Review of Parameter Determination for Thermal Modeling of Lithium Ion Batteries

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Seyed Saeed Madani

2018-04-01

Full Text Available This paper reviews different methods for determination of thermal parameters of lithium ion batteries. Lithium ion batteries are extensively employed for various applications owing to their low memory effect, high specific energy, and power density. One of the problems in the expansion of hybrid and electric vehicle technology is the management and control of operation temperatures and heat generation. Successful battery thermal management designs can lead to better reliability and performance of hybrid and electric vehicles. Thermal cycling and temperature gradients could have a considerable impact on the lifetime of lithium ion battery cells. Thermal management is critical in electric vehicles (EVs and good thermal battery models are necessary to design proper heating and cooling systems. Consequently, it is necessary to determine thermal parameters of a single cell, such as internal resistance, specific heat capacity, entropic heat coefficient, and thermal conductivity in order to design suitable thermal management system.

Determining extreme parameter correlation in ground water models

DEFF Research Database (Denmark)

Hill, Mary Cole; Østerby, Ole

2003-01-01

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

Modelling of slaughterhouse solid waste anaerobic digestion: determination of parameters and continuous reactor simulation.

Science.gov (United States)

López, Iván; Borzacconi, Liliana

2010-10-01

A model based on the work of Angelidaki et al. (1993) was applied to simulate the anaerobic biodegradation of ruminal contents. In this study, two fractions of solids with different biodegradation rates were considered. A first-order kinetic was used for the easily biodegradable fraction and a kinetic expression that is function of the extracellular enzyme concentration was used for the slowly biodegradable fraction. Batch experiments were performed to obtain an accumulated methane curve that was then used to obtain the model parameters. For this determination, a methodology derived from the "multiple-shooting" method was successfully used. Monte Carlo simulations allowed a confidence range to be obtained for each parameter. Simulations of a continuous reactor were performed using the optimal set of model parameters. The final steady-states were determined as functions of the operational conditions (solids load and residence time). The simulations showed that methane flow peaked at a flow rate of 0.5-0.8 Nm(3)/d/m(reactor)(3) at a residence time of 10-20 days. Simulations allow the adequate selection of operating conditions of a continuous reactor. (c) 2010 Elsevier Ltd. All rights reserved.

Parameters Determination of Yoshida Uemori Model Through Optimization Process of Cyclic Tension-Compression Test and V-Bending Springback

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Serkan Toros

Full Text Available Abstract In recent years, the studies on the enhancement of the prediction capability of the sheet metal forming simulations have increased remarkably. Among the used models in the finite element simulations, the yield criteria and hardening models have a great importance for the prediction of the formability and springback. The required model parameters are determined by using the several test results, i.e. tensile, compression, biaxial stretching tests (bulge test and cyclic tests (tension-compression. In this study, the Yoshida-Uemori (combined isotropic and kinematic hardening model is used to determine the performance of the springback prediction. The model parameters are determined by the optimization processes of the cyclic test by finite element simulations. However, in the study besides the cyclic tests, the model parameters are also evaluated by the optimization process of both cyclic and V-die bending simulations. The springback angle predictions with the model parameters obtained by the optimization of both cyclic and V-die bending simulations are found to mimic the experimental results in a better way than those obtained from only cyclic tests. However, the cyclic simulation results are found to be close enough to the experimental results.

Assessing the accuracy of subject-specific, muscle-model parameters determined by optimizing to match isometric strength.

Science.gov (United States)

DeSmitt, Holly J; Domire, Zachary J

2016-12-01

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

Improving fault image by determination of optimum seismic survey parameters using ray-based modeling

Science.gov (United States)

Saffarzadeh, Sadegh; Javaherian, Abdolrahim; Hasani, Hossein; Talebi, Mohammad Ali

2018-06-01

In complex structures such as faults, salt domes and reefs, specifying the survey parameters is more challenging and critical owing to the complicated wave field behavior involved in such structures. In the petroleum industry, detecting faults has become crucial for reservoir potential where faults can act as traps for hydrocarbon. In this regard, seismic survey modeling is employed to construct a model close to the real structure, and obtain very realistic synthetic seismic data. Seismic modeling software, the velocity model and parameters pre-determined by conventional methods enable a seismic survey designer to run a shot-by-shot virtual survey operation. A reliable velocity model of structures can be constructed by integrating the 2D seismic data, geological reports and the well information. The effects of various survey designs can be investigated by the analysis of illumination maps and flower plots. Also, seismic processing of the synthetic data output can describe the target image using different survey parameters. Therefore, seismic modeling is one of the most economical ways to establish and test the optimum acquisition parameters to obtain the best image when dealing with complex geological structures. The primary objective of this study is to design a proper 3D seismic survey orientation to achieve fault zone structures through ray-tracing seismic modeling. The results prove that a seismic survey designer can enhance the image of fault planes in a seismic section by utilizing the proposed modeling and processing approach.

Reactive decontamination of absorbing thin film polymer coatings: model development and parameter determination

Science.gov (United States)

Varady, Mark; Mantooth, Brent; Pearl, Thomas; Willis, Matthew

2014-03-01

A continuum model of reactive decontamination in absorbing polymeric thin film substrates exposed to the chemical warfare agent O-ethyl S-[2-(diisopropylamino)ethyl] methylphosphonothioate (known as VX) was developed to assess the performance of various decontaminants. Experiments were performed in conjunction with an inverse analysis method to obtain the necessary model parameters. The experiments involved contaminating a substrate with a fixed VX exposure, applying a decontaminant, followed by a time-resolved, liquid phase extraction of the absorbing substrate to measure the residual contaminant by chromatography. Decontamination model parameters were uniquely determined using the Levenberg-Marquardt nonlinear least squares fitting technique to best fit the experimental time evolution of extracted mass. The model was implemented numerically in both a 2D axisymmetric finite element program and a 1D finite difference code, and it was found that the more computationally efficient 1D implementation was sufficiently accurate. The resulting decontamination model provides an accurate quantification of contaminant concentration profile in the material, which is necessary to assess exposure hazards.

Determination of the atrazine migration parameters in Vertisol

Science.gov (United States)

Raymundo-Raymundo, E.; Hernandez-Vargas, J.; Nikol'Skii, Yu. N.; Guber, A. K.; Gavi-Reyes, F.; Prado-Pano, B. L.; Figueroa-Sandoval, B.; Mendosa-Hernandez, J. R.

2010-05-01

The parameters of the atrazine migration in columns with undisturbed Vertisol sampled from an irrigated plot in Guanajuato, Mexico were determined. A model of the convection-dispersion transport of the chemical compounds accounting for the decomposition and equilibrium adsorption, which is widely applied for assessing the risk of contamination of natural waters with pesticides, was used. The model parameters were obtained by solving the inverse problem of the transport equation on the basis of laboratory experiments on the transport of the 18O isotope and atrazine in soil columns with an undisturbed structure at three filtration velocities. The model adequately described the experimental data at the individual selection of the parameters for each output curve. Physically unsubstantiated parameters of the atrazine adsorption and degradation were obtained when the parameter of the hydrodynamic dispersion was determined from the data on the 18O migration. The simulation also showed that the use of parameters obtained at water content close to saturation in the calculations for an unsaturated soil resulted in the overestimation of the leaching rate and the maximum concentration of atrazine in the output curve compared to the experimental data.

Black hole algorithm for determining model parameter in self-potential data

Science.gov (United States)

Sungkono; Warnana, Dwa Desa

2018-01-01

Analysis of self-potential (SP) data is increasingly popular in geophysical method due to its relevance in many cases. However, the inversion of SP data is often highly nonlinear. Consequently, local search algorithms commonly based on gradient approaches have often failed to find the global optimum solution in nonlinear problems. Black hole algorithm (BHA) was proposed as a solution to such problems. As the name suggests, the algorithm was constructed based on the black hole phenomena. This paper investigates the application of BHA to solve inversions of field and synthetic self-potential (SP) data. The inversion results show that BHA accurately determines model parameters and model uncertainty. This indicates that BHA is highly potential as an innovative approach for SP data inversion.

Improvement of LCM model and determination of model parameters at watershed scale for flood events in Hongde Basin of China

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Jun Li

2017-01-01

Full Text Available Considering the fact that the original two-parameter LCM model can only be used to investigate rainfall losses during the runoff period because the initial abstraction is not included, the LCM model was redefined as a three-parameter model, including the initial abstraction coefficient λ, the initial abstraction Ia, and the rainfall loss coefficient R. The improved LCM model is superior to the original two-parameter model, which only includes r and R, where r is the initial rainfall loss index and can be calculated with λ using the Soil Conservation Service curve number (SCS-CN method, with r=1/(1+λ. The trial method was used to determine the parameter values of the improved LCM model at the watershed scale for 15 flood events in the Hongde Basin in China. The results show that larger r values are associated with smaller R values, and the parameter R ranges widely from 0.5 to 2.0. In order to improve the practicability of the LCM model, r=0.833 with λ=0.2 is reasonable for simplifying calculation. When the LCM model is applied to arid and semi-arid regions, rainfall without yielding runoff should be deducted from the total rainfall for more accurate estimation of rainfall-runoff.

Determination of remodeling parameters for a strain-adaptive finite element model of the distal ulna.

Science.gov (United States)

Neuert, Mark A C; Dunning, Cynthia E

2013-09-01

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

Parameter estimation and determinability analysis applied to Drosophila gap gene circuits

Directory of Open Access Journals (Sweden)

Jaeger Johannes

2008-09-01

Full Text Available Abstract Background Mathematical modeling of real-life processes often requires the estimation of unknown parameters. Once the parameters are found by means of optimization, it is important to assess the quality of the parameter estimates, especially if parameter values are used to draw biological conclusions from the model. Results In this paper we describe how the quality of parameter estimates can be analyzed. We apply our methodology to assess parameter determinability for gene circuit models of the gap gene network in early Drosophila embryos. Conclusion Our analysis shows that none of the parameters of the considered model can be determined individually with reasonable accuracy due to correlations between parameters. Therefore, the model cannot be used as a tool to infer quantitative regulatory weights. On the other hand, our results show that it is still possible to draw reliable qualitative conclusions on the regulatory topology of the gene network. Moreover, it improves previous analyses of the same model by allowing us to identify those interactions for which qualitative conclusions are reliable, and those for which they are ambiguous.

Determining Spacecraft Reaction Wheel Friction Parameters

Science.gov (United States)

Sarani, Siamak

2009-01-01

Software was developed to characterize the drag in each of the Cassini spacecraft's Reaction Wheel Assemblies (RWAs) to determine the RWA friction parameters. This tool measures the drag torque of RWAs for not only the high spin rates (greater than 250 RPM), but also the low spin rates (less than 250 RPM) where there is a lack of an elastohydrodynamic boundary layer in the bearings. RWA rate and drag torque profiles as functions of time are collected via telemetry once every 4 seconds and once every 8 seconds, respectively. Intermediate processing steps single-out the coast-down regions. A nonlinear model for the drag torque as a function of RWA spin rate is incorporated in order to characterize the low spin rate regime. The tool then uses a nonlinear parameter optimization algorithm based on the Nelder-Mead simplex method to determine the viscous coefficient, the Dahl friction, and the two parameters that account for the low spin-rate behavior.

Contaminant transport in aquifers: improving the determination of model parameters

International Nuclear Information System (INIS)

Sabino, C.V.S.; Moreira, R.M.; Lula, Z.L.; Chausson, Y.; Magalhaes, W.F.; Vianna, M.N.

1998-01-01

Parameters conditioning the migration behavior of cesium and mercury are measured with their tracers 137 Cs and 203 Hg in the laboratory, using both batch and column experiments. Batch tests were used to define the sorption isotherm characteristics. Also investigated were the influences of some test parameters, in particular those due to the volume of water to mass of soil ratio (V/m). A provisional relationship between V/m and the distribution coefficient, K d , has been advanced, and a procedure to estimate K d 's valid for environmental values of the ratio V/m has been suggested. Column tests provided the parameters for a transport model. A major problem to be dealt with in such tests is the collimation of the radioactivity probe. Besides mechanically optimizing the collimator, a deconvolution procedure has been suggested and tested, with statistical criteria, to filter off both noise and spurious tracer signals. Correction procedures for the integrating effect introduced by sampling at the exit of columns have also been developed. These techniques may be helpful in increasing the accuracy required in the measurement of parameters conditioning contaminant migration in soils, thus allowing more reliable predictions based on mathematical model applications. (author)

Ammonium removal from aqueous solutions by clinoptilolite: determination of isotherm and thermodynamic parameters and comparison of kinetics by the double exponential model and conventional kinetic models.

Science.gov (United States)

Tosun, Ismail

2012-03-01

The adsorption isotherm, the adsorption kinetics, and the thermodynamic parameters of ammonium removal from aqueous solution by using clinoptilolite in aqueous solution was investigated in this study. Experimental data obtained from batch equilibrium tests have been analyzed by four two-parameter (Freundlich, Langmuir, Tempkin and Dubinin-Radushkevich (D-R)) and four three-parameter (Redlich-Peterson (R-P), Sips, Toth and Khan) isotherm models. D-R and R-P isotherms were the models that best fitted to experimental data over the other two- and three-parameter models applied. The adsorption energy (E) from the D-R isotherm was found to be approximately 7 kJ/mol for the ammonium-clinoptilolite system, thereby indicating that ammonium is adsorbed on clinoptilolite by physisorption. Kinetic parameters were determined by analyzing the nth-order kinetic model, the modified second-order model and the double exponential model, and each model resulted in a coefficient of determination (R(2)) of above 0.989 with an average relative error lower than 5%. A Double Exponential Model (DEM) showed that the adsorption process develops in two stages as rapid and slow phase. Changes in standard free energy (∆G°), enthalpy (∆H°) and entropy (∆S°) of ammonium-clinoptilolite system were estimated by using the thermodynamic equilibrium coefficients.

Ammonium Removal from Aqueous Solutions by Clinoptilolite: Determination of Isotherm and Thermodynamic Parameters and Comparison of Kinetics by the Double Exponential Model and Conventional Kinetic Models

Directory of Open Access Journals (Sweden)

İsmail Tosun

2012-03-01

Full Text Available The adsorption isotherm, the adsorption kinetics, and the thermodynamic parameters of ammonium removal from aqueous solution by using clinoptilolite in aqueous solution was investigated in this study. Experimental data obtained from batch equilibrium tests have been analyzed by four two-parameter (Freundlich, Langmuir, Tempkin and Dubinin-Radushkevich (D-R and four three-parameter (Redlich-Peterson (R-P, Sips, Toth and Khan isotherm models. D-R and R-P isotherms were the models that best fitted to experimental data over the other two- and three-parameter models applied. The adsorption energy (E from the D-R isotherm was found to be approximately 7 kJ/mol for the ammonium-clinoptilolite system, thereby indicating that ammonium is adsorbed on clinoptilolite by physisorption. Kinetic parameters were determined by analyzing the nth-order kinetic model, the modified second-order model and the double exponential model, and each model resulted in a coefficient of determination (R2 of above 0.989 with an average relative error lower than 5%. A Double Exponential Model (DEM showed that the adsorption process develops in two stages as rapid and slow phase. Changes in standard free energy (∆G°, enthalpy (∆H° and entropy (∆S° of ammonium-clinoptilolite system were estimated by using the thermodynamic equilibrium coefficients.

Inverse modeling for the determination of hydrogeological parameters of a two-phase system

International Nuclear Information System (INIS)

Finsterle, S.

1993-02-01

Investigations related to the disposal of radioactive wastes in Switzerland consider formations containing natural gas as potential rocks for a repository. Moreover, gas generation in the repository itself may lead to an unsaturated zone of significant extent and impact on the system's performance. The site characterization procedure requires the estimation of hydraulic properties being used as input parameters for a two-phase two-component numerical simulator. In this study, estimates of gas-related formation parameters are obtained by inverse modeling. Based on discrete observations of the system's state, model parameters can be estimated within the framework of a given conceptual model by means of optimization techniques. This study presents the theoretical background that related field data to the model parameters. A parameter estimation procedure is proposed and implemented in a computer code for automatic model calibration. This tool allows identification of key parameters affecting flow of water and gas in porous media. The inverse modeling approach is verified using data from a synthetic laboratory experiment. In addition, the Gas test performed at the Grimsel Test Site is analyzed in order to demonstrate the applicability of the proposed procedure when used with data from a real geologic environment. Estimation of hydrogeologic parameters by automatic model calibration improves the understanding of the two-phase flow processes and therefore increases the reliability of the subsequent simulation runs. (author) figs., tabs., refs

Inverse modeling for the determination of hydrogeological parameters of a two-phase system

International Nuclear Information System (INIS)

Finsterle, S.

1993-01-01

Investigations related to the disposal of radioactive wastes in Switzerland are dealing with formations containing natural gas as potential host rock for a repository. Moreover, gas generation in the repository itself may lead to an unsaturated zone of significant extent and impact on the system's performance. The site characterization procedure requires the estimation of hydraulic properties being used as input parameters for a two-phase two-component numerical simulator. In this study, estimates of gas related formation parameters are obtained by inverse modeling. Based on discrete observations of the system's state, model parameters can be estimated within the framework of a given conceptual model by means of optimization techniques. This study presents the theoretical background that relates field data to the model parameters. A parameter estimation procedure is proposed and implemented in a computer code for automatic model calibration. This tool allows to identify key parameters affecting flow of water and gas in porous media. The inverse modeling approach is verified using data from a synthetic laboratory experiment. In addition, the Gastest performed at the Grimsel Test Site is analyzed in order to demonstrate the applicability of the proposed procedure when used with data from a real geologic environment. Estimation of hydrogeologic parameters by automatic model calibration improves the understanding of the two-phase flow processes and therefore increases the reliability of the subsequent simulation runs. (author) figs., tabs., 100 refs

Impact parameter determination in experimental analysis using neural network

International Nuclear Information System (INIS)

Haddad, F.; David, C.; Freslier, M.; Aichelin, J.; Haddad, F.; Hagel, K.; Li, J.; Mdeiwayeh, N.; Natowitz, J.B.; Wada, R.; Xiao, B.

1997-01-01

A neural network is used to determine the impact parameter in 40 Ca + 40 Ca reactions. The effect of the detection efficiency as well as the model dependence of the training procedure have been studied carefully. An overall improvement of the impact parameter determination of 25 % is obtained using this technique. The analysis of Amphora 40 Ca+ 40 Ca data at 35 MeV per nucleon using a neural network shows two well separated classes of events among the selected 'complete' events. (authors)

A method for model identification and parameter estimation

International Nuclear Information System (INIS)

Bambach, M; Heinkenschloss, M; Herty, M

2013-01-01

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

Cosmological-model-parameter determination from satellite-acquired type Ia and IIP Supernova Data

International Nuclear Information System (INIS)

Podariu, Silviu; Nugent, Peter; Ratra, Bharat

2000-01-01

We examine the constraints that satellite-acquired Type Ia and IIP supernova apparent magnitude versus redshift data will place on cosmological model parameters in models with and without a constant or time-variable cosmological constant lambda. High-quality data which could be acquired in the near future will result in tight constraints on these parameters. For example, if all other parameters of a spatially-flat model with a constant lambda are known, the supernova data should constrain the non-relativistic matter density parameter omega to better than 1 (2, 0.5) at 1 sigma with neutral (worst case, best case) assumptions about data quality

Determining the Walker exponent and developing a modified Smith-Watson-Topper parameter model

Energy Technology Data Exchange (ETDEWEB)

Lv, Zhiqiang; Huang, Hong Zhong; Wang, Hai Kun; Gao, Huiying; Zuo, Fang Jun [University of Electronic Science and Technology of China, Chengdu (China)

2016-03-15

Mean stress effects significantly influence the fatigue life of components. In general, tensile mean stresses are known to reduce the fatigue life of components, whereas compressive mean stresses are known to increase it. To date, various methods that account for mean stress effects have been studied. In this research, considering the high accuracy of mean stress correction and the difficulty in obtaining the material parameter of the Walker method, a practical method is proposed to describe the material parameter of this method. The test data of various materials are then used to verify the proposed practical method. Furthermore, by applying the Walker material parameter and the Smith-Watson-Topper (SWT) parameter, a modified strain-life model is developed to consider sensitivity to mean stress of materials. In addition, three sets of experimental fatigue data from super alloy GH4133, aluminum alloy 7075-T651, and carbon steel are used to estimate the accuracy of the proposed model. A comparison is also made between the SWT parameter method and the proposed strainlife model. The proposed strain-life model provides more accurate life prediction results than the SWT parameter method.

Parameter determination in a groundwater field polluted by radioactive pollutant

International Nuclear Information System (INIS)

Sidauruk, P.; Barokah A; Syafalni; Wibagiyo

1998-01-01

The determination of source location and the corresponding parameters in a contaminated groundwater is very important. To be able to predict the distribution of radioactive contaminant in a contaminated field, the knowledge about the source location and the corresponding parameters is a necessity. The model developed in this paper is based on the fact that the relation between the logarithm of the concentration of the radio active contaminant with the squared coordinate is linear. The contaminant transport parameters as well as the a straight line. In other words, the parameters and the source location are determined in a such way that the linear correlation coefficient between the logarithm of the concentration of the radio active contaminant with the squared coordinate is optimized. The developed model is tested with a synthetic data with a satisfactory results. The synthetic data is generated such that can represent the real field. The synthetic data are generated because the real field data is not available. (authors)

DETERMINATION ALGORITHM OF OPTIMAL GEOMETRICAL PARAMETERS FOR COMPONENTS OF FREIGHT CARS ON THE BASIS OF GENERALIZED MATHEMATICAL MODELS

Directory of Open Access Journals (Sweden)

O. V. Fomin

2013-10-01

Full Text Available Purpose. Presentation of features and example of the use of the offered determination algorithm of optimum geometrical parameters for the components of freight cars on the basis of the generalized mathematical models, which is realized using computer. Methodology. The developed approach to search for optimal geometrical parameters can be described as the determination of optimal decision of the selected set of possible variants. Findings. The presented application example of the offered algorithm proved its operation capacity and efficiency of use. Originality. The determination procedure of optimal geometrical parameters for freight car components on the basis of the generalized mathematical models was formalized in the paper. Practical value. Practical introduction of the research results for universal open cars allows one to reduce container of their design and accordingly to increase the carrying capacity almost by100 kg with the improvement of strength characteristics. Taking into account the mass of their park this will provide a considerable economic effect when producing and operating. The offered approach is oriented to the distribution of the software packages (for example Microsoft Excel, which are used by technical services of the most enterprises, and does not require additional capital investments (acquisitions of the specialized programs and proper technical staff training. This proves the correctness of the research direction. The offered algorithm can be used for the solution of other optimization tasks on the basis of the generalized mathematical models.

Lumped-parameter models

Energy Technology Data Exchange (ETDEWEB)

Ibsen, Lars Bo; Liingaard, M.

2006-12-15

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

Spectroscopic properties of a two-dimensional time-dependent Cepheid model. II. Determination of stellar parameters and abundances

Science.gov (United States)

Vasilyev, V.; Ludwig, H.-G.; Freytag, B.; Lemasle, B.; Marconi, M.

2018-03-01

Context. Standard spectroscopic analyses of variable stars are based on hydrostatic 1D model atmospheres. This quasi-static approach has not been theoretically validated. Aim. We aim at investigating the validity of the quasi-static approximation for Cepheid variables. We focus on the spectroscopic determination of the effective temperature Teff, surface gravity log g, microturbulent velocity ξt, and a generic metal abundance log A, here taken as iron. Methods: We calculated a grid of 1D hydrostatic plane-parallel models covering the ranges in effective temperature and gravity that are encountered during the evolution of a 2D time-dependent envelope model of a Cepheid computed with the radiation-hydrodynamics code CO5BOLD. We performed 1D spectral syntheses for artificial iron lines in local thermodynamic equilibrium by varying the microturbulent velocity and abundance. We fit the resulting equivalent widths to corresponding values obtained from our dynamical model for 150 instances in time, covering six pulsational cycles. In addition, we considered 99 instances during the initial non-pulsating stage of the temporal evolution of the 2D model. In the most general case, we treated Teff, log g, ξt, and log A as free parameters, and in two more limited cases, we fixed Teff and log g by independent constraints. We argue analytically that our approach of fitting equivalent widths is closely related to current standard procedures focusing on line-by-line abundances. Results: For the four-parametric case, the stellar parameters are typically underestimated and exhibit a bias in the iron abundance of ≈-0.2 dex. To avoid biases of this type, it is favorable to restrict the spectroscopic analysis to photometric phases ϕph ≈ 0.3…0.65 using additional information to fix the effective temperature and surface gravity. Conclusions: Hydrostatic 1D model atmospheres can provide unbiased estimates of stellar parameters and abundances of Cepheid variables for particular

Determination of electrodebiles parameters of quark b

International Nuclear Information System (INIS)

Chamizo Llatas, M.

1995-01-01

In the present work we analyze the process e e→ bb with the data collected during 1991 and 1992 by the Z,3 detector situated in the LEP e es torage-ring (CERN). From the measurements of the cross-sections and the charge asymmetry we determine the parameters of the b quark in the framework of the Standard Model. Finally, we parametrize the possible deviations from the model an obtain upper and lower. limits for the mass of the t quark. (Author) 23 refs

Standard model parameters determination and validity tests in Z{sup 0} hadronic disintegrations; Determination des parametres du modele standard et tests de sa validite dans les desintegrations hadroniques du Z{sup 0}

Energy Technology Data Exchange (ETDEWEB)

Todorov, T

1993-05-01

This thesis describes the determination of the electroweak parameters from the measurements of the total hadronic cross-section by the DELPHI experiment at LEP-I. The analysed data was taken in the years 1991 and 1992; a previous analysis of the data taken in 1990 is included in the final fits. The first part of the thesis describes the interest of the measurement of the Z{sup 0} resonance parameters in the framework of the Standard Model as well as their implications for alternative models. The Standard Model predictions are described in some detail, and their precision is estimated. Then follows a brief description of the LEP collider, of the measurement of the collision energy, and of the experimental setup. A chapter is devoted to the description of the luminosity measurement, essential for the determination of total cross-sections. The measurement of the hadronic cross-section (event selection, study of backgrounds, study of sources of systematic uncertainties) is described in detail in the next chapter. Then follows a description of the method of the extraction of the resonance parameters, and a discussion of the uncertainties in their determination. The values obtained are interpreted in the framework of the Standard Model, as well as in the framework of some more general theories. Finally, the event generator for hadron production in two-photon collisions is described in the appendix. (author). 69 refs., 51 figs., 9 tabs., 1 ann.

A proposal of parameter determination method in the residual strength degradation model for the prediction of fatigue life (I)

International Nuclear Information System (INIS)

Kim, Sang Tae; Jang, Seong Soo

2001-01-01

The static and fatigue tests have been carried out to verify the validity of a generalized residual strength degradation model. And a new method of parameter determination in the model is verified experimentally to account for the effect of tension-compression fatigue loading of spheroidal graphite cast iron. It is shown that the correlation between the experimental results and the theoretical prediction on the statistical distribution of fatigue life by using the proposed method is very reasonable. Furthermore, it is found that the correlation between the theoretical prediction and the experimental results of fatigue life in case of tension-tension fatigue data in composite material appears to be reasonable. Therefore, the proposed method is more adjustable in the determination of the parameter than maximum likelihood method and minimization technique

Automated parameter estimation for biological models using Bayesian statistical model checking.

Science.gov (United States)

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

2015-01-01

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

Determination of N metabolism parameters following 15N-amino acid infusion based on a mathematical model

International Nuclear Information System (INIS)

Pahle, T.; Koehler, R.; Souffrant, W.B.; Gebhardt, G.; Matkowitz, R.; Hartig, W.

1983-01-01

Two female pigs (25 kg live weight) received a continuous infusion of 15 N-glycine and 15 N-lysine solutions, resp., for 45 h and for further 72 h unlabelled amino acid solutions. The main protein and energy sources, however, were administered orally. The time course of the 15 N level and the differential urinary N excretion were determined from blood urea and urine. For the demonstration of synthesis and decay rates of the total body protein a mathematical model has been developed. The suitability of 15 N-lysine and 15 N-glycine for the determination of N metabolism parameters is discussed

Parameters and error of a theoretical model

International Nuclear Information System (INIS)

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

1986-09-01

We propose a definition for the error of a theoretical model of the type whose parameters are determined from adjustment to experimental data. By applying a standard statistical method, the maximum-likelihoodlmethod, we derive expressions for both the parameters of the theoretical model and its error. We investigate the derived equations by solving them for simulated experimental and theoretical quantities generated by use of random number generators. 2 refs., 4 tabs

Uncertainty in the determination of soil hydraulic parameters and its influence on the performance of two hydrological models of different complexity

Directory of Open Access Journals (Sweden)

G. Baroni

2010-02-01

Full Text Available Data of soil hydraulic properties forms often a limiting factor in unsaturated zone modelling, especially at the larger scales. Investigations for the hydraulic characterization of soils are time-consuming and costly, and the accuracy of the results obtained by the different methodologies is still debated. However, we may wonder how the uncertainty in soil hydraulic parameters relates to the uncertainty of the selected modelling approach. We performed an intensive monitoring study during the cropping season of a 10 ha maize field in Northern Italy. The data were used to: i compare different methods for determining soil hydraulic parameters and ii evaluate the effect of the uncertainty in these parameters on different variables (i.e. evapotranspiration, average water content in the root zone, flux at the bottom boundary of the root zone simulated by two hydrological models of different complexity: SWAP, a widely used model of soil moisture dynamics in unsaturated soils based on Richards equation, and ALHyMUS, a conceptual model of the same dynamics based on a reservoir cascade scheme. We employed five direct and indirect methods to determine soil hydraulic parameters for each horizon of the experimental profile. Two methods were based on a parameter optimization of: a laboratory measured retention and hydraulic conductivity data and b field measured retention and hydraulic conductivity data. The remaining three methods were based on the application of widely used Pedo-Transfer Functions: c Rawls and Brakensiek, d HYPRES, and e ROSETTA. Simulations were performed using meteorological, irrigation and crop data measured at the experimental site during the period June – October 2006. Results showed a wide range of soil hydraulic parameter values generated with the different methods, especially for the saturated hydraulic conductivity K_sat and the shape parameter α of the van Genuchten curve. This is reflected in a variability of

Determination of electroweak parameters of the b quark

International Nuclear Information System (INIS)

Chamizo Llatas, M.

1995-01-01

In the present work we analyze the process e+e→ bb with the data collected during 1991 and 1992 by the L 3 detector situated in the LEP e+e-storage-ring (CERN). From the measurements of the crossections and the charge asymmetry we determine the parameters of the b quark in the framework of the Standar Model. Finally, we parametrize the possible deviations from the model an obtain upper and lower limits for the mass of the t quark

Determination of the numerical parameters of a continuous damage model for the structural analysis of clay brick masonry

Directory of Open Access Journals (Sweden)

Felipe Barbosa Mangueira

2012-12-01

Full Text Available Models based on the continuous damage theory present good responses in representing the nonlinear behavior of reinforced concrete structures with loss of strength and stiffness of the material. However, damage theory is rarely employed in the analysis of masonry structures and numerical simulations are currently performed mostly by Finite Element Method formulations. A computational program was designed to determine the numerical parameters of a damage model of the physical properties of masonry components, solid clay brick and mortar. The model was formulated based on the composition of tensile and compressive surface strengths in the plane stress state. The numerical parameters, the corresponding curves of the activation surfaces and the evolution of the surfaces are presented. The results were fed into the computational program based on the Boundary Element Method (BEM for the simulation of masonry walls, and two types of masonry were simulated. The results confirm the good performance of the model and the program based on the BEM.

Two and Three Parameter Waveform Retracking of Cryosat-2 LRM Waveforms for Gravity Field Determination

DEFF Research Database (Denmark)

Jain, Maulik; Andersen, Ole Baltazar; Dall, Jørgen

2013-01-01

The project deals with sea surface height and gravity field determination in open ocean using Cryosat-2 LRM data. A three parameter model is being used to find the retracking offset for sea surface height determination. The estimates from the three parameter model are further improved upon by using...... a two parameter model. The sea surface heights thus obtained are used to develop sea surface height anomalies which are further processed to give gravity fields. Retracker performance evaluation is done using sea surface height anomaly and gravity field anomaly....

Determining the optimum process parameter for grinding operations using robust process

International Nuclear Information System (INIS)

Neseli, Suley Man; Asilturk, Ilhan; Celik, Levent

2012-01-01

We applied combined response surface methodology (RSM) and Taguchi methodology (TM) to determine optimum parameters for minimum surface roughness (Ra) and vibration (Vb) in external cylindrical grinding. First, an experiment was conducted in a CNC cylindrical grinding machine. The TM using L 27 orthogonal array was applied to the design of the experiment. The three input parameters were workpiece revolution, feed rate and depth of cut; the outputs were vibrations and surface roughness. Second, to minimize wheel vibration and surface roughness, two optimized models were developed using computer aided single objective optimization. The experimental and statistical results revealed that the most significant grinding parameter for surface roughness and vibration is workpiece revolution followed by the depth of cut. The predicted values and measured values were fairly close, which indicates 2 ( 94.99 R 2Ra =and 2 92.73) R 2Vb =that the developed models can be effectively used to predict surface roughness and vibration in the grinding. The established model for determination of optimal operating conditions shows that a hybrid approach can lead to success of a robust process

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.

Incorporating model parameter uncertainty into inverse treatment planning

International Nuclear Information System (INIS)

Lian Jun; Xing Lei

2004-01-01

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

Systematic parameter inference in stochastic mesoscopic modeling

Energy Technology Data Exchange (ETDEWEB)

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

2017-02-01

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

Determining "small parameters" for quasi-steady state

Science.gov (United States)

Goeke, Alexandra; Walcher, Sebastian; Zerz, Eva

2015-08-01

For a parameter-dependent system of ordinary differential equations we present a systematic approach to the determination of parameter values near which singular perturbation scenarios (in the sense of Tikhonov and Fenichel) arise. We call these special values Tikhonov-Fenichel parameter values. The principal application we intend is to equations that describe chemical reactions, in the context of quasi-steady state (or partial equilibrium) settings. Such equations have rational (or even polynomial) right-hand side. We determine the structure of the set of Tikhonov-Fenichel parameter values as a semi-algebraic set, and present an algorithmic approach to their explicit determination, using Groebner bases. Examples and applications (which include the irreversible and reversible Michaelis-Menten systems) illustrate that the approach is rather easy to implement.

Heart rate variability as determinism with jump stochastic parameters.

Science.gov (United States)

Zheng, Jiongxuan; Skufca, Joseph D; Bollt, Erik M

2013-08-01

We use measured heart rate information (RR intervals) to develop a one-dimensional nonlinear map that describes short term deterministic behavior in the data. Our study suggests that there is a stochastic parameter with persistence which causes the heart rate and rhythm system to wander about a bifurcation point. We propose a modified circle map with a jump process noise term as a model which can qualitatively capture such this behavior of low dimensional transient determinism with occasional (stochastically defined) jumps from one deterministic system to another within a one parameter family of deterministic systems.

Modeling of adsorption isotherms of phenol and chlorophenols onto granular activated carbon. Part I. Two-parameter models and equations allowing determination of thermodynamic parameters.

Science.gov (United States)

Hamdaoui, Oualid; Naffrechoux, Emmanuel

2007-08-17

The adsorption equilibrium isotherms of five phenolic compounds from aqueous solutions onto granular activated carbon (GAC) were studied and modeled. Phenol (Ph), 2-chlorophenol (2-CP), 4-chlorophenol (4-CP), 2,4-dichlorophenol (DCP), and 2,4,6-trichlorophenol (TCP) were chosen for the adsorption tests. To predict the adsorption isotherms and to determine the characteristic parameters for process design, seven isotherm models: Langmuir (five linear forms), Freundlich, Elovich, Temkin, Fowler-Guggenheim, Kiselev, and Hill-de Boer models were applied to experimental data. The results reveal that the adsorption isotherm models fitted the data in the order: Fowler-Guggenheim>Hill-de Boer>Temkin>Freundlich>Kiselev>Langmuir isotherms. Adsorption isotherms modeling shows that the interaction of phenolic compounds with activated carbon surface is localized monolayer adsorption, that is adsorbed molecules are adsorbed at definite, localized sites. Each site can accommodate only one molecule. The interaction among adsorbed molecules is repulsive and there is no association between them, adsorption is carried out on energetically different sites and is an exothermic process. Uptake of phenols increases in the order Ph<2-CP<4-CP

Determination of microstructural parameters in damage models for ductile metals; Bestimmung von mikrostrukturellen Parametern in Schaedigungsmodellen fuer duktile Metalle

Energy Technology Data Exchange (ETDEWEB)

Steglich, D. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Werkstofforschung

1999-07-01

For the determination of material parameters in micromechanical damage models the mechanical behaviour of representative volume elements of a two-phase material has been investigated and the phase morphology quantified by microstructural analysis. The material parameters have been successfully correlated to microstructural quantities and a prediction of the damage behaviour of structures is performed. Special emphasis is given to the model of Gurson, Tvergaard and Needleman, which has been used to predict the macroscopic behaviour of smooth tensile test specimens and the fracture resistance curves of bending specimens for two different materials, a nodular cast iron and a particle reinforced aluminium compound. (orig.) [German] Zur Bestimmung der Materialparameter in mikromechanischen Schaedigungsmodellen werden repraesentative Strukturelemente eines Werkstoffes untersucht und die Morphologie eines zweiphasigen Gefueges durch quantitative Gefuegeanalyse beschrieben. Mit dieser Strategie gelingen eine Identifikation der im Modell enthaltenen Parameter sowie die Vorhersage des Versagensverhaltens von Strukturen. Als mikromechanisches Materialmodell wird hauptsaechlich das Modell von Gurson, Tvergaard und Needleman verwendet. Seine Anwendbarkeit zur Vorhersage des globalen Verhaltens von glatten Zugproben und zur Simulation von Risswiderstandskurven wird bei zwei verschiedenen Werkstoffen gezeigt, einen Gusseisen und einem Aluminium-Verbundwerkstoff. (orig.)

Four-parameter model for polarization-resolved rough-surface BRDF.

Science.gov (United States)

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

2011-01-17

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

Determination of CME 3D parameters based on a new full ice-cream cone model

Science.gov (United States)

Na, Hyeonock; Moon, Yong-Jae

2017-08-01

In space weather forecast, it is important to determine three-dimensional properties of CMEs. Using 29 limb CMEs, we examine which cone type is close to a CME three-dimensional structure. We find that most CMEs have near full ice-cream cone structure which is a symmetrical circular cone combined with a hemisphere. We develop a full ice-cream cone model based on a new methodology that the full ice-cream cone consists of many flat cones with different heights and angular widths. By applying this model to 12 SOHO/LASCO halo CMEs, we find that 3D parameters from our method are similar to those from other stereoscopic methods (i.e., a triangulation method and a Graduated Cylindrical Shell model). In addition, we derive CME mean density (ρmean=Mtotal/Vcone) based on the full ice-cream cone structure. For several limb events, we determine CME mass by applying the Solarsoft procedure (e.g., cme_mass.pro) to SOHO/LASCO C3 images. CME volumes are estimated from the full ice-cream cone structure. From the power-law relationship between CME mean density and its height, we estimate CME mean densities at 20 solar radii (Rs). We will compare the CME densities at 20 Rs with their corresponding ICME densities.

Han's model parameters for microalgae grown under intermittent illumination: Determined using particle swarm optimization.

Science.gov (United States)

Pozzobon, Victor; Perre, Patrick

2018-01-21

This work provides a model and the associated set of parameters allowing for microalgae population growth computation under intermittent lightning. Han's model is coupled with a simple microalgae growth model to yield a relationship between illumination and population growth. The model parameters were obtained by fitting a dataset available in literature using Particle Swarm Optimization method. In their work, authors grew microalgae in excess of nutrients under flashing conditions. Light/dark cycles used for these experimentations are quite close to those found in photobioreactor, i.e. ranging from several seconds to one minute. In this work, in addition to producing the set of parameters, Particle Swarm Optimization robustness was assessed. To do so, two different swarm initialization techniques were used, i.e. uniform and random distribution throughout the search-space. Both yielded the same results. In addition, swarm distribution analysis reveals that the swarm converges to a unique minimum. Thus, the produced set of parameters can be trustfully used to link light intensity to population growth rate. Furthermore, the set is capable to describe photodamages effects on population growth. Hence, accounting for light overexposure effect on algal growth. Copyright © 2017 Elsevier Ltd. All rights reserved.

The mobilisation model and parameter sensitivity

International Nuclear Information System (INIS)

Blok, B.M.

1993-12-01

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

Determining the optimum process parameter for grinding operations using robust process

Energy Technology Data Exchange (ETDEWEB)

Neseli, Suley Man; Asilturk, Ilhan; Celik, Levent [Univ. of Selcuk, Konya (Turkmenistan)

2012-11-15

We applied combined response surface methodology (RSM) and Taguchi methodology (TM) to determine optimum parameters for minimum surface roughness (Ra) and vibration (Vb) in external cylindrical grinding. First, an experiment was conducted in a CNC cylindrical grinding machine. The TM using L{sup 27} orthogonal array was applied to the design of the experiment. The three input parameters were workpiece revolution, feed rate and depth of cut; the outputs were vibrations and surface roughness. Second, to minimize wheel vibration and surface roughness, two optimized models were developed using computer aided single objective optimization. The experimental and statistical results revealed that the most significant grinding parameter for surface roughness and vibration is workpiece revolution followed by the depth of cut. The predicted values and measured values were fairly close, which indicates 2 ( 94.99 R{sup 2Ra}=and 2 92.73) R{sup 2Vb}=that the developed models can be effectively used to predict surface roughness and vibration in the grinding. The established model for determination of optimal operating conditions shows that a hybrid approach can lead to success of a robust process.

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.

Determination of N metabolism parameters following /sup 15/N-amino acid infusion based on a mathematical model

Energy Technology Data Exchange (ETDEWEB)

Pahle, T; Koehler, R; Souffrant, W B; Gebhardt, G [Karl-Marx-Universitaet, Leipzig (German Democratic Republic). Sektion Tierproduktion und Veterinaermedizin; Matkowitz, R; Hartig, W [Bezirkskrankenhaus Leipzig (German Democratic Republic). Chirurgische Klinik

1983-01-01

Two female pigs (25 kg live weight) received a continuous infusion of /sup 15/N-glycine and /sup 15/N-lysine solutions, resp., for 45 h and for further 72 h unlabelled amino acid solutions. The main protein and energy sources, however, were administered orally. The time course of the /sup 15/N level and the differential urinary N excretion were determined from blood urea and urine. For the demonstration of synthesis and decay rates of the total body protein a mathematical model has been developed. The suitability of /sup 15/N-lysine and /sup 15/N-glycine for the determination of N metabolism parameters is discussed.

Verification Techniques for Parameter Selection and Bayesian Model Calibration Presented for an HIV Model

Science.gov (United States)

Wentworth, Mami Tonoe

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

Lumped-parameters equivalent circuit for condenser microphones modeling.

Science.gov (United States)

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

2017-10-01

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

Determination of resist parameters using the extended Nijboer-Zernike theory

NARCIS (Netherlands)

Dirksen, P.; Braat, J.; Janssen, A.J.E.M.; Leeuwestein, A.; Kwinten, H.; Van Steenwinckel, D.

2004-01-01

This study presents an experimental method to determine the resist parameters that are at the origin of a general blurring of the projected aerial image. The resist model includes the effects of diffusion in the horizontal plane and a second cause for image blur that originates from a stochastic

Determination of resonance parameters in QCD by functional analysis methods

International Nuclear Information System (INIS)

Ciulli, S.; Geniet, F.; Papadopoulos, N.A.; Schilcher, K.

1988-01-01

A mathematically rigorous method based on functional analysis is used to determine resonance parameters of an amplitude from its given asymptotic expression in the space-like region. This method is checked on a model amplitude where both the asymptotic expression and the exact function are known. This method is then applied to the determination of the mass and the width of the ρ-meson from the corresponding space-like asymptotic QCD expression. (orig.)

Construction of an experimental simplified model for determining of flow parameters in chemical reactors, using nuclear techniques

International Nuclear Information System (INIS)

Araujo Paiva, J.A. de.

1981-03-01

The development of a simplified experimental model for investigation of nuclear techniques to determine the solid phase parameters in gas-solid flows is presented. A method for the measurement of the solid phase residence time inside a chemical reactor of the type utilised in the cracking process of catalytic fluids is described. An appropriate radioactive labelling technique of the solid phase and the construction of an eletronic timing circuit were the principal stages in the definition of measurement technique. (Author) [pt

Implementation of the Global Parameters Determination in Gaia's Astrometric Solution (AGIS)

Science.gov (United States)

Raison, F.; Olias, A.; Hobbs, D.; Lindegren, L.

2010-12-01

Gaia is ESA’s space astrometry mission with a foreseen launch date in early 2012. Its main objective is to perform a stellar census of the 1000 Million brightest objects in our galaxy (completeness to V=20 mag) from which an astrometric catalog of micro-arcsec level accuracy will be constructed. A key element in this endeavor is the Astrometric Global Iterative Solution (AGIS). A core part of AGIS is to determine the accurate spacecraft attitude, geometric instrument calibration and astrometric model parameters for a well-behaved subset of all the objects (the ‘primary stars’). In addition, a small number of global parameters will be estimated, one of these being PPN γ. We present here the implementation of the algorithms dedicated to the determination of the global parameters.

Normal Values for Heart Electrophysiology Parameters of Healthy Swine Determined on Electrophysiology Study.

Science.gov (United States)

Noszczyk-Nowak, Agnieszka; Cepiel, Alicja; Janiszewski, Adrian; Pasławski, Robert; Gajek, Jacek; Pasławska, Urszula; Nicpoń, Józef

2016-01-01

Swine are a well-recognized animal model for human cardiovascular diseases. Despite the widespread use of porcine model in experimental electrophysiology, still no reference values for intracardiac electrical activity and conduction parameters determined during an invasive electrophysiology study (EPS) have been developed in this species thus far. The aim of the study was to develop a set of normal values for intracardiac electrical activity and conduction parameters determined during an invasive EPS of swine. The study included 36 healthy domestic swine (24-40 kg body weight). EPS was performed under a general anesthesia with midazolam, propofol and isoflurane. The reference values for intracardiac electrical activity and conduction parameters were calculated as arithmetic means ± 2 standard deviations. The reference values were determined for AH, HV and PA intervals, interatrial conduction time at its own and imposed rhythm, sinus node recovery time (SNRT), corrected sinus node recovery time (CSNRT), anterograde and retrograde Wenckebach points, atrial, atrioventricular node and ventricular refractory periods. No significant correlations were found between body weight and heart rate of the examined pigs and their electrophysiological parameters. The hereby presented reference values can be helpful in comparing the results of various studies, as well as in more accurately estimating the values of electrophysiological parameters that can be expected in a given experiment.

The application of virtual prototyping methods to determine the dynamic parameters of mobile robot

Science.gov (United States)

Kurc, Krzysztof; Szybicki, Dariusz; Burghardt, Andrzej; Muszyńska, Magdalena

2016-04-01

The paper presents methods used to determine the parameters necessary to build a mathematical model of an underwater robot with a crawler drive. The parameters present in the dynamics equation will be determined by means of advanced mechatronic design tools, including: CAD/CAE software andMES modules. The virtual prototyping process is described as well as the various possible uses (design adaptability) depending on the optional accessories added to the vehicle. A mathematical model is presented to show the kinematics and dynamics of the underwater crawler robot, essential for the design stage.

Determination of beam characteristic parameters for a linear accelerator

International Nuclear Information System (INIS)

Lima, D.A. de.

1978-01-01

A mechanism to determine electron beam characteristic parameters of a linear accelerator was constructed. The mechanism consists in an electro-calorimeter and an accurate optical densitometer. The following parameters: mean power, mean current, mean energy/particle, pulse Width, pulse amplitude dispersion, and pulse frequency, operating the 2 MeV linear accelerator of CBPF (Brazilian Center pf Physics Researches). The optical isodensity curves of irradiated glass lamellae were obtained, providing information about focus degradation penetration direction in material and the reach of particle. The point to point dose distribution in the material from optical density curves were obtained, using a semi empirical and approached model. (M.C.K.) [pt

Determining global parameters of the oscillations of solar-like stars

DEFF Research Database (Denmark)

Mathur, S.; García, R. A.; Régulo, C.

2010-01-01

Context. Helioseismology has enabled us to better understand the solar interior, while also allowing us to better constrain solar models. But now is a tremendous epoch for asteroseismology as space missions dedicated to studying stellar oscillations have been launched within the last years (MOST....... Aims. The goal of this research work is to estimate the global parameters of any solar-like oscillating target in an automatic manner. We want to determine the global parameters of the acoustic modes (large separation, range of excited pressure modes, maximum amplitude, and its corresponding frequency...

Bi facial silicon solar cell study in modelling in frequency dynamic regime under multispectral illumination: Recombination parameters determination methods

International Nuclear Information System (INIS)

ZERBO Issa

2010-01-01

A bibliographic study on the techniques of characterization of silicon solar cell, diodes, massifs and silicon wafer are presented. The influence of the modulation frequency and recombination in volume and in surface phenomena of on the profiles of carriers' densities, photocurrent and photovoltage has been put in evidence. The study of surface recombination velocities permitted to show that the bi facial silicon solar cell of Back Surface Field type behaves like an ohmic contacts solar cell for modulation frequencies above 40 khz. pplicability in frequency dynamic regime in the frequency range [0 - 40 khz] of three techniques of steady state recombination parameters determination is shown. A technique of diffusion length determination, in the range of (200 Hz - 40 khz] is proposed. It rests on the measurement of the short circuit current phase that is compared with the theoretical curve of short circuit current phase. The intersection of the experimental short circuit current phase and the theoretical curve of short circuit current phase permits to get the minority carriers effective diffusion length. An equivalent electric model of a solar cell in frequency dynamic regime is proposed. A study in modelling of the bi facial solar cell shunt resistance and space charge zone capacity is led from a determination method of these parameters proposed in steady state. (Author [fr

Modeling and Simulation Monte Carlo by the MCNP code for determining neutron parameters of the nuclear reactor-subcritical assembly in CNSTN

International Nuclear Information System (INIS)

Romdhani, Ibtissem

2014-01-01

As part of developing its nuclear infrastructure base, the National Science and Technology Center Nuclear (CNSTN) examines the technical feasibility of setting up a new installation of subcritical assembly. Our study focuses on determining the neutron parameters of a nuclear zero power reactor based on Monte Carlo simulation MCNP. The objective of the simulation is to model the installation, determine the effective multiplication factor, and spatial distribution of neutron flux.

Comparison of adsorption equilibrium and kinetic models for a case study of pharmaceutical active ingredient adsorption from fermentation broths: parameter determination, simulation, sensitivity analysis and optimization

Directory of Open Access Journals (Sweden)

B. Likozar

2012-09-01

Full Text Available Mathematical models for a batch process were developed to predict concentration distributions for an active ingredient (vancomycin adsorption on a representative hydrophobic-molecule adsorbent, using differently diluted crude fermentation broth with cells as the feedstock. The kinetic parameters were estimated using the maximization of the coefficient of determination by a heuristic algorithm. The parameters were estimated for each fermentation broth concentration using four concentration distributions at initial vancomycin concentrations of 4.96, 1.17, 2.78, and 5.54 g l−¹. In sequence, the models and their parameters were validated for fermentation broth concentrations of 0, 20, 50, and 100% (v/v by calculating the coefficient of determination for each concentration distribution at the corresponding initial concentration. The applicability of the validated models for process optimization was investigated by using the models as process simulators to optimize the two process efficiencies.

Biological parameters for lung cancer in mathematical models of carcinogenesis

International Nuclear Information System (INIS)

Jacob, P.; Jacob, V.

2003-01-01

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

Model parameter learning using Kullback-Leibler divergence

Science.gov (United States)

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

2018-02-01

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

A distributed approach for parameters estimation in System Biology models

International Nuclear Information System (INIS)

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

2009-01-01

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

Key Variables Screening of Near-Infrared Models for Simultaneous Determination of Quality Parameters in Traditional Chinese Food “Fuzhu”

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Jiahua Wang

2018-01-01

Full Text Available The traditional Chinese food Fuzhu is a dried soy protein-lipid film formed during the heating of soymilk. This study investigates whether a simple and accurate model can nondestructively determine the quality parameters of intact Fuzhu. The diffused reflectance spectra (1000–2499 nm of intact Fuzhu were collected by a commercial near-infrared (NIR spectrometer. Among various preprocessing methods, the derivative by wavelet transform method optimally enhanced the characteristic signals of Fuzhu spectra. Uninformative variable elimination based on Monte Carlo (MC-UVE, random frog (RF, and competitive adaptive reweighted sampling (CARS were proposed to select key variables for partial least squares (PLS calculation. The strong performance of the developed models is attributed to the high ratios of prediction to deviation values (3.32–3.51 for protein, 3.62–3.89 for lipid, and 4.27–4.55 for moisture. The prediction set was used to assess the performances of the best models of protein (CARS-PLS, lipid (RF-PLS, and moisture (CARS-PLS, which resulted in greater coefficients of determination of 0.958, 0.966, and 0.976, respectively, and lower root mean square errors of prediction of 0.656%, 0.442%, and 0.123%, respectively. Combined with chemometrics methods, the NIR technique is promising for simultaneous testing of quality parameters of intact Fuzhu.

A software for parameter estimation in dynamic models

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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.

Determination of adsorption parameters in numerical simulation for polymer flooding

Science.gov (United States)

Bao, Pengyu; Li, Aifen; Luo, Shuai; Dang, Xu

2018-02-01

A study on the determination of adsorption parameters for polymer flooding simulation was carried out. The study mainly includes polymer static adsorption and dynamic adsorption. The law of adsorption amount changing with polymer concentration and core permeability was presented, and the one-dimensional numerical model of CMG was established under the support of a large number of experimental data. The adsorption laws of adsorption experiments were applied to the one-dimensional numerical model to compare the influence of two adsorption laws on the historical matching results. The results show that the static adsorption and dynamic adsorption abide by different rules, and differ greatly in adsorption. If the static adsorption results were directly applied to the numerical model, the difficulty of the historical matching will increase. Therefore, dynamic adsorption tests in the porous medium are necessary before the process of parameter adjustment in order to achieve the ideal history matching result.

Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model

Science.gov (United States)

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

2017-06-01

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

Determining cosmological parameters with the latest observational data

International Nuclear Information System (INIS)

Xia Junqing; Li Hong; Zhao Gongbo; Zhang Xinmin

2008-01-01

In this paper, we combine the latest observational data, including the WMAP five-year data (WMAP5), BOOMERanG, CBI, VSA, ACBAR, as well as the baryon acoustic oscillations (BAO) and type Ia supernovae (SN) ''union'' compilation (307 sample), and use the Markov Chain Monte Carlo method to determine the cosmological parameters, such as the equation of state (EoS) of dark energy, the curvature of the universe, the total neutrino mass, and the parameters associated with the power spectrum of primordial fluctuations. In a flat universe, we obtain the tight limit on the constant EoS of dark energy as w=-0.977±0.056(stat)±0.057(sys). For the dynamical dark energy models with the time evolving EoS parametrized as w de (a)=w 0 +w 1 (1-a), we find that the best-fit values are w 0 =-1.08 and w 1 =0.368, while the ΛCDM model remains a good fit to the current data. For the curvature of the universe Ω k , our results give -0.012 k de =-1. When considering the dynamics of dark energy, the flat universe is still a good fit to the current data, -0.015 k s ≥1 are excluded at more than 2σ confidence level. However, in the framework of dynamical dark energy models, the allowed region in the parameter space of (n s ,r) is enlarged significantly. Finally, we find no strong evidence for the large running of the spectral index.

Integral data analysis for resonance parameters determination

International Nuclear Information System (INIS)

Larson, N.M.; Leal, L.C.; Derrien, H.

1997-09-01

Neutron time-of-flight experiments have long been used to determine resonance parameters. Those resonance parameters have then been used in calculations of integral quantities such as Maxwellian averages or resonance integrals, and results of those calculations in turn have been used as a criterion for acceptability of the resonance analysis. However, the calculations were inadequate because covariances on the parameter values were not included in the calculations. In this report an effort to correct for that deficiency is documented: (1) the R-matrix analysis code SAMMY has been modified to include integral quantities of importance, (2) directly within the resonance parameter analysis, and (3) to determine the best fit to both differential (microscopic) and integral (macroscopic) data simultaneously. This modification was implemented because it is expected to have an impact on the intermediate-energy range that is important for criticality safety applications

Application of isotopic information for estimating parameters in Philip infiltration model

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Tao Wang

2016-10-01

Full Text Available Minimizing parameter uncertainty is crucial in the application of hydrologic models. Isotopic information in various hydrologic components of the water cycle can expand our knowledge of the dynamics of water flow in the system, provide additional information for parameter estimation, and improve parameter identifiability. This study combined the Philip infiltration model with an isotopic mixing model using an isotopic mass balance approach for estimating parameters in the Philip infiltration model. Two approaches to parameter estimation were compared: (a using isotopic information to determine the soil water transmission and then hydrologic information to estimate the soil sorptivity, and (b using hydrologic information to determine the soil water transmission and the soil sorptivity. Results of parameter estimation were verified through a rainfall infiltration experiment in a laboratory under rainfall with constant isotopic compositions and uniform initial soil water content conditions. Experimental results showed that approach (a, using isotopic and hydrologic information, estimated the soil water transmission in the Philip infiltration model in a manner that matched measured values well. The results of parameter estimation of approach (a were better than those of approach (b. It was also found that the analytical precision of hydrogen and oxygen stable isotopes had a significant effect on parameter estimation using isotopic information.

Mathematical determination of setup parameters for carcinoma breast cases

International Nuclear Information System (INIS)

Prasad, P.B.L.D.; Suresh, P.; Sridhar, A.

2008-01-01

Determining proper patient set up parameters like IFD, Gantry angles and field width in Ca Breast are prime important to achieve precise treatment. In a center where 3D Treatment Planning Systems (TPS) and simulator are not available to determine the set up parameters, contouring of target region is essential which is time consuming. The mathematical formula described here provides instant patient set up parameters using machine parameters. (author)

Determination of supersymmetric parameters with neural networks at the large hadron collider

International Nuclear Information System (INIS)

Bornhauser, Nicki

2013-12-01

The LHC is running and in the near future potentially some signs of new physics are measured. In this thesis it is assumed that the underlying theory of such a signal would be identified and that it is some kind of minimal supersymmetric extension of the Standard Model. Generally, the mapping from the measurable observables onto the parameter values of the supersymmetric theory is unknown. Instead, only the opposite direction is known, i.e. for fixed parameters the measurable observables can be computed with some uncertainties. In this thesis, the ability of artifical neural networks to determine this unknown function is demonstrated. At the end of a training process, the created networks are capable to calculate the parameter values with errors for an existing measurement. To do so, at first a set of mostly counting observables is introduced. In the following, the usefulness of these observables for the determination of supersymmetric parameters is checked. This is done by applying them on 283 pairs of parameter sets of a MSSM with 15 parameters. These pairs were found to be indistinguishable at the LHC by another study, even without the consideration of SM background. It can be shown that 260 of these pairs can be discriminated using the introduced observables. Without systematic errors even all pairs can be distinguished. Also with the consideration of SM background still most pairs can be disentangled (282 without and 237 with systematic errors). This result indicates the usefulness of the observables for the direct parameter determination. The performance of neural networks is investigated for four different parameter regions of the CMSSM. With the right set of observables, the neural network approach generally could also be used for any other (non-supersymmetric) theory. In each region, a reference point with around 1,000 events after cuts should be determined in the context of a LHC with a center of mass energy of 14 TeV and an integrated luminosity of 10 fb

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.

Condition Parameter Modeling for Anomaly Detection in Wind Turbines

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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 sensitivity and uncertainty of the forest carbon flux model FORUG : a Monte Carlo analysis

Energy Technology Data Exchange (ETDEWEB)

Verbeeck, H.; Samson, R.; Lemeur, R. [Ghent Univ., Ghent (Belgium). Laboratory of Plant Ecology; Verdonck, F. [Ghent Univ., Ghent (Belgium). Dept. of Applied Mathematics, Biometrics and Process Control

2006-06-15

The FORUG model is a multi-layer process-based model that simulates carbon dioxide (CO{sub 2}) and water exchange between forest stands and the atmosphere. The main model outputs are net ecosystem exchange (NEE), total ecosystem respiration (TER), gross primary production (GPP) and evapotranspiration. This study used a sensitivity analysis to identify the parameters contributing to NEE uncertainty in the FORUG model. The aim was to determine if it is necessary to estimate the uncertainty of all parameters of a model to determine overall output uncertainty. Data used in the study were the meteorological and flux data of beech trees in Hesse. The Monte Carlo method was used to rank sensitivity and uncertainty parameters in combination with a multiple linear regression. Simulations were run in which parameters were assigned probability distributions and the effect of variance in the parameters on the output distribution was assessed. The uncertainty of the output for NEE was estimated. Based on the arbitrary uncertainty of 10 key parameters, a standard deviation of 0.88 Mg C per year per NEE was found, which was equal to 24 per cent of the mean value of NEE. The sensitivity analysis showed that the overall output uncertainty of the FORUG model could be determined by accounting for only a few key parameters, which were identified as corresponding to critical parameters in the literature. It was concluded that the 10 most important parameters determined more than 90 per cent of the output uncertainty. High ranking parameters included soil respiration; photosynthesis; and crown architecture. It was concluded that the Monte Carlo technique is a useful tool for ranking the uncertainty of parameters of process-based forest flux models. 48 refs., 2 tabs., 2 figs.

On unique parameters and unified formal form of hot-wire anemometric sensor model

International Nuclear Information System (INIS)

LigePza, P.

2005-01-01

This note reviews the extensively adopted equations used as models of hot-wire anemometric sensors. An unified formal form of the mathematical model of a hot-wire anemometric sensor with otherwise defined parameters is proposed. Those parameters, static and dynamic, have simple physical interpretation and can be easily determined. They show directly the range of sensor application. They determine the metrological properties of the given sensor in the actual medium. Hence, the parameters' values might be ascribed to each sensor in the given medium and be quoted in manufacturers' catalogues, supplementing the sensor specifications. Because of their simple physical interpretation, those parameters allow the direct comparison of the fundamental metrological properties of various sensors and selection of the optimal sensor for the given research measurement application. The parameters are also useful in modeling complex hot-wire systems

Calibration of discrete element model parameters: soybeans

Science.gov (United States)

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

2018-05-01

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

Effect of caffeine intake on critical power model parameters determined on a cycle ergometer

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Marcus Vinicius Machado

2010-01-01

Full Text Available The aim of this study was to evaluate the effect of caffeine intake on critical power model parameters determined on a cycle ergometer. Eight male subjects participated in this study. A double-blind protocol consisting of the intake of pure caffeine (6 mg/kg or placebo (maltodextrin 60 min before testing was used. Subjects were submitted to four constant-load tests on a cycle ergometer. These tests were conducted randomly in the caffeine and placebo groups [checar] at intensities of 80, 90, 100 and 110% maximum power at a rate of 70 rpm until exhaustion to determine the critical power. As a criterion for stopping the test was adopted any rate fall without recovery by more than five seconds. The critical power and anaerobic work capacity were obtained by nonlinear regression and fitting of the curve to a hyperbolic power-time model. The Shapiro-Wilk test and paired Student t-test were used for statistical analysis. No significant differences in critical power were observed between the caffeine and placebo groups (192.9 ± 31.3 vs 197.7 ± 29.4 W, respectively. The anaerobic work capacity was significantly higher in the caffeine group (20.1 ± 5.2 vs 16.3 ± 4.2 W, p< 0.01. A high association (r2 was observed between the caffeine and placebo conditions (0.98 ± 0.02 and 0.99 ± 0.0, respectively. We conclude that caffeine intake did not improve critical power performance but increased anaerobic work capacity by influencing performance at loads of higher intensity and shorter duration.

Determination of Kinetic Parameters for the Thermal Decomposition of Parthenium hysterophorus

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Dhaundiyal Alok

2018-02-01

Full Text Available A kinetic study of pyrolysis process of Parthenium hysterophorous is carried out by using thermogravimetric analysis (TGA equipment. The present study investigates the thermal degradation and determination of the kinetic parameters such as activation E and the frequency factor A using model-free methods given by Flynn Wall and Ozawa (FWO, Kissinger-Akahira-Sonuse (KAS and Kissinger, and model-fitting (Coats Redfern. The results derived from thermal decomposition process demarcate decomposition of Parthenium hysterophorous among the three main stages, such as dehydration, active and passive pyrolysis. It is shown through DTG thermograms that the increase in the heating rate caused temperature peaks at maximum weight loss rate to shift towards higher temperature regime. The results are compared with Coats Redfern (Integral method and experimental results have shown that values of kinetic parameters obtained from model-free methods are in good agreement. Whereas the results obtained through Coats Redfern model at different heating rates are not promising, however, the diffusion models provided the good fitting with the experimental data.

Determination of cosmological parameters: An introduction for non ...

Indian Academy of Sciences (India)

Then I show how the age of the universe depends on them, followed by the evolution of the scale parameter of the universe for various values of the density parameters. Then I define strategies for measuring them, and show the results for the recent determination of these parameters from measurements on supernovas of ...

Error propagation of partial least squares for parameters optimization in NIR modeling

Science.gov (United States)

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

2018-03-01

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

Error propagation of partial least squares for parameters optimization in NIR modeling.

Science.gov (United States)

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

2018-03-05

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

Method for Determining the Time Parameter

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K. P. Baslyk

2014-01-01

Full Text Available This article proposes a method for calculating one of the characteristics that represents the flight program of the first stage of ballistic rocket i.e. time parameter of the program of attack angle.In simulation of placing the payload for the first stage, a program of flight is used which consists of three segments, namely a vertical climb of the rocket, a segment of programmed reversal by attack angle, and a segment of gravitational reversal with zero angle of attack.The programed reversal by attack angle is simulated as a rapidly decreasing and increasing function. This function depends on the attack angle amplitude, time and time parameter.If the projected and ballistic parameters and the amplitude of attack angle were determined this coefficient is calculated based the constraint that the rocket velocity is equal to 0.8 from the sound velocity (0,264 km/sec when the angle of attack becomes equal to zero. Such constraint is transformed to the nonlinear equation, which can be solved using a Newton method.The attack angle amplitude value is unknown for the design analysis. Exceeding some maximum admissible value for this parameter may lead to excessive trajectory collapsing (foreshortening, which can be identified as an arising negative trajectory angle.Consequently, therefore it is necessary to compute the maximum value of the attack angle amplitude with the following constraints: a trajectory angle is positive during the entire first stage flight and the rocket velocity is equal to 0,264 km/sec by the end of program of angle attack. The problem can be formulated as a task of the nonlinear programming, minimization of the modified Lagrange function, which is solved using the multipliers method.If multipliers and penalty parameter are constant the optimization problem without constraints takes place. Using the determined coordinate descent method allows solving the problem of modified Lagrange function of unconstrained minimization with fixed

Model parameter updating using Bayesian networks

International Nuclear Information System (INIS)

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

2004-01-01

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

Physical property parameter set for modeling ICPP aqueous wastes with ASPEN electrolyte NRTL model

International Nuclear Information System (INIS)

Schindler, R.E.

1996-09-01

The aqueous waste evaporators at the Idaho Chemical Processing Plant (ICPP) are being modeled using ASPEN software. The ASPEN software calculates chemical and vapor-liquid equilibria with activity coefficients calculated using the electrolyte Non-Random Two Liquid (NRTL) model for local excess Gibbs free energies of interactions between ions and molecules in solution. The use of the electrolyte NRTL model requires the determination of empirical parameters for the excess Gibbs free energies of the interactions between species in solution. This report covers the development of a set parameters, from literature data, for the use of the electrolyte NRTL model with the major solutes in the ICPP aqueous wastes

Analysis of sensitivity of simulated recharge to selected parameters for seven watersheds modeled using the precipitation-runoff modeling system

Science.gov (United States)

Ely, D. Matthew

2006-01-01

Recharge is a vital component of the ground-water budget and methods for estimating it range from extremely complex to relatively simple. The most commonly used techniques, however, are limited by the scale of application. One method that can be used to estimate ground-water recharge includes process-based models that compute distributed water budgets on a watershed scale. These models should be evaluated to determine which model parameters are the dominant controls in determining ground-water recharge. Seven existing watershed models from different humid regions of the United States were chosen to analyze the sensitivity of simulated recharge to model parameters. Parameter sensitivities were determined using a nonlinear regression computer program to generate a suite of diagnostic statistics. The statistics identify model parameters that have the greatest effect on simulated ground-water recharge and that compare and contrast the hydrologic system responses to those parameters. Simulated recharge in the Lost River and Big Creek watersheds in Washington State was sensitive to small changes in air temperature. The Hamden watershed model in west-central Minnesota was developed to investigate the relations that wetlands and other landscape features have with runoff processes. Excess soil moisture in the Hamden watershed simulation was preferentially routed to wetlands, instead of to the ground-water system, resulting in little sensitivity of any parameters to recharge. Simulated recharge in the North Fork Pheasant Branch watershed, Wisconsin, demonstrated the greatest sensitivity to parameters related to evapotranspiration. Three watersheds were simulated as part of the Model Parameter Estimation Experiment (MOPEX). Parameter sensitivities for the MOPEX watersheds, Amite River, Louisiana and Mississippi, English River, Iowa, and South Branch Potomac River, West Virginia, were similar and most sensitive to small changes in air temperature and a user-defined flow

Experimental determination of chosen document elements parameters from raster graphics sources

Directory of Open Access Journals (Sweden)

Jiří Rybička

2010-01-01

Full Text Available Visual appearance of documents and their formal quality is considered to be as important as the content quality. Formal and typographical quality of documents can be evaluated by an automated system that processes raster images of documents. A document is described by a formal model that treats a page as an object and also as a set of elements, whereas page elements include text and graphic object. All elements are described by their parameters depending on elements’ type. For future evaluation, mainly text objects are important. This paper describes the experimental determination of chosen document elements parameters from raster images. Techniques for image processing are used, where an image is represented as a matrix of dots and parameter values are extracted. Algorithms for parameter extraction from raster images were designed and were aimed mainly at typographical parameters like indentation, alignment, font size or spacing. Algorithms were tested on a set of 100 images of paragraphs or pages and provide very good results. Extracted parameters can be directly used for typographical quality evaluation.

Recommended direct simulation Monte Carlo collision model parameters for modeling ionized air transport processes

Energy Technology Data Exchange (ETDEWEB)

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

2016-02-15

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

PARAMETER ESTIMATION IN BREAD BAKING MODEL

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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

Quantitative Determination of Spring Water Quality Parameters via Electronic Tongue

Directory of Open Access Journals (Sweden)

Noèlia Carbó

2017-12-01

Full Text Available The use of a voltammetric electronic tongue for the quantitative analysis of quality parameters in spring water is proposed here. The electronic voltammetric tongue consisted of a set of four noble electrodes (iridium, rhodium, platinum, and gold housed inside a stainless steel cylinder. These noble metals have a high durability and are not demanding for maintenance, features required for the development of future automated equipment. A pulse voltammetry study was conducted in 83 spring water samples to determine concentrations of nitrate (range: 6.9–115 mg/L, sulfate (32–472 mg/L, fluoride (0.08–0.26 mg/L, chloride (17–190 mg/L, and sodium (11–94 mg/L as well as pH (7.3–7.8. These parameters were also determined by routine analytical methods in spring water samples. A partial least squares (PLS analysis was run to obtain a model to predict these parameter. Orthogonal signal correction (OSC was applied in the preprocessing step. Calibration (67% and validation (33% sets were selected randomly. The electronic tongue showed good predictive power to determine the concentrations of nitrate, sulfate, chloride, and sodium as well as pH and displayed a lower R2 and slope in the validation set for fluoride. Nitrate and fluoride concentrations were estimated with errors lower than 15%, whereas chloride, sulfate, and sodium concentrations as well as pH were estimated with errors below 10%.

Determination of power system component parameters using nonlinear dead beat estimation method

Science.gov (United States)

Kolluru, Lakshmi

Power systems are considered the most complex man-made wonders in existence today. In order to effectively supply the ever increasing demands of the consumers, power systems are required to remain stable at all times. Stability and monitoring of these complex systems are achieved by strategically placed computerized control centers. State and parameter estimation is an integral part of these facilities, as they deal with identifying the unknown states and/or parameters of the systems. Advancements in measurement technologies and the introduction of phasor measurement units (PMU) provide detailed and dynamic information of all measurements. Accurate availability of dynamic measurements provides engineers the opportunity to expand and explore various possibilities in power system dynamic analysis/control. This thesis discusses the development of a parameter determination algorithm for nonlinear power systems, using dynamic data obtained from local measurements. The proposed algorithm was developed by observing the dead beat estimator used in state space estimation of linear systems. The dead beat estimator is considered to be very effective as it is capable of obtaining the required results in a fixed number of steps. The number of steps required is related to the order of the system and the number of parameters to be estimated. The proposed algorithm uses the idea of dead beat estimator and nonlinear finite difference methods to create an algorithm which is user friendly and can determine the parameters fairly accurately and effectively. The proposed algorithm is based on a deterministic approach, which uses dynamic data and mathematical models of power system components to determine the unknown parameters. The effectiveness of the algorithm is tested by implementing it to identify the unknown parameters of a synchronous machine. MATLAB environment is used to create three test cases for dynamic analysis of the system with assumed known parameters. Faults are

Determining generator parameters of Camargos hydroelectric power plant through frequency response measurement

Energy Technology Data Exchange (ETDEWEB)

Oliveira, Sebastiao E.M. de; Padua Guarini, Antonio de [Centro de Pesquisas de Energia Eletrica (CEPEL), Rio de Janeiro, RJ (Brazil); Souza, Joao A. de; Valgas, Helio M; Pinto, Roberto del Giudice R. [Companhia Energetica de Minas Gerais (CEMIG), Belo Horizonte, MG (Brazil)

1994-12-31

This work describes the results of the set frequency response tests performed in the generator number 2, 6.9 kV, 25 MVA, of Camargos hydroelectric power plant, CEMIG, and the parameters relatives to determined structures of model. This tests are unpublished in Brazil. (author) 7 refs., 16 figs., 7 tabs.

Description of the Hexadecapole Deformation Parameter in the sdg Interacting Boson Model

Science.gov (United States)

Liu, Yu-xin; Sun, Di; Wang, Jia-jun; Han, Qi-zhi

1998-04-01

The hexadecapole deformation parameter β4 of the rare-earth and actinide nuclei is investigated in the framework of the sdg interacing boson model. An explicit relation between the geometric hexadecapole deformation parameter β4 and the intrinsic deformation parameters epsilon4, epsilon2 are obtained. The deformation parameters β4 of the rare-earths and actinides are determined without any free parameter. The calculated results agree with experimental data well. It also shows that the SU(5) limit of the sdg interacting boson model can describe the β4 systematics as well as the SU(3) limit.

Description of the hexadecapole deformation parameter in the sdg interacting boson model

International Nuclear Information System (INIS)

Liu Yuxin; Sun Di; Wang Jiajun; Han Qizhi

1998-01-01

The hexadecapole deformation parameter β 4 of the rare-earth and actinide nuclei is investigated in the framework of the sdg interacting boson model. An explicit relation between the geometric hexadecapole deformation parameter β 4 and the intrinsic deformation parameters ε 4 , ε 2 are obtained. The deformation parameters β 4 of the rare-earths and actinides are determined without any free parameter. The calculated results agree with experimental data well. It also shows that the SU(5) limit of the sdg interacting boson model can describe the β 4 systematics as well as the SU(3) limit

Repetitive Identification of Structural Systems Using a Nonlinear Model Parameter Refinement Approach

Directory of Open Access Journals (Sweden)

Jeng-Wen Lin

2009-01-01

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

A neutron balance approach in critical parameter determination

International Nuclear Information System (INIS)

Dall'Osso, Aldo

2008-01-01

The determination of a critical parameter, process known also as criticality or eigenvalue search, is one of the major functionalities in neutronics codes. The determination of the critical boron concentration or the critical control rod position are two examples. Classical procedures used to solve this problem are based on the iterative Newton-Raphson method where the value of the parameter is changed until the eigenvalue matches the target. We present here a different approach where an equation, derived from the neutron balance, is set and the critical parameter is the unknown. Solving this equation is equivalent to solve an eigenvalue problem where the critical parameter is the eigenvalue. It is also shown that this approach can be seen as an application of inverse perturbation theory. This method reduces considerably the computation time in situations where changes on the critical parameter make a high distortion on the flux distribution, as it is the case of the control rods. Some numerical examples illustrate the performances and the gain in stability in cases of simultaneous control of criticality and axial offset of the power distribution. The application to the determination of the critical uranium enrichment in a transport code is also presented. The simplicity of the method makes its implementation in fuel bundle lattice and reactor codes very easy

EXPERIMENTAL DETERMINATION OF DOUBLE VIBE FUNCTION PARAMETERS IN DIESEL ENGINES WITH BIODIESEL

Directory of Open Access Journals (Sweden)

Radivoje B Pešić

2010-01-01

Full Text Available A zero-dimensional, one zone model of engine cycle for steady-state regimes of engines and a simplified procedure for indicator diagrams analysis have been developed at the Laboratory for internal combustion engines, fuels and lubricants of the Faculty of Mechanical Engineering in Kragujevac. In addition to experimental research, thermodynamic modeling of working process of diesel engine with direct injection has been presented in this paper. The simplified procedure for indicator diagrams analysis has been applied, also. The basic problem, a selection of shape parameters of double Vibe function used for modeling the engine operation process, has been solved. The influence of biodiesel fuel and engine working regimes on the start of combustion, combustion duration and shape parameter of double Vibe was determined by a least square fit of experimental heat release curve.

Determination of radial profile of ICF hot spot's state by multi-objective parameters optimization

International Nuclear Information System (INIS)

Dong Jianjun; Deng Bo; Cao Zhurong; Ding Yongkun; Jiang Shaoen

2014-01-01

A method using multi-objective parameters optimization is presented to determine the radial profile of hot spot temperature and density. And a parameter space which contain five variables: the temperatures at center and the interface of fuel and remain ablator, the maximum model density of remain ablator, the mass ratio of remain ablator to initial ablator and the position of interface between fuel and the remain ablator, is used to described the hot spot radial temperature and density. Two objective functions are set as the variances of normalized intensity profile from experiment X-ray images and the theory calculation. Another objective function is set as the variance of experiment average temperature of hot spot and the average temperature calculated by theoretical model. The optimized parameters are obtained by multi-objective genetic algorithm searching for the five dimension parameter space, thereby the optimized radial temperature and density profiles can be determined. The radial temperature and density profiles of hot spot by experiment data measured by KB microscope cooperating with X-ray film are presented. It is observed that the temperature profile is strongly correlated to the objective functions. (authors)

Noise-spectroscopy of multiqubit systems: Determining all their parameters by applying an external classical noise

Energy Technology Data Exchange (ETDEWEB)

Savel' ev, S., E-mail: S.Saveliev@lboro.ac.uk [Department of Physics, Loughborough University, Leicestershire LE11 3TU (United Kingdom); Advanced Science Institute, RIKEN, Wako-shi, Saitama 351-0198 (Japan); Zagoskin, A.M. [Department of Physics, Loughborough University, Leicestershire LE11 3TU (United Kingdom); Advanced Science Institute, RIKEN, Wako-shi, Saitama 351-0198 (Japan); Omelyanchouk, A.N. [Advanced Science Institute, RIKEN, Wako-shi, Saitama 351-0198 (Japan); B. Verkin Institute for Low Temperature Physics and Engineering, 61103 Kharkov (Ukraine); Nori, Franco [Advanced Science Institute, RIKEN, Wako-shi, Saitama 351-0198 (Japan); Physics Department, University of Michigan, Ann Arbor, MI 48109-1040 (United States)

2010-10-05

Imagine that you have several sets of two coupled qubits, but you do not know the parameters of their Hamitonians. How to determine these without resorting to the usual spectroscopy approach to the problem? Based on numerical modeling, we show that all the parameters of a system of two coupled qubits can be determined by applying to it an external classical noise and analyzing the Fourier spectrum of the elements of the system's density matrix. In particular, the interlevel spacings as well as the strength and sign of the qubit-qubit coupling can be determined this way.

Spectroscopic determination of valence band parameters in InP

International Nuclear Information System (INIS)

Lewis, R.A.; Lough, B.C.C.

2003-01-01

Full text: The general form of the Hamiltonian for an electron or hole in a semiconductor has been given by Luttinger. The valence band is characterised by three parameters - γ 1 , γ 2 , γ 3 -now commonly known as the Luttinger parameters. Despite many investigations there is still considerable uncertainty regarding the Luttinger parameters of InP. The situation has been reviewed by Hackenberg et al. These authors themselves sought to determine the Luttinger parameters by hot-electron luminescence and discovered that many Luttinger parameter triplets were consistent with their data. We employ a spectroscopic approach to estimating valence-band parameters in InP. Calculations have been made for both the unperturbed energy levels and the energy levels in a magnetic field of acceptor impurities in semiconductors characterised by different Luttinger parameters. We compare our recent experimental data for the transitions associated with the Zn acceptor impurity in InP in magnetic fields up to 30 T to determine the most appropriate set of valence-band parameters for InP

Robust estimation of hydrological model parameters

Directory of Open Access Journals (Sweden)

A. Bárdossy

2008-11-01

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

Photovoltaic module parameters acquisition model

Energy Technology Data Exchange (ETDEWEB)

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

2014-09-01

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

Photovoltaic module parameters acquisition model

International Nuclear Information System (INIS)

Cibira, Gabriel; Koščová, Marcela

2014-01-01

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

Physically based model for extracting dual permeability parameters using non-Newtonian fluids

Science.gov (United States)

Abou Najm, M. R.; Basset, C.; Stewart, R. D.; Hauswirth, S.

2017-12-01

Dual permeability models are effective for the assessment of flow and transport in structured soils with two dominant structures. The major challenge to those models remains in the ability to determine appropriate and unique parameters through affordable, simple, and non-destructive methods. This study investigates the use of water and a non-Newtonian fluid in saturated flow experiments to derive physically-based parameters required for improved flow predictions using dual permeability models. We assess the ability of these two fluids to accurately estimate the representative pore sizes in dual-domain soils, by determining the effective pore sizes of macropores and micropores. We developed two sub-models that solve for the effective macropore size assuming either cylindrical (e.g., biological pores) or planar (e.g., shrinkage cracks and fissures) pore geometries, with the micropores assumed to be represented by a single effective radius. Furthermore, the model solves for the percent contribution to flow (wi) corresponding to the representative macro and micro pores. A user-friendly solver was developed to numerically solve the system of equations, given that relevant non-Newtonian viscosity models lack forms conducive to analytical integration. The proposed dual-permeability model is a unique attempt to derive physically based parameters capable of measuring dual hydraulic conductivities, and therefore may be useful in reducing parameter uncertainty and improving hydrologic model predictions.

Empirical flow parameters : a tool for hydraulic model validity

Science.gov (United States)

Asquith, William H.; Burley, Thomas E.; Cleveland, Theodore G.

2013-01-01

The objectives of this project were (1) To determine and present from existing data in Texas, relations between observed stream flow, topographic slope, mean section velocity, and other hydraulic factors, to produce charts such as Figure 1 and to produce empirical distributions of the various flow parameters to provide a methodology to "check if model results are way off!"; (2) To produce a statistical regional tool to estimate mean velocity or other selected parameters for storm flows or other conditional discharges at ungauged locations (most bridge crossings) in Texas to provide a secondary way to compare such values to a conventional hydraulic modeling approach. (3.) To present ancillary values such as Froude number, stream power, Rosgen channel classification, sinuosity, and other selected characteristics (readily determinable from existing data) to provide additional information to engineers concerned with the hydraulic-soil-foundation component of transportation infrastructure.

Assessing robustness of designs for random effects parameters for nonlinear mixed-effects models.

Science.gov (United States)

Duffull, Stephen B; Hooker, Andrew C

2017-12-01

Optimal designs for nonlinear models are dependent on the choice of parameter values. Various methods have been proposed to provide designs that are robust to uncertainty in the prior choice of parameter values. These methods are generally based on estimating the expectation of the determinant (or a transformation of the determinant) of the information matrix over the prior distribution of the parameter values. For high dimensional models this can be computationally challenging. For nonlinear mixed-effects models the question arises as to the importance of accounting for uncertainty in the prior value of the variances of the random effects parameters. In this work we explore the influence of the variance of the random effects parameters on the optimal design. We find that the method for approximating the expectation and variance of the likelihood is of potential importance for considering the influence of random effects. The most common approximation to the likelihood, based on a first-order Taylor series approximation, yields designs that are relatively insensitive to the prior value of the variance of the random effects parameters and under these conditions it appears to be sufficient to consider uncertainty on the fixed-effects parameters only.

A new approach to the extraction of single exponential diode model parameters

Science.gov (United States)

Ortiz-Conde, Adelmo; García-Sánchez, Francisco J.

2018-06-01

A new integration method is presented for the extraction of the parameters of a single exponential diode model with series resistance from the measured forward I-V characteristics. The extraction is performed using auxiliary functions based on the integration of the data which allow to isolate the effects of each of the model parameters. A differentiation method is also presented for data with low level of experimental noise. Measured and simulated data are used to verify the applicability of both proposed method. Physical insight about the validity of the model is also obtained by using the proposed graphical determinations of the parameters.

Systematic and random erros in lattice parameter determinations

International Nuclear Information System (INIS)

Nascimento, E.M.

1980-01-01

A new method is proposed for evaluation of diffraction data used in precise determination of lattice parameters. The method is based on separation and systematic erros on the diffraction angles level, where the randon part of erros is independent on the 0 angle. The separation is enable by assumption that the systematic part of erros depends on the 0 angle linearly. In that situation the high precision in lattice parameters determination is related more to reducing the randon errors content that to the presence of unremoved systematic errors. (Author) [pt

Sensitivity of Tumor Motion Simulation Accuracy to Lung Biomechanical Modeling Approaches and Parameters

OpenAIRE

Tehrani, Joubin Nasehi; Yang, Yin; Werner, Rene; Lu, Wei; Low, Daniel; Guo, Xiaohu; Wang, Jing

2015-01-01

Finite element analysis (FEA)-based biomechanical modeling can be used to predict lung respiratory motion. In this technique, elastic models and biomechanical parameters are two important factors that determine modeling accuracy. We systematically evaluated the effects of lung and lung tumor biomechanical modeling approaches and related parameters to improve the accuracy of motion simulation of lung tumor center of mass (TCM) displacements. Experiments were conducted with four-dimensional com...

Parameter optimization for surface flux transport models

Science.gov (United States)

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

2017-11-01

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

Oyster Creek cycle 10 nodal model parameter optimization study using PSMS

International Nuclear Information System (INIS)

Dougher, J.D.

1987-01-01

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

Parameters-related uncertainty in modeling sugar cane yield with an agro-Land Surface Model

Science.gov (United States)

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

2012-12-01

Agro-Land Surface Models (agro-LSM) have been developed from the coupling of specific crop models and large-scale generic vegetation models. They aim at accounting for the spatial distribution and variability of energy, water and carbon fluxes within soil-vegetation-atmosphere continuum with a particular emphasis on how crop phenology and agricultural management practice influence the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty in these models is related to the many parameters included in the models' equations. In this study, we quantify the parameter-based uncertainty in the simulation of sugar cane biomass production with the agro-LSM ORCHIDEE-STICS on a multi-regional approach with data from sites in Australia, La Reunion and Brazil. First, the main source of uncertainty for the output variables NPP, GPP, and sensible heat flux (SH) is determined through a screening of the main parameters of the model on a multi-site basis leading to the selection of a subset of most sensitive parameters causing most of the uncertainty. In a second step, a sensitivity analysis is carried out on the parameters selected from the screening analysis at a regional scale. For this, a Monte-Carlo sampling method associated with the calculation of Partial Ranked Correlation Coefficients is used. First, we quantify the sensitivity of the output variables to individual input parameters on a regional scale for two regions of intensive sugar cane cultivation in Australia and Brazil. Then, we quantify the overall uncertainty in the simulation's outputs propagated from the uncertainty in the input parameters. Seven parameters are identified by the screening procedure as driving most of the uncertainty in the agro-LSM ORCHIDEE-STICS model output at all sites. These parameters control photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), root

Determination of Geometric and Kinematical Parameters of Coronal Mass Ejections Using STEREO Data

Science.gov (United States)

Fainshtein, V. G.; Tsivileva, D. M.; Kashapova, L. K.

2010-03-01

We present a new, relatively simple and fast method to determine true geometric and kinematical CME parameters from simultaneous STEREO A, B observations of CMEs. These parameters are the three-dimensional direction of CME propagation, velocity and acceleration of CME front, CME angular sizes and front position depending on time. The method is based on the assumption that CME shape may be described by a modification of so-called ice-cream cone models. The method has been tested for several CMEs.

Determination of Geometric and Kinematical Parameters of Coronal Mass Ejections Using STEREO Data

International Nuclear Information System (INIS)

Fainshtein, V. G.; Tsivileva, D. M.; Kashapova, L. K.

2010-01-01

We present a new, relatively simple and fast method to determine true geometric and kinematical CME parameters from simultaneous STEREO A, B observations of CMEs. These parameters are the three-dimensional direction of CME propagation, velocity and acceleration of CME front, CME angular sizes and front position depending on time. The method is based on the assumption that CME shape may be described by a modification of so-called ice-cream cone models. The method has been tested for several CMEs.

Estimating Parameters for the PVsyst Version 6 Photovoltaic Module Performance Model

Energy Technology Data Exchange (ETDEWEB)

Hansen, Clifford [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

2015-10-01

We present an algorithm to determine parameters for the photovoltaic module perf ormance model encoded in the software package PVsyst(TM) version 6. Our method operates on current - voltage (I - V) measured over a range of irradiance and temperature conditions. We describe the method and illustrate its steps using data for a 36 cell crystalli ne silicon module. We qualitatively compare our method with one other technique for estimating parameters for the PVsyst(TM) version 6 model .

Determination of Dosimetric Parameters of the Second Model of Pd-103 Seed Manufactured at Agricultural, Medical and Industrial Research School

Directory of Open Access Journals (Sweden)

Gholamreza Raisali

2008-06-01

Full Text Available Introduction: The use of low energy isotopes such as  103 Pd in brachytherapy for the treatment of cancers  such as prostate, eye, head, neck, breast and cervix is increasing. In this regard, different models of Pd- 103  seeds  have  been  designed  and  manufactured  at  the  Agricultural,  Medical  and  Industrial  Research  School (AMIRS of Atomic Energy Organization of Iran. In this research, the dosimetric parameters of  the second model of Pd-103 seed manufactured at AMIRS have been calculated and measured.   Materials and Methods: The dosimetric parameters of the second Pd-103 seed manufactured at AMIRS  were determined according to TG-43U1 protocol using Monte Carlo calculations (MCNP4C computer  code  and  measurements  performed  using  TLD-GR200A  dosimeters  in  a  Perspex  phantom.  The  parameters  include  dose  rate  constant,  geometry  function,  radial  dose  function,  anisotropy  function,  anisotropy factor and anisotropy constant.  Results:  It  was  found  that  by  using  MCNP4C  code  the  calculated  dose  rate  constant  in  water  and  Perspex  was  0.706±0.001   and  0.501±0.001  cGyh -1 U -1 , respectively.  Using  the  calculated  geometry  function,  the  radial  dose  function  and  the  anisotropy  function  were  determined  by  experimental  and  theoretical methods in water and Perspex phantom. Also, the calculated value of anisotropy constant in  water was equal to 0.88.  Discussion and Conclusion: A discrepancy of less than 10% between the calculated and the measured  values indicates a reasonable agreement between the simulation and the measurement method. Also, the  dosimetric parameters of this seed have been compared to the dosimetric parameters of the first Pd-103  seed  manufactured  at  AMIRS  and  some  other  seeds.  The  obtained  results  indicate  that  the  seeds  manufactured at AMIRS

EXTRACTION OF SPATIAL PARAMETERS FROM CLASSIFIED LIDAR DATA AND AERIAL PHOTOGRAPH FOR SOUND MODELING

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S. Biswas

2012-07-01

Full Text Available Prediction of outdoor sound levels in 3D space is important for noise management, soundscaping etc. Sound levels at outdoor can be predicted using sound propagation models which need terrain parameters. The existing practices of incorporating terrain parameters into models are often limited due to inadequate data or inability to determine accurate sound transmission paths through a terrain. This leads to poor accuracy in modelling. LIDAR data and Aerial Photograph (or Satellite Images provide opportunity to incorporate high resolution data into sound models. To realize this, identification of building and other objects and their use for extraction of terrain parameters are fundamental. However, development of a suitable technique, to incorporate terrain parameters from classified LIDAR data and Aerial Photograph, for sound modelling is a challenge. Determination of terrain parameters along various transmission paths of sound from sound source to a receiver becomes very complex in an urban environment due to the presence of varied and complex urban features. This paper presents a technique to identify the principal paths through which sound transmits from source to receiver. Further, the identified principal paths are incorporated inside the sound model for sound prediction. Techniques based on plane cutting and line tracing are developed for determining principal paths and terrain parameters, which use various information, e.g., building corner and edges, triangulated ground, tree points and locations of source and receiver. The techniques developed are validated through a field experiment. Finally efficacy of the proposed technique is demonstrated by developing a noise map for a test site.

DETERMINATION OF ACTIVATED SLUDGE MODEL ASDM PARAMETERS FOR WASTE WATER TREATMENT PLANT OPERATING IN THE SEQUENTIAL–FLOW TECHNOLOGY

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Dariusz Zdebik

2015-01-01

Full Text Available This paper presents a method for calibration of activated sludge model with the use of computer program BioWin. Computer scheme has been developed on the basis of waste water treatment plant operating in the sequential – flow technology. For calibration of the activated sludge model data of influent and treated effluent from the existing object were used. As a result of conducted analysis was a change in biokinetic model and kinetic parameters parameters of wastewater treatment facilities. The presented method of study of the selected parameters impact on the activated sludge biokinetic model (including autotrophs maximum growth rate, the share of organic slurry in suspension general operational, efficiency secondary settling tanks can be used for conducting simulation studies of other treatment plants.

Genetic algorithm approach to thin film optical parameters determination

International Nuclear Information System (INIS)

Jurecka, S.; Jureckova, M.; Muellerova, J.

2003-01-01

Optical parameters of thin film are important for several optical and optoelectronic applications. In this work the genetic algorithm proposed to solve optical parameters of thin film values. The experimental reflectance is modelled by the Forouhi - Bloomer dispersion relations. The refractive index, the extinction coefficient and the film thickness are the unknown parameters in this model. Genetic algorithm use probabilistic examination of promissing areas of the parameter space. It creates a population of solutions based on the reflectance model and then operates on the population to evolve the best solution by using selection, crossover and mutation operators on the population individuals. The implementation of genetic algorithm method and the experimental results are described too (Authors)

An Application of a Multidimensional Extension of the Two-Parameter Logistic Latent Trait Model.

Science.gov (United States)

McKinley, Robert L.; Reckase, Mark D.

A latent trait model is described that is appropriate for use with tests that measure more than one dimension, and its application to both real and simulated test data is demonstrated. Procedures for estimating the parameters of the model are presented. The research objectives are to determine whether the two-parameter logistic model more…

Determination of parameters of microstructural inhomogeneity of metal deformation by the method of modelling

International Nuclear Information System (INIS)

Kornienko, V.T.

1991-01-01

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

Application of genetic algorithm in radio ecological models parameter determination

Energy Technology Data Exchange (ETDEWEB)

Pantelic, G. [Institute of Occupatioanl Health and Radiological Protection ' Dr Dragomir Karajovic' , Belgrade (Serbia)

2006-07-01

The method of genetic algorithms was used to determine the biological half-life of 137 Cs in cow milk after the accident in Chernobyl. Methodologically genetic algorithms are based on the fact that natural processes tend to optimize themselves and therefore this method should be more efficient in providing optimal solutions in the modeling of radio ecological and environmental events. The calculated biological half-life of 137 Cs in milk is (32 {+-} 3) days and transfer coefficient from grass to milk is (0.019 {+-} 0.005). (authors)

Modeling Coronal Mass Ejections with EUHFORIA: A Parameter Study of the Gibson-Low Flux Rope Model using Multi-Viewpoint Observations

Science.gov (United States)

Verbeke, C.; Asvestari, E.; Scolini, C.; Pomoell, J.; Poedts, S.; Kilpua, E.

2017-12-01

Coronal Mass Ejections (CMEs) are one of the big influencers on the coronal and interplanetary dynamics. Understanding their origin and evolution from the Sun to the Earth is crucial in order to determine the impact on our Earth and society. One of the key parameters that determine the geo-effectiveness of the coronal mass ejection is its internal magnetic configuration. We present a detailed parameter study of the Gibson-Low flux rope model. We focus on changes in the input parameters and how these changes affect the characteristics of the CME at Earth. Recently, the Gibson-Low flux rope model has been implemented into the inner heliosphere model EUHFORIA, a magnetohydrodynamics forecasting model of large-scale dynamics from 0.1 AU up to 2 AU. Coronagraph observations can be used to constrain the kinematics and morphology of the flux rope. One of the key parameters, the magnetic field, is difficult to determine directly from observations. In this work, we approach the problem by conducting a parameter study in which flux ropes with varying magnetic configurations are simulated. We then use the obtained dataset to look for signatures in imaging observations and in-situ observations in order to find an empirical way of constraining the parameters related to the magnetic field of the flux rope. In particular, we focus on events observed by at least two spacecraft (STEREO + L1) in order to discuss the merits of using observations from multiple viewpoints in constraining the parameters.

Application of an Evolutionary Algorithm for Parameter Optimization in a Gully Erosion Model

Energy Technology Data Exchange (ETDEWEB)

Rengers, Francis; Lunacek, Monte; Tucker, Gregory

2016-06-01

Herein we demonstrate how to use model optimization to determine a set of best-fit parameters for a landform model simulating gully incision and headcut retreat. To achieve this result we employed the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), an iterative process in which samples are created based on a distribution of parameter values that evolve over time to better fit an objective function. CMA-ES efficiently finds optimal parameters, even with high-dimensional objective functions that are non-convex, multimodal, and non-separable. We ran model instances in parallel on a high-performance cluster, and from hundreds of model runs we obtained the best parameter choices. This method is far superior to brute-force search algorithms, and has great potential for many applications in earth science modeling. We found that parameters representing boundary conditions tended to converge toward an optimal single value, whereas parameters controlling geomorphic processes are defined by a range of optimal values.

Nonlinear System Identification Using Quasi-ARX RBFN Models with a Parameter-Classified Scheme

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Lan Wang

2017-01-01

Full Text Available Quasi-linear autoregressive with exogenous inputs (Quasi-ARX models have received considerable attention for their usefulness in nonlinear system identification and control. In this paper, identification methods of quasi-ARX type models are reviewed and categorized in three main groups, and a two-step learning approach is proposed as an extension of the parameter-classified methods to identify the quasi-ARX radial basis function network (RBFN model. Firstly, a clustering method is utilized to provide statistical properties of the dataset for determining the parameters nonlinear to the model, which are interpreted meaningfully in the sense of interpolation parameters of a local linear model. Secondly, support vector regression is used to estimate the parameters linear to the model; meanwhile, an explicit kernel mapping is given in terms of the nonlinear parameter identification procedure, in which the model is transformed from the nonlinear-in-nature to the linear-in-parameter. Numerical and real cases are carried out finally to demonstrate the effectiveness and generalization ability of the proposed method.

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

Science.gov (United States)

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

2018-05-01

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

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

Directory of Open Access Journals (Sweden)

S. Pathiraja

2018-05-01

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

Parameter Estimation of Partial Differential Equation Models.

Science.gov (United States)

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

2013-01-01

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

NMR determination of the order parameter in proton and deuteron glasses

International Nuclear Information System (INIS)

Blinc, R.; Dolinsek, J.; Zalar, B.

1989-01-01

The inhomogeneous broadening of the ND + deuteron, O-D--O deuteron and 87 Rb quadrapole perturbed NMR spectra in Rb 0.56 (ND 4 ) 0.44 D 2 PO 4 is used for a direct determination of the Edwards-Anderson pseudo-spin glass order parameter. The data provide strong support for a model where the basic difference between magnetic spin glasses and proton or deuteron glasses is the presence of an inherent random field resulting from substitutional disorder which linearly couples to the O-D--O pseudo spins. In these systems we do not deal with a transition from a paraelectric to a pseudo-spin glass phase but rather with a transition from an ergodic pseudo-spin glass phase with a single order parameter q to a non-ergodic pseudo-spin glass phase with an infinite number of order parameters. (author). 11 refs.; 6 figs

Good Models Gone Bad: Quantifying and Predicting Parameter-Induced Climate Model Simulation Failures

Science.gov (United States)

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

2012-12-01

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

Application of genetic algorithm in radio ecological models parameter determination

International Nuclear Information System (INIS)

Pantelic, G.

2006-01-01

The method of genetic algorithms was used to determine the biological half-life of 137 Cs in cow milk after the accident in Chernobyl. Methodologically genetic algorithms are based on the fact that natural processes tend to optimize themselves and therefore this method should be more efficient in providing optimal solutions in the modeling of radio ecological and environmental events. The calculated biological half-life of 137 Cs in milk is (32 ± 3) days and transfer coefficient from grass to milk is (0.019 ± 0.005). (authors)

Parameter Estimation for Traffic Noise Models Using a Harmony Search Algorithm

Directory of Open Access Journals (Sweden)

Deok-Soon An

2013-01-01

Full Text Available A technique has been developed for predicting road traffic noise for environmental assessment, taking into account traffic volume as well as road surface conditions. The ASJ model (ASJ Prediction Model for Road Traffic Noise, 1999, which is based on the sound power level of the noise emitted by the interaction between the road surface and tires, employs regression models for two road surface types: dense-graded asphalt (DGA and permeable asphalt (PA. However, these models are not applicable to other types of road surfaces. Accordingly, this paper introduces a parameter estimation procedure for ASJ-based noise prediction models, utilizing a harmony search (HS algorithm. Traffic noise measurement data for four different vehicle types were used in the algorithm to determine the regression parameters for several road surface types. The parameters of the traffic noise prediction models were evaluated using another measurement set, and good agreement was observed between the predicted and measured sound power levels.

Failure analysis of parameter-induced simulation crashes in climate models

Science.gov (United States)

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

2013-08-01

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

Patient-specific parameter estimation in single-ventricle lumped circulation models under uncertainty

Science.gov (United States)

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

2017-01-01

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

Quality assessment for radiological model parameters

International Nuclear Information System (INIS)

Funtowicz, S.O.

1989-01-01

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

Study on Identification of Material Model Parameters from Compact Tension Test on Concrete Specimens

Science.gov (United States)

Hokes, Filip; Kral, Petr; Husek, Martin; Kala, Jiri

2017-10-01

Identification of a concrete material model parameters using optimization is based on a calculation of a difference between experimentally measured and numerically obtained data. Measure of the difference can be formulated via root mean squared error that is often used for determination of accuracy of a mathematical model in the field of meteorology or demography. The quality of the identified parameters is, however, determined not only by right choice of an objective function but also by the source experimental data. One of the possible way is to use load-displacement curves from three-point bending tests that were performed on concrete specimens. This option shows the significance of modulus of elasticity, tensile strength and specific fracture energy. Another possible option is to use experimental data from compact tension test. It is clear that the response in the second type of test is also dependent on the above mentioned material parameters. The question is whether the parameters identified within three-point bending test and within compact tension test will reach the same values. The presented article brings the numerical study of inverse identification of material model parameters from experimental data measured during compact tension tests. The article also presents utilization of the modified sensitivity analysis that calculates the sensitivity of the material model parameters for different parts of loading curve. The main goal of the article is to describe the process of inverse identification of parameters for plasticity-based material model of concrete and prepare data for future comparison with identified values of the material model parameters from different type of fracture tests.

Towards automated diffraction tomography. Part II-Cell parameter determination

International Nuclear Information System (INIS)

Kolb, U.; Gorelik, T.; Otten, M.T.

2008-01-01

Automated diffraction tomography (ADT) allows the collection of three-dimensional (3d) diffraction data sets from crystals down to a size of only few nanometres. Imaging is done in STEM mode, and diffraction data are collected with quasi-parallel beam nanoelectron diffraction (NED). Here, we present a set of developed processing steps necessary for automatic unit-cell parameter determination from the collected 3d diffraction data. Cell parameter determination is done via extraction of peak positions from a recorded data set (called the data reduction path) followed by subsequent cluster analysis of difference vectors. The procedure of lattice parameter determination is presented in detail for a beam-sensitive organic material. Independently, we demonstrate a potential (called the full integration path) based on 3d reconstruction of the reciprocal space visualising special structural features of materials such as partial disorder. Furthermore, we describe new features implemented into the acquisition part

A sensitivity analysis of a personalized pulse wave propagation model for arteriovenous fistula surgery. Part B: Identification of possible generic model parameters.

Science.gov (United States)

Huberts, W; de Jonge, C; van der Linden, W P M; Inda, M A; Passera, K; Tordoir, J H M; van de Vosse, F N; Bosboom, E M H

2013-06-01

Decision-making in vascular access surgery for hemodialysis can be supported by a pulse wave propagation model that is able to simulate pressure and flow changes induced by the creation of a vascular access. To personalize such a model, patient-specific input parameters should be chosen. However, the number of input parameters that can be measured in clinical routine is limited. Besides, patient data are compromised with uncertainty. Incomplete and uncertain input data will result in uncertainties in model predictions. In part A, we analyzed how the measurement uncertainty in the input propagates to the model output by means of a sensitivity analysis. Of all 73 input parameters, 16 parameters were identified to be worthwhile to measure more accurately and 51 could be fixed within their measurement uncertainty range, but these latter parameters still needed to be measured. Here, we present a methodology for assessing the model input parameters that can be taken constant and therefore do not need to be measured. In addition, a method to determine the value of this parameter is presented. For the pulse wave propagation model applied to vascular access surgery, six patient-specific datasets were analyzed and it was found that 47 out of 73 parameters can be fixed on a generic value. These model parameters are not important for personalization of the wave propagation model. Furthermore, we were able to determine a generic value for 37 of the 47 fixable model parameters. Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.

A note on modeling of tumor regression for estimation of radiobiological parameters

International Nuclear Information System (INIS)

Zhong, Hualiang; Chetty, Indrin

2014-01-01

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

Determination of spatially dependent diffusion parameters in bovine bone using Kalman filter.

Science.gov (United States)

Shokry, Abdallah; Ståhle, Per; Svensson, Ingrid

2015-11-07

Although many studies have been made for homogenous constant diffusion, bone is an inhomogeneous material. It has been suggested that bone porosity decreases from the inner boundaries to the outer boundaries of the long bones. The diffusivity of substances in the bone matrix is believed to increase as the bone porosity increases. In this study, an experimental set up is used where bovine bone samples, saturated with potassium chloride (KCl), were put into distilled water and the conductivity of the water was followed. Chloride ions in the bone samples escaped out in the water through diffusion and the increase of the conductivity was measured. A one-dimensional, spatially dependent mathematical model describing the diffusion process is used. The diffusion parameters in the model are determined using a Kalman filter technique. The parameters for spatially dependent at endosteal and periosteal surfaces are found to be (12.8 ± 4.7) × 10(-11) and (5 ± 3.5) × 10(-11)m(2)/s respectively. The mathematical model function using the obtained diffusion parameters fits very well with the experimental data with mean square error varies from 0.06 × 10(-6) to 0.183 × 10(-6) (μS/m)(2). Copyright © 2015 Elsevier Ltd. All rights reserved.

A Consistent Methodology Based Parameter Estimation for a Lactic Acid Bacteria Fermentation Model

DEFF Research Database (Denmark)

Spann, Robert; Roca, Christophe; Kold, David

2017-01-01

Lactic acid bacteria are used in many industrial applications, e.g. as starter cultures in the dairy industry or as probiotics, and research on their cell production is highly required. A first principles kinetic model was developed to describe and understand the biological, physical, and chemical...... mechanisms in a lactic acid bacteria fermentation. We present here a consistent approach for a methodology based parameter estimation for a lactic acid fermentation. In the beginning, just an initial knowledge based guess of parameters was available and an initial parameter estimation of the complete set...... of parameters was performed in order to get a good model fit to the data. However, not all parameters are identifiable with the given data set and model structure. Sensitivity, identifiability, and uncertainty analysis were completed and a relevant identifiable subset of parameters was determined for a new...

Parameter Estimation of Partial Differential Equation Models

KAUST Repository

Xun, Xiaolei

2013-09-01

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

One-loop effects on MSSM parameter determination via chargino production at the LC

Energy Technology Data Exchange (ETDEWEB)

Bharucha, Aoife [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Kalinowski, Jan [Warsaw Univ. (Poland). Faculty of Physics; Moortgat-Pick, Gudrid [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Rolbiecki, Krzysztof [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); IFT-UAM/CSIC, Madrid (Spain). Inst. de Fisica Teorica; Weiglein, Georg [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)

2012-11-15

At a future linear collider very precise measurements, typically with errors of <1%, are expected to be achievable. Such an accuracy gives sensitivity to the quantum corrections, which therefore must be incorporated in theoretical calculations in order to determine the underlying new physics parameters from prospective linear collider measurements. In the context of the chargino-neutralino sector of the minimal supersymmetric standard model, this involves fitting one-loop predictions to prospective measurements of the cross sections, forward-backward asymmetries and of the accessible chargino and neutralino masses. Taking recent results from LHC SUSY and Higgs searches into account we consider three benchmark scenarios, each with characteristic features. Our analysis shows how an accurate determination of the desired parameters is possible, providing in addition access to the stop masses and mixing angle.

One-loop effects on MSSM parameter determination via chargino production at the LC

International Nuclear Information System (INIS)

Bharucha, Aoife; Rolbiecki, Krzysztof

2012-11-01

At a future linear collider very precise measurements, typically with errors of <1%, are expected to be achievable. Such an accuracy gives sensitivity to the quantum corrections, which therefore must be incorporated in theoretical calculations in order to determine the underlying new physics parameters from prospective linear collider measurements. In the context of the chargino-neutralino sector of the minimal supersymmetric standard model, this involves fitting one-loop predictions to prospective measurements of the cross sections, forward-backward asymmetries and of the accessible chargino and neutralino masses. Taking recent results from LHC SUSY and Higgs searches into account we consider three benchmark scenarios, each with characteristic features. Our analysis shows how an accurate determination of the desired parameters is possible, providing in addition access to the stop masses and mixing angle.

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.

Centrifuge modeling of one-step outflow tests for unsaturated parameter estimations

Directory of Open Access Journals (Sweden)

H. Nakajima

2006-01-01

Full Text Available Centrifuge modeling of one-step outflow tests were carried out using a 2-m radius geotechnical centrifuge, and the cumulative outflow and transient pore water pressure were measured during the tests at multiple gravity levels. Based on the scaling laws of centrifuge modeling, the measurements generally showed reasonable agreement with prototype data calculated from forward simulations with input parameters determined from standard laboratory tests. The parameter optimizations were examined for three different combinations of input data sets using the test measurements. Within the gravity level examined in this study up to 40g, the optimized unsaturated parameters compared well when accurate pore water pressure measurements were included along with cumulative outflow as input data. With its capability to implement variety of instrumentations under well controlled initial and boundary conditions and to shorten testing time, the centrifuge modeling technique is attractive as an alternative experimental method that provides more freedom to set inverse problem conditions for the parameter estimation.

Centrifuge modeling of one-step outflow tests for unsaturated parameter estimations

Science.gov (United States)

Nakajima, H.; Stadler, A. T.

2006-10-01

Centrifuge modeling of one-step outflow tests were carried out using a 2-m radius geotechnical centrifuge, and the cumulative outflow and transient pore water pressure were measured during the tests at multiple gravity levels. Based on the scaling laws of centrifuge modeling, the measurements generally showed reasonable agreement with prototype data calculated from forward simulations with input parameters determined from standard laboratory tests. The parameter optimizations were examined for three different combinations of input data sets using the test measurements. Within the gravity level examined in this study up to 40g, the optimized unsaturated parameters compared well when accurate pore water pressure measurements were included along with cumulative outflow as input data. With its capability to implement variety of instrumentations under well controlled initial and boundary conditions and to shorten testing time, the centrifuge modeling technique is attractive as an alternative experimental method that provides more freedom to set inverse problem conditions for the parameter estimation.

Reactor parameters and constants determination by using measurements in subcritical and exponential assembly

International Nuclear Information System (INIS)

Voi, Dante Luiz; Santos Bastos, Wilma dos

1995-01-01

Subcritical and exponential experiments are important for Reactor Physics integral parameter determinations both to validate and confirm theoretical models for reactor calculations. An exponential and subcritical facility has been constructed to be used on the internal thermal column of the Argonauta reactor at IEN-CNEN- Rio de Janeiro. An experimental research program has been developed for the determination of fundamental reactor constants as buckling, migration areas, resonance escape probabilities, thermal utilization, fast fission and fuel eta factors. (author) 23 refs

Do Lumped-Parameter Models Provide the Correct Geometrical Damping?

DEFF Research Database (Denmark)

Andersen, Lars

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 simple but accurate procedure for solving the five-parameter model

International Nuclear Information System (INIS)

Mares, Oana; Paulescu, Marius; Badescu, Viorel

2015-01-01

Highlights: • A new procedure for extracting the parameters of the one-diode model is proposed. • Only the basic information listed in the datasheet of PV modules are required. • Results demonstrate a simple, robust and accurate procedure. - Abstract: The current–voltage characteristic of a photovoltaic module is typically evaluated by using a model based on the solar cell equivalent circuit. The complexity of the procedure applied for extracting the model parameters depends on data available in manufacture’s datasheet. Since the datasheet is not detailed enough, simplified models have to be used in many cases. This paper proposes a new procedure for extracting the parameters of the one-diode model in standard test conditions, using only the basic data listed by all manufactures in datasheet (short circuit current, open circuit voltage and maximum power point). The procedure is validated by using manufacturers’ data for six commercially crystalline silicon photovoltaic modules. Comparing the computed and measured current–voltage characteristics the determination coefficient is in the range 0.976–0.998. Thus, the proposed procedure represents a feasible tool for solving the five-parameter model applied to crystalline silicon photovoltaic modules. The procedure is described in detail, to guide potential users to derive similar models for other types of photovoltaic modules.

Development of Health Parameter Model for Risk Prediction of CVD Using SVM

Directory of Open Access Journals (Sweden)

P. Unnikrishnan

2016-01-01

Full Text Available Current methods of cardiovascular risk assessment are performed using health factors which are often based on the Framingham study. However, these methods have significant limitations due to their poor sensitivity and specificity. We have compared the parameters from the Framingham equation with linear regression analysis to establish the effect of training of the model for the local database. Support vector machine was used to determine the effectiveness of machine learning approach with the Framingham health parameters for risk assessment of cardiovascular disease (CVD. The result shows that while linear model trained using local database was an improvement on Framingham model, SVM based risk assessment model had high sensitivity and specificity of prediction of CVD. This indicates that using the health parameters identified using Framingham study, machine learning approach overcomes the low sensitivity and specificity of Framingham model.

Modal parameter determination of a lightweight aerospace panel using laser Doppler vibrometer measurements

Science.gov (United States)

de Sousa, Kleverson C.; Domingues, Allan C.; Pereira, Pedro P. de S.; Carneiro, Sergio H.; de Morais, Marcus V. G.; Fabro, Adriano T.

2016-06-01

The experimental determination of modal parameters, i.e. natural frequencies, mode shapes and damping ratio, are key in characterizing the dynamic behaviour of structures. Typically, such parameters are obtained from dynamic measurements using one or a set of accelerometers, for response measurements, along with force transducers from an impact hammer or an electrodynamic actuator, i.e. a shaker. However, lightweight structures, commonly applied in the aerospace industry, can be significantly affected by the added mass from accelerometers. Therefore, non-contact measurement techniques, like Laser Doppler Vibrometer (LDV), are a more suitable approach in determining the dynamic characteristics of such structures. In this article, the procedures and results of a modal test for a honeycomb sandwich panel for aerospace applications are presented and discussed. The main objectives of the test are the identification of natural frequencies and mode shapes in order to validate a numerical model, as well as the identification of the damping characteristics of the panel. A validated numerical model will be necessary for future detailed response analysis of the satellite, including vibroacoustic investigations to account for acoustic excitations encountered during launching. The numerical model using homogenised material properties is updated to fit the experimental results and very good agreement between experimental and numerically obtained natural frequencies and mode shapes.

Determination of thermodynamic parameters of Cr(VI) adsorption from aqueous solution onto Agave lechuguilla biomass

Energy Technology Data Exchange (ETDEWEB)

Romero-Gonzalez, J. [Environmental Science and Engineering, University of Texas at El Paso, El Paso, TX 79968 (United States); Peralta-Videa, J.R. [Department of Chemistry, University of Texas at El Paso, El Paso, TX 79968 (United States); Rodriguez, E. [Environmental Science and Engineering, University of Texas at El Paso, El Paso, TX 79968 (United States); Ramirez, S.L. [Department of Chemistry, University of Texas at El Paso, El Paso, TX 79968 (United States); Gardea-Torresdey, J.L. [Environmental Science and Engineering, University of Texas at El Paso, El Paso, TX 79968 (United States) and Department of Chemistry, University of Texas at El Paso, El Paso, TX 79968 (United States)]. E-mail: jgardea@utep.edu

2005-04-15

The temperature dependence of the Cr(VI) bioadsorption and its possible reduction to Cr(III) by Agave lechuguilla biomass were studied. The experimental data obtained in batch experiments at different temperatures were fitted to the Langmuir and Freundlich isotherms to obtain the characteristic parameters of each model. The adsorption equilibrium data fitted well with the Freundlich model. The average model parameters calculated from Freundlich's isotherms (adsorption capacity K{sub F} = 4 . 10{sup -2} mol . g{sup -1} and an average adsorption intensity value n = 13.07) showed that A. lechuguilla can be considered as an effective biomaterial for Cr(VI) removal from aqueous solution. Thermodynamic parameters ({delta}G{sup .}, {delta}H{sup .}, and {delta}S{sup .}) for Cr(VI) adsorption determined in the temperature range from (283 to 313) K suggest that a portion of Cr(VI) may be bound to functional groups on the surface of the adsorbent and then reduced to Cr(III). Additionally, the parameters of the Dubinin-Radushkevick equation indicated that the sorption of chromium species onto lechuguilla biomass mainly proceeds through binding surface functional groups.

On 4-degree-of-freedom biodynamic models of seated occupants: Lumped-parameter modeling

Science.gov (United States)

Bai, Xian-Xu; Xu, Shi-Xu; Cheng, Wei; Qian, Li-Jun

2017-08-01

It is useful to develop an effective biodynamic model of seated human occupants to help understand the human vibration exposure to transportation vehicle vibrations and to help design and improve the anti-vibration devices and/or test dummies. This study proposed and demonstrated a methodology for systematically identifying the best configuration or structure of a 4-degree-of-freedom (4DOF) human vibration model and for its parameter identification. First, an equivalent simplification expression for the models was made. Second, all of the possible 23 structural configurations of the models were identified. Third, each of them was calibrated using the frequency response functions recommended in a biodynamic standard. An improved version of non-dominated sorting genetic algorithm (NSGA-II) based on Pareto optimization principle was used to determine the model parameters. Finally, a model evaluation criterion proposed in this study was used to assess the models and to identify the best one, which was based on both the goodness of curve fits and comprehensive goodness of the fits. The identified top configurations were better than those reported in the literature. This methodology may also be extended and used to develop the models with other DOFs.

The sensitivity of flowline models of tidewater glaciers to parameter uncertainty

Directory of Open Access Journals (Sweden)

E. M. Enderlin

2013-10-01

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

Determination of the temperature coefficients and the kinetic parameters for the HTTR safety analysis

International Nuclear Information System (INIS)

Tokuhara, K.; Nakata, T.; Murata, I.; Yamashita, K.; Shindo, R.

1991-01-01

This report describes the calculational methods which were employed to determine the temperature coefficients and the kinetic parameters for the safety analysis in the HTTR (High Temperature Engineering Test Reactor). The temperature coefficients (doppler, moderator temperature) and the kinetic parameters (prompt neutron life time; l, effective delayed neutron fraction; β eff) are important for the point model core dynamic analysis and should be evaluated properly. The temperature coefficients were calculated by the whole core model. Doppler coefficient was evaluated under the conditions of all control rods withdrawn and the uniform change of fuel temperature. The minimum and the maximum value of the evaluated doppler coefficients in a burnup cycle are -4.6x10 -5 and -1.5x10 -5 ΔK/K/deg. C respectively. The moderator temperature coefficient was evaluated under the conditions of all control rods withdrawn and the uniform change of moderator temperature. The minimum and the maximum value of the evaluated moderator temperature coefficients in a burnup cycle are -17.1x10 -5 and 0.99x10 -5 ΔK/K/deg. C respectively. In spite of positive moderator temperature coefficient, the power coefficient is always negative. Therefore the HTTR possesses inherent power-suppressing feed back characteristic in all operating condition. We surveyed the effects of the Xe existence, the control rods existence, the fuel temperature and the region in which the temperature was changed on the moderator temperature coefficients. The kinetic parameters were calculated by the perturbation method with the whole core model. The minimum and the maximum value of the evaluated effective delayed neutron fraction (β eff) are 0.0047 and 0.0065 respectively. These of the evaluated prompt neutron life time (l) are 0.67 and 0.78 ms respectively. We have surveyed the effects of the fuel depletion and the core power level on these parameters, and considered these effects on the kinetic parameters. From

Study on Developing Degradation Model for Nuclear Power Plants With Ageing Elements Affected on Operation Parameter

International Nuclear Information System (INIS)

Choi, Yong Won; Lim, Sung Won; Lee, Un Chul; Kim, Man Woong; Kim, Kab; Ryu, Yong Ho

2009-01-01

As a part of development the evaluation system of safety margin effects for degradation of CANDU reactors, it is required that the degradation model represents the distribution of each ageing factor's value during operating year. Unfortunately, it is not easy to make an explicit relation between the RELAP-CANDU parameters and ageing mechanism because of insufficient data and lack of applicable models. So, operating parameter related with ageing is used for range determination of ageing factor. Then, relation between operating parameter and ageing elements is analyzed and ageing constant values for degradation model are determined. Also the other ageing factor is derived for more accurate ageing analysis

Application of mathematical modelling when determining the parameters effect of biomass densification process on solid biofuels quality

Directory of Open Access Journals (Sweden)

Križan Peter

2018-01-01

Full Text Available The main aim of this paper is to present the design of experiment (DOE and evaluation methodology for this experimental plan in order to determine the parameters effect of biomass densification process on final solid biofuels quality. One of the recovery possibilities for waste biomass raw materials is production of solid biofuels. Using a variety combination of influencing variables can be improve the final quality of solid biofuels. Raw biomass material variables influence, especially (type of raw material, particle size, moisture content, compression pressure and compression temperature can be recognized during the production of solid biofuels. Their effect can be seen through the quality indicators; especially mentioned variables significantly influence the mechanical quality indicators of solid biofuels. In this experimental research authors would like to investigate properties and behaviour of wood raw waste biomass during densification. This contribution discusses the analysis and design of experimental process, its individual steps and their subsequent DOE leading to the development of a mathematical model that will describe this process. This paper also presents the research findings regarding the effect of influencing variables on final density of solid biofuels during densification. Aim of the experimental process is to determine the mutual interaction between solid biofuels density and influencing variables during densification. Effect of compression pressure, compression temperature, moisture content and particle size on solid biofuels density from wood sawdust was determined.

The influence of model parameters on catchment-response

International Nuclear Information System (INIS)

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

2002-01-01

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

Intelligent methods for the process parameter determination of plastic injection molding

Science.gov (United States)

Gao, Huang; Zhang, Yun; Zhou, Xundao; Li, Dequn

2018-03-01

Injection molding is one of the most widely used material processing methods in producing plastic products with complex geometries and high precision. The determination of process parameters is important in obtaining qualified products and maintaining product quality. This article reviews the recent studies and developments of the intelligent methods applied in the process parameter determination of injection molding. These intelligent methods are classified into three categories: Case-based reasoning methods, expert system- based methods, and data fitting and optimization methods. A framework of process parameter determination is proposed after comprehensive discussions. Finally, the conclusions and future research topics are discussed.

Determination of electromagnetic absorption parameters by reflection measurements

International Nuclear Information System (INIS)

Vittitoe, C.N.

1975-09-01

The method described is for determining the electromagnetic absorption parameters of a material by measuring the optical reflection from a thick sample. With linearly polarized incident light (both perpendicular to and parallel to the plane of incidence), the ratio of the reflected intensities at three or more angles of incidence offers promise for determining the complex index of refraction of a material for a broad range of parameter values. The method may be applicable to molten materials, such as UO 2 , where high temperatures cause corrosion and containment difficulties. A method is given for extending the data to neighboring frequencies. Use of the method was successful for all portions of the complex index of refraction plane except for small values of the extinction coefficient

On parameter estimation in deformable models

DEFF Research Database (Denmark)

Fisker, Rune; Carstensen, Jens Michael

1998-01-01

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

SPOTting model parameters using a ready-made Python package

Science.gov (United States)

Houska, Tobias; Kraft, Philipp; Breuer, Lutz

2015-04-01

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

Set-base dynamical parameter estimation and model invalidation for biochemical reaction networks.

Science.gov (United States)

Rumschinski, Philipp; Borchers, Steffen; Bosio, Sandro; Weismantel, Robert; Findeisen, Rolf

2010-05-25

Mathematical modeling and analysis have become, for the study of biological and cellular processes, an important complement to experimental research. However, the structural and quantitative knowledge available for such processes is frequently limited, and measurements are often subject to inherent and possibly large uncertainties. This results in competing model hypotheses, whose kinetic parameters may not be experimentally determinable. Discriminating among these alternatives and estimating their kinetic parameters is crucial to improve the understanding of the considered process, and to benefit from the analytical tools at hand. In this work we present a set-based framework that allows to discriminate between competing model hypotheses and to provide guaranteed outer estimates on the model parameters that are consistent with the (possibly sparse and uncertain) experimental measurements. This is obtained by means of exact proofs of model invalidity that exploit the polynomial/rational structure of biochemical reaction networks, and by making use of an efficient strategy to balance solution accuracy and computational effort. The practicability of our approach is illustrated with two case studies. The first study shows that our approach allows to conclusively rule out wrong model hypotheses. The second study focuses on parameter estimation, and shows that the proposed method allows to evaluate the global influence of measurement sparsity, uncertainty, and prior knowledge on the parameter estimates. This can help in designing further experiments leading to improved parameter estimates.

Using a scalar parameter to trace dislocation evolution in atomistic modeling

Energy Technology Data Exchange (ETDEWEB)

Yang, Jinbo [ORNL; Zhang, Z F [Shenyang National Laboratory for Materials Science; Osetskiy, Yury N [ORNL; Stoller, Roger E [ORNL

2015-01-01

A scalar gamma-parameter is proposed from the Nye tensor. Its maximum value occurs along a dislocation line, either straight or curved, when the coordinate system is purposely chosen. This parameter can be easily obtained from the Nye tensor calculated at each atom in atomistic modeling. Using the gamma-parameter, a fully automated approach is developed to determine core atoms and the Burgers vectors of dislocations simultaneously. The approach is validated by revealing the smallest dislocation loop and by tracing the whole formation process of complicated dislocation networks on the fly.

Simultaneous determination of six quality parameters of biodiesel through 1H NMR spectroscopy and partial least squares.

Science.gov (United States)

Shimamoto, Gustavo G; Tubino, Matthieu

2018-03-01

Biodiesel quality is checked by determining several parameters. Considering the large number of analyses in this verification, as well as the disadvantages of the use of toxic solvents and waste generation, multivariate calibration is suggested to reduce the number of tests. In this work, hydrogen nuclear magnetic resonance ( 1 H NMR) spectra were used to build multivariate models, from partial least squares (PLS), in order to perform simultaneous determination of six important quality parameters of biodiesel: density at 20°C, kinematic viscosity at 40°C, iodine value, acid number, oxidative stability, and water content. 1 H NMR spectrum reflects the structures of the compounds present in biodiesel and showed suitable correlations with the six parameters. In addition, the models were appropriate to predict all parameters for external samples. Thus, the alliance between 1 H NMR spectra and PLS was shown to be applicable to extract a lot of information about biodiesel quality, significantly reducing analysis time, reagent and solvent consumption, and waste generation. Copyright © 2017 Elsevier B.V. All rights reserved.

A Study on the Pyrolysis of Peanut Shells at Different Isothermal Conditions and Determination of the Kinetic Parameters

Directory of Open Access Journals (Sweden)

Şeyda Taşar

2015-12-01

Full Text Available The pyrolysis process, which is applied for the aim of producing energy and raw materials which are implemented for the chemical industry from biomass sources, is a thermal conversion process. Determination of the pyrolysis kinetic parameters are important In order to suitable equipment and process design. In this target, in the study the pyrolysis of peanut shells was conducted in a muffle furnace at static atmosphere with temperatures ranging from 300-700 °C. The effects of various parameters on the rate of thermal decomposition rate and the solid yield were determined. The parameters of interest were temperature 300-700 °C, particle size 4-50 mesh, pelletizing, and pelletizing pressure 1.103-5.103 kgf/cm2. Regression coefficients for the total decomposition step were obtained using the thermographs were obtained as a result of the pyrolysis of the peanut shells, and 20 different theoretical model equations that represented the degradation by the Coast-Redfern method. According to regression coefficients of the theoretical model equations, we determined the kinetic model that best represented the degradation. Using this model to represent the degradation, the activation energy (Ea and Arhenius frequency factor ln(A for the total reaction were calculated to be 38.245 kJ/mol and 8.124, respectively.

Determination of Eros Physical Parameters for Near Earth Asteroid Rendezvous Orbit Phase Navigation

Science.gov (United States)

Miller, J. K.; Antreasian, P. J.; Georgini, J.; Owen, W. M.; Williams, B. G.; Yeomans, D. K.

1995-01-01

Navigation of the orbit phase of the Near Earth steroid Rendezvous (NEAR) mission will re,quire determination of certain physical parameters describing the size, shape, gravity field, attitude and inertial properties of Eros. Prior to launch, little was known about Eros except for its orbit which could be determined with high precision from ground based telescope observations. Radar bounce and light curve data provided a rough estimate of Eros shape and a fairly good estimate of the pole, prime meridian and spin rate. However, the determination of the NEAR spacecraft orbit requires a high precision model of Eros's physical parameters and the ground based data provides only marginal a priori information. Eros is the principal source of perturbations of the spacecraft's trajectory and the principal source of data for determining the orbit. The initial orbit determination strategy is therefore concerned with developing a precise model of Eros. The original plan for Eros orbital operations was to execute a series of rendezvous burns beginning on December 20,1998 and insert into a close Eros orbit in January 1999. As a result of an unplanned termination of the rendezvous burn on December 20, 1998, the NEAR spacecraft continued on its high velocity approach trajectory and passed within 3900 km of Eros on December 23, 1998. The planned rendezvous burn was delayed until January 3, 1999 which resulted in the spacecraft being placed on a trajectory that slowly returns to Eros with a subsequent delay of close Eros orbital operations until February 2001. The flyby of Eros provided a brief glimpse and allowed for a crude estimate of the pole, prime meridian and mass of Eros. More importantly for navigation, orbit determination software was executed in the landmark tracking mode to determine the spacecraft orbit and a preliminary shape and landmark data base has been obtained. The flyby also provided an opportunity to test orbit determination operational procedures that will be

Complexity, parameter sensitivity and parameter transferability in the modelling of floodplain inundation

Science.gov (United States)

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

2012-12-01

In this we paper we consider two related questions. First, we address the issue of how much physical complexity is necessary in a model in order to simulate floodplain inundation to within validation data error. This is achieved through development of a single code/multiple physics hydraulic model (LISFLOOD-FP) where different degrees of complexity can be switched on or off. Different configurations of this code are applied to four benchmark test cases, and compared to the results of a number of industry standard models. Second we address the issue of how parameter sensitivity and transferability change with increasing complexity using numerical experiments with models of different physical and geometric intricacy. Hydraulic models are a good example system with which to address such generic modelling questions as: (1) they have a strong physical basis; (2) there is only one set of equations to solve; (3) they require only topography and boundary conditions as input data; and (4) they typically require only a single free parameter, namely boundary friction. In terms of complexity required we show that for the problem of sub-critical floodplain inundation a number of codes of different dimensionality and resolution can be found to fit uncertain model validation data equally well, and that in this situation Occam's razor emerges as a useful logic to guide model selection. We find also find that model skill usually improves more rapidly with increases in model spatial resolution than increases in physical complexity, and that standard approaches to testing hydraulic models against laboratory data or analytical solutions may fail to identify this important fact. Lastly, we find that in benchmark testing studies significant differences can exist between codes with identical numerical solution techniques as a result of auxiliary choices regarding the specifics of model implementation that are frequently unreported by code developers. As a consequence, making sound

Application of a free parameter model to plastic scintillation samples

Energy Technology Data Exchange (ETDEWEB)

Tarancon Sanz, Alex, E-mail: alex.tarancon@ub.edu [Departament de Quimica Analitica, Universitat de Barcelona, Diagonal 647, E-08028 Barcelona (Spain); Kossert, Karsten, E-mail: Karsten.Kossert@ptb.de [Physikalisch-Technische Bundesanstalt (PTB), Bundesallee 100, 38116 Braunschweig (Germany)

2011-08-21

In liquid scintillation (LS) counting, the CIEMAT/NIST efficiency tracing method and the triple-to-double coincidence ratio (TDCR) method have proved their worth for reliable activity measurements of a number of radionuclides. In this paper, an extended approach to apply a free-parameter model to samples containing a mixture of solid plastic scintillation microspheres and radioactive aqueous solutions is presented. Several beta-emitting radionuclides were measured in a TDCR system at PTB. For the application of the free parameter model, the energy loss in the aqueous phase must be taken into account, since this portion of the particle energy does not contribute to the creation of scintillation light. The energy deposit in the aqueous phase is determined by means of Monte Carlo calculations applying the PENELOPE software package. To this end, great efforts were made to model the geometry of the samples. Finally, a new geometry parameter was defined, which was determined by means of a tracer radionuclide with known activity. This makes the analysis of experimental TDCR data of other radionuclides possible. The deviations between the determined activity concentrations and reference values were found to be lower than 3%. The outcome of this research work is also important for a better understanding of liquid scintillation counting. In particular the influence of (inverse) micelles, i.e. the aqueous spaces embedded in the organic scintillation cocktail, can be investigated. The new approach makes clear that it is important to take the energy loss in the aqueous phase into account. In particular for radionuclides emitting low-energy electrons (e.g. M-Auger electrons from {sup 125}I), this effect can be very important.

PLS-NIR determination of five parameters in different types of Chinese rice wine

Science.gov (United States)

Yu, Haiyan; Ying, Yibin; Fu, Xiaping; Lu, Huishan

2005-11-01

To evaluate the applicability of near infrared spectroscopy for determination of the five enological parameters (alcoholic degree, pH value, total acid and amino acid nitrogen, °Brix) of Chinese rice wine, transmission spectra were collected in the spectral range from 12500 to 3800 cm-1 in a 1 mm path length rectangular quartz cuvette with air as reference at room temperature. Five calibration equations for the five parameters were established between the reference data and spectra by partial least squares (PLS) regression, separately. The best calibration results were achieved for the determination of alcoholic degree and °Brix. The RPD (ration of the standard deviation of the samples to the SECV) values of the calibration for both alcoholic degree and °Brix were higher than 3 (4.30 and 7.94, respectively), which demonstrated the robustness and power of the calibration models. The determination coefficients (R2) for alcoholic degree and °Brix were 0.987 and 0.991, respectively. The performance of pH, total acid and amino acid nitrogen was not as good as that of alcoholic degree and °Brix. The RPD values for the three parameters were 1.48, 1.85 and 1.82, respectively, and R2 values were 0.964, 0.970 and 0.971, respectively. In validation step, R2 value of the five parameters are all higher than 0.7, especially for alcoholic degree and °Brix (0.968 and 0.956, respectively). The results demonstrated that NIR spectroscopy could be used to predict the concentration of the five enological parameters in Chinese rice wine.

Fast determination of plasma parameters

International Nuclear Information System (INIS)

Wijnands, T.J.; Parlange, F.; Joffrin, E.

1995-01-01

Fast analysis of diagnostic signals of a tokamak discharge is demonstrated by using 4 fundamentally different techniques. A comparison between Function Parametrization (FP), Canonical Correlation Analysis (CCA) and a particular Neural Network (NN) configuration known as the Multi Layer Perceptron (MLP) is carried out, thereby taking a unique linear model based on a Singular Value Decomposition (SVD) as a reference. The various techniques provide all functional representations of characteristic plasma parameters in terms of the values of the measurements and are based on an analysis of a large, experimentally achieved database. A brief mathematical description of the various techniques is given, followed by two particular applications to Tore Supra diagnostic data. The first problem is concerned with the identification of the plasma boundary parameters using the poloidal field and differential poloidal flux measurements. A second application involves the interpretation of line integrated data from the multichannel interfero-polarimeter to obtain the central value of the safety factor. (author) 4 refs.; 3 figs

Data-driven techniques to estimate parameters in a rate-dependent ferromagnetic hysteresis model

International Nuclear Information System (INIS)

Hu Zhengzheng; Smith, Ralph C.; Ernstberger, Jon M.

2012-01-01

The quantification of rate-dependent ferromagnetic hysteresis is important in a range of applications including high speed milling using Terfenol-D actuators. There exist a variety of frameworks for characterizing rate-dependent hysteresis including the magnetic model in Ref. , the homogenized energy framework, Preisach formulations that accommodate after-effects, and Prandtl-Ishlinskii models. A critical issue when using any of these models to characterize physical devices concerns the efficient estimation of model parameters through least squares data fits. A crux of this issue is the determination of initial parameter estimates based on easily measured attributes of the data. In this paper, we present data-driven techniques to efficiently and robustly estimate parameters in the homogenized energy model. This framework was chosen due to its physical basis and its applicability to ferroelectric, ferromagnetic and ferroelastic materials.

Parameter estimation of variable-parameter nonlinear Muskingum model using excel solver

Science.gov (United States)

Kang, Ling; Zhou, Liwei

2018-02-01

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

Parameter sensitivity analysis of a 1-D cold region lake model for land-surface schemes

Science.gov (United States)

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

2017-12-01

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

Parameter identification and model validation for the piezoelectric actuator in an inertia motor

International Nuclear Information System (INIS)

Hunstig, Matthias; Hemsel, Tobias

2010-01-01

Piezoelectric inertia motors make use of the inertia of a slider to drive the slider by friction contact in a series of small steps which are generally composed of a stick phase and a slip phase. If the best electrical drive signal for the piezoelectric actuator in an inertia motor is to be determined, its dynamical behaviour must be known. A classic dynamic lumped parameter model for piezoelectric actuators is valid only in resonance and, therefore, is not suitable for modelling the actuator in an inertia motor. A reduced dynamic model is used instead. Its parameters are identified using a step response measurement. This model is used to predict the movement of the actuator in response to a velocity-optimized signal introduced in a separate contribution. Results show that the model cannot represent the dynamical characteristics of the actuator completely. For determining voltage signals that let piezoelectric actuators follow a calculated movement pattern exactly, the model can, therefore, only be used with limitations.

Key radionuclides and parameters that determine performance of geologic repositories for high-level radioactive wastes

International Nuclear Information System (INIS)

Joonhong Ahn; Atsuyuki Suzuki

1993-01-01

This paper presents results of a mathematical analysis for performance of the engineered barriers of high-level radioactive waste repositories. The main body of the mathematical model developed in this study is mass transport of actinides in a bentonite region. In an analysis of actinide transport, radioactive decay chain and effects of low solubilities must be taken into account. In many previous models for mass transport in engineered barriers including radioactive decay chain, however, boundary conditions at the interface between the waste form and the bentonite region cannot be determined flexibly. In some models, solubility-limited boundary condition is assumed for all the members in a chain. In order to investigate what are key radionuclides and parameters that control performance of engineered barriers of a geologic repository, we must evaluate mass transport with the source boundary condition determined by a detailed analysis on mass transfer at the boundary. In this study, we developed a mathematical model, which can determine whether the inner boundary condition is solubility-limited or congruent release, based on a mathematical analysis for mass transfer at the glass dissolution location, and how long the solubility-limited boundary condition applies. Based on the mathematical model, we point out radionuclides and parameters that have primary influences on the performance of a repository, and investigate a reasonable strategy for coupling geologic disposal and partitioning of those key radionuclides from the standpoint of reducing hazard of geologic disposal. (authors). 4 tabs., 2 figs., 8 refs

Evaluation of some infiltration models and hydraulic parameters

International Nuclear Information System (INIS)

Haghighi, F.; Gorji, M.; Shorafa, M.; Sarmadian, F.; Mohammadi, M. H.

2010-01-01

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.

Effect of Uncertainty Parameters in Blowdown and Reflood Models for OPR1000 LBLOCA Analysis

Energy Technology Data Exchange (ETDEWEB)

Huh, Byung Gil; Jin, Chang Yong; Seul, Kwangwon; Hwang, Taesuk [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)

2014-05-15

KINS(Korea Institute of Nuclear Safety) has also performed the audit calculation with the KINS Realistic Evaluation Methodology(KINS-REM) to confirm the validity of licensee's calculation. In the BEPU method, it is very important to quantify the code and model uncertainty. It is referred in the following requirement: BE calculations in Regulatory Guide 1.157 - 'the code and models used are acceptable and applicable to the specific facility over the intended operating range and must quantify the uncertainty in the specific application'. In general, the uncertainty of model/code should be obtained through the data comparison with relevant integral- and separate-effect tests at different scales. However, it is not easy to determine these kinds of uncertainty because of the difficulty for evaluating accurately various experiments. Therefore, the expert judgment has been used in many cases even with the limitation that the uncertainty range of important parameters can be wide and inaccurate. In the KINS-REM, six heat transfer parameters in the blowdown phase have been used to consider the uncertainty of models. Recently, MARS-KS code was modified to consider the uncertainty of the five heat transfer parameters in the reflood phase. Accordingly, it is required that the uncertainty range for parameters of reflood models is determined and the effect of these ranges is evaluated. In this study, the large break LOCA (LBLOCA) analysis for OPR1000 was performed to identify the effect of uncertainty parameters in blowdown and reflood models.

Determination of reactor parameters by single rod experiments

Energy Technology Data Exchange (ETDEWEB)

Raisic, N; Zdravkovic, Z; Ivkovic, M [Department of Reactor Physics and Dynamics, Boris Kidric Institute of Nuclear Sciences, Vinca, Belgrade (Yugoslavia)

1969-07-01

A method is developed for the experimental determination of reactor parameters by using an isolated fuel element. The method is based on the consideration of the fuel element as the source and sink of neutrons when placed in a constant neutron field. By measuring the perturbation of the original field produced by insertion of the test fuel element it was possible to determine the fuel element parameters defined by the heterogeneous reactor theory of Feinberg and Galanin as thermal neutron absorption constant {gamma}, and neutron multiplication constant {eta}. Statistical error for one series of measurement amount to 2% in the values of {eta} and {gamma}. The developed method was intended for the analysis of the nuclear characteristics of the fuel element in the stage of its construction and development for a given reactor system. (author)

Fast determination of plasma parameters through function parametrization

International Nuclear Information System (INIS)

Braams, B.J.; Jilge, W.; Lackner, K.

1985-09-01

The method of function parametrization, developed by H. Wind for fast data evaluation in high energy physics, is demonstrated in the context of controlled fusion research. This method relies on a statistical analysis of a large data base of simulated experiments in order to obtain a functional representation for intrinsic physical parameters of a system in terms of the values of the measurements. Rapid determination of characteristic equilibrium parameters of a tokamak discharge is shown to be a particularly indicated application. The method is employed on the ASDEX experiment to determine the following parameters of the plasma: position of the magnetic axis, geometric center, and current center; minor radius, elongation, and area of the plasma column; a normalized safety factor at the plasma boundary; the Shafranov parameter βsub(p)+lsub(i)/2; the flux difference between the plasma boundary and an external reference value; the position of the lower and upper saddle points, and the intersections of the separatrix with the four divertor plates. The relevant measurements consist of three differential poloidal flux measurements, four poloidal field measurements, the current through the multipole shaping coils, and the total plasma current. Function parametrization supplies a very accurate interpretation of these data, which is now used for online data analysis, and is also sufficiently fast to be suitable for real-time control of the plasma. (orig.)

Determining Mechanical Parameters for Spin in Tennis Strings

DEFF Research Database (Denmark)

Bendtsen, Kaare; Rasmussen, Kasper; Hansen, Martin B.

2015-01-01

The ability to generate spin is a key element for any tennis player. However, the mechanical parameters of tennis strings which contribute to producing spin are poorly understood. This study attempted to determine some of these parameters through a spin test and a tensile test. Nine different...... string types with different gauges, geometry, price and user ratings were tested. The main finding of the study was that the three gauges of MSV Co Focus were able to generate significantly (p

Model Parameter Variability for Enhanced Anaerobic Bioremediation of DNAPL Source Zones

Science.gov (United States)

Mao, X.; Gerhard, J. I.; Barry, D. A.

2005-12-01

The objective of the Source Area Bioremediation (SABRE) project, an international collaboration of twelve companies, two government agencies and three research institutions, is to evaluate the performance of enhanced anaerobic bioremediation for the treatment of chlorinated ethene source areas containing dense, non-aqueous phase liquids (DNAPL). This 4-year, 5.7 million dollars research effort focuses on a pilot-scale demonstration of enhanced bioremediation at a trichloroethene (TCE) DNAPL field site in the United Kingdom, and includes a significant program of laboratory and modelling studies. Prior to field implementation, a large-scale, multi-laboratory microcosm study was performed to determine the optimal system properties to support dehalogenation of TCE in site soil and groundwater. This statistically-based suite of experiments measured the influence of key variables (electron donor, nutrient addition, bioaugmentation, TCE concentration and sulphate concentration) in promoting the reductive dechlorination of TCE to ethene. As well, a comprehensive biogeochemical numerical model was developed for simulating the anaerobic dehalogenation of chlorinated ethenes. An appropriate (reduced) version of this model was combined with a parameter estimation method based on fitting of the experimental results. Each of over 150 individual microcosm calibrations involved matching predicted and observed time-varying concentrations of all chlorinated compounds. This study focuses on an analysis of this suite of fitted model parameter values. This includes determining the statistical correlation between parameters typically employed in standard Michaelis-Menten type rate descriptions (e.g., maximum dechlorination rates, half-saturation constants) and the key experimental variables. The analysis provides insight into the degree to which aqueous phase TCE and cis-DCE inhibit dechlorination of less-chlorinated compounds. Overall, this work provides a database of the numerical

The Use of Asymptotic Functions for Determining Empirical Values of CN Parameter in Selected Catchments of Variable Land Cover

Directory of Open Access Journals (Sweden)

Wałęga Andrzej

2017-12-01

Full Text Available The aim of the study was to assess the applicability of asymptotic functions for determining the value of CN parameter as a function of precipitation depth in mountain and upland catchments. The analyses were carried out in two catchments: the Rudawa, left tributary of the Vistula, and the Kamienica, right tributary of the Dunajec. The input material included data on precipitation and flows for a multi-year period 1980–2012, obtained from IMGW PIB in Warsaw. Two models were used to determine empirical values of CNobs parameter as a function of precipitation depth: standard Hawkins model and 2-CN model allowing for a heterogeneous nature of a catchment area.

Universally sloppy parameter sensitivities in systems biology models.

Directory of Open Access Journals (Sweden)

Ryan N Gutenkunst

2007-10-01

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

Universally sloppy parameter sensitivities in systems biology models.

Science.gov (United States)

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

2007-10-01

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

Determination of rock fracture parameters from crack models for failure in compression

International Nuclear Information System (INIS)

Kemeny, J.M.; Cook, N.G.W.

1987-01-01

Micromechanical models for axial splitting and for shear faulting are used to investigate parameters associated with rock fracture under compressive stresses. The fracture energies to create splitting fractures and shear faults are calculated using laboratory triaxial data. These energies are compared with the fracture energies for the propagation of microcracks that coalesce to form the larger scale fractures. It is found that for Westerly granite, the energies to create splitting fractures and shear faults are about three orders of magnitude greater than the energy needed to drive the tensile microcracks, due to the large amount of subsidiary crack surface area created in forming the larger scale fractures. A similar scale effect can be expected when extrapolating the laboratory results to field scale problems

Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models.

Directory of Open Access Journals (Sweden)

Jonathan R Karr

2015-05-01

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

Kinetic parameter estimation model for anaerobic co-digestion of waste activated sludge and microalgae.

Science.gov (United States)

Lee, Eunyoung; Cumberbatch, Jewel; Wang, Meng; Zhang, Qiong

2017-03-01

Anaerobic co-digestion has a potential to improve biogas production, but limited kinetic information is available for co-digestion. This study introduced regression-based models to estimate the kinetic parameters for the co-digestion of microalgae and Waste Activated Sludge (WAS). The models were developed using the ratios of co-substrates and the kinetic parameters for the single substrate as indicators. The models were applied to the modified first-order kinetics and Monod model to determine the rate of hydrolysis and methanogenesis for the co-digestion. The results showed that the model using a hyperbola function was better for the estimation of the first-order kinetic coefficients, while the model using inverse tangent function closely estimated the Monod kinetic parameters. The models can be used for estimating kinetic parameters for not only microalgae-WAS co-digestion but also other substrates' co-digestion such as microalgae-swine manure and WAS-aquatic plants. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effect of Process Parameters on Friction Model in Computer Simulation of Linear Friction Welding

Directory of Open Access Journals (Sweden)

A. Yamileva

2014-07-01

Full Text Available The friction model is important part of a numerical model of linear friction welding. Its selection determines the accuracy of the results. Existing models employ the classical law of Amonton-Coulomb where the friction coefficient is either constant or linearly dependent on a single parameter. Determination of the coefficient of friction is a time consuming process that requires a lot of experiments. So the feasibility of determinating the complex dependence should be assessing by analysis of effect of approximating law for friction model on simulation results.

A new approach to determine geomechanical parameters of Vertical Transverse Isotropic media using VSP data

Science.gov (United States)

Gholami, Raoof; Moradzadeh, Ali; Rasouli, Vamegh; Hanachi, Javid

2014-12-01

Conventionally, high frequency Dipole Shear sonic Imager (DSI) logs are used for anisotropic modeling where fast and slow shear wave's velocities are required. However, the results obtained from a DSI log are restricted to a specific and possibly short interval of the wellbore. The aims of this paper are to use Vertical Seismic Profile (VSP) data and show its application in geomechanical analysis of subsurface layers under anisotropic condition. After processing and separating upgoing and downgoing P- and S-waves, a methodology based Vertical Transverse Isotropic (VTI) condition was presented to determine elastic stiffness parameters. Having stiffness parameters determined, elastic modulus, strength and in-situ stress parameters were estimated and calibrated against the field and core sample data. Although the VSP based geomechanical parameters were calibrated against the real field data, the accuracy of the method cannot be as much as that of the well logs. However, the method presented in this paper may become a very good asset for geomechanical evaluation of the intervals where well log data are not available.

Inferring the temperature dependence of Beremin cleavage model parameters from the Master Curve

International Nuclear Information System (INIS)

Cao Yupeng; Hui Hu; Wang Guozhen; Xuan Fuzhen

2011-01-01

Research highlights: → Temperature dependence of Beremin model parameters is inferred by Master Curve approach. → Weibull modulus decreases while Weibull stress scale parameter increases with increasing the temperature. → Estimation of Weibull stress parameters in terms of small amounts of specimens leads to a considerable uncertainty. - Abstract: The temperature dependence of Beremin model parameters in the ductile-to-brittle transition region was addressed by employing the Master Curve. Monte Carlo simulation was performed to produce a large number of 1T fracture toughness data randomly drawn from the scatter band at a temperature of interest and thus to determine Beremin model parameters. In terms of the experimental data of a C-Mn steel (the 16MnR steel in China), results revealed that the Weibull modulus, m, decreases with temperature over the lower transition range and remains a constant in the lower-to-mid transition region. The Weibull scale parameter, σ u , increases with temperature over the temperature range of investigated. A small sample may lead to a considerable uncertainty in estimates of the Weibull stress parameters. However, no significant difference was observed for the average of Weibull stress parameters from different sample sizes.

A sensitivity analysis of a personalized pulse wave propagation model for arteriovenous fistula surgery. Part A: Identification of most influential model parameters.

Science.gov (United States)

Huberts, W; de Jonge, C; van der Linden, W P M; Inda, M A; Tordoir, J H M; van de Vosse, F N; Bosboom, E M H

2013-06-01

Previously, a pulse wave propagation model was developed that has potential in supporting decision-making in arteriovenous fistula (AVF) surgery for hemodialysis. To adapt the wave propagation model to personalized conditions, patient-specific input parameters should be available. In clinics, the number of measurable input parameters is limited which results in sparse datasets. In addition, patient data are compromised with uncertainty. These uncertain and incomplete input datasets will result in model output uncertainties. By means of a sensitivity analysis the propagation of input uncertainties into output uncertainty can be studied which can give directions for input measurement improvement. In this study, a computational framework has been developed to perform such a sensitivity analysis with a variance-based method and Monte Carlo simulations. The framework was used to determine the influential parameters of our pulse wave propagation model applied to AVF surgery, with respect to parameter prioritization and parameter fixing. With this we were able to determine the model parameters that have the largest influence on the predicted mean brachial flow and systolic radial artery pressure after AVF surgery. Of all 73 parameters 51 could be fixed within their measurement uncertainty interval without significantly influencing the output, while 16 parameters importantly influence the output uncertainty. Measurement accuracy improvement should thus focus on these 16 influential parameters. The most rewarding are measurement improvements of the following parameters: the mean aortic flow, the aortic windkessel resistance, the parameters associated with the smallest arterial or venous diameters of the AVF in- and outflow tract and the radial artery windkessel compliance. Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.

Modeling and Parameter Identification Involving 3-Hydroxypropionaldehyde Inhibitory Effects in Glycerol Continuous Fermentation

Directory of Open Access Journals (Sweden)

Zhaohua Gong

2012-01-01

Full Text Available Mathematical modeling and parameter estimation are critical steps in the optimization of biotechnological processes. In the 1,3-propanediol (1,3-PD production by glycerol fermentation process under anaerobic conditions, 3-hydroxypropionaldehyde (3-HPA accumulation would arouse an irreversible cessation of the fermentation process. Considering 3-HPA inhibitions to cells growth and to activities of enzymes, we propose a novel mathematical model to describe glycerol continuous cultures. Some properties of the above model are discussed. On the basis of the concentrations of extracellular substances, a parameter identification model is established to determine the kinetic parameters in the presented system. Through the penalty function technique combined with an extension of the state space method, an improved genetic algorithm is then constructed to solve the parameter identification model. An illustrative numerical example shows the appropriateness of the proposed model and the validity of optimization algorithm. Since it is difficult to measure the concentrations of intracellular substances, a quantitative robustness analysis method is given to infer whether the model is plausible for the intracellular substances. Numerical results show that the proposed model is of good robustness.

A "total parameter estimation" method in the varification of distributed hydrological models

Science.gov (United States)

Wang, M.; Qin, D.; Wang, H.

2011-12-01

Conventionally hydrological models are used for runoff or flood forecasting, hence the determination of model parameters are common estimated based on discharge measurements at the catchment outlets. With the advancement in hydrological sciences and computer technology, distributed hydrological models based on the physical mechanism such as SWAT, MIKESHE, and WEP, have gradually become the mainstream models in hydrology sciences. However, the assessments of distributed hydrological models and model parameter determination still rely on runoff and occasionally, groundwater level measurements. It is essential in many countries, including China, to understand the local and regional water cycle: not only do we need to simulate the runoff generation process and for flood forecasting in wet areas, we also need to grasp the water cycle pathways and consumption process of transformation in arid and semi-arid regions for the conservation and integrated water resources management. As distributed hydrological model can simulate physical processes within a catchment, we can get a more realistic representation of the actual water cycle within the simulation model. Runoff is the combined result of various hydrological processes, using runoff for parameter estimation alone is inherits problematic and difficult to assess the accuracy. In particular, in the arid areas, such as the Haihe River Basin in China, runoff accounted for only 17% of the rainfall, and very concentrated during the rainy season from June to August each year. During other months, many of the perennial rivers within the river basin dry up. Thus using single runoff simulation does not fully utilize the distributed hydrological model in arid and semi-arid regions. This paper proposed a "total parameter estimation" method to verify the distributed hydrological models within various water cycle processes, including runoff, evapotranspiration, groundwater, and soil water; and apply it to the Haihe river basin in

Test models for improving filtering with model errors through stochastic parameter estimation

International Nuclear Information System (INIS)

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

2010-01-01

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

Parameters Design for a Parallel Hybrid Electric Bus Using Regenerative Brake Model

Directory of Open Access Journals (Sweden)

Zilin Ma

2014-01-01

Full Text Available A design methodology which uses the regenerative brake model is introduced to determine the major system parameters of a parallel electric hybrid bus drive train. Hybrid system parameters mainly include the power rating of internal combustion engine (ICE, gear ratios of transmission, power rating, and maximal torque of motor, power, and capacity of battery. The regenerative model is built in the vehicle model to estimate the regenerative energy in the real road conditions. The design target is to ensure that the vehicle meets the specified vehicle performance, such as speed and acceleration, and at the same time, operates the ICE within an expected speed range. Several pairs of parameters are selected from the result analysis, and the fuel saving result in the road test shows that a 25% reduction is achieved in fuel consumption.

Determination of performance parameters of vertical axis wind turbines in wind tunnel

Directory of Open Access Journals (Sweden)

Nguyen Van Bang

2017-01-01

Full Text Available The paper deals with the determination of the performance parameters of a small vertical axis wind turbines (VAWT, which operate by the utilization of drag forces acting on the blades of the turbine. The performance was evaluated by investigating the electrical power output and torque moment of the wind machine. Measurements were performed on the full-scale model and the experimental data are assessed and compared to other types of wind turbines, with respect to its purpose.

Deriving global parameter estimates for the Noah land surface model using FLUXNET and machine learning

Science.gov (United States)

Chaney, Nathaniel W.; Herman, Jonathan D.; Ek, Michael B.; Wood, Eric F.

2016-11-01

With their origins in numerical weather prediction and climate modeling, land surface models aim to accurately partition the surface energy balance. An overlooked challenge in these schemes is the role of model parameter uncertainty, particularly at unmonitored sites. This study provides global parameter estimates for the Noah land surface model using 85 eddy covariance sites in the global FLUXNET network. The at-site parameters are first calibrated using a Latin Hypercube-based ensemble of the most sensitive parameters, determined by the Sobol method, to be the minimum stomatal resistance (rs,min), the Zilitinkevich empirical constant (Czil), and the bare soil evaporation exponent (fxexp). Calibration leads to an increase in the mean Kling-Gupta Efficiency performance metric from 0.54 to 0.71. These calibrated parameter sets are then related to local environmental characteristics using the Extra-Trees machine learning algorithm. The fitted Extra-Trees model is used to map the optimal parameter sets over the globe at a 5 km spatial resolution. The leave-one-out cross validation of the mapped parameters using the Noah land surface model suggests that there is the potential to skillfully relate calibrated model parameter sets to local environmental characteristics. The results demonstrate the potential to use FLUXNET to tune the parameterizations of surface fluxes in land surface models and to provide improved parameter estimates over the globe.

A novel and practical approach for determination of the acoustic nonlinearity parameter using a pulse-echo method

Science.gov (United States)

Jeong, Hyunjo; Zhang, Shuzeng; Barnard, Dan; Li, Xiongbing

2016-02-01

Measurements of the acoustic nonlinearity parameter β are frequently made for early detection of damage in various materials. The practical implementation of the measurement technique has been limited to the through-transmission setup for determining the nonlinearity parameter of the second harmonic wave. In this work, a feasibility study is performed to assess the possibility of using pulse-echo methods in determining the nonlinearity parameter β of solids with a stress-free boundary. The multi-Gaussian beam model is developed based on the quasilinear theory of the KZK equation. Simulation results and discussion are presented for the reflected beam fields of the fundamental and second harmonic waves, the uncorrected β behavior and the properties of total correction that incorporate reflection, attenuation and diffraction effects.

Determination of nutritional parameters of yoghurts by FT Raman spectroscopy

Science.gov (United States)

Czaja, Tomasz; Baranowska, Maria; Mazurek, Sylwester; Szostak, Roman

2018-05-01

FT-Raman quantitative analysis of nutritional parameters of yoghurts was performed with the help of partial least squares models. The relative standard errors of prediction for fat, lactose and protein determination in the quantified commercial samples equalled to 3.9, 3.2 and 3.6%, respectively. Models based on attenuated total reflectance spectra of the liquid yoghurt samples and of dried yoghurt films collected with the single reflection diamond accessory showed relative standard errors of prediction values of 1.6-5.0% and 2.7-5.2%, respectively, for the analysed components. Despite a relatively low signal-to-noise ratio in the obtained spectra, Raman spectroscopy, combined with chemometrics, constitutes a fast and powerful tool for macronutrients quantification in yoghurts. Errors received for attenuated total reflectance method were found to be relatively higher than those for Raman spectroscopy due to inhomogeneity of the analysed samples.

Repository environmental parameters and models/methodologies relevant to assessing the performance of high-level waste packages in basalt, tuff, and salt

Energy Technology Data Exchange (ETDEWEB)

Claiborne, H.C.; Croff, A.G.; Griess, J.C.; Smith, F.J.

1987-09-01

This document provides specifications for models/methodologies that could be employed in determining postclosure repository environmental parameters relevant to the performance of high-level waste packages for the Basalt Waste Isolation Project (BWIP) at Richland, Washington, the tuff at Yucca Mountain by the Nevada Test Site, and the bedded salt in Deaf Smith County, Texas. Guidance is provided on the identify of the relevant repository environmental parameters; the models/methodologies employed to determine the parameters, and the input data base for the models/methodologies. Supporting studies included are an analysis of potential waste package failure modes leading to identification of the relevant repository environmental parameters, an evaluation of the credible range of the repository environmental parameters, and a summary of the review of existing models/methodologies currently employed in determining repository environmental parameters relevant to waste package performance. 327 refs., 26 figs., 19 tabs.

Repository environmental parameters and models/methodologies relevant to assessing the performance of high-level waste packages in basalt, tuff, and salt

International Nuclear Information System (INIS)

Claiborne, H.C.; Croff, A.G.; Griess, J.C.; Smith, F.J.

1987-09-01

This document provides specifications for models/methodologies that could be employed in determining postclosure repository environmental parameters relevant to the performance of high-level waste packages for the Basalt Waste Isolation Project (BWIP) at Richland, Washington, the tuff at Yucca Mountain by the Nevada Test Site, and the bedded salt in Deaf Smith County, Texas. Guidance is provided on the identify of the relevant repository environmental parameters; the models/methodologies employed to determine the parameters, and the input data base for the models/methodologies. Supporting studies included are an analysis of potential waste package failure modes leading to identification of the relevant repository environmental parameters, an evaluation of the credible range of the repository environmental parameters, and a summary of the review of existing models/methodologies currently employed in determining repository environmental parameters relevant to waste package performance. 327 refs., 26 figs., 19 tabs

Exploiting intrinsic fluctuations to identify model parameters.

Science.gov (United States)

Zimmer, Christoph; Sahle, Sven; Pahle, Jürgen

2015-04-01

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

Linear least squares compartmental-model-independent parameter identification in PET

International Nuclear Information System (INIS)

Thie, J.A.; Smith, G.T.; Hubner, K.F.

1997-01-01

A simplified approach involving linear-regression straight-line parameter fitting of dynamic scan data is developed for both specific and nonspecific models. Where compartmental-model topologies apply, the measured activity may be expressed in terms of: its integrals, plasma activity and plasma integrals -- all in a linear expression with macroparameters as coefficients. Multiple linear regression, as in spreadsheet software, determines parameters for best data fits. Positron emission tomography (PET)-acquired gray-matter images in a dynamic scan are analyzed: both by this method and by traditional iterative nonlinear least squares. Both patient and simulated data were used. Regression and traditional methods are in expected agreement. Monte-Carlo simulations evaluate parameter standard deviations, due to data noise, and much smaller noise-induced biases. Unique straight-line graphical displays permit visualizing data influences on various macroparameters as changes in slopes. Advantages of regression fitting are: simplicity, speed, ease of implementation in spreadsheet software, avoiding risks of convergence failures or false solutions in iterative least squares, and providing various visualizations of the uptake process by straight line graphical displays. Multiparameter model-independent analyses on lesser understood systems is also made possible

Magnetoresistance based determination of basic parameters of minority charge carriers in solid matter

Directory of Open Access Journals (Sweden)

Y.O. Uhryn

2017-12-01

Full Text Available Magnetoresistance as a tool of basic parameters determination of minority charge carriers and the ratio of minority charge carriers conductivity to majority ones in solid matter has been considered within the framework of the phenomenological two-band model. The criterion of the application of this model has been found. As examples of these equations usage the conductor, semiconductor and superconductor have been introduced. From the obtained temperature dependences of the aforementioned values in superconductor, a supposition of a deciding role of minority charge carriers in the emergence of superconductivity state has been made.

METHODOLOGY FOR THE ESTIMATION OF PARAMETERS, OF THE MODIFIED BOUC-WEN MODEL

Directory of Open Access Journals (Sweden)

Tomasz HANISZEWSKI

2015-03-01

Full Text Available Bouc-Wen model is theoretical formulation that allows to reflect real hysteresis loop of modeled object. Such object is for example a wire rope, which is present on equipment of crane lifting mechanism. Where adopted modified version of the model has nine parameters. Determination of such a number of parameters is complex and problematic issue. In this article are shown the methodology to identify and sample results of numerical simulations. The results were compared with data obtained on the basis of laboratory tests of ropes [3] and on their basis it was found that there is compliance between results and there is possibility to apply in dynamic systems containing in their structures wire ropes [4].

BAYESIAN PARAMETER ESTIMATION IN A MIXED-ORDER MODEL OF BOD DECAY. (U915590)

Science.gov (United States)

We describe a generalized version of the BOD decay model in which the reaction is allowed to assume an order other than one. This is accomplished by making the exponent on BOD concentration a free parameter to be determined by the data. This "mixed-order" model may be ...

Determination of probability density functions for parameters in the Munson-Dawson model for creep behavior of salt

International Nuclear Information System (INIS)

Pfeifle, T.W.; Mellegard, K.D.; Munson, D.E.

1992-10-01

The modified Munson-Dawson (M-D) constitutive model that describes the creep behavior of salt will be used in performance assessment calculations to assess compliance of the Waste Isolation Pilot Plant (WIPP) facility with requirements governing the disposal of nuclear waste. One of these standards requires that the uncertainty of future states of the system, material model parameters, and data be addressed in the performance assessment models. This paper presents a method in which measurement uncertainty and the inherent variability of the material are characterized by treating the M-D model parameters as random variables. The random variables can be described by appropriate probability distribution functions which then can be used in Monte Carlo or structural reliability analyses. Estimates of three random variables in the M-D model were obtained by fitting a scalar form of the model to triaxial compression creep data generated from tests of WIPP salt. Candidate probability distribution functions for each of the variables were then fitted to the estimates and their relative goodness-of-fit tested using the Kolmogorov-Smirnov statistic. A sophisticated statistical software package obtained from BMDP Statistical Software, Inc. was used in the M-D model fitting. A separate software package, STATGRAPHICS, was used in fitting the candidate probability distribution functions to estimates of the variables. Skewed distributions, i.e., lognormal and Weibull, were found to be appropriate for the random variables analyzed

Variational estimation of process parameters in a simplified atmospheric general circulation model

Science.gov (United States)

Lv, Guokun; Koehl, Armin; Stammer, Detlef

2016-04-01

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

Calculation of the fermionic determinant in the Schwinger model

International Nuclear Information System (INIS)

Dias, S.A.; Linhares, C.A.

1991-01-01

We compute explicitly the fermionic determinant and the effective action for the generalized Schwinger model in two dimensions and compare it with respective results for the particular cases of the Schwinger, chiral Schwinger and axial Schwinger models. The parameters that signal the ambiguity in the regularization scheme fo the determinant are introduced through the point-splitting method. The Wess-Zumino functional is also obtained and compared with the known expressions for the above-mentioned particular cases. (author)

Parameter discovery in stochastic biological models using simulated annealing and statistical model checking.

Science.gov (United States)

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

2014-01-01

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

Determining Representative Elementary Volume For Multiple Petrophysical Parameters using a Convex Hull Analysis of Digital Rock Data

Science.gov (United States)

Shah, S.; Gray, F.; Yang, J.; Crawshaw, J.; Boek, E.

2016-12-01

Advances in 3D pore-scale imaging and computational methods have allowed an exceptionally detailed quantitative and qualitative analysis of the fluid flow in complex porous media. A fundamental problem in pore-scale imaging and modelling is how to represent and model the range of scales encountered in porous media, starting from the smallest pore spaces. In this study, a novel method is presented for determining the representative elementary volume (REV) of a rock for several parameters simultaneously. We calculate the two main macroscopic petrophysical parameters, porosity and single-phase permeability, using micro CT imaging and Lattice Boltzmann (LB) simulations for 14 different porous media, including sandpacks, sandstones and carbonates. The concept of the `Convex Hull' is then applied to calculate the REV for both parameters simultaneously using a plot of the area of the convex hull as a function of the sub-volume, capturing the different scales of heterogeneity from the pore-scale imaging. The results also show that the area of the convex hull (for well-chosen parameters such as the log of the permeability and the porosity) decays exponentially with sub-sample size suggesting a computationally efficient way to determine the system size needed to calculate the parameters to high accuracy (small convex hull area). Finally we propose using a characteristic length such as the pore size to choose an efficient absolute voxel size for the numerical rock.

Multi-Scale Parameter Identification of Lithium-Ion Battery Electric Models Using a PSO-LM Algorithm

Directory of Open Access Journals (Sweden)

Wen-Jing Shen

2017-03-01

Full Text Available This paper proposes a multi-scale parameter identification algorithm for the lithium-ion battery (LIB electric model by using a combination of particle swarm optimization (PSO and Levenberg-Marquardt (LM algorithms. Two-dimensional Poisson equations with unknown parameters are used to describe the potential and current density distribution (PDD of the positive and negative electrodes in the LIB electric model. The model parameters are difficult to determine in the simulation due to the nonlinear complexity of the model. In the proposed identification algorithm, PSO is used for the coarse-scale parameter identification and the LM algorithm is applied for the fine-scale parameter identification. The experiment results show that the multi-scale identification not only improves the convergence rate and effectively escapes from the stagnation of PSO, but also overcomes the local minimum entrapment drawback of the LM algorithm. The terminal voltage curves from the PDD model with the identified parameter values are in good agreement with those from the experiments at different discharge/charge rates.

Establishing statistical models of manufacturing parameters

International Nuclear Information System (INIS)

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

1991-01-01

This paper reports on the effect of pilgering and cold-work parameters on contractile strain ratio and mechanical properties that were investigated using a large population of Zircaloy tubes. Statistical models were established between: contractile strain ratio and tooling parameters, mechanical properties (tensile test, creep test) and cold-work parameters, and mechanical properties and stress-relieving temperature

Determination of heterogeneous medium parameters by single fuel element method

International Nuclear Information System (INIS)

Veloso, M.A.F.

1985-01-01

The neutron pulse propagation technique was employed to study an heterogeneous system consisting of a single fuel element placed at the symmetry axis of a large cylindrical D 2 O tank. The response of system for the pulse propagation technique is related to the inverse complex relaxation length of the neutron waves also known as the system dispersion law ρ (ω). Experimental values of ρ (ω) were compared with the ones derived from Fermi age - Diffusion theory. The main purpose of the experiment was to obtain the Feinberg-Galanin thermal constant (γ), which is the logaritmic derivative of the neutron flux at the fuel-moderator interface and a such a main input data for heterogeneous reactor theory calculations. The γ thermal constant was determined as the number giving the best agreement between the theoretical and experimental values of ρ (ω). The simultaneous determination of two among four parameters η,ρ,τ and L s is possible through the intersection of dispersion laws of the pure moderator system and the fuel moderator system. The parameters τ and η were termined by this method. It was shown that the thermal constant γ and the product η ρ can be computed from the real and imaginary parts of the fuel-moderator dispersion law. The results for this evaluation scheme showns a not stable behavior of γ as a function of frequency, a result not foreseen by the theoretical model. (Author) [pt

Some tests for parameter constancy in cointegrated VAR-models

DEFF Research Database (Denmark)

Hansen, Henrik; Johansen, Søren

1999-01-01

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

Edge Modeling by Two Blur Parameters in Varying Contrasts.

Science.gov (United States)

Seo, Suyoung

2018-06-01

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

On-line adaptive battery impedance parameter and state estimation considering physical principles in reduced order equivalent circuit battery models part 2. Parameter and state estimation

Science.gov (United States)

Fleischer, Christian; Waag, Wladislaw; Heyn, Hans-Martin; Sauer, Dirk Uwe

2014-09-01

Lithium-ion battery systems employed in high power demanding systems such as electric vehicles require a sophisticated monitoring system to ensure safe and reliable operation. Three major states of the battery are of special interest and need to be constantly monitored. These include: battery state of charge (SoC), battery state of health (capacity fade determination, SoH), and state of function (power fade determination, SoF). The second paper concludes the series by presenting a multi-stage online parameter identification technique based on a weighted recursive least quadratic squares parameter estimator to determine the parameters of the proposed battery model from the first paper during operation. A novel mutation based algorithm is developed to determine the nonlinear current dependency of the charge-transfer resistance. The influence of diffusion is determined by an on-line identification technique and verified on several batteries at different operation conditions. This method guarantees a short response time and, together with its fully recursive structure, assures a long-term stable monitoring of the battery parameters. The relative dynamic voltage prediction error of the algorithm is reduced to 2%. The changes of parameters are used to determine the states of the battery. The algorithm is real-time capable and can be implemented on embedded systems.

Determination of optimal tool parameters for hot mandrel bending of pipe elbows

Science.gov (United States)

Tabakajew, Dmitri; Homberg, Werner

2018-05-01

Seamless pipe elbows are important components in mechanical, plant and apparatus engineering. Typically, they are produced by the so-called `Hamburg process'. In this hot forming process, the initial pipes are subsequently pushed over an ox-horn-shaped bending mandrel. The geometric shape of the mandrel influences the diameter, bending radius and wall thickness distribution of the pipe elbow. This paper presents the numerical simulation model of the hot mandrel bending process created to ensure that the optimum mandrel geometry can be determined at an early stage. A fundamental analysis was conducted to determine the influence of significant parameters on the pipe elbow quality. The chosen methods and approach as well as the corresponding results are described in this paper.

A proposed method for fast determination of plasma parameters

International Nuclear Information System (INIS)

Braams, B.J.; Lackner, K.

1984-09-01

The method of function parametrization, developed and applied by H. Wind for fast data evaluation in high energy physics, is presented in the context of controlled fusion research. This method relies on statistical analysis of a data base of simulated experiments in order to obtain a functional representation for the intrinsic physical parameters of a system in terms of the values of the measurements. Some variations on Wind's original procedure are suggested. A specific application for tokamak experiments would be the determination of certain global parameters of the plasma, characterizing the current profile, shape of the cross-section, plasma pressure, and the internal inductance. The relevant measurements for this application include values of the poloidal field and flux external to the plasma, and a diamagnetic measurement. These may be combined with other diagnostics, such as electron-cyclotron emission and laser interferometry, in order to obtain also density and temperature profiles. There appears to be a capability for on-line determination of basic physical parameters, in a millisecond timescale on a minicomputer instead of in seconds on a large mainframe. (orig.)

A Review of Distributed Parameter Groundwater Management Modeling Methods

Science.gov (United States)

Gorelick, Steven M.

1983-04-01

Models which solve the governing groundwater flow or solute transport equations in conjunction with optimization techniques, such as linear and quadratic programing, are powerful aquifer management tools. Groundwater management models fall in two general categories: hydraulics or policy evaluation and water allocation. Groundwater hydraulic management models enable the determination of optimal locations and pumping rates of numerous wells under a variety of restrictions placed upon local drawdown, hydraulic gradients, and water production targets. Groundwater policy evaluation and allocation models can be used to study the influence upon regional groundwater use of institutional policies such as taxes and quotas. Furthermore, fairly complex groundwater-surface water allocation problems can be handled using system decomposition and multilevel optimization. Experience from the few real world applications of groundwater optimization-management techniques is summarized. Classified separately are methods for groundwater quality management aimed at optimal waste disposal in the subsurface. This classification is composed of steady state and transient management models that determine disposal patterns in such a way that water quality is protected at supply locations. Classes of research missing from the literature are groundwater quality management models involving nonlinear constraints, models which join groundwater hydraulic and quality simulations with political-economic management considerations, and management models that include parameter uncertainty.

Determinants of dermal exposure relevant for exposure modelling in regulatory risk assessment.

Science.gov (United States)

Marquart, J; Brouwer, D H; Gijsbers, J H J; Links, I H M; Warren, N; van Hemmen, J J

2003-11-01

Risk assessment of chemicals requires assessment of the exposure levels of workers. In the absence of adequate specific measured data, models are often used to estimate exposure levels. For dermal exposure only a few models exist, which are not validated externally. In the scope of a large European research programme, an analysis of potential dermal exposure determinants was made based on the available studies and models and on the expert judgement of the authors of this publication. Only a few potential determinants appear to have been studied in depth. Several studies have included clusters of determinants into vaguely defined parameters, such as 'task' or 'cleaning and maintenance of clothing'. Other studies include several highly correlated parameters, such as 'amount of product handled', 'duration of task' and 'area treated', and separation of these parameters to study their individual influence is not possible. However, based on the available information, a number of determinants could clearly be defined as proven or highly plausible determinants of dermal exposure in one or more exposure situation. This information was combined with expert judgement on the scientific plausibility of the influence of parameters that have not been extensively studied and on the possibilities to gather relevant information during a risk assessment process. The result of this effort is a list of determinants relevant for dermal exposure models in the scope of regulatory risk assessment. The determinants have been divided into the major categories 'substance and product characteristics', 'task done by the worker', 'process technique and equipment', 'exposure control measures', 'worker characteristics and habits' and 'area and situation'. To account for the complex nature of the dermal exposure processes, a further subdivision was made into the three major processes 'direct contact', 'surface contact' and 'deposition'.

Identifyability measures to select the parameters to be estimated in a solid-state fermentation distributed parameter model.

Science.gov (United States)

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

2016-07-08

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

Determination of Intermediate Resonance Parameter with RMET21 for nTRACER

International Nuclear Information System (INIS)

Sohail, Muhammad; Kim, Myung Hyun

2012-01-01

Ray Tracing based code nTRACER is being developed in Seoul National University that has the capability of 3-dimensional whole core neutron transport calculation. As a part of development of multi-group neutron cross section library for nTRACER, the current work is intended to accurately determine intermediate resonance parameters. Beside the systematic calculation of subgroup parameters for resonance self shielding calculation, intermediate resonance parameters itself can be as important as the multi-group neutron cross section in the library and its overall accuracy. In this paper lambda factors were computed using RMET21 from ENDF/B-VII.1 for nTRACER to investigate its dependence on temperature and background cross section and replaced with lambda factors from HELIOS multi-group library. The procedure used for determining the intermediate resonance parameter for the isotope under study is introduced in the next section. Oxygen being one of the primary nuclide in PWR fuel has been selected for intermediate resonance parameters calculation

Environmental Transport Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

M. A. Wasiolek

2003-06-27

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

Environmental Transport Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

Wasiolek, M. A.

2003-01-01

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

Parameter estimation in stochastic rainfall-runoff models

DEFF Research Database (Denmark)

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

2006-01-01

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

Determination of combustion parameters using engine crankshaft speed

Science.gov (United States)

Taglialatela, F.; Lavorgna, M.; Mancaruso, E.; Vaglieco, B. M.

2013-07-01

Electronic engine controls based on real time diagnosis of combustion process can significantly help in complying with the stricter and stricter regulations on pollutants emissions and fuel consumption. The most important parameter for the evaluation of combustion quality in internal combustion engines is the in-cylinder pressure, but its direct measurement is very expensive and involves an intrusive approach to the cylinder. Previous researches demonstrated the direct relationship existing between in-cylinder pressure and engine crankshaft speed and several authors tried to reconstruct the pressure cycle on the basis of the engine speed signal. In this paper we propose the use of a Multi-Layer Perceptron neural network to model the relationship between the engine crankshaft speed and some parameters derived from the in-cylinder pressure cycle. This allows to have a non-intrusive estimation of cylinder pressure and a real time evaluation of combustion quality. The structure of the model and the training procedure is outlined in the paper. A possible combustion controller using the information extracted from the crankshaft speed information is also proposed. The application of the neural network model is demonstrated on a single-cylinder spark ignition engine tested in a wide range of speeds and loads. Results confirm that a good estimation of some combustion pressure parameters can be obtained by means of a suitable processing of crankshaft speed signal.

Tracer techniques for determination of groundwater flow parameters

International Nuclear Information System (INIS)

Drost, W.; Klotz, D.

1988-05-01

The most common one-borehole and multiple borehole methods using tracers for the direct determination of the groundwater flow parameters (velocity of flow, flow direction) and for the indirect determination of characteristic quantities of the aquifer (effective porosity, dispersivity, transmissivity) are presented methodically and their value is documented by practical examples. Especially, the properties of and measuring technique with suitable tracers are considered (e.g. T, Na-24, Cr-51, Co-58, Co-60, Br-82, Tc-99, I-125, I-131, Au-198). (orig./HP) [de

Determination of Stark parameters by cross-calibration in a multi-element laser-induced plasma

Science.gov (United States)

Liu, Hao; Truscott, Benjamin S.; Ashfold, Michael N. R.

2016-05-01

We illustrate a Stark broadening analysis of the electron density Ne and temperature Te in a laser-induced plasma (LIP), using a model free of assumptions regarding local thermodynamic equilibrium (LTE). The method relies on Stark parameters determined also without assuming LTE, which are often unknown and unavailable in the literature. Here, we demonstrate that the necessary values can be obtained in situ by cross-calibration between the spectral lines of different charge states, and even different elements, given determinations of Ne and Te based on appropriate parameters for at least one observed transition. This approach enables essentially free choice between species on which to base the analysis, extending the range over which these properties can be measured and giving improved access to low-density plasmas out of LTE. Because of the availability of suitable tabulated values for several charge states of both Si and C, the example of a SiC LIP is taken to illustrate the consistency and accuracy of the procedure. The cross-calibrated Stark parameters are at least as reliable as values obtained by other means, offering a straightforward route to extending the literature in this area.

Optimization of Saturn paraboloid magnetospheric field model parameters using Cassini equatorial magnetic field data

Directory of Open Access Journals (Sweden)

E. S. Belenkaya

2016-07-01

Full Text Available The paraboloid model of Saturn's magnetosphere describes the magnetic field as being due to the sum of contributions from the internal field of the planet, the ring current, and the tail current, all contained by surface currents inside a magnetopause boundary which is taken to be a paraboloid of revolution about the planet-Sun line. The parameters of the model have previously been determined by comparison with data from a few passes through Saturn's magnetosphere in compressed and expanded states, depending on the prevailing dynamic pressure of the solar wind. Here we significantly expand such comparisons through examination of Cassini magnetic field data from 18 near-equatorial passes that span wide ranges of local time, focusing on modelling the co-latitudinal field component that defines the magnetic flux passing through the equatorial plane. For 12 of these passes, spanning pre-dawn, via noon, to post-midnight, the spacecraft crossed the magnetopause during the pass, thus allowing an estimate of the concurrent subsolar radial distance of the magnetopause R1 to be made, considered to be the primary parameter defining the scale size of the system. The best-fit model parameters from these passes are then employed to determine how the parameters vary with R1, using least-squares linear fits, thus providing predictive model parameters for any value of R1 within the range. We show that the fits obtained using the linear approximation parameters are of the same order as those for the individually selected parameters. We also show that the magnetic flux mapping to the tail lobes in these models is generally in good accord with observations of the location of the open-closed field line boundary in Saturn's ionosphere, and the related position of the auroral oval. We then investigate the field data on six passes through the nightside magnetosphere, for which the spacecraft did not cross the magnetopause, such that in this case we compare the

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...

Determination of the Performance Parameters of a Spectrophotometer: An Advanced Experiment.

Science.gov (United States)

Cope, Virgil W.

1978-01-01

Describes an advanced analytical chemistry laboratory experiment developed for the determination of the performance parameters of a spectrophotometer. Among the parameters are the baseline linearity with wavelength, wavelength accuracy and respectability, stray light, noise level and pen response time. (HM)

A simulation of water pollution model parameter estimation

Science.gov (United States)

Kibler, J. F.

1976-01-01

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

Identification of ecosystem parameters by SDE-modelling

DEFF Research Database (Denmark)

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

Estimation Parameters And Modelling Zero Inflated Negative Binomial

Directory of Open Access Journals (Sweden)

Cindy Cahyaning Astuti

2016-11-01

Full Text Available Regression analysis is used to determine relationship between one or several response variable (Y with one or several predictor variables (X. Regression model between predictor variables and the Poisson distributed response variable is called Poisson Regression Model. Since, Poisson Regression requires an equality between mean and variance, it is not appropriate to apply this model on overdispersion (variance is higher than mean. Poisson regression model is commonly used to analyze the count data. On the count data type, it is often to encounteredd some observations that have zero value with large proportion of zero value on the response variable (zero Inflation. Poisson regression can be used to analyze count data but it has not been able to solve problem of excess zero value on the response variable. An alternative model which is more suitable for overdispersion data and can solve the problem of excess zero value on the response variable is Zero Inflated Negative Binomial (ZINB. In this research, ZINB is applied on the case of Tetanus Neonatorum in East Java. The aim of this research is to examine the likelihood function and to form an algorithm to estimate the parameter of ZINB and also applying ZINB model in the case of Tetanus Neonatorum in East Java. Maximum Likelihood Estimation (MLE method is used to estimate the parameter on ZINB and the likelihood function is maximized using Expectation Maximization (EM algorithm. Test results of ZINB regression model showed that the predictor variable have a partial significant effect at negative binomial model is the percentage of pregnant women visits and the percentage of maternal health personnel assisted, while the predictor variables that have a partial significant effect at zero inflation model is the percentage of neonatus visits.

Millimeter-wave small-signal modeling with optimizing sensitive-parameters for metamorphic high electron mobility transistors

International Nuclear Information System (INIS)

Moon, S-W; Baek, Y-H; Han, M; Rhee, J-K; Kim, S-D; Oh, J-H

2010-01-01

In this paper, we present a simple and reliable technique for determining the small-signal equivalent circuit model parameters of the 0.1 µm metamorphic high electron mobility transistors (MHEMTs) in a millimeter-wave frequency range. The initial eight extrinsic parameters of the MHEMT are extracted using two S-parameter (scattering parameter) sets measured under the pinched-off and zero-biased cold field-effect transistor conditions by avoiding the forward gate biasing. Furthermore, highly calibration-sensitive values of the R s , L s and C pd are optimized by using a gradient optimization method to improve the modeling accuracy. The accuracy enhancement of this procedure is successfully verified with an excellent correlation between the measured and calculated S-parameters up to 65 GHz

Spatio-temporal modeling of nonlinear distributed parameter systems

CERN Document Server

Li, Han-Xiong

2011-01-01

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

A fundamental parameter-based calibration model for an intrinsic germanium X-ray fluorescence spectrometer

International Nuclear Information System (INIS)

Christensen, L.H.; Pind, N.

1982-01-01

A matrix-independent fundamental parameter-based calibration model for an energy-dispersive X-ray fluorescence spectrometer has been developed. This model, which is part of a fundamental parameter approach quantification method, accounts for both the excitation and detection probability. For each secondary target a number of relative calibration constants are calculated on the basis of knowledge of the irradiation geometry, the detector specifications, and tabulated fundamental physical parameters. The absolute calibration of the spectrometer is performed by measuring one pure element standard per secondary target. For sample systems where all elements can be analyzed by means of the same secondary target the absolute calibration constant can be determined during the iterative solution of the basic equation. Calculated and experimentally determined relative calibration constants agree to within 5-10% of each other and so do the results obtained from the analysis of an NBS certified alloy using the two sets of constants. (orig.)

Mathematical modelling of nonstationary processes in a regenerator with dissociating coolant at supercritical parameters

International Nuclear Information System (INIS)

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

1985-01-01

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

Models for estimating photosynthesis parameters from in situ production profiles

Science.gov (United States)

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

2017-12-01

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

GEMSFITS: Code package for optimization of geochemical model parameters and inverse modeling

International Nuclear Information System (INIS)

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

2015-01-01

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

A determination of electroweak parameters at HERA

Science.gov (United States)

H1 Collaboration; Aktas, A.; Andreev, V.; Anthonis, T.; Aplin, S.; Asmone, A.; Astvatsatourov, A.; Babaev, A.; Backovic, S.; Bähr, J.; Baghdasaryan, A.; Baranov, P.; Barrelet, E.; Bartel, W.; Baudrand, S.; Baumgartner, S.; Becker, J.; Beckingham, M.; Behnke, O.; Behrendt, O.; Belousov, A.; Berger, Ch.; Berger, N.; Bizot, J. C.; Boenig, M.-O.; Boudry, V.; Bracinik, J.; Brandt, G.; Brisson, V.; Brown, D. P.; Bruncko, D.; Büsser, F. W.; Bunyatyan, A.; Buschhorn, G.; Bystritskaya, L.; Campbell, A. J.; Caron, S.; Cassol-Brunner, F.; Cerny, K.; Cerny, V.; Chekelian, V.; Contreras, J. G.; Coughlan, J. A.; Cox, B. E.; Cozzika, G.; Cvach, J.; Dainton, J. B.; Dau, W. D.; Daum, K.; de Boer, Y.; Delcourt, B.; de Roeck, A.; Desch, K.; de Wolf, E. A.; Diaconu, C.; Dodonov, V.; Dubak, A.; Eckerlin, G.; Efremenko, V.; Egli, S.; Eichler, R.; Eisele, F.; Ellerbrock, M.; Erdmann, W.; Essenov, S.; Falkewicz, A.; Faulkner, P. J. W.; Favart, L.; Fedotov, A.; Felst, R.; Ferencei, J.; Finke, L.; Fleischer, M.; Fleischmann, P.; Fleming, Y. H.; Flucke, G.; Fomenko, A.; Foresti, I.; Franke, G.; Frisson, T.; Gabathuler, E.; Garutti, E.; Gayler, J.; Gerlich, C.; Ghazaryan, S.; Ginzburgskaya, S.; Glazov, A.; Glushkov, I.; Goerlich, L.; Goettlich, M.; Gogitidze, N.; Gorbounov, S.; Goyon, C.; Grab, C.; Greenshaw, T.; Gregori, M.; Grell, B. R.; Grindhammer, G.; Gwilliam, C.; Haidt, D.; Hajduk, L.; Hansson, M.; Heinzelmann, G.; Henderson, R. C. W.; Henschel, H.; Henshaw, O.; Herrera, G.; Hildebrandt, M.; Hiller, K. H.; Hoffmann, D.; Horisberger, R.; Hovhannisyan, A.; Hreus, T.; Hussain, S.; Ibbotson, M.; Ismail, M.; Jacquet, M.; Janauschek, L.; Janssen, X.; Jemanov, V.; Jönsson, L.; Johnson, D. P.; Jung, A. W.; Jung, H.; Kapichine, M.; Katzy, J.; Keller, N.; Kenyon, I. R.; Kiesling, C.; Klein, M.; Kleinwort, C.; Klimkovich, T.; Kluge, T.; Knies, G.; Knutsson, A.; Korbel, V.; Kostka, P.; Krastev, K.; Kretzschmar, J.; Kropivnitskaya, A.; Krüger, K.; Kückens, J.; Landon, M. P. J.; Lange, W.; Laštovička, T.; Laštovička-Medin, G.; Laycock, P.; Lebedev, A.; Leibenguth, G.; Lendermann, V.; Levonian, S.; Lindfeld, L.; Lipka, K.; Liptaj, A.; List, B.; Lobodzinska, E.; Loktionova, N.; Lopez-Fernandez, R.; Lubimov, V.; Lucaci-Timoce, A.-I.; Lueders, H.; Lüke, D.; Lux, T.; Lytkin, L.; Makankine, A.; Malden, N.; Malinovski, E.; Mangano, S.; Marage, P.; Marshall, R.; Martisikova, M.; Martyn, H.-U.; Maxfield, S. J.; Meer, D.; Mehta, A.; Meier, K.; Meyer, A. B.; Meyer, H.; Meyer, J.; Mikocki, S.; Milcewicz-Mika, I.; Milstead, D.; Mladenov, D.; Mohamed, A.; Moreau, F.; Morozov, A.; Morris, J. V.; Mozer, M. U.; Müller, K.; Murín, P.; Nankov, K.; Naroska, B.; Naumann, Th.; Newman, P. R.; Niebuhr, C.; Nikiforov, A.; Nikitin, D.; Nowak, G.; Nozicka, M.; Oganezov, R.; Olivier, B.; Olsson, J. E.; Osman, S.; Ozerov, D.; Palichik, V.; Panagoulias, I.; Papadopoulou, T.; Pascaud, C.; Patel, G. D.; Peez, M.; Perez, E.; Perez-Astudillo, D.; Perieanu, A.; Petrukhin, A.; Pitzl, D.; Plačakytė, R.; Portheault, B.; Povh, B.; Prideaux, P.; Raicevic, N.; Reimer, P.; Rimmer, A.; Risler, C.; Rizvi, E.; Robmann, P.; Roland, B.; Roosen, R.; Rostovtsev, A.; Rurikova, Z.; Rusakov, S.; Salvaire, F.; Sankey, D. P. C.; Sauvan, E.; Schätzel, S.; Schilling, F.-P.; Schmidt, S.; Schmitt, S.; Schmitz, C.; Schoeffel, L.; Schöning, A.; Schultz-Coulon, H.-C.; Sedlák, K.; Sefkow, F.; Shaw-West, R. N.; Sheviakov, I.; Shtarkov, L. N.; Sloan, T.; Smirnov, P.; Soloviev, Y.; South, D.; Spaskov, V.; Specka, A.; Stella, B.; Stiewe, J.; Strauch, I.; Straumann, U.; Tchoulakov, V.; Thompson, G.; Thompson, P. D.; Tomasz, F.; Traynor, D.; Truöl, P.; Tsakov, I.; Tsipolitis, G.; Tsurin, I.; Turnau, J.; Tzamariudaki, E.; Urban, M.; Usik, A.; Utkin, D.; Valkár, S.; Valkárová, A.; Vallée, C.; van Mechelen, P.; Vargas Trevino, A.; Vazdik, Y.; Veelken, C.; Vest, A.; Vinokurova, S.; Volchinski, V.; Vujicic, B.; Wacker, K.; Wagner, J.; Weber, G.; Weber, R.; Wegener, D.; Werner, C.; Werner, N.; Wessels, M.; Wessling, B.; Wigmore, C.; Wissing, Ch.; Wolf, R.; Wünsch, E.; Xella, S.; Yan, W.; Yeganov, V.; Žáček, J.; Zálešák, J.; Zhang, Z.; Zhelezov, A.; Zhokin, A.; Zhu, Y. C.; Zimmermann, J.; Zimmermann, T.; Zohrabyan, H.; Zomer, F.

2006-01-01

Using the deep inelastic ep and ep charged and neutral current scattering cross sections previously published, a combined electroweak and QCD analysis is performed to determine electroweak parameters accounting for their correlation with parton distributions. The data used have been collected by the H1 experiment in 1994 2000 and correspond to an integrated luminosity of 117.2 pb. A measurement is obtained of the W propagator mass in charged current ep scattering. The weak mixing angle sinθ is determined in the on-mass-shell renormalisation scheme. A first measurement at HERA is made of the light quark weak couplings to the Z boson and a possible contribution of right-handed isospin components to the weak couplings is investigated.

A Determination of Electroweak Parameters at HERA

CERN Document Server

Aktas, A.; Anthonis, T.; Aplin, S.; Asmone, A.; Astvatsatourov, A.; Babaev, A.; Backovic, S.; Bahr, J.; Baghdasaryan, A.; Baranov, P.; Barrelet, E.; Bartel, W.; Baudrand, S.; Baumgartner, S.; Becker, J.; Beckingham, M.; Behnke, O.; Behrendt, O.; Belousov, A.; Berger, Ch.; Berger, N.; Bizot, J.C.; Boenig, M.-O.; Boudry, V.; Bracinik, J.; Brandt, G.; Brisson, V.; Brown, D.P.; Bruncko, D.; Busser, F.W.; Bunyatyan, A.; Buschhorn, G.; Bystritskaya, L.; Campbell, A.J.; Caron, S.; Cassol-Brunner, F.; Cerny, K.; Cerny, V.; Chekelian, V.; Contreras, J.G.; Coughlan, J.A.; Cox, B.E.; Cozzika, G.; Cvach, J.; Dainton, J.B.; Dau, W.D.; Daum, K.; de Boer, Y.; Delcourt, B.; De Roeck, A.; Desch, K.; De Wolf, E.A.; Diaconu, C.; Dodonov, V.; Dubak, A.; Eckerlin, Guenter; Efremenko, V.; Egli, S.; Eichler, R.; Eisele, F.; Ellerbrock, M.; Erdmann, W.; Essenov, S.; Falkewicz, A.; Faulkner, P.J.W.; Favart, L.; Fedotov, A.; Felst, R.; Ferencei, J.; Finke, L.; Fleischer, M.; Fleischmann, P.; Fleming, Y.H.; Flucke, G.; Fomenko, A.; Foresti, I.; Franke, G.; Frisson, T.; Gabathuler, E.; Garutti, E.; Gayler, J.; Gerlich, C.; Ghazaryan, Samvel; Ginzburgskaya, S.; Glazov, A.; Glushkov, I.; Goerlich, L.; Goettlich, M.; Gogitidze, N.; Gorbounov, S.; Goyon, C.; Grab, C.; Greenshaw, T.; Gregori, M.; Grell, B.R.; Grindhammer, Guenter; Gwilliam, C.; Haidt, D.; Hajduk, L.; Hansson, M.; Heinzelmann, G.; Henderson, R.C.W.; Henschel, H.; Henshaw, O.; Herrera, G.; Hildebrandt, M.; Hiller, K.H.; Hoffmann, D.; Horisberger, R.; Hovhannisyan, A.; Hreus, T.; Hussain, S.; Ibbotson, M.; Ismail, M.; Jacquet, M.; Janauschek, L.; Janssen, X.; Jemanov, V.; Jonsson, L.; Johnson, D.P.; Jung, Andreas Werner; Jung, H.; Kapichine, M.; Katzy, J.; Keller, N.; Kenyon, I.R.; Kiesling, Christian M.; Klein, M.; Kleinwort, C.; Klimkovich, T.; Kluge, T.; Knies, G.; Knutsson, A.; Korbel, V.; Kostka, P.; Krastev, K.; Kretzschmar, J.; Kropivnitskaya, A.; Kruger, K.; Kuckens, J.; Landon, M.P.J.; Lange, W.; Lastovicka, T.; Lastovicka-Medin, G.; Laycock, P.; Lebedev, A.; Leibenguth, G.; Lendermann, V.; Levonian, S.; Lindfeld, L.; Lipka, K.; Liptaj, A.; List, B.; Lobodzinska, E.; Loktionova, N.; Lopez-Fernandez, R.; Lubimov, V.; Lucaci-Timoce, A.-I.; Lueders, H.; Luke, D.; Lux, T.; Lytkin, L.; Makankine, A.; Malden, N.; Malinovski, E.; Mangano, S.; Marage, P.; Marshall, R.; Martisikova, M.; Martyn, H.-U.; Maxeld, S.J.; Meer, D.; Mehta, A.; Meier, K.; Meyer, A.B.; Meyer, H.; Meyer, J.; Mikocki, S.; Milcewicz-Mika, I.; Milstead, D.; Mladenov, D.; Mohamed, A.; Moreau, F.; Morozov, A.; Morris, J.V.; Mozer, Matthias Ulrich; Muller, K.; Murin, P.; Nankov, K.; Naroska, B.; Naumann, Th.; Newman, Paul R.; Niebuhr, C.; Nikiforov, A.; Nikitin, D.; Nowak, G.; Nozicka, M.; Oganezov, R.; Olivier, B.; Olsson, J.E.; Osman, S.; Ozerov, D.; Palichik, V.; Panagoulias, I.; Papadopoulou, T.; Pascaud, C.; Patel, G.D.; Peez, M.; Perez, E.; Perez-Astudillo, D.; Perieanu, A.; Petrukhin, A.; Pitzl, D.; Placakyte, R.; Portheault, B.; Povh, B.; Prideaux, P.; Raicevic, N.; Reimer, P.; Rimmer, A.; Risler, C.; Rizvi, E.; Robmann, P.; Roland, B.; Roosen, R.; Rostovtsev, A.; Rurikova, Z.; Rusakov, S.; Salvaire, F.; Sankey, D.P.C.; Sauvan, E.; Schatzel, S.; Schilling, F.-P.; Schmidt, S.; Schmitt, S.; Schmitz, C.; Schoeffel, L.; Schoning, A.; Schultz-Coulon, H.-C.; Sedlak, K.; Sefkow, F.; Shaw-West, R.N.; Sheviakov, I.; Shtarkov, L.N.; Sloan, T.; Smirnov, P.; Soloviev, Y.; South, D.; Spaskov, V.; Specka, Arnd E.; Stella, B.; Stiewe, J.; Strauch, I.; Straumann, U.; Tchoulakov, V.; Thompson, Graham; Thompson, P.D.; Tomasz, F.; Traynor, D.; Truoel, Peter; Tsakov, I.; Tsipolitis, G.; Tsurin, I.; Turnau, J.; Tzamariudaki, E.; Urban, Marcel; Usik, A.; Utkin, D.; Valkar, S.; Valkarova, A.; Vallee, C.; Van Mechelen, P.; Vargas Trevino, A.; Vazdik, Y.; Veelken, C.; Vest, A.; Vinokurova, S.; Volchinski, V.; Vujicic, B.; Wacker, K.; Wagner, J.; Weber, G.; Weber, R.; Wegener, D.; Werner, C.; Werner, N.; Wessels, M.; Wessling, B.; Wigmore, C.; Wissing, Ch.; Wolf, R.; Wunsch, E.; Xella, S.; Yan, W.; Yeganov, V.; Zacek, J.; Zalesak, J.; Zhang, Z.; Zhelezov, A.; Zhokin, A.; Zhu, Y.C.; Zimmermann, J.; Zimmermann, T.; Zohrabyan, H.; Zomer, F.

2006-01-01

Using the deep inelastic e^+p and e^-p charged and neutral current scattering cross sections previously published, a combined electroweak and QCD analysis is performed to determine electroweak parameters accounting for their correlation with parton distributions. The data used have been collected by the H1 experiment in 1994-2000 and correspond to an integrated luminosity of 117.2 pb^{-1}. A measurement is obtained of the W propagator mass in charged current ep scattering. The weak mixing angle sin^2 theta_W is determined in the on-mass-shell renormalisation scheme. A first measurement at HERA is made of the light quark weak couplings to the Z^0 boson and a possible contribution of right-handed isospin components to the weak couplings is investigated.

Determination of Morphological Parameters of Supported Gold Nanoparticles: Comparison of AFM Combined with Optical Spectroscopy and Theoretical Modeling versus TEM

Directory of Open Access Journals (Sweden)

Frank Hubenthal

2012-07-01

Full Text Available The morphology of small gold particles prepared by Volmer–Weber growth on sapphire substrates have been investigated by two different characterization techniques. First, by non-extensive atomic force microscopy (AFM in combination with optical spectroscopy and modeling of the optical properties using a theoretical model, recently developed in our group. Second, by extensive transmission electron microscopy (TEM. Comparing the results obtained with both techniques demonstrate that for small gold nanoparticles within the quasistatic limit, the morphological properties can be precisely determined by an appropriate theoretical modeling of the optical properties in combination with simple AFM measurements. The apparent mean axial ratio of the nanoparticles, i.e., the axial ratio that corresponds to the center frequency of the ensemble plasmon resonance, is obtained easily from the extinction spectrum. The mean size is determined by the nanoparticle number density and the amount of deposited material, measured by AFM and a quartz micro balance, respectively. To extract the most probable axial ratio of the nanoparticle ensemble, i.e., the axial ratio that corresponds to the most probable nanoparticle size in the ensemble, we apply the new theoretical model, which allows to extract the functional dependence of the nanoparticle shape on its size. The morphological parameters obtained with this procedure will be afterwards compared to extensive TEM measurements. The results obtained with both techniques yield excellent agreement. For example, the lateral dimensions of the nanoparticles after deposition of 15.2 × 1015 atoms/cm2 of gold has been compared. While a mean lateral diameter of (13 ± 2 nm has been extracted from AFM, optical spectroscopy and modeling, a value of (12 ± 2 nm is derived from TEM. The consistency of the results demonstrate the precision of our new model. Moreover, since our theoretical model allows to extract the functional

Modeling sugarcane yield with a process-based model from site to continental scale: uncertainties arising from model structure and parameter values

Science.gov (United States)

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

2014-06-01

Agro-land surface models (agro-LSM) have been developed from the integration of specific crop processes into large-scale generic land surface models that allow calculating the spatial distribution and variability of energy, water and carbon fluxes within the soil-vegetation-atmosphere continuum. When developing agro-LSM models, particular attention must be given to the effects of crop phenology and management on the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty of agro-LSM models is related to their usually large number of parameters. In this study, we quantify the parameter-values uncertainty in the simulation of sugarcane biomass production with the agro-LSM ORCHIDEE-STICS, using a multi-regional approach with data from sites in Australia, La Réunion and Brazil. In ORCHIDEE-STICS, two models are chained: STICS, an agronomy model that calculates phenology and management, and ORCHIDEE, a land surface model that calculates biomass and other ecosystem variables forced by STICS phenology. First, the parameters that dominate the uncertainty of simulated biomass at harvest date are determined through a screening of 67 different parameters of both STICS and ORCHIDEE on a multi-site basis. Secondly, the uncertainty of harvested biomass attributable to those most sensitive parameters is quantified and specifically attributed to either STICS (phenology, management) or to ORCHIDEE (other ecosystem variables including biomass) through distinct Monte Carlo runs. The uncertainty on parameter values is constrained using observations by calibrating the model independently at seven sites. In a third step, a sensitivity analysis is carried out by varying the most sensitive parameters to investigate their effects at continental scale. A Monte Carlo sampling method associated with the calculation of partial ranked correlation coefficients is used to quantify the sensitivity of harvested biomass to input

Identification of parameters of discrete-continuous models

International Nuclear Information System (INIS)

Cekus, Dawid; Warys, Pawel

2015-01-01

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

Identification of parameters of discrete-continuous models

Energy Technology Data Exchange (ETDEWEB)

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

2015-03-10

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

Site-specific parameter values for the Nuclear Regulatory Commission's food pathway dose model

International Nuclear Information System (INIS)

Hamby, D.M.

1992-01-01

Routine operations at the Savannah River Site (SRS) in Western South Carolina result in radionuclide releases to the atmosphere and to the Savannah River. The resulting radiation doses to the off-site maximum individual and the off-site population within 80 km of the SRS are estimated on a yearly basis. These estimates are currently generated using dose models prescribed for the commercial nuclear power industry by the Nuclear Regulatory Commission (NRC). The NRC provides default values for dose-model parameters for facilities without resources to develop site-specific values. A survey of land- and water-use characteristics for the Savannah River area has been conducted to determine site-specific values for water recreation, consumption, and agricultural parameters used in the NRC Regulatory Guide 1.109 (1977) dosimetric models. These site parameters include local characteristics of meat, milk, and vegetable production; recreational and commercial activities on the Savannah River; and meat, milk, vegetable, and seafood consumption rates. This paper describes how parameter data were obtained at the Savannah River Site and the impacts of such data on off-site dose. Dose estimates using site-specific parameter values are compared to estimates using the NRC default values

Study of vector boson decay and determination of the Standard Model parameters at hadronic colliders

International Nuclear Information System (INIS)

Amidei, D.

1991-01-01

The power of the detectors and the datasets at hadronic colliders begins to allow measurement of the electroweak parameters with a precision that confronts the perturbative corrections to the theory. Recent measurements of M z , M w , and sin θ w by CDF and UA2 are reviewed, with some emphasis on how experimental precision is achieved, and some discussion of the import for the specifications of the Standard Model. 14 refs., 10 figs., 4 tabs

Application of Time-series Model to Predict Groundwater Quality Parameters for Agriculture: (Plain Mehran Case Study)

Science.gov (United States)

Mehrdad Mirsanjari, Mir; Mohammadyari, Fatemeh

2018-03-01

Underground water is regarded as considerable water source which is mainly available in arid and semi arid with deficient surface water source. Forecasting of hydrological variables are suitable tools in water resources management. On the other hand, time series concepts is considered efficient means in forecasting process of water management. In this study the data including qualitative parameters (electrical conductivity and sodium adsorption ratio) of 17 underground water wells in Mehran Plain has been used to model the trend of parameters change over time. Using determined model, the qualitative parameters of groundwater is predicted for the next seven years. Data from 2003 to 2016 has been collected and were fitted by AR, MA, ARMA, ARIMA and SARIMA models. Afterward, the best model is determined using information criterion or Akaike (AIC) and correlation coefficient. After modeling parameters, the map of agricultural land use in 2016 and 2023 were generated and the changes between these years were studied. Based on the results, the average of predicted SAR (Sodium Adsorption Rate) in all wells in the year 2023 will increase compared to 2016. EC (Electrical Conductivity) average in the ninth and fifteenth holes and decreases in other wells will be increased. The results indicate that the quality of groundwater for Agriculture Plain Mehran will decline in seven years.

BANYAN. IV. Fundamental parameters of low-mass star candidates in nearby young stellar kinematic groups—isochronal age determination using magnetic evolutionary models

Energy Technology Data Exchange (ETDEWEB)

Malo, Lison; Doyon, René; Albert, Loïc; Lafrenière, David; Artigau, Étienne; Gagné, Jonathan [Département de physique and Observatoire du Mont-Mégantic, Université de Montréal, Montréal, QC H3C 3J7 (Canada); Feiden, Gregory A. [Department of Physics and Astronomy, Uppsala University, Box 516, SE-751 20 Uppsala (Sweden); Riedel, Adric, E-mail: malo@cfht.hawaii.edu, E-mail: doyon@astro.umontreal.ca [Department of Astrophysics, American Museum of Natural History, Central Park West at 79th Street, New York, NY 10024 (United States)

2014-09-01

Based on high-resolution optical spectra obtained with ESPaDOnS at Canada-France-Hawaii Telescope, we determine fundamental parameters (T {sub eff}, R, L {sub bol}, log g, and metallicity) for 59 candidate members of nearby young kinematic groups. The candidates were identified through the BANYAN Bayesian inference method of Malo et al., which takes into account the position, proper motion, magnitude, color, radial velocity, and parallax (when available) to establish a membership probability. The derived parameters are compared to Dartmouth magnetic evolutionary models and field stars with the goal of constraining the age of our candidates. We find that, in general, low-mass stars in our sample are more luminous and have inflated radii compared to older stars, a trend expected for pre-main-sequence stars. The Dartmouth magnetic evolutionary models show a good fit to observations of field K and M stars, assuming a magnetic field strength of a few kG, as typically observed for cool stars. Using the low-mass members of the β Pictoris moving group, we have re-examined the age inconsistency problem between lithium depletion age and isochronal age (Hertzspring-Russell diagram). We find that the inclusion of the magnetic field in evolutionary models increases the isochronal age estimates for the K5V-M5V stars. Using these models and field strengths, we derive an average isochronal age between 15 and 28 Myr and we confirm a clear lithium depletion boundary from which an age of 26 ± 3 Myr is derived, consistent with previous age estimates based on this method.

Identifying the connective strength between model parameters and performance criteria

Directory of Open Access Journals (Sweden)

B. Guse

2017-11-01

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

Determination of charged particle beam parameters with taking into account of space charge

International Nuclear Information System (INIS)

Ishkhanov, B.S.; Poseryaev, A.V.; Shvedunov, V.I.

2005-01-01

One describes a procedure to determine the basic parameters of a paraxial axially-symmetric beam of charged particles taking account of space charge contribution. The described procedure is based on application of the general equation for beam envelope. Paper presents data on its convergence and resistance to measurement errors. The position determination error of crossover (stretching) and radius of beam in crossover is maximum 15% , while the emittance determination error depends on emittance and space charge correlation. The introduced procedure was used to determine parameters of the available electron gun 20 keV energy beam with 0.64 A current. The derived results turned to agree closely with the design parameters [ru

Agricultural and Environmental Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

Kaylie Rasmuson; Kurt Rautenstrauch

2003-01-01

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

Determination of electrodebiles parameters of quark b; Determinacion de los parametros electrodebiles del quark b

Energy Technology Data Exchange (ETDEWEB)

Chamizo Llatas, M.

1995-07-01

In the present work we analyze the process e{sup e{yields}}bb with the data collected during 1991 and 1992 by the Z,3 detector situated in the LEP e{sup es}torage-ring (CERN). From the measurements of the cross-sections and the charge asymmetry we determine the parameters of the b quark in the framework of the Standard Model. Finally, we parametrize the possible deviations from the model an obtain upper and lower. limits for the mass of the t quark. (Author) 23 refs.

Zener Diode Compact Model Parameter Extraction Using Xyce-Dakota Optimization.

Energy Technology Data Exchange (ETDEWEB)

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

2017-12-01

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

Brownian motion model with stochastic parameters for asset prices

Science.gov (United States)

Ching, Soo Huei; Hin, Pooi Ah

2013-09-01

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

Study on Parameters Modeling of Wind Turbines Using SCADA Data

Directory of Open Access Journals (Sweden)

Yonglong YAN

2014-08-01

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

Parameter identification in a generalized time-harmonic Rayleigh damping model for elastography.

Directory of Open Access Journals (Sweden)

Elijah E W Van Houten

Full Text Available The identifiability of the two damping components of a Generalized Rayleigh Damping model is investigated through analysis of the continuum equilibrium equations as well as a simple spring-mass system. Generalized Rayleigh Damping provides a more diversified attenuation model than pure Viscoelasticity, with two parameters to describe attenuation effects and account for the complex damping behavior found in biological tissue. For heterogeneous Rayleigh Damped materials, there is no equivalent Viscoelastic system to describe the observed motions. For homogeneous systems, the inverse problem to determine the two Rayleigh Damping components is seen to be uniquely posed, in the sense that the inverse matrix for parameter identification is full rank, with certain conditions: when either multi-frequency data is available or when both shear and dilatational wave propagation is taken into account. For the multi-frequency case, the frequency dependency of the elastic parameters adds a level of complexity to the reconstruction problem that must be addressed for reasonable solutions. For the dilatational wave case, the accuracy of compressional wave measurement in fluid saturated soft tissues becomes an issue for qualitative parameter identification. These issues can be addressed with reasonable assumptions on the negligible damping levels of dilatational waves in soft tissue. In general, the parameters of a Generalized Rayleigh Damping model are identifiable for the elastography inverse problem, although with more complex conditions than the simpler Viscoelastic damping model. The value of this approach is the additional structural information provided by the Generalized Rayleigh Damping model, which can be linked to tissue composition as well as rheological interpretations.

Seven-parameter statistical model for BRDF in the UV band.

Science.gov (United States)

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

2012-05-21

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

Determination of kinetic parameters in the pyrolysis operation and thermal behavior of Prosopis juliflora using thermogravimetric analysis.

Science.gov (United States)

Chandrasekaran, Arunkumar; Ramachandran, Sethumadhavan; Subbiah, Senthilmurugan

2017-06-01

This paper deals with the pyrolysis of Prosopis juliflora fuelwood using thermogravimetric analysis to determine the kinetic parameters at six different heating rates of 2, 5, 10, 15, 20 and 25°C/min. The activation energy of pyrolysis was calculated using different methods, namely Kissinger, Kissinger-Akahira-Sunose, Ozawa-Flynn-Wall and Friedman model and corresponding calculated activation energy were found to be 164.6, 204, 203.2, and 219.3kJ/mol, respectively for each method. The three-pseudo component model was applied to calculate the following three kinetic parameters: activation energy, pre-exponential factor and order of reaction. The experimental results were validated with model prediction for all the six heating rates. The three-pseudo component model is able to predict experimental results much accurately while considering variable order reaction model (n≠1). Copyright © 2017 Elsevier Ltd. All rights reserved.

Lumped-parameter Model of a Bucket Foundation

DEFF Research Database (Denmark)

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

2009-01-01

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

Seasonal variation of photosynthetic model parameters and leaf area index from global Fluxnet eddy covariance data

NARCIS (Netherlands)

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

2011-01-01

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

Source term modelling parameters for Project-90

International Nuclear Information System (INIS)

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

1992-04-01

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

Agricultural and Environmental Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

Kaylie Rasmuson; Kurt Rautenstrauch

2003-06-20

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

Sensitivity of tumor motion simulation accuracy to lung biomechanical modeling approaches and parameters.

Science.gov (United States)

Tehrani, Joubin Nasehi; Yang, Yin; Werner, Rene; Lu, Wei; Low, Daniel; Guo, Xiaohu; Wang, Jing

2015-11-21

Finite element analysis (FEA)-based biomechanical modeling can be used to predict lung respiratory motion. In this technique, elastic models and biomechanical parameters are two important factors that determine modeling accuracy. We systematically evaluated the effects of lung and lung tumor biomechanical modeling approaches and related parameters to improve the accuracy of motion simulation of lung tumor center of mass (TCM) displacements. Experiments were conducted with four-dimensional computed tomography (4D-CT). A Quasi-Newton FEA was performed to simulate lung and related tumor displacements between end-expiration (phase 50%) and other respiration phases (0%, 10%, 20%, 30%, and 40%). Both linear isotropic and non-linear hyperelastic materials, including the neo-Hookean compressible and uncoupled Mooney-Rivlin models, were used to create a finite element model (FEM) of lung and tumors. Lung surface displacement vector fields (SDVFs) were obtained by registering the 50% phase CT to other respiration phases, using the non-rigid demons registration algorithm. The obtained SDVFs were used as lung surface displacement boundary conditions in FEM. The sensitivity of TCM displacement to lung and tumor biomechanical parameters was assessed in eight patients for all three models. Patient-specific optimal parameters were estimated by minimizing the TCM motion simulation errors between phase 50% and phase 0%. The uncoupled Mooney-Rivlin material model showed the highest TCM motion simulation accuracy. The average TCM motion simulation absolute errors for the Mooney-Rivlin material model along left-right, anterior-posterior, and superior-inferior directions were 0.80 mm, 0.86 mm, and 1.51 mm, respectively. The proposed strategy provides a reliable method to estimate patient-specific biomechanical parameters in FEM for lung tumor motion simulation.

Multivariate modelling of prostate cancer combining magnetic resonance derived T2, diffusion, dynamic contrast-enhanced and spectroscopic parameters

Energy Technology Data Exchange (ETDEWEB)

Riches, S.F.; Payne, G.S.; Morgan, V.A.; DeSouza, N.M. [Royal Marsden NHS Foundation Trust and Institute of Cancer Research, CRUK and EPSRC Cancer Imaging Centre, Sutton, Surrey (United Kingdom); Dearnaley, D. [Royal Marsden NHS Foundation Trust and Institute of Cancer Research, Department of Urology and Department of Academic Radiotherapy, Sutton, Surrey (United Kingdom); Morgan, S. [The Ottawa Hospital Cancer Centre and the University of Ottawa, Division of Radiation Oncology, Ottawa, Ontario (Canada); Partridge, M. [The Institute of Cancer Research, Section of Radiotherapy and Imaging, Sutton, Surrey (United Kingdom); University of Oxford, The Gray Institute for Radiation Oncology and Biology, Oxford (United Kingdom); Livni, N. [Royal Marsden NHS Foundation Trust Chelsea, Department of Histopathology, London (United Kingdom); Ogden, C. [Royal Marsden NHS Foundation Trust Chelsea, Department of Urology, London (United Kingdom)

2015-05-01

The objectives are determine the optimal combination of MR parameters for discriminating tumour within the prostate using linear discriminant analysis (LDA) and to compare model accuracy with that of an experienced radiologist. Multiparameter MRIs in 24 patients before prostatectomy were acquired. Tumour outlines from whole-mount histology, T{sub 2}-defined peripheral zone (PZ), and central gland (CG) were superimposed onto slice-matched parametric maps. T{sub 2,} Apparent Diffusion Coefficient, initial area under the gadolinium curve, vascular parameters (K{sup trans},K{sub ep},V{sub e}), and (choline+polyamines+creatine)/citrate were compared between tumour and non-tumour tissues. Receiver operating characteristic (ROC) curves determined sensitivity and specificity at spectroscopic voxel resolution and per lesion, and LDA determined the optimal multiparametric model for identifying tumours. Accuracy was compared with an expert observer. Tumours were significantly different from PZ and CG for all parameters (all p < 0.001). Area under the ROC curve for discriminating tumour from non-tumour was significantly greater (p < 0.001) for the multiparametric model than for individual parameters; at 90 % specificity, sensitivity was 41 % (MRSI voxel resolution) and 59 % per lesion. At this specificity, an expert observer achieved 28 % and 49 % sensitivity, respectively. The model was more accurate when parameters from all techniques were included and performed better than an expert observer evaluating these data. (orig.)

Determination of kinetic parameters for 123-I thyroid uptake in healthy Japanese

Science.gov (United States)

Kusuhara, Hiroyuki; Maeda, Kazuya

2017-09-01

The purpose of this study was to compare the kinetic parameters for iodide thyroid accumulation in Japanese today with previously reported values. We determined the thyroid uptake of 123-I at 24 hours after the oral administration in healthy male Japanese without any diet restriction. The mean value was 16.1±5.4%, which was similar or rather lower than those previously reported in Japan (1958-1972). Kinetic model analysis was conducted to obtain the clearance for thyroid uptake from the blood circulation. The thyroid uptake clearance of 123-I was 0.540±0.073 ml/min, which was almost similar to those reported previously. There is no obvious difference in the thyroid uptake for 24 hours, and kinetic parameters in healthy Japanese for these 50 years. The fraction of distributed to the thyroid gland is lower than the ICRP reference man, and such difference must be taken into consideration to estimate the radiation exposure upon Fukushima accident in Japan.

Groundwater potentiality mapping using geoelectrical-based aquifer hydraulic parameters: A GIS-based multi-criteria decision analysis modeling approach

Directory of Open Access Journals (Sweden)

Kehinde Anthony Mogaji Hwee San Lim

2017-01-01

Full Text Available This study conducted a robust analysis on acquired 2D resistivity imaging data and borehole pumping test records to optimize groundwater potentiality mapping in Perak province, Malaysia using derived aquifer hydraulic properties. The transverse resistance (TR parameter was determined from the interpreted 2D resistivity imaging data by applying the Dar-Zarrouk parameter equation. Linear regression and GIS techniques were used to regress the estimated values for TR parameters with the aquifer transmissivity values extracted from the geospatially produced BPT records-based aquifer transmissivity map to develop the aquifer transmissivity parameter predictive (ATPP model. The reliability evaluated ATPP model using the Theil inequality coefficient measurement approach was used to establish geoelectrical-based hydraulic parameters (GHP modeling equations for the modeling of transmissivity (Tr, hydraulic conductivity (K, storativity (St, and hydraulic diffusivity (D properties. The applied GHP modeling equation results to the delineated aquifer media was used to produce aquifer potential conditioning factor maps for Tr, K, St, and D. The maps were modeled to develop an aquifer potential mapping index (APMI model via applying the multi-criteria decision analysis-analytic hierarchy process principle. The area groundwater reservoir productivity potential model map produced based on the processed APMI model estimates in the GIS environment was found to be 71% accurate. This study establishes a good alternative approach to determine aquifer hydraulic parameters even in areas where pumping test information is unavailable using a cost effective geophysical data. The produced map can be explored for hydrological decision making.

The importance of variables and parameters in radiolytic chemical kinetics modeling

International Nuclear Information System (INIS)

Piepho, M.G.; Turner, P.J.; Reimus, P.W.

1989-01-01

Many of the pertinent radiochemical reactions are not completely understood, and most of the associated rate constants are poorly characterized. To help identify the important radiochemical reactions, rate constants, species, and environmental conditions, an importance theory code, SWATS (Sensitivitiy With Adjoint Theory-Sparse version)-LOOPCHEM, has been developed for the radiolytic chemical kinetics model in the radiolysis code LOOPCHEM. The LOOPCHEM code calculates the concentrations of various species in a radiolytic field over time. The SWATS-LOOPCHEM code efficiently calculates: the importance (relative to a defined response of interest) of each species concentration over time, the sensitivity of each parameter of interest, and the importance of each equation in the radiolysis model. The calculated results will be used to guide future experimental and modeling work for determining the importance of radiolysis on waste package performance. A demonstration (the importance of selected concentrations and the sensitivities of selected parameters) of the SWATS-LOOPCHEM code is provided for illustrative purposes

Bayesian estimation of parameters in a regional hydrological model

Directory of Open Access Journals (Sweden)

K. Engeland

2002-01-01

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

Models and parameters for environmental radiological assessments

International Nuclear Information System (INIS)

Miller, C.W.

1983-01-01

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

Parameter Estimation of Nonlinear Models in Forestry.

OpenAIRE

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

1999-01-01

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

Parameter values for the long-term nuclear waste management food chain model LIMCAL

International Nuclear Information System (INIS)

Zach, Reto.

1982-09-01

Eighteen parameters of LIMCAL, a comprehensive food chain model for predicting ICRP 26 50-year committed effective dose equivalents to man due to long-term nuclear waste management are reviewed. The parameters are: soil bulk density, plowlayer depth, soil surface layer depth, resusupension factor, atmospheric dust load, deposition velocity, plant interception fraction, plant environmental half-time, translocation factor, time of above-ground exposure, plant yield, holdup time, animals' feed consumption rate, animals' water consumption rate, man's water consumption rate, food type calorie conversion factors, man's total caloric intake rate and food type calorie fractions. LIMCAL has both traditional and unique parameters. The former occur in most of the currently used assessment models for nuclear installations, whereas the latter do not. For each of the parameters of LIMCAL, a suitable generic value for long-term nuclear waste management was determined. Thus, the general literature and the values currently used or recommended by various agencies were reviewed

Identification of the most sensitive parameters in the activated sludge model implemented in BioWin software.

Science.gov (United States)

Liwarska-Bizukojc, Ewa; Biernacki, Rafal

2010-10-01

In order to simulate biological wastewater treatment processes, data concerning wastewater and sludge composition, process kinetics and stoichiometry are required. Selection of the most sensitive parameters is an important step of model calibration. The aim of this work is to verify the predictability of the activated sludge model, which is implemented in BioWin software, and select its most influential kinetic and stoichiometric parameters with the help of sensitivity analysis approach. Two different measures of sensitivity are applied: the normalised sensitivity coefficient (S(i,j)) and the mean square sensitivity measure (delta(j)(msqr)). It occurs that 17 kinetic and stoichiometric parameters of the BioWin activated sludge (AS) model can be regarded as influential on the basis of S(i,j) calculations. Half of the influential parameters are associated with growth and decay of phosphorus accumulating organisms (PAOs). The identification of the set of the most sensitive parameters should support the users of this model and initiate the elaboration of determination procedures for the parameters, for which it has not been done yet. Copyright 2010 Elsevier Ltd. All rights reserved.

Learning about physical parameters: the importance of model discrepancy

International Nuclear Information System (INIS)

Brynjarsdóttir, Jenný; O'Hagan, Anthony

2014-01-01

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

Wind Farm Decentralized Dynamic Modeling With Parameters

DEFF Research Database (Denmark)

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

2010-01-01

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

Parameters of Models of Structural Transformations in Alloy Steel Under Welding Thermal Cycle

Science.gov (United States)

Kurkin, A. S.; Makarov, E. L.; Kurkin, A. B.; Rubtsov, D. E.; Rubtsov, M. E.

2017-05-01

A mathematical model of structural transformations in an alloy steel under the thermal cycle of multipass welding is suggested for computer implementation. The minimum necessary set of parameters for describing the transformations under heating and cooling is determined. Ferritic-pearlitic, bainitic and martensitic transformations under cooling of a steel are considered. A method for deriving the necessary temperature and time parameters of the model from the chemical composition of the steel is described. Published data are used to derive regression models of the temperature ranges and parameters of transformation kinetics in alloy steels. It is shown that the disadvantages of the active visual methods of analysis of the final phase composition of steels are responsible for inaccuracy and mismatch of published data. The hardness of a specimen, which correlates with some other mechanical properties of the material, is chosen as the most objective and reproducible criterion of the final phase composition. The models developed are checked by a comparative analysis of computational results and experimental data on the hardness of 140 alloy steels after cooling at various rates.

The determination of parameters of the upper atmosphere by the radio-meteor measurements

Science.gov (United States)

Shamukov, Damir; Fahrutdinova, Antonina; Nugmanov, Ildus

Study of the parameters of the upper atmosphere on the basis of amplitude-time characteristics of meteor ionization. Together with various methods meteor observations (optical, photographic, visual, spectral, television), the most effective modern method of studying meteors means is radar. The development of modern radar technology allows us to apply this tool to monitor meteors. This method allows to determine the parameters of temperature and atmospheric pressure. Actual issue is the development of methods of determining the coefficient of ambipolar diffusion, pressure, density and temperature of the atmosphere in the meteor zone. Graph of amplitude-time characteristic has the exponential form. This fact allows to determine the coefficient of ambipolar diffusion. New algorithm for estimation of the ambipolar diffusion coefficient based on a set of statistical methods and techniques of digital signal processing. There are decomposition of data on singular values and Prony's method. This method of modeling the sample data as a linear combination of exponential. Prony’s method approximates the amplitude-time characteristics of using a deterministic exponential model. Input data is amplitude-time characteristics of the meteor trail x[1]…x[N]. The method allows to estimate x[n] p-membered exponential model: begin{center} x[n]=Sigma2A_{k}exp[a _{k}(n-1)]Cos[2Pif_{k}(n-1)T+Fi_{k}] (1) end{center} 1<=n<=N, T - time range in seconds, A_{k} and a_{k} - amplitude and damping coefficient, f_{k} and Fi_{k} - frequency and initial phase. The equation describing the decay of radio signal: begin{center} A=A_{0}exp(-16Pi^{2}$D_{a}t/λ (2) ). (2) lambdaλ - radar wavelength. The output of the algorithm - the ambipolar diffusion coefficient values D_{a}. begin{center} T=0.5lnD-T_{0}+mg/2kT_{0} (3) Last equation allows to obtain temperature values using the coefficient of ambipolar diffusion depends on the height.

Research on CO2 ejector component efficiencies by experiment measurement and distributed-parameter modeling

International Nuclear Information System (INIS)

Zheng, Lixing; Deng, Jianqiang

2017-01-01

Highlights: • The ejector distributed-parameter model is developed to study ejector efficiencies. • Feasible component and total efficiency correlations of ejector are established. • New efficiency correlations are applied to obtain dynamic characteristics of EERC. • More suitable fixed efficiency value can be determined by the proposed correlations. - Abstract: In this study we combine the experimental measurement data and the theoretical model of ejector to determine CO 2 ejector component efficiencies including the motive nozzle, suction chamber, mixing section, diffuser as well as the total ejector efficiency. The ejector is modeled utilizing the distributed-parameter method, and the flow passage is divided into a number of elements and the governing equations are formulated based on the differential equation of mass, momentum and energy conservation. The efficiencies of ejector are investigated under different ejector geometric parameters and operational conditions, and the corresponding empirical correlations are established. Moreover, the correlations are incorporated into a transient model of transcritical CO 2 ejector expansion refrigeration cycle (EERC) and the dynamic simulations is performed based on variable component efficiencies and fixed values. The motive nozzle, suction chamber, mixing section and diffuser efficiencies vary from 0.74 to 0.89, 0.86 to 0.96, 0.73 to 0.9 and 0.75 to 0.95 under the studied conditions, respectively. The response diversities of suction flow pressure and discharge pressure are obvious between the variable efficiencies and fixed efficiencies referring to the previous studies, while when the fixed value is determined by the presented correlations, their response differences are basically the same.

Optimizing incomplete sample designs for item response model parameters

NARCIS (Netherlands)

van der Linden, Willem J.

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

A Test Procedure for Determining Models of LV Equipment

NARCIS (Netherlands)

Cuk, Vladimir; Cobben, Joseph F.G.; Kling, Wil L.; Timens, R.B.; Leferink, Frank Bernardus Johannes

2009-01-01

An automated test technique for determining parameters of low voltage equipment is presented in the paper. The aim of this research is to obtain simple models of household, office and industrial equipment which could be used to predict power quality problems during the design of low voltage

Modelling of bio-optical parameters of open ocean waters

Directory of Open Access Journals (Sweden)

Vadim N. Pelevin

2001-12-01

Full Text Available An original method for estimating the concentration of chlorophyll pigments, absorption of yellow substance and absorption of suspended matter without pigments and yellow substance in detritus using spectral diffuse attenuation coefficient for downwelling irradiance and irradiance reflectance data has been applied to sea waters of different types in the open ocean (case 1. Using the effective numerical single parameter classification with the water type optical index m as a parameter over the whole range of the open ocean waters, the calculations have been carried out and the light absorption spectra of sea waters tabulated. These spectra are used to optimize the absorption models and thus to estimate the concentrations of the main admixtures in sea water. The value of m can be determined from direct measurements of the downward irradiance attenuation coefficient at 500 nm or calculated from remote sensing data using the regressions given in the article. The sea water composition can then be readily estimated from the tables given for any open ocean area if that one parameter m characterizing the basin is known.

Determination of trapping parameters and the chemical diffusion coefficient from hydrogen permeation experiments

International Nuclear Information System (INIS)

Svoboda, J.; Mori, G.; Prethaler, A.; Fischer, F.D.

2014-01-01

Highlights: • A modeling study for diffusion of hydrogen with traps is presented. • Introduction of a new chemical diffusion coefficient. • Density of traps and average depth of traps can be determined. • Lattice diffusion and sub-surface concentration of atomic hydrogen can be determined. - Abstract: An improved diffusion theory accounting for trapping effects is applied to evaluation of hydrogen permeation experiments performed for pure iron and pearlitic and martensitic steels. The trapping parameters as molar volume and depth of traps are determined by fitting experiments by simulations based on the theory. The concentration-dependent chemical diffusion coefficient of hydrogen is extracted indicating that the trapping effect on diffusion in pure iron and pearlitic steel is negligible. However, it is significant for martensitic steel, for which the chemical diffusion coefficient cannot be considered as concentration-independent as it is established in current standards

Environmental Transport Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

M. Wasiolek

2004-01-01

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

Environmental Transport Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

M. Wasiolek

2004-09-10

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

A new trend to determine biochemical parameters by quantitative FRET assays.

Science.gov (United States)

Liao, Jia-yu; Song, Yang; Liu, Yan

2015-12-01

Förster resonance energy transfer (FRET) has been widely used in biological and biomedical research because it can determine molecule or particle interactions within a range of 1-10 nm. The sensitivity and efficiency of FRET strongly depend on the distance between the FRET donor and acceptor. Historically, FRET assays have been used to quantitatively deduce molecular distances. However, another major potential application of the FRET assay has not been fully exploited, that is, the use of FRET signals to quantitatively describe molecular interactive events. In this review, we discuss the use of quantitative FRET assays for the determination of biochemical parameters, such as the protein interaction dissociation constant (K(d)), enzymatic velocity (k(cat)) and K(m). We also describe fluorescent microscopy-based quantitative FRET assays for protein interaction affinity determination in cells as well as fluorimeter-based quantitative FRET assays for protein interaction and enzymatic parameter determination in solution.

Sensitivity of tumor motion simulation accuracy to lung biomechanical modeling approaches and parameters

International Nuclear Information System (INIS)

Tehrani, Joubin Nasehi; Wang, Jing; Yang, Yin; Werner, Rene; Lu, Wei; Low, Daniel; Guo, Xiaohu

2015-01-01

Finite element analysis (FEA)-based biomechanical modeling can be used to predict lung respiratory motion. In this technique, elastic models and biomechanical parameters are two important factors that determine modeling accuracy. We systematically evaluated the effects of lung and lung tumor biomechanical modeling approaches and related parameters to improve the accuracy of motion simulation of lung tumor center of mass (TCM) displacements. Experiments were conducted with four-dimensional computed tomography (4D-CT). A Quasi-Newton FEA was performed to simulate lung and related tumor displacements between end-expiration (phase 50%) and other respiration phases (0%, 10%, 20%, 30%, and 40%). Both linear isotropic and non-linear hyperelastic materials, including the neo-Hookean compressible and uncoupled Mooney–Rivlin models, were used to create a finite element model (FEM) of lung and tumors. Lung surface displacement vector fields (SDVFs) were obtained by registering the 50% phase CT to other respiration phases, using the non-rigid demons registration algorithm. The obtained SDVFs were used as lung surface displacement boundary conditions in FEM. The sensitivity of TCM displacement to lung and tumor biomechanical parameters was assessed in eight patients for all three models. Patient-specific optimal parameters were estimated by minimizing the TCM motion simulation errors between phase 50% and phase 0%. The uncoupled Mooney–Rivlin material model showed the highest TCM motion simulation accuracy. The average TCM motion simulation absolute errors for the Mooney–Rivlin material model along left-right, anterior–posterior, and superior–inferior directions were 0.80 mm, 0.86 mm, and 1.51 mm, respectively. The proposed strategy provides a reliable method to estimate patient-specific biomechanical parameters in FEM for lung tumor motion simulation. (paper)

Determination of the cell parameters of β-quartz at 1003 K by neutron multiple diffraction

International Nuclear Information System (INIS)

Campos, Luiz Carlos de

2002-01-01

In this work, neutron multiple diffraction (NMD) data was employed for the determination of the parameters a and c of the β-quartz hexagonal cell at 1003 K. An experimental 00.1 β-quartz NMD 'Umweg' pattern has been used for the determinations. During the indexing of the β-quartz pattern it was verified that most of the peaks could be classified as either 'good for the determination of the parameter a' or 'good for the determination of the parameter c'. With such a classification, it became possible to employ an iterative process for the determination of both parameters. To attain this purpose, two methods were developed. The first one, named 'absolute method', used angular azimuthal positions of the peaks, related to the origin of the experimental diagram. The second method, named 'relative method', used azimuthal angular differences between two selected peaks. The values obtained for both parameters, in the two methods employed, were found by applying the angular azimuthal positions, for the first method, and the azimuthal angular differences, for the second method, upon appropriate theoretical indexing diagrams. An iterative process was applied in order to obtain the values of the parameters. In this process, the value obtained for one of the parameters was used in the determination of the other parameter. The process continues until both parameters converge. The iterative process was used in both methods. The relative method proved to be better than the absolute method. The best values of the parameters obtained by the relative method were: a 4.99638 ± 0.00057 angstrom and c = 5.46119 ± 0.00044 angstrom. (author)

Application of multi-parameter chorus and plasmaspheric hiss wave models in radiation belt modeling

Science.gov (United States)

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

2017-12-01

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

Modelling hydrodynamic parameters to predict flow assisted corrosion

International Nuclear Information System (INIS)

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

1992-01-01

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

Identifying the effects of parameter uncertainty on the reliability of riverbank stability modelling

Science.gov (United States)

Samadi, A.; Amiri-Tokaldany, E.; Darby, S. E.

2009-05-01

Bank retreat is a key process in fluvial dynamics affecting a wide range of physical, ecological and socioeconomic issues in the fluvial environment. To predict the undesirable effects of bank retreat and to inform effective measures to prevent it, a wide range of bank stability models have been presented in the literature. These models typically express bank stability by defining a factor of safety as the ratio of driving and resisting forces acting on the incipient failure block. These forces are affected by a range of controlling factors that include such aspects as the bank profile (bank height and angle), the geotechnical properties of the bank materials, as well as the hydrological status of the riverbanks. In this paper we evaluate the extent to which uncertainties in the parameterization of these controlling factors feed through to influence the reliability of the resulting bank stability estimate. This is achieved by employing a simple model of riverbank stability with respect to planar failure (which is the most common type of bank stability model) in a series of sensitivity tests and Monte Carlo analyses to identify, for each model parameter, the range of values that induce significant changes in the simulated factor of safety. These identified parameter value ranges are compared to empirically derived parameter uncertainties to determine whether they are likely to confound the reliability of the resulting bank stability calculations. Our results show that parameter uncertainties are typically high enough that the likelihood of generating unreliable predictions is typically very high (> ˜ 80% for predictions requiring a precision of < ± 15%). Because parameter uncertainties are derived primarily from the natural variability of the parameters, rather than measurement errors, much more careful attention should be paid to field sampling strategies, such that the parameter uncertainties and consequent prediction unreliabilities can be quantified more

Generative probabilistic models extend the scope of inferential structure determination

DEFF Research Database (Denmark)

Olsson, Simon; Boomsma, Wouter; Frellsen, Jes

2011-01-01

demonstrate that the use of generative probabilistic models instead of physical forcefields in the Bayesian formalism is not only conceptually attractive, but also improves precision and efficiency. Our results open new vistas for the use of sophisticated probabilistic models of biomolecular structure......Conventional methods for protein structure determination from NMR data rely on the ad hoc combination of physical forcefields and experimental data, along with heuristic determination of free parameters such as weight of experimental data relative to a physical forcefield. Recently, a theoretically...

Elastoplastic constitutive models parameters for unsaturated compacted bentonite sand buffer (BSB)

International Nuclear Information System (INIS)

Priyanto, D.; Man, A.; Dixon, D.; Blatz, J.

2010-01-01

Document available in extended abstract form only. Compacted Bentonite-Sand Buffer (BSB) material is one of the clay based sealing-system components proposed for use in a Canadian Deep Geological Repository (DGR) for used nuclear fuel. BSB is a 50:50 mixture (by dry mass) of bentonite and well-graded silica sand, compacted to a dry density of at least 1.67 Mg/m 3 . Numerical modelling of the evolution of a DGR requires defining of the Hydro-Mechanical (HM) parameters of the BSB. The objective of this paper is to determine the parameters that are needed to utilize an elastoplastic model to describe the BSB. The parameters of the Basic Barcelona Model (BBM) for BSB are determined based on the results of laboratory tests done under both water-saturated and unsaturated conditions. The BBM utilizes three key stress-state variables: net mean stress (p), deviatoric stress (q), and suction (s). Modification of the BBM to improve the prediction of the BSB behaviour is made based on these laboratory test results. Pre-consolidation stress (p o ), stiffness parameters due to changes in p in elastic (?) and plastic (λ(s)) ranges are determined from triaxial test results under isotropic loading, unloading and constant mass conditions with suctions in the range of 0-125 MPa. An increase of s results in an increase of p o and a decrease of λ(s) for s < 30 MPa, and constant po and λ(s) for s > 30 MPa. These data are used to determine the LC-Line. Blatz (2000) and Anderson (2003) concluded that the BSB has clay-dominated behaviour for s < 30 MPa and sand-dominated behaviour for s > 30 MPa. Based on this conclusion, the hardening parameter so of the suction increase yield curve is equal to 30 MPa. Using a measured s-v relationship from shrinkage tests, stiffness parameters for changes in s in the elastic range (?s) are approximately ∼ 0.065 and in the plastic range (λs) are approximately ∼ 0, which is different from the original BBM featuring λs > ?s. The tensile strength

WINKLER'S SINGLE-PARAMETER SUBGRADE MODEL FROM ...

African Journals Online (AJOL)

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Page 1 ... corresponding single-parameter Winkler model presented in this work. Keywords: Heterogeneous subgrade, Reissner's simplified continuum, Shear interaction, Simplified continuum, Winkler ... model in practical applications and its long time familiarity among practical engineers, its usage has endured to this date ...

Integrating retention soil filters into urban hydrologic models - Relevant processes and important parameters

Science.gov (United States)

Bachmann-Machnik, Anna; Meyer, Daniel; Waldhoff, Axel; Fuchs, Stephan; Dittmer, Ulrich

2018-04-01

Retention Soil Filters (RSFs), a form of vertical flow constructed wetlands specifically designed for combined sewer overflow (CSO) treatment, have proven to be an effective tool to mitigate negative impacts of CSOs on receiving water bodies. Long-term hydrologic simulations are used to predict the emissions from urban drainage systems during planning of stormwater management measures. So far no universally accepted model for RSF simulation exists. When simulating hydraulics and water quality in RSFs, an appropriate level of detail must be chosen for reasonable balancing between model complexity and model handling, considering the model input's level of uncertainty. The most crucial parameters determining the resultant uncertainties of the integrated sewer system and filter bed model were identified by evaluating a virtual drainage system with a Retention Soil Filter for CSO treatment. To determine reasonable parameter ranges for RSF simulations, data of 207 events from six full-scale RSF plants in Germany were analyzed. Data evaluation shows that even though different plants with varying loading and operation modes were examined, a simple model is sufficient to assess relevant suspended solids (SS), chemical oxygen demand (COD) and NH4 emissions from RSFs. Two conceptual RSF models with different degrees of complexity were assessed. These models were developed based on evaluation of data from full scale RSF plants and column experiments. Incorporated model processes are ammonium adsorption in the filter layer and degradation during subsequent dry weather period, filtration of SS and particulate COD (XCOD) to a constant background concentration and removal of solute COD (SCOD) by a constant removal rate during filter passage as well as sedimentation of SS and XCOD in the filter overflow. XCOD, SS and ammonium loads as well as ammonium concentration peaks are discharged primarily via RSF overflow not passing through the filter bed. Uncertainties of the integrated

Insight into model mechanisms through automatic parameter fitting: a new methodological framework for model development.

Science.gov (United States)

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

2014-05-20

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

Modelling of intermittent microwave convective drying: parameter sensitivity

Directory of Open Access Journals (Sweden)

Zhang Zhijun

2017-06-01

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

On the determination of the mutual exclusion statistics parameter

Indian Academy of Sciences (India)

On the determination of the mutual exclusion statistics parameter. SAPTARSHI MANDAL. Department of Theoretical Physics, Indian Association for the Cultivation of Science,. 2A&2B Raja S.C. Mullick Road, Jadavpur, Kolkata 700 032, India. E-mail: mandal.saptarshi1@gmail.com. MS received 7 September 2012; revised ...

Determination of the kinetic parameters of BeO using isothermal decay method

International Nuclear Information System (INIS)

Nieto, Juan Azorin; Vega, Claudia Azorin; Montalvo, Teodoro Rivera; Cabrera, Eugenio Torijano

2016-01-01

Most of the existing methods for obtaining the frequency factors make use of the trap depth (activation energy) making some assumptions about the order of the kinetics. This causes inconsistencies in the reported values of trapping parameters due that the values of the activation energy obtained by different methods differ appreciably among them. Then, it is necessary to use a method independent of the trap depth making use of the isothermal luminescence decay (ILD) method. The trapping parameters associated with the prominent glow peak of BeO (280 °C) are reported using ILD method. As a check, the trap parameters are also calculated by glow curve shape (Chen's) method after isolating the prominent glow peak by thermal cleaning technique. Our results show a very good agreement between the trapping parameters calculated by the two methods. ILD method was used for determining the trapping parameters of BeO. Results obtained applying this method are in good agreement with those obtained using other methods, except in the value of the frequency factor. - Highlights: • Kinetic parameters of BeO were determined. • Isothermal decay method was used. • Frecuency factor not agree with those obtained by other methods.

Standard Test Method for Determining the Linearity of a Photovoltaic Device Parameter with Respect To a Test Parameter

CERN Document Server

American Society for Testing and Materials. Philadelphia

2005-01-01

1.1 This test method determines the degree of linearity of a photovoltaic device parameter with respect to a test parameter, for example, short-circuit current with respect to irradiance. 1.2 The linearity determined by this test method applies only at the time of testing, and implies no past or future performance level. 1.3 This test method applies only to non-concentrator terrestrial photovoltaic devices. 1.4 The values stated in SI units are to be regarded as standard. No other units of measurement are included in this standard. 1.5 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

Retrospective forecast of ETAS model with daily parameters estimate

Science.gov (United States)

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

2016-04-01

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

Metodology of identification parameters of models control objects of automatic trailing system

Directory of Open Access Journals (Sweden)

I.V. Zimchuk

2017-04-01

Full Text Available The determining factor for the successful solution of the problem of synthesis of optimal control systems of different processes are adequacy of mathematical model of control object. In practice, the options can differ from the objects taken priori, causing a need to clarification of them. In this context, the article presents the results of the development and application of methods parameters identification of mathematical models of control object of automatic trailing system. The stated problem in the article is solved provided that control object is fully controlled and observed, and a differential equation of control object is known a priori. The coefficients of this equation to be determined. Identifying quality criterion is to minimize the integral value of squared error of identification. The method is based on a description of the dynamics of the object in space state. Equation of identification synthesized using the vector-matrix representation of model. This equation describes the interconnection of coefficients of matrix state and control with inputs and outputs of object. The initial data for calculation are the results of experimental investigation of the reaction of phase coordinates of control object at a typical input signal. The process of calculating the model parameters is reduced to solving the system of equations of the first order each. Application the above approach is illustrated in the example identification of coefficients transfer function of control object first order. Results of digital simulation are presented, they are confirming the justice of set out mathematical calculations. The approach enables to do the identification of models of one-dimensional and multidimensional objects and does not require a large amount of calculation for its implementation. The order of identified model is limited capabilities of measurement phase coordinates of corresponding control object. The practical significance of the work is

Mathematical models in the analysis of quality parameters to the Almendares river

International Nuclear Information System (INIS)

Dominguez, J.; Borroto, J.; Hernandez, A.; Santiago, J.F.; CU)

2003-01-01

The river Almendares, one of the most important water bodies of the Havana City, is very polluted. The analysis of parameters as dissolved oxygen and biochemical oxygen demand is very helpful for the studies aimed to the recovery of the river. There is a growing recognition around the word that the water quality models are very useful tools to plan sanitary strategies for the handling of the contamination. In the present work, the advective, steady- state Streeter and Phelps model was validated to simulate the effect of the multiple-point and distributed sources on the carbonaceous oxygen demand, NH4 and dissolved oxygen. For modeling purposes the section of the river located between the point where the waste water treatment station Maria del Carmen discharges to the river and the Bridge El Bosque, was divided in 11 segments. The use of the 99mTc and the Rodamine WT as tracers allowed determining the hydrodynamic parameters necessary for modeling purposes. The validated model allows to predict the effect of the sanitary strategies on the water quality of the river

Parameter identification in multinomial processing tree models

NARCIS (Netherlands)

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

2010-01-01

Multinomial processing tree models form a popular class of statistical models for categorical data that have applications in various areas of psychological research. As in all statistical models, establishing which parameters are identified is necessary for model inference and selection on the basis

Coffee Bean Grade Determination Based on Image Parameter

Directory of Open Access Journals (Sweden)

F. Ferdiansjah

2011-12-01

Full Text Available Quality standard for coffee as an agriculture commodity in Indonesia uses defect system which is regulated in Standar Nasional Indonesia (SNI for coffee bean, No: 01-2907-1999. In the Defect System standard, coffee bean is classified into six grades, from grade I to grade VI depending on the number of defect found in the coffee bean. Accuracy of this method heavily depends on the experience and the expertise of the human operators. The objective of the research is to develop a system to determine the coffee bean grading based on SNI No: 01-2907-1999. A visual sensor, a webcam connected to a computer, was used for image acquisition of coffee bean image samples, which were placed under uniform illumination of 414.5+2.9 lux. The computer performs feature extraction from parameters of coffee bean image samples in the term of texture (energy, entropy, contrast, homogeneity and color (R mean, G mean, and B mean and determines the grade of coffee bean based on the image parameters by implementing neural network algorithm. The accuracy of system testing for the coffee beans of grade I, II, III, IVA, IVB, V, and VI have the value of 100, 80, 60, 40, 100, 40, and 100%, respectively.

Parameters of importance to determine in geoscientific site studies

International Nuclear Information System (INIS)

Andersson, Johan; Almen, K.E.; Ericsson, L.O.; Karlsson, Fred; Stroem, A.; Fredriksson, Anders; Stanfors, R.

1996-12-01

This report identifies and describes parameters, that may be determined in a site characterization study, for performing functional and safety analyses of a deep rock repository for radioactive wastes. The report discusses data needs for rock engineering and for description of other environmental aspects. It is intended that the report be used as a basis for formulating the criteria of acceptance in evaluating a candidate site. The report describes how different parameters influence the safety function, and how they are evaluated in practice. The logical order of performing measurements, due to the need of in-data and influence on other measurements is also discussed. 65 refs

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)

Interpretation of hydraulic conductivity data and parameter evaluation for groundwater flow models

International Nuclear Information System (INIS)

Niemi, A.

1991-01-01

The report reviews recent developments in evaluating effective permeabilities for groundwater flow models, starting from methods of well test interpretation for and proceeding to the principles of parameter estimation. Basic concepts of parameter evaluation as well as expressions derived for effective permeabilities in traditional porous medium are described. Due to the assumptions made, these do often not apply for fractured media. Specific features of fractured medium are discussed, including approaches used determining the size of a possible REV and questions related to the application of stochastic theories. Due to the difficulties encountered when applying traditional deterministic models for fractured media, stochastic and fracture network approaches have been developed. The application of these techniques is still under development, the main questions to be resolved being related to the scarcity of data

Computational model for real-time determination of tritium inventory in a detritiation installation

International Nuclear Information System (INIS)

Bornea, Anisia; Stefanescu, Ioan; Zamfirache, Marius; Stefan, Iuliana; Sofalca, Nicolae; Bidica, Nicolae

2008-01-01

Full text: At ICIT Rm.Valcea an experimental pilot plant was built having as main objective the development of a technology for detritiation of heavy water processed in the CANDU-type reactors of the nuclear power plant at Cernavoda, Romania. The aspects related to safeguards and safety for such a detritiation installation being of great importance, a complex computational model has been developed. The model allows real-time calculation of tritium inventory in a working installation. The applied detritiation technology is catalyzed isotopic exchange coupled with cryogenic distillation. Computational models for non-steady working conditions have been developed for each process of isotopic exchange. By coupling these processes tritium inventory can be determined in real-time. The computational model was developed based on the experience gained on the pilot installation. The model uses a set of parameters specific to isotopic exchange processes. These parameters were experimentally determined in the pilot installation. The model is included in the monitoring system and uses as input data the parameters acquired in real-time from automation system of the pilot installation. A friendly interface has been created to visualize the final results as data or graphs. (authors)

Improved treatment of global positioning system force parameters in precise orbit determination applications

Science.gov (United States)

Vigue, Y.; Lichten, S. M.; Muellerschoen, R. J.; Blewitt, G.; Heflin, M. B.

1993-01-01

Data collected from a worldwide 1992 experiment were processed at JPL to determine precise orbits for the satellites of the Global Positioning System (GPS). A filtering technique was tested to improve modeling of solar-radiation pressure force parameters for GPS satellites. The new approach improves orbit quality for eclipsing satellites by a factor of two, with typical results in the 25- to 50-cm range. The resultant GPS-based estimates for geocentric coordinates of the tracking sites, which include the three DSN sites, are accurate to 2 to 8 cm, roughly equivalent to 3 to 10 nrad of angular measure.

Global sensitivity analysis of the joint kinematics during gait to the parameters of a lower limb multi-body model.

Science.gov (United States)

El Habachi, Aimad; Moissenet, Florent; Duprey, Sonia; Cheze, Laurence; Dumas, Raphaël

2015-07-01

Sensitivity analysis is a typical part of biomechanical models evaluation. For lower limb multi-body models, sensitivity analyses have been mainly performed on musculoskeletal parameters, more rarely on the parameters of the joint models. This study deals with a global sensitivity analysis achieved on a lower limb multi-body model that introduces anatomical constraints at the ankle, tibiofemoral, and patellofemoral joints. The aim of the study was to take into account the uncertainty of parameters (e.g. 2.5 cm on the positions of the skin markers embedded in the segments, 5° on the orientation of hinge axis, 2.5 mm on the origin and insertion of ligaments) using statistical distributions and propagate it through a multi-body optimisation method used for the computation of joint kinematics from skin markers during gait. This will allow us to identify the most influential parameters on the minimum of the objective function of the multi-body optimisation (i.e. the sum of the squared distances between measured and model-determined skin marker positions) and on the joint angles and displacements. To quantify this influence, a Fourier-based algorithm of global sensitivity analysis coupled with a Latin hypercube sampling is used. This sensitivity analysis shows that some parameters of the motor constraints, that is to say the distances between measured and model-determined skin marker positions, and the kinematic constraints are highly influencing the joint kinematics obtained from the lower limb multi-body model, for example, positions of the skin markers embedded in the shank and pelvis, parameters of the patellofemoral hinge axis, and parameters of the ankle and tibiofemoral ligaments. The resulting standard deviations on the joint angles and displacements reach 36° and 12 mm. Therefore, personalisation, customisation or identification of these most sensitive parameters of the lower limb multi-body models may be considered as essential.

Analysis of Modeling Parameters on Threaded Screws.

Energy Technology Data Exchange (ETDEWEB)

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

2015-06-01

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

Parameter Estimates in Differential Equation Models for Chemical Kinetics

Science.gov (United States)

Winkel, Brian

2011-01-01

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

Simultaneous inference for model averaging of derived parameters

DEFF Research Database (Denmark)

Jensen, Signe Marie; Ritz, Christian

2015-01-01

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

Parameter identification in the logistic STAR model

DEFF Research Database (Denmark)

Ekner, Line Elvstrøm; Nejstgaard, Emil

We propose a new and simple parametrization of the so-called speed of transition parameter of the logistic smooth transition autoregressive (LSTAR) model. The new parametrization highlights that a consequence of the well-known identification problem of the speed of transition parameter is that th...

Modelling and determination of the kinetic parameters of the pyrolysis of Dichrostachys cinerea

International Nuclear Information System (INIS)

Abreu Naranjo, Reinier; Romero Romero, Osvaldo

2011-01-01

In the present study were analyzed biomass samples of Dichrostachys cinerea, commonly known in Cuba as marabou, by thermogravimetric method at various heating rates of devolatilization in nitrogen atmosphere at 5, 10 and 20 C min-1. On the kinetic analysis was used a mechanism of three independent reactions of order 1, generally attributed to three chief components of this kind of lignocellulose materials, hemicelluloses, cellulose and lignin. The values of activation energy, pre-exponential factor and contribution factor were similar to those reported in previous research for this type of biomass. The proposed model predicts with acceptable correlation the experimental and calculated curves of the decomposition of D. cinerea, with a deviation factor less than 5% for the temperature range studied. On the other hand, the kinetic parameters of the thermal decomposition coupled at equations of transport phenomena are essential to optimize the design and use of biomass thermochemical conversion processes, hence the importance of the research. (author)

Reactivity and kinetic parameters determination in a multiplicative non-stationary system

International Nuclear Information System (INIS)

Minguez, E.

1982-01-01

A revision of several methods used for solving kinetic equations of a neutronic system is considered. Firstly, kinetic equations in general form are analized, before to revise more important aproximations: point-kinetic method; adiabatic; cuasistatic; eigenvalue equations; nodal, modal and systhesis methods; and variational principles for obtaining kinetic equations. Perturbation theory is used to obtain these parameters, with differents eigenvalue equations representatives of the parameter to be calculated. Also, experimental methods have been included in this work, because of importance the parameters can be measured, and related with those obtained by calculations. Finally, adjoint kinetic equations are resolved to obtain the importance function used in weighted reactivity and kinetic parameters determinations. (author)

Determination of fuel irradiation parameters. Required accuracies and available methods

International Nuclear Information System (INIS)

Mas, P.

1977-01-01

This paper reports on the present point of some main methods to determine the nuclear parameters of fuel irradiation in testing reactors (nuclear power, burn up, ...) The different methods (theoretical or experimental) are reviewed: neutron measurements and calculations, gamma scanning, heat balance, ... . The required accuracies are reviewed: they are of 3-5 % on flux, fluences, nuclear power, burn-up, conversion factor. These required accuracies are compared with the real accuracies available which are the present time of order of 5-20 % on these parameters

Determination of material irradiation parameters. Required accuracies and available methods

International Nuclear Information System (INIS)

Cerles, J.M.; Mas, P.

1978-01-01

In this paper, the author reports some main methods to determine the nuclear parameters of material irradiation in testing reactor (nuclear power, burn-up, fluxes, fluences, ...). The different methods (theoretical or experimental) are reviewed: neutronics measurements and calculations, gamma scanning, thermal balance, ... The required accuracies are reviewed: they are of 3-5% on flux, fluences, nuclear power, burn-up, conversion factor, ... These required accuracies are compared with the real accuracies available which are at the present time of order of 5-20% on these parameters

Soil-related Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

A. J. Smith

2003-01-01

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

Support Vector Data Description Model to Map Specific Land Cover with Optimal Parameters Determined from a Window-Based Validation Set

Directory of Open Access Journals (Sweden)

Jinshui Zhang

2017-04-01

Full Text Available This paper developed an approach, the window-based validation set for support vector data description (WVS-SVDD, to determine optimal parameters for support vector data description (SVDD model to map specific land cover by integrating training and window-based validation sets. Compared to the conventional approach where the validation set included target and outlier pixels selected visually and randomly, the validation set derived from WVS-SVDD constructed a tightened hypersphere because of the compact constraint by the outlier pixels which were located neighboring to the target class in the spectral feature space. The overall accuracies for wheat and bare land achieved were as high as 89.25% and 83.65%, respectively. However, target class was underestimated because the validation set covers only a small fraction of the heterogeneous spectra of the target class. The different window sizes were then tested to acquire more wheat pixels for validation set. The results showed that classification accuracy increased with the increasing window size and the overall accuracies were higher than 88% at all window size scales. Moreover, WVS-SVDD showed much less sensitivity to the untrained classes than the multi-class support vector machine (SVM method. Therefore, the developed method showed its merits using the optimal parameters, tradeoff coefficient (C and kernel width (s, in mapping homogeneous specific land cover.

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