis concerns the development of consistent lumped-parameter models for this type of foundation. The aim is to formulate a computationally effic...
Improved parameter estimation for hydrological models using weighted object functions
Stein, A.; Zaadnoordijk, W.J.
1999-01-01
This paper discusses the sensitivity of calibration of hydrological model parameters to different objective functions. Several functions are defined with weights depending upon the hydrological background. These are compared with an objective function based upon kriging. Calibration is applied to pi
Parameter Estimation for a Computable General Equilibrium Model
DEFF Research Database (Denmark)
Arndt, Channing; Robinson, Sherman; Tarp, Finn
We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (CGE) models. The approach applies information theory to estimating a system of nonlinear simultaneous equations. It has a number of advantages. First, it imposes all general equilibrium constraints...
PARAMETER ESTIMATION IN LINEAR REGRESSION MODELS FOR LONGITUDINAL CONTAMINATED DATA
Institute of Scientific and Technical Information of China (English)
QianWeimin; LiYumei
2005-01-01
The parameter estimation and the coefficient of contamination for the regression models with repeated measures are studied when its response variables are contaminated by another random variable sequence. Under the suitable conditions it is proved that the estimators which are established in the paper are strongly consistent estimators.
Modeling and simulation of HTS cables for scattering parameter analysis
Bang, Su Sik; Lee, Geon Seok; Kwon, Gu-Young; Lee, Yeong Ho; Chang, Seung Jin; Lee, Chun-Kwon; Sohn, Songho; Park, Kijun; Shin, Yong-June
2016-11-01
Most of modeling and simulation of high temperature superconducting (HTS) cables are inadequate for high frequency analysis since focus of the simulation's frequency is fundamental frequency of the power grid, which does not reflect transient characteristic. However, high frequency analysis is essential process to research the HTS cables transient for protection and diagnosis of the HTS cables. Thus, this paper proposes a new approach for modeling and simulation of HTS cables to derive the scattering parameter (S-parameter), an effective high frequency analysis, for transient wave propagation characteristics in high frequency range. The parameters sweeping method is used to validate the simulation results to the measured data given by a network analyzer (NA). This paper also presents the effects of the cable-to-NA connector in order to minimize the error between the simulated and the measured data under ambient and superconductive conditions. Based on the proposed modeling and simulation technique, S-parameters of long-distance HTS cables can be accurately derived in wide range of frequency. The results of proposed modeling and simulation can yield the characteristics of the HTS cables and will contribute to analyze the HTS cables.
Directory of Open Access Journals (Sweden)
Paige Lacy
Full Text Available We discovered that serious issues could arise that may complicate interpretation of metabolomic data when identical samples are analyzed at more than one NMR facility, or using slightly different NMR parameters on the same instrument. This is important because cross-center validation metabolomics studies are essential for the reliable application of metabolomics to clinical biomarker discovery. To test the reproducibility of quantified metabolite data at multiple sites, technical replicates of urine samples were assayed by 1D-(1H-NMR at the University of Alberta and the University of Michigan. Urine samples were obtained from healthy controls under a standard operating procedure for collection and processing. Subsequent analysis using standard statistical techniques revealed that quantitative data across sites can be achieved, but also that previously unrecognized NMR parameter differences can dramatically and widely perturb results. We present here a confirmed validation of NMR analysis at two sites, and report the range and magnitude that common NMR parameters involved in solvent suppression can have on quantitated metabolomics data. Specifically, saturation power levels greatly influenced peak height intensities in a frequency-dependent manner for a number of metabolites, which markedly impacted the quantification of metabolites. We also investigated other NMR parameters to determine their effects on further quantitative accuracy and precision. Collectively, these findings highlight the importance of and need for consistent use of NMR parameter settings within and across centers in order to generate reliable, reproducible quantified NMR metabolomics data.
Non-linear regression model for spatial variation in precipitation chemistry for South India
Siva Soumya, B.; Sekhar, M.; Riotte, J.; Braun, Jean-Jacques
Chemical composition of rainwater changes from sea to inland under the influence of several major factors - topographic location of area, its distance from sea, annual rainfall. A model is developed here to quantify the variation in precipitation chemistry under the influence of inland distance and rainfall amount. Various sites in India categorized as 'urban', 'suburban' and 'rural' have been considered for model development. pH, HCO 3, NO 3 and Mg do not change much from coast to inland while, SO 4 and Ca change is subjected to local emissions. Cl and Na originate solely from sea salinity and are the chemistry parameters in the model. Non-linear multiple regressions performed for the various categories revealed that both rainfall amount and precipitation chemistry obeyed a power law reduction with distance from sea. Cl and Na decrease rapidly for the first 100 km distance from sea, then decrease marginally for the next 100 km, and later stabilize. Regression parameters estimated for different cases were found to be consistent ( R2 ˜ 0.8). Variation in one of the parameters accounted for urbanization. Model was validated using data points from the southern peninsular region of the country. Estimates are found to be within 99.9% confidence interval. Finally, this relationship between the three parameters - rainfall amount, coastline distance, and concentration (in terms of Cl and Na) was validated with experiments conducted in a small experimental watershed in the south-west India. Chemistry estimated using the model was in good correlation with observed values with a relative error of ˜5%. Monthly variation in the chemistry is predicted from a downscaling model and then compared with the observed data. Hence, the model developed for rain chemistry is useful in estimating the concentrations at different spatio-temporal scales and is especially applicable for south-west region of India.
Chen, Qian; Shou, Weiling; Wu, Wei; Guo, Ye; Zhang, Yujuan; Huang, Chunmei; Cui, Wei
2015-04-01
To accurately estimate longitudinal changes in individuals, it is important to take into consideration the biological variability of the measurement. The few studies available on the biological variations of coagulation parameters are mostly outdated. We confirmed the published results using modern, fully automated methods. Furthermore, we added data for additional coagulation parameters. At 8:00 am, 12:00 pm, and 4:00 pm on days 1, 3, and 5, venous blood was collected from 31 healthy volunteers. A total of 16 parameters related to coagulation screening tests as well as the activity of coagulation factors were analyzed; these included prothrombin time, fibrinogen (Fbg), activated partial thromboplastin time, thrombin time, international normalized ratio, prothrombin time activity, activated partial thromboplastin time ratio, fibrin(-ogen) degradation products, as well as the activity of factor II, factor V, factor VII, factor VIII, factor IX, and factor X. All intraindividual coefficients of variation (CVI) values for the parameters of the screening tests (except Fbg) were less than 5%. Conversely, the CVI values for the activity of coagulation factors were all greater than 5%. In addition, we calculated the reference change value to determine whether a significant difference exists between two test results from the same individual.
Evaluation of some infiltration models and hydraulic parameters
Energy Technology Data Exchange (ETDEWEB)
Haghighi, F.; Gorji, M.; Shorafa, M.; Sarmadian, F.; Mohammadi, M. H.
2010-07-01
The evaluation of infiltration characteristics and some parameters of infiltration models such as sorptivity and final steady infiltration rate in soils are important in agriculture. The aim of this study was to evaluate some of the most common models used to estimate final soil infiltration rate. The equality of final infiltration rate with saturated hydraulic conductivity (Ks) was also tested. Moreover, values of the estimated sorptivity from the Philips model were compared to estimates by selected pedotransfer functions (PTFs). The infiltration experiments used the doublering method on soils with two different land uses in the Taleghan watershed of Tehran province, Iran, from September to October, 2007. The infiltration models of Kostiakov-Lewis, Philip two-term and Horton were fitted to observed infiltration data. Some parameters of the models and the coefficient of determination goodness of fit were estimated using MATLAB software. The results showed that, based on comparing measured and model-estimated infiltration rate using root mean squared error (RMSE), Hortons model gave the best prediction of final infiltration rate in the experimental area. Laboratory measured Ks values gave significant differences and higher values than estimated final infiltration rates from the selected models. The estimated final infiltration rate was not equal to laboratory measured Ks values in the study area. Moreover, the estimated sorptivity factor by Philips model was significantly different to those estimated by selected PTFs. It is suggested that the applicability of PTFs is limited to specific, similar conditions. (Author) 37 refs.
Agricultural and Environmental Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
K. Rasmuson; K. Rautenstrauch
2004-09-14
This analysis is one of 10 technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) (i.e., the biosphere model). It documents development of agricultural and environmental 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 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 ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the ERMYN and its input parameters.
Estimating model parameters in nonautonomous chaotic systems using synchronization
Yang, Xiaoli; Xu, Wei; Sun, Zhongkui
2007-05-01
In this Letter, a technique is addressed for estimating unknown model parameters of multivariate, in particular, nonautonomous chaotic systems from time series of state variables. This technique uses an adaptive strategy for tracking unknown parameters in addition to a linear feedback coupling for synchronizing systems, and then some general conditions, by means of the periodic version of the LaSalle invariance principle for differential equations, are analytically derived to ensure precise evaluation of unknown parameters and identical synchronization between the concerned experimental system and its corresponding receiver one. Exemplifies are presented by employing a parametrically excited 4D new oscillator and an additionally excited Ueda oscillator. The results of computer simulations reveal that the technique not only can quickly track the desired parameter values but also can rapidly respond to changes in operating parameters. In addition, the technique can be favorably robust against the effect of noise when the experimental system is corrupted by bounded disturbance and the normalized absolute error of parameter estimation grows almost linearly with the cutoff value of noise strength in simulation.
Estimating model parameters in nonautonomous chaotic systems using synchronization
Energy Technology Data Exchange (ETDEWEB)
Yang, Xiaoli [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China)]. E-mail: yangxl205@mail.nwpu.edu.cn; Xu, Wei [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China); Sun, Zhongkui [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China)
2007-05-07
In this Letter, a technique is addressed for estimating unknown model parameters of multivariate, in particular, nonautonomous chaotic systems from time series of state variables. This technique uses an adaptive strategy for tracking unknown parameters in addition to a linear feedback coupling for synchronizing systems, and then some general conditions, by means of the periodic version of the LaSalle invariance principle for differential equations, are analytically derived to ensure precise evaluation of unknown parameters and identical synchronization between the concerned experimental system and its corresponding receiver one. Exemplifies are presented by employing a parametrically excited 4D new oscillator and an additionally excited Ueda oscillator. The results of computer simulations reveal that the technique not only can quickly track the desired parameter values but also can rapidly respond to changes in operating parameters. In addition, the technique can be favorably robust against the effect of noise when the experimental system is corrupted by bounded disturbance and the normalized absolute error of parameter estimation grows almost linearly with the cutoff value of noise strength in simulation.
Localization of periodic orbits of the Roessler system under variation of its parameters
Energy Technology Data Exchange (ETDEWEB)
Starkov, Konstantin E. [CITEDI-IPN, Av. del Parque 1310, Mesa de Otay, Tijuana, BC (Mexico)]. E-mail: konst@citedi.mx; Starkov, Konstantin K. [UABC - Campus Tijuana, Facultad de Ciencias Quimicas e Ingenieria, Calzada Tecnologico, Mesa de Otay, Tijuana, BC (Mexico)
2007-08-15
The localization problem of compact invariant sets of the Roessler system is considered in this paper. The main interest is attracted to a localization of periodic orbits. We establish a number of algebraic conditions imposed on parameters under which the Roessler system has no compact invariant sets contained in half-spaces z > 0; z < 0 and in some others. We prove that if parameters (a, b, c) of the Roessler system are such that this system has no equilibrium points then it has no periodic orbits as well. In addition, we give localization conditions of compact invariant sets by using linear functions and one quadratic function.
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
Multiscale Parameter Regionalization for consistent global water resources modelling
Wanders, Niko; Wood, Eric; Pan, Ming; Samaniego, Luis; Thober, Stephan; Kumar, Rohini; Sutanudjaja, Edwin; van Beek, Rens; Bierkens, Marc F. P.
2017-04-01
Due to an increasing demand for high- and hyper-resolution water resources information, it has become increasingly important to ensure consistency in model simulations across scales. This consistency can be ensured by scale independent parameterization of the land surface processes, even after calibration of the water resource model. Here, we use the Multiscale Parameter Regionalization technique (MPR, Samaniego et al. 2010, WRR) to allow for a novel, spatially consistent, scale independent parameterization of the global water resource model PCR-GLOBWB. The implementation of MPR in PCR-GLOBWB allows for calibration at coarse resolutions and subsequent parameter transfer to the hyper-resolution. In this study, the model was calibrated at 50 km resolution over Europe and validation carried out at resolutions of 50 km, 10 km and 1 km. MPR allows for a direct transfer of the calibrated transfer function parameters across scales and we find that we can maintain consistent land-atmosphere fluxes across scales. Here we focus on the 2003 European drought and show that the new parameterization allows for high-resolution calibrated simulations of water resources during the drought. For example, we find a reduction from 29% to 9.4% in the percentile difference in the annual evaporative flux across scales when compared against default simulations. Soil moisture errors are reduced from 25% to 6.9%, clearly indicating the benefits of the MPR implementation. This new parameterization allows us to show more spatial detail in water resources simulations that are consistent across scales and also allow validation of discharge for smaller catchments, even with calibrations at a coarse 50 km resolution. The implementation of MPR allows for novel high-resolution calibrated simulations of a global water resources model, providing calibrated high-resolution model simulations with transferred parameter sets from coarse resolutions. The applied methodology can be transferred to other
Model and parameter uncertainty in IDF relationships under climate change
Chandra, Rupa; Saha, Ujjwal; Mujumdar, P. P.
2015-05-01
Quantifying distributional behavior of extreme events is crucial in hydrologic designs. Intensity Duration Frequency (IDF) relationships are used extensively in engineering especially in urban hydrology, to obtain return level of extreme rainfall event for a specified return period and duration. Major sources of uncertainty in the IDF relationships are due to insufficient quantity and quality of data leading to parameter uncertainty due to the distribution fitted to the data and uncertainty as a result of using multiple GCMs. It is important to study these uncertainties and propagate them to future for accurate assessment of return levels for future. The objective of this study is to quantify the uncertainties arising from parameters of the distribution fitted to data and the multiple GCM models using Bayesian approach. Posterior distribution of parameters is obtained from Bayes rule and the parameters are transformed to obtain return levels for a specified return period. Markov Chain Monte Carlo (MCMC) method using Metropolis Hastings algorithm is used to obtain the posterior distribution of parameters. Twenty six CMIP5 GCMs along with four RCP scenarios are considered for studying the effects of climate change and to obtain projected IDF relationships for the case study of Bangalore city in India. GCM uncertainty due to the use of multiple GCMs is treated using Reliability Ensemble Averaging (REA) technique along with the parameter uncertainty. Scale invariance theory is employed for obtaining short duration return levels from daily data. It is observed that the uncertainty in short duration rainfall return levels is high when compared to the longer durations. Further it is observed that parameter uncertainty is large compared to the model uncertainty.
Image Denoising Using Total Variation Model Guided by Steerable Filter
Directory of Open Access Journals (Sweden)
Wenxue Zhang
2014-01-01
Full Text Available We propose an adaptive total variation (TV model by introducing the steerable filter into the TV-based diffusion process for image filtering. The local energy measured by the steerable filter can effectively characterize the object edges and ramp regions and guide the TV-based diffusion process so that the new model behaves like the TV model at edges and leads to linear diffusion in flat and ramp regions. This way, the proposed model can provide a better image processing tool which enables noise removal, edge-preserving, and staircase suppression.
Feng, Bin; Shi, Zelin; Zhang, Chengshuo; Xu, Baoshu; Zhang, Xiaodong
2016-05-01
The point spread function (PSF) inconsistency caused by temperature variation leads to artifacts in decoded images of a wavefront coding infrared imaging system. Therefore, this paper proposes an analytical model for the effect of temperature variation on the PSF consistency. In the proposed model, a formula for the thermal deformation of an optical phase mask is derived. This formula indicates that a cubic optical phase mask (CPM) is still cubic after thermal deformation. A proposed equivalent cubic phase mask (E-CPM) is a virtual and room-temperature lens which characterizes the optical effect of temperature variation on the CPM. Additionally, a calculating method for PSF consistency after temperature variation is presented. Numerical simulation illustrates the validity of the proposed model and some significant conclusions are drawn. Given the form parameter, the PSF consistency achieved by a Ge-material CPM is better than the PSF consistency by a ZnSe-material CPM. The effect of the optical phase mask on PSF inconsistency is much slighter than that of the auxiliary lens group. A large form parameter of the CPM will introduce large defocus-insensitive aberrations, which improves the PSF consistency but degrades the room-temperature MTF.
Cognitive Modeling of Individual Variation in Reference Production and Comprehension.
Hendriks, Petra
2016-01-01
A challenge for most theoretical and computational accounts of linguistic reference is the observation that language users vary considerably in their referential choices. Part of the variation observed among and within language users and across tasks may be explained from variation in the cognitive resources available to speakers and listeners. This paper presents a computational model of reference production and comprehension developed within the cognitive architecture ACT-R. Through simulations with this ACT-R model, it is investigated how cognitive constraints interact with linguistic constraints and features of the linguistic discourse in speakers' production and listeners' comprehension of referring expressions in specific tasks, and how this interaction may give rise to variation in referential choice. The ACT-R model of reference explains and predicts variation among language users in their referential choices as a result of individual and task-related differences in processing speed and working memory capacity. Because of limitations in their cognitive capacities, speakers sometimes underspecify or overspecify their referring expressions, and listeners sometimes choose incorrect referents or are overly liberal in their interpretation of referring expressions.
Cognitive Modeling of Individual Variation in Reference Production and Comprehension
Directory of Open Access Journals (Sweden)
Petra eHendriks
2016-04-01
Full Text Available A challenge for most theoretical and computational accounts of linguistic reference is the observation that language users vary considerably in their referential choices. Part of the variation observed among and within language users and across tasks may be explained from variation in the cognitive resources available to speakers and listeners. This paper presents a computational model of reference production and comprehension developed within the cognitive architecture ACT-R. Through simulations with this ACT-R model, it is investigated how cognitive constraints interact with linguistic constraints and features of the linguistic discourse in speakers’ production and listeners’ comprehension of referring expressions in specific tasks, and how this interaction may give rise to variation in referential choice. The ACT-R model of reference explains and predicts variation among language users in their referential choices as a result of individual and task-related differences in processing speed and working memory capacity. Because of limitations in their cognitive capacities, speakers sometimes underspecify or overspecify their referring expressions, and listeners sometimes choose incorrect referents or are overly liberal in their interpretation of referring expressions.