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
Soil-Related Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
Smith, A. J.
2004-01-01
This report presents one of the analyses that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the details of the conceptual model as well as the mathematical model and the required input parameters. The biosphere model is one of a series of process models supporting the postclosure Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A schematic representation of the documentation flow for the Biosphere input to TSPA is presented in Figure 1-1. This figure shows the evolutionary relationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (TWP) (BSC 2004 [DIRS 169573]). This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil-Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. The purpose of this analysis was to develop the biosphere model parameters associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation or ash deposition and, as a direct consequence, radionuclide concentration in other environmental media that are affected by radionuclide concentrations in soil. The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573]) where the governing procedure was defined as AP-SIII.9Q, ''Scientific Analyses''. This
Soil-Related Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
A. J. Smith
2004-09-09
This report presents one of the analyses that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the details of the conceptual model as well as the mathematical model and the required input parameters. The biosphere model is one of a series of process models supporting the postclosure Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A schematic representation of the documentation flow for the Biosphere input to TSPA is presented in Figure 1-1. This figure shows the evolutionary relationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (TWP) (BSC 2004 [DIRS 169573]). This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil-Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. The purpose of this analysis was to develop the biosphere model parameters associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation or ash deposition and, as a direct consequence, radionuclide concentration in other environmental media that are affected by radionuclide concentrations in soil. The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573]) where the governing procedure
Parameters-related uncertainty in modeling sugar cane yield with an agro-Land Surface Model
Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Ruget, F.; Gabrielle, B.
2012-12-01
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
International Nuclear Information System (INIS)
Singh, Lakhwinder; Aggarwal, M. L.; Khan, R. A.
2012-01-01
The attempt of this paper is to present an effective approach for the optimization of the shot peening process of welded AISI 304 austenitic stainless steel with multi performance characteristics using Grey relational analysis (GRA) based on Taguchi orthogonal array. Twenty-seven experimental runs are performed to determine best process parameters level. An analysis of variance (ANOVA) is carried out to identify significant peening parameters. The response tables are obtained for analyzing the optimal levels of shot peening parameters and major factors that affect the quality function. The multiple performance characteristics including tensile strength, surface hardness and surface roughness are the quality functions considered for the optimization. Further mathematical models are developed using regression analysis for the tensile strength, surface hardness and surface roughness. It will be very helpful to the engineers in deciding the levels of the shot peening parameters for desired performance characteristics
Directory of Open Access Journals (Sweden)
Eunice Molinar-Toribio
Full Text Available SHROB rats have been suggested as a model for metabolic syndrome (MetS as a situation prior to the onset of CVD or type-2 diabetes, but information on descriptive biochemical parameters for this model is limited. Here, we extensively evaluate parameters related to CVD and oxidative stress (OS in SHROB rats. SHROB rats were monitored for 15 weeks and compared to a control group of Wistar rats. Body weight was recorded weekly. At the end of the study, parameters related to CVD and OS were evaluated in plasma, urine and different organs. SHROB rats presented statistically significant differences from Wistar rats in CVD risk factors: total cholesterol, LDL-cholesterol, triglycerides, apoA1, apoB100, abdominal fat, insulin, blood pressure, C-reactive protein, ICAM-1 and PAI-1. In adipose tissue, liver and brain, the endogenous antioxidant systems were activated, yet there was no significant oxidative damage to lipids (MDA or proteins (carbonylation. We conclude that SHROB rats present significant alterations in parameters related to inflammation, endothelial dysfunction, thrombotic activity, insulin resistance and OS measured in plasma as well as enhanced redox defence systems in vital organs that will be useful as markers of MetS and CVD for nutrition interventions.
Wang, Q; Wang, C M
2007-02-21
In this paper, the constitutive relations of nonlocal elasticity theory are presented for application in the analysis of carbon nanotubes (CNTs) when modelled as Euler-Bernoulli beams, Timoshenko beams or as cylindrical shells. In particular, the shear stress and strain relation for the nonlocal Timoshenko beam theory is discussed in great detail due to a misconception by some researchers that the nonlocal effect should appear in this constitutive relation. Different theories for proposing the value of the small scale parameter are also introduced and a recommendation for the value from the standpoint of wave propagation of CNTs is given.
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)
Estimation of genetic parameters related to eggshell strength using random regression models.
Guo, J; Ma, M; Qu, L; Shen, M; Dou, T; Wang, K
2015-01-01
This study examined the changes in eggshell strength and the genetic parameters related to this trait throughout a hen's laying life using random regression. The data were collected from a crossbred population between 2011 and 2014, where the eggshell strength was determined repeatedly for 2260 hens. Using random regression models (RRMs), several Legendre polynomials were employed to estimate the fixed, direct genetic and permanent environment effects. The residual effects were treated as independently distributed with heterogeneous variance for each test week. The direct genetic variance was included with second-order Legendre polynomials and the permanent environment with third-order Legendre polynomials. The heritability of eggshell strength ranged from 0.26 to 0.43, the repeatability ranged between 0.47 and 0.69, and the estimated genetic correlations between test weeks was high at > 0.67. The first eigenvalue of the genetic covariance matrix accounted for about 97% of the sum of all the eigenvalues. The flexibility and statistical power of RRM suggest that this model could be an effective method to improve eggshell quality and to reduce losses due to cracked eggs in a breeding plan.
The influence of hyper-parameters in the infinite relational model
DEFF Research Database (Denmark)
Albers, Kristoffer Jon; Mørup, Morten; Schmidt, Mikkel Nørgaard
2016-01-01
The infinite relational model (IRM) is a Bayesian nonparametric stochastic block model; a generative model for random networks parameterized for uni-partite undirected networks by a partition of the node set and symmetric matrix of inter-partion link probabilities. The prior for the node clusters...
Mockler, E. M.; Chun, K. P.; Sapriza-Azuri, G.; Bruen, M.; Wheater, H. S.
2016-11-01
Predictions of river flow dynamics provide vital information for many aspects of water management including water resource planning, climate adaptation, and flood and drought assessments. Many of the subjective choices that modellers make including model and criteria selection can have a significant impact on the magnitude and distribution of the output uncertainty. Hydrological modellers are tasked with understanding and minimising the uncertainty surrounding streamflow predictions before communicating the overall uncertainty to decision makers. Parameter uncertainty in conceptual rainfall-runoff models has been widely investigated, and model structural uncertainty and forcing data have been receiving increasing attention. This study aimed to assess uncertainties in streamflow predictions due to forcing data and the identification of behavioural parameter sets in 31 Irish catchments. By combining stochastic rainfall ensembles and multiple parameter sets for three conceptual rainfall-runoff models, an analysis of variance model was used to decompose the total uncertainty in streamflow simulations into contributions from (i) forcing data, (ii) identification of model parameters and (iii) interactions between the two. The analysis illustrates that, for our subjective choices, hydrological model selection had a greater contribution to overall uncertainty, while performance criteria selection influenced the relative intra-annual uncertainties in streamflow predictions. Uncertainties in streamflow predictions due to the method of determining parameters were relatively lower for wetter catchments, and more evenly distributed throughout the year when the Nash-Sutcliffe Efficiency of logarithmic values of flow (lnNSE) was the evaluation criterion.
Swanson, Ryan D; Binley, Andrew; Keating, Kristina; France, Samantha; Osterman, Gordon; Day-Lewis, Frederick D.; Singha, Kamini
2015-01-01
The advection-dispersion equation (ADE) fails to describe commonly observed non-Fickian solute transport in saturated porous media, necessitating the use of other models such as the dual-domain mass-transfer (DDMT) model. DDMT model parameters are commonly calibrated via curve fitting, providing little insight into the relation between effective parameters and physical properties of the medium. There is a clear need for material characterization techniques that can provide insight into the geometry and connectedness of pore spaces related to transport model parameters. Here, we consider proton nuclear magnetic resonance (NMR), direct-current (DC) resistivity, and complex conductivity (CC) measurements for this purpose, and assess these methods using glass beads as a control and two different samples of the zeolite clinoptilolite, a material that demonstrates non-Fickian transport due to intragranular porosity. We estimate DDMT parameters via calibration of a transport model to column-scale solute tracer tests, and compare NMR, DC resistivity, CC results, which reveal that grain size alone does not control transport properties and measured geophysical parameters; rather, volume and arrangement of the pore space play important roles. NMR cannot provide estimates of more-mobile and less-mobile pore volumes in the absence of tracer tests because these estimates depend critically on the selection of a material-dependent and flow-dependent cutoff time. Increased electrical connectedness from DC resistivity measurements are associated with greater mobile pore space determined from transport model calibration. CC was hypothesized to be related to length scales of mass transfer, but the CC response is unrelated to DDMT.
Response model parameter linking
Barrett, M.L.D.
2015-01-01
With a few exceptions, the problem of linking item response model parameters from different item calibrations has been conceptualized as an instance of the problem of equating observed scores on different test forms. This thesis argues, however, that the use of item response models does not require
International Nuclear Information System (INIS)
Sakai, Ryutaro; Munakata, Masahiro; Ohoka, Masao; Kameya, Hiroshi
2009-11-01
In the safety assessment for a geological disposal of radioactive waste, it is important to develop a methodology for long-term estimation of regional groundwater flow from data acquisition to numerical analyses. In the uncertainties associated with estimation of regional groundwater flow, there are the one that concerns parameters and the one that concerns the hydrologeological evolution. The uncertainties of parameters include measurement errors and their heterogeneity. The authors discussed the uncertainties of hydraulic conductivity as a significant parameter for regional groundwater flow analysis. This study suggests that hydraulic conductivities of rock mass are controlled by rock characteristics such as fractures, porosity and test conditions such as hydraulic gradient, water quality, water temperature and that there exists variations more than ten times in hydraulic conductivity by difference due to test conditions such as hydraulic gradient or due to rock type variations such as rock fractures, porosity. In addition this study demonstrated that confining pressure change caused by uplift and subsidence and change of hydraulic gradient under the long-term evolution of hydrogeological environment could possibly produce variations more than ten times of magnitude in hydraulic conductivity. It was also shown that the effect of water quality change on hydraulic conductivity was not negligible and that the replacement of fresh water and saline water caused by sea level change could induce 0.6 times in current hydraulic conductivities in case of Horonobe site. (author)
Directory of Open Access Journals (Sweden)
Dario Constantinescu
2016-12-01
Full Text Available Drought stress is a major abiotic stres threatening plant and crop productivity. In case of fleshy fruits, understanding Drought stress is a major abiotic stress threatening plant and crop productivity. In case of fleshy fruits, understanding mechanisms governing water and carbon accumulations and identifying genes, QTLs and phenotypes, that will enable trade-offs between fruit growth and quality under Water Deficit (WD condition is a crucial challenge for breeders and growers. In the present work, 117 recombinant inbred lines of a population of Solanum lycopersicum were phenotyped under control and WD conditions. Plant water status, fruit growth and composition were measured and data were used to calibrate a process-based model describing water and carbon fluxes in a growing fruit as a function of plant and environment. Eight genotype-dependent model parameters were estimated using a multiobjective evolutionary algorithm in order to minimize the prediction errors of fruit dry and fresh mass throughout fruit development. WD increased the fruit dry matter content (up to 85 % and decreased its fresh weight (up to 60 %, big fruit size genotypes being the most sensitive. The mean normalized root mean squared errors of the predictions ranged between 16-18 % in the population. Variability in model genotypic parameters allowed us to explore diverse genetic strategies in response to WD. An interesting group of genotypes could be discriminated in which i the low loss of fresh mass under WD was associated with high active uptake of sugars and low value of the maximum cell wall extensibility, and ii the high dry matter content in control treatment (C was associated with a slow decrease of mass flow. Using 501 SNP markers genotyped across the genome, a QTL analysis of model parameters allowed to detect three main QTLs related to xylem and phloem conductivities, on chromosomes 2, 4 and 8. The model was then applied to design ideotypes with high dry matter
Linking Item Response Model Parameters.
van der Linden, Wim J; Barrett, Michelle D
2016-09-01
With a few exceptions, the problem of linking item response model parameters from different item calibrations has been conceptualized as an instance of the problem of test equating scores on different test forms. This paper argues, however, that the use of item response models does not require any test score equating. Instead, it involves the necessity of parameter linking due to a fundamental problem inherent in the formal nature of these models-their general lack of identifiability. More specifically, item response model parameters need to be linked to adjust for the different effects of the identifiability restrictions used in separate item calibrations. Our main theorems characterize the formal nature of these linking functions for monotone, continuous response models, derive their specific shapes for different parameterizations of the 3PL model, and show how to identify them from the parameter values of the common items or persons in different linking designs.
International Nuclear Information System (INIS)
Tuttobene, R.; Cosentino, S.; Cavallaro, V.
1993-01-01
This research aimed at studying a simulation model to describe the growth and yield of durum wheat in relation to meterological parameters in Mediterranean environment, using data of trials carried out by the Institute of Agronomy and filed crops of the University of Catania in two years and three localities of the Eastern Sicily. The model is divided into four modules which determine separately main phenological phases, leaf area index, total biomass and yield and soil water balance. The model uses air maximum and minimum temperature, photoperiod, solar radiation, rainfall and evaporation from a class A pan. Simulation carried out on the data of the trials showed a good interpretation of the variability of the actual data in relation to meteorological parameters. The model could simulate the variation due to plant density and sowing date. The model should be verified using independent data [it
Onicescu, Georgiana; Lawson, Andrew B.; McDermott, Suzanne; Aelion, C. Marjorie; Cai, Bo
2014-01-01
In this paper, we propose a novel spatial importance parameter hierarchical logistic regression modeling approach that includes measurement error from misalignment. We apply this model to study the relationship between the estimated concentration of soil metals at the residence of mothers and the development of intellectual disability (ID) in their children. The data consist of monthly computerized claims data about the prenatal experience of pregnant women living in nine areas within South Carolina and insured by Medicaid during January 1, 1996 and December 31, 2001 and the outcome of ID in their children during early childhood. We excluded mother-child pairs if the mother moved to an unknown location during pregnancy. We identified an association of the ID outcome with arsenic (As) and mercury (Hg) concentration in soil during pregnancy, controlling for infant sex, maternal race, mother's age, and gestational weeks at delivery. There is some indication that Hg has a slightly higher importance in the third and fourth months of pregnancy, while As has a more uniform effect over all the months with a suggestion of a slight increase in risk in later months. PMID:24888618
Onicescu, Georgiana; Lawson, Andrew B; McDermott, Suzanne; Aelion, C Marjorie; Cai, Bo
2014-09-01
In this paper, we propose a novel spatial importance parameter hierarchical logistic regression modeling approach that includes measurement error from misalignment. We apply this model to study the relationship between the estimated concentration of soil metals at the residence of mothers and the development of intellectual disability (ID) in their children. The data consist of monthly computerized claims data about the prenatal experience of pregnant women living in nine areas within South Carolina and insured by Medicaid during January 1, 1996 and December 31, 2001 and the outcome of ID in their children during early childhood. We excluded mother-child pairs if the mother moved to an unknown location during pregnancy. We identified an association of the ID outcome with arsenic (As) and mercury (Hg) concentration in soil during pregnancy, controlling for infant sex, maternal race, mother's age, and gestational weeks at delivery. There is some indication that Hg has a slightly higher importance in the third and fourth months of pregnancy, while As has a more uniform effect over all the months with a suggestion of a slight increase in risk in later months.
Sharif, Khan M; Kulsing, Chadin; Chin, Sung-Tong; Marriott, Philip J
2016-07-15
The differential pressure drop of carrier gas by tuning the junction point pressure of a coupled column gas chromatographic system leads to a unique selectivity of the overall separation, which can be tested using a mixture of compounds with a wide range of polarity. This study demonstrates a pressure tuning (PT) GC system employing a microfluidic Deans switch located at the mid-point of the two capillary columns. This PT system allowed variations of inlet-outlet pressure differences of the two columns in a range of 52-17psi for the upstream column and 31-11psi for the downstream column. Peak shifting (differential migration) of compounds due to PT difference are related to a first order regression equation in a Plackett-Burman factorial study. Increased first (upstream) column pressure drop makes the second column characteristics more significant in the coupled column retention behavior, and conversely increased second (downstream) column pressure drop makes the first column characteristics more apparent; such variation can result in component swapping between polar and non-polar compounds. The coupled column system selectivity was evaluated in terms of linear solvation energy relationship (LSER) parameters, and their relation with different pressure drop effects has been constructed by applying multivariate principle component analysis (PCA). It has been found that the coupled column PT system descriptors provide a result that shows a clear clustering of different pressure settings, somewhat intermediate between those of the two commercial columns. This is equivalent to that obtained from a conventional single-column GC analysis where the interaction energy contributed from the stationary phases can be significantly adjusted by choice of midpoint PT. This result provides a foundation for pressure differentiation for selectivity enhancement. Copyright © 2016 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Mathieu Andraud
2018-01-01
Full Text Available The outputs of epidemiological models are strongly related to the structure of the model and input parameters. The latter are defined by fitting theoretical concepts to actual data derived from field or experimental studies. However, some parameters may remain difficult to estimate and are subject to uncertainty or sensitivity analyses to determine their variation range and their global impact on model outcomes. As such, the evaluation of immunity duration is often a puzzling issue requiring long-term follow-up data that are, most of time, not available. The present analysis aims at characterizing the kinetics of antibodies against Porcine Reproductive and Respiratory Syndrome virus (PRRSv from longitudinal data sets. The first data set consisted in the serological follow-up of 22 vaccinated gilts during 21 weeks post-vaccination (PV. The second one gathered the maternally derived antibodies (MDAs kinetics in piglets from three different farms up to 14 weeks of age. The peak of the PV serological response against PRRSv was reached 6.9 weeks PV on average with an average duration of antibodies persistence of 26.5 weeks. In the monitored cohort of piglets, the duration of passive immunity was found relatively short, with an average duration of 4.8 weeks. The level of PRRSv-MDAs was found correlated with the dams’ antibody titer at birth, and the antibody persistence was strongly related to the initial MDAs titers in piglets. These results evidenced the importance of PRRSv vaccination schedule in sows, to optimize the delivery of antibodies to suckling piglets. These estimates of the duration of active and passive immunity could be further used as input parameters of epidemiological models to analyze their impact on the persistence of PRRSv within farms.
Andraud, Mathieu; Fablet, Christelle; Renson, Patricia; Eono, Florent; Mahé, Sophie; Bourry, Olivier; Rose, Nicolas
2018-01-01
The outputs of epidemiological models are strongly related to the structure of the model and input parameters. The latter are defined by fitting theoretical concepts to actual data derived from field or experimental studies. However, some parameters may remain difficult to estimate and are subject to uncertainty or sensitivity analyses to determine their variation range and their global impact on model outcomes. As such, the evaluation of immunity duration is often a puzzling issue requiring long-term follow-up data that are, most of time, not available. The present analysis aims at characterizing the kinetics of antibodies against Porcine Reproductive and Respiratory Syndrome virus (PRRSv) from longitudinal data sets. The first data set consisted in the serological follow-up of 22 vaccinated gilts during 21 weeks post-vaccination (PV). The second one gathered the maternally derived antibodies (MDAs) kinetics in piglets from three different farms up to 14 weeks of age. The peak of the PV serological response against PRRSv was reached 6.9 weeks PV on average with an average duration of antibodies persistence of 26.5 weeks. In the monitored cohort of piglets, the duration of passive immunity was found relatively short, with an average duration of 4.8 weeks. The level of PRRSv-MDAs was found correlated with the dams' antibody titer at birth, and the antibody persistence was strongly related to the initial MDAs titers in piglets. These results evidenced the importance of PRRSv vaccination schedule in sows, to optimize the delivery of antibodies to suckling piglets. These estimates of the duration of active and passive immunity could be further used as input parameters of epidemiological models to analyze their impact on the persistence of PRRSv within farms.
Andraud, Mathieu; Fablet, Christelle; Renson, Patricia; Eono, Florent; Mahé, Sophie; Bourry, Olivier; Rose, Nicolas
2018-01-01
The outputs of epidemiological models are strongly related to the structure of the model and input parameters. The latter are defined by fitting theoretical concepts to actual data derived from field or experimental studies. However, some parameters may remain difficult to estimate and are subject to uncertainty or sensitivity analyses to determine their variation range and their global impact on model outcomes. As such, the evaluation of immunity duration is often a puzzling issue requiring long-term follow-up data that are, most of time, not available. The present analysis aims at characterizing the kinetics of antibodies against Porcine Reproductive and Respiratory Syndrome virus (PRRSv) from longitudinal data sets. The first data set consisted in the serological follow-up of 22 vaccinated gilts during 21 weeks post-vaccination (PV). The second one gathered the maternally derived antibodies (MDAs) kinetics in piglets from three different farms up to 14 weeks of age. The peak of the PV serological response against PRRSv was reached 6.9 weeks PV on average with an average duration of antibodies persistence of 26.5 weeks. In the monitored cohort of piglets, the duration of passive immunity was found relatively short, with an average duration of 4.8 weeks. The level of PRRSv-MDAs was found correlated with the dams’ antibody titer at birth, and the antibody persistence was strongly related to the initial MDAs titers in piglets. These results evidenced the importance of PRRSv vaccination schedule in sows, to optimize the delivery of antibodies to suckling piglets. These estimates of the duration of active and passive immunity could be further used as input parameters of epidemiological models to analyze their impact on the persistence of PRRSv within farms. PMID:29435455
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.
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)
Perceived stress and stress-related parameters.
Tomei, G; Sancini, A; Capozzella, A; Caciari, T; Tomei, F; Nieto, H A; Gioffrè, P A; Marrocco, M; De Sio, S; Rosati, M V; Ciarrocca, M
2012-01-01
The purpose of this study is to evaluate, using a questionnaire developed by our research group, whether occupational exposure to physical, chemical and psychosocial urban stressors can lead to alterations in perceived stress in a group of both male and female outdoor workers. The study also examines possible correlations between the levels of stress as inferred from the scores of the questionnaire and the levels of certain stress-related parameters (prolactin levels, consumption of coffee, chocolate, alcohol and cigarette smoking). We evaluated a final sample of 480 subjects (342 male and 138 female). All workers included in the study were divided into three groups on the basis of scores of the questionnaire. About 60% of workers showed a moderate or severe stress condition, with a statistically significant prevalence of female workers and younger subjects. There was a statistically significant correlation between the questionnaire score and the mean levels of stress-related parameters. The increase of perceived stress increases significantly the mean levels of prolactin and the consumption of coffee, chocolate and cigarettes. There was no statistically significant differences for alcohol consumption. The results show that exposure to chemical physical and psycho-social urban stressors can influence perceived stress in outdoor workers. The questionnaire used in our research could be an useful instruments for physicians during the health surveillance visits
Sample Size and Item Parameter Estimation Precision When Utilizing the One-Parameter "Rasch" Model
Custer, Michael
2015-01-01
This study examines the relationship between sample size and item parameter estimation precision when utilizing the one-parameter model. Item parameter estimates are examined relative to "true" values by evaluating the decline in root mean squared deviation (RMSD) and the number of outliers as sample size increases. This occurs across…
Archontoulis, S V; Yin, X; Vos, J; Danalatos, N G; Struik, P C
2012-01-01
Given the need for parallel increases in food and energy production from crops in the context of global change, crop simulation models and data sets to feed these models with photosynthesis and respiration parameters are increasingly important. This study provides information on photosynthesis and respiration for three energy crops (sunflower, kenaf, and cynara), reviews relevant information for five other crops (wheat, barley, cotton, tobacco, and grape), and assesses how conserved photosynthesis parameters are among crops. Using large data sets and optimization techniques, the C(3) leaf photosynthesis model of Farquhar, von Caemmerer, and Berry (FvCB) and an empirical night respiration model for tested energy crops accounting for effects of temperature and leaf nitrogen were parameterized. Instead of the common approach of using information on net photosynthesis response to CO(2) at the stomatal cavity (A(n)-C(i)), the model was parameterized by analysing the photosynthesis response to incident light intensity (A(n)-I(inc)). Convincing evidence is provided that the maximum Rubisco carboxylation rate or the maximum electron transport rate was very similar whether derived from A(n)-C(i) or from A(n)-I(inc) data sets. Parameters characterizing Rubisco limitation, electron transport limitation, the degree to which light inhibits leaf respiration, night respiration, and the minimum leaf nitrogen required for photosynthesis were then determined. Model predictions were validated against independent sets. Only a few FvCB parameters were conserved among crop species, thus species-specific FvCB model parameters are needed for crop modelling. Therefore, information from readily available but underexplored A(n)-I(inc) data should be re-analysed, thereby expanding the potential of combining classical photosynthetic data and the biochemical model.
Archontoulis, S. V.; Yin, X.; Vos, J.; Danalatos, N. G.; Struik, P. C.
2012-01-01
Given the need for parallel increases in food and energy production from crops in the context of global change, crop simulation models and data sets to feed these models with photosynthesis and respiration parameters are increasingly important. This study provides information on photosynthesis and respiration for three energy crops (sunflower, kenaf, and cynara), reviews relevant information for five other crops (wheat, barley, cotton, tobacco, and grape), and assesses how conserved photosynthesis parameters are among crops. Using large data sets and optimization techniques, the C3 leaf photosynthesis model of Farquhar, von Caemmerer, and Berry (FvCB) and an empirical night respiration model for tested energy crops accounting for effects of temperature and leaf nitrogen were parameterized. Instead of the common approach of using information on net photosynthesis response to CO2 at the stomatal cavity (An–Ci), the model was parameterized by analysing the photosynthesis response to incident light intensity (An–Iinc). Convincing evidence is provided that the maximum Rubisco carboxylation rate or the maximum electron transport rate was very similar whether derived from An–Ci or from An–Iinc data sets. Parameters characterizing Rubisco limitation, electron transport limitation, the degree to which light inhibits leaf respiration, night respiration, and the minimum leaf nitrogen required for photosynthesis were then determined. Model predictions were validated against independent sets. Only a few FvCB parameters were conserved among crop species, thus species-specific FvCB model parameters are needed for crop modelling. Therefore, information from readily available but underexplored An–Iinc data should be re-analysed, thereby expanding the potential of combining classical photosynthetic data and the biochemical model. PMID:22021569
Nienałtowski, Karol; Włodarczyk, Michał; Lipniacki, Tomasz; Komorowski, Michał
2015-09-29
Compared to engineering or physics problems, dynamical models in quantitative biology typically depend on a relatively large number of parameters. Progress in developing mathematics to manipulate such multi-parameter models and so enable their efficient interplay with experiments has been slow. Existing solutions are significantly limited by model size. In order to simplify analysis of multi-parameter models a method for clustering of model parameters is proposed. It is based on a derived statistically meaningful measure of similarity between groups of parameters. The measure quantifies to what extend changes in values of some parameters can be compensated by changes in values of other parameters. The proposed methodology provides a natural mathematical language to precisely communicate and visualise effects resulting from compensatory changes in values of parameters. As a results, a relevant insight into identifiability analysis and experimental planning can be obtained. Analysis of NF-κB and MAPK pathway models shows that highly compensative parameters constitute clusters consistent with the network topology. The method applied to examine an exceptionally rich set of published experiments on the NF-κB dynamics reveals that the experiments jointly ensure identifiability of only 60% of model parameters. The method indicates which further experiments should be performed in order to increase the number of identifiable parameters. We currently lack methods that simplify broadly understood analysis of multi-parameter models. The introduced tools depict mutually compensative effects between parameters to provide insight regarding role of individual parameters, identifiability and experimental design. The method can also find applications in related methodological areas of model simplification and parameters estimation.
Relation between axial length and ocular parameters
Directory of Open Access Journals (Sweden)
Xue-Qiu Yang
2013-09-01
Full Text Available AIM: To investigatethe relation between axial length(AL, age and ocular parameters.METHODS: A total of 360 subjects(360 eyeswith emmetropia or myopia were recruited. Refraction, center corneal thickness(CCT, AL, intraocular pressure(IOPwere measured by automatic-refractor, Pachymeter, A-mode ultrasound and non-contact tonometer, respectively. Corneal curvature(CC, anterior chamber depth(ACDand white-to-white distance(WWDwere measured by Orbscan II. Three dimensional frequency domain coherent optical tomography(3D-OCTwas used to examine the retinal nerve fiber layer thickness(RNFLT. The Pearson correlation coefficient(rand multiple regression analysis were performed to evaluate the relationship between AL, age and ocular parameters.RESULTS: The average AL was 24.15±1.26mm. With elongation of the AL, spherical equivalent(SE(r=-0.742,Pr=-0.395, Pr=-0.374, Pr=0.411, Pr=0.099, P=0.060and WWD(r=0.061, P=0.252. There was also a significant correlation between AL and age(P=0.001, SE(PPPCONCLUSION: In longer eyes, there is a tendency toward myopia, a flatter cornea, a deeper ACD and a thinner RNFLT. Age is an influencing factor for the AL as well.
Remarkable analytic relations among greybody parameters
Elia, Davide; Pezzuto, S.
2016-09-01
In this paper we derive and discuss several implications of the analytic form of a modified blackbody, also called greybody, which is widely used in Astrophysics, and in particular in the study of star formation in the far-infrared/submillimetre domain. The research in this area has been greatly improved thanks to recent observations taken with the Herschel satellite, so that it became important to clarify the sense of the greybody approximation, to suggest possible further uses, and to delimit its intervals of validity. First, we discuss the position of the greybody peak, making difference between the optically thin and thick regimes. Second, we analyse the behaviour of bolometric quantities as a function of the different greybody parameters. The ratio between the bolometric luminosity and the mass of a source, the ratio between the so-called `submillimetre luminosity' and the bolometric one, and the bolometric temperature are observables used to characterize the evolutionary stage of a source, and it is of primary importance to have analytic equations describing the dependence of such quantities on the greybody parameters. Here we discuss all these aspects, providing analytic relations, illustrating particular cases, and providing graphical examples. Some equations reported here are well known in Astrophysics, but are often spread over different publications. Some of them, instead, are brand new and represent a novelty in Astrophysics literature. Finally, we indicate an alternative way to obtain, under some conditions, the greybody temperature and dust emissivity index directly from an observing spectral energy distribution, avoiding a best-fitting procedure.
Relativity Parameters Determined from Lunar Laser Ranging
Williams, J. G.; Newhall, X. X.; Dickey, J. O.
1996-01-01
Analysis of 24 years of lunar laser ranging data is used to test the principle of equivalence, geodetic precession, the PPN parameters beta and gamma, and G/G. Recent data can be fitted with a rms scatter of 3 cm. (a) Using the Nordtvedt effect to test the principle of equivalence, it is found that the Moon and Earth accelerate alike in the Sun's field. The relative accelerations match to within 5 x 10(exp -13) . This limit, combined with an independent determination of y from planetary time delay, gives beta. Including the uncertainty due to compositional differences, the parameter beta differs from unity by no more than 0.0014; and, if the weak equivalence principle is satisfied, the difference is no more than 0.0006. (b) Geodetic precession matches its expected 19.2 marc sec/yr rate within 0.7%. This corresponds to a 1% test of gamma. (c) Apart from the Nordtvedt effect, beta and gamma can be tested from their influence on the lunar orbit. It is argued theoretically that the linear combination 0.8(beta) + 1.4(gamma) can be tested at the 1% level of accuracy. For solutions using numerically derived partial derivatives, higher sensitivity is found. Both 6 and y match the values of general relativity to within 0.005, and the linear combination beta+ gamma matches to within 0,003, but caution is advised due to the lack of theoretical understanding of these sensitivities. (d) No evidence for a changing gravitational constant is found, with absolute value of G/G less than or equal to 8 x lO(exp -12)/yr. There is significant sensitivity to G/G through solar perturbations on the lunar orbit.
Modelling tourists arrival using time varying parameter
Suciptawati, P.; Sukarsa, K. G.; Kencana, Eka N.
2017-06-01
The importance of tourism and its related sectors to support economic development and poverty reduction in many countries increase researchers’ attentions to study and model tourists’ arrival. This work is aimed to demonstrate time varying parameter (TVP) technique to model the arrival of Korean’s tourists to Bali. The number of Korean tourists whom visiting Bali for period January 2010 to December 2015 were used to model the number of Korean’s tourists to Bali (KOR) as dependent variable. The predictors are the exchange rate of Won to IDR (WON), the inflation rate in Korea (INFKR), and the inflation rate in Indonesia (INFID). Observing tourists visit to Bali tend to fluctuate by their nationality, then the model was built by applying TVP and its parameters were approximated using Kalman Filter algorithm. The results showed all of predictor variables (WON, INFKR, INFID) significantly affect KOR. For in-sample and out-of-sample forecast with ARIMA’s forecasted values for the predictors, TVP model gave mean absolute percentage error (MAPE) as much as 11.24 percent and 12.86 percent, respectively.
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.
Model parameter updating using Bayesian networks
Energy Technology Data Exchange (ETDEWEB)
Treml, C. A. (Christine 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.
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...
An approach to adjustment of relativistic mean field model parameters
Directory of Open Access Journals (Sweden)
Bayram Tuncay
2017-01-01
Full Text Available The Relativistic Mean Field (RMF model with a small number of adjusted parameters is powerful tool for correct predictions of various ground-state nuclear properties of nuclei. Its success for describing nuclear properties of nuclei is directly related with adjustment of its parameters by using experimental data. In the present study, the Artificial Neural Network (ANN method which mimics brain functionality has been employed for improvement of the RMF model parameters. In particular, the understanding capability of the ANN method for relations between the RMF model parameters and their predictions for binding energies (BEs of 58Ni and 208Pb have been found in agreement with the literature values.
Parameter estimation in fractional diffusion models
Kubilius, Kęstutis; Ralchenko, Kostiantyn
2017-01-01
This book is devoted to parameter estimation in diffusion models involving fractional Brownian motion and related processes. For many years now, standard Brownian motion has been (and still remains) a popular model of randomness used to investigate processes in the natural sciences, financial markets, and the economy. The substantial limitation in the use of stochastic diffusion models with Brownian motion is due to the fact that the motion has independent increments, and, therefore, the random noise it generates is “white,” i.e., uncorrelated. However, many processes in the natural sciences, computer networks and financial markets have long-term or short-term dependences, i.e., the correlations of random noise in these processes are non-zero, and slowly or rapidly decrease with time. In particular, models of financial markets demonstrate various kinds of memory and usually this memory is modeled by fractional Brownian diffusion. Therefore, the book constructs diffusion models with memory and provides s...
Parameter identification in the logistic STAR model
DEFF Research Database (Denmark)
Ekner, Line Elvstrøm; Nejstgaard, Emil
We propose a new and simple parametrization of the so-called speed of transition parameter of the logistic smooth transition autoregressive (LSTAR) model. The new parametrization highlights that a consequence of the well-known identification problem of the speed of transition parameter is that th......We propose a new and simple parametrization of the so-called speed of transition parameter of the logistic smooth transition autoregressive (LSTAR) model. The new parametrization highlights that a consequence of the well-known identification problem of the speed of transition parameter...
A test for the parameters of multiple linear regression models ...
African Journals Online (AJOL)
A test for the parameters of multiple linear regression models is developed for conducting tests simultaneously on all the parameters of multiple linear regression models. The test is robust relative to the assumptions of homogeneity of variances and absence of serial correlation of the classical F-test. Under certain null and ...
Parameter Estimation of Partial Differential Equation Models
Xun, Xiaolei
2013-09-01
Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown and need to be estimated from the measurements of the dynamic system in the presence of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from long-range infrared light detection and ranging data. Supplementary materials for this article are available online. © 2013 American Statistical Association.
Application of lumped-parameter models
Energy Technology Data Exchange (ETDEWEB)
Ibsen, Lars Bo; Liingaard, M.
2006-12-15
This technical report concerns the lumped-parameter models for a suction caisson with a ratio between skirt length and foundation diameter equal to 1/2, embedded into an viscoelastic soil. The models are presented for three different values of the shear modulus of the subsoil. Subsequently, the assembly of the dynamic stiffness matrix for the foundation is considered, and the solution for obtaining the steady state response, when using lumped-parameter models is given. (au)
CHAMP: Changepoint Detection Using Approximate Model Parameters
2014-06-01
form (with independent emissions or otherwise), in which parameter estimates are available via means such as maximum likelihood fit, MCMC , or sample ...counterparts, including the ability to generate a full posterior distribution over changepoint locations and offering a natural way to incorporate prior... sample consensus method. Our modifications also remove a significant restriction on model definition when detecting parameter changes within a single
Exploiting intrinsic fluctuations to identify model parameters.
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.
Setting Parameters for Biological Models With ANIMO
Schivo, Stefano; Scholma, Jetse; Karperien, Hermanus Bernardus Johannes; Post, Janine Nicole; van de Pol, Jan Cornelis; Langerak, Romanus; André, Étienne; Frehse, Goran
2014-01-01
ANIMO (Analysis of Networks with Interactive MOdeling) is a software for modeling biological networks, such as e.g. signaling, metabolic or gene networks. An ANIMO model is essentially the sum of a network topology and a number of interaction parameters. The topology describes the interactions
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
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......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...
Setting Parameters for Biological Models With ANIMO
Directory of Open Access Journals (Sweden)
Stefano Schivo
2014-03-01
Full Text Available ANIMO (Analysis of Networks with Interactive MOdeling is a software for modeling biological networks, such as e.g. signaling, metabolic or gene networks. An ANIMO model is essentially the sum of a network topology and a number of interaction parameters. The topology describes the interactions between biological entities in form of a graph, while the parameters determine the speed of occurrence of such interactions. When a mismatch is observed between the behavior of an ANIMO model and experimental data, we want to update the model so that it explains the new data. In general, the topology of a model can be expanded with new (known or hypothetical nodes, and enables it to match experimental data. However, the unrestrained addition of new parts to a model causes two problems: models can become too complex too fast, to the point of being intractable, and too many parts marked as "hypothetical" or "not known" make a model unrealistic. Even if changing the topology is normally the easier task, these problems push us to try a better parameter fit as a first step, and resort to modifying the model topology only as a last resource. In this paper we show the support added in ANIMO to ease the task of expanding the knowledge on biological networks, concentrating in particular on the parameter settings.
Directory of Open Access Journals (Sweden)
S. Martorell
2017-01-01
Full Text Available One can find many reliability, availability, and maintainability (RAM models proposed in the literature. However, such models become more complex day after day, as there is an attempt to capture equipment performance in a more realistic way, such as, explicitly addressing the effect of component ageing and degradation, surveillance activities, and corrective and preventive maintenance policies. Then, there is a need to fit the best model to real data by estimating the model parameters using an appropriate tool. This problem is not easy to solve in some cases since the number of parameters is large and the available data is scarce. This paper considers two main failure models commonly adopted to represent the probability of failure on demand (PFD of safety equipment: (1 by demand-caused and (2 standby-related failures. It proposes a maximum likelihood estimation (MLE approach for parameter estimation of a reliability model of demand-caused and standby-related failures of safety components exposed to degradation by demand stress and ageing that undergo imperfect maintenance. The case study considers real failure, test, and maintenance data for a typical motor-operated valve in a nuclear power plant. The results of the parameters estimation and the adoption of the best model are discussed.
Do Lumped-Parameter Models Provide the Correct Geometrical Damping?
DEFF Research Database (Denmark)
Andersen, Lars
2007-01-01
This paper concerns the formulation of lumped-parameter models for rigid footings on homogenous or stratified soil with focus on the horizontal sliding and rocking. Such models only contain a few degrees of freedom, which makes them ideal for inclusion in aero-elastic codes for wind turbines......-parameter models with respect to the prediction of the maximum response during excitation and the geometrical damping related to free vibrations of a footing....
Modelling and parameter estimation of dynamic systems
Raol, JR; Singh, J
2004-01-01
Parameter estimation is the process of using observations from a system to develop mathematical models that adequately represent the system dynamics. The assumed model consists of a finite set of parameters, the values of which are calculated using estimation techniques. Most of the techniques that exist are based on least-square minimization of error between the model response and actual system response. However, with the proliferation of high speed digital computers, elegant and innovative techniques like filter error method, H-infinity and Artificial Neural Networks are finding more and mor
Models and parameters for environmental radiological assessments
Energy Technology Data Exchange (ETDEWEB)
Miller, C W [ed.
1984-01-01
This book presents a unified compilation of models and parameters appropriate for assessing the impact of radioactive discharges to the environment. Models examined include those developed for the prediction of atmospheric and hydrologic transport and deposition, for terrestrial and aquatic food-chain bioaccumulation, and for internal and external dosimetry. Chapters have been entered separately into the data base. (ACR)
Consistent Stochastic Modelling of Meteocean Design Parameters
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Sterndorff, M. J.
2000-01-01
Consistent stochastic models of metocean design parameters and their directional dependencies are essential for reliability assessment of offshore structures. In this paper a stochastic model for the annual maximum values of the significant wave height, and the associated wind velocity, current...
Models and parameters for environmental radiological assessments
International Nuclear Information System (INIS)
Miller, C.W.
1984-01-01
This book presents a unified compilation of models and parameters appropriate for assessing the impact of radioactive discharges to the environment. Models examined include those developed for the prediction of atmospheric and hydrologic transport and deposition, for terrestrial and aquatic food-chain bioaccumulation, and for internal and external dosimetry. Chapters have been entered separately into the data base
the relation to lipid parameters in patients
African Journals Online (AJOL)
2011-11-14
Nov 14, 2011 ... 0.1 ml of a test serum, and the mixture was incubat- ed at 37°C for 10 ... variables was performed using the nonparametric. Kruskal Wallis test. The chi-square Mantel-Haenszel was used to compare allele frequencies between groups. Two regression models were performed, namely a linear regression ...
Carrstensen, H; Müller, R H; Müller, B W
1992-10-01
Fat emulsions for parenteral nutrition, stabilized by egg lecithin, were characterized in terms of parameters relevant to uptake by the reticuloendothelial system (RES), e.g. size distribution, surface hydrophobicity and adsorption of serum components as a measure of the degree of opsonization. Adsorption of serum components was quantified by zeta potential measurement. Fat emulsions for nutrition were compared with emulsions used for drug delivery and model drug carries for intravenous injection. The emulsions for drug delivery were stabilized by the blockcopolymers Poloxamer 188 and 407 (Pluronic F68 and F127) and Poloxamine 908. Model drug carriers were hydrophobic and hydrophilic polystyrene latex particles. Hydrophilic particles were prepared by adsorption of Poloxamine 908 (coating) onto the particle surface. The hydrophobicity and serum protein adsorption decreased from hydrophobic latex particles to egg lecithin emulsions and blockcopolymer emulsions and particles. The data correlated with that in the literature concerning liver uptake in vivo showing complete RES clearance of hydrophobic latex particles, reduced uptake of egg lecithin emulsions and avoidance of RES uptake by Poloxamine 908 coated particles.
Advances in Modelling, System Identification and Parameter ...
Indian Academy of Sciences (India)
models determined from flight test data by using parameter estimation methods find extensive use in design/modification of flight control systems, high fidelity flight simulators and evaluation of handling qualitites of aircraft and rotorcraft. R K Mehra et al present new algorithms and results for flutter tests and adaptive notching ...
A lumped parameter model of plasma focus
International Nuclear Information System (INIS)
Gonzalez, Jose H.; Florido, Pablo C.; Bruzzone, H.; Clausse, Alejandro
1999-01-01
A lumped parameter model to estimate neutron emission of a plasma focus (PF) device is developed. The dynamic of the current sheet is calculated using a snowplow model, and the neutron production with the thermal fusion cross section for a deuterium filling gas. The results were contrasted as a function of the filling pressure with experimental measurements of a 3.68 KJ Mather-type PF. (author)
One parameter model potential for noble metals
International Nuclear Information System (INIS)
Idrees, M.; Khwaja, F.A.; Razmi, M.S.K.
1981-08-01
A phenomenological one parameter model potential which includes s-d hybridization and core-core exchange contributions is proposed for noble metals. A number of interesting properties like liquid metal resistivities, band gaps, thermoelectric powers and ion-ion interaction potentials are calculated for Cu, Ag and Au. The results obtained are in better agreement with experiment than the ones predicted by the other model potentials in the literature. (author)
A distributed approach for parameters estimation in System Biology models
International Nuclear Information System (INIS)
Mosca, E.; Merelli, I.; Alfieri, R.; Milanesi, L.
2009-01-01
Due to the lack of experimental measurements, biological variability and experimental errors, the value of many parameters of the systems biology mathematical models is yet unknown or uncertain. A possible computational solution is the parameter estimation, that is the identification of the parameter values that determine the best model fitting respect to experimental data. We have developed an environment to distribute each run of the parameter estimation algorithm on a different computational resource. The key feature of the implementation is a relational database that allows the user to swap the candidate solutions among the working nodes during the computations. The comparison of the distributed implementation with the parallel one showed that the presented approach enables a faster and better parameter estimation of systems biology models.
Do Lumped-Parameter Models Provide the Correct Geometrical Damping?
DEFF Research Database (Denmark)
Andersen, Lars
This paper concerns the formulation of lumped-parameter models for rigid footings on homogenous or stratified soil. Such models only contain a few degrees of freedom, which makes them ideal for inclusion in aero-elastic codes for wind turbines and other models applied to fast evaluation of struct......This paper concerns the formulation of lumped-parameter models for rigid footings on homogenous or stratified soil. Such models only contain a few degrees of freedom, which makes them ideal for inclusion in aero-elastic codes for wind turbines and other models applied to fast evaluation...... response during excitation and the geometrical damping related to free vibrations of a hexagonal footing. The optimal order of a lumped-parameter model is determined for each degree of freedom, i.e. horizontal and vertical translation as well as torsion and rocking. In particular, the necessity of coupling...
Incorporating model parameter uncertainty into inverse treatment planning
International Nuclear Information System (INIS)
Lian Jun; Xing Lei
2004-01-01
Radiobiological treatment planning depends not only on the accuracy of the models describing the dose-response relation of different tumors and normal tissues but also on the accuracy of tissue specific radiobiological parameters in these models. Whereas the general formalism remains the same, different sets of model parameters lead to different solutions and thus critically determine the final plan. Here we describe an inverse planning formalism with inclusion of model parameter uncertainties. This is made possible by using a statistical analysis-based frameset developed by our group. In this formalism, the uncertainties of model parameters, such as the parameter a that describes tissue-specific effect in the equivalent uniform dose (EUD) model, are expressed by probability density function and are included in the dose optimization process. We found that the final solution strongly depends on distribution functions of the model parameters. Considering that currently available models for computing biological effects of radiation are simplistic, and the clinical data used to derive the models are sparse and of questionable quality, the proposed technique provides us with an effective tool to minimize the effect caused by the uncertainties in a statistical sense. With the incorporation of the uncertainties, the technique has potential for us to maximally utilize the available radiobiology knowledge for better IMRT treatment
Parameter optimization for surface flux transport models
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.
Procedures for parameter estimates of computational models for localized failure
Iacono, C.
2007-01-01
In the last years, many computational models have been developed for tensile fracture in concrete. However, their reliability is related to the correct estimate of the model parameters, not all directly measurable during laboratory tests. Hence, the development of inverse procedures is needed, that
Fadly, Romi; Dewi, Citra
2014-01-01
This research aims to compare the 14 transformation parameters between ITRF from computation result using the Helmert 14-parameter models with IERS standard parameters. The transforma- tion parameters are calculated from the coordinates and velocities of ITRF05 to ITRF00 epoch 2000.00, and from ITRF08 to ITRF05 epoch 2005.00 for respectively transformation models. The transformation parameters are compared to the IERS standard parameters, then tested the signifi- cance of the d...
Constant-parameter capture-recapture models
Brownie, C.; Hines, J.E.; Nichols, J.D.
1986-01-01
Jolly (1982, Biometrics 38, 301-321) presented modifications of the Jolly-Seber model for capture-recapture data, which assume constant survival and/or capture rates. Where appropriate, because of the reduced number of parameters, these models lead to more efficient estimators than the Jolly-Seber model. The tests to compare models given by Jolly do not make complete use of the data, and we present here the appropriate modifications, and also indicate how to carry out goodness-of-fit tests which utilize individual capture history information. We also describe analogous models for the case where young and adult animals are tagged. The availability of computer programs to perform the analysis is noted, and examples are given using output from these programs.
Aqueous Electrolytes: Model Parameters and Process Simulation
DEFF Research Database (Denmark)
Thomsen, Kaj
This thesis deals with aqueous electrolyte mixtures. The Extended UNIQUAC model is being used to describe the excess Gibbs energy of such solutions. Extended UNIQUAC parameters for the twelve ions Na+, K+, NH4+, H+, Cl-, NO3-, SO42-, HSO4-, OH-, CO32-, HCO3-, and S2O82- are estimated. A computer ...... program including a steady state process simulator for the design, simulation, and optimization of fractional crystallization processes is presented.......This thesis deals with aqueous electrolyte mixtures. The Extended UNIQUAC model is being used to describe the excess Gibbs energy of such solutions. Extended UNIQUAC parameters for the twelve ions Na+, K+, NH4+, H+, Cl-, NO3-, SO42-, HSO4-, OH-, CO32-, HCO3-, and S2O82- are estimated. A computer...
Cosmological models in general relativity
Indian Academy of Sciences (India)
Cosmological models in general relativity. B B PAUL. Department of Physics, Nowgong College, Nagaon, Assam, India. MS received 4 October 2002; revised 6 March 2003; accepted 21 May 2003. Abstract. LRS Bianchi type-I space-time filled with perfect fluid is considered here with deceler- ation parameter as variable.
DEFF Research Database (Denmark)
Beauquier, Maxime; Schürmann, Carsten
2011-01-01
In this paper, we present a model based on relations for bigraphical reactive system [Milner09]. Its defining characteristics are that validity and reaction relations are captured as traces in a multi-set rewriting system. The relational model is derived from Milner's graphical definition...
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.
Models as Relational Categories
Kokkonen, Tommi
2017-11-01
Model-based learning (MBL) has an established position within science education. It has been found to enhance conceptual understanding and provide a way for engaging students in authentic scientific activity. Despite ample research, few studies have examined the cognitive processes regarding learning scientific concepts within MBL. On the other hand, recent research within cognitive science has examined the learning of so-called relational categories. Relational categories are categories whose membership is determined on the basis of the common relational structure. In this theoretical paper, I argue that viewing models as relational categories provides a well-motivated cognitive basis for MBL. I discuss the different roles of models and modeling within MBL (using ready-made models, constructive modeling, and generative modeling) and discern the related cognitive aspects brought forward by the reinterpretation of models as relational categories. I will argue that relational knowledge is vital in learning novel models and in the transfer of learning. Moreover, relational knowledge underlies the coherent, hierarchical knowledge of experts. Lastly, I will examine how the format of external representations may affect the learning of models and the relevant relations. The nature of the learning mechanisms underlying students' mental representations of models is an interesting open question to be examined. Furthermore, the ways in which the expert-like knowledge develops and how to best support it is in need of more research. The discussion and conceptualization of models as relational categories allows discerning students' mental representations of models in terms of evolving relational structures in greater detail than previously done.
Lumped Parameters Model of a Crescent Pump
Directory of Open Access Journals (Sweden)
Massimo Rundo
2016-10-01
Full Text Available This paper presents the lumped parameters model of an internal gear crescent pump with relief valve, able to estimate the steady-state flow-pressure characteristic and the pressure ripple. The approach is based on the identification of three variable control volumes regardless of the number of gear teeth. The model has been implemented in the commercial environment LMS Amesim with the development of customized components. Specific attention has been paid to the leakage passageways, some of them affected by the deformation of the cover plate under the action of the delivery pressure. The paper reports the finite element method analysis of the cover for the evaluation of the deflection and the validation through a contactless displacement transducer. Another aspect described in this study is represented by the computational fluid dynamics analysis of the relief valve, whose results have been used for tuning the lumped parameters model. Finally, the validation of the entire model of the pump is presented in terms of steady-state flow rate and of pressure oscillations.
Adolescent antisocial behavior explained by combining stress-related parameters
Platje, Evelien; Jansen, Lucres M. C.; Vermeiren, Robert R. J. M.; Doreleijers, Theo A. H.; van Lier, Pol A. C.; Koot, Hans M.; Meeus, W.H.J.; Branje, Suzan J. T.; Popma, Arne
Many stress-related parameters have been associated with antisocial behavior, including low cortisol awakening responses (CAR), as well as low cortisol and alpha-amylase reactivity to stress. These parameters reflect different, yet interrelated components of the stress system, yet it remains to be
Assessment of the water quality parameters in relation to fish ...
African Journals Online (AJOL)
Physicochemical indices of water body changed seasonally and this necessitated an investigation to assess the water quality parameters of Osinmo reservoir in relation to its fish species. The water quality parameters were measured using standard methods. Results obtained show that the reservoir is alkaline in nature with ...
Relation of Core Dominance Parameter and Extended Spectral ...
Indian Academy of Sciences (India)
Relation of Core Dominance Parameter and Extended Spectral Index for Radio Sources. J. H. Yang1,2,∗, J. J. ... nance parameters and core/extended spectral index are investigated. The extended spectral index is ... (10JJ3020), and the research fund of Hunan University of Arts and Science (JJZD. 201101). References.
Modeling of Parameters of Subcritical Assembly SAD
Petrochenkov, S; Puzynin, I
2005-01-01
The accepted conceptual design of the experimental Subcritical Assembly in Dubna (SAD) is based on the MOX core with a nominal unit capacity of 25 kW (thermal). This corresponds to the multiplication coefficient $k_{\\rm eff} =0.95$ and accelerator beam power 1 kW. A subcritical assembly driven with the existing 660 MeV proton accelerator at the Joint Institute for Nuclear Research has been modelled in order to make choice of the optimal parameters for the future experiments. The Monte Carlo method was used to simulate neutron spectra, energy deposition and doses calculations. Some of the calculation results are presented in the paper.
A software for parameter estimation in dynamic models
Directory of Open Access Journals (Sweden)
M. Yuceer
2008-12-01
Full Text Available A common problem in dynamic systems is to determine parameters in an equation used to represent experimental data. The goal is to determine the values of model parameters that provide the best fit to measured data, generally based on some type of least squares or maximum likelihood criterion. In the most general case, this requires the solution of a nonlinear and frequently non-convex optimization problem. Some of the available software lack in generality, while others do not provide ease of use. A user-interactive parameter estimation software was needed for identifying kinetic parameters. In this work we developed an integration based optimization approach to provide a solution to such problems. For easy implementation of the technique, a parameter estimation software (PARES has been developed in MATLAB environment. When tested with extensive example problems from literature, the suggested approach is proven to provide good agreement between predicted and observed data within relatively less computing time and iterations.
Moose models with vanishing S parameter
International Nuclear Information System (INIS)
Casalbuoni, R.; De Curtis, S.; Dominici, D.
2004-01-01
In the linear moose framework, which naturally emerges in deconstruction models, we show that there is a unique solution for the vanishing of the S parameter at the lowest order in the weak interactions. We consider an effective gauge theory based on K SU(2) gauge groups, K+1 chiral fields, and electroweak groups SU(2) L and U(1) Y at the ends of the chain of the moose. S vanishes when a link in the moose chain is cut. As a consequence one has to introduce a dynamical nonlocal field connecting the two ends of the moose. Then the model acquires an additional custodial symmetry which protects this result. We examine also the possibility of a strong suppression of S through an exponential behavior of the link couplings as suggested by the Randall Sundrum metric
A lumped parameter, low dimension model of heat exchanger
International Nuclear Information System (INIS)
Kanoh, Hideaki; Furushoo, Junji; Masubuchi, Masami
1980-01-01
This paper reports on the results of investigation of the distributed parameter model, the difference model, and the model of the method of weighted residuals for heat exchangers. By the method of weighted residuals (MWR), the opposite flow heat exchanger system is approximated by low dimension, lumped parameter model. By assuming constant specific heat, constant density, the same form of tube cross-section, the same form of the surface of heat exchange, uniform flow velocity, the linear relation of heat transfer to flow velocity, liquid heat carrier, and the thermal insulation of liquid from outside, fundamental equations are obtained. The experimental apparatus was made of acrylic resin. The response of the temperature at the exit of first liquid to the variation of the flow rate of second liquid was measured and compared with the models. The MWR model shows good approximation for the low frequency region, and as the number of division increases, good approximation spreads to higher frequency region. (Kato, T.)
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
Assessment of Lumped-Parameter Models for Rigid Footings
DEFF Research Database (Denmark)
Andersen, Lars
2010-01-01
The quality of consistent lumped-parameter models of rigid footings is examined. Emphasis is put on the maximum response during excitation and the geometrical damping related to free vibrations. The optimal order of a lumped-parameter model is determined for each degree of freedom, i.e. horizontal...... and vertical translations as well as torsion and rocking, and the necessity of coupling between horizontal sliding and rocking is discussed. Most of the analyses are carried out for hexagonal footings; but in order to generalise the conclusions to a broader variety of footings, comparisons are made...... with the response of circular and square foundations....
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
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
Inhalation Exposure Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
K. Rautenstrauch
2004-01-01
This analysis is one of 10 reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. Inhalation Exposure Input Parameters for the Biosphere Model is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the Technical Work Plan for Biosphere Modeling and Expert Support (BSC 2004 [DIRS 169573]). This analysis report defines and justifies values of mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception
Inhalation Exposure Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
K. Rautenstrauch
2004-09-10
This analysis is one of 10 reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. Inhalation Exposure Input Parameters for the Biosphere Model is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the Technical Work Plan for Biosphere Modeling and Expert Support (BSC 2004 [DIRS 169573]). This analysis report defines and justifies values of mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception.
Some relations of parameters in quantum field theory
International Nuclear Information System (INIS)
Ishikawa, K.
1986-01-01
Two schemes of parameter relations, linear relation and non-linear relation are discussed. The linear relation of coupling constants is derived directly from an underlying symmetry of the classical theory and is preserved usually in the quantum theory. The non-linear relation is not derived by a same manner but is derived by more involved way which is intrinsically connected with quantum theory. An underlying symmetry which leads the linear relation is shown to be essential in the non-linear relation too. Some extension is also discussed
Mohammed, Aminu; Koorbanally, Neil Anthony; Islam, Md Shahidul
2015-12-04
In West Africa, various preparations of the fruit, seed and leaf of Aframomum melegueta K. Schum. are reputably used for the management of diabetes mellitus (DM) and other metabolic disorders. The present study evaluated the anti-diabetic effects of A. melegueta ethyl acetate fraction (AMEF) from fruit ethanolic extract in a type 2 diabetes (T2D) model of rats. T2D was induced in rats by feeding a 10% fructose solution ad libitum for two weeks followed by a single intraperitoneal injection of streptozotocin (40 mg/kg body weight) and the animals were orally treated with 150 or 300 mg/kg body weight (bw) of the AMEF once daily for four weeks. At the end of the intervention, diabetic untreated animals showed significantly higher serum glucose, serum fructosamine, LDH, CK-MB, serum lipids, liver glycogen, insulin resistance (HOMA-IR), AI, CRI and lower serum insulin, pancreatic β-cell function (HOMA- β) and glucose tolerance ability compared to the normal animals. Histopathological examination of their pancreas revealed corresponding pathological changes in the islets and β-cells. These alterations were reverted to near-normal after the treatment of AMEF at 150 and 300 mg/kg bw when, the effects were more pronounced at 300 mg/kg bw compared to the 150 mg/kg bw. The results of our study suggest that AMEF treatment at 300 mg/kg bw showed potent anti-diabetic effect in a T2D model of rats. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Xintao Xia; Yantao Shang; Yinping Jin; Long Chen
2013-01-01
With the aid of the grey system theory, the grey relational analysis of the reliability with the three-parameter Weibull distribution is made for the Weibull parameter evaluation and its significance test. Via the theoretical value set and the experimental value set of the reliability relied on the lifetime data of a product, the model of the constrained optimization of the Weibull parameter evaluation based on the maximum grey relational grade. The grey significance of the reliability functi...
Influence of physical fitness parameters on relative age effect on ...
African Journals Online (AJOL)
Influence of physical fitness parameters on relative age effect on amateur secondary school rugby union players. ... At the onset of puberty, boys experience great changes in growth and development. ... Keywords: Adolescent boys; Rugby; Fitness characteristics; Maturation; Relatively older athletes; Secondary school.
Models for setting ATM parameter values
DEFF Research Database (Denmark)
Blaabjerg, Søren; Gravey, A.; Romæuf, L.
1996-01-01
presents approximate methods and discusses their applicability. We then discuss the problem of obtaining traffic characteristic values for a connection that has crossed a series of switching nodes. This problem is particularly relevant for the traffic contract components corresponding to ICIs...... (CDV) tolerance(s). The values taken by these traffic parameters characterize the so-called ''Worst Case Traffic'' that is used by CAC procedures for accepting a new connection and allocating resources to it. Conformance to the negotiated traffic characteristics is defined, at the ingress User...... essential to set traffic characteristic values that are relevant to the considered cell stream, and that ensure that the amount of non-conforming traffic is small. Using a queueing model representation for the GCRA formalism, several methods are available for choosing the traffic characteristics. This paper...
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.
Modelling of intermittent microwave convective drying: parameter sensitivity
Zhang, Zhijun; Qin, Wenchao; Shi, Bin; Gao, Jingxin; Zhang, Shiwei
2017-06-01
The reliability of the predictions of a mathematical model is a prerequisite to its utilization. A multiphase porous media model of intermittent microwave convective drying is developed based on the literature. The model considers the liquid water, gas and solid matrix inside of food. The model is simulated by COMSOL software. Its sensitivity parameter is analysed by changing the parameter values by ±20%, with the exception of several parameters. The sensitivity analysis of the process of the microwave power level shows that each parameter: ambient temperature, effective gas diffusivity, and evaporation rate constant, has significant effects on the process. However, the surface mass, heat transfer coefficient, relative and intrinsic permeability of the gas, and capillary diffusivity of water do not have a considerable effect. The evaporation rate constant has minimal parameter sensitivity with a ±20% value change, until it is changed 10-fold. In all results, the temperature and vapour pressure curves show the same trends as the moisture content curve. However, the water saturation at the medium surface and in the centre show different results. Vapour transfer is the major mass transfer phenomenon that affects the drying process.
Dengue human infection model performance parameters.
Endy, Timothy P
2014-06-15
Dengue is a global health problem and of concern to travelers and deploying military personnel with development and licensure of an effective tetravalent dengue vaccine a public health priority. The dengue viruses (DENVs) are mosquito-borne flaviviruses transmitted by infected Aedes mosquitoes. Illness manifests across a clinical spectrum with severe disease characterized by intravascular volume depletion and hemorrhage. DENV illness results from a complex interaction of viral properties and host immune responses. Dengue vaccine development efforts are challenged by immunologic complexity, lack of an adequate animal model of disease, absence of an immune correlate of protection, and only partially informative immunogenicity assays. A dengue human infection model (DHIM) will be an essential tool in developing potential dengue vaccines or antivirals. The potential performance parameters needed for a DHIM to support vaccine or antiviral candidates are discussed. © The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Dimensionality reduction of RKHS model parameters.
Taouali, Okba; Elaissi, Ilyes; Messaoud, Hassani
2015-07-01
This paper proposes a new method to reduce the parameter number of models developed in the Reproducing Kernel Hilbert Space (RKHS). In fact, this number is equal to the number of observations used in the learning phase which is assumed to be high. The proposed method entitled Reduced Kernel Partial Least Square (RKPLS) consists on approximating the retained latent components determined using the Kernel Partial Least Square (KPLS) method by their closest observation vectors. The paper proposes the design and the comparative study of the proposed RKPLS method and the Support Vector Machines on Regression (SVR) technique. The proposed method is applied to identify a nonlinear Process Trainer PT326 which is a physical process available in our laboratory. Moreover as a thermal process with large time response may help record easily effective observations which contribute to model identification. Compared to the SVR technique, the results from the proposed RKPLS method are satisfactory. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Climate change decision-making: Model & parameter uncertainties explored
Energy Technology Data Exchange (ETDEWEB)
Dowlatabadi, H.; Kandlikar, M.; Linville, C.
1995-12-31
A critical aspect of climate change decision-making is uncertainties in current understanding of the socioeconomic, climatic and biogeochemical processes involved. Decision-making processes are much better informed if these uncertainties are characterized and their implications understood. Quantitative analysis of these uncertainties serve to inform decision makers about the likely outcome of policy initiatives, and help set priorities for research so that outcome ambiguities faced by the decision-makers are reduced. A family of integrated assessment models of climate change have been developed at Carnegie Mellon. These models are distinguished from other integrated assessment efforts in that they were designed from the outset to characterize and propagate parameter, model, value, and decision-rule uncertainties. The most recent of these models is ICAM 2.1. This model includes representation of the processes of demographics, economic activity, emissions, atmospheric chemistry, climate and sea level change and impacts from these changes and policies for emissions mitigation, and adaptation to change. The model has over 800 objects of which about one half are used to represent uncertainty. In this paper we show, that when considering parameter uncertainties, the relative contribution of climatic uncertainties are most important, followed by uncertainties in damage calculations, economic uncertainties and direct aerosol forcing uncertainties. When considering model structure uncertainties we find that the choice of policy is often dominated by model structure choice, rather than parameter uncertainties.
SPOTting model parameters using a ready-made Python package
Houska, Tobias; Kraft, Philipp; Breuer, Lutz
2015-04-01
The selection and parameterization of reliable process descriptions in ecological modelling is driven by several uncertainties. The procedure is highly dependent on various criteria, like the used algorithm, the likelihood function selected and the definition of the prior parameter distributions. A wide variety of tools have been developed in the past decades to optimize parameters. Some of the tools are closed source. Due to this, the choice for a specific parameter estimation method is sometimes more dependent on its availability than the performance. A toolbox with a large set of methods can support users in deciding about the most suitable method. Further, it enables to test and compare different methods. We developed the SPOT (Statistical Parameter Optimization Tool), an open source python package containing a comprehensive set of modules, to analyze and optimize parameters of (environmental) models. SPOT comes along with a selected set of algorithms for parameter optimization and uncertainty analyses (Monte Carlo, MC; Latin Hypercube Sampling, LHS; Maximum Likelihood, MLE; Markov Chain Monte Carlo, MCMC; Scuffled Complex Evolution, SCE-UA; Differential Evolution Markov Chain, DE-MCZ), together with several likelihood functions (Bias, (log-) Nash-Sutcliff model efficiency, Correlation Coefficient, Coefficient of Determination, Covariance, (Decomposed-, Relative-, Root-) Mean Squared Error, Mean Absolute Error, Agreement Index) and prior distributions (Binomial, Chi-Square, Dirichlet, Exponential, Laplace, (log-, multivariate-) Normal, Pareto, Poisson, Cauchy, Uniform, Weibull) to sample from. The model-independent structure makes it suitable to analyze a wide range of applications. We apply all algorithms of the SPOT package in three different case studies. Firstly, we investigate the response of the Rosenbrock function, where the MLE algorithm shows its strengths. Secondly, we study the Griewank function, which has a challenging response surface for
Carrier concentration effect and other structure-related parameters ...
Indian Academy of Sciences (India)
Lattice thermal conductivity (LTC) of Si bulk and nanowires (NWs) with diameter 22, 37, 50, 56, 98 and 115 nm was investigated in the temperature range 3–300 K using a modified Callaway model that contains both longitudinal and transverse modes. Using proper equations, mean bond length, lattice parameter, unit cell ...
Relations between source parameters for large Persian earthquakes
Directory of Open Access Journals (Sweden)
Majid Nemati
2015-11-01
Full Text Available Empirical relationships for magnitude scales and fault parameters were produced using 436 Iranian intraplate earthquakes of recently regional databases since the continental events represent a large portion of total seismicity of Iran. The relations between different source parameters of the earthquakes were derived using input information which has usefully been provided from the databases after 1900. Suggested equations for magnitude scales relate the body-wave, surface-wave as well as local magnitude scales to scalar moment of the earthquakes. Also, dependence of source parameters as surface and subsurface rupture length and maximum surface displacement on the moment magnitude for some well documented earthquakes was investigated. For meeting this aim, ordinary linear regression procedures were employed for all relations. Our evaluations reveal a fair agreement between obtained relations and equations described in other worldwide and regional works in literature. The M0-mb and M0-MS equations are correlated well to the worldwide relations. Also, both M0-MS and M0-ML relations have a good agreement with regional studies in Taiwan. The equations derived from this study mainly confirm the results of the global investigations about rupture length of historical and instrumental events. However, some relations like MW-MN and MN-ML which are remarkably unlike to available regional works (e.g., American and Canadian were also found.
Testing general relativity at cosmological scales: Implementation and parameter correlations
International Nuclear Information System (INIS)
Dossett, Jason N.; Ishak, Mustapha; Moldenhauer, Jacob
2011-01-01
The testing of general relativity at cosmological scales has become a possible and timely endeavor that is not only motivated by the pressing question of cosmic acceleration but also by the proposals of some extensions to general relativity that would manifest themselves at large scales of distance. We analyze here correlations between modified gravity growth parameters and some core cosmological parameters using the latest cosmological data sets including the refined Cosmic Evolution Survey 3D weak lensing. We provide the parametrized modified growth equations and their evolution. We implement known functional and binning approaches, and propose a new hybrid approach to evolve the modified gravity parameters in redshift (time) and scale. The hybrid parametrization combines a binned redshift dependence and a smooth evolution in scale avoiding a jump in the matter power spectrum. The formalism developed to test the consistency of current and future data with general relativity is implemented in a package that we make publicly available and call ISiTGR (Integrated Software in Testing General Relativity), an integrated set of modified modules for the publicly available packages CosmoMC and CAMB, including a modified version of the integrated Sachs-Wolfe-galaxy cross correlation module of Ho et al. and a new weak-lensing likelihood module for the refined Hubble Space Telescope Cosmic Evolution Survey weak gravitational lensing tomography data. We obtain parameter constraints and correlation coefficients finding that modified gravity parameters are significantly correlated with σ 8 and mildly correlated with Ω m , for all evolution methods. The degeneracies between σ 8 and modified gravity parameters are found to be substantial for the functional form and also for some specific bins in the hybrid and binned methods indicating that these degeneracies will need to be taken into consideration when using future high precision data.
Inhalation Exposure Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
M. Wasiolek
2006-01-01
This analysis is one of the technical reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), referred to in this report as the biosphere model. ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. ''Inhalation Exposure Input Parameters for the Biosphere Model'' is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the biosphere model is presented in Figure 1-1 (based on BSC 2006 [DIRS 176938]). This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and how this analysis report contributes to biosphere modeling. This analysis report defines and justifies values of atmospheric mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of the biosphere model to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception. This report is concerned primarily with the
Inhalation Exposure Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
M. Wasiolek
2006-06-05
This analysis is one of the technical reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), referred to in this report as the biosphere model. ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. ''Inhalation Exposure Input Parameters for the Biosphere Model'' is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the biosphere model is presented in Figure 1-1 (based on BSC 2006 [DIRS 176938]). This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and how this analysis report contributes to biosphere modeling. This analysis report defines and justifies values of atmospheric mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of the biosphere model to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception. This
Modelling dense relational data
DEFF Research Database (Denmark)
Herlau, Tue; Mørup, Morten; Schmidt, Mikkel Nørgaard
2012-01-01
Relational modelling classically consider sparse and discrete data. Measures of influence computed pairwise between temporal sources naturally give rise to dense continuous-valued matrices, for instance p-values from Granger causality. Due to asymmetry or lack of positive definiteness they are no......Relational modelling classically consider sparse and discrete data. Measures of influence computed pairwise between temporal sources naturally give rise to dense continuous-valued matrices, for instance p-values from Granger causality. Due to asymmetry or lack of positive definiteness...... they are not naturally suited for kernel K-means. We propose a generative Bayesian model for dense matrices which generalize kernel K-means to consider off-diagonal interactions in matrices of interactions, and demonstrate its ability to detect structure on both artificial data and two real data sets....
Sun, T T; Liu, W H; Zhang, Y Q; Li, L H; Wang, R; Ye, Y Y
2017-08-01
Objective: To explore the differential between the value of dynamic contrast-enhanced MRI quantitative pharmacokinetic parameters and relative pharmacokinetic quantitative parameters in breast lesions. Methods: Retrospective analysis of 255 patients(262 breast lesions) who was obtained by clinical palpation , ultrasound or full-field digital mammography , and then all lessions were pathologically confirmed in Zhongda Hospital, Southeast University from May 2012 to May 2016. A 3.0 T MRI scanner was used to obtain the quantitative MR pharmacokinetic parameters: volume transfer constant (K(trans)), exchange rate constant (k(ep))and extravascular extracellular volume fraction (V(e)). And measured the quantitative pharmacokinetic parameters of normal glands tissues which on the same side of the same level of the lesions; and then calculated the value of relative pharmacokinetic parameters: rK(rans)、rk(ep) and rV(e).To explore the diagnostic value of two pharmacokinetic parameters in differential diagnosis of benign and malignant breast lesions using receiver operating curves and model of logistic regression. Results: (1)There were significant differences between benign lesions and malignant lesions in K(trans) and k(ep) ( t =15.489, 15.022, respectively, P 0.05). The areas under the ROC curve(AUC)of K(trans), k(ep) and V(e) between malignant and benign lesions were 0.933, 0.948 and 0.387, the sensitivity of K(trans), k(ep) and V(e) were 77.1%, 85.0%, 51.0% , and the specificity of K(trans), k(ep) and V(e) were 96.3%, 93.6%, 60.8% for the differential diagnosis of breast lesions if taken the maximum Youden's index as cut-off. (2)There were significant differences between benign lesions and malignant lesions in rK(trans), rk(ep) and rV(e) ( t =14.177, 11.726, 2.477, respectively, P pharmacokinetic parameters and the prediction probability of relative quantitative pharmacokinetic parameters( Z =0.867, P =0.195). Conclusion: There was no significant difference between the
Robust linear parameter varying induction motor control with polytopic models
Directory of Open Access Journals (Sweden)
Dalila Khamari
2013-01-01
Full Text Available This paper deals with a robust controller for an induction motor which is represented as a linear parameter varying systems. To do so linear matrix inequality (LMI based approach and robust Lyapunov feedback controller are associated. This new approach is related to the fact that the synthesis of a linear parameter varying (LPV feedback controller for the inner loop take into account rotor resistance and mechanical speed as varying parameter. An LPV flux observer is also synthesized to estimate rotor flux providing reference to cited above regulator. The induction motor is described as a polytopic model because of speed and rotor resistance affine dependence their values can be estimated on line during systems operations. The simulation results are presented to confirm the effectiveness of the proposed approach where robustness stability and high performances have been achieved over the entire operating range of the induction motor.
Relating stick-slip friction experiments to earthquake source parameters
McGarr, Arthur F.
2012-01-01
Analytical results for parameters, such as static stress drop, for stick-slip friction experiments, with arbitrary input parameters, can be determined by solving an energy-balance equation. These results can then be related to a given earthquake based on its seismic moment and the maximum slip within its rupture zone, assuming that the rupture process entails the same physics as stick-slip friction. This analysis yields overshoots and ratios of apparent stress to static stress drop of about 0.25. The inferred earthquake source parameters static stress drop, apparent stress, slip rate, and radiated energy are robust inasmuch as they are largely independent of the experimental parameters used in their estimation. Instead, these earthquake parameters depend on C, the ratio of maximum slip to the cube root of the seismic moment. C is controlled by the normal stress applied to the rupture plane and the difference between the static and dynamic coefficients of friction. Estimating yield stress and seismic efficiency using the same procedure is only possible when the actual static and dynamic coefficients of friction are known within the earthquake rupture zone.
Integrating microbial diversity in soil carbon dynamic models parameters
Louis, Benjamin; Menasseri-Aubry, Safya; Leterme, Philippe; Maron, Pierre-Alain; Viaud, Valérie
2015-04-01
sampling time in order to follow the dynamic of residue and soil organic matter mineralization. Diversity, structure and composition of microbial communities have been characterized before incubation time. The dynamic of carbon fluxes through CO2 emissions has been modelled through a simple model. Using statistical tools, relations between parameters of the model and microbial diversity indexes and/or pedological characteristics have been developed and integrated to the model. First results show that global diversity has an impact on the models parameters. Moreover, larger fungi diversity seems to lead to larger parameters representing decomposition rates and/or carbon use efficiencies than bacterial diversity. Classically, pedological factors such as soil pH and texture must also be taken into account.
Models for estimating photosynthesis parameters from in situ production profiles
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
Local sensitivity analysis of a distributed parameters water quality model
International Nuclear Information System (INIS)
Pastres, R.; Franco, D.; Pecenik, G.; Solidoro, C.; Dejak, C.
1997-01-01
A local sensitivity analysis is presented of a 1D water-quality reaction-diffusion model. The model describes the seasonal evolution of one of the deepest channels of the lagoon of Venice, that is affected by nutrient loads from the industrial area and heat emission from a power plant. Its state variables are: water temperature, concentrations of reduced and oxidized nitrogen, Reactive Phosphorous (RP), phytoplankton, and zooplankton densities, Dissolved Oxygen (DO) and Biological Oxygen Demand (BOD). Attention has been focused on the identifiability and the ranking of the parameters related to primary production in different mixing conditions
Information Theoretic Tools for Parameter Fitting in Coarse Grained Models
Kalligiannaki, Evangelia
2015-01-07
We study the application of information theoretic tools for model reduction in the case of systems driven by stochastic dynamics out of equilibrium. The model/dimension reduction is considered by proposing parametrized coarse grained dynamics and finding the optimal parameter set for which the relative entropy rate with respect to the atomistic dynamics is minimized. The minimization problem leads to a generalization of the force matching methods to non equilibrium systems. A multiplicative noise example reveals the importance of the diffusion coefficient in the optimization problem.
Near Work Related Parameters and Myopia in Chinese Children: the Anyang Childhood Eye Study
Li, Shi-Ming; Li, Si-Yuan; Kang, Meng-Tian; Zhou, Yuehua; Liu, Luo-Ru; Li, He; Wang, Yi-Peng; Zhan, Si-Yan; Gopinath, Bamini; Mitchell, Paul; Wang, Ningli
2015-01-01
Purpose To examine the associations of near work related parameters with spherical equivalent refraction and axial length in Chinese children. Methods A total of 1770 grade 7 students with mean age of 12.7 years were examined with cycloplegic autorefraction and axial length. Questions were asked regarding time spent in near work and outdoors per day, and near work related parameters. Results Multivariate models revealed the following associations with greater odds of myopia: continuous readin...
Empirical flow parameters : a tool for hydraulic model validity
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.
Optimizing incomplete sample designs for item response model parameters
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
Mass balance model parameter transferability on a tropical glacier
Gurgiser, Wolfgang; Mölg, Thomas; Nicholson, Lindsey; Kaser, Georg
2013-04-01
The mass balance and melt water production of glaciers is of particular interest in the Peruvian Andes where glacier melt water has markedly increased water supply during the pronounced dry seasons in recent decades. However, the melt water contribution from glaciers is projected to decrease with appreciable negative impacts on the local society within the coming decades. Understanding mass balance processes on tropical glaciers is a prerequisite for modeling present and future glacier runoff. As a first step towards this aim we applied a process-based surface mass balance model in order to calculate observed ablation at two stakes in the ablation zone of Shallap Glacier (4800 m a.s.l., 9°S) in the Cordillera Blanca, Peru. Under the tropical climate, the snow line migrates very frequently across most of the ablation zone all year round causing large temporal and spatial variations of glacier surface conditions and related ablation. Consequently, pronounced differences between the two chosen stakes and the two years were observed. Hourly records of temperature, humidity, wind speed, short wave incoming radiation, and precipitation are available from an automatic weather station (AWS) on the moraine near the glacier for the hydrological years 2006/07 and 2007/08 while stake readings are available at intervals of between 14 to 64 days. To optimize model parameters, we used 1000 model simulations in which the most sensitive model parameters were varied randomly within their physically meaningful ranges. The modeled surface height change was evaluated against the two stake locations in the lower ablation zone (SH11, 4760m) and in the upper ablation zone (SH22, 4816m), respectively. The optimal parameter set for each point achieved good model skill but if we transfer the best parameter combination from one stake site to the other stake site model errors increases significantly. The same happens if we optimize the model parameters for each year individually and transfer
DEFF Research Database (Denmark)
Willerslev, Eske; Hansen, Anders J.; Nielsen, Kirstine Klitgaard
2002-01-01
By simple and multiple regression analyses we investigate updated species numbers of endemic and native vascular plants and seed plants in the Galapagos Archipelago in relation to geographical parameters. We find that the best models to describe species numbers are regression models with log...... explained variation is in general small. The results show that the species area relationships are different for native and endemic species. This is discussed in relation to classical island biogeographical models, and the concepts of radiative speciation....
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 and Uncertainty Estimation in Groundwater Modelling
DEFF Research Database (Denmark)
Jensen, Jacob Birk
The data basis on which groundwater models are constructed is in general very incomplete, and this leads to uncertainty in model outcome. Groundwater models form the basis for many, often costly decisions and if these are to be made on solid grounds, the uncertainty attached to model results must...... be quantified. This study was motivated by the need to estimate the uncertainty involved in groundwater models.Chapter 2 presents an integrated surface/subsurface unstructured finite difference model that was developed and applied to a synthetic case study.The following two chapters concern calibration...... was applied.Capture zone modelling was conducted on a synthetic stationary 3-dimensional flow problem involving river, surface and groundwater flow. Simulated capture zones were illustrated as likelihood maps and compared with a deterministic capture zones derived from a reference model. The results showed...
WINKLER'S SINGLE-PARAMETER SUBGRADE MODEL FROM ...
African Journals Online (AJOL)
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SUBGRADE MODELING. Asrat Worku. Department of ... The models give consistently larger stiffness for the Winkler springs as compared to previously proposed similar continuum-based models that ignore the lateral stresses. ...... (ν = 0.25 and E = 40MPa); (b) a medium stiff clay (ν = 0.45 and E = 50MPa). In contrast to this, ...
DEFF Research Database (Denmark)
Willerslev, E.; Hansen, Anders J.; Nielsen, K. K.
2002-01-01
By simple and multiple regression analyses we investigate updated species numbers of endemic and native vascular plants and seed plants in the Galapagos Archipelago in relation to geographical parameters. We find that the best models to describe species numbers are regression models with log...
New relations between lN-scattering cross sections and neutral current parameters
International Nuclear Information System (INIS)
Bednyakov, V.A.; Kovalenko, S.G.
1989-01-01
New relations which connect cross sections with neutral current parameters have been obtained in deep inelastic and (quasi-)elastic ν(ν-bar)N, e ± (μ ± )N scattering. The relations are independent of the structure functions and formfactors of the nucleon. A known example is the Paschos-Wolfenstein relation in ν(ν-bar)N scattering. The relations have been obtained with allowance for the contribution of the extra Z' bozon which makes it possible to use them both for extractions of the standard model parameters (ρ, sin 2 Θ W ) and for the search for some manifestations of new physics. 21 refs.; 1 tab
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
Hydrological Modelling and Parameter Identification for Green Roof
Lo, W.; Tung, C.
2012-12-01
Green roofs, a multilayered system covered by plants, can be used to replace traditional concrete roofs as one of various measures to mitigate the increasing stormwater runoff in the urban environment. Moreover, facing the high uncertainty of the climate change, the present engineering method as adaptation may be regarded as improper measurements; reversely, green roofs are unregretful and flexible, and thus are rather important and suitable. The related technology has been developed for several years and the researches evaluating the stormwater reduction performance of green roofs are ongoing prosperously. Many European counties, cities in the U.S., and other local governments incorporate green roof into the stormwater control policy. Therefore, in terms of stormwater management, it is necessary to develop a robust hydrologic model to quantify the efficacy of green roofs over different types of designs and environmental conditions. In this research, a physical based hydrologic model is proposed to simulate water flowing process in the green roof system. In particular, the model adopts the concept of water balance, bringing a relatively simple and intuitive idea. Also, the research compares the two methods in the surface water balance calculation. One is based on Green-Ampt equation, and the other is under the SCS curve number calculation. A green roof experiment is designed to collect weather data and water discharge. Then, the proposed model is verified with these observed data; furthermore, the parameters using in the model are calibrated to find appropriate values in the green roof hydrologic simulation. This research proposes a simple physical based hydrologic model and the measures to determine parameters for the model.
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.
Estimation of Kinetic Parameters in an Automotive SCR Catalyst Model
DEFF Research Database (Denmark)
Åberg, Andreas; Widd, Anders; Abildskov, Jens
2016-01-01
A challenge during the development of models for simulation of the automotive Selective Catalytic Reduction catalyst is the parameter estimation of the kinetic parameters, which can be time consuming and problematic. The parameter estimation is often carried out on small-scale reactor tests...
Edge Modeling by Two Blur Parameters in Varying Contrasts.
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.
Estimation of Parameters in Latent Class Models with Constraints on the Parameters.
Paulson, James A.
This paper reviews the application of the EM Algorithm to marginal maximum likelihood estimation of parameters in the latent class model and extends the algorithm to the case where there are monotone homogeneity constraints on the item parameters. It is shown that the EM algorithm can be used to obtain marginal maximum likelihood estimates of the…
Flare parameters inferred from a 3D loop model database
Cuambe, Valente A.; Costa, J. E. R.; Simões, P. J. A.
2018-04-01
We developed a database of pre-calculated flare images and spectra exploring a set of parameters which describe the physical characteristics of coronal loops and accelerated electron distribution. Due to the large number of parameters involved in describing the geometry and the flaring atmosphere in the model used (Costa et al. 2013), we built a large database of models (˜250 000) to facilitate the flare analysis. The geometry and characteristics of non-thermal electrons are defined on a discrete grid with spatial resolution greater than 4 arcsec. The database was constructed based on general properties of known solar flares and convolved with instrumental resolution to replicate the observations from the Nobeyama radio polarimeter (NoRP) spectra and Nobeyama radio-heliograph (NoRH) brightness maps. Observed spectra and brightness distribution maps are easily compared with the modelled spectra and images in the database, indicating a possible range of solutions. The parameter search efficiency in this finite database is discussed. Eight out of ten parameters analysed for one thousand simulated flare searches were recovered with a relative error of less than 20 per cent on average. In addition, from the analysis of the observed correlation between NoRH flare sizes and intensities at 17 GHz, some statistical properties were derived. From these statistics the energy spectral index was found to be δ ˜ 3, with non-thermal electron densities showing a peak distribution ⪅107 cm-3, and Bphotosphere ⪆2000 G. Some bias for larger loops with heights as great as ˜2.6 × 109 cm, and looptop events were noted. An excellent match of the spectrum and the brightness distribution at 17 and 34 GHz of the 2002 May 31 flare, is presented as well.
Clark, D Angus; Nuttall, Amy K; Bowles, Ryan P
2018-01-01
Latent change score models (LCS) are conceptually powerful tools for analyzing longitudinal data (McArdle & Hamagami, 2001). However, applications of these models typically include constraints on key parameters over time. Although practically useful, strict invariance over time in these parameters is unlikely in real data. This study investigates the robustness of LCS when invariance over time is incorrectly imposed on key change-related parameters. Monte Carlo simulation methods were used to explore the impact of misspecification on parameter estimation, predicted trajectories of change, and model fit in the dual change score model, the foundational LCS. When constraints were incorrectly applied, several parameters, most notably the slope (i.e., constant change) factor mean and autoproportion coefficient, were severely and consistently biased, as were regression paths to the slope factor when external predictors of change were included. Standard fit indices indicated that the misspecified models fit well, partly because mean level trajectories over time were accurately captured. Loosening constraint improved the accuracy of parameter estimates, but estimates were more unstable, and models frequently failed to converge. Results suggest that potentially common sources of misspecification in LCS can produce distorted impressions of developmental processes, and that identifying and rectifying the situation is a challenge.
Incremental parameter estimation of kinetic metabolic network models
Directory of Open Access Journals (Sweden)
Jia Gengjie
2012-11-01
Full Text Available Abstract Background An efficient and reliable parameter estimation method is essential for the creation of biological models using ordinary differential equation (ODE. Most of the existing estimation methods involve finding the global minimum of data fitting residuals over the entire parameter space simultaneously. Unfortunately, the associated computational requirement often becomes prohibitively high due to the large number of parameters and the lack of complete parameter identifiability (i.e. not all parameters can be uniquely identified. Results In this work, an incremental approach was applied to the parameter estimation of ODE models from concentration time profiles. Particularly, the method was developed to address a commonly encountered circumstance in the modeling of metabolic networks, where the number of metabolic fluxes (reaction rates exceeds that of metabolites (chemical species. Here, the minimization of model residuals was performed over a subset of the parameter space that is associated with the degrees of freedom in the dynamic flux estimation from the concentration time-slopes. The efficacy of this method was demonstrated using two generalized mass action (GMA models, where the method significantly outperformed single-step estimations. In addition, an extension of the estimation method to handle missing data is also presented. Conclusions The proposed incremental estimation method is able to tackle the issue on the lack of complete parameter identifiability and to significantly reduce the computational efforts in estimating model parameters, which will facilitate kinetic modeling of genome-scale cellular metabolism in the future.
A simulation of water pollution model parameter estimation
Kibler, J. F.
1976-01-01
A parameter estimation procedure for a water pollution transport model is elaborated. A two-dimensional instantaneous-release shear-diffusion model serves as representative of a simple transport process. Pollution concentration levels are arrived at via modeling of a remote-sensing system. The remote-sensed data are simulated by adding Gaussian noise to the concentration level values generated via the transport model. Model parameters are estimated from the simulated data using a least-squares batch processor. Resolution, sensor array size, and number and location of sensor readings can be found from the accuracies of the parameter estimates.
Lumped parameter models for the interpretation of environmental tracer data
International Nuclear Information System (INIS)
Maloszewski, P.; Zuber, A.
1996-01-01
Principles of the lumped-parameter approach to the interpretation of environmental tracer data are given. The following models are considered: the piston flow model (PFM), exponential flow model (EM), linear model (LM), combined piston flow and exponential flow model (EPM), combined linear flow and piston flow model (LPM), and dispersion model (DM). The applicability of these models for the interpretation of different tracer data is discussed for a steady state flow approximation. Case studies are given to exemplify the applicability of the lumped-parameter approach. Description of a user-friendly computer program is given. (author). 68 refs, 25 figs, 4 tabs
Assessing models for parameters of the Ångström-Prescott formula in China
DEFF Research Database (Denmark)
Liu, Xiaoying; Xu, Yinlong; Zhong, Xiuli
2012-01-01
Application of the Ångström–Prescott (A–P) model, one of the best rated global solar irradiation (Rs) models based on sunshine, is often limited by the lack of model parameters. Increasing the availability of its parameters in the absence of Rs measurement provides an effective way to overcome...... this problem. Although some models relating the A–P parameters to other variables have been developed, they generally lack worldwide validity test. Using data from 80 sites covering three agro-climatic zones in China, we evaluated seven models that relate the parameters to annual average of relative sunshine...... in zone I in predicting Rs, indicating larger errors in humid climates. Since most productive agricultural areas in China are located in zone I, developing parameter models tailored to this zone would be valuable to improve Rs accuracy....
Modeling Water Quality Parameters Using Data-driven Methods
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Shima Soleimani
2017-02-01
Full Text Available Introduction: Surface water bodies are the most easily available water resources. Increase use and waste water withdrawal of surface water causes drastic changes in surface water quality. Water quality, importance as the most vulnerable and important water supply resources is absolutely clear. Unfortunately, in the recent years because of city population increase, economical improvement, and industrial product increase, entry of pollutants to water bodies has been increased. According to that water quality parameters express physical, chemical, and biological water features. So the importance of water quality monitoring is necessary more than before. Each of various uses of water, such as agriculture, drinking, industry, and aquaculture needs the water with a special quality. In the other hand, the exact estimation of concentration of water quality parameter is significant. Material and Methods: In this research, first two input variable models as selection methods (namely, correlation coefficient and principal component analysis were applied to select the model inputs. Data processing is consisting of three steps, (1 data considering, (2 identification of input data which have efficient on output data, and (3 selecting the training and testing data. Genetic Algorithm-Least Square Support Vector Regression (GA-LSSVR algorithm were developed to model the water quality parameters. In the LSSVR method is assumed that the relationship between input and output variables is nonlinear, but by using a nonlinear mapping relation can create a space which is named feature space in which relationship between input and output variables is defined linear. The developed algorithm is able to gain maximize the accuracy of the LSSVR method with auto LSSVR parameters. Genetic algorithm (GA is one of evolutionary algorithm which automatically can find the optimum coefficient of Least Square Support Vector Regression (LSSVR. The GA-LSSVR algorithm was employed to
WATGIS: A GIS-Based Lumped Parameter Water Quality Model
Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya
2002-01-01
A Geographic Information System (GIS)Âbased, lumped parameter water quality model was developed to estimate the spatial and temporal nitrogenÂloading patterns for lower coastal plain watersheds in eastern North Carolina. The model uses a spatially distributed delivery ratio (DR) parameter to account for nitrogen retention or loss along a drainage network. Delivery...
Exploring the interdependencies between parameters in a material model.
Energy Technology Data Exchange (ETDEWEB)
Silling, Stewart Andrew; Fermen-Coker, Muge
2014-01-01
A method is investigated to reduce the number of numerical parameters in a material model for a solid. The basis of the method is to detect interdependencies between parameters within a class of materials of interest. The method is demonstrated for a set of material property data for iron and steel using the Johnson-Cook plasticity model.
Regionalization of SWAT Model Parameters for Use in Ungauged Watersheds
Directory of Open Access Journals (Sweden)
Indrajeet Chaubey
2010-11-01
Full Text Available There has been a steady shift towards modeling and model-based approaches as primary methods of assessing watershed response to hydrologic inputs and land management, and of quantifying watershed-wide best management practice (BMP effectiveness. Watershed models often require some degree of calibration and validation to achieve adequate watershed and therefore BMP representation. This is, however, only possible for gauged watersheds. There are many watersheds for which there are very little or no monitoring data available, thus the question as to whether it would be possible to extend and/or generalize model parameters obtained through calibration of gauged watersheds to ungauged watersheds within the same region. This study explored the possibility of developing regionalized model parameter sets for use in ungauged watersheds. The study evaluated two regionalization methods: global averaging, and regression-based parameters, on the SWAT model using data from priority watersheds in Arkansas. Resulting parameters were tested and model performance determined on three gauged watersheds. Nash-Sutcliffe efficiencies (NS for stream flow obtained using regression-based parameters (0.53–0.83 compared well with corresponding values obtained through model calibration (0.45–0.90. Model performance obtained using global averaged parameter values was also generally acceptable (0.4 ≤ NS ≤ 0.75. Results from this study indicate that regionalized parameter sets for the SWAT model can be obtained and used for making satisfactory hydrologic response predictions in ungauged watersheds.
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
Brownian motion model with stochastic parameters for asset prices
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.
Estimation of shape model parameters for 3D surfaces
DEFF Research Database (Denmark)
Erbou, Søren Gylling Hemmingsen; Darkner, Sune; Fripp, Jurgen
2008-01-01
is applied to a database of 3D surfaces from a section of the porcine pelvic bone extracted from 33 CT scans. A leave-one-out validation shows that the parameters of the first 3 modes of the shape model can be predicted with a mean difference within [-0.01,0.02] from the true mean, with a standard deviation......Statistical shape models are widely used as a compact way of representing shape variation. Fitting a shape model to unseen data enables characterizing the data in terms of the model parameters. In this paper a Gauss-Newton optimization scheme is proposed to estimate shape model parameters of 3D...... surfaces using distance maps, which enables the estimation of model parameters without the requirement of point correspondence. For applications with acquisition limitations such as speed and cost, this formulation enables the fitting of a statistical shape model to arbitrarily sampled data. The method...
Phosphorus adsorption parameters in relation to soil characteristics
International Nuclear Information System (INIS)
Mehmood, A.; Akther, M.S.; Hayat, R.; Memon, M.
2010-01-01
Understanding of soil phosphorus (P) adsorption chemistry is essential for evolving best fertilizer management practices aimed at enhancing fertilizer P use efficiency and environment quality. Soil chemical parameters which govern P adsorption maxima and binding strength in calcareous and non-calcareous soils were determined. Five soils representing three different parent materials i.e. mixed mineralogy alluvium, loess and non calcareous sandstone were sampled at genetic horizons in each profile. Phosphorus adsorption isotherm was developed for each of the 32 soil samples by equilibration of two g air dry soil with 0 to 4000 mgl/sup -1/ (0 to 125 mM) P in 20 ml of 10 mM KCI; and fitted to Langmuir and Freundlich equations. The chemical parameters i.e. pH, CaCO/sub 3/, total and dissolved organic carbon, exchangeable calcium, dithionite extractable iron (Fe/sub d/) and aluminum (AI/sub d/), oxalate extractable iron (Fe/sub o/) and aluminum (Al/sub o/) and as a test for plant available P extractable with NaHCO/sub 3/ were determined. The Fruendlich equation, an empirical relation between adsorbed and solution P, fitted the adsorption isotherms better than the Langmuir equation which relates adsorption to solid surface coverage by adsorbate. Adsorption maxima at low affinity sites positively correlated with soil CaCO/sub 3/ due to precipitation as Ca-P and to extractable iron oxide; and the binding strength of high affinity (kJ sites correlated positively with soil Fe/sub d/, Al/sub o/, AI/sub d/, and crystalline iron oxide (Fe/sub d/-Fe/sub o/) contents. The Freundlich parameter b/sub r/, adsorption exponent which signifies sorption intensity also positively correlated with soil Fe/sub d/, Fe/sub cr/ and Aid contents. Phosphorus adsorption at its low concentration in equilibrium solution seems to be governed by soil iron oxides and precipitation as Ca-P is important only at high P concentration, less frequently achieved in farm fields. (author)
Determination of the Corona model parameters with artificial neural networks
International Nuclear Information System (INIS)
Ahmet, Nayir; Bekir, Karlik; Arif, Hashimov
2005-01-01
Full text : The aim of this study is to calculate new model parameters taking into account the corona of electrical transmission line wires. For this purpose, a neural network modeling proposed for the corona frequent characteristics modeling. Then this model was compared with the other model developed at the Polytechnic Institute of Saint Petersburg. The results of development of the specified corona model for calculation of its influence on the wave processes in multi-wires line and determination of its parameters are submitted. Results of obtained calculation equations are brought for electrical transmission line with allowance for superficial effect in the ground and wires with reference to developed corona model
Wentworth, Mami Tonoe
techniques for model calibration. For Bayesian model calibration, we employ adaptive Metropolis algorithms to construct densities for input parameters in the heat model and the HIV model. To quantify the uncertainty in the parameters, we employ two MCMC algorithms: Delayed Rejection Adaptive Metropolis (DRAM) [33] and Differential Evolution Adaptive Metropolis (DREAM) [66, 68]. The densities obtained using these methods are compared to those obtained through the direct numerical evaluation of the Bayes' formula. We also combine uncertainties in input parameters and measurement errors to construct predictive estimates for a model response. A significant emphasis is on the development and illustration of techniques to verify the accuracy of sampling-based Metropolis algorithms. We verify the accuracy of DRAM and DREAM by comparing chains, densities and correlations obtained using DRAM, DREAM and the direct evaluation of Bayes formula. We also perform similar analysis for credible and prediction intervals for responses. Once the parameters are estimated, we employ energy statistics test [63, 64] to compare the densities obtained by different methods for the HIV model. The energy statistics are used to test the equality of distributions. We also consider parameter selection and verification techniques for models having one or more parameters that are noninfluential in the sense that they minimally impact model outputs. We illustrate these techniques for a dynamic HIV model but note that the parameter selection and verification framework is applicable to a wide range of biological and physical models. To accommodate the nonlinear input to output relations, which are typical for such models, we focus on global sensitivity analysis techniques, including those based on partial correlations, Sobol indices based on second-order model representations, and Morris indices, as well as a parameter selection technique based on standard errors. A significant objective is to provide
Empirically modelled Pc3 activity based on solar wind parameters
Directory of Open Access Journals (Sweden)
B. Heilig
2010-09-01
Full Text Available It is known that under certain solar wind (SW/interplanetary magnetic field (IMF conditions (e.g. high SW speed, low cone angle the occurrence of ground-level Pc3–4 pulsations is more likely. In this paper we demonstrate that in the event of anomalously low SW particle density, Pc3 activity is extremely low regardless of otherwise favourable SW speed and cone angle. We re-investigate the SW control of Pc3 pulsation activity through a statistical analysis and two empirical models with emphasis on the influence of SW density on Pc3 activity. We utilise SW and IMF measurements from the OMNI project and ground-based magnetometer measurements from the MM100 array to relate SW and IMF measurements to the occurrence of Pc3 activity. Multiple linear regression and artificial neural network models are used in iterative processes in order to identify sets of SW-based input parameters, which optimally reproduce a set of Pc3 activity data. The inclusion of SW density in the parameter set significantly improves the models. Not only the density itself, but other density related parameters, such as the dynamic pressure of the SW, or the standoff distance of the magnetopause work equally well in the model. The disappearance of Pc3s during low-density events can have at least four reasons according to the existing upstream wave theory: 1. Pausing the ion-cyclotron resonance that generates the upstream ultra low frequency waves in the absence of protons, 2. Weakening of the bow shock that implies less efficient reflection, 3. The SW becomes sub-Alfvénic and hence it is not able to sweep back the waves propagating upstream with the Alfvén-speed, and 4. The increase of the standoff distance of the magnetopause (and of the bow shock. Although the models cannot account for the lack of Pc3s during intervals when the SW density is extremely low, the resulting sets of optimal model inputs support the generation of mid latitude Pc3 activity predominantly through
Spatio-temporal modeling of nonlinear distributed parameter systems
Li, Han-Xiong
2011-01-01
The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein s
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. ...
Determining extreme parameter correlation in ground water models
DEFF Research Database (Denmark)
Hill, Mary Cole; Østerby, Ole
2003-01-01
In ground water flow system models with hydraulic-head observations but without significant imposed or observed flows, extreme parameter correlation generally exists. As a result, hydraulic conductivity and recharge parameters cannot be uniquely estimated. In complicated problems, such correlation...... correlation coefficients 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...
Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model
Zuhdi, Shaifudin; Retno Sari Saputro, Dewi; Widyaningsih, Purnami
2017-06-01
A regression model is the representation of relationship between independent variable and dependent variable. The dependent variable has categories used in the logistic regression model to calculate odds on. The logistic regression model for dependent variable has levels in the logistics regression model is ordinal. GWOLR model is an ordinal logistic regression model influenced the geographical location of the observation site. Parameters estimation in the model needed to determine the value of a population based on sample. The purpose of this research is to parameters estimation of GWOLR model using R software. Parameter estimation uses the data amount of dengue fever patients in Semarang City. Observation units used are 144 villages in Semarang City. The results of research get GWOLR model locally for each village and to know probability of number dengue fever patient categories.
Modeling and Parameter Estimation of a Small Wind Generation System
Directory of Open Access Journals (Sweden)
Carlos A. Ramírez Gómez
2013-11-01
Full Text Available The modeling and parameter estimation of a small wind generation system is presented in this paper. The system consists of a wind turbine, a permanent magnet synchronous generator, a three phase rectifier, and a direct current load. In order to estimate the parameters wind speed data are registered in a weather station located in the Fraternidad Campus at ITM. Wind speed data were applied to a reference model programed with PSIM software. From that simulation, variables were registered to estimate the parameters. The wind generation system model together with the estimated parameters is an excellent representation of the detailed model, but the estimated model offers a higher flexibility than the programed model in PSIM software.
Parameter estimation of variable-parameter nonlinear Muskingum model using excel solver
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.
He, Minxue; Hogue, Terri S.; Franz, Kristie J.; Margulis, Steven A.; Vrugt, Jasper A.
2011-07-01
The current study evaluates the impacts of various sources of uncertainty involved in hydrologic modeling on parameter behavior and regionalization utilizing different Bayesian likelihood functions and the Differential Evolution Adaptive Metropolis (DREAM) algorithm. The developed likelihood functions differ in their underlying assumptions and treatment of error sources. We apply the developed method to a snow accumulation and ablation model (National Weather Service SNOW17) and generate parameter ensembles to predict snow water equivalent (SWE). Observational data include precipitation and air temperature forcing along with SWE measurements from 24 sites with diverse hydroclimatic characteristics. A multiple linear regression model is used to construct regionalization relationships between model parameters and site characteristics. Results indicate that model structural uncertainty has the largest influence on SNOW17 parameter behavior. Precipitation uncertainty is the second largest source of uncertainty, showing greater impact at wetter sites. Measurement uncertainty in SWE tends to have little impact on the final model parameters and resulting SWE predictions. Considering all sources of uncertainty, parameters related to air temperature and snowfall fraction exhibit the strongest correlations to site characteristics. Parameters related to the length of the melting period also show high correlation to site characteristics. Finally, model structural uncertainty and precipitation uncertainty dramatically alter parameter regionalization relationships in comparison to cases where only uncertainty in model parameters or output measurements is considered. Our results demonstrate that accurate treatment of forcing, parameter, model structural, and calibration data errors is critical for deriving robust regionalization relationships.
Zoom lens calibration with zoom- and focus-related intrinsic parameters applied to bundle adjustment
Zheng, Shunyi; Wang, Zheng; Huang, Rongyong
2015-04-01
A zoom lens is more flexible for photogrammetric measurements under diverse environments than a fixed lens. However, challenges in calibration of zoom-lens cameras preclude the wide use of zoom lenses in the field of close-range photogrammetry. Thus, a novel zoom lens calibration method is proposed in this study. In this method, instead of conducting modeling after monofocal calibrations, we summarize the empirical zoom/focus models of intrinsic parameters first and then incorporate these parameters into traditional collinearity equations to construct the fundamental mathematical model, i.e., collinearity equations with zoom- and focus-related intrinsic parameters. Similar to monofocal calibration, images taken at several combinations of zoom and focus settings are processed in a single self-calibration bundle adjustment. In the self-calibration bundle adjustment, three types of unknowns, namely, exterior orientation parameters, unknown space point coordinates, and model coefficients of the intrinsic parameters, are solved simultaneously. Experiments on three different digital cameras with zoom lenses support the feasibility of the proposed method, and their relative accuracies range from 1:4000 to 1:15,100. Furthermore, the nominal focal length written in the exchangeable image file header is found to lack reliability in experiments. Thereafter, the joint influence of zoom lens instability and zoom recording errors is further analyzed quantitatively. The analysis result is consistent with the experimental result and explains the reason why zoom lens calibration can never have the same accuracy as monofocal self-calibration.
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)
The electronic disability record: purpose, parameters, and model use case.
Tulu, Bengisu; Horan, Thomas A
2009-01-01
The active engagement of consumers is an important factor in achieving widespread success of health information systems. The disability community represents a major segment of the healthcare arena, with more than 50 million Americans experiencing some form of disability. In keeping with the "consumer-driven" approach to e-health systems, this paper considers the distinctive aspects of electronic and personal health record use by this segment of society. Drawing upon the information shared during two national policy forums on this topic, the authors present the concept of Electronic Disability Records (EDR). The authors outline the purpose and parameters of such records, with specific attention to its ability to organize health and financial data in a manner that can be used to expedite the disability determination process. In doing so, the authors discuss its interaction with Electronic Health Records (EHR) and Personal Health Records (PHR). The authors then draw upon these general parameters to outline a model use case for disability determination and discuss related implications for disability health management. The paper further reports on the subsequent considerations of these and related deliberations by the American Health Information Community (AHIC).
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)
Diabatic models with transferrable parameters for generalized chemical reactions
Reimers, Jeffrey R.; McKemmish, Laura K.; McKenzie, Ross H.; Hush, Noel S.
2017-05-01
Diabatic models applied to adiabatic electron-transfer theory yield many equations involving just a few parameters that connect ground-state geometries and vibration frequencies to excited-state transition energies and vibration frequencies to the rate constants for electron-transfer reactions, utilizing properties of the conical-intersection seam linking the ground and excited states through the Pseudo Jahn-Teller effect. We review how such simplicity in basic understanding can also be obtained for general chemical reactions. The key feature that must be recognized is that electron-transfer (or hole transfer) processes typically involve one electron (hole) moving between two orbitals, whereas general reactions typically involve two electrons or even four electrons for processes in aromatic molecules. Each additional moving electron leads to new high-energy but interrelated conical-intersection seams that distort the shape of the critical lowest-energy seam. Recognizing this feature shows how conical-intersection descriptors can be transferred between systems, and how general chemical reactions can be compared using the same set of simple parameters. Mathematical relationships are presented depicting how different conical-intersection seams relate to each other, showing that complex problems can be reduced into an effective interaction between the ground-state and a critical excited state to provide the first semi-quantitative implementation of Shaik’s “twin state” concept. Applications are made (i) demonstrating why the chemistry of the first-row elements is qualitatively so different to that of the second and later rows, (ii) deducing the bond-length alternation in hypothetical cyclohexatriene from the observed UV spectroscopy of benzene, (iii) demonstrating that commonly used procedures for modelling surface hopping based on inclusion of only the first-derivative correction to the Born-Oppenheimer approximation are valid in no region of the chemical
Parameter estimation for groundwater models under uncertain irrigation data
Demissie, Yonas; Valocchi, Albert J.; Cai, Ximing; Brozovic, Nicholas; Senay, Gabriel; Gebremichael, Mekonnen
2015-01-01
The success of modeling groundwater is strongly influenced by the accuracy of the model parameters that are used to characterize the subsurface system. However, the presence of uncertainty and possibly bias in groundwater model source/sink terms may lead to biased estimates of model parameters and model predictions when the standard regression-based inverse modeling techniques are used. This study first quantifies the levels of bias in groundwater model parameters and predictions due to the presence of errors in irrigation data. Then, a new inverse modeling technique called input uncertainty weighted least-squares (IUWLS) is presented for unbiased estimation of the parameters when pumping and other source/sink data are uncertain. The approach uses the concept of generalized least-squares method with the weight of the objective function depending on the level of pumping uncertainty and iteratively adjusted during the parameter optimization process. We have conducted both analytical and numerical experiments, using irrigation pumping data from the Republican River Basin in Nebraska, to evaluate the performance of ordinary least-squares (OLS) and IUWLS calibration methods under different levels of uncertainty of irrigation data and calibration conditions. The result from the OLS method shows the presence of statistically significant (p model predictions that persist despite calibrating the models to different calibration data and sample sizes. However, by directly accounting for the irrigation pumping uncertainties during the calibration procedures, the proposed IUWLS is able to minimize the bias effectively without adding significant computational burden to the calibration processes.
Remote sensing of wetland parameters related to carbon cycling
Bartlett, David S.; Johnson, Robert W.
1985-01-01
Measurement of the rates of important biogeochemical fluxes on regional or global scales is vital to understanding the geochemical and climatic consequences of natural biospheric processes and of human intervention in those processes. Remote data gathering and interpretation techniques were used to examine important cycling processes taking place in wetlands over large geographic expanses. Large area estimation of vegetative biomass and productivity depends upon accurate, consistent measurements of canopy spectral reflectance and upon wide applicability of algorithms relating reflectance to biometric parameters. Results of the use of airborne multispectral scanner data to map above-ground biomass in a Delaware salt marsh are shown. The mapping uses an effective algorithm linking biomass to measured spectral reflectance and a means to correct the scanner data for large variations in the angle of observation of the canopy. The consistency of radiometric biomass algorithms for marsh grass when they are applied over large latitudinal and tidal range gradients were also examined. Results of a 1 year study of methane emissions from tidal wetlands along a salinity gradient show marked effects of temperature, season, and pore-water chemistry in mediating flux to the atmosphere.
International Nuclear Information System (INIS)
Marin Arias, Juan Pablo; Salcedo Hurtado, Elkin de Jesus; Castillo Gonzalez, Hardany
2008-01-01
In order to establish the relationships between macroseismic and instrumental parameters, macroseismic field of 28 historical earthquakes that produced great effects in the Colombian territory were studied. The integration of the parameters was made by using the methodology of Kaussel and Ramirez (1992), for great Chilean earthquakes; Kanamori and Anderson (1975) and Coppersmith and Well (1994) for world-wide earthquakes. Once determined the macroseismic and instrumental parameters it was come to establish the model of the source of each earthquake, with which the data base of these parameters was completed. For each earthquake parameters related to the local and normal macroseismic epicenter were complemented, depth of the local and normal center, horizontal extension of both centers, vertical extension of the normal center, model of the source, area of rupture. The obtained empirical relations from linear equations, even show behaviors very similar to the found ones by other authors for other regions of the world and to world-wide level. The results of this work allow establishing that certain mutual non compatibility exists between the area of rupture and the length of rupture determined by the macroseismic methods, with parameters found with instrumental data like seismic moment, Ms magnitude and Mw magnitude.
Transformations among CE–CVM model parameters for ...
Indian Academy of Sciences (India)
Unknown
parameters which exclusively represent interactions of the higher order systems. Such a procedure is presen- ted in detail in this communication. Furthermore, the details of transformations required to express the model parameters in one basis from those defined in another basis for the same system are also presented.
Transformations among CE–CVM model parameters for ...
Indian Academy of Sciences (India)
... of parameters which exclusively represent interactions of the higher order systems. Such a procedure is presented in detail in this communication. Furthermore, the details of transformations required to express the model parameters in one basis from those defined in another basis for the same system are also presented.
Prior distributions for item parameters in IRT models
Matteucci, M.; S. Mignani, Prof.; Veldkamp, Bernard P.
2012-01-01
The focus of this article is on the choice of suitable prior distributions for item parameters within item response theory (IRT) models. In particular, the use of empirical prior distributions for item parameters is proposed. Firstly, regression trees are implemented in order to build informative
Retrospective forecast of ETAS model with daily parameters estimate
Falcone, Giuseppe; Murru, Maura; Console, Rodolfo; Marzocchi, Warner; Zhuang, Jiancang
2016-04-01
We present a retrospective ETAS (Epidemic Type of Aftershock Sequence) model based on the daily updating of free parameters during the background, the learning and the test phase of a seismic sequence. The idea was born after the 2011 Tohoku-Oki earthquake. The CSEP (Collaboratory for the Study of Earthquake Predictability) Center in Japan provided an appropriate testing benchmark for the five 1-day submitted models. Of all the models, only one was able to successfully predict the number of events that really happened. This result was verified using both the real time and the revised catalogs. The main cause of the failure was in the underestimation of the forecasted events, due to model parameters maintained fixed during the test. Moreover, the absence in the learning catalog of an event similar to the magnitude of the mainshock (M9.0), which drastically changed the seismicity in the area, made the learning parameters not suitable to describe the real seismicity. As an example of this methodological development we show the evolution of the model parameters during the last two strong seismic sequences in Italy: the 2009 L'Aquila and the 2012 Reggio Emilia episodes. The achievement of the model with daily updated parameters is compared with that of same model where the parameters remain fixed during the test time.
Stochastic hyperelastic modeling considering dependency of material parameters
Caylak, Ismail; Penner, Eduard; Dridger, Alex; Mahnken, Rolf
2018-03-01
This paper investigates the uncertainty of a hyperelastic model by treating random material parameters as stochastic variables. For its stochastic discretization a polynomial chaos expansion (PCE) is used. An important aspect in our work is the consideration of stochastic dependencies in the stochastic modeling of Ogden's material model. To this end, artificial experiments are generated using the auto-regressive moving average process based on real experiments. The parameter identification for all data provides statistics of Ogden's material parameters, which are subsequently used for stochastic modeling. Stochastic dependencies are incorporated into the PCE using a Nataf transformation from dependent distributed random variables to independent standard normal distributed ones. The representative numerical example shows that our proposed method adequately takes into account the stochastic dependencies of Ogden's material parameters.
A compact cyclic plasticity model with parameter evolution
DEFF Research Database (Denmark)
Krenk, Steen; Tidemann, L.
2017-01-01
by the Armstrong–Frederick model, contained as a special case of the present model for a particular choice of the shape parameter. In contrast to previous work, where shaping the stress-strain loops is derived from multiple internal stress states, this effect is here represented by a single parameter......The paper presents a compact model for cyclic plasticity based on energy in terms of external and internal variables, and plastic yielding described by kinematic hardening and a flow potential with an additive term controlling the nonlinear cyclic hardening. The model is basically described by five...... parameters: external and internal stiffness, a yield stress and a limiting ultimate stress, and finally a parameter controlling the gradual development of plastic deformation. Calibration against numerous experimental results indicates that typically larger plastic strains develop than predicted...
Parameter Estimation for the Thurstone Case III Model.
Mackay, David B.; Chaiy, Seoil
1982-01-01
The ability of three estimation criteria to recover parameters of the Thurstone Case V and Case III models from comparative judgment data was investigated via Monte Carlo techniques. Significant differences in recovery are shown to exist. (Author/JKS)
Improved parameter estimation for hydrological models using weighted object functions
Stein, A.; Zaadnoordijk, W.J.
1999-01-01
This paper discusses the sensitivity of calibration of hydrological model parameters to different objective functions. Several functions are defined with weights depending upon the hydrological background. These are compared with an objective function based upon kriging. Calibration is applied to
DEFF Research Database (Denmark)
Pauwels, Valentijn; Balenzano, Anna; Satalino, Giuseppe
2009-01-01
that no direct relationships between the remote-sensing observations, more specifically radar backscatter values, and the parameter values can be derived. However, land surface models can provide these relationships. The objective of this paper is to retrieve a number of soil physical model parameters through...... model is, thus, used to determine the relationship between the soil physical parameters and the remote-sensing data. An analysis is then performed, relating the retrieved soil parameters to the soil texture data available over the study area. The results of the study show that there is a potential...
Sound propagation and absorption in foam - A distributed parameter model.
Manson, L.; Lieberman, S.
1971-01-01
Liquid-base foams are highly effective sound absorbers. A better understanding of the mechanisms of sound absorption in foams was sought by exploration of a mathematical model of bubble pulsation and coupling and the development of a distributed-parameter mechanical analog. A solution by electric-circuit analogy was thus obtained and transmission-line theory was used to relate the physical properties of the foams to the characteristic impedance and propagation constants of the analog transmission line. Comparison of measured physical properties of the foam with values obtained from measured acoustic impedance and propagation constants and the transmission-line theory showed good agreement. We may therefore conclude that the sound propagation and absorption mechanisms in foam are accurately described by the resonant response of individual bubbles coupled to neighboring bubbles.
Partial sum approaches to mathematical parameters of some growth models
Korkmaz, Mehmet
2016-04-01
Growth model is fitted by evaluating the mathematical parameters, a, b and c. In this study, the method of partial sums were used. For finding the mathematical parameters, firstly three partial sums were used, secondly four partial sums were used, thirdly five partial sums were used and finally N partial sums were used. The purpose of increasing the partial decomposition is to produce a better phase model which gives a better expected value by minimizing error sum of squares in the interval used.
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....... For a comparison the parameters are also estimated by an output error method, where the sum of squared simulation error is minimized. The former methodology is optimal for short-term prediction whereas the latter is optimal for simulations. Hence, depending on the purpose it is possible to select whether...... the parameter values are optimal for simulation or prediction. The data originates from Iceland and the model is designed for Icelandic conditions, including a snow routine for mountainous areas. The model demands only two input data series, precipitation and temperature and one output data series...
Luminescence model with quantum impact parameter for low energy ions
Cruz-Galindo, H S; Martínez-Davalos, A; Belmont-Moreno, E; Galindo, S
2002-01-01
We have modified an analytical model of induced light production by energetic ions interacting in scintillating materials. The original model is based on the distribution of energy deposited by secondary electrons produced along the ion's track. The range of scattered electrons, and thus the energy distribution, depends on a classical impact parameter between the electron and the ion's track. The only adjustable parameter of the model is the quenching density rho sub q. The modification here presented, consists in proposing a quantum impact parameter that leads to a better fit of the model to the experimental data at low incident ion energies. The light output response of CsI(Tl) detectors to low energy ions (<3 MeV/A) is fitted with the modified model and comparison is made to the original model.
Study of the seismic source parameters and its relation with other seismic engineering parameters
Rodríguez-Pérez, Quetzalcoatl
2013-01-01
The term seismic source refers to the sources which can generate seismic waves. The seismic source of tectonic earthquakes is represented as a displacement discontinuity on a plane surface as a result of shear faulting. Earthquakes can be defined as a rapid release of strain energy caused by tectonic forces. The elastic wave radiation carries with it information concerning the parameters of faulting or seismic source parameters, so estimating them provides us valuable informati...
Agricultural and Environmental Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
K. Rasmuson; K. Rautenstrauch
2004-01-01
This analysis is one of 10 technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) (i.e., the biosphere model). It documents development of agricultural and environmental input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the ERMYN and its input parameters
Combined Estimation of Hydrogeologic Conceptual Model and Parameter Uncertainty
Energy Technology Data Exchange (ETDEWEB)
Meyer, Philip D.; Ye, Ming; Neuman, Shlomo P.; Cantrell, Kirk J.
2004-03-01
The objective of the research described in this report is the development and application of a methodology for comprehensively assessing the hydrogeologic uncertainties involved in dose assessment, including uncertainties associated with conceptual models, parameters, and scenarios. This report describes and applies a statistical method to quantitatively estimate the combined uncertainty in model predictions arising from conceptual model and parameter uncertainties. The method relies on model averaging to combine the predictions of a set of alternative models. Implementation is driven by the available data. When there is minimal site-specific data the method can be carried out with prior parameter estimates based on generic data and subjective prior model probabilities. For sites with observations of system behavior (and optionally data characterizing model parameters), the method uses model calibration to update the prior parameter estimates and model probabilities based on the correspondence between model predictions and site observations. The set of model alternatives can contain both simplified and complex models, with the requirement that all models be based on the same set of data. The method was applied to the geostatistical modeling of air permeability at a fractured rock site. Seven alternative variogram models of log air permeability were considered to represent data from single-hole pneumatic injection tests in six boreholes at the site. Unbiased maximum likelihood estimates of variogram and drift parameters were obtained for each model. Standard information criteria provided an ambiguous ranking of the models, which would not justify selecting one of them and discarding all others as is commonly done in practice. Instead, some of the models were eliminated based on their negligibly small updated probabilities and the rest were used to project the measured log permeabilities by kriging onto a rock volume containing the six boreholes. These four
SPOTting Model Parameters Using a Ready-Made Python Package.
Directory of Open Access Journals (Sweden)
Tobias Houska
Full Text Available The choice for specific parameter estimation methods is often more dependent on its availability than its performance. We developed SPOTPY (Statistical Parameter Optimization Tool, an open source python package containing a comprehensive set of methods typically used to calibrate, analyze and optimize parameters for a wide range of ecological models. SPOTPY currently contains eight widely used algorithms, 11 objective functions, and can sample from eight parameter distributions. SPOTPY has a model-independent structure and can be run in parallel from the workstation to large computation clusters using the Message Passing Interface (MPI. We tested SPOTPY in five different case studies to parameterize the Rosenbrock, Griewank and Ackley functions, a one-dimensional physically based soil moisture routine, where we searched for parameters of the van Genuchten-Mualem function and a calibration of a biogeochemistry model with different objective functions. The case studies reveal that the implemented SPOTPY methods can be used for any model with just a minimal amount of code for maximal power of parameter optimization. They further show the benefit of having one package at hand that includes number of well performing parameter search methods, since not every case study can be solved sufficiently with every algorithm or every objective function.
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...
Updating parameters of the chicken processing line model
DEFF Research Database (Denmark)
Kurowicka, Dorota; Nauta, Maarten; Jozwiak, Katarzyna
2010-01-01
A mathematical model of chicken processing that quantitatively describes the transmission of Campylobacter on chicken carcasses from slaughter to chicken meat product has been developed in Nauta et al. (2005). This model was quantified with expert judgment. Recent availability of data allows...... updating parameters of the model to better describe processes observed in slaughterhouses. We propose Bayesian updating as a suitable technique to update expert judgment with microbiological data. Berrang and Dickens’s data are used to demonstrate performance of this method in updating parameters...... of the chicken processing line model....
Lumped-Parameter Models for Windturbine Footings on Layered Ground
DEFF Research Database (Denmark)
Andersen, Lars
The design of modern wind turbines is typically based on lifetime analyses using aeroelastic codes. In this regard, the impedance of the foundations must be described accurately without increasing the overall size of the computationalmodel significantly. This may be obtained by the fitting...... of a lumped-parameter model to the results of a rigorous model or experimental results. In this paper, guidelines are given for the formulation of such lumped-parameter models and examples are given in which the models are utilised for the analysis of a wind turbine supported by a surface footing on a layered...
Parameter estimation and model selection in computational biology.
Directory of Open Access Journals (Sweden)
Gabriele Lillacci
2010-03-01
Full Text Available A central challenge in computational modeling of biological systems is the determination of the model parameters. Typically, only a fraction of the parameters (such as kinetic rate constants are experimentally measured, while the rest are often fitted. The fitting process is usually based on experimental time course measurements of observables, which are used to assign parameter values that minimize some measure of the error between these measurements and the corresponding model prediction. The measurements, which can come from immunoblotting assays, fluorescent markers, etc., tend to be very noisy and taken at a limited number of time points. In this work we present a new approach to the problem of parameter selection of biological models. We show how one can use a dynamic recursive estimator, known as extended Kalman filter, to arrive at estimates of the model parameters. The proposed method follows. First, we use a variation of the Kalman filter that is particularly well suited to biological applications to obtain a first guess for the unknown parameters. Secondly, we employ an a posteriori identifiability test to check the reliability of the estimates. Finally, we solve an optimization problem to refine the first guess in case it should not be accurate enough. The final estimates are guaranteed to be statistically consistent with the measurements. Furthermore, we show how the same tools can be used to discriminate among alternate models of the same biological process. We demonstrate these ideas by applying our methods to two examples, namely a model of the heat shock response in E. coli, and a model of a synthetic gene regulation system. The methods presented are quite general and may be applied to a wide class of biological systems where noisy measurements are used for parameter estimation or model selection.
Mattia, F.; Pauwels, V. R.; Balenzano, A.; Satalino, G.; Skriver, H.; Verhoest, N. E.
2008-12-01
It is widely recognized that Synthetic Aperture Radar (SAR) data are a very valuable source of information for the modeling of the interactions between the land surface and the atmosphere. During the last couple of decades, most of the research on the use of SAR data in hydrologic applications has been focused on the retrieval of land and bio-geophysical parameters (e.g. soil moisture contents). One relatively unexplored issue consists of the optimization of soil hydraulic model parameters, such as for example hydraulic conductivity values, through remote sensing. This is due to the fact that no direct relationships between the remote sensing observations, more specifically radar backscatter values, and the parameter values can be derived. However, land surface models can provide these relationships. The objective of this study is to retrieve a number of soil physical model parameters through a combination of remote sensing and land surface modeling. Spatially distributed and multitemporal SAR-based soil moisture maps are the basis of the study. The surface soil moisture values are used in a parameter estimation procedure based on the Extended Kalman Filter equations. In fact, the land surface model is thus used to determine the relationship between the soil physical parameters and the remote sensing data. An analysis is then performed, relating the retrieved soil parameters to the soil texture data available over the study area. The results of the study show that there is a potential to retrieve soil physical model parameters through a combination of land surface modeling and remote sensing.
Stability of neutrino parameters and self-complementarity relation with varying SUSY breaking scale
Singh, K. Sashikanta; Roy, Subhankar; Singh, N. Nimai
2018-03-01
The scale at which supersymmetry (SUSY) breaks (ms) is still unknown. The present article, following a top-down approach, endeavors to study the effect of varying ms on the radiative stability of the observational parameters associated with the neutrino mixing. These parameters get additional contributions in the minimal supersymmetric model (MSSM). A variation in ms will influence the bounds for which the Standard Model (SM) and MSSM work and hence, will account for the different radiative contributions received from both sectors, respectively, while running the renormalization group equations (RGE). The present work establishes the invariance of the self complementarity relation among the three mixing angles, θ13+θ12≈θ23 against the radiative evolution. A similar result concerning the mass ratio, m2:m1 is also found to be valid. In addition to varying ms, the work incorporates a range of different seesaw (SS) scales and tries to see how the latter affects the parameters.
Catchment classification and model parameter transfer with a view to regionalisation
Ley, Rita; Hellebrand, Hugo; Casper, Markus C.
2013-04-01
strong connection between runoff behaviour, catchment properties and model parameter sets within the classes. The next step is the classification of the catchments based on calibrated model parameters with SOM. If the parameter sets show significant relation to the previous classification, model parameters may be used as an easy accessible start for catchment description. Physiographic and climatic properties can now be related directly to model parameters, corroborating a quantitative approach to basin classification. Furthermore, one representative parameter set for each class of catchments can describe the runoff behaviour for a whole class. The description of runoff behaviour by calibrated model parameters of a conceptual model in relation to classes of physically and climatically similar catchments can facilitates catchment description, classification and regionalisation and provides insight into the processes and functioning of catchments. The use of calibrated model parameters for classification instead of time-consuming description of the runoff behaviour with event runoff coefficients offers an attractive alternative for regionalisation.
Development of new model for high explosives detonation parameters calculation
Directory of Open Access Journals (Sweden)
Jeremić Radun
2012-01-01
Full Text Available The simple semi-empirical model for calculation of detonation pressure and velocity for CHNO explosives has been developed, which is based on experimental values of detonation parameters. Model uses Avakyan’s method for determination of detonation products' chemical composition, and is applicable in wide range of densities. Compared with the well-known Kamlet's method and numerical model of detonation based on BKW EOS, the calculated values from proposed model have significantly better accuracy.
Relating auditory attributes of multichannel sound to preference and to physical parameters
DEFF Research Database (Denmark)
Choisel, Sylvain; Wickelmaier, Florian Maria
2006-01-01
playing a role in sound quality evaluation. Eight selected attributes are quantified by a panel of 39 listeners using paired-comparison judgments and probabilistic choice models, and related to overall preference. A multiple-regression model predicts preference well, and some similarities are observed......Sound reproduced by multichannel systems is affected by many factors giving rise to various sensations, or auditory attributes. Relating specific attributes to overall preference and to physical measures of the sound field provides valuable information for a better understanding of the parameters...
Parameter uncertainty analysis of a biokinetic model of caesium
International Nuclear Information System (INIS)
Li, W.B.; Oeh, U.; Klein, W.; Blanchardon, E.; Puncher, M.; Leggett, R.W.; Breustedt, B.; Nosske, D.; Lopez, M.A.
2015-01-01
Parameter uncertainties for the biokinetic model of caesium (Cs) developed by Leggett et al. were inventoried and evaluated. The methods of parameter uncertainty analysis were used to assess the uncertainties of model predictions with the assumptions of model parameter uncertainties and distributions. Furthermore, the importance of individual model parameters was assessed by means of sensitivity analysis. The calculated uncertainties of model predictions were compared with human data of Cs measured in blood and in the whole body. It was found that propagating the derived uncertainties in model parameter values reproduced the range of bioassay data observed in human subjects at different times after intake. The maximum ranges, expressed as uncertainty factors (UFs) (defined as a square root of ratio between 97.5. and 2.5. percentiles) of blood clearance, whole-body retention and urinary excretion of Cs predicted at earlier time after intake were, respectively: 1.5, 1.0 and 2.5 at the first day; 1.8, 1.1 and 2.4 at Day 10 and 1.8, 2.0 and 1.8 at Day 100; for the late times (1000 d) after intake, the UFs were increased to 43, 24 and 31, respectively. The model parameters of transfer rates between kidneys and blood, muscle and blood and the rate of transfer from kidneys to urinary bladder content are most influential to the blood clearance and to the whole-body retention of Cs. For the urinary excretion, the parameters of transfer rates from urinary bladder content to urine and from kidneys to urinary bladder content impact mostly. The implication and effect on the estimated equivalent and effective doses of the larger uncertainty of 43 in whole-body retention in the later time, say, after Day 500 will be explored in a successive work in the framework of EURADOS. (authors)
Sun, C. T.; Yoon, K. J.
1990-01-01
A one-parameter plasticity model was shown to adequately describe the orthotropic plastic deformation of AS4/PEEK (APC-2) unidirectional thermoplastic composite. This model was verified further for unidirectional and laminated composite panels with and without a hole. The nonlinear stress-strain relations were measured and compared with those predicted by the finite element analysis using the one-parameter elastic-plastic constitutive model. The results show that the one-parameter orthotropic plasticity model is suitable for the analysis of elastic-plastic deformation of AS4/PEEK composite laminates.
Sensor placement for calibration of spatially varying model parameters
Nath, Paromita; Hu, Zhen; Mahadevan, Sankaran
2017-08-01
This paper presents a sensor placement optimization framework for the calibration of spatially varying model parameters. To account for the randomness of the calibration parameters over space and across specimens, the spatially varying parameter is represented as a random field. Based on this representation, Bayesian calibration of spatially varying parameter is investigated. To reduce the required computational effort during Bayesian calibration, the original computer simulation model is substituted with Kriging surrogate models based on the singular value decomposition (SVD) of the model response and the Karhunen-Loeve expansion (KLE) of the spatially varying parameters. A sensor placement optimization problem is then formulated based on the Bayesian calibration to maximize the expected information gain measured by the expected Kullback-Leibler (K-L) divergence. The optimization problem needs to evaluate the expected K-L divergence repeatedly which requires repeated calibration of the spatially varying parameter, and this significantly increases the computational effort of solving the optimization problem. To overcome this challenge, an approximation for the posterior distribution is employed within the optimization problem to facilitate the identification of the optimal sensor locations using the simulated annealing algorithm. A heat transfer problem with spatially varying thermal conductivity is used to demonstrate the effectiveness of the proposed method.
Geometry parameters for musculoskeletal modelling of the shoulder system
Van der Helm, F C; Veeger, DirkJan (H. E. J.); Pronk, G M; Van der Woude, L H; Rozendal, R H
A dynamical finite-element model of the shoulder mechanism consisting of thorax, clavicula, scapula and humerus is outlined. The parameters needed for the model are obtained in a cadaver experiment consisting of both shoulders of seven cadavers. In this paper, in particular, the derivation of
International Nuclear Information System (INIS)
Rout, S.; Mishra, D.G.; Ravi, P.M.; Tripathi, R.M.
2016-01-01
Tritium is one of the radionuclides likely to get released to the environment from Pressurized Heavy Water Reactors. Environmental models are extensively used to quantify the complex environmental transport processes of radionuclides and also to assess the impact to the environment. Model parameters exerting the significant influence on model results are identified through a sensitivity analysis (SA). SA is the study of how the variation (uncertainty) in the output of a mathematical model can be apportioned, qualitatively or quantitatively, to different sources of variation in the input parameters. This study was designed to identify the sensitive model parameters of specific activity model (TRS 1616, IAEA) for environmental transfer of 3 H following release to air and then to vegetation and animal products. Model includes parameters such as air to soil transfer factor (CRs), Tissue Free Water 3 H to Organically Bound 3 H ratio (Rp), Relative humidity (RH), WCP (fractional water content) and WEQp (water equivalent factor) any change in these parameters leads to change in 3 H level in vegetation and animal products consequently change in dose due to ingestion. All these parameters are function of climate and/or plant which change with time, space and species. Estimation of these parameters at every time is a time consuming and also required sophisticated instrumentation. Therefore it is necessary to identify the sensitive parameters and freeze the values of least sensitive parameters at constant values for more accurate estimation of 3 H dose in short time for routine assessment
Improving the realism of hydrologic model through multivariate parameter estimation
Rakovec, Oldrich; Kumar, Rohini; Attinger, Sabine; Samaniego, Luis
2017-04-01
Increased availability and quality of near real-time observations should improve understanding of predictive skills of hydrological models. Recent studies have shown the limited capability of river discharge data alone to adequately constrain different components of distributed model parameterizations. In this study, the GRACE satellite-based total water storage (TWS) anomaly is used to complement the discharge data with an aim to improve the fidelity of mesoscale hydrologic model (mHM) through multivariate parameter estimation. The study is conducted in 83 European basins covering a wide range of hydro-climatic regimes. The model parameterization complemented with the TWS anomalies leads to statistically significant improvements in (1) discharge simulations during low-flow period, and (2) evapotranspiration estimates which are evaluated against independent (FLUXNET) data. Overall, there is no significant deterioration in model performance for the discharge simulations when complemented by information from the TWS anomalies. However, considerable changes in the partitioning of precipitation into runoff components are noticed by in-/exclusion of TWS during the parameter estimation. A cross-validation test carried out to assess the transferability and robustness of the calibrated parameters to other locations further confirms the benefit of complementary TWS data. In particular, the evapotranspiration estimates show more robust performance when TWS data are incorporated during the parameter estimation, in comparison with the benchmark model constrained against discharge only. This study highlights the value for incorporating multiple data sources during parameter estimation to improve the overall realism of hydrologic model and its applications over large domains. Rakovec, O., Kumar, R., Attinger, S. and Samaniego, L. (2016): Improving the realism of hydrologic model functioning through multivariate parameter estimation. Water Resour. Res., 52, http://dx.doi.org/10
Ground level enhancement (GLE) energy spectrum parameters model
Qin, G.; Wu, S.
2017-12-01
We study the ground level enhancement (GLE) events in solar cycle 23 with the four energy spectra parameters, the normalization parameter C, low-energy power-law slope γ 1, high-energy power-law slope γ 2, and break energy E0, obtained by Mewaldt et al. 2012 who fit the observations to the double power-law equation. we divide the GLEs into two groups, one with strong acceleration by interplanetary (IP) shocks and another one without strong acceleration according to the condition of solar eruptions. We next fit the four parameters with solar event conditions to get models of the parameters for the two groups of GLEs separately. So that we would establish a model of energy spectrum for GLEs for the future space weather prediction.
Determination of appropriate models and parameters for premixing calculations
Energy Technology Data Exchange (ETDEWEB)
Park, Ik-Kyu; Kim, Jong-Hwan; Min, Beong-Tae; Hong, Seong-Wan
2008-03-15
The purpose of the present work is to use experiments that have been performed at Forschungszentrum Karlsruhe during about the last ten years for determining the most appropriate models and parameters for premixing calculations. The results of a QUEOS experiment are used to fix the parameters concerning heat transfer. The QUEOS experiments are especially suited for this purpose as they have been performed with small hot solid spheres. Therefore the area of heat exchange is known. With the heat transfer parameters fixed in this way, a PREMIX experiment is recalculated. These experiments have been performed with molten alumina (Al{sub 2}O{sub 3}) as a simulant of corium. Its initial temperature is 2600 K. With these experiments the models and parameters for jet and drop break-up are tested.
Parameter uncertainty in CGE Modeling of the environmental impacts of economic policies
Energy Technology Data Exchange (ETDEWEB)
Abler, D.G.; Shortle, J.S. [Agricultural Economics, Pennsylvania State University, University Park, PA (United States); Rodriguez, A.G. [University of Costa Rica, San Jose (Costa Rica)
1999-07-01
This study explores the role of parameter uncertainty in Computable General Equilibrium (CGE) modeling of the environmental impacts of macroeconomic and sectoral policies, using Costa Rica as a case for study. A CGE model is constructed which includes eight environmental indicators covering deforestation, pesticides, overfishing, hazardous wastes, inorganic wastes, organic wastes, greenhouse gases, and air pollution. The parameters are treated as random variables drawn from prespecified distributions. Evaluation of each policy option consists of a Monte Carlo experiment. The impacts of the policy options on the environmental indicators are relatively robust to different parameter values, in spite of the wide range of parameter values employed. 33 refs.
Parameter uncertainty in CGE Modeling of the environmental impacts of economic policies
International Nuclear Information System (INIS)
Abler, D.G.; Shortle, J.S.; Rodriguez, A.G.
1999-01-01
This study explores the role of parameter uncertainty in Computable General Equilibrium (CGE) modeling of the environmental impacts of macroeconomic and sectoral policies, using Costa Rica as a case for study. A CGE model is constructed which includes eight environmental indicators covering deforestation, pesticides, overfishing, hazardous wastes, inorganic wastes, organic wastes, greenhouse gases, and air pollution. The parameters are treated as random variables drawn from prespecified distributions. Evaluation of each policy option consists of a Monte Carlo experiment. The impacts of the policy options on the environmental indicators are relatively robust to different parameter values, in spite of the wide range of parameter values employed. 33 refs
Parameter Estimation for Single Diode Models of Photovoltaic Modules
Energy Technology Data Exchange (ETDEWEB)
Hansen, Clifford [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Photovoltaic and Distributed Systems Integration Dept.
2015-03-01
Many popular models for photovoltaic system performance employ a single diode model to compute the I - V curve for a module or string of modules at given irradiance and temperature conditions. A single diode model requires a number of parameters to be estimated from measured I - V curves. Many available parameter estimation methods use only short circuit, o pen circuit and maximum power points for a single I - V curve at standard test conditions together with temperature coefficients determined separately for individual cells. In contrast, module testing frequently records I - V curves over a wide range of irradi ance and temperature conditions which, when available , should also be used to parameterize the performance model. We present a parameter estimation method that makes use of a fu ll range of available I - V curves. We verify the accuracy of the method by recov ering known parameter values from simulated I - V curves . We validate the method by estimating model parameters for a module using outdoor test data and predicting the outdoor performance of the module.
Relation of Core Dominance Parameter and Extended Spectral ...
Indian Academy of Sciences (India)
2016-01-27
Jan 27, 2016 ... The correlations between differences of two core dominance parameters and core/extended spectral index are investigated. The extended spectral index is associated with the differences very well, while there is a weak relationship between core spectral index and the differences. The average core ...
Determining Rheological Parameters of Generalized Yield-Power-Law Fluid Model
Directory of Open Access Journals (Sweden)
Stryczek Stanislaw
2004-09-01
Full Text Available The principles of determining rheological parameters of drilling muds described by a generalized yield-power-law are presented in the paper. Functions between tangent stresses and shear rate are given. The conditions of laboratory measurements of rheological parameters of generalized yield-power-law fluids are described and necessary mathematical relations for rheological model parameters given. With the block diagrams, the methodics of numerical solution of these relations has been presented. Rheological parameters of an exemplary drilling mud have been calculated with the use of this numerical program.
Modeling Chinese ionospheric layer parameters based on EOF analysis
Yu, You; Wan, Weixing
2016-04-01
Using 24-ionosonde observations in and around China during the 20th solar cycle, an assimilative model is constructed to map the ionospheric layer parameters (foF2, hmF2, M(3000)F2, and foE) over China based on empirical orthogonal function (EOF) analysis. First, we decompose the background maps from the International Reference Ionosphere model 2007 (IRI-07) into different EOF modes. The obtained EOF modes consist of two factors: the EOF patterns and the corresponding EOF amplitudes. These two factors individually reflect the spatial distributions (e.g., the latitudinal dependence such as the equatorial ionization anomaly structure and the longitude structure with east-west difference) and temporal variations on different time scales (e.g., solar cycle, annual, semiannual, and diurnal variations) of the layer parameters. Then, the EOF patterns and long-term observations of ionosondes are assimilated to get the observed EOF amplitudes, which are further used to construct the Chinese Ionospheric Maps (CIMs) of the layer parameters. In contrast with the IRI-07 model, the mapped CIMs successfully capture the inherent temporal and spatial variations of the ionospheric layer parameters. Finally, comparison of the modeled (EOF and IRI-07 model) and observed values reveals that the EOF model reproduces the observation with smaller root-mean-square errors and higher linear correlation co- efficients. In addition, IRI discrepancy at the low latitude especially for foF2 is effectively removed by EOF model.
Parameters and variables appearing in repository design models
International Nuclear Information System (INIS)
Curtis, R.H.; Wart, R.J.
1983-12-01
This report defines the parameters and variables appearing in repository design models and presents typical values and ranges of values of each. Areas covered by this report include thermal, geomechanical, and coupled stress and flow analyses in rock. Particular emphasis is given to conductivity, radiation, and convection parameters for thermal analysis and elastic constants, failure criteria, creep laws, and joint properties for geomechanical analysis. The data in this report were compiled to help guide the selection of values of parameters and variables to be used in code benchmarking. 102 references, 33 figures, 51 tables
Radcliffe, D E; Lin, Z; Risse, L M; Romeis, J J; Jackson, C R
2009-01-01
Lake Allatoona is a large reservoir north of Atlanta, GA, that drains an area of about 2870 km2 scheduled for a phosphorus (P) total maximum daily load (TMDL). The Soil and Water Assessment Tool (SWAT) model has been widely used for watershed-scale modeling of P, but there is little guidance on how to estimate P-related parameters, especially those related to in-stream P processes. In this paper, methods are demonstrated to individually estimate SWAT soil-related P parameters and to collectively estimate P parameters related to stream processes. Stream related parameters were obtained using the nutrient uptake length concept. In a manner similar to experiments conducted by stream ecologists, a small point source is simulated in a headwater sub-basin of the SWAT models, then the in-stream parameter values are adjusted collectively to get an uptake length of P similar to the values measured in the streams in the region. After adjusting the in-stream parameters, the P uptake length estimated in the simulations ranged from 53 to 149 km compared to uptake lengths measured by ecologists in the region of 11 to 85 km. Once the a priori P-related parameter set was developed, the SWAT models of main tributaries to Lake Allatoona were calibrated for daily transport. Models using SWAT P parameters derived from the methods in this paper outperformed models using default parameter values when predicting total P (TP) concentrations in streams during storm events and TP annual loads to Lake Allatoona.
Control of the SCOLE configuration using distributed parameter models
Hsiao, Min-Hung; Huang, Jen-Kuang
1994-01-01
A continuum model for the SCOLE configuration has been derived using transfer matrices. Controller designs for distributed parameter systems have been analyzed. Pole-assignment controller design is considered easy to implement but stability is not guaranteed. An explicit transfer function of dynamic controllers has been obtained and no model reduction is required before the controller is realized. One specific LQG controller for continuum models had been derived, but other optimal controllers for more general performances need to be studied.
The Hill model of concentration-response is ubiquitous in toxicology, perhaps because its parameters directly relate to biologically significant metrics of toxicity such as efficacy and potency. Point estimates of these parameters obtained through least squares regression or maxi...
Synchronous Generator Model Parameter Estimation Based on Noisy Dynamic Waveforms
Berhausen, Sebastian; Paszek, Stefan
2016-01-01
In recent years, there have occurred system failures in many power systems all over the world. They have resulted in a lack of power supply to a large number of recipients. To minimize the risk of occurrence of power failures, it is necessary to perform multivariate investigations, including simulations, of power system operating conditions. To conduct reliable simulations, the current base of parameters of the models of generating units, containing the models of synchronous generators, is necessary. In the paper, there is presented a method for parameter estimation of a synchronous generator nonlinear model based on the analysis of selected transient waveforms caused by introducing a disturbance (in the form of a pseudorandom signal) in the generator voltage regulation channel. The parameter estimation was performed by minimizing the objective function defined as a mean square error for deviations between the measurement waveforms and the waveforms calculated based on the generator mathematical model. A hybrid algorithm was used for the minimization of the objective function. In the paper, there is described a filter system used for filtering the noisy measurement waveforms. The calculation results of the model of a 44 kW synchronous generator installed on a laboratory stand of the Institute of Electrical Engineering and Computer Science of the Silesian University of Technology are also given. The presented estimation method can be successfully applied to parameter estimation of different models of high-power synchronous generators operating in a power system.
Using a 4D-Variational Method to Optimize Model Parameters in an Intermediate Coupled Model of ENSO
Gao, C.; Zhang, R. H.
2017-12-01
Large biases exist in real-time ENSO prediction, which is attributed to uncertainties in initial conditions and model parameters. Previously, a four dimentional variational (4D-Var) data assimilation system was developed for an intermediate coupled model (ICM) and used to improve ENSO modeling through optimized initial conditions. In this paper, this system is further applied to optimize model parameters. In the ICM used, one important process for ENSO is related to the anomalous temperature of subsurface water entrained into the mixed layer (Te), which is empirically and explicitly related to sea level (SL) variation, written as Te=αTe×FTe (SL). The introduced parameter, αTe, represents the strength of the thermocline effect on sea surface temperature (SST; referred as the thermocline effect). A numerical procedure is developed to optimize this model parameter through the 4D-Var assimilation of SST data in a twin experiment context with an idealized setting. Experiments having initial condition optimized only and having initial condition plus this additional model parameter optimized both are compared. It is shown that ENSO evolution can be more effectively recovered by including the additional optimization of this parameter in ENSO modeling. The demonstrated feasibility of optimizing model parameter and initial condition together through the 4D-Var method provides a modeling platform for ENSO studies. Further applications of the 4D-Var data assimilation system implemented in the ICM are also discussed.
Gao, Chuan; Zhang, Rong-Hua; Wu, Xinrong; Sun, Jichang
2018-04-01
Large biases exist in real-time ENSO prediction, which can be attributed to uncertainties in initial conditions and model parameters. Previously, a 4D variational (4D-Var) data assimilation system was developed for an intermediate coupled model (ICM) and used to improve ENSO modeling through optimized initial conditions. In this paper, this system is further applied to optimize model parameters. In the ICM used, one important process for ENSO is related to the anomalous temperature of subsurface water entrained into the mixed layer ( T e), which is empirically and explicitly related to sea level (SL) variation. The strength of the thermocline effect on SST (referred to simply as "the thermocline effect") is represented by an introduced parameter, α Te. A numerical procedure is developed to optimize this model parameter through the 4D-Var assimilation of SST data in a twin experiment context with an idealized setting. Experiments having their initial condition optimized only, and having their initial condition plus this additional model parameter optimized, are compared. It is shown that ENSO evolution can be more effectively recovered by including the additional optimization of this parameter in ENSO modeling. The demonstrated feasibility of optimizing model parameters and initial conditions together through the 4D-Var method provides a modeling platform for ENSO studies. Further applications of the 4D-Var data assimilation system implemented in the ICM are also discussed.
On the role of modeling parameters in IMRT plan optimization
International Nuclear Information System (INIS)
Krause, Michael; Scherrer, Alexander; Thieke, Christian
2008-01-01
The formulation of optimization problems in intensity-modulated radiotherapy (IMRT) planning comprises the choice of various values such as function-specific parameters or constraint bounds. In current inverse planning programs that yield a single treatment plan for each optimization, it is often unclear how strongly these modeling parameters affect the resulting plan. This work investigates the mathematical concepts of elasticity and sensitivity to deal with this problem. An artificial planning case with a horse-shoe formed target with different opening angles surrounding a circular risk structure is studied. As evaluation functions the generalized equivalent uniform dose (EUD) and the average underdosage below and average overdosage beyond certain dose thresholds are used. A single IMRT plan is calculated for an exemplary parameter configuration. The elasticity and sensitivity of each parameter are then calculated without re-optimization, and the results are numerically verified. The results show the following. (1) elasticity can quantify the influence of a modeling parameter on the optimization result in terms of how strongly the objective function value varies under modifications of the parameter value. It also can describe how strongly the geometry of the involved planning structures affects the optimization result. (2) Based on the current parameter settings and corresponding treatment plan, sensitivity analysis can predict the optimization result for modified parameter values without re-optimization, and it can estimate the value intervals in which such predictions are valid. In conclusion, elasticity and sensitivity can provide helpful tools in inverse IMRT planning to identify the most critical parameters of an individual planning problem and to modify their values in an appropriate way
Continuous radon measurements in schools: time variations and related parameters
International Nuclear Information System (INIS)
Giovani, C.; Cappelletto, C.; Garavaglia, M.; Pividore, S.; Villalta, R.
2004-01-01
Some results are reported of observations made within a four-year survey, during different seasons and in different conditions of school building use. Natural radon variations (day-night cycles, seasonal and temperature dependent variations etc..) and artificial ones (opening of windows, weekends and vacations, deployment of air conditioning or heating systems. etc.) were investigated as parameters affecting time dependent radon concentrations. (P.A.)
Parameter estimation in nonlinear models for pesticide degradation
International Nuclear Information System (INIS)
Richter, O.; Pestemer, W.; Bunte, D.; Diekkrueger, B.
1991-01-01
A wide class of environmental transfer models is formulated as ordinary or partial differential equations. With the availability of fast computers, the numerical solution of large systems became feasible. The main difficulty in performing a realistic and convincing simulation of the fate of a substance in the biosphere is not the implementation of numerical techniques but rather the incomplete data basis for parameter estimation. Parameter estimation is a synonym for statistical and numerical procedures to derive reasonable numerical values for model parameters from data. The classical method is the familiar linear regression technique which dates back to the 18th century. Because it is easy to handle, linear regression has long been established as a convenient tool for analysing relationships. However, the wide use of linear regression has led to an overemphasis of linear relationships. In nature, most relationships are nonlinear and linearization often gives a poor approximation of reality. Furthermore, pure regression models are not capable to map the dynamics of a process. Therefore, realistic models involve the evolution in time (and space). This leads in a natural way to the formulation of differential equations. To establish the link between data and dynamical models, numerical advanced parameter identification methods have been developed in recent years. This paper demonstrates the application of these techniques to estimation problems in the field of pesticide dynamics. (7 refs., 5 figs., 2 tabs.)
The level density parameters for fermi gas model
International Nuclear Information System (INIS)
Zuang Youxiang; Wang Cuilan; Zhou Chunmei; Su Zongdi
1986-01-01
Nuclear level densities are crucial ingredient in the statistical models, for instance, in the calculations of the widths, cross sections, emitted particle spectra, etc. for various reaction channels. In this work 667 sets of more reliable and new experimental data are adopted, which include average level spacing D D , radiative capture width Γ γ 0 at neutron binding energy and cumulative level number N 0 at the low excitation energy. They are published during 1973 to 1983. Based on the parameters given by Gilbert-Cameon and Cook the physical quantities mentioned above are calculated. The calculated results have the deviation obviously from experimental values. In order to improve the fitting, the parameters in the G-C formula are adjusted and new set of level density parameters is obsained. The parameters is this work are more suitable to fit new measurements
Parameter estimation of component reliability models in PSA model of Krsko NPP
International Nuclear Information System (INIS)
Jordan Cizelj, R.; Vrbanic, I.
2001-01-01
In the paper, the uncertainty analysis of component reliability models for independent failures is shown. The present approach for parameter estimation of component reliability models in NPP Krsko is presented. Mathematical approaches for different types of uncertainty analyses are introduced and used in accordance with some predisposed requirements. Results of the uncertainty analyses are shown in an example for time-related components. As the most appropriate uncertainty analysis proved the Bayesian estimation with the numerical estimation of a posterior, which can be approximated with some appropriate probability distribution, in this paper with lognormal distribution.(author)
Identifiability and error minimization of receptor model parameters with PET
International Nuclear Information System (INIS)
Delforge, J.; Syrota, A.; Mazoyer, B.M.
1989-01-01
The identifiability problem and the general framework for experimental design optimization are presented. The methodology is applied to the problem of the receptor-ligand model parameter estimation with dynamic positron emission tomography data. The first attempts to identify the model parameters from data obtained with a single tracer injection led to disappointing numerical results. The possibility of improving parameter estimation using a new experimental design combining an injection of the labelled ligand and an injection of the cold ligand (displacement experiment) has been investigated. However, this second protocol led to two very different numerical solutions and it was necessary to demonstrate which solution was biologically valid. This has been possible by using a third protocol including both a displacement and a co-injection experiment. (authors). 16 refs.; 14 figs
X-Parameter Based Modelling of Polar Modulated Power Amplifiers
DEFF Research Database (Denmark)
Wang, Yelin; Nielsen, Troels Studsgaard; Sira, Daniel
2013-01-01
X-parameters are developed as an extension of S-parameters capable of modelling non-linear devices driven by large signals. They are suitable for devices having only radio frequency (RF) and DC ports. In a polar power amplifier (PA), phase and envelope of the input modulated signal are applied...... at separate ports and the envelope port is neither an RF nor a DC port. As a result, X-parameters may fail to characterise the effect of the envelope port excitation and consequently the polar PA. This study introduces a solution to the problem for a commercial polar PA. In this solution, the RF-phase path...... PA for simulations. The simulated error vector magnitude (EVM) and adjacent channel power ratio (ACPR) were compared with the measured data to validate the model. The maximum differences between the simulated and measured EVM and ACPR are less than 2% point and 3 dB, respectively....
Joint Dynamics Modeling and Parameter Identification for Space Robot Applications
Directory of Open Access Journals (Sweden)
Adenilson R. da Silva
2007-01-01
Full Text Available Long-term mission identification and model validation for in-flight manipulator control system in almost zero gravity with hostile space environment are extremely important for robotic applications. In this paper, a robot joint mathematical model is developed where several nonlinearities have been taken into account. In order to identify all the required system parameters, an integrated identification strategy is derived. This strategy makes use of a robust version of least-squares procedure (LS for getting the initial conditions and a general nonlinear optimization method (MCS—multilevel coordinate search—algorithm to estimate the nonlinear parameters. The approach is applied to the intelligent robot joint (IRJ experiment that was developed at DLR for utilization opportunity on the International Space Station (ISS. The results using real and simulated measurements have shown that the developed algorithm and strategy have remarkable features in identifying all the parameters with good accuracy.
Prediction of interest rate using CKLS model with stochastic parameters
Energy Technology Data Exchange (ETDEWEB)
Ying, Khor Chia [Faculty of Computing and Informatics, Multimedia University, Jalan Multimedia, 63100 Cyberjaya, Selangor (Malaysia); Hin, Pooi Ah [Sunway University Business School, No. 5, Jalan Universiti, Bandar Sunway, 47500 Subang Jaya, Selangor (Malaysia)
2014-06-19
The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector φ{sup (j)} of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j′-th time point where j≤j′≤j+n. To model the variation of φ{sup (j)}, we assume that φ{sup (j)} depends on φ{sup (j−m)}, φ{sup (j−m+1)},…, φ{sup (j−1)} and the interest rate r{sub j+n} at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r{sub j+n+1} of the interest rate at the next time point when the value r{sub j+n} of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r{sub j+n+d} at the next d-th (d≥2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters.
Model parameters estimation and sensitivity by genetic algorithms
International Nuclear Information System (INIS)
Marseguerra, Marzio; Zio, Enrico; Podofillini, Luca
2003-01-01
In this paper we illustrate the possibility of extracting qualitative information on the importance of the parameters of a model in the course of a Genetic Algorithms (GAs) optimization procedure for the estimation of such parameters. The Genetic Algorithms' search of the optimal solution is performed according to procedures that resemble those of natural selection and genetics: an initial population of alternative solutions evolves within the search space through the four fundamental operations of parent selection, crossover, replacement, and mutation. During the search, the algorithm examines a large amount of solution points which possibly carries relevant information on the underlying model characteristics. A possible utilization of this information amounts to create and update an archive with the set of best solutions found at each generation and then to analyze the evolution of the statistics of the archive along the successive generations. From this analysis one can retrieve information regarding the speed of convergence and stabilization of the different control (decision) variables of the optimization problem. In this work we analyze the evolution strategy followed by a GA in its search for the optimal solution with the aim of extracting information on the importance of the control (decision) variables of the optimization with respect to the sensitivity of the objective function. The study refers to a GA search for optimal estimates of the effective parameters in a lumped nuclear reactor model of literature. The supporting observation is that, as most optimization procedures do, the GA search evolves towards convergence in such a way to stabilize first the most important parameters of the model and later those which influence little the model outputs. In this sense, besides estimating efficiently the parameters values, the optimization approach also allows us to provide a qualitative ranking of their importance in contributing to the model output. The
Revised Parameters for the AMOEBA Polarizable Atomic Multipole Water Model.
Laury, Marie L; Wang, Lee-Ping; Pande, Vijay S; Head-Gordon, Teresa; Ponder, Jay W
2015-07-23
A set of improved parameters for the AMOEBA polarizable atomic multipole water model is developed. An automated procedure, ForceBalance, is used to adjust model parameters to enforce agreement with ab initio-derived results for water clusters and experimental data for a variety of liquid phase properties across a broad temperature range. The values reported here for the new AMOEBA14 water model represent a substantial improvement over the previous AMOEBA03 model. The AMOEBA14 model accurately predicts the temperature of maximum density and qualitatively matches the experimental density curve across temperatures from 249 to 373 K. Excellent agreement is observed for the AMOEBA14 model in comparison to experimental properties as a function of temperature, including the second virial coefficient, enthalpy of vaporization, isothermal compressibility, thermal expansion coefficient, and dielectric constant. The viscosity, self-diffusion constant, and surface tension are also well reproduced. In comparison to high-level ab initio results for clusters of 2-20 water molecules, the AMOEBA14 model yields results similar to AMOEBA03 and the direct polarization iAMOEBA models. With advances in computing power, calibration data, and optimization techniques, we recommend the use of the AMOEBA14 water model for future studies employing a polarizable water model.
Parameter sensitivity analysis of a lumped-parameter model of a chain of lymphangions in series.
Jamalian, Samira; Bertram, Christopher D; Richardson, William J; Moore, James E
2013-12-01
Any disruption of the lymphatic system due to trauma or injury can lead to edema. There is no effective cure for lymphedema, partly because predictive knowledge of lymphatic system reactions to interventions is lacking. A well-developed model of the system could greatly improve our understanding of its function. Lymphangions, defined as the vessel segment between two valves, are the individual pumping units. Based on our previous lumped-parameter model of a chain of lymphangions, this study aimed to identify the parameters that affect the system output the most using a sensitivity analysis. The system was highly sensitive to minimum valve resistance, such that variations in this parameter caused an order-of-magnitude change in time-average flow rate for certain values of imposed pressure difference. Average flow rate doubled when contraction frequency was increased within its physiological range. Optimum lymphangion length was found to be some 13-14.5 diameters. A peak of time-average flow rate occurred when transmural pressure was such that the pressure-diameter loop for active contractions was centered near maximum passive vessel compliance. Increasing the number of lymphangions in the chain improved the pumping in the presence of larger adverse pressure differences. For a given pressure difference, the optimal number of lymphangions increased with the total vessel length. These results indicate that further experiments to estimate valve resistance more accurately are necessary. The existence of an optimal value of transmural pressure may provide additional guidelines for increasing pumping in areas affected by edema.
Investigation of land use effects on Nash model parameters
Niazi, Faegheh; Fakheri Fard, Ahmad; Nourani, Vahid; Goodrich, David; Gupta, Hoshin
2015-04-01
Flood forecasting is of great importance in hydrologic planning, hydraulic structure design, water resources management and sustainable designs like flood control and management. Nash's instantaneous unit hydrograph is frequently used for simulating hydrological response in natural watersheds. Urban hydrology is gaining more attention due to population increases and associated construction escalation. Rapid development of urban areas affects the hydrologic processes of watersheds by decreasing soil permeability, flood base flow, lag time and increase in flood volume, peak runoff rates and flood frequency. In this study the influence of urbanization on the significant parameters of the Nash model have been investigated. These parameters were calculated using three popular methods (i.e. moment, root mean square error and random sampling data generation), in a small watershed consisting of one natural sub-watershed which drains into a residentially developed sub-watershed in the city of Sierra Vista, Arizona. The results indicated that for all three methods, the lag time, which is product of Nash parameters "K" and "n", in the natural sub-watershed is greater than the developed one. This logically implies more storage and/or attenuation in the natural sub-watershed. The median K and n parameters derived from the three methods using calibration events were tested via a set of verification events. The results indicated that all the three method have acceptable accuracy in hydrograph simulation. The CDF curves and histograms of the parameters clearly show the difference of the Nash parameter values between the natural and developed sub-watersheds. Some specific upper and lower percentile values of the median of the generated parameters (i.e. 10, 20 and 30 %) were analyzed to future investigates the derived parameters. The model was sensitive to variations in the value of the uncertain K and n parameter. Changes in n are smaller than K in both sub-watersheds indicating
Revised models and genetic parameter estimates for production and ...
African Journals Online (AJOL)
Genetic parameters for production and reproduction traits in the Elsenburg Dormer sheep stud were estimated using records of 11743 lambs born between 1943 and 2002. An animal model with direct and maternal additive, maternal permanent and temporary environmental effects was fitted for traits considered traits of the ...
Transformations among CE–CVM model parameters for ...
Indian Academy of Sciences (India)
In the development of thermodynamic databases for multicomponent systems using the cluster expansion–cluster variation methods, we need to have a consistent procedure for expressing the model parameters (CECs) of a higher order system in terms of those of the lower order subsystems and to an independent set of ...
Parameter Estimation for a Computable General Equilibrium Model
DEFF Research Database (Denmark)
Arndt, Channing; Robinson, Sherman; Tarp, Finn
We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (CGE) models. The approach applies information theory to estimating a system of nonlinear simultaneous equations. It has a number of advantages. First, it imposes all general equilibrium constraints...
Comparison of parameter estimation algorithms in hydrological modelling
DEFF Research Database (Denmark)
Blasone, Roberta-Serena; Madsen, Henrik; Rosbjerg, Dan
2006-01-01
for these types of models, although at a more expensive computational cost. The main purpose of this study is to investigate the performance of a global and a local parameter optimization algorithm, respectively, the Shuffled Complex Evolution (SCE) algorithm and the gradient-based Gauss...
Parameter Estimation for a Computable General Equilibrium Model
DEFF Research Database (Denmark)
Arndt, Channing; Robinson, Sherman; Tarp, Finn
2002-01-01
We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (CGE) models. The approach applies information theory to estimating a system of non-linear simultaneous equations. It has a number of advantages. First, it imposes all general equilibrium constraints...
Constraint on Parameters of Inverse Compton Scattering Model for ...
Indian Academy of Sciences (India)
J. Astrophys. Astr. (2011) 32, 299–300 c Indian Academy of Sciences. Constraint on Parameters of Inverse Compton Scattering Model for PSR B2319+60. H. G. Wang. ∗. & M. Lv. Center for Astrophysics,Guangzhou University, Guangzhou, China. ∗ e-mail: cosmic008@yahoo.com.cn. Abstract. Using the multifrequency radio ...
Surface density: a new parameter in the fundamental metallicity relation of star-forming galaxies
Hashimoto, Tetsuya; Goto, Tomotsugu; Momose, Rieko
2018-04-01
Star-forming galaxies display a close relation among stellar mass, metallicity, and star formation rate (or molecular-gas mass). This is known as the fundamental metallicity relation (FMR) (or molecular-gas FMR), and it has a profound implication on models of galaxy evolution. However, there still remains a significant residual scatter around the FMR. We show here that a fourth parameter, the surface density of stellar mass, reduces the dispersion around the molecular-gas FMR. In a principal component analysis of 29 physical parameters of 41 338 star-forming galaxies, the surface density of stellar mass is found to be the fourth most important parameter. The new 4D fundamental relation forms a tighter hypersurface that reduces the metallicity dispersion to 50 per cent of that of the molecular-gas FMR. We suggest that future analyses and models of galaxy evolution should consider the FMR in a 4D space that includes surface density. The dilution time-scale of gas inflow and the star-formation efficiency could explain the observational dependence on surface density of stellar mass.
Measurements of Physical Parameters of White Dwarfs: A Test of the Mass–Radius Relation
Energy Technology Data Exchange (ETDEWEB)
Bédard, A.; Bergeron, P.; Fontaine, G., E-mail: bedard@astro.umontreal.ca, E-mail: bergeron@astro.umontreal.ca, E-mail: fontaine@astro.umontreal.ca [Département de Physique, Université de Montréal, C.P. 6128, Succ. Centre-Ville, Montréal, Québec H3C 3J7 (Canada)
2017-10-10
We present a detailed spectroscopic and photometric analysis of 219 DA and DB white dwarfs for which trigonometric parallax measurements are available. Our aim is to compare the physical parameters derived from the spectroscopic and photometric techniques, and then to test the theoretical mass–radius relation for white dwarfs using these results. The agreement between spectroscopic and photometric parameters is found to be excellent, especially for effective temperatures, showing that our model atmospheres and fitting procedures provide an accurate, internally consistent analysis. The values of surface gravity and solid angle obtained, respectively, from spectroscopy and photometry, are combined with parallax measurements in various ways to study the validity of the mass–radius relation from an empirical point of view. After a thorough examination of our results, we find that 73% and 92% of the white dwarfs are consistent within 1 σ and 2 σ confidence levels, respectively, with the predictions of the mass–radius relation, thus providing strong support to the theory of stellar degeneracy. Our analysis also allows us to identify 15 stars that are better interpreted in terms of unresolved double degenerate binaries. Atmospheric parameters for both components in these binary systems are obtained using a novel approach. We further identify a few white dwarfs that are possibly composed of an iron core rather than a carbon/oxygen core, since they are consistent with Fe-core evolutionary models.
DEFF Research Database (Denmark)
Sales-Cruz, Mauricio; Heitzig, Martina; Cameron, Ian
2011-01-01
In this chapter the importance of parameter estimation in model development is illustrated through various applications related to reaction systems. In particular, rate constants in a reaction system are obtained through parameter estimation methods. These approaches often require the application...... of algebraic equations as the basis for parameter estimation.These approaches are illustrated using estimations of kinetic constants from reaction system models....
Inhalation Exposure Input Parameters for the Biosphere Model
International Nuclear Information System (INIS)
M. A. Wasiolek
2003-01-01
This analysis is one of the nine reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2003a) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents a set of input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for a Yucca Mountain repository. This report, ''Inhalation Exposure Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003b). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available at that time. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this analysis report. This analysis report defines and justifies values of mass loading, which is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Measurements of mass loading are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air surrounding crops and concentrations in air inhaled by a receptor. Concentrations in air to which the
Inhalation Exposure Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
M. A. Wasiolek
2003-09-24
This analysis is one of the nine reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2003a) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents a set of input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for a Yucca Mountain repository. This report, ''Inhalation Exposure Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003b). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available at that time. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this analysis report. This analysis report defines and justifies values of mass loading, which is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Measurements of mass loading are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air surrounding crops and concentrations in air
Agricultural and Environmental Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
K. Rasmuson; K. Rautenstrauch
2004-09-14
This analysis is one of 10 technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) (i.e., the biosphere model). It documents development of agricultural and environmental input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the ERMYN and its input parameters.
Estimating model parameters in nonautonomous chaotic systems using synchronization
International Nuclear Information System (INIS)
Yang, Xiaoli; Xu, Wei; Sun, Zhongkui
2007-01-01
In this Letter, a technique is addressed for estimating unknown model parameters of multivariate, in particular, nonautonomous chaotic systems from time series of state variables. This technique uses an adaptive strategy for tracking unknown parameters in addition to a linear feedback coupling for synchronizing systems, and then some general conditions, by means of the periodic version of the LaSalle invariance principle for differential equations, are analytically derived to ensure precise evaluation of unknown parameters and identical synchronization between the concerned experimental system and its corresponding receiver one. Exemplifies are presented by employing a parametrically excited 4D new oscillator and an additionally excited Ueda oscillator. The results of computer simulations reveal that the technique not only can quickly track the desired parameter values but also can rapidly respond to changes in operating parameters. In addition, the technique can be favorably robust against the effect of noise when the experimental system is corrupted by bounded disturbance and the normalized absolute error of parameter estimation grows almost linearly with the cutoff value of noise strength in simulation
Space geodetic techniques for global modeling of ionospheric peak parameters
Alizadeh, M. Mahdi; Schuh, Harald; Schmidt, Michael
The rapid development of new technological systems for navigation, telecommunication, and space missions which transmit signals through the Earth’s upper atmosphere - the ionosphere - makes the necessity of precise, reliable and near real-time models of the ionospheric parameters more crucial. In the last decades space geodetic techniques have turned into a capable tool for measuring ionospheric parameters in terms of Total Electron Content (TEC) or the electron density. Among these systems, the current space geodetic techniques, such as Global Navigation Satellite Systems (GNSS), Low Earth Orbiting (LEO) satellites, satellite altimetry missions, and others have found several applications in a broad range of commercial and scientific fields. This paper aims at the development of a three-dimensional integrated model of the ionosphere, by using various space geodetic techniques and applying a combination procedure for computation of the global model of electron density. In order to model ionosphere in 3D, electron density is represented as a function of maximum electron density (NmF2), and its corresponding height (hmF2). NmF2 and hmF2 are then modeled in longitude, latitude, and height using two sets of spherical harmonic expansions with degree and order 15. To perform the estimation, GNSS input data are simulated in such a way that the true position of the satellites are detected and used, but the STEC values are obtained through a simulation procedure, using the IGS VTEC maps. After simulating the input data, the a priori values required for the estimation procedure are calculated using the IRI-2012 model and also by applying the ray-tracing technique. The estimated results are compared with F2-peak parameters derived from the IRI model to assess the least-square estimation procedure and moreover, to validate the developed maps, the results are compared with the raw F2-peak parameters derived from the Formosat-3/Cosmic data.
Chapman, Michael S; Trzynka, Andrew; Chapman, Brynmor K
2013-04-01
When refining the fit of component atomic structures into electron microscopic reconstructions, use of a resolution-dependent atomic density function makes it possible to jointly optimize the atomic model and imaging parameters of the microscope. Atomic density is calculated by one-dimensional Fourier transform of atomic form factors convoluted with a microscope envelope correction and a low-pass filter, allowing refinement of imaging parameters such as resolution, by optimizing the agreement of calculated and experimental maps. A similar approach allows refinement of atomic displacement parameters, providing indications of molecular flexibility even at low resolution. A modest improvement in atomic coordinates is possible following optimization of these additional parameters. Methods have been implemented in a Python program that can be used in stand-alone mode for rigid-group refinement, or embedded in other optimizers for flexible refinement with stereochemical restraints. The approach is demonstrated with refinements of virus and chaperonin structures at resolutions of 9 through 4.5 Å, representing regimes where rigid-group and fully flexible parameterizations are appropriate. Through comparisons to known crystal structures, flexible fitting by RSRef is shown to be an improvement relative to other methods and to generate models with all-atom rms accuracies of 1.5-2.5 Å at resolutions of 4.5-6 Å. Copyright © 2013 Elsevier Inc. All rights reserved.
SIMULATION OF SOME PARAMETERS OF PLANT WATER RELATION IN MAIZE
Directory of Open Access Journals (Sweden)
A ANDA
2002-11-01
Full Text Available Investigations on simulation of plant temperature and stomatal resistance in maize by using the microclimate simulation model of Goudriaan (1977 were carried out at Keszthely Agrometeorological Research Station, during the growing season of 2001. The size of plot was 0.5 ha, because of parallel investigations done on the elements of microclimate. To facilitate the validation of the model field observations were measured. Two watering levels, rainfed plots with natural rainfall only, and irrigated plant stand were applied in simulation study. We irrigated the plants by using the amounts of crop water stress index with +drop irrigation system. The limit value for watering was the CWSI >0,25. In summer of 2001 the weather was dry and hot. The lack of water was substituted by 170 mm irrigation water on 4 occasions. To validate the model the root mean square deviation (RMSD between a number of pairs of simulated and measured microclimate elements was applied. The estimation of plant temperature was very accurate, the error of simulation was below 0.5 degree for noon irrigated plots and 0.3 degree for irrigated ones. The accuracy in stomatal resistance simulation was weaker than that of plant temperature, the error was 5.9 % for nonirrigated, and 21 % for irrigated plots. The estimation of stomatal resistance for irrigated plants need further refinement, but this requires changes in the basic equations of the model.
Parameter sensitivity analysis of a 1-D cold region lake model for land-surface schemes
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.
Investigation of RADTRAN Stop Model input parameters for truck stops
International Nuclear Information System (INIS)
Griego, N.R.; Smith, J.D.; Neuhauser, K.S.
1996-01-01
RADTRAN is a computer code for estimating the risks and consequences as transport of radioactive materials (RAM). RADTRAN was developed and is maintained by Sandia National Laboratories for the US Department of Energy (DOE). For incident-free transportation, the dose to persons exposed while the shipment is stopped is frequently a major percentage of the overall dose. This dose is referred to as Stop Dose and is calculated by the Stop Model. Because stop dose is a significant portion of the overall dose associated with RAM transport, the values used as input for the Stop Model are important. Therefore, an investigation of typical values for RADTRAN Stop Parameters for truck stops was performed. The resulting data from these investigations were analyzed to provide mean values, standard deviations, and histograms. Hence, the mean values can be used when an analyst does not have a basis for selecting other input values for the Stop Model. In addition, the histograms and their characteristics can be used to guide statistical sampling techniques to measure sensitivity of the RADTRAN calculated Stop Dose to the uncertainties in the stop model input parameters. This paper discusses the details and presents the results of the investigation of stop model input parameters at truck stops
Four-parameter analytical local model potential for atoms
International Nuclear Information System (INIS)
Fei, Yu; Jiu-Xun, Sun; Rong-Gang, Tian; Wei, Yang
2009-01-01
Analytical local model potential for modeling the interaction in an atom reduces the computational effort in electronic structure calculations significantly. A new four-parameter analytical local model potential is proposed for atoms Li through Lr, and the values of four parameters are shell-independent and obtained by fitting the results of X a method. At the same time, the energy eigenvalues, the radial wave functions and the total energies of electrons are obtained by solving the radial Schrödinger equation with a new form of potential function by Numerov's numerical method. The results show that our new form of potential function is suitable for high, medium and low Z atoms. A comparison among the new potential function and other analytical potential functions shows the greater flexibility and greater accuracy of the present new potential function. (atomic and molecular physics)
Improving the transferability of hydrological model parameters under changing conditions
Huang, Yingchun; Bárdossy, András
2014-05-01
Hydrological models are widely utilized to describe catchment behaviors with observed hydro-meteorological data. Hydrological process may be considered as non-stationary under the changing climate and land use conditions. An applicable hydrological model should be able to capture the essential features of the target catchment and therefore be transferable to different conditions. At present, many model applications based on the stationary assumptions are not sufficient for predicting further changes or time variability. The aim of this study is to explore new model calibration methods in order to improve the transferability of model parameters. To cope with the instability of model parameters calibrated on catchments in non-stationary conditions, we investigate the idea of simultaneously calibration on streamflow records for the period with dissimilar climate characteristics. In additional, a weather based weighting function is implemented to adjust the calibration period to future trends. For regions with limited data and ungauged basins, the common calibration was applied by using information from similar catchments. Result shows the model performance and transfer quantity could be well improved via common calibration. This model calibration approach will be used to enhance regional water management and flood forecasting capabilities.
Detecting Life and Biology-Related Parameters on Mars
Levin, Gilbet V.; Miller, Joseph D.; Straat, Patricia A.; Lodder, Robert; Hoover, Richard B.
2007-01-01
An integrated, miniaturized, low-power instrument capable of the detection and early characterization of microbial life in the soil of Mars is proposed. Based on the detection apd monitoring of on-going metabolism as being the surest evidence for extant life, the experiments will probe for chirality in metabolism, for circadian rhythm, and for photosynthesis. However, the instrument package will also be able to detect biosignatures and a variety of other physical and chemical parameters of the Martian surface that have significance for life. These include the presence and the physical state of water, the existence of an oxidant, the pH and the penetrability of the soil. Using the legacy of the 1976 Viking Labeled Release (LR) life detection experiment in conjunction with state-of-the-art laser diode spectral analysis, the instrument can be flown stand-alone, with or without a rover, or as part of an MSL-type mission. Sterility for experiment integrity and for planetary protection is provided.
A first look for parameters of public relations in Europe
van Ruler, A.A.; Vercic, D.; Buetschi, G.; Flodin, B.
2004-01-01
Teaching of public relations in Europe is largely U.S. oriented. A study has been conducted to determine whether this also applies to the practical and academic approaches in this area. A Delphi panel, consisting of experts in research, education, or both from countries in Europe, identified four
Zhang, Hong Mei; Wang, Yue; Fatemi, Mostafa; Insana, Michael F
2017-03-01
Kelvin-Voigt fractional derivative (KVFD) model parameters have been used to describe viscoelastic properties of soft tissues. However, translating model parameters into a concise set of intrinsic mechanical properties related to tissue composition and structure remains challenging. This paper begins by exploring these relationships using a biphasic emulsion materials with known composition. Mechanical properties are measured by analyzing data from two indentation techniques - ramp-stress relaxation and load-unload hysteresis tests. Material composition is predictably correlated with viscoelastic model parameters. Model parameters estimated from the tests reveal that elastic modulus E 0 closely approximates the shear modulus for pure gelatin. Fractional-order parameter α and time constant τ vary monotonically with the volume fraction of the material's fluid component. α characterizes medium fluidity and the rate of energy dissipation, and τ is a viscous time constant. Numerical simulations suggest that the viscous coefficient η is proportional to the energy lost during quasi-static force-displacement cycles, E A . The slope of E A versus η is determined by α and the applied indentation ramp time T r . Experimental measurements from phantom and ex vivo liver data show close agreement with theoretical predictions of the η - E A relation. The relative error is less than 20% for emulsions 22% for liver. We find that KVFD model parameters form a concise features space for biphasic medium characterization that described time-varying mechanical properties.
Luo, Chuan; Li, Zhaofu; Wu, Min; Jiang, Kaixia; Chen, Xiaomin; Li, Hengpeng
2017-09-01
Numerous parameters are used to construct the HSPF (Hydrological Simulation Program Fortran) model, which results in significant difficulty in calibrating the model. Parameter sensitivity analysis is an efficient method to identify important model parameters. Through this method, a model's calibration process can be simplified on the basis of understanding the model's structure. This study investigated the sensitivity of the flow and nutrient parameters of HSPF using the DSA (differential sensitivity analysis) method in the Xitiaoxi watershed, China. The results showed that flow was mostly affected by parameters related to groundwater and evapotranspiration, including DEEPFR (fraction of groundwater inflow to deep recharge), LZETP (lower-zone evapotranspiration parameter), and AGWRC (base groundwater recession), and most of the sensitive parameters had negative and nonlinear effects on flow. Additionally, nutrient components were commonly affected by parameters from land processes, including MON-SQOLIM (monthly values limiting storage of water quality in overland flow), MON-ACCUM (monthly values of accumulation), MON-IFLW-CONC (monthly concentration of water quality in interflow), and MON-GRND-CONC (monthly concentration of water quality in active groundwater). Besides, parameters from river systems, KATM20 (unit oxidation rate of total ammonia at 20 °C) had a negative and almost linear effect on ammonia concentration and MALGR (maximal unit algal growth rate for phytoplankton) had a negative and nonlinear effect on ammonia and orthophosphate concentrations. After calibrating these sensitive parameters, our model performed well for simulating flow and nutrient outputs, with R 2 and E NS (Nash-Sutcliffe efficiency) both greater than 0.75 for flow and greater than 0.5 for nutrient components. This study is expected to serve as a valuable complement to the documentation of the HSPF model to help users identify key parameters and provide a reference for performing
PARAMETER ESTIMATION AND MODEL SELECTION FOR INDOOR ENVIRONMENTS BASED ON SPARSE OBSERVATIONS
Directory of Open Access Journals (Sweden)
Y. Dehbi
2017-09-01
Full Text Available This paper presents a novel method for the parameter estimation and model selection for the reconstruction of indoor environments based on sparse observations. While most approaches for the reconstruction of indoor models rely on dense observations, we predict scenes of the interior with high accuracy in the absence of indoor measurements. We use a model-based top-down approach and incorporate strong but profound prior knowledge. The latter includes probability density functions for model parameters and sparse observations such as room areas and the building footprint. The floorplan model is characterized by linear and bi-linear relations with discrete and continuous parameters. We focus on the stochastic estimation of model parameters based on a topological model derived by combinatorial reasoning in a first step. A Gauss-Markov model is applied for estimation and simulation of the model parameters. Symmetries are represented and exploited during the estimation process. Background knowledge as well as observations are incorporated in a maximum likelihood estimation and model selection is performed with AIC/BIC. The likelihood is also used for the detection and correction of potential errors in the topological model. Estimation results are presented and discussed.
Parameter Estimation and Model Selection for Indoor Environments Based on Sparse Observations
Dehbi, Y.; Loch-Dehbi, S.; Plümer, L.
2017-09-01
This paper presents a novel method for the parameter estimation and model selection for the reconstruction of indoor environments based on sparse observations. While most approaches for the reconstruction of indoor models rely on dense observations, we predict scenes of the interior with high accuracy in the absence of indoor measurements. We use a model-based top-down approach and incorporate strong but profound prior knowledge. The latter includes probability density functions for model parameters and sparse observations such as room areas and the building footprint. The floorplan model is characterized by linear and bi-linear relations with discrete and continuous parameters. We focus on the stochastic estimation of model parameters based on a topological model derived by combinatorial reasoning in a first step. A Gauss-Markov model is applied for estimation and simulation of the model parameters. Symmetries are represented and exploited during the estimation process. Background knowledge as well as observations are incorporated in a maximum likelihood estimation and model selection is performed with AIC/BIC. The likelihood is also used for the detection and correction of potential errors in the topological model. Estimation results are presented and discussed.
Directory of Open Access Journals (Sweden)
Jie Bao
2015-12-01
Full Text Available Effective sensitivity analysis approaches are needed to identify important parameters or factors and their uncertainties in complex Earth system models composed of multi-phase multi-component phenomena and multiple biogeophysical-biogeochemical processes. In this study, the impacts of 10 hydrologic parameters in the Community Land Model on simulations of runoff and latent heat flux are evaluated using data from a watershed. Different metrics, including residual statistics, the Nash–Sutcliffe coefficient, and log mean square error, are used as alternative measures of the deviations between the simulated and field observed values. Four sensitivity analysis (SA approaches, including analysis of variance based on the generalized linear model, generalized cross validation based on the multivariate adaptive regression splines model, standardized regression coefficients based on a linear regression model, and analysis of variance based on support vector machine, are investigated. Results suggest that these approaches show consistent measurement of the impacts of major hydrologic parameters on response variables, but with differences in the relative contributions, particularly for the secondary parameters. The convergence behaviors of the SA with respect to the number of sampling points are also examined with different combinations of input parameter sets and output response variables and their alternative metrics. This study helps identify the optimal SA approach, provides guidance for the calibration of the Community Land Model parameters to improve the model simulations of land surface fluxes, and approximates the magnitudes to be adjusted in the parameter values during parametric model optimization.
Mountain bike trail compaction relation to selected physical parameters
Jeff Hale; Rodney R. Zwick
2002-01-01
The purpose of this research is to explore the rates of compaction and their relation to trail contextual aspects of: soil type, slope and crown cover on a newly established mountain bike trail in the northern reach of Vermont. A random sample of 52 sites was selected for monitoring on the 1.09-mile trail. Three penetrometer readings were taken at each of the sample...
Modeling extreme events: Sample fraction adaptive choice in parameter estimation
Neves, Manuela; Gomes, Ivette; Figueiredo, Fernanda; Gomes, Dora Prata
2012-09-01
When modeling extreme events there are a few primordial parameters, among which we refer the extreme value index and the extremal index. The extreme value index measures the right tail-weight of the underlying distribution and the extremal index characterizes the degree of local dependence in the extremes of a stationary sequence. Most of the semi-parametric estimators of these parameters show the same type of behaviour: nice asymptotic properties, but a high variance for small values of k, the number of upper order statistics to be used in the estimation, and a high bias for large values of k. This shows a real need for the choice of k. Choosing some well-known estimators of those parameters we revisit the application of a heuristic algorithm for the adaptive choice of k. The procedure is applied to some simulated samples as well as to some real data sets.
Directory of Open Access Journals (Sweden)
Filip Górski
2013-09-01
Full Text Available The paper presents the results of experimental study – part of research of additive technology using thermoplastics as a build material, namely Fused Deposition Modelling (FDM. Aim of the study was to identify the relation between basic parameter of the FDM process – model orientation during manufacturing – and a dimensional accuracy and repeatability of obtained products. A set of samples was prepared – they were manufactured with variable process parameters and they were measured using 3D scanner. Significant differences in accuracy of products of the same geometry, but manufactured with different set of process parameters were observed.
Model parameter learning using Kullback-Leibler divergence
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.
Shabani, Farzin; Kumar, Lalit
2014-01-01
Using CLIMEX and the Taguchi Method, a process-based niche model was developed to estimate potential distributions of Phoenix dactylifera L. (date palm), an economically important crop in many counties. Development of the model was based on both its native and invasive distribution and validation was carried out in terms of its extensive distribution in Iran. To identify model parameters having greatest influence on distribution of date palm, a sensitivity analysis was carried out. Changes in suitability were established by mapping of regions where the estimated distribution changed with parameter alterations. This facilitated the assessment of certain areas in Iran where parameter modifications impacted the most, particularly in relation to suitable and highly suitable locations. Parameter sensitivities were also evaluated by the calculation of area changes within the suitable and highly suitable categories. The low temperature limit (DV2), high temperature limit (DV3), upper optimal temperature (SM2) and high soil moisture limit (SM3) had the greatest impact on sensitivity, while other parameters showed relatively less sensitivity or were insensitive to change. For an accurate fit in species distribution models, highly sensitive parameters require more extensive research and data collection methods. Results of this study demonstrate a more cost effective method for developing date palm distribution models, an integral element in species management, and may prove useful for streamlining requirements for data collection in potential distribution modeling for other species as well. PMID:24722140
Directory of Open Access Journals (Sweden)
Farzin Shabani
Full Text Available Using CLIMEX and the Taguchi Method, a process-based niche model was developed to estimate potential distributions of Phoenix dactylifera L. (date palm, an economically important crop in many counties. Development of the model was based on both its native and invasive distribution and validation was carried out in terms of its extensive distribution in Iran. To identify model parameters having greatest influence on distribution of date palm, a sensitivity analysis was carried out. Changes in suitability were established by mapping of regions where the estimated distribution changed with parameter alterations. This facilitated the assessment of certain areas in Iran where parameter modifications impacted the most, particularly in relation to suitable and highly suitable locations. Parameter sensitivities were also evaluated by the calculation of area changes within the suitable and highly suitable categories. The low temperature limit (DV2, high temperature limit (DV3, upper optimal temperature (SM2 and high soil moisture limit (SM3 had the greatest impact on sensitivity, while other parameters showed relatively less sensitivity or were insensitive to change. For an accurate fit in species distribution models, highly sensitive parameters require more extensive research and data collection methods. Results of this study demonstrate a more cost effective method for developing date palm distribution models, an integral element in species management, and may prove useful for streamlining requirements for data collection in potential distribution modeling for other species as well.
Biosphere modelling for a HLW repository - scenario and parameter variations
International Nuclear Information System (INIS)
Grogan, H.
1985-03-01
In Switzerland high-level radioactive wastes have been considered for disposal in deep-lying crystalline formations. The individual doses to man resulting from radionuclides entering the biosphere via groundwater transport are calculated. The main recipient area modelled, which constitutes the base case, is a broad gravel terrace sited along the south bank of the river Rhine. An alternative recipient region, a small valley with a well, is also modelled. A number of parameter variations are performed in order to ascertain their impact on the doses. Finally two scenario changes are modelled somewhat simplistically, these consider different prevailing climates, namely tundra and a warmer climate than present. In the base case negligibly low doses to man in the long term, resulting from the existence of a HLW repository have been calculated. Cs-135 results in the largest dose (8.4E-7 mrem/y at 6.1E+6 y) while Np-237 gives the largest dose from the actinides (3.6E-8 mrem/y). The response of the model to parameter variations cannot be easily predicted due to non-linear coupling of many of the parameters. However, the calculated doses were negligibly low in all cases as were those resulting from the two scenario variations. (author)
Thermal Model Parameter Identification of a Lithium Battery
Directory of Open Access Journals (Sweden)
Dirk Nissing
2017-01-01
Full Text Available The temperature of a Lithium battery cell is important for its performance, efficiency, safety, and capacity and is influenced by the environmental temperature and by the charging and discharging process itself. Battery Management Systems (BMS take into account this effect. As the temperature at the battery cell is difficult to measure, often the temperature is measured on or nearby the poles of the cell, although the accuracy of predicting the cell temperature with those quantities is limited. Therefore a thermal model of the battery is used in order to calculate and estimate the cell temperature. This paper uses a simple RC-network representation for the thermal model and shows how the thermal parameters are identified using input/output measurements only, where the load current of the battery represents the input while the temperatures at the poles represent the outputs of the measurement. With a single measurement the eight model parameters (thermal resistances, electric contact resistances, and heat capacities can be determined using the method of least-square. Experimental results show that the simple model with the identified parameters fits very accurately to the measurements.
Douglas, P; Tyrrel, S F; Kinnersley, R P; Whelan, M; Longhurst, P J; Walsh, K; Pollard, S J T; Drew, G H
2016-12-15
Bioaerosols are released in elevated quantities from composting facilities and are associated with negative health effects, although dose-response relationships are not well understood, and require improved exposure classification. Dispersion modelling has great potential to improve exposure classification, but has not yet been extensively used or validated in this context. We present a sensitivity analysis of the ADMS dispersion model specific to input parameter ranges relevant to bioaerosol emissions from open windrow composting. This analysis provides an aid for model calibration by prioritising parameter adjustment and targeting independent parameter estimation. Results showed that predicted exposure was most sensitive to the wet and dry deposition modules and the majority of parameters relating to emission source characteristics, including pollutant emission velocity, source geometry and source height. This research improves understanding of the accuracy of model input data required to provide more reliable exposure predictions. Copyright © 2016. Published by Elsevier Ltd.
Parameter dependence and outcome dependence in dynamical models for state vector reduction
International Nuclear Information System (INIS)
Ghirardi, G.C.; Grassi, R.; Butterfield, J.; Fleming, G.N.
1993-01-01
The authors apply the distinction between parameter independence and outcome independence to the linear and nonlinear models of a recent nonrelativistic theory of continuous state vector reduction. It is shown that in the nonlinear model there is a set of realizations of the stochastic process that drives the state vector reduction for which parameter independence is violated for parallel spin components in the EPR-Bohm setup. Such a set has an appreciable probability of occurrence (∼ 1/2). On the other hand, the linear model exhibits only extremely small parameter dependence effects. Some specific features of the models are investigated and it is recalled that, as has been pointed out recently, to be able to speak of definite outcomes (or equivalently of possessed objective elements of reality) at finite times, the criteria for their attribution to physical systems must be slightly changed. The concluding section is devoted to a detailed discussion of the difficulties met when attempting to take, as a starting point for the formulation of a relativistic theory, a nonrelativistic scheme which exhibits parameter dependence. Here the authors derive a theorem which identifies the precise sense in which the occurrence of parameter dependence forbids a genuinely relativistic generalization. Finally, the authors show how the appreciable parameter dependence of the nonlinear model gives rise to problems with relativity, while the extremely weak parameter dependence of the linear model does not give rise to any difficulty, provided the appropriate criteria for the attribution of definite outcomes are taken into account. 19 refs
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)
HOM study and parameter calculation of the TESLA cavity model
Zeng, Ri-Hua; Gerigk Frank; Wang Guang-Wei; Wegner Rolf; Liu Rong; Schuh Marcel
2010-01-01
The Superconducting Proton Linac (SPL) is the project for a superconducting, high current H-accelerator at CERN. To find dangerous higher order modes (HOMs) in the SPL superconducting cavities, simulation and analysis for the cavity model using simulation tools are necessary. The. existing TESLA 9-cell cavity geometry data have been used for the initial construction of the models in HFSS. Monopole, dipole and quadrupole modes have been obtained by applying different symmetry boundaries on various cavity models. In calculation, scripting language in HFSS was used to create scripts to automatically calculate the parameters of modes in these cavity models (these scripts are also available in other cavities with different cell numbers and geometric structures). The results calculated automatically are then compared with the values given in the TESLA paper. The optimized cavity model with the minimum error will be taken as the base for further simulation of the SPL cavities.
Combustion Model and Control Parameter Optimization Methods for Single Cylinder Diesel Engine
Directory of Open Access Journals (Sweden)
Bambang Wahono
2014-01-01
Full Text Available This research presents a method to construct a combustion model and a method to optimize some control parameters of diesel engine in order to develop a model-based control system. The construction purpose of the model is to appropriately manage some control parameters to obtain the values of fuel consumption and emission as the engine output objectives. Stepwise method considering multicollinearity was applied to construct combustion model with the polynomial model. Using the experimental data of a single cylinder diesel engine, the model of power, BSFC, NOx, and soot on multiple injection diesel engines was built. The proposed method succesfully developed the model that describes control parameters in relation to the engine outputs. Although many control devices can be mounted to diesel engine, optimization technique is required to utilize this method in finding optimal engine operating conditions efficiently beside the existing development of individual emission control methods. Particle swarm optimization (PSO was used to calculate control parameters to optimize fuel consumption and emission based on the model. The proposed method is able to calculate control parameters efficiently to optimize evaluation item based on the model. Finally, the model which added PSO then was compiled in a microcontroller.
Progressive Learning of Topic Modeling Parameters: A Visual Analytics Framework.
El-Assady, Mennatallah; Sevastjanova, Rita; Sperrle, Fabian; Keim, Daniel; Collins, Christopher
2018-01-01
Topic modeling algorithms are widely used to analyze the thematic composition of text corpora but remain difficult to interpret and adjust. Addressing these limitations, we present a modular visual analytics framework, tackling the understandability and adaptability of topic models through a user-driven reinforcement learning process which does not require a deep understanding of the underlying topic modeling algorithms. Given a document corpus, our approach initializes two algorithm configurations based on a parameter space analysis that enhances document separability. We abstract the model complexity in an interactive visual workspace for exploring the automatic matching results of two models, investigating topic summaries, analyzing parameter distributions, and reviewing documents. The main contribution of our work is an iterative decision-making technique in which users provide a document-based relevance feedback that allows the framework to converge to a user-endorsed topic distribution. We also report feedback from a two-stage study which shows that our technique results in topic model quality improvements on two independent measures.
The definition of input parameters for modelling of energetic subsystems
Directory of Open Access Journals (Sweden)
Ptacek M.
2013-06-01
Full Text Available This paper is a short review and a basic description of mathematical models of renewable energy sources which present individual investigated subsystems of a system created in Matlab/Simulink. It solves the physical and mathematical relationships of photovoltaic and wind energy sources that are often connected to the distribution networks. The fuel cell technology is much less connected to the distribution networks but it could be promising in the near future. Therefore, the paper informs about a new dynamic model of the low-temperature fuel cell subsystem, and the main input parameters are defined as well. Finally, the main evaluated and achieved graphic results for the suggested parameters and for all the individual subsystems mentioned above are shown.
The definition of input parameters for modelling of energetic subsystems
Ptacek, M.
2013-06-01
This paper is a short review and a basic description of mathematical models of renewable energy sources which present individual investigated subsystems of a system created in Matlab/Simulink. It solves the physical and mathematical relationships of photovoltaic and wind energy sources that are often connected to the distribution networks. The fuel cell technology is much less connected to the distribution networks but it could be promising in the near future. Therefore, the paper informs about a new dynamic model of the low-temperature fuel cell subsystem, and the main input parameters are defined as well. Finally, the main evaluated and achieved graphic results for the suggested parameters and for all the individual subsystems mentioned above are shown.
Propagation channel characterization, parameter estimation, and modeling for wireless communications
Yin, Xuefeng
2016-01-01
Thoroughly covering channel characteristics and parameters, this book provides the knowledge needed to design various wireless systems, such as cellular communication systems, RFID and ad hoc wireless communication systems. It gives a detailed introduction to aspects of channels before presenting the novel estimation and modelling techniques which can be used to achieve accurate models. To systematically guide readers through the topic, the book is organised in three distinct parts. The first part covers the fundamentals of the characterization of propagation channels, including the conventional single-input single-output (SISO) propagation channel characterization as well as its extension to multiple-input multiple-output (MIMO) cases. Part two focuses on channel measurements and channel data post-processing. Wideband channel measurements are introduced, including the equipment, technology and advantages and disadvantages of different data acquisition schemes. The channel parameter estimation methods are ...
Lumped-parameter Model of a Bucket Foundation
DEFF Research Database (Denmark)
Andersen, Lars; Ibsen, Lars Bo; Liingaard, Morten
2009-01-01
As an alternative to gravity footings or pile foundations, offshore wind turbines at shallow water can be placed on a bucket foundation. The present analysis concerns the development of consistent lumped-parameter models for this type of foundation. The aim is to formulate a computationally effic...... be disregarded without significant loss of accuracy. Finally, special attention is drawn to the influence of the skirt stiffness, i.e. whether the embedded part of the caisson is rigid or flexible....
Directory of Open Access Journals (Sweden)
Jessica H Farley
Full Text Available Knowledge of spawning behaviour and fecundity of fish is important for estimating the reproductive potential of a stock and for constructing appropriate statistical models for assessing sustainable catch levels. Estimates of length-based reproductive parameters are particularly important for determining potential annual fecundity as a function of fish size, but they are often difficult to estimate reliably. Here we provide new information on the reproductive dynamics of southern bluefin tuna (SBT Thunnus maccoyii through the analysis of fish size and ovary histology collected on the spawning ground in 1993-1995 and 1999-2002. These are used to refine previous parameter estimates of spawning dynamics and investigate size related trends in these parameters. Our results suggest that the small SBT tend to arrive on the spawning ground slightly later and depart earlier in the spawning season relative to large fish. All females were mature and the majority were classed as spawning capable (actively spawning or non-spawning with a very small proportion classed as regressing. The fraction of females spawning per day decreased with fish size, but once females start a spawning episode, they spawned daily irrespective of size. Mean batch fecundity was estimated directly at 6.5 million oocytes. Analysis of ovary histology and ovary weight data indicated that relative batch fecundity, and the duration of spawning and non-spawning episodes, increased with fish size. These reproductive parameter estimates could be used with estimates of residency time on the spawning ground as a function of fish size (if known and demographic data for the spawning population to provide a time series of relative annual fecundity for SBT.
A procedure for determining parameters of a simplified ligament model.
Barrett, Jeff M; Callaghan, Jack P
2018-01-03
A previous mathematical model of ligament force-generation treated their behavior as a population of collagen fibres arranged in parallel. When damage was ignored in this model, an expression for ligament force in terms of the deflection, x, effective stiffness, k, mean collagen slack length, μ, and the standard deviation of slack lengths, σ, was obtained. We present a simple three-step method for determining the three model parameters (k, μ, and σ) from force-deflection data: (1) determine the equation of the line in the linear region of this curve, its slope is k and its x -intercept is -μ; (2) interpolate the force-deflection data when x is -μ to obtain F 0 ; (3) calculate σ with the equation σ=2πF 0 /k. Results from this method were in good agreement to those obtained from a least-squares procedure on experimental data - all falling within 6%. Therefore, parameters obtained using the proposed method provide a systematic way of reporting ligament parameters, or for obtaining an initial guess for nonlinear least-squares. Copyright © 2017 Elsevier Ltd. All rights reserved.
Modelling spatial-temporal and coordinative parameters in swimming.
Seifert, L; Chollet, D
2009-07-01
This study modelled the changes in spatial-temporal and coordinative parameters through race paces in the four swimming strokes. The arm and leg phases in simultaneous strokes (butterfly and breaststroke) and the inter-arm phases in alternating strokes (crawl and backstroke) were identified by video analysis to calculate the time gaps between propulsive phases. The relationships among velocity, stroke rate, stroke length and coordination were modelled by polynomial regression. Twelve elite male swimmers swam at four race paces. Quadratic regression modelled the changes in spatial-temporal and coordinative parameters with velocity increases for all four strokes. First, the quadratic regression between coordination and velocity showed changes common to all four strokes. Notably, the time gaps between the key points defining the beginning and end of the stroke phases decreased with increases in velocity, which led to decreases in glide times and increases in the continuity between propulsive phases. Conjointly, the quadratic regression among stroke rate, stroke length and velocity was similar to the changes in coordination, suggesting that these parameters may influence coordination. The main practical application for coaches and scientists is that ineffective time gaps can be distinguished from those that simply reflect an individual swimmer's profile by monitoring the glide times within a stroke cycle. In the case of ineffective time gaps, targeted training could improve the swimmer's management of glide time.
Relating auditory attributes of multichannel sound to preference and to physical parameters
DEFF Research Database (Denmark)
Choisel, Sylvain; Wickelmaier, Florian Maria
2006-01-01
within and between musical program materials, allowing for a careful generalization regarding the perception of spatial audio reproduction. Finally, a set of objective measures is derived from analysis of the sound field at the listening position in an attempt to predict the auditory attributes.......Sound reproduced by multichannel systems is affected by many factors giving rise to various sensations, or auditory attributes. Relating specific attributes to overall preference and to physical measures of the sound field provides valuable information for a better understanding of the parameters...... playing a role in sound quality evaluation. Eight selected attributes are quantified by a panel of 39 listeners using paired-comparison judgments and probabilistic choice models, and related to overall preference. A multiple-regression model predicts preference well, and some similarities are observed...
Kim, Kyung Yong; Lee, Won-Chan
2017-01-01
This article provides a detailed description of three factors (specification of the ability distribution, numerical integration, and frame of reference for the item parameter estimates) that might affect the item parameter estimation of the three-parameter logistic model, and compares five item calibration methods, which are combinations of the…
Plumb, John M.; Moffitt, Christine M.
2015-01-01
Researchers have cautioned against the borrowing of consumption and growth parameters from other species and life stages in bioenergetics growth models. In particular, the function that dictates temperature dependence in maximum consumption (Cmax) within the Wisconsin bioenergetics model for Chinook Salmon Oncorhynchus tshawytscha produces estimates that are lower than those measured in published laboratory feeding trials. We used published and unpublished data from laboratory feeding trials with subyearling Chinook Salmon from three stocks (Snake, Nechako, and Big Qualicum rivers) to estimate and adjust the model parameters for temperature dependence in Cmax. The data included growth measures in fish ranging from 1.5 to 7.2 g that were held at temperatures from 14°C to 26°C. Parameters for temperature dependence in Cmax were estimated based on relative differences in food consumption, and bootstrapping techniques were then used to estimate the error about the parameters. We found that at temperatures between 17°C and 25°C, the current parameter values did not match the observed data, indicating that Cmax should be shifted by about 4°C relative to the current implementation under the bioenergetics model. We conclude that the adjusted parameters for Cmax should produce more accurate predictions from the bioenergetics model for subyearling Chinook Salmon.
Surrogate based approaches to parameter inference in ocean models
Knio, Omar
2016-01-06
This talk discusses the inference of physical parameters using model surrogates. Attention is focused on the use of sampling schemes to build suitable representations of the dependence of the model response on uncertain input data. Non-intrusive spectral projections and regularized regressions are used for this purpose. A Bayesian inference formalism is then applied to update the uncertain inputs based on available measurements or observations. To perform the update, we consider two alternative approaches, based on the application of Markov Chain Monte Carlo methods or of adjoint-based optimization techniques. We outline the implementation of these techniques to infer dependence of wind drag, bottom drag, and internal mixing coefficients.
Entropy Parameter M in Modeling a Flow Duration Curve
Directory of Open Access Journals (Sweden)
Yu Zhang
2017-12-01
Full Text Available A flow duration curve (FDC is widely used for predicting water supply, hydropower, environmental flow, sediment load, and pollutant load. Among different methods of constructing an FDC, the entropy-based method, developed recently, is appealing because of its several desirable characteristics, such as simplicity, flexibility, and statistical basis. This method contains a parameter, called entropy parameter M, which constitutes the basis for constructing the FDC. Since M is related to the ratio of the average streamflow to the maximum streamflow which, in turn, is related to the drainage area, it may be possible to determine M a priori and construct an FDC for ungauged basins. This paper, therefore, analyzed the characteristics of M in both space and time using streamflow data from 73 gauging stations in the Brazos River basin, Texas, USA. Results showed that the M values were impacted by reservoir operation and possibly climate change. The values were fluctuating, but relatively stable, after the operation of the reservoirs. Parameter M was found to change inversely with the ratio of average streamflow to the maximum streamflow. When there was an extreme event, there occurred a jump in the M value. Further, spatially, M had a larger value if the drainage area was small.
Moolenaar, H.E.; Selten, F.M.
2004-01-01
Climate models contain numerous parameters for which the numeric values are uncertain. In the context of climate simulation and prediction, a relevant question is what range of climate outcomes is possible given the range of parameter uncertainties. Which parameter perturbation changes the climate
Estimating material parameters of a structurally based constitutive relation for skin mechanics
Jor, Jessica W. Y.
2010-11-25
This paper presents a structurally based modeling framework to characterize the structure-function relation in skin tissues, based upon biaxial tensile experiments performed in vitro on porcine skin. Equi-axial deformations were imposed by stretching circular skin specimens uniformly along twelve directions, and the resultant loads at the membrane attachment points were measured. Displacement fields at each deformation step were tracked using an image 2D cross-correlation technique. A modeling framework was developed to simulate the experiments, whereby measured forces were applied to finite element models that were created to represent the geometry and structure of the tissue samples. Parameters of a structurally based constitutive relation were then identified using nonlinear optimization. Results showed that the ground matrix stiffness ranged from 5 to 32 kPa, fiber orientation mean from 2 to 13. from the torso midline, fiber undulation mean from 1.04 to 1.34 and collagen fiber stiffness from 48 to 366 MPa. It was concluded that the objective function was highly sensitive to the mean orientation and that a priori information about fiber orientation mean was important for the reliable identification of constitutive parameters. © Springer-Verlag 2010.
Lake and lake-related drainage area parameters for site investigation program
International Nuclear Information System (INIS)
Blomqvist, P.; Brunberg, A.K.; Brydsten, L
2000-09-01
In this paper, a number of parameters of importance to a preliminary determination of the ecological function of lakes are presented. The choice of parameters have been made with respect to a model for the determination of the nature conservation values of lakes which is currently being developed by the authors of this report, but is also well suited for a general description of the lake type and the functioning of the inherent ecosystem. The parameters have been divided into five groups: 1) The location of the object relative important gradients in the surrounding nature; 2) The lake catchment area and its major constituents; 3) The lake morphometry; 4) The lake ecosystem; 5) Human-induced damages to the lake ecosystem. The first two groups, principally based on the climate, hydrology, geology and vegetation of the catchment area represent parameters that can be used to establish the rarity and representativity of the lake, and will in the context of site investigation program be used as a basis for generalisation of the results. The third group, the lake morphometry parameters, are standard parameters for the outline of sampling programmes and for calculations of the physical extension of different key habitats in the system. The fourth group, the ecosystem of the lake, includes physical, chemical and biological parameters required for determination of the stratification pattern, light climate, influence from the terrestrial ecosystem of the catchment area, trophic status, distribution of key habitats, and presence of fish and rare fauna and flora in the lake. In the context of site investigation program, the parameters in these two groups will be used for budget calculations of the flow of energy and material in the system. The fifth group, finally, describes the degree on anthropogenic influence on the ecosystem and will in the context of site investigation programmes be used to judge eventual malfunctioning within the entire, or parts of, the lake ecosystem
Lake and lake-related drainage area parameters for site investigation program
Energy Technology Data Exchange (ETDEWEB)
Blomqvist, P.; Brunberg, A.K. [Uppsala Univ. (Sweden). Dept. of Limnology; Brydsten, L [Umeaa Univ. (Sweden). Dept. of Ecology and Environmental Science
2000-09-01
In this paper, a number of parameters of importance to a preliminary determination of the ecological function of lakes are presented. The choice of parameters have been made with respect to a model for the determination of the nature conservation values of lakes which is currently being developed by the authors of this report, but is also well suited for a general description of the lake type and the functioning of the inherent ecosystem. The parameters have been divided into five groups: (1) The location of the object relative important gradients in the surrounding nature; (2) The lake catchment area and its major constituents; (3) The lake morphometry; (4) The lake ecosystem; (5) Human-induced damages to the lake ecosystem. The first two groups, principally based on the climate, hydrology, geology and vegetation of the catchment area represent parameters that can be used to establish the rarity and representativity of the lake, and will in the context of site investigation program be used as a basis for generalisation of the results. The third group, the lake morphometry parameters, are standard parameters for the outline of sampling programmes and for calculations of the physical extension of different key habitats in the system. The fourth group, the ecosystem of the lake, includes physical, chemical and biological parameters required for determination of the stratification pattern, light climate, influence from the terrestrial ecosystem of the catchment area, trophic status, distribution of key habitats, and presence of fish and rare fauna and flora in the lake. In the context of site investigation program, the parameters in these two groups will be used for budget calculations of the flow of energy and material in the system. The fifth group, finally, describes the degree on anthropogenic influence on the ecosystem and will in the context of site investigation programmes be used to judge eventual malfunctioning within the entire, or parts of, the lake
Comparison of parameter estimation algorithms in hydrological modelling
DEFF Research Database (Denmark)
Blasone, Roberta-Serena; Madsen, Henrik; Rosbjerg, Dan
2006-01-01
Local search methods have been applied successfully in calibration of simple groundwater models, but might fail in locating the optimum for models of increased complexity, due to the more complex shape of the response surface. Global search algorithms have been demonstrated to perform well...... for these types of models, although at a more expensive computational cost. The main purpose of this study is to investigate the performance of a global and a local parameter optimization algorithm, respectively, the Shuffled Complex Evolution (SCE) algorithm and the gradient-based Gauss......-Marquardt-Levenberg algorithm (implemented in the PEST software), when applied to a steady-state and a transient groundwater model. The results show that PEST can have severe problems in locating the global optimum and in being trapped in local regions of attractions. The global SCE procedure is, in general, more effective...
Parameter and uncertainty estimation for mechanistic, spatially explicit epidemiological models
Finger, Flavio; Schaefli, Bettina; Bertuzzo, Enrico; Mari, Lorenzo; Rinaldo, Andrea
2014-05-01
Epidemiological models can be a crucially important tool for decision-making during disease outbreaks. The range of possible applications spans from real-time forecasting and allocation of health-care resources to testing alternative intervention mechanisms such as vaccines, antibiotics or the improvement of sanitary conditions. Our spatially explicit, mechanistic models for cholera epidemics have been successfully applied to several epidemics including, the one that struck Haiti in late 2010 and is still ongoing. Calibration and parameter estimation of such models represents a major challenge because of properties unusual in traditional geoscientific domains such as hydrology. Firstly, the epidemiological data available might be subject to high uncertainties due to error-prone diagnosis as well as manual (and possibly incomplete) data collection. Secondly, long-term time-series of epidemiological data are often unavailable. Finally, the spatially explicit character of the models requires the comparison of several time-series of model outputs with their real-world counterparts, which calls for an appropriate weighting scheme. It follows that the usual assumption of a homoscedastic Gaussian error distribution, used in combination with classical calibration techniques based on Markov chain Monte Carlo algorithms, is likely to be violated, whereas the construction of an appropriate formal likelihood function seems close to impossible. Alternative calibration methods, which allow for accurate estimation of total model uncertainty, particularly regarding the envisaged use of the models for decision-making, are thus needed. Here we present the most recent developments regarding methods for parameter and uncertainty estimation to be used with our mechanistic, spatially explicit models for cholera epidemics, based on informal measures of goodness of fit.
Application of Powell's optimization method to surge arrester circuit models' parameters
Energy Technology Data Exchange (ETDEWEB)
Christodoulou, C.A.; Stathopulos, I.A. [National Technical University of Athens, School of Electrical and Computer Engineering, 9 Iroon Politechniou St., Zografou Campus, 157 80 Athens (Greece); Vita, V.; Ekonomou, L.; Chatzarakis, G.E. [A.S.PE.T.E. - School of Pedagogical and Technological Education, Department of Electrical Engineering Educators, N. Heraklion, 141 21 Athens (Greece)
2010-08-15
Powell's optimization method has been used for the evaluation of the surge arrester models parameters. The proper modelling of metal-oxide surge arresters and the right selection of equivalent circuit parameters are very significant issues, since quality and reliability of lightning performance studies can be improved with the more efficient representation of the arresters' dynamic behavior. The proposed approach selects optimum arrester model equivalent circuit parameter values, minimizing the error between the simulated peak residual voltage value and this given by the manufacturer. Application of the method in performed on a 120 kV metal oxide arrester. The use of the obtained optimum parameter values reduces significantly the relative error between the simulated and manufacturer's peak residual voltage value, presenting the effectiveness of the method. (author)
Prediction Model of Battery State of Charge and Control Parameter Optimization for Electric Vehicle
Directory of Open Access Journals (Sweden)
Bambang Wahono
2015-07-01
Full Text Available This paper presents the construction of a battery state of charge (SOC prediction model and the optimization method of the said model to appropriately control the number of parameters in compliance with the SOC as the battery output objectives. Research Centre for Electrical Power and Mechatronics, Indonesian Institute of Sciences has tested its electric vehicle research prototype on the road, monitoring its voltage, current, temperature, time, vehicle velocity, motor speed, and SOC during the operation. Using this experimental data, the prediction model of battery SOC was built. Stepwise method considering multicollinearity was able to efficiently develops the battery prediction model that describes the multiple control parameters in relation to the characteristic values such as SOC. It was demonstrated that particle swarm optimization (PSO succesfully and efficiently calculated optimal control parameters to optimize evaluation item such as SOC based on the model.
Kinetic Parameters of Thermal Decomposition Process Analyzed using a Mathematical Model
Nandiyanto, A. B. D.; Ekawati, R.; Wibawa, S. C.
2018-01-01
The purpose of this study was to show a mathematical analysis model for understanding kinetic parameters of thermal decomposition process. The mathematical model was derived based on phenomena happen during the thermal-related reaction. To get the kinetic parameters (i.e. reaction order, activation energy, and Arrhenius constant), the model was combined with the thermal characteristics of material gained from the thermal gravity (TG) and differential thermal analysis (DTA) curves. As an example, the model was used for analyzing the kinetic properties of trinitrotoluene. Interestingly, identical results gained from the present model with current literatures were obtained; in which these were because the present model was derived directly from the analysis of stoichiometrical and thermal analysis of the ideal chemical reaction. Since the present model confirmed to have a good agreement with current theories, further derivation from the present mathematical model can be useful for further development.
A review of distributed parameter groundwater management modeling methods
Gorelick, Steven M.
1983-01-01
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.
Utilising temperature differences as constraints for estimating parameters in a simple climate model
International Nuclear Information System (INIS)
Bodman, Roger W; Karoly, David J; Enting, Ian G
2010-01-01
Simple climate models can be used to estimate the global temperature response to increasing greenhouse gases. Changes in the energy balance of the global climate system are represented by equations that necessitate the use of uncertain parameters. The values of these parameters can be estimated from historical observations, model testing, and tuning to more complex models. Efforts have been made at estimating the possible ranges for these parameters. This study continues this process, but demonstrates two new constraints. Previous studies have shown that land-ocean temperature differences are only weakly correlated with global mean temperature for natural internal climate variations. Hence, these temperature differences provide additional information that can be used to help constrain model parameters. In addition, an ocean heat content ratio can also provide a further constraint. A pulse response technique was used to identify relative parameter sensitivity which confirmed the importance of climate sensitivity and ocean vertical diffusivity, but the land-ocean warming ratio and the land-ocean heat exchange coefficient were also found to be important. Experiments demonstrate the utility of the land-ocean temperature difference and ocean heat content ratio for setting parameter values. This work is based on investigations with MAGICC (Model for the Assessment of Greenhouse-gas Induced Climate Change) as the simple climate model.
Directory of Open Access Journals (Sweden)
Zhenggang Du
2015-03-01
Full Text Available To improve models for accurate projections, data assimilation, an emerging statistical approach to combine models with data, have recently been developed to probe initial conditions, parameters, data content, response functions and model uncertainties. Quantifying how many information contents are contained in different data streams is essential to predict future states of ecosystems and the climate. This study uses a data assimilation approach to examine the information contents contained in flux- and biometric-based data to constrain parameters in a terrestrial carbon (C model, which includes canopy photosynthesis and vegetation–soil C transfer submodels. Three assimilation experiments were constructed with either net ecosystem exchange (NEE data only or biometric data only [including foliage and woody biomass, litterfall, soil organic C (SOC and soil respiration], or both NEE and biometric data to constrain model parameters by a probabilistic inversion application. The results showed that NEE data mainly constrained parameters associated with gross primary production (GPP and ecosystem respiration (RE but were almost invalid for C transfer coefficients, while biometric data were more effective in constraining C transfer coefficients than other parameters. NEE and biometric data constrained about 26% (6 and 30% (7 of a total of 23 parameters, respectively, but their combined application constrained about 61% (14 of all parameters. The complementarity of NEE and biometric data was obvious in constraining most of parameters. The poor constraint by only NEE or biometric data was probably attributable to either the lack of long-term C dynamic data or errors from measurements. Overall, our results suggest that flux- and biometric-based data, containing different processes in ecosystem C dynamics, have different capacities to constrain parameters related to photosynthesis and C transfer coefficients, respectively. Multiple data sources could also
Some notes on unobserved parameters (frailties) in reliability modeling
International Nuclear Information System (INIS)
Cha, Ji Hwan; Finkelstein, Maxim
2014-01-01
Unobserved random quantities (frailties) often appear in various reliability problems especially when dealing with the failure rates of items from heterogeneous populations. As the failure rate is a conditional characteristic, the distributions of these random quantities, similar to Bayesian approaches, are updated in accordance with the corresponding survival information. At some instances, apart from a statistical meaning, frailties can have also useful interpretations describing the underlying lifetime model. We discuss and clarify these issues in reliability context and present and analyze several meaningful examples. We consider the proportional hazards model with a random factor; the stress–strength model, where the unobserved strength of a system can be viewed as frailty; a parallel system with a random number of components and, finally, the first passage time problem for the Wiener process with random parameters. - Highlights: • We discuss and clarify the notion of frailty in reliability context and present and analyze several meaningful examples. • The paper provides a new insight and general perspective on reliability models with unobserved parameters. • The main message of the paper is well illustrated by several meaningful examples and emphasized by detailed discussion
A parameter network and model pyramid for managing technical information flow
International Nuclear Information System (INIS)
Sinnock, S.; Hartman, H.A.
1994-01-01
Prototypes of information management tools have been developed that can help communicate the technical basis for nuclear waste disposal to a broad audience of program scientists and engineers, project managers, and informed observers from stakeholder organizations. These tools include system engineering concepts, parameter networks expressed as influence diagrams, associated model hierarchies, and a relational database. These tools are used to express relationships among data-collection parameters, model input parameters, model output parameters, systems requirements, physical elements of a system description, and functional analysis of the contribution of physical elements and their associated parameters in satisfying the system requirements. By organizing parameters, models, physical elements, functions, and requirements in a visually reviewable network and a relational database the severe communication challenges facing participants in the nuclear waste dialog can be addressed. The network identifies the influences that data collected in the field have on measures of repository suitability, providing a visual, traceable map that clarifies the role of data and models in supporting conclusions about repository suitability. The map allows conclusions to be traced directly to the underlying parameters and models. Uncertainty in these underlying elements can be exposed to open review in the context of the effects uncertainty has on judgements about suitability. A parameter network provides a stage upon which an informed social dialog about the technical merits of a nuclear waste repository can be conducted. The basis for such dialog must be that stage, if decisions about repository suitability are to be based on a repository's ability to meet requirements embodied in laws and regulations governing disposal of nuclear wastes
Modelling Technical and Economic Parameters in Selection of Manufacturing Devices
Directory of Open Access Journals (Sweden)
Naqib Daneshjo
2017-11-01
Full Text Available Sustainable science and technology development is also conditioned by continuous development of means of production which have a key role in structure of each production system. Mechanical nature of the means of production is complemented by controlling and electronic devices in context of intelligent industry. A selection of production machines for a technological process or technological project has so far been practically resolved, often only intuitively. With regard to increasing intelligence, the number of variable parameters that have to be considered when choosing a production device is also increasing. It is necessary to use computing techniques and decision making methods according to heuristic methods and more precise methodological procedures during the selection. The authors present an innovative model for optimization of technical and economic parameters in the selection of manufacturing devices for industry 4.0.
Gas ultracentrifuge separative parameters modeling using hybrid neural networks
International Nuclear Information System (INIS)
Crus, Maria Ursulina de Lima
2005-01-01
A hybrid neural network is developed for the calculation of the separative performance of an ultracentrifuge. A feed forward neural network is trained to estimate the internal flow parameters of a gas ultracentrifuge, and then these parameters are applied in the diffusion equation. For this study, a 573 experimental data set is used to establish the relation between the separative performance and the controlled variables. The process control variables considered are: the feed flow rate F, the cut θ and the product pressure Pp. The mechanical arrangements consider the radial waste scoop dimension, the rotating baffle size D s and the axial feed location Z E . The methodology was validated through the comparison of the calculated separative performance with experimental values. This methodology may be applied to other processes, just by adapting the phenomenological procedures. (author)
Dynamic systems models new methods of parameter and state estimation
2016-01-01
This monograph is an exposition of a novel method for solving inverse problems, a method of parameter estimation for time series data collected from simulations of real experiments. These time series might be generated by measuring the dynamics of aircraft in flight, by the function of a hidden Markov model used in bioinformatics or speech recognition or when analyzing the dynamics of asset pricing provided by the nonlinear models of financial mathematics. Dynamic Systems Models demonstrates the use of algorithms based on polynomial approximation which have weaker requirements than already-popular iterative methods. Specifically, they do not require a first approximation of a root vector and they allow non-differentiable elements in the vector functions being approximated. The text covers all the points necessary for the understanding and use of polynomial approximation from the mathematical fundamentals, through algorithm development to the application of the method in, for instance, aeroplane flight dynamic...
Parameter Estimation for a Class of Lifetime Models
Directory of Open Access Journals (Sweden)
Xinyang Ji
2014-01-01
Full Text Available Our purpose in this paper is to present a better method of parametric estimation for a bivariate nonlinear regression model, which takes the performance indicator of rubber aging as the dependent variable and time and temperature as the independent variables. We point out that the commonly used two-step method (TSM, which splits the model and estimate parameters separately, has limitation. Instead, we apply the Marquardt’s method (MM to implement parametric estimation directly for the model and compare these two methods of parametric estimation by random simulation. Our results show that MM has better effect of data fitting, more reasonable parametric estimates, and smaller prediction error compared with TSM.
The parameter space of Cubic Galileon models for cosmic acceleration
Bellini, Emilio
2013-01-01
We use recent measurements of the expansion history of the universe to place constraints on the parameter space of cubic Galileon models. This gives strong constraints on the Lagrangian of these models. Most dynamical terms in the Galileon Lagrangian are constraint to be small and the acceleration is effectively provided by a constant term in the scalar potential, thus reducing, effectively, to a LCDM model for current acceleration. The effective equation of state is indistinguishable from that of a cosmological constant w = -1 and the data constraint it to have no temporal variations of more than at the few % level. The energy density of the Galileon can contribute only to about 10% of the acceleration energy density, being the other 90% a cosmological constant term. This demonstrates how useful direct measurements of the expansion history of the universe are at constraining the dynamical nature of dark energy.
A new relation of parameters of Bohr-Mottelson rotational spectra formula
International Nuclear Information System (INIS)
Li Mingliang; Xu Fuxin
2003-01-01
With the first three terms of Harris formula included and Mottelson's method followed, a new relation of the parameters of Bohr-Mottelson rotational spectra formula is brought forward. Superdeformed bands of even-even nuclei and normal deformed bands of nuclei in actinide and rare-earth are fitted with four-parameter Bohr-Mottelson rotational spectra formula. The relations of the parameters A, B, C, D are studied. The result show, for normal deformed bands, the new relation approach the experiment value in the same degree as the relation deduced from ab formula, but for superdeformed bands, the new relation is closer to the experiment than the relation deduced from ab formula. Three-parameter Harris formula may have better convergence than two-parameter Harris formula
Water quality modelling for ephemeral rivers: Model development and parameter assessment
Mannina, Giorgio; Viviani, Gaspare
2010-11-01
SummaryRiver water quality models can be valuable tools for the assessment and management of receiving water body quality. However, such water quality models require accurate model calibration in order to specify model parameters. Reliable model calibration requires an extensive array of water quality data that are generally rare and resource-intensive, both economically and in terms of human resources, to collect. In the case of small rivers, such data are scarce due to the fact that these rivers are generally considered too insignificant, from a practical and economic viewpoint, to justify the investment of such considerable time and resources. As a consequence, the literature contains very few studies on the water quality modelling for small rivers, and such studies as have been published are fairly limited in scope. In this paper, a simplified river water quality model is presented. The model is an extension of the Streeter-Phelps model and takes into account the physico-chemical and biological processes most relevant to modelling the quality of receiving water bodies (i.e., degradation of dissolved carbonaceous substances, ammonium oxidation, algal uptake and denitrification, dissolved oxygen balance, including depletion by degradation processes and supply by physical reaeration and photosynthetic production). The model has been applied to an Italian case study, the Oreto river (IT), which has been the object of an Italian research project aimed at assessing the river's water quality. For this reason, several monitoring campaigns have been previously carried out in order to collect water quantity and quality data on this river system. In particular, twelve river cross sections were monitored, and both flow and water quality data were collected for each cross section. The results of the calibrated model show satisfactory agreement with the measured data and results reveal important differences between the parameters used to model small rivers as compared to
Energy balance and the Malthusian parameter, m, of grazing small rodents : A graphic model.
Stenseth, Nils Chr
1978-01-01
A graphic model based on cost and gain functions is developed for predicting the relative magnitude of the Malthusian parameter, m, for different phenotypes. The analysis is mainly restricted to grazing small rodents. The cost function is derived by depicting the probability of death due to predation, parasitism etc. as a function of time spent outside the nest. The gain function is derived by comparing the energy obtained by digestion, with energy used (or needed) for maintenance metabolism, both when outside and inside the nest.The model is applied for predicting the relative magnitude of the Malthusian parameter of small versus large phenotypes of grazing rodents. Of these, the smaller phenotypes are concluded to have the larger Malthusian parameter. This may not hold true for hunters (granivores and predators). These conclusions are used for reinterpreting the often observed geographical size trend in warm-blooded vertebrates (Bergmann's rule).The model is further applied to the determination of the relative magnitude of the Malthusian parameter for aggresive and docile strategies hypothesized in Chitty's theory for fluctuating populations. Of these, the aggressive strategy is concluded to have the lowest Malthusian parameter. Although not verifying Chitty's theory, these results support the earlier hypothesis that the aggressive strategy may under certain situations have lower survival. Based on the present model, nothing can be said about whether or not a polymorphic population as hypothesized by Chitty will exhibit oscillations.
Analysis of Model Parameters for a Polymer Filtration Simulator
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N. Brackett-Rozinsky
2011-01-01
Full Text Available We examine a simulation model for polymer extrusion filters and determine its sensitivity to filter parameters. The simulator is a three-dimensional, time-dependent discretization of a coupled system of nonlinear partial differential equations used to model fluid flow and debris transport, along with statistical relationships that define debris distributions and retention probabilities. The flow of polymer fluid, and suspended debris particles, is tracked to determine how well a filter performs and how long it operates before clogging. A filter may have multiple layers, characterized by thickness, porosity, and average pore diameter. In this work, the thickness of each layer is fixed, while the porosities and pore diameters vary for a two-layer and three-layer study. The effects of porosity and average pore diameter on the measures of filter quality are calculated. For the three layer model, these effects are tested for statistical significance using analysis of variance. Furthermore, the effects of each pair of interacting parameters are considered. This allows the detection of complexity, where in changing two aspects of a filter together may generate results substantially different from what occurs when those same aspects change separately. The principal findings indicate that the first layer of a filter is the most important.
Optimization of Experimental Model Parameter Identification for Energy Storage Systems
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Rosario Morello
2013-09-01
Full Text Available The smart grid approach is envisioned to take advantage of all available modern technologies in transforming the current power system to provide benefits to all stakeholders in the fields of efficient energy utilisation and of wide integration of renewable sources. Energy storage systems could help to solve some issues that stem from renewable energy usage in terms of stabilizing the intermittent energy production, power quality and power peak mitigation. With the integration of energy storage systems into the smart grids, their accurate modeling becomes a necessity, in order to gain robust real-time control on the network, in terms of stability and energy supply forecasting. In this framework, this paper proposes a procedure to identify the values of the battery model parameters in order to best fit experimental data and integrate it, along with models of energy sources and electrical loads, in a complete framework which represents a real time smart grid management system. The proposed method is based on a hybrid optimisation technique, which makes combined use of a stochastic and a deterministic algorithm, with low computational burden and can therefore be repeated over time in order to account for parameter variations due to the battery’s age and usage.
Applying Atmospheric Measurements to Constrain Parameters of Terrestrial Source Models
Hyer, E. J.; Kasischke, E. S.; Allen, D. J.
2004-12-01
Quantitative inversions of atmospheric measurements have been widely applied to constrain atmospheric budgets of a range of trace gases. Experiments of this type have revealed persistent discrepancies between 'bottom-up' and 'top-down' estimates of source magnitudes. The most common atmospheric inversion uses the absolute magnitude as the sole parameter for each source, and returns the optimal value of that parameter. In order for atmospheric measurements to be useful for improving 'bottom-up' models of terrestrial sources, information about other properties of the sources must be extracted. As the density and quality of atmospheric trace gas measurements improve, examination of higher-order properties of trace gas sources should become possible. Our model of boreal forest fire emissions is parameterized to permit flexible examination of the key uncertainties in this source. Using output from this model together with the UM CTM, we examined the sensitivity of CO concentration measurements made by the MOPITT instrument to various uncertainties in the boreal source: geographic distribution of burned area, fire type (crown fires vs. surface fires), and fuel consumption in above-ground and ground-layer fuels. Our results indicate that carefully designed inversion experiments have the potential to help constrain not only the absolute magnitudes of terrestrial sources, but also the key uncertainties associated with 'bottom-up' estimates of those sources.
Bayesian parameter estimation for stochastic models of biological cell migration
Dieterich, Peter; Preuss, Roland
2013-08-01
Cell migration plays an essential role under many physiological and patho-physiological conditions. It is of major importance during embryonic development and wound healing. In contrast, it also generates negative effects during inflammation processes, the transmigration of tumors or the formation of metastases. Thus, a reliable quantification and characterization of cell paths could give insight into the dynamics of these processes. Typically stochastic models are applied where parameters are extracted by fitting models to the so-called mean square displacement of the observed cell group. We show that this approach has several disadvantages and problems. Therefore, we propose a simple procedure directly relying on the positions of the cell's trajectory and the covariance matrix of the positions. It is shown that the covariance is identical with the spatial aging correlation function for the supposed linear Gaussian models of Brownian motion with drift and fractional Brownian motion. The technique is applied and illustrated with simulated data showing a reliable parameter estimation from single cell paths.
Proliferation in Non-Hodgkin’S Lymphomas and Its Prognostic Value Related to Staging Parameters
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Irene Lorand‐Metze
2004-01-01
Full Text Available In malignant lymphomas, cell kinetics has shown to be related with histologic type as well as with the clinical behaviour. The aim of our study was to investigate the relevance of cell proliferation parameters on overall survival in non‐Hodgkin's lymphomas as well as their relationship with prognostic factors such as International Prognostic Index (IPI. We performed DNA‐flow‐cytometry (S‐phase fraction and detection of DNA‐aneuploidy as well as cytologic examination and the AgNOR technique in material obtained by fine needle aspiration of lymph nodes at diagnosis. The majority of the patients were stage IV by Ann Arbor and intermediate risk by IPI (42/55. When analyzing all patients together, histologic type by the WHO classification, IPI and the presence of a DNA‐aneuploid clone could not separate well patients with a different survival. For all patients, univariate Cox analysis revealed S‐phase (SPF and AgNOR parameters to be of prognostic value. In the multivariate analysis, however, only SPF remained in the final model. Yet, when stratifying for DNA‐ploidy, only the total number of AgNORs/nucleus was an independent parameter. Looking only at the DNA‐diploid cases, the AgNOR pattern remained the most important parameter, whereas for the DNA‐aneuploid cases this was true for SPF. When studying patients with B large cell lymphoma separately, only DNA‐ploidy was a prognostic factor. In summary, cell kinetic parameters reveal important prognostic information in NHL patients. Furthermore, DNA‐aneuploidy seems to interfere with the analysis of the AgNOR pattern.
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.
Microbial Communities Model Parameter Calculation for TSPA/SR
Energy Technology Data Exchange (ETDEWEB)
D. Jolley
2001-07-16
This calculation has several purposes. First the calculation reduces the information contained in ''Committed Materials in Repository Drifts'' (BSC 2001a) to useable parameters required as input to MING V1.O (CRWMS M&O 1998, CSCI 30018 V1.O) for calculation of the effects of potential in-drift microbial communities as part of the microbial communities model. The calculation is intended to replace the parameters found in Attachment II of the current In-Drift Microbial Communities Model revision (CRWMS M&O 2000c) with the exception of Section 11-5.3. Second, this calculation provides the information necessary to supercede the following DTN: M09909SPAMING1.003 and replace it with a new qualified dataset (see Table 6.2-1). The purpose of this calculation is to create the revised qualified parameter input for MING that will allow {Delta}G (Gibbs Free Energy) to be corrected for long-term changes to the temperature of the near-field environment. Calculated herein are the quadratic or second order regression relationships that are used in the energy limiting calculations to potential growth of microbial communities in the in-drift geochemical environment. Third, the calculation performs an impact review of a new DTN: M00012MAJIONIS.000 that is intended to replace the currently cited DTN: GS9809083 12322.008 for water chemistry data used in the current ''In-Drift Microbial Communities Model'' revision (CRWMS M&O 2000c). Finally, the calculation updates the material lifetimes reported on Table 32 in section 6.5.2.3 of the ''In-Drift Microbial Communities'' AMR (CRWMS M&O 2000c) based on the inputs reported in BSC (2001a). Changes include adding new specified materials and updating old materials information that has changed.
Microbial Communities Model Parameter Calculation for TSPA/SR
International Nuclear Information System (INIS)
D. Jolley
2001-01-01
This calculation has several purposes. First the calculation reduces the information contained in ''Committed Materials in Repository Drifts'' (BSC 2001a) to useable parameters required as input to MING V1.O (CRWMS M and O 1998, CSCI 30018 V1.O) for calculation of the effects of potential in-drift microbial communities as part of the microbial communities model. The calculation is intended to replace the parameters found in Attachment II of the current In-Drift Microbial Communities Model revision (CRWMS M and O 2000c) with the exception of Section 11-5.3. Second, this calculation provides the information necessary to supercede the following DTN: M09909SPAMING1.003 and replace it with a new qualified dataset (see Table 6.2-1). The purpose of this calculation is to create the revised qualified parameter input for MING that will allow ΔG (Gibbs Free Energy) to be corrected for long-term changes to the temperature of the near-field environment. Calculated herein are the quadratic or second order regression relationships that are used in the energy limiting calculations to potential growth of microbial communities in the in-drift geochemical environment. Third, the calculation performs an impact review of a new DTN: M00012MAJIONIS.000 that is intended to replace the currently cited DTN: GS9809083 12322.008 for water chemistry data used in the current ''In-Drift Microbial Communities Model'' revision (CRWMS M and O 2000c). Finally, the calculation updates the material lifetimes reported on Table 32 in section 6.5.2.3 of the ''In-Drift Microbial Communities'' AMR (CRWMS M and O 2000c) based on the inputs reported in BSC (2001a). Changes include adding new specified materials and updating old materials information that has changed
A new method to estimate parameters of linear compartmental models using artificial neural networks
International Nuclear Information System (INIS)
Gambhir, Sanjiv S.; Keppenne, Christian L.; Phelps, Michael E.; Banerjee, Pranab K.
1998-01-01
At present, the preferred tool for parameter estimation in compartmental analysis is an iterative procedure; weighted nonlinear regression. For a large number of applications, observed data can be fitted to sums of exponentials whose parameters are directly related to the rate constants/coefficients of the compartmental models. Since weighted nonlinear regression often has to be repeated for many different data sets, the process of fitting data from compartmental systems can be very time consuming. Furthermore the minimization routine often converges to a local (as opposed to global) minimum. In this paper, we examine the possibility of using artificial neural networks instead of weighted nonlinear regression in order to estimate model parameters. We train simple feed-forward neural networks to produce as outputs the parameter values of a given model when kinetic data are fed to the networks' input layer. The artificial neural networks produce unbiased estimates and are orders of magnitude faster than regression algorithms. At noise levels typical of many real applications, the neural networks are found to produce lower variance estimates than weighted nonlinear regression in the estimation of parameters from mono- and biexponential models. These results are primarily due to the inability of weighted nonlinear regression to converge. These results establish that artificial neural networks are powerful tools for estimating parameters for simple compartmental models. (author)
Azam, Mohammad; Rahman, Zillur; Talib, Faisal; Singh, K J
2012-01-01
The purpose of this article is to identify and critically analyze healthcare establishment (HCE) quality parameters described in the literature. It aims to propose an integrated quality model that includes technical quality and associated supportive quality parameters to achieve optimum patient satisfaction. The authors use an extensive in-depth healthcare quality literature review, discerning gaps via a critical analysis in relation to their overall impact on patient management, while identifying an integrated quality model acceptable to hospital staff. The article provides insights into contemporary HCE quality parameters by critically analyzing relevant literature. It also evolves and proposes an integrated HCE-quality model. Owing to HCE confidentiality, especially regarding patient data, information cannot be accessed. The integrated quality model parameters have practical utility for healthcare service managers. However, further studies may be required to refine and integrate newer parameters to ensure continuous quality improvement. This article adds a new perspective to understanding quality parameters and suggests an integrated quality model that has practical value for maintaining HCE service quality to benefit many stakeholders.
Epistemology and Rosen's Modeling Relation
International Nuclear Information System (INIS)
Dress, W.B.
1999-01-01
Rosen's modeling relation is embedded in Popper's three worlds to provide an heuristic tool for model building and a guide for thinking about complex systems. The utility of this construct is demonstrated by suggesting a solution to the problem of pseudo science and a resolution of the famous Bohr-Einstein debates. A theory of bizarre systems is presented by an analogy with entangled particles of quantum mechanics. This theory underscores the poverty of present-day computational systems (e.g., computers) for creating complex and bizarre entities by distinguishing between mechanism and organism
Modelled basic parameters for semi-industrial irradiation plant design
International Nuclear Information System (INIS)
Mangussi, J.
2009-01-01
The basic parameters of an irradiation plant design are the total activity, the product uniformity ratio and the efficiency process. The target density, the minimum dose required and the throughput depends on the use to which the irradiator will be put at. In this work, a model for calculating the specific dose rate at several depths in an infinite homogeneous medium produced by a slab source irradiator is presented. The product minimum dose rate for a set of target thickness is obtained. The design method steps are detailed and an illustrative example is presented. (author)
Lumped-parameter fuel rod model for rapid thermal transients
International Nuclear Information System (INIS)
Perkins, K.R.; Ramshaw, J.D.
1975-07-01
The thermal behavior of fuel rods during simulated accident conditions is extremely sensitive to the heat transfer coefficient which is, in turn, very sensitive to the cladding surface temperature and the fluid conditions. The development of a semianalytical, lumped-parameter fuel rod model which is intended to provide accurate calculations, in a minimum amount of computer time, of the thermal response of fuel rods during a simulated loss-of-coolant accident is described. The results show good agreement with calculations from a comprehensive fuel-rod code (FRAP-T) currently in use at Aerojet Nuclear Company
Taming Many-Parameter BSM Models with Bayesian Neural Networks
Kuchera, M. P.; Karbo, A.; Prosper, H. B.; Sanchez, A.; Taylor, J. Z.
2017-09-01
The search for physics Beyond the Standard Model (BSM) is a major focus of large-scale high energy physics experiments. One method is to look for specific deviations from the Standard Model that are predicted by BSM models. In cases where the model has a large number of free parameters, standard search methods become intractable due to computation time. This talk presents results using Bayesian Neural Networks, a supervised machine learning method, to enable the study of higher-dimensional models. The popular phenomenological Minimal Supersymmetric Standard Model was studied as an example of the feasibility and usefulness of this method. Graphics Processing Units (GPUs) are used to expedite the calculations. Cross-section predictions for 13 TeV proton collisions will be presented. My participation in the Conference Experience for Undergraduates (CEU) in 2004-2006 exposed me to the national and global significance of cutting-edge research. At the 2005 CEU, I presented work from the previous summer's SULI internship at Lawrence Berkeley Laboratory, where I learned to program while working on the Majorana Project. That work inspired me to follow a similar research path, which led me to my current work on computational methods applied to BSM physics.
Bayesian analysis of inflation: Parameter estimation for single field models
International Nuclear Information System (INIS)
Mortonson, Michael J.; Peiris, Hiranya V.; Easther, Richard
2011-01-01
Future astrophysical data sets promise to strengthen constraints on models of inflation, and extracting these constraints requires methods and tools commensurate with the quality of the data. In this paper we describe ModeCode, a new, publicly available code that computes the primordial scalar and tensor power spectra for single-field inflationary models. ModeCode solves the inflationary mode equations numerically, avoiding the slow roll approximation. It is interfaced with CAMB and CosmoMC to compute cosmic microwave background angular power spectra and perform likelihood analysis and parameter estimation. ModeCode is easily extendable to additional models of inflation, and future updates will include Bayesian model comparison. Errors from ModeCode contribute negligibly to the error budget for analyses of data from Planck or other next generation experiments. We constrain representative single-field models (φ n with n=2/3, 1, 2, and 4, natural inflation, and 'hilltop' inflation) using current data, and provide forecasts for Planck. From current data, we obtain weak but nontrivial limits on the post-inflationary physics, which is a significant source of uncertainty in the predictions of inflationary models, while we find that Planck will dramatically improve these constraints. In particular, Planck will link the inflationary dynamics with the post-inflationary growth of the horizon, and thus begin to probe the ''primordial dark ages'' between TeV and grand unified theory scale energies.
Brand, Jonathan; Zhang, Zheming; Agarwal, Ramesh K.
2014-02-01
A simple but reasonably accurate battery model is required for simulating the performance of electrical systems that employ a battery for example an electric vehicle, as well as for investigating their potential as an energy storage device. In this paper, a relatively simple equivalent circuit based model is employed for modeling the performance of a battery. A computer code utilizing a multi-objective genetic algorithm is developed for the purpose of extracting the battery performance parameters. The code is applied to several existing industrial batteries as well as to two recently proposed high performance batteries which are currently in early research and development stage. The results demonstrate that with the optimally extracted performance parameters, the equivalent circuit based battery model can accurately predict the performance of various batteries of different sizes, capacities, and materials. Several test cases demonstrate that the multi-objective genetic algorithm can serve as a robust and reliable tool for extracting the battery performance parameters.
Directory of Open Access Journals (Sweden)
Khaled MAMMAR
2013-11-01
Full Text Available In this paper, a new approach based on Experimental of design methodology (DoE is used to estimate the optimal of unknown model parameters proton exchange membrane fuel cell (PEMFC. This proposed approach combines the central composite face-centered (CCF and numerical PEMFC electrochemical. Simulation results obtained using electrochemical model help to predict the cell voltage in terms of inlet partial pressures of hydrogen and oxygen, stack temperature, and operating current. The value of the previous model and (CCF design methodology is used for parametric analysis of electrochemical model. Thus it is possible to evaluate the relative importance of each parameter to the simulation accuracy. However this methodology is able to define the exact values of the parameters from the manufacture data. It was tested for the BCS 500-W stack PEM Generator, a stack rated at 500 W, manufactured by American Company BCS Technologies FC.
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.
Application of regression model on stream water quality parameters
International Nuclear Information System (INIS)
Suleman, M.; Maqbool, F.; Malik, A.H.; Bhatti, Z.A.
2012-01-01
Statistical analysis was conducted to evaluate the effect of solid waste leachate from the open solid waste dumping site of Salhad on the stream water quality. Five sites were selected along the stream. Two sites were selected prior to mixing of leachate with the surface water. One was of leachate and other two sites were affected with leachate. Samples were analyzed for pH, water temperature, electrical conductivity (EC), total dissolved solids (TDS), Biological oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO) and total bacterial load (TBL). In this study correlation coefficient r among different water quality parameters of various sites were calculated by using Pearson model and then average of each correlation between two parameters were also calculated, which shows TDS and EC and pH and BOD have significantly increasing r value, while temperature and TDS, temp and EC, DO and BL, DO and COD have decreasing r value. Single factor ANOVA at 5% level of significance was used which shows EC, TDS, TCL and COD were significantly differ among various sites. By the application of these two statistical approaches TDS and EC shows strongly positive correlation because the ions from the dissolved solids in water influence the ability of that water to conduct an electrical current. These two parameters significantly vary among 5 sites which are further confirmed by using linear regression. (author)
Persuasion, Politeness and Relational Models
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Jerzy Świątek
2017-06-01
Full Text Available Politeness Theory, just like Grice’s Cooperative Principle, points out that pragmatic analysis of language behaviour has to be grounded in extra-linguistic facts of social (or even biological nature. Additionally, despite the slightly misleading label, Politeness Theory provides a sound methodology to explain some persuasive as well as politeness phenomena. In the same vein, the so called Relational Model Theory provides another theoretical framework for the explanation of persuasive phenomena and persuasive language. Both Relational Model Theory and Politeness Theory show that persuasion is also to be understood as a rational response to not-so-rational social and biological needs. In the article an attempt is made to compare the two theories focusing on their explanatory power in reference to language choices aiming at enhancing the persuasive potential of a language message.
Optimization of process parameters through GRA, TOPSIS and RSA models
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Suresh Nipanikar
2018-01-01
Full Text Available This article investigates the effect of cutting parameters on the surface roughness and flank wear during machining of titanium alloy Ti-6Al-4V ELI( Extra Low Interstitial in minimum quantity lubrication environment by using PVD TiAlN insert. Full factorial design of experiment was used for the machining 2 factors 3 levels and 2 factors 2 levels. Turning parameters studied were cutting speed (50, 65, 80 m/min, feed (0.08, 0.15, 0.2 mm/rev and depth of cut 0.5 mm constant. The results show that 44.61 % contribution of feed and 43.57 % contribution of cutting speed on surface roughness also 53.16 % contribution of cutting tool and 26.47 % contribution of cutting speed on tool flank wear. Grey relational analysis and TOPSIS method suggest the optimum combinations of machining parameters as cutting speed: 50 m/min, feed: 0.8 mm/rev., cutting tool: PVD TiAlN, cutting fluid: Palm oi
Energy Technology Data Exchange (ETDEWEB)
Tonk, Elisa C.M., E-mail: ilse.tonk@rivm.nl [Department of Toxicogenomics, Maastricht University, Maastricht (Netherlands); Laboratory for Health Protection Research, National Institute for Public Health and the Environment (RIVM), Bilthoven (Netherlands); Verhoef, Aart; Gremmer, Eric R. [Laboratory for Health Protection Research, National Institute for Public Health and the Environment (RIVM), Bilthoven (Netherlands); Loveren, Henk van [Department of Toxicogenomics, Maastricht University, Maastricht (Netherlands); Laboratory for Health Protection Research, National Institute for Public Health and the Environment (RIVM), Bilthoven (Netherlands); Piersma, Aldert H. [Laboratory for Health Protection Research, National Institute for Public Health and the Environment (RIVM), Bilthoven (Netherlands); Institute for Risk Assessment Sciences, Veterinary Faculty, Utrecht University, Utrecht (Netherlands)
2012-04-01
The developing immune system displays a relatively high sensitivity as compared to both general toxicity parameters and to the adult immune system. In this study we have performed such comparisons using di(2-ethylhexyl) phthalate (DEHP) as a model compound. DEHP is the most abundant phthalate in the environment and perinatal exposure to DEHP has been shown to disrupt male sexual differentiation. In addition, phthalate exposure has been associated with immune dysfunction as evidenced by effects on the expression of allergy. Male wistar rats were dosed with corn oil or DEHP by gavage from postnatal day (PND) 10–50 or PND 50–90 at doses between 1 and 1000 mg/kg/day. Androgen-dependent organ weights showed effects at lower dose levels in juvenile versus adult animals. Immune parameters affected included TDAR parameters in both age groups, NK activity in juvenile animals and TNF-α production by adherent splenocytes in adult animals. Immune parameters were affected at lower dose levels compared to developmental parameters. Overall, more immune parameters were affected in juvenile animals compared to adult animals and effects were observed at lower dose levels. The results of this study show a relatively higher sensitivity of juvenile versus adult rats. Furthermore, they illustrate the relative sensitivity of the developing immune system in juvenile animals as compared to general toxicity and developmental parameters. This study therefore provides further argumentation for performing dedicated developmental immune toxicity testing as a default in regulatory toxicology. -- Highlights: ► In this study we evaluate the relative sensitivities for DEHP induced effects. ► Results of this study demonstrate the age-dependency of DEHP toxicity. ► Functional immune parameters were more sensitive than structural immune parameters. ► Immune parameters were affected at lower dose levels than developmental parameters. ► Findings demonstrate the susceptibility of the
International Nuclear Information System (INIS)
Tonk, Elisa C.M.; Verhoef, Aart; Gremmer, Eric R.; Loveren, Henk van; Piersma, Aldert H.
2012-01-01
The developing immune system displays a relatively high sensitivity as compared to both general toxicity parameters and to the adult immune system. In this study we have performed such comparisons using di(2-ethylhexyl) phthalate (DEHP) as a model compound. DEHP is the most abundant phthalate in the environment and perinatal exposure to DEHP has been shown to disrupt male sexual differentiation. In addition, phthalate exposure has been associated with immune dysfunction as evidenced by effects on the expression of allergy. Male wistar rats were dosed with corn oil or DEHP by gavage from postnatal day (PND) 10–50 or PND 50–90 at doses between 1 and 1000 mg/kg/day. Androgen-dependent organ weights showed effects at lower dose levels in juvenile versus adult animals. Immune parameters affected included TDAR parameters in both age groups, NK activity in juvenile animals and TNF-α production by adherent splenocytes in adult animals. Immune parameters were affected at lower dose levels compared to developmental parameters. Overall, more immune parameters were affected in juvenile animals compared to adult animals and effects were observed at lower dose levels. The results of this study show a relatively higher sensitivity of juvenile versus adult rats. Furthermore, they illustrate the relative sensitivity of the developing immune system in juvenile animals as compared to general toxicity and developmental parameters. This study therefore provides further argumentation for performing dedicated developmental immune toxicity testing as a default in regulatory toxicology. -- Highlights: ► In this study we evaluate the relative sensitivities for DEHP induced effects. ► Results of this study demonstrate the age-dependency of DEHP toxicity. ► Functional immune parameters were more sensitive than structural immune parameters. ► Immune parameters were affected at lower dose levels than developmental parameters. ► Findings demonstrate the susceptibility of the
Assessing robustness of designs for random effects parameters for nonlinear mixed-effects models.
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.
Convergence of surface diffusion parameters with model crystal size
Cohen, Jennifer M.; Voter, Arthur F.
1994-07-01
A study of the variation in the calculated quantities for adatom diffusion with respect to the size of the model crystal is presented. The reported quantities include surface diffusion barrier heights, pre-exponential factors, and dynamical correction factors. Embedded atom method (EAM) potentials were used throughout this effort. Both the layer size and the depth of the crystal were found to influence the values of the Arrhenius factors significantly. In particular, exchange type mechanisms required a significantly larger model than standard hopping mechanisms to determine adatom diffusion barriers of equivalent accuracy. The dynamical events that govern the corrections to transition state theory (TST) did not appear to be as sensitive to crystal depth. Suitable criteria for the convergence of the diffusion parameters with regard to the rate properties are illustrated.
Piecewise Model and Parameter Obtainment of Governor Actuator in Turbine
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Jie Zhao
2015-01-01
Full Text Available The governor actuators in some heat-engine plants have nonlinear valves. This nonlinearity of valves may lead to the inaccuracy of the opening and closing time constants calculated based on the whole segment fully open and fully close experimental test curves of the valve. An improved mathematical model of the turbine governor actuator is proposed to reflect the nonlinearity of the valve, in which the main and auxiliary piecewise opening and closing time constants instead of the fixed oil motive opening and closing time constants are adopted to describe the characteristics of the actuator. The main opening and closing time constants are obtained from the linear segments of the whole fully open and close curves. The parameters of proportional integral derivative (PID controller are identified based on the small disturbance experimental tests of the valve. Then the auxiliary opening and closing time constants and the piecewise opening and closing valve points are determined by the fully open/close experimental tests. Several testing functions are selected to compare genetic algorithm and particle swarm optimization algorithm (GA-PSO with other basic intelligence algorithms. The effectiveness of the piecewise linear model and its parameters are validated by practical power plant case studies.
Standard model parameters and the search for new physics
International Nuclear Information System (INIS)
Marciano, W.J.
1988-04-01
In these lectures, my aim is to present an up-to-date status report on the standard model and some key tests of electroweak unification. Within that context, I also discuss how and where hints of new physics may emerge. To accomplish those goals, I have organized my presentation as follows: I discuss the standard model parameters with particular emphasis on the gauge coupling constants and vector boson masses. Examples of new physics appendages are also briefly commented on. In addition, because these lectures are intended for students and thus somewhat pedagogical, I have included an appendix on dimensional regularization and a simple computational example that employs that technique. Next, I focus on weak charged current phenomenology. Precision tests of the standard model are described and up-to-date values for the Cabibbo-Kobayashi-Maskawa (CKM) mixing matrix parameters are presented. Constraints implied by those tests for a 4th generation, supersymmetry, extra Z/prime/ bosons, and compositeness are also discussed. I discuss weak neutral current phenomenology and the extraction of sin/sup 2/ /theta//sub W/ from experiment. The results presented there are based on a recently completed global analysis of all existing data. I have chosen to concentrate that discussion on radiative corrections, the effect of a heavy top quark mass, and implications for grand unified theories (GUTS). The potential for further experimental progress is also commented on. I depart from the narrowest version of the standard model and discuss effects of neutrino masses and mixings. I have chosen to concentrate on oscillations, the Mikheyev-Smirnov- Wolfenstein (MSW) effect, and electromagnetic properties of neutrinos. On the latter topic, I will describe some recent work on resonant spin-flavor precession. Finally, I conclude with a prospectus on hopes for the future. 76 refs
Spatial extrapolation of light use efficiency model parameters to predict gross primary production
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Karsten Schulz
2011-12-01
Full Text Available To capture the spatial and temporal variability of the gross primary production as a key component of the global carbon cycle, the light use efficiency modeling approach in combination with remote sensing data has shown to be well suited. Typically, the model parameters, such as the maximum light use efficiency, are either set to a universal constant or to land class dependent values stored in look-up tables. In this study, we employ the machine learning technique support vector regression to explicitly relate the model parameters of a light use efficiency model calibrated at several FLUXNET sites to site-specific characteristics obtained by meteorological measurements, ecological estimations and remote sensing data. A feature selection algorithm extracts the relevant site characteristics in a cross-validation, and leads to an individual set of characteristic attributes for each parameter. With this set of attributes, the model parameters can be estimated at sites where a parameter calibration is not possible due to the absence of eddy covariance flux measurement data. This will finally allow a spatially continuous model application. The performance of the spatial extrapolation scheme is evaluated with a cross-validation approach, which shows the methodology to be well suited to recapture the variability of gross primary production across the study sites.
Bacon, D. H.; Keating, E. H.; Viswanathan, H. S.; Dai, Z.
2011-12-01
Accurate prediction of the impact of leaking CO2 on groundwater quality is limited by the complexity of subsurface aquifers and the geochemical reactions that control drinking water compositions. As a result there is a high uncertainty associated with any predictions, hampering monitoring plans, interpretation of the monitoring results, and mitigation plans for a given site. Many physical and geochemical characteristics will dictate a drinking water aquifer's response to a CO2 leak. As a part of the National Risk Assessment Program (NRAP), funded by the U.S. Department of Energy, scientists at Pacific Northwest National Laboratory (PNNL) and Los Alamos National Laboratory (LANL) have collaborated on the development of a 3D heterogeneous model of the Edwards Aquifer in Texas to examine the impacts of CO2 leakage into an unconfined, carbonate aquifer. Using the same base case model, LANL has focused on uncertainty quantification (UQ) of the aquifer's hydraulic properties, whereas PNNL has examined the impact of uncertainty related to geochemical parameters. This abstract describes PNNL's work on geochemical UQ. The uncertainty analysis looks at the impact on several model outputs, including CO2 leakage rate from the water table, mean pH value, and pHdisordered dolomite. We also examine the impact on drinking water quality, specifically TDS, from leakage of brine from the underlying formation, forced upwards by increased pressure due to CO2 injection. To conduct these simulations we use STOMP-CO2-R, which is a multiphase flow simulator, coupled with the reactive transport module ECKEChem, developed at PNNL to simulate CO2 sequestration in deep saline formations and the associated reactions with formation minerals. For uncertainty quantification, we use the PSUADE code. The user defines a range and/or distribution of key input parameters. PSUADE then generates a number of parameter files containing sample points from prescribed sampling method (i.e. Latin hypercube
Sun, Y.; Hou, Z.; Huang, M.; Tian, F.; Leung, L. Ruby
2013-12-01
This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4). Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Both deterministic least-square fitting and stochastic Markov-chain Monte Carlo (MCMC)-Bayesian inversion approaches are evaluated by applying them to CLM4 at selected sites with different climate and soil conditions. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find that using model parameters calibrated by the sampling-based stochastic inversion approaches provides significant improvements in the model simulations compared to using default CLM4 parameter values, and that as more information comes in, the predictive intervals (ranges of posterior distributions) of the calibrated parameters become narrower. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty bounds.
Influence of parameter values on the oscillation sensitivities of two p53-Mdm2 models.
Cuba, Christian E; Valle, Alexander R; Ayala-Charca, Giancarlo; Villota, Elizabeth R; Coronado, Alberto M
2015-09-01
Biomolecular networks that present oscillatory behavior are ubiquitous in nature. While some design principles for robust oscillations have been identified, it is not well understood how these oscillations are affected when the kinetic parameters are constantly changing or are not precisely known, as often occurs in cellular environments. Many models of diverse complexity level, for systems such as circadian rhythms, cell cycle or the p53 network, have been proposed. Here we assess the influence of hundreds of different parameter sets on the sensitivities of two configurations of a well-known oscillatory system, the p53 core network. We show that, for both models and all parameter sets, the parameter related to the p53 positive feedback, i.e. self-promotion, is the only one that presents sizeable sensitivities on extrema, periods and delay. Moreover, varying the parameter set values to change the dynamical characteristics of the response is more restricted in the simple model, whereas the complex model shows greater tunability. These results highlight the importance of the presence of specific network patterns, in addition to the role of parameter values, when we want to characterize oscillatory biochemical systems.
Optimal parameters for the Green-Ampt infiltration model under rainfall conditions
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Chen Li
2015-06-01
Full Text Available The Green-Ampt (GA model is widely used in hydrologic studies as a simple, physically-based method to estimate infiltration processes. The accuracy of the model for applications under rainfall conditions (as opposed to initially ponded situations has not been studied extensively. We compared calculated rainfall infiltration results for various soils obtained using existing GA parameterizations with those obtained by solving the Richards equation for variably saturated flow. Results provided an overview of GA model performance evaluated by means of a root-meansquare- error-based objective function across a large region in GA parameter space as compared to the Richards equation, which showed a need for seeking optimal GA parameters. Subsequent analysis enabled the identification of optimal GA parameters that provided a close fit with the Richards equation. The optimal parameters were found to substantially outperform the standard theoretical parameters, thus improving the utility and accuracy of the GA model for infiltration simulations under rainfall conditions. A sensitivity analyses indicated that the optimal parameters may change for some rainfall scenarios, but are relatively stable for high-intensity rainfall events.
Parameter sensitivity analysis of a 1-D cold region lake model for land-surface schemes
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J.-L. Guerrero
2017-12-01
Full Text Available 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.
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Teresa eLehnert
2015-06-01
Full Text Available Opportunistic fungal pathogens can cause bloodstream infection and severe sepsis upon entering the blood stream of the host. The early immune response in human blood comprises the elimination of pathogens by antimicrobial peptides and innate immune cells, such as neutrophils or monocytes. Mathematical modeling is a predictive method to examine these complex processes and to quantify the dynamics of pathogen-host interactions. Since model parameters are often not directly accessible from experiment, their estimation is required by calibrating model predictions with experimental data. Depending on the complexity of the mathematical model, parameter estimation can be associated with excessively high computational costs in terms of run time and memory. We apply a strategy for reliable parameter estimation where different modeling approaches with increasing complexity are used that build on one another. This bottom-up modeling approach is applied to an experimental human whole-blood infection assay for Candida albicans. Aiming for the quantification of the relative impact of different routes of the immune response against this human-pathogenic fungus, we start from a non-spatial state-based model (SBM, because this level of model complexity allows estimating textit{a priori} unknown transition rates between various system states by the global optimization method simulated annealing. Building on the non-spatial SBM, an agent-based model (ABM is implemented that incorporates the migration of interacting cells in three-dimensional space. The ABM takes advantage of estimated parameters from the non-spatial SBM, leading to a decreased dimensionality of the parameter space. This space can be scanned using a local optimization approach, i.e. least-squares error estimation based on an adaptive regular grid search, to predict cell migration parameters that are not accessible in experiment.
Performance Analysis of Different NeQuick Ionospheric Model Parameters
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WANG Ningbo
2017-04-01
Full Text Available Galileo adopts NeQuick model for single-frequency ionospheric delay corrections. For the standard operation of Galileo, NeQuick model is driven by the effective ionization level parameter Az instead of the solar activity level index, and the three broadcast ionospheric coefficients are determined by a second-polynomial through fitting the Az values estimated from globally distributed Galileo Sensor Stations (GSS. In this study, the processing strategies for the estimation of NeQuick ionospheric coefficients are discussed and the characteristics of the NeQuick coefficients are also analyzed. The accuracy of Global Position System (GPS broadcast Klobuchar, original NeQuick2 and fitted NeQuickC as well as Galileo broadcast NeQuickG models is evaluated over the continental and oceanic regions, respectively, in comparison with the ionospheric total electron content (TEC provided by global ionospheric maps (GIM, GPS test stations and JASON-2 altimeter. The results show that NeQuickG can mitigate ionospheric delay by 54.2%~65.8% on a global scale, and NeQuickC can correct for 71.1%~74.2% of the ionospheric delay. NeQuick2 performs at the same level with NeQuickG, which is a bit better than that of GPS broadcast Klobuchar model.
Exploring parameter constraints on quintessential dark energy: The exponential model
International Nuclear Information System (INIS)
Bozek, Brandon; Abrahamse, Augusta; Albrecht, Andreas; Barnard, Michael
2008-01-01
We present an analysis of a scalar field model of dark energy with an exponential potential using the Dark Energy Task Force (DETF) simulated data models. Using Markov Chain Monte Carlo sampling techniques we examine the ability of each simulated data set to constrain the parameter space of the exponential potential for data sets based on a cosmological constant and a specific exponential scalar field model. We compare our results with the constraining power calculated by the DETF using their 'w 0 -w a ' parametrization of the dark energy. We find that respective increases in constraining power from one stage to the next produced by our analysis give results consistent with DETF results. To further investigate the potential impact of future experiments, we also generate simulated data for an exponential model background cosmology which cannot be distinguished from a cosmological constant at DETF 'Stage 2', and show that for this cosmology good DETF Stage 4 data would exclude a cosmological constant by better than 3σ
Zhang, Hongmei; Wang, Yue; Fatemi, Mostafa; Insana, Michael F.
2017-03-01
Kelvin-Voigt fractional derivative (KVFD) model parameters have been used to describe viscoelastic properties of soft tissues. However, translating model parameters into a concise set of intrinsic mechanical properties related to tissue composition and structure remains challenging. This paper begins by exploring these relationships using a biphasic emulsion materials with known composition. Mechanical properties are measured by analyzing data from two indentation techniques—ramp-stress relaxation and load-unload hysteresis tests. Material composition is predictably correlated with viscoelastic model parameters. Model parameters estimated from the tests reveal that elastic modulus E 0 closely approximates the shear modulus for pure gelatin. Fractional-order parameter α and time constant τ vary monotonically with the volume fraction of the material’s fluid component. α characterizes medium fluidity and the rate of energy dissipation, and τ is a viscous time constant. Numerical simulations suggest that the viscous coefficient η is proportional to the energy lost during quasi-static force-displacement cycles, E A . The slope of E A versus η is determined by α and the applied indentation ramp time T r. Experimental measurements from phantom and ex vivo liver data show close agreement with theoretical predictions of the η -{{E}A} relation. The relative error is less than 20% for emulsions 22% for liver. We find that KVFD model parameters form a concise features space for biphasic medium characterization that described time-varying mechanical properties. The experimental work was carried out at the Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. Methodological development, including numerical simulation and all data analysis, were carried out at the school of Life Science and Technology, Xi’an JiaoTong University, 710049, China.
Quantification of key parameters for treating contrails in a large scale climate model
Energy Technology Data Exchange (ETDEWEB)
Ponater, M.; Gierens, K. [Deutsche Forschungsanstalt fuer Luft- und Raumfahrt e.V. (DLR), Wessling (Germany). Inst. fuer Physik der Atmosphaere
1997-12-01
The general objective of this project, to determine contrail key parameters with respect to their climate effect, has been approached by three tasks: (1) quantification of microphysical key parameters, (2) development of a contrail coverage parametrization for climate models, and (3) determination of the worldwide coverage with persistent contrails due to present day air traffic. The microphysical key parameters are determined using microphysical box model simulations. The contrail parametrization was achieved by deriving (from aircraft measurements) the instantaneous fluctuations of temperature and relative humidity that occur on spatial scales beyond the resolution of climate models. The global and annual mean coverage by persistent contrails was calculated from ECMWF numerical analyses and from actual air traffic density. It was found to be currently about 0.1%, though the atmosphere has the potential to form persistent contrails over a much larger area. (orig.) 144 figs., 42 tabs., 497 refs.
Han, Xiao; Gao, Xiguang; Song, Yingdong
2017-10-01
An approach to identify parameters of interface friction model for Ceramic Matrix composites based on stress-strain response was developed. The stress distribution of fibers in the interface slip region and intact region of the damaged composite was determined by adopting the interface friction model. The relation between maximum strain, secant moduli of hysteresis loop and interface shear stress, interface de-bonding stress was established respectively with the method of symbolic-graphic combination. By comparing the experimental strain, secant moduli of hysteresis loop with computation values, the interface shear stress and interface de-bonding stress corresponding to first cycle were identified. Substituting the identification of parameters into interface friction model, the stress-strain curves were predicted and the predicted results fit experiments well. Besides, the influence of number of data points on identifying the value of interface parameters was discussed. And the approach was compared with the method based on the area of hysteresis loop.
Application of multi-parameter chorus and plasmaspheric hiss wave models in radiation belt modeling
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.
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K. Fujimura
2015-06-01
Full Text Available The storage-discharge relations have been widely used for water resource management and have led to reliable estimation of the impact of climate change on water resources. In a previous study, we carried out a sensitivity analysis of the parameters in a discharge-storage relation in the form of a power function and found that the optimum parameters can be characterized by an exponential function (Fujimura et al., 2014. The aim of this study is to extend the previous study to clarify the properties of the parameters in the storage–discharge relations by carrying out a sensitivity analysis of efficiency using a hydrological model. The study basins are four mountainous basins in Japan with different climates and geologies. The results confirm that the two parameters in the storage–discharge relations can be expressed in an inversely proportional relationship. In addition, we can conveniently assume a practical function for the storage–discharge relations where only one parameter is used on the basis of the new relationship between the two parameters.
EMF 7 model comparisons: key relationships and parameters
Energy Technology Data Exchange (ETDEWEB)
Hickman, B.G.
1983-12-01
A simplified textbook model of aggregate demand and supply interprets the similarities and differences in the price and income responses of the various EMF 7 models to oil and policy shocks. The simplified model is a marriage of Hicks' classic IS-LM formulation of the Keynesian theory of effective demand with a rudimentary model of aggregate supply, combining a structural Phillips curve for wage determination and a markup theory of price determination. The reduced-form income equation from the fix-price IS-LM model is used to define an aggregate demand (AD) locus in P-Y space, showing alternative pairs of the implicit GNP deflator and real GNP which would simultaneously satisfy the saving-investment identity and the condition for money market equilibrium. An aggregate supply (AS) schedule is derived by a similar reduction of relations between output and labor demand, unemployment and wage inflation, and the wage-price-productivity nexus governing markup pricing. Given a particular econometric model it is possible to derive IS and LM curves algebraically. The resulting locuses would show alternative combinations of interest rate and real income which equilibrate real income identity on the IS side and the demand and supply of money on the LM side. By further substitution the reduced form fix-price income relation could be obtained for direct quantification of the AD locus. The AS schedule is obtainable by algebraic reduction of the structural supply side equations.
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H. C. Winsemius
2008-12-01
Full Text Available In this study, land surface related parameter distributions of a conceptual semi-distributed hydrological model are constrained by employing time series of satellite-based evaporation estimates during the dry season as explanatory information. The approach has been applied to the ungauged Luangwa river basin (150 000 (km^{2} in Zambia. The information contained in these evaporation estimates imposes compliance of the model with the largest outgoing water balance term, evaporation, and a spatially and temporally realistic depletion of soil moisture within the dry season. The model results in turn provide a better understanding of the information density of remotely sensed evaporation. Model parameters to which evaporation is sensitive, have been spatially distributed on the basis of dominant land cover characteristics. Consequently, their values were conditioned by means of Monte-Carlo sampling and evaluation on satellite evaporation estimates. The results show that behavioural parameter sets for model units with similar land cover are indeed clustered. The clustering reveals hydrologically meaningful signatures in the parameter response surface: wetland-dominated areas (also called dambos show optimal parameter ranges that reflect vegetation with a relatively small unsaturated zone (due to the shallow rooting depth of the vegetation which is easily moisture stressed. The forested areas and highlands show parameter ranges that indicate a much deeper root zone which is more drought resistent. Clustering was consequently used to formulate fuzzy membership functions that can be used to constrain parameter realizations in further calibration. Unrealistic parameter ranges, found for instance in the high unsaturated soil zone values in the highlands may indicate either overestimation of satellite-based evaporation or model structural deficiencies. We believe that in these areas, groundwater uptake into the root zone and lateral movement of
Relative humidity impact on aerosol parameters in a Paris suburban area
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H. Randriamiarisoa
2006-01-01
Full Text Available Measurements of relative humidity (RH and aerosol parameters (scattering cross section, size distributions and chemical composition, performed in ambient atmospheric conditions, have been used to study the influence of relative humidity on aerosol properties. The data were acquired in a suburban area south of Paris, between 18 and 24 July 2000, in the framework of the 'Etude et Simulation de la Qualité de l'air en Ile-de-France' (ESQUIF program. According to the origin of the air masses arriving over the Paris area, the aerosol hygroscopicity is more or less pronounced. The aerosol chemical composition data were used as input of a thermodynamic model to simulate the variation of the aerosol water mass content with ambient RH and to determine the main inorganic salt compounds. The coupling of observations and modelling reveals the presence of deliquescence processes with hysteresis phenomenon in the hygroscopic growth cycle. Based on the Hänel model, parameterisations of the scattering cross section, the modal radius of the accumulation mode of the size distribution and the aerosol water mass content, as a function of increasing RH, have been assessed. For the first time, a crosscheck of these parameterisations has been performed and shows that the hygroscopic behaviour of the accumulation mode can be coherently characterized by combined optical, size distribution and chemical measurements.
Energy Technology Data Exchange (ETDEWEB)
Turner, D P; Ritts, W D; Wharton, S; Thomas, C; Monson, R; Black, T A
2009-02-26
The combination of satellite remote sensing and carbon cycle models provides an opportunity for regional to global scale monitoring of terrestrial gross primary production, ecosystem respiration, and net ecosystem production. FPAR (the fraction of photosynthetically active radiation absorbed by the plant canopy) is a critical input to diagnostic models, however little is known about the relative effectiveness of FPAR products from different satellite sensors nor about the sensitivity of flux estimates to different parameterization approaches. In this study, we used multiyear observations of carbon flux at four eddy covariance flux tower sites within the conifer biome to evaluate these factors. FPAR products from the MODIS and SeaWiFS sensors, and the effects of single site vs. cross-site parameter optimization were tested with the CFLUX model. The SeaWiFs FPAR product showed greater dynamic range across sites and resulted in slightly reduced flux estimation errors relative to the MODIS product when using cross-site optimization. With site-specific parameter optimization, the flux model was effective in capturing seasonal and interannual variation in the carbon fluxes at these sites. The cross-site prediction errors were lower when using parameters from a cross-site optimization compared to parameter sets from optimization at single sites. These results support the practice of multisite optimization within a biome for parameterization of diagnostic carbon flux models.
Sensitivity Analysis of Input Parameters for a Dynamic Food Chain Model DYNACON
International Nuclear Information System (INIS)
Hwang, Won Tae; Lee, Geun Chang; Han, Moon Hee; Cho, Gyu Seong
2000-01-01
The sensitivity analysis of input parameters for a dynamic food chain model DYNACON was conducted as a function of deposition data for the long-lived radionuclides ( 137 Cs, 90 Sr). Also, the influence of input parameters for the short and long-terms contamination of selected foodstuffs (cereals, leafy vegetables, milk) was investigated. The input parameters were sampled using the LHS technique, and their sensitivity indices represented as PRCC. The sensitivity index was strongly dependent on contamination period as well as deposition data. In case of deposition during the growing stages of plants, the input parameters associated with contamination by foliar absorption were relatively important in long-term contamination as well as short-term contamination. They were also important in short-term contamination in case of deposition during the non-growing stages. In long-term contamination, the influence of input parameters associated with foliar absorption decreased, while the influence of input parameters associated with root uptake increased. These phenomena were more remarkable in case of the deposition of non-growing stages than growing stages, and in case of 90 Sr deposition than 137 Cs deposition. In case of deposition during growing stages of pasture, the input parameters associated with the characteristics of cattle such as feed-milk transfer factor and daily intake rate of cattle were relatively important in contamination of milk
Assessment of parameter regionalization methods for modeling flash floods in China
Ragettli, Silvan; Zhou, Jian; Wang, Haijing
2017-04-01
catchments resulted in good model performance (NSE > 0.5) in 10 and medium performance (NSE > 0.2) in 3 catchments. Optimal model parameters proofed to be relatively insensitive to different HRU configurations. This suggests that dominant controls on hydrologic parameter transfer can potentially be identified based on catchment attributes describing meteorological, geological or landscape characteristics. Parameter regionalization based on a principal component analysis (PCA) nearest neighbor search (using all available catchment attributes) resulted in a 54% success rate in transferring optimal parameter sets and still yielding acceptable model performance. Data from more catchments are required to further increase the parameter transferability success rate or to develop regionalization strategies for individual parameters.
Kahl, Gunnar M; Sidorenko, Yury; Gottesbüren, Bernhard
2015-04-01
As an option for higher-tier leaching assessment of pesticides in Europe according to FOCUS, pesticide properties can be estimated from lysimeter studies by inversely fitting parameter values (substance half-life DT50 and sorption coefficient to organic matter kom ). The aim of the study was to identify adequate methods for inverse modelling. Model parameters for the PEARL (Pesticide Emission Assessment at Regional and Local scales) model were estimated with different inverse optimisation algorithms - the Levenberg-Marquardt (LM), PD_MS2 (PEST Driver Multiple Starting Points 2) and SCEM (Shuffled Complex Evolution Metropolis) algorithms. Optimisation of crop factors and hydraulic properties was found to be an ill-posed problem, and all algorithms failed to identify reliable global minima for the hydrological parameters. All algorithms performed equally well in estimating pesticide sorption and degradation parameters. SCEM was in most cases the only algorithm that reliably calculated uncertainties. The most reliable approach for finding the best parameter set in the stepwise approach of optimising evapotranspiration, soil hydrology and pesticide parameters was to run only SCEM or a combined approach with more than one algorithm using the best fit of each step for further processing. PD_MS2 was well suited to a quick parameter search. The linear parameter uncertainty intervals estimated by LM and PD_MS2 were usually larger than by the non-linear method used by SCEM. With the suggested methods, parameter optimisation, together with reliable estimation of uncertainties, is possible also for relatively complex systems. © 2014 Society of Chemical Industry.
Analysis report for WIPP colloid model constraints and performance assessment parameters
Energy Technology Data Exchange (ETDEWEB)
Mariner, Paul E.; Sassani, David Carl
2014-03-01
An analysis of the Waste Isolation Pilot Plant (WIPP) colloid model constraints and parameter values was performed. The focus of this work was primarily on intrinsic colloids, mineral fragment colloids, and humic substance colloids, with a lesser focus on microbial colloids. Comments by the US Environmental Protection Agency (EPA) concerning intrinsic Th(IV) colloids and Mg-Cl-OH mineral fragment colloids were addressed in detail, assumptions and data used to constrain colloid model calculations were evaluated, and inconsistencies between data and model parameter values were identified. This work resulted in a list of specific conclusions regarding model integrity, model conservatism, and opportunities for improvement related to each of the four colloid types included in the WIPP performance assessment.
The S-parameter in Holographic Technicolor Models
Agashe, Kaustubh; Grojean, Christophe; Reece, Matthew
2007-01-01
We study the S parameter, considering especially its sign, in models of electroweak symmetry breaking (EWSB) in extra dimensions, with fermions localized near the UV brane. Such models are conjectured to be dual to 4D strong dynamics triggering EWSB. The motivation for such a study is that a negative value of S can significantly ameliorate the constraints from electroweak precision data on these models, allowing lower mass scales (TeV or below) for the new particles and leading to easier discovery at the LHC. We first extend an earlier proof of S>0 for EWSB by boundary conditions in arbitrary metric to the case of general kinetic functions for the gauge fields or arbitrary kinetic mixing. We then consider EWSB in the bulk by a Higgs VEV showing that S is positive for arbitrary metric and Higgs profile, assuming that the effects from higher-dimensional operators in the 5D theory are sub-leading and can therefore be neglected. For the specific case of AdS_5 with a power law Higgs profile, we also show that S ~ ...
Extracting Structure Parameters of Dimers for Molecular Tunneling Ionization Model
Zhao, Song-Feng; Huang, Fang; Wang, Guo-Li; Zhou, Xiao-Xin
2016-03-01
We determine structure parameters of the highest occupied molecular orbital (HOMO) of 27 dimers for the molecular tunneling ionization (so called MO-ADK) model of Tong et al. [Phys. Rev. A 66 (2002) 033402]. The molecular wave functions with correct asymptotic behavior are obtained by solving the time-independent Schrödinger equation with B-spline functions and molecular potentials which are numerically created using the density functional theory. We examine the alignment-dependent tunneling ionization probabilities from MO-ADK model for several molecules by comparing with the molecular strong-field approximation (MO-SFA) calculations. We show the molecular Perelomov–Popov–Terent'ev (MO-PPT) can successfully give the laser wavelength dependence of ionization rates (or probabilities). Based on the MO-PPT model, two diatomic molecules having valence orbital with antibonding systems (i.e., Cl2, Ne2) show strong ionization suppression when compared with their corresponding closest companion atoms. Supported by National Natural Science Foundation of China under Grant Nos. 11164025, 11264036, 11465016, 11364038, the Specialized Research Fund for the Doctoral Program of Higher Education of China under Grant No. 20116203120001, and the Basic Scientific Research Foundation for Institution of Higher Learning of Gansu Province
Coupled 1D-2D hydrodynamic inundation model for sewer overflow: Influence of modeling parameters
Directory of Open Access Journals (Sweden)
Adeniyi Ganiyu Adeogun
2015-10-01
Full Text Available This paper presents outcome of our investigation on the influence of modeling parameters on 1D-2D hydrodynamic inundation model for sewer overflow, developed through coupling of an existing 1D sewer network model (SWMM and 2D inundation model (BREZO. The 1D-2D hydrodynamic model was developed for the purpose of examining flood incidence due to surcharged water on overland surface. The investigation was carried out by performing sensitivity analysis on the developed model. For the sensitivity analysis, modeling parameters, such as mesh resolution Digital Elevation Model (DEM resolution and roughness were considered. The outcome of the study shows the model is sensitive to changes in these parameters. The performance of the model is significantly influenced, by the Manning's friction value, the DEM resolution and the area of the triangular mesh. Also, changes in the aforementioned modeling parameters influence the Flood characteristics, such as the inundation extent, the flow depth and the velocity across the model domain.
Directory of Open Access Journals (Sweden)
Lezhnin Sergey
2017-01-01
Full Text Available The two-temperature model of the outflow from a vessel with initial supercritical parameters of medium has been realized. The model uses thermodynamic non-equilibrium relaxation approach to describe phase transitions. Based on a new asymptotic model for computing the relaxation time, the outflow of water with supercritical initial pressure and super- and subcritical temperatures has been calculated.
Artificial Neural Network model for the determination of GSM Rxlevel from atmospheric parameters
Directory of Open Access Journals (Sweden)
Julia Ofure Eichie
2017-04-01
Full Text Available Accurate received signal level (Rxlevel values are useful for mobile telecommunication network planning. Rxlevel is affected by the dynamics of the atmosphere through which it propagates. Adequate knowledge of the prevailing atmospheric conditions in an environment is essential for proper network planning. However most of the existing GSM received signal determination model are function of distance between point of signal reception and transmitting site thus necessitating the development of a model that involve the use of atmospheric parameters in the determination of received GSM signal level. In this paper, a three stage approach was used in the development of the model using some atmospheric parameters such as atmospheric temperature, relative humidity and dew point. The selected and easily measurable atmospheric parameters were used as input parameters in developing two new models for computing the Rxlevel of GSM signal using a three-step approach. Data acquisition and pre-processing serves as the first stage and formulation of ANN design and the development of parametric model for the Rxlevel using ANN synaptic weights form the second stage of the proposed approach. The third stage involves the use of ANN weight and bias values, and network architecture in the development of the model equation. In evaluating the performance of the proposed models, network parameters were varied and the results obtained using mean squared error (MSE as performance measure showed the developed model with 33 neurons in the hidden layer and tansig activation, function in both the hidden and output layers as the optimal model with least MSE value of 0.056. Thus showing that the developed model has an acceptable accuracy value as demonstrated from comparison of results with actual measured values.
Directory of Open Access Journals (Sweden)
Hongshan Zhao
2012-05-01
Full Text Available Short-term solar irradiance forecasting (STSIF is of great significance for the optimal operation and power predication of grid-connected photovoltaic (PV plants. However, STSIF is very complex to handle due to the random and nonlinear characteristics of solar irradiance under changeable weather conditions. Artificial Neural Network (ANN is suitable for STSIF modeling and many research works on this topic are presented, but the conciseness and robustness of the existing models still need to be improved. After discussing the relation between weather variations and irradiance, the characteristics of the statistical feature parameters of irradiance under different weather conditions are figured out. A novel ANN model using statistical feature parameters (ANN-SFP for STSIF is proposed in this paper. The input vector is reconstructed with several statistical feature parameters of irradiance and ambient temperature. Thus sufficient information can be effectively extracted from relatively few inputs and the model complexity is reduced. The model structure is determined by cross-validation (CV, and the Levenberg-Marquardt algorithm (LMA is used for the network training. Simulations are carried out to validate and compare the proposed model with the conventional ANN model using historical data series (ANN-HDS, and the results indicated that the forecast accuracy is obviously improved under variable weather conditions.
Kinematic parameter calibration method for industrial robot manipulator using the relative position
Energy Technology Data Exchange (ETDEWEB)
Ha, In Chul [Samsung Heavy Industries Co., Daejeon (Korea, Republic of)
2008-06-15
A new calibration method for industrial robot system calibration on a manufacturing floor is presented in this paper. To calibrate the robot system, a laser sensor to measure the distance between robot tool and measurement surface is attached to the robot end-effector and a grid is established in the floor. Given two position command pulses for a robot manipulator and using the position difference between two command pulses, the relative position measurement calibration method will find the real robot kinematic parameters. The procedures developed have been applied to an industrial robot. Finally, the effects of the models used to calibrate the robot are discussed. This calibration method represents an effective, low cost and feasible technique for the industrial robot calibration in lab. projects and industrial environments
Kinematic parameter calibration method for industrial robot manipulator using the relative position
International Nuclear Information System (INIS)
Ha, In Chul
2008-01-01
A new calibration method for industrial robot system calibration on a manufacturing floor is presented in this paper. To calibrate the robot system, a laser sensor to measure the distance between robot tool and measurement surface is attached to the robot end-effector and a grid is established in the floor. Given two position command pulses for a robot manipulator and using the position difference between two command pulses, the relative position measurement calibration method will find the real robot kinematic parameters. The procedures developed have been applied to an industrial robot. Finally, the effects of the models used to calibrate the robot are discussed. This calibration method represents an effective, low cost and feasible technique for the industrial robot calibration in lab. projects and industrial environments
Achleitner, S; Rinderer, M; Kirnbauer, R
2009-01-01
For the Tyrolean part of the river Inn, a hybrid model for flood forecast has been set up and is currently in its test phase. The system is a hybrid system which comprises of a hydraulic 1D model for the river Inn, and the hydrological models HQsim (Rainfall-runoff-discharge model) and the snow and ice melt model SES for modeling the rainfall runoff form non-glaciated and glaciated tributary catchment respectively. Within this paper the focus is put on the hydrological modeling of the totally 49 connected non-glaciated catchments realized with the software HQsim. In the course of model calibration, the identification of the most sensitive parameters is important aiming at an efficient calibration procedure. The indicators used for explaining the parameter sensitivities were chosen specifically for the purpose of flood forecasting. Finally five model parameters could be identified as being sensitive for model calibration when aiming for a well calibrated model for flood conditions. In addition two parameters were identified which are sensitive in situations where the snow line plays an important role.
A new method for determination of parameters in sewer pollutant transformation process model.
Jiang, F; Leung, H W D; Li, S Y; Lin, G S; Chen, G H
2007-11-01
Understanding pollutant transformation in sewers is important in controlling odor emission from pressure mains as well as in assessing organic pollutant removal capacity of gravity sewers. Sewer process models have thus been developed to quantify the pollutant transformation processes under various sewer conditions. The quantification largely depends on model parameter values, in particular the kinetic and stoichiometric parameters related to microbial activities. The current approaches not only involve a large amount of experimental work but also may induce significant errors when microbial reactions cannot be differentiated effectively during the experiments. Therefore, this study is aimed at developing a new method that can reduce experimental work significantly. The proposed method utilizes a genetic algorithm (GA) to enable the determination with a single set of batch experiments. To study the feasibility of the proposed method, a set of 72-hr batch experiments was first conducted for determining the parameters of a sewer model developed in this study, which adopted a full version of the International Water Association (IWA) Activated Sludge Model No. 3 (ASM3) to describe the microbial activities in sewers. The results were then verified with two different sets of the batch experiments. Furthermore, dynamic variation data of dissolved oxygen level were collected at the outlet of a 1.5-km gravity sewer to validate the determined parameters. All the results showed that the proposed parameter determination method is effective.
Directory of Open Access Journals (Sweden)
Zhiqiang GENG
2014-01-01
Full Text Available Output noise is strongly related to input in closed-loop control system, which makes model identification of closed-loop difficult, even unidentified in practice. The forward channel model is chosen to isolate disturbance from the output noise to input, and identified by optimization the dynamic characteristics of the process based on closed-loop operation data. The characteristics parameters of the process, such as dead time and time constant, are calculated and estimated based on the PI/PID controller parameters and closed-loop process input/output data. And those characteristics parameters are adopted to define the search space of the optimization identification algorithm. PSO-SQP optimization algorithm is applied to integrate the global search ability of PSO with the local search ability of SQP to identify the model parameters of forward channel. The validity of proposed method has been verified by the simulation. The practicability is checked with the PI/PID controller parameter turning based on identified forward channel model.
A Note on the Relation between Factor Analytic and Item Response Theory Models
Kamata, Akihito; Bauer, Daniel J.
2008-01-01
The relations among several alternative parameterizations of the binary factor analysis model and the 2-parameter item response theory model are discussed. It is pointed out that different parameterizations of factor analysis model parameters can be transformed into item response model theory parameters, and general formulas are provided.…
THE NATURE OF THE SECOND PARAMETER IN THE IRX-β RELATION FOR LOCAL GALAXIES
International Nuclear Information System (INIS)
Grasha, Kathryn; Calzetti, Daniela; Andrews, Jennifer E.; Lee, Janice C.; Dale, Daniel A.
2013-01-01
We present an analysis of 98 galaxies of low-dust content, selected from the Spitzer Local Volume Legacy survey, aimed at examining the relation between the ultraviolet (UV) color and dust attenuation in normal star-forming galaxies. The IRX-β diagram relates the total dust attenuation in a galaxy, traced by the far-IR (FIR) to UV ratio, to the observed UV color, indicated by β. Previous research has indicated that while starburst galaxies exhibit a relatively tight IRX-β relation, normal star-forming galaxies do not, and have a much larger spread in the total-IR to far-UV (FUV) luminosity for a fixed UV color. We examine the role that the age of the stellar population plays as the ''second parameter'' responsible for the observed deviation and spread of star-forming galaxies from the starburst relation. We model the FUV to FIR spectral energy distribution of each galaxy according to two broad bins of star formation history (SFH): constant and instantaneous burst. We find clear trends between stellar population mean age estimators (extinction-corrected FUV/NIR, U – B, and EW(Hα)) and the UV color β; the trends are mostly driven by the galaxies best-described by instantaneous burst populations. We also find a significant correlation between β and the mean age directly determined from the best-fit instantaneous models. As already indicated by other authors, the UV attenuation in star-forming galaxies may not be recovered with the UV color alone and is highly influenced by the stellar population's mean age and SFH. Overall, the scatter in the IRX-β diagram is better correlated with β than with the perpendicular distance, d p
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
Testing for parameter instability across different modeling frameworks
Calvori, Francesco; Creal, Drew; Koopman, Siem Jan; Lucas, André
2017-01-01
We develop a new parameter instability test that generalizes the seminal ARCHLagrange Multiplier test of Engle (1982) for a constant variance against the alternative of autoregressive conditional heteroskedasticity to settings with nonlinear timevarying parameters and non-Gaussian distributions. We
Relating drilling parameters at the bit-rock interface: theoretical and field studies
Energy Technology Data Exchange (ETDEWEB)
Sinkala, T. (Luleaa University of Technology, Luleaa (Sweden). Division of Mining Equipment Engineering)
1991-01-01
An explicit expression relating drilling parameters at the bit-rock contact is derived. The expression estimates the minimum torque, related to bit-rock contact only, required to maintain constant bit rotation. Theoretical results from the developed bit-rock contact relation agree very satisfactorily with those obtained from field tests and other previous experience. 15 refs., 8 figs., 2 tabs.
Statistical osteoporosis models using composite finite elements: a parameter study.
Wolfram, Uwe; Schwen, Lars Ole; Simon, Ulrich; Rumpf, Martin; Wilke, Hans-Joachim
2009-09-18
Osteoporosis is a widely spread disease with severe consequences for patients and high costs for health care systems. The disease is characterised by a loss of bone mass which induces a loss of mechanical performance and structural integrity. It was found that transverse trabeculae are thinned and perforated while vertical trabeculae stay intact. For understanding these phenomena and the mechanisms leading to fractures of trabecular bone due to osteoporosis, numerous researchers employ micro-finite element models. To avoid disadvantages in setting up classical finite element models, composite finite elements (CFE) can be used. The aim of the study is to test the potential of CFE. For that, a parameter study on numerical lattice samples with statistically simulated, simplified osteoporosis is performed. These samples are subjected to compression and shear loading. Results show that the biggest drop of compressive stiffness is reached for transverse isotropic structures losing 32% of the trabeculae (minus 89.8% stiffness). The biggest drop in shear stiffness is found for an isotropic structure also losing 32% of the trabeculae (minus 67.3% stiffness). The study indicates that losing trabeculae leads to a worse drop of macroscopic stiffness than thinning of trabeculae. The results further demonstrate the advantages of CFEs for simulating micro-structured samples.
SAC-SMA a priori parameter differences and their impact on distributed hydrologic model simulations
Zhang, Ziya; Koren, Victor; Reed, Seann; Smith, Michael; Zhang, Yu; Moreda, Fekadu; Cosgrove, Brian
2012-02-01
SummaryDeriving a priori gridded parameters is an important step in the development and deployment of an operational distributed hydrologic model. Accurate a priori parameters can reduce the manual calibration effort and/or speed up the automatic calibration process, reduce calibration uncertainty, and provide valuable information at ungauged locations. Underpinned by reasonable parameter data sets, distributed hydrologic modeling can help improve water resource and flood and flash flood forecasting capabilities. Initial efforts at the National Weather Service Office of Hydrologic Development (NWS OHD) to derive a priori gridded Sacramento Soil Moisture Accounting (SAC-SMA) model parameters for the conterminous United States (CONUS) were based on a relatively coarse resolution soils property database, the State Soil Geographic Database (STATSGO) (Soil Survey Staff, 2011) and on the assumption of uniform land use and land cover. In an effort to improve the parameters, subsequent work was performed to fully incorporate spatially variable land cover information into the parameter derivation process. Following that, finer-scale soils data (the county-level Soil Survey Geographic Database (SSURGO) ( Soil Survey Staff, 2011a,b), together with the use of variable land cover data, were used to derive a third set of CONUS, a priori gridded parameters. It is anticipated that the second and third parameter sets, which incorporate more physical data, will be more realistic and consistent. Here, we evaluate whether this is actually the case by intercomparing these three sets of a priori parameters along with their associated hydrologic simulations which were generated by applying the National Weather Service Hydrology Laboratory's Research Distributed Hydrologic Model (HL-RDHM) ( Koren et al., 2004) in a continuous fashion with an hourly time step. This model adopts a well-tested conceptual water balance model, SAC-SMA, applied on a regular spatial grid, and links to physically
Directory of Open Access Journals (Sweden)
W. Castaings
2009-04-01
Full Text Available Variational methods are widely used for the analysis and control of computationally intensive spatially distributed systems. In particular, the adjoint state method enables a very efficient calculation of the derivatives of an objective function (response function to be analysed or cost function to be optimised with respect to model inputs.
In this contribution, it is shown that the potential of variational methods for distributed catchment scale hydrology should be considered. A distributed flash flood model, coupling kinematic wave overland flow and Green Ampt infiltration, is applied to a small catchment of the Thoré basin and used as a relatively simple (synthetic observations but didactic application case.
It is shown that forward and adjoint sensitivity analysis provide a local but extensive insight on the relation between the assigned model parameters and the simulated hydrological response. Spatially distributed parameter sensitivities can be obtained for a very modest calculation effort (~6 times the computing time of a single model run and the singular value decomposition (SVD of the Jacobian matrix provides an interesting perspective for the analysis of the rainfall-runoff relation.
For the estimation of model parameters, adjoint-based derivatives were found exceedingly efficient in driving a bound-constrained quasi-Newton algorithm. The reference parameter set is retrieved independently from the optimization initial condition when the very common dimension reduction strategy (i.e. scalar multipliers is adopted.
Furthermore, the sensitivity analysis results suggest that most of the variability in this high-dimensional parameter space can be captured with a few orthogonal directions. A parametrization based on the SVD leading singular vectors was found very promising but should be combined with another regularization strategy in order to prevent overfitting.
Vijaya Ramnath, B.; Sharavanan, S.; Jeykrishnan, J.
2017-03-01
Nowadays quality plays a vital role in all the products. Hence, the development in manufacturing process focuses on the fabrication of composite with high dimensional accuracy and also incurring low manufacturing cost. In this work, an investigation on machining parameters has been performed on jute-flax hybrid composite. Here, the two important responses characteristics like surface roughness and material removal rate are optimized by employing 3 machining input parameters. The input variables considered are drill bit diameter, spindle speed and feed rate. Machining is done on CNC vertical drilling machine at different levels of drilling parameters. Taguchi’s L16 orthogonal array is used for optimizing individual tool parameters. Analysis Of Variance is used to find the significance of individual parameters. The simultaneous optimization of the process parameters is done by grey relational analysis. The results of this investigation shows that, spindle speed and drill bit diameter have most effect on material removal rate and surface roughness followed by feed rate.
Ye, Long
2018-02-02
Although it is known that molecular interactions govern morphology formation and purity of mixed domains of conjugated polymer donors and small-molecule acceptors, and thus largely control the achievable performance of organic solar cells, quantifying interaction-function relations has remained elusive. Here, we first determine the temperature-dependent effective amorphous-amorphous interaction parameter, χaa(T), by mapping out the phase diagram of a model amorphous polymer:fullerene material system. We then establish a quantitative \\'constant-kink-saturation\\' relation between χaa and the fill factor in organic solar cells that is verified in detail in a model system and delineated across numerous high- and low-performing materials systems, including fullerene and non-fullerene acceptors. Our experimental and computational data reveal that a high fill factor is obtained only when χaa is large enough to lead to strong phase separation. Our work outlines a basis for using various miscibility tests and future simulation methods that will significantly reduce or eliminate trial-and-error approaches to material synthesis and device fabrication of functional semiconducting blends and organic blends in general.
Pan, Hongsheng; Liu, Bing; Lu, Yanhui; Desneux, Nicolas
2014-01-01
The genus Adelphocoris (Hemiptera: Miridae) is a group of important insect pests of Bt cotton in China. The three dominant species are A. lineolatus, A. suturalis, and A. fasciaticollis, and these species have different population dynamics. The causal factors for the differences in population dynamics have not been determined; one hypothesis is that humidity may be important for the growth of Adelphocoris populations. In the laboratory, the demographic parameters of the three Adelphocoris species were compared when the mirid bugs were subjected to various levels of relative humidity (40, 50, 60, 70 and 80% RH). Middle to high levels of RH (60, 70 and 80%) were associated with higher egg and nymph survival rates and increased adult longevity and female fecundity. Lower humidity levels (40 and 50% RH) had negative effects on the survival of nymphs, adult longevity and fecundity. The intrinsic rate of increase (rm), the net reproductive rate (R0) and the finite rate of increase (λ) for each Adelphocoris species increased with increasing RH. Significant positive relationships were found between RH and the life table parameters, rm, R0 and λ for the three Adelphocoris species. These results will help to better understand the phenology of the three Adelphocoris species, and the information can be used in population growth models to optimize pest forecasting and management strategies for these key pests.
Directory of Open Access Journals (Sweden)
Hongsheng Pan
Full Text Available The genus Adelphocoris (Hemiptera: Miridae is a group of important insect pests of Bt cotton in China. The three dominant species are A. lineolatus, A. suturalis, and A. fasciaticollis, and these species have different population dynamics. The causal factors for the differences in population dynamics have not been determined; one hypothesis is that humidity may be important for the growth of Adelphocoris populations. In the laboratory, the demographic parameters of the three Adelphocoris species were compared when the mirid bugs were subjected to various levels of relative humidity (40, 50, 60, 70 and 80% RH. Middle to high levels of RH (60, 70 and 80% were associated with higher egg and nymph survival rates and increased adult longevity and female fecundity. Lower humidity levels (40 and 50% RH had negative effects on the survival of nymphs, adult longevity and fecundity. The intrinsic rate of increase (rm, the net reproductive rate (R0 and the finite rate of increase (λ for each Adelphocoris species increased with increasing RH. Significant positive relationships were found between RH and the life table parameters, rm, R0 and λ for the three Adelphocoris species. These results will help to better understand the phenology of the three Adelphocoris species, and the information can be used in population growth models to optimize pest forecasting and management strategies for these key pests.
Assigning probability distributions to input parameters of performance assessment models
International Nuclear Information System (INIS)
Mishra, Srikanta
2002-02-01
This study presents an overview of various approaches for assigning probability distributions to input parameters and/or future states of performance assessment models. Specifically,three broad approaches are discussed for developing input distributions: (a) fitting continuous distributions to data, (b) subjective assessment of probabilities, and (c) Bayesian updating of prior knowledge based on new information. The report begins with a summary of the nature of data and distributions, followed by a discussion of several common theoretical parametric models for characterizing distributions. Next, various techniques are presented for fitting continuous distributions to data. These include probability plotting, method of moments, maximum likelihood estimation and nonlinear least squares analysis. The techniques are demonstrated using data from a recent performance assessment study for the Yucca Mountain project. Goodness of fit techniques are also discussed, followed by an overview of how distribution fitting is accomplished in commercial software packages. The issue of subjective assessment of probabilities is dealt with in terms of the maximum entropy distribution selection approach, as well as some common rules for codifying informal expert judgment. Formal expert elicitation protocols are discussed next, and are based primarily on the guidance provided by the US NRC. The Bayesian framework for updating prior distributions (beliefs) when new information becomes available is discussed. A simple numerical approach is presented for facilitating practical applications of the Bayes theorem. Finally, a systematic framework for assigning distributions is presented: (a) for the situation where enough data are available to define an empirical CDF or fit a parametric model to the data, and (b) to deal with the situation where only a limited amount of information is available
Assigning probability distributions to input parameters of performance assessment models
Energy Technology Data Exchange (ETDEWEB)
Mishra, Srikanta [INTERA Inc., Austin, TX (United States)
2002-02-01
This study presents an overview of various approaches for assigning probability distributions to input parameters and/or future states of performance assessment models. Specifically,three broad approaches are discussed for developing input distributions: (a) fitting continuous distributions to data, (b) subjective assessment of probabilities, and (c) Bayesian updating of prior knowledge based on new information. The report begins with a summary of the nature of data and distributions, followed by a discussion of several common theoretical parametric models for characterizing distributions. Next, various techniques are presented for fitting continuous distributions to data. These include probability plotting, method of moments, maximum likelihood estimation and nonlinear least squares analysis. The techniques are demonstrated using data from a recent performance assessment study for the Yucca Mountain project. Goodness of fit techniques are also discussed, followed by an overview of how distribution fitting is accomplished in commercial software packages. The issue of subjective assessment of probabilities is dealt with in terms of the maximum entropy distribution selection approach, as well as some common rules for codifying informal expert judgment. Formal expert elicitation protocols are discussed next, and are based primarily on the guidance provided by the US NRC. The Bayesian framework for updating prior distributions (beliefs) when new information becomes available is discussed. A simple numerical approach is presented for facilitating practical applications of the Bayes theorem. Finally, a systematic framework for assigning distributions is presented: (a) for the situation where enough data are available to define an empirical CDF or fit a parametric model to the data, and (b) to deal with the situation where only a limited amount of information is available.
MATHEMATICAL MODELING OF FLOW PARAMETERS FOR SINGLE WIND TURBINE
Directory of Open Access Journals (Sweden)
2016-01-01
Full Text Available It is known that on the territory of the Russian Federation the construction of several large wind farms is planned. The tasks connected with design and efficiency evaluation of wind farm work are in demand today. One of the possible directions in design is connected with mathematical modeling. The method of large eddy simulation developed within the direction of computational hydrodynamics allows to reproduce unsteady structure of the flow in details and to determine various integrated values. The calculation of work for single wind turbine installation by means of large eddy simulation and Actuator Line Method along the turbine blade is given in this work. For problem definition the numerical method in the form of a box was considered and the adapted unstructured grid was used.The mathematical model included the main equations of continuity and momentum equations for incompressible fluid. The large-scale vortex structures were calculated by means of integration of the filtered equations. The calculation was carried out with Smagorinsky model for determination of subgrid scale turbulent viscosity. The geometrical parametersof wind turbine were set proceeding from open sources in the Internet.All physical values were defined at center of computational cell. The approximation of items in equations was ex- ecuted with the second order of accuracy for time and space. The equations for coupling velocity and pressure were solved by means of iterative algorithm PIMPLE. The total quantity of the calculated physical values on each time step was equal to 18. So, the resources of a high performance cluster were required.As a result of flow calculation in wake for the three-bladed turbine average and instantaneous values of velocity, pressure, subgrid kinetic energy and turbulent viscosity, components of subgrid stress tensor were worked out. The re- ceived results matched the known results of experiments and numerical simulation, testify the opportunity
Relation of Certain Quantum Chemical Parameters to Lubrication Behavior of Solid Oxides
Directory of Open Access Journals (Sweden)
Yuansheng Jin
2005-08-01
Full Text Available Abstract: It is well-documented that certain oxides (such as Re2O7, B2O3, MoO3, V2O5, etc. can provide friction coefficients of 0.1-0.3 to sliding surfaces at elevated temperatures and thus they are often referred to as lubricious oxides in the tribology literature. In a recently proposed crystal chemical model, Erdemir was able to establish a close correlation between the reported friction coefficients of such oxides and their ionic potentials [1]. In the present paper, we expand on this original concept and explore the relevance of two other quantum chemical parameters, electronegativity and chemical hardness, to the lubricity of solid oxides. These parameters have already been used by scientists to explain the nature of tribochemical interactions between various oil additives and sliding surfaces. It is conceivable that electronegativity and chemical hardness may also be strongly related to the extent of adhesive interactions and shear rheology of solid oxides and hence to their lubricity. The new results have confirmed that electronegativity, like ionic potential, is indeed a valid quantum chemistry parameter that can be used in predicting the lubrication behavior of solid oxides. Generally, the higher the electronegativity of the solid oxides is, the lower the friction coefficients will be. However, chemical hardness did not yield a similar trend. In light of these new findings, we propose some guidelines for the formulation of novel oxide or alloy systems that can lead to the formation of lubricious oxides at elevated temperatures. The findings of this study may pave the way for designer-based tribosystems in general and smart tribochemical systems in particular in future tribological applications such as dry machining.
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
Distribution-centric 3-parameter thermodynamic models of partition gas chromatography.
Blumberg, Leonid M
2017-03-31
If both parameters (the entropy, ΔS, and the enthalpy, ΔH) of the classic van't Hoff model of dependence of distribution coefficients (K) of analytes on temperature (T) are treated as the temperature-independent constants then the accuracy of the model is known to be insufficient for the needed accuracy of retention time prediction. A more accurate 3-parameter Clarke-Glew model offers a way to treat ΔS and ΔH as functions, ΔS(T) and ΔH(T), of T. A known T-centric construction of these functions is based on relating them to the reference values (ΔS ref and ΔH ref ) corresponding to a predetermined reference temperature (T ref ). Choosing a single T ref for all analytes in a complex sample or in a large database might lead to practically irrelevant values of ΔS ref and ΔH ref for those analytes that have too small or too large retention factors at T ref . Breaking all analytes in several subsets each with its own T ref leads to discontinuities in the analyte parameters. These problems are avoided in the K-centric modeling where ΔS(T) and ΔS(T) and other analyte parameters are described in relation to their values corresponding to a predetermined reference distribution coefficient (K Ref ) - the same for all analytes. In this report, the mathematics of the K-centric modeling are described and the properties of several types of K-centric parameters are discussed. It has been shown that the earlier introduced characteristic parameters of the analyte-column interaction (the characteristic temperature, T char , and the characteristic thermal constant, θ char ) are a special chromatographically convenient case of the K-centric parameters. Transformations of T-centric parameters into K-centric ones and vice-versa as well as the transformations of one set of K-centric parameters into another set and vice-versa are described. Copyright © 2017 Elsevier B.V. All rights reserved.
mr. A C++ library for the matching and running of the Standard Model parameters
International Nuclear Information System (INIS)
Kniehl, Bernd A.; Veretin, Oleg L.; Pikelner, Andrey F.; Joint Institute for Nuclear Research, Dubna
2016-01-01
We present the C++ program library mr that allows us to reliably calculate the values of the running parameters in the Standard Model at high energy scales. The initial conditions are obtained by relating the running parameters in the MS renormalization scheme to observables at lower energies with full two-loop precision. The evolution is then performed in accordance with the renormalization group equations with full three-loop precision. Pure QCD corrections to the matching and running are included through four loops. We also provide a Mathematica interface for this program library.
Estimation of the Malthusian parameter in an stochastic epidemic model using martingale methods.
Lindenstrand, David; Svensson, Åke
2013-12-01
Data, on the number of infected, gathered from a large epidemic outbreak can be used to estimate parameters related to the strength and speed of the spread. The Malthusian parameter, which determines the initial growth rate of the epidemic is often of crucial interest. Using a simple epidemic SEIR model with known generation time distribution, we define and analyze an estimate, based on martingale methods. We derive asymptotic properties of the estimate and compare them to the results from simulations of the epidemic. The estimate uses all the information contained in the epidemic curve, in contrast to estimates which only use data from the start of the outbreak.
Schelling's Segregation Model: Parameters, scaling, and aggregation
Directory of Open Access Journals (Sweden)
Abhinav Singh
2009-09-01
Full Text Available Thomas Schelling proposed a simple spatial model to illustrate how, even with relatively mild assumptions on each individual's nearest neighbor preferences, an integrated city would likely unravel to a segregated city, even if all individuals prefer integration. This agent based lattice model has become quite influential amongst social scientists, demographers, and economists. Aggregation relates to individuals coming together to form groups and Schelling equated global aggregation with segregation. Many authors assumed that the segregation which Schelling observed in simulations on very small cities persists for larger, realistic size cities. We describe how different measures could be used to quantify the segregation and unlock its dependence on city size, disparate neighbor comfortability threshold, and population density. We identify distinct scales of global aggregation, and show that the striking global aggregation Schelling observed is strictly a small city phenomenon. We also discover several scaling laws for the aggregation measures. Along the way we prove that as the Schelling model evolves, the total perimeter of the interface between the different agents decreases, which provides a useful analytical tool to study the evolution.
Modelling pesticide leaching under climate change: parameter vs. climate input uncertainty
Directory of Open Access Journals (Sweden)
K. Steffens
2014-02-01
Full Text Available Assessing climate change impacts on pesticide leaching requires careful consideration of different sources of uncertainty. We investigated the uncertainty related to climate scenario input and its importance relative to parameter uncertainty of the pesticide leaching model. The pesticide fate model MACRO was calibrated against a comprehensive one-year field data set for a well-structured clay soil in south-western Sweden. We obtained an ensemble of 56 acceptable parameter sets that represented the parameter uncertainty. Nine different climate model projections of the regional climate model RCA3 were available as driven by different combinations of global climate models (GCM, greenhouse gas emission scenarios and initial states of the GCM. The future time series of weather data used to drive the MACRO model were generated by scaling a reference climate data set (1970–1999 for an important agricultural production area in south-western Sweden based on monthly change factors for 2070–2099. 30 yr simulations were performed for different combinations of pesticide properties and application seasons. Our analysis showed that both the magnitude and the direction of predicted change in pesticide leaching from present to future depended strongly on the particular climate scenario. The effect of parameter uncertainty was of major importance for simulating absolute pesticide losses, whereas the climate uncertainty was relatively more important for predictions of changes of pesticide losses from present to future. The climate uncertainty should be accounted for by applying an ensemble of different climate scenarios. The aggregated ensemble prediction based on both acceptable parameterizations and different climate scenarios has the potential to provide robust probabilistic estimates of future pesticide losses.
Elastic-plastic analysis of AS4/PEEK composite laminate using a one-parameter plasticity model
Sun, C. T.; Yoon, K. J.
1992-01-01
A one-parameter plasticity model was shown to adequately describe the plastic deformation of AS4/PEEK (APC-2) unidirectional thermoplastic composite. This model was verified further for unidirectional and laminated composite panels with and without a hole. The elastic-plastic stress-strain relations of coupon specimens were measured and compared with those predicted by the finite element analysis using the one-parameter plasticity model. The results show that the one-parameter plasticity model is suitable for the analysis of elastic-plastic deformation of AS4/PEEK composite laminates.
House thermal model parameter estimation method for Model Predictive Control applications
van Leeuwen, Richard Pieter; de Wit, J.B.; Fink, J.; Smit, Gerardus Johannes Maria
In this paper we investigate thermal network models with different model orders applied to various Dutch low-energy house types with high and low interior thermal mass and containing floor heating. Parameter estimations are performed by using data from TRNSYS simulations. The paper discusses results
Model-Based Material Parameter Estimation for Terahertz Reflection Spectroscopy
Kniffin, Gabriel Paul
Many materials such as drugs and explosives have characteristic spectral signatures in the terahertz (THz) band. These unique signatures imply great promise for spectral detection and classification using THz radiation. While such spectral features are most easily observed in transmission, real-life imaging systems will need to identify materials of interest from reflection measurements, often in non-ideal geometries. One important, yet commonly overlooked source of signal corruption is the etalon effect -- interference phenomena caused by multiple reflections from dielectric layers of packaging and clothing likely to be concealing materials of interest in real-life scenarios. This thesis focuses on the development and implementation of a model-based material parameter estimation technique, primarily for use in reflection spectroscopy, that takes the influence of the etalon effect into account. The technique is adapted from techniques developed for transmission spectroscopy of thin samples and is demonstrated using measured data taken at the Northwest Electromagnetic Research Laboratory (NEAR-Lab) at Portland State University. Further tests are conducted, demonstrating the technique's robustness against measurement noise and common sources of error.
Geomagnetically induced currents in Uruguay: Sensitivity to modelling parameters
Caraballo, R.
2016-11-01
According to the traditional wisdom, geomagnetically induced currents (GIC) should occur rarely at mid-to-low latitudes, but in the last decades a growing number of reports have addressed their effects on high-voltage (HV) power grids at mid-to-low latitudes. The growing trend to interconnect national power grids to meet regional integration objectives, may lead to an increase in the size of the present energy transmission networks to form a sort of super-grid at continental scale. Such a broad and heterogeneous super-grid can be exposed to the effects of large GIC if appropriate mitigation actions are not taken into consideration. In the present study, we present GIC estimates for the Uruguayan HV power grid during severe magnetic storm conditions. The GIC intensities are strongly dependent on the rate of variation of the geomagnetic field, conductivity of the ground, power grid resistances and configuration. Calculated GIC are analysed as functions of these parameters. The results show a reasonable agreement with measured data in Brazil and Argentina, thus confirming the reliability of the model. The expansion of the grid leads to a strong increase in GIC intensities in almost all substations. The power grid response to changes in ground conductivity and resistances shows similar results in a minor extent. This leads us to consider GIC as a non-negligible phenomenon in South America. Consequently, GIC must be taken into account in mid-to-low latitude power grids as well.
Near Work Related Parameters and Myopia in Chinese Children: the Anyang Childhood Eye Study.
Li, Shi-Ming; Li, Si-Yuan; Kang, Meng-Tian; Zhou, Yuehua; Liu, Luo-Ru; Li, He; Wang, Yi-Peng; Zhan, Si-Yan; Gopinath, Bamini; Mitchell, Paul; Wang, Ningli
2015-01-01
To examine the associations of near work related parameters with spherical equivalent refraction and axial length in Chinese children. A total of 1770 grade 7 students with mean age of 12.7 years were examined with cycloplegic autorefraction and axial length. Questions were asked regarding time spent in near work and outdoors per day, and near work related parameters. Multivariate models revealed the following associations with greater odds of myopia: continuous reading (> 45min), odds ratio [OR], 1.4; 95% confidence interval [CI], 1.1-1.8; close television viewing distance (≤ 3m), OR, 1.7; 95% CI, 1.2-2.3; head tilt when writing, OR, 1.3; 95% CI, 1.1-1.7, and desk lighting using fluorescent vs. incandescent lamp, OR, 1.5; 95% CI, 1.2-2.0. These factors, together with close reading distance and close nib-to-fingertip distance were significantly associated with greater myopia (Preading more books for pleasure was significantly associated with greater myopia (P=0.03). Television viewing distance (≤ 3 m), fluorescent desk light, close reading distance (≤20 cm) and close nib-to-fingertip distance (≤ 2 cm) were significantly associated with longer axial length (PReading distance, desk light, and reading books for pleasure had significant interaction effects with parental myopia. Continuous reading, close distances of reading, television viewing and nib-to-fingertip, head tilt when writing, reading more books for pleasure and use of fluorescent desk light were significantly associated with myopia in 12-year-old Chinese children, which indicates that visual behaviors and environments may be important factors mediating the effects of near work on myopia.
Parameter and State Estimator for State Space Models
Directory of Open Access Journals (Sweden)
Ruifeng Ding
2014-01-01
Full Text Available This paper proposes a parameter and state estimator for canonical state space systems from measured input-output data. The key is to solve the system state from the state equation and to substitute it into the output equation, eliminating the state variables, and the resulting equation contains only the system inputs and outputs, and to derive a least squares parameter identification algorithm. Furthermore, the system states are computed from the estimated parameters and the input-output data. Convergence analysis using the martingale convergence theorem indicates that the parameter estimates converge to their true values. Finally, an illustrative example is provided to show that the proposed algorithm is effective.
Parameter and state estimator for state space models.
Ding, Ruifeng; Zhuang, Linfan
2014-01-01
This paper proposes a parameter and state estimator for canonical state space systems from measured input-output data. The key is to solve the system state from the state equation and to substitute it into the output equation, eliminating the state variables, and the resulting equation contains only the system inputs and outputs, and to derive a least squares parameter identification algorithm. Furthermore, the system states are computed from the estimated parameters and the input-output data. Convergence analysis using the martingale convergence theorem indicates that the parameter estimates converge to their true values. Finally, an illustrative example is provided to show that the proposed algorithm is effective.
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
Directory of Open Access Journals (Sweden)
Janet M T Van Uem
Full Text Available The instrumented-Timed-Up-and-Go test (iTUG provides detailed information about the following movement patterns: sit-to-walk (siwa, straight walking, turning and walk-to-sit (wasi. We were interested in the relative contributions of respective iTUG sub-phases to specific clinical deficits most relevant for daily life in Parkinson's disease (PD. More specifically, we investigated which condition-fast speed (FS or convenient speed (CS-differentiates best between mild- to moderate-stage PD patients and controls, which parameters of the iTUG sub-phases are significantly different between PD patients and controls, and how the iTUG parameters associate with cognitive parameters (with particular focus on cognitive flexibility and working memory and Health-Related-Quality of Life (HRQoL.Twenty-eight PD participants (65.1 ± 7.1 years, H&Y stage 1-3, medication OFF state and 20 controls (66.1 ± 7.5 years performed an iTUG (DynaPort®, McRoberts BV, The Netherlands under CS and FS conditions. The PD Questionnaire 39 (PDQ-39 was employed to assess HRQoL. General cognitive and executive functions were assessed using the Montreal Cognitive Assessment and the Trail Making Test.The total iTUG duration and sub-phases durations under FS condition differentiated PD patients slightly better from controls, compared to the CS condition. The following sub-phases were responsible for the observed longer total duration PD patients needed to perform the iTUG: siwa, turn and wasi. None of the iTUG parameters correlated relevantly with general cognitive function. Turning duration and wasi maximum flexion velocity correlated strongest with executive function. Walking back duration correlated strongest with HRQoL.This study confirms that mild- to moderate-stage PD patients need more time to perform the iTUG than controls, and adds the following aspects to current literature: FS may be more powerful than CS to delineate subtle movement deficits in mild- to moderate-stage PD
THREE-PARAMETER CREEP DAMAGE CONSTITUTIVE MODEL AND ITS APPLICATION IN HYDRAULIC TUNNELLING
Luo Gang; Chen Liang
2016-01-01
Rock deformation is a time-dependent process, generally referred to as rheology. Especially for soft rock strata, design and construction of tunnel shall take full account of rheological properties of adjoining rocks. Based on classic three-parameter HK model (generalized Kelvin model), this paper proposes a three-parameter H-K damage model of which parameters attenuate with increase of equivalent strain, provides attenuation equation of model parameters in the first, second and third stage o...
Mikhailov, E.; Vlasenko, S.; Rose, D.; Pöschl, U.
2013-01-01
organic aerosol) we present first mass-based measurements of water uptake over a wide range of relative humidity (1-99.4%) obtained with a new filter-based differential hygroscopicity analyzer (FDHA) technique. For these samples the concentration dependence of κm can be described by a simple KIM model equation based on observable mass growth factors and a total of only six fit parameters summarizing the combined effects of the dilute hygroscopicity parameters, self- and cross-interaction parameters, and solubilities of all involved chemical components. One of the fit parameters represents κm0 and can be used to predict critical dry diameters for the activation of cloud condensation nuclei (CCN) as a function of water vapor supersaturation according to Köhler theory. For sodium chloride and ammonium sulfate reference particles as well as for pristine rainforest aerosols consisting mostly of secondary organic matter, we obtained good agreement between the KIM predictions and measurement data of CCN activation. The application of KIM and mass-based measurement techniques shall help to bridge gaps in the current understanding of water uptake by atmospheric aerosols: (1) the gap between hygroscopicity parameters determined by hygroscopic growth measurements under sub-saturated conditions and by CCN activation measurements at water vapor supersaturation, and (2) the gap between the results of simplified single parameter models widely used in atmospheric or climate science and the results of complex multi-parameter ion- and molecule-interaction models frequently used in physical chemistry and solution thermodynamics (e.g., AIM, E-AIM, ADDEM, UNIFAC, AIOMFAC).
Directory of Open Access Journals (Sweden)
E. Mikhailov
2013-01-01
collected from boreal rural air and from pristine tropical rainforest air (secondary organic aerosol we present first mass-based measurements of water uptake over a wide range of relative humidity (1–99.4% obtained with a new filter-based differential hygroscopicity analyzer (FDHA technique. For these samples the concentration dependence of κ_{m} can be described by a simple KIM model equation based on observable mass growth factors and a total of only six fit parameters summarizing the combined effects of the dilute hygroscopicity parameters, self- and cross-interaction parameters, and solubilities of all involved chemical components. One of the fit parameters represents κ_{m}^{0} and can be used to predict critical dry diameters for the activation of cloud condensation nuclei (CCN as a function of water vapor supersaturation according to Köhler theory. For sodium chloride and ammonium sulfate reference particles as well as for pristine rainforest aerosols consisting mostly of secondary organic matter, we obtained good agreement between the KIM predictions and measurement data of CCN activation.
The application of KIM and mass-based measurement techniques shall help to bridge gaps in the current understanding of water uptake by atmospheric aerosols: (1 the gap between hygroscopicity parameters determined by hygroscopic growth measurements under sub-saturated conditions and by CCN activation measurements at water vapor supersaturation, and (2 the gap between the results of simplified single parameter models widely used in atmospheric or climate science and the results of complex multi-parameter ion- and molecule-interaction models frequently used in physical chemistry and solution thermodynamics (e.g., AIM, E-AIM, ADDEM, UNIFAC, AIOMFAC.
Cosmological models in general relativity
Indian Academy of Sciences (India)
LRS Bianchi type-I space-time ﬁlled with perfect ﬂuid is considered here with deceleration parameter as variable. The metric potentials and are functions of as well as . Assuming '/=(), where prime denotes differentiation with respect to , it was found that =('/) and =(), where =() and is the ...
Estimating Parameters in Physical Models through Bayesian Inversion: A Complete Example
Allmaras, Moritz
2013-02-07
All mathematical models of real-world phenomena contain parameters that need to be estimated from measurements, either for realistic predictions or simply to understand the characteristics of the model. Bayesian statistics provides a framework for parameter estimation in which uncertainties about models and measurements are translated into uncertainties in estimates of parameters. This paper provides a simple, step-by-step example-starting from a physical experiment and going through all of the mathematics-to explain the use of Bayesian techniques for estimating the coefficients of gravity and air friction in the equations describing a falling body. In the experiment we dropped an object from a known height and recorded the free fall using a video camera. The video recording was analyzed frame by frame to obtain the distance the body had fallen as a function of time, including measures of uncertainty in our data that we describe as probability densities. We explain the decisions behind the various choices of probability distributions and relate them to observed phenomena. Our measured data are then combined with a mathematical model of a falling body to obtain probability densities on the space of parameters we seek to estimate. We interpret these results and discuss sources of errors in our estimation procedure. © 2013 Society for Industrial and Applied Mathematics.
Are subject-specific musculoskeletal models robust to the uncertainties in parameter identification?
Valente, Giordano; Pitto, Lorenzo; Testi, Debora; Seth, Ajay; Delp, Scott L; Stagni, Rita; Viceconti, Marco; Taddei, Fulvia
2014-01-01
Subject-specific musculoskeletal modeling can be applied to study musculoskeletal disorders, allowing inclusion of personalized anatomy and properties. Independent of the tools used for model creation, there are unavoidable uncertainties associated with parameter identification, whose effect on model predictions is still not fully understood. The aim of the present study was to analyze the sensitivity of subject-specific model predictions (i.e., joint angles, joint moments, muscle and joint contact forces) during walking to the uncertainties in the identification of body landmark positions, maximum muscle tension and musculotendon geometry. To this aim, we created an MRI-based musculoskeletal model of the lower limbs, defined as a 7-segment, 10-degree-of-freedom articulated linkage, actuated by 84 musculotendon units. We then performed a Monte-Carlo probabilistic analysis perturbing model parameters according to their uncertainty, and solving a typical inverse dynamics and static optimization problem using 500 models that included the different sets of perturbed variable values. Model creation and gait simulations were performed by using freely available software that we developed to standardize the process of model creation, integrate with OpenSim and create probabilistic simulations of movement. The uncertainties in input variables had a moderate effect on model predictions, as muscle and joint contact forces showed maximum standard deviation of 0.3 times body-weight and maximum range of 2.1 times body-weight. In addition, the output variables significantly correlated with few input variables (up to 7 out of 312) across the gait cycle, including the geometry definition of larger muscles and the maximum muscle tension in limited gait portions. Although we found subject-specific models not markedly sensitive to parameter identification, researchers should be aware of the model precision in relation to the intended application. In fact, force predictions could be
Are subject-specific musculoskeletal models robust to the uncertainties in parameter identification?
Directory of Open Access Journals (Sweden)
Giordano Valente
Full Text Available Subject-specific musculoskeletal modeling can be applied to study musculoskeletal disorders, allowing inclusion of personalized anatomy and properties. Independent of the tools used for model creation, there are unavoidable uncertainties associated with parameter identification, whose effect on model predictions is still not fully understood. The aim of the present study was to analyze the sensitivity of subject-specific model predictions (i.e., joint angles, joint moments, muscle and joint contact forces during walking to the uncertainties in the identification of body landmark positions, maximum muscle tension and musculotendon geometry. To this aim, we created an MRI-based musculoskeletal model of the lower limbs, defined as a 7-segment, 10-degree-of-freedom articulated linkage, actuated by 84 musculotendon units. We then performed a Monte-Carlo probabilistic analysis perturbing model parameters according to their uncertainty, and solving a typical inverse dynamics and static optimization problem using 500 models that included the different sets of perturbed variable values. Model creation and gait simulations were performed by using freely available software that we developed to standardize the process of model creation, integrate with OpenSim and create probabilistic simulations of movement. The uncertainties in input variables had a moderate effect on model predictions, as muscle and joint contact forces showed maximum standard deviation of 0.3 times body-weight and maximum range of 2.1 times body-weight. In addition, the output variables significantly correlated with few input variables (up to 7 out of 312 across the gait cycle, including the geometry definition of larger muscles and the maximum muscle tension in limited gait portions. Although we found subject-specific models not markedly sensitive to parameter identification, researchers should be aware of the model precision in relation to the intended application. In fact, force
CONSTRUCTION MODELS OF ANTROPOMETRIC AND DERMATOGLIPHIC PARAMETERS OF THE FACILITY
Directory of Open Access Journals (Sweden)
Novikova A.O.
2017-12-01
Full Text Available The scientific work is devoted to the analysis of constitutional and morpho - functional parameters of a person. The relevance of the chosen topic is substantiated, the problem of determining the functional state of a person, in particular the level of health, is analyzed. Correlation analysis of anthropometric parameters of a person and dermatoglyphic signs of a person is carried out.
Behavioural Pattern of Invertibility Parameter of Arima Model ...
African Journals Online (AJOL)
It was deduced that behaviour of invertibility parameter πidepends on the order of autoregressive part (p), the order of integrated part (d), positive and negative values of moving average parameter (ϑ). Journal of the Nigerian Association of Mathematical Physics, Volume 19 (November, 2011), pp 591 – 606 ...
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
A Note on the Item Information Function of the Four-Parameter Logistic Model
Magis, David
2013-01-01
This article focuses on four-parameter logistic (4PL) model as an extension of the usual three-parameter logistic (3PL) model with an upper asymptote possibly different from 1. For a given item with fixed item parameters, Lord derived the value of the latent ability level that maximizes the item information function under the 3PL model. The…
Ecohydrological model parameter selection for stream health evaluation.
Woznicki, Sean A; Nejadhashemi, A Pouyan; Ross, Dennis M; Zhang, Zhen; Wang, Lizhu; Esfahanian, Abdol-Hossein
2015-04-01
Variable selection is a critical step in development of empirical stream health prediction models. This study develops a framework for selecting important in-stream variables to predict four measures of biological integrity: total number of Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa, family index of biotic integrity (FIBI), Hilsenhoff biotic integrity (HBI), and fish index of biotic integrity (IBI). Over 200 flow regime and water quality variables were calculated using the Hydrologic Index Tool (HIT) and Soil and Water Assessment Tool (SWAT). Streams of the River Raisin watershed in Michigan were grouped using the Strahler stream classification system (orders 1-3 and orders 4-6), k-means clustering technique (two clusters: C1 and C2), and all streams (one grouping). For each grouping, variable selection was performed using Bayesian variable selection, principal component analysis, and Spearman's rank correlation. Following selection of best variable sets, models were developed to predict the measures of biological integrity using adaptive-neuro fuzzy inference systems (ANFIS), a technique well-suited to complex, nonlinear ecological problems. Multiple unique variable sets were identified, all which differed by selection method and stream grouping. Final best models were mostly built using the Bayesian variable selection method. The most effective stream grouping method varied by health measure, although k-means clustering and grouping by stream order were always superior to models built without grouping. Commonly selected variables were related to streamflow magnitude, rate of change, and seasonal nitrate concentration. Each best model was effective in simulating stream health observations, with EPT taxa validation R2 ranging from 0.67 to 0.92, FIBI ranging from 0.49 to 0.85, HBI from 0.56 to 0.75, and fish IBI at 0.99 for all best models. The comprehensive variable selection and modeling process proposed here is a robust method that extends our
Parameter Estimation for Dynamic Model of the Financial System
Directory of Open Access Journals (Sweden)
Veronika Novotná
2015-01-01
Full Text Available Economy can be considered a large, open system which is influenced by fluctuations, both internal and external. Based on non-linear dynamics theory, the dynamic models of a financial system try to provide a new perspective by explaining the complicated behaviour of the system not as a result of external influences or random behaviour, but as a result of the behaviour and trends of the system’s internal structures. The present article analyses a chaotic financial system from the point of view of determining the time delay of the model variables – the interest rate, investment demand, and price index. The theory is briefly explained in the first chapters of the paper and serves as a basis for formulating the relations. This article aims to determine the appropriate length of time delay variables in a dynamic model of the financial system in order to express the real economic situation and respect the effect of the history of factors under consideration. The determination of the delay length is carried out for the time series representing Euro area. The methodology for the determination of the time delay is illustrated by a concrete example.
Frontczak, Monika Joanna; Wargocki, Pawel
2011-01-01
The main objective of the Ph.D. study was to examine occupants’ perception of comfort and self-estimated job performance in non-industrial buildings (homes and offices), in particular how building occupants understand comfort and which parameters, not necessarily related to indoor environments, influence the perception of comfort.To meet the objective, the following actions were taken: (1) a literature survey exploring which indoor environmental parameters (thermal, acoustic, visualenvironmen...
Coarse-graining for fast dynamics of order parameters in the phase-field model
Jou, D.; Galenko, P. K.
2018-01-01
In standard descriptions, the master equation can be obtained by coarse-graining with the application of the hypothesis of full local thermalization that is equivalent to the local thermodynamic equilibrium. By contrast, fast transformations proceed in the absence of local equilibrium and the master equation must be obtained with the absence of thermalization. In the present work, a non-Markovian master equation leading, in specific cases of relaxation to local thermodynamic equilibrium, to hyperbolic evolution equations for a binary alloy, is derived for a system with two order parameters. One of them is a conserved order parameter related to the atomistic composition, and the other one is a non-conserved order parameter, which is related to phase field. A microscopic basis for phenomenological phase-field models of fast phase transitions, when the transition is so fast that there is not sufficient time to achieve local thermalization between two successive elementary processes in the system, is provided. In a particular case, when the relaxation to local thermalization proceeds by the exponential law, the obtained coarse-grained equations are related to the hyperbolic phase-field model. The solution of the model equations is obtained to demonstrate non-equilibrium phenomenon of solute trapping which appears in rapid growth of dendritic crystals. This article is part of the theme issue `From atomistic interfaces to dendritic patterns'.
Le, Vu H.; Buscaglia, Robert; Chaires, Jonathan B.; Lewis, Edwin A.
2013-01-01
Isothermal Titration Calorimetry, ITC, is a powerful technique that can be used to estimate a complete set of thermodynamic parameters (e.g. Keq (or ΔG), ΔH, ΔS, and n) for a ligand binding interaction described by a thermodynamic model. Thermodynamic models are constructed by combination of equilibrium constant, mass balance, and charge balance equations for the system under study. Commercial ITC instruments are supplied with software that includes a number of simple interaction models, for example one binding site, two binding sites, sequential sites, and n-independent binding sites. More complex models for example, three or more binding sites, one site with multiple binding mechanisms, linked equilibria, or equilibria involving macromolecular conformational selection through ligand binding need to be developed on a case by case basis by the ITC user. In this paper we provide an algorithm (and a link to our MATLAB program) for the non-linear regression analysis of a multiple binding site model with up to four overlapping binding equilibria. Error analysis demonstrates that fitting ITC data for multiple parameters (e.g. up to nine parameters in the three binding site model) yields thermodynamic parameters with acceptable accuracy. PMID:23262283
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Michala Jakubcová
2015-01-01
Full Text Available The presented paper provides the analysis of selected versions of the particle swarm optimization (PSO algorithm. The tested versions of the PSO were combined with the shuffling mechanism, which splits the model population into complexes and performs distributed PSO optimization. One of them is a new proposed PSO modification, APartW, which enhances the global exploration and local exploitation in the parametric space during the optimization process through the new updating mechanism applied on the PSO inertia weight. The performances of four selected PSO methods were tested on 11 benchmark optimization problems, which were prepared for the special session on single-objective real-parameter optimization CEC 2005. The results confirm that the tested new APartW PSO variant is comparable with other existing distributed PSO versions, AdaptW and LinTimeVarW. The distributed PSO versions were developed for finding the solution of inverse problems related to the estimation of parameters of hydrological model Bilan. The results of the case study, made on the selected set of 30 catchments obtained from MOPEX database, show that tested distributed PSO versions provide suitable estimates of Bilan model parameters and thus can be used for solving related inverse problems during the calibration process of studied water balance hydrological model.
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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
Neural Models: An Option to Estimate Seismic Parameters of Accelerograms
Alcántara, L.; García, S.; Ovando-Shelley, E.; Macías, M. A.
2014-12-01
Seismic instrumentation for recording strong earthquakes, in Mexico, goes back to the 60´s due the activities carried out by the Institute of Engineering at Universidad Nacional Autónoma de México. However, it was after the big earthquake of September 19, 1985 (M=8.1) when the project of seismic instrumentation assumes a great importance. Currently, strong ground motion networks have been installed for monitoring seismic activity mainly along the Mexican subduction zone and in Mexico City. Nevertheless, there are other major regions and cities that can be affected by strong earthquakes and have not yet begun their seismic instrumentation program or this is still in development.Because of described situation some relevant earthquakes (e.g. Huajuapan de León Oct 24, 1980 M=7.1, Tehuacán Jun 15, 1999 M=7 and Puerto Escondido Sep 30, 1999 M= 7.5) have not been registered properly in some cities, like Puebla and Oaxaca, and that were damaged during those earthquakes. Fortunately, the good maintenance work carried out in the seismic network has permitted the recording of an important number of small events in those cities. So in this research we present a methodology based on the use of neural networks to estimate significant duration and in some cases the response spectra for those seismic events. The neural model developed predicts significant duration in terms of magnitude, epicenter distance, focal depth and soil characterization. Additionally, for response spectra we used a vector of spectral accelerations. For training the model we selected a set of accelerogram records obtained from the small events recorded in the strong motion instruments installed in the cities of Puebla and Oaxaca. The final results show that neural networks as a soft computing tool that use a multi-layer feed-forward architecture provide good estimations of the target parameters and they also have a good predictive capacity to estimate strong ground motion duration and response spectra.
Modeling Parameters of Reliability of Technological Processes of Hydrocarbon Pipeline Transportation
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Shalay Viktor
2016-01-01
Full Text Available On the basis of methods of system analysis and parametric reliability theory, the mathematical modeling of processes of oil and gas equipment operation in reliability monitoring was conducted according to dispatching data. To check the quality of empiric distribution coordination , an algorithm and mathematical methods of analysis are worked out in the on-line mode in a changing operating conditions. An analysis of physical cause-and-effect relations mechanism between the key factors and changing parameters of technical systems of oil and gas facilities is made, the basic types of technical distribution parameters are defined. Evaluation of the adequacy the analyzed parameters of the type of distribution is provided by using a criterion A.Kolmogorov, as the most universal, accurate and adequate to verify the distribution of continuous processes of complex multiple-technical systems. Methods of calculation are provided for supervising by independent bodies for risk assessment and safety facilities.
Trap configuration and spacing influences parameter estimates in spatial capture-recapture models.
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Catherine C Sun
Full Text Available An increasing number of studies employ spatial capture-recapture models to estimate population size, but there has been limited research on how different spatial sampling designs and trap configurations influence parameter estimators. Spatial capture-recapture models provide an advantage over non-spatial models by explicitly accounting for heterogeneous detection probabilities among individuals that arise due to the spatial organization of individuals relative to sampling devices. We simulated black bear (Ursus americanus populations and spatial capture-recapture data to evaluate the influence of trap configuration and trap spacing on estimates of population size and a spatial scale parameter, sigma, that relates to home range size. We varied detection probability and home range size, and considered three trap configurations common to large-mammal mark-recapture studies: regular spacing, clustered, and a temporal sequence of different cluster configurations (i.e., trap relocation. We explored trap spacing and number of traps per cluster by varying the number of traps. The clustered arrangement performed well when detection rates were low, and provides for easier field implementation than the sequential trap arrangement. However, performance differences between trap configurations diminished as home range size increased. Our simulations suggest it is important to consider trap spacing relative to home range sizes, with traps ideally spaced no more than twice the spatial scale parameter. While spatial capture-recapture models can accommodate different sampling designs and still estimate parameters with accuracy and precision, our simulations demonstrate that aspects of sampling design, namely trap configuration and spacing, must consider study area size, ranges of individual movement, and home range sizes in the study population.
Trap configuration and spacing influences parameter estimates in spatial capture-recapture models.
Sun, Catherine C; Fuller, Angela K; Royle, J Andrew
2014-01-01
An increasing number of studies employ spatial capture-recapture models to estimate population size, but there has been limited research on how different spatial sampling designs and trap configurations influence parameter estimators. Spatial capture-recapture models provide an advantage over non-spatial models by explicitly accounting for heterogeneous detection probabilities among individuals that arise due to the spatial organization of individuals relative to sampling devices. We simulated black bear (Ursus americanus) populations and spatial capture-recapture data to evaluate the influence of trap configuration and trap spacing on estimates of population size and a spatial scale parameter, sigma, that relates to home range size. We varied detection probability and home range size, and considered three trap configurations common to large-mammal mark-recapture studies: regular spacing, clustered, and a temporal sequence of different cluster configurations (i.e., trap relocation). We explored trap spacing and number of traps per cluster by varying the number of traps. The clustered arrangement performed well when detection rates were low, and provides for easier field implementation than the sequential trap arrangement. However, performance differences between trap configurations diminished as home range size increased. Our simulations suggest it is important to consider trap spacing relative to home range sizes, with traps ideally spaced no more than twice the spatial scale parameter. While spatial capture-recapture models can accommodate different sampling designs and still estimate parameters with accuracy and precision, our simulations demonstrate that aspects of sampling design, namely trap configuration and spacing, must consider study area size, ranges of individual movement, and home range sizes in the study population.
Checking the new IRI model The bottomside B parameters
Mosert, M; Ezquer, R; Lazo, B; Miro, G
2002-01-01
Electron density profiles obtained at Pruhonice (50.0, 15.0), El Arenosillo (37.1, 353.2) and Havana (23, 278) were used to check the bottom-side B parameters BO (thickness parameter) and B1 (shape parameter) predicted by the new IRI - 2000 version. The electron density profiles were derived from ionograms using the ARP technique. The data base includes daytime and nighttime ionograms recorded under different seasonal and solar activity conditions. Comparisons with IRI predictions were also done. The analysis shows that: a) The parameter B1 given by IRI 2000 reproduces better the observed ARP values than the IRI-90 version and b) The observed BO values are in general well reproduced by both IRI versions: IRI-90 and IRI-2000.
Xiu, Wanjing; Liao, Yuan
2014-12-01
Transmission lines are essential components of electric power grids. Diverse power system applications and simulation based studies require transmission line parameters including series resistance, reactance, and shunt susceptance, and accurate parameters are pivotal in ensuring the accuracy of analyses and reliable system operation. Commercial software packages for performing power system studies usually have their own databases that store the power system model including line parameters. When there is a physical system model change, the corresponding component in the database of the software packages will need to be modified. Manually updating line parameters are tedious and error-prone. This paper proposes a solution for streamlining the calculation of line parameters and updating of their values in respective software databases. The algorithms used for calculating the values of line parameters are described. The software developed for implementing the solution is described, and typical results are presented. The proposed solution is developed for a utility and has a potential to be put into use by other utilities.
Proposal for the Use of a New Parameter in the Composite Road Traffic Model
Boroiu, A.; Tabacu, I.; Boroiu, A. A.; Neagu, E.; Vieru, I.
2017-10-01
Comparative analysis of the models used in the literature for the fundamental traffic diagram reveals that the improvement of these models can only be achieved by taking into account the vehicle tracking models. Given that it is of great interest to model the relation between density and speed, to identify the conditions in which maximum flow can be achieved with a high operating speed and safely. For the non-homogeneous traffic, met in our country due to the lack of highways, the model describing the minimum range of vehicles was developed based on the relation of the minimum distance between vehicles taking into account the difference between the vehicle braking modes. Finally it is explained the maximum volume of traffic according to a parameter that includes the decelerations of the two vehicles, which determined the proposed use of this new concept in road traffic theory. This has made it possible to conclude that in the case of non-homogeneous traffic the volume increases only to a certain speed value, then decreases, while in the case of homogeneous traffic the volume continues to increase to a limit value. The paper argues the necessity of using this new parameter for road traffic models.
A cooperative strategy for parameter estimation in large scale systems biology models.
Villaverde, Alejandro F; Egea, Jose A; Banga, Julio R
2012-06-22
Mathematical models play a key role in systems biology: they summarize the currently available knowledge in a way that allows to make experimentally verifiable predictions. Model calibration consists of finding the parameters that give the best fit to a set of experimental data, which entails minimizing a cost function that measures the goodness of this fit. Most mathematical models in systems biology present three characteristics which make this problem very difficult to solve: they are highly non-linear, they have a large number of parameters to be estimated, and the information content of the available experimental data is frequently scarce. Hence, there is a need for global optimization methods capable of solving this problem efficiently. A new approach for parameter estimation of large scale models, called Cooperative Enhanced Scatter Search (CeSS), is presented. Its key feature is the cooperation between different programs ("threads") that run in parallel in different processors. Each thread implements a state of the art metaheuristic, the enhanced Scatter Search algorithm (eSS). Cooperation, meaning information sharing between threads, modifies the systemic properties of the algorithm and allows to speed up performance. Two parameter estimation problems involving models related with the central carbon metabolism of E. coli which include different regulatory levels (metabolic and transcriptional) are used as case studies. The performance and capabilities of the method are also evaluated using benchmark problems of large-scale global optimization, with excellent results. The cooperative CeSS strategy is a general purpose technique that can be applied to any model calibration problem. Its capability has been demonstrated by calibrating two large-scale models of different characteristics, improving the performance of previously existing methods in both cases. The cooperative metaheuristic presented here can be easily extended to incorporate other global and
A cooperative strategy for parameter estimation in large scale systems biology models
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Villaverde Alejandro F
2012-06-01
Full Text Available Abstract Background Mathematical models play a key role in systems biology: they summarize the currently available knowledge in a way that allows to make experimentally verifiable predictions. Model calibration consists of finding the parameters that give the best fit to a set of experimental data, which entails minimizing a cost function that measures the goodness of this fit. Most mathematical models in systems biology present three characteristics which make this problem very difficult to solve: they are highly non-linear, they have a large number of parameters to be estimated, and the information content of the available experimental data is frequently scarce. Hence, there is a need for global optimization methods capable of solving this problem efficiently. Results A new approach for parameter estimation of large scale models, called Cooperative Enhanced Scatter Search (CeSS, is presented. Its key feature is the cooperation between different programs (“threads” that run in parallel in different processors. Each thread implements a state of the art metaheuristic, the enhanced Scatter Search algorithm (eSS. Cooperation, meaning information sharing between threads, modifies the systemic properties of the algorithm and allows to speed up performance. Two parameter estimation problems involving models related with the central carbon metabolism of E. coli which include different regulatory levels (metabolic and transcriptional are used as case studies. The performance and capabilities of the method are also evaluated using benchmark problems of large-scale global optimization, with excellent results. Conclusions The cooperative CeSS strategy is a general purpose technique that can be applied to any model calibration problem. Its capability has been demonstrated by calibrating two large-scale models of different characteristics, improving the performance of previously existing methods in both cases. The cooperative metaheuristic presented here
Modeling and Dynamic Properties of a Four-Parameter Zener Model Vibration Isolator
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Wen-ku Shi
2016-01-01
Full Text Available To install high-performance isolators in a limited installation space, a novel passive isolator based on the four-parameter Zener model is proposed. The proposed isolator consists of three major parts, namely, connecting structure, sealing construction, and upper and lower cavities, all of which are enclosed by four segments of metal bellows with the same diameter. The equivalent stiffness and damping model of the isolator are derived from the dynamic stiffness of the isolation system. Experiments are conducted, and the experiment error is analyzed. Test results verify the validity of the model. Theoretical analysis and numerical simulation reveal that the stiffness and damping of the isolator have multiple properties with different exciting amplitudes and structural parameters. In consideration of the design of the structural parameter, the effects of exciting amplitude, damp channel diameter, equivalent cylinder diameter of cavities, sum of the stiffness of the bellows at the end of the isolator, and length of damp channel on the dynamic properties of the isolator are discussed comprehensively. A design method based on the parameter sensitivity of the isolator’s design parameter is proposed. Thus, the novel isolator can be practically applied to engineering and provide a significant contribution in the field.
Parameter sensitivity and uncertainty analysis for a storm surge and wave model
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L. A. Bastidas
2016-09-01
Full Text Available Development and simulation of synthetic hurricane tracks is a common methodology used to estimate hurricane hazards in the absence of empirical coastal surge and wave observations. Such methods typically rely on numerical models to translate stochastically generated hurricane wind and pressure forcing into coastal surge and wave estimates. The model output uncertainty associated with selection of appropriate model parameters must therefore be addressed. The computational overburden of probabilistic surge hazard estimates is exacerbated by the high dimensionality of numerical surge and wave models. We present a model parameter sensitivity analysis of the Delft3D model for the simulation of hazards posed by Hurricane Bob (1991 utilizing three theoretical wind distributions (NWS23, modified Rankine, and Holland. The sensitive model parameters (of 11 total considered include wind drag, the depth-induced breaking γB, and the bottom roughness. Several parameters show no sensitivity (threshold depth, eddy viscosity, wave triad parameters, and depth-induced breaking αB and can therefore be excluded to reduce the computational overburden of probabilistic surge hazard estimates. The sensitive model parameters also demonstrate a large number of interactions between parameters and a nonlinear model response. While model outputs showed sensitivity to several parameters, the ability of these parameters to act as tuning parameters for calibration is somewhat limited as proper model calibration is strongly reliant on accurate wind and pressure forcing data. A comparison of the model performance with forcings from the different wind models is also presented.
Evaluation of parameters of color profile models of LCD and LED screens
Zharinov, I. O.; Zharinov, O. O.
2017-12-01
The purpose of the research relates to the problem of parametric identification of the color profile model of LCD (liquid crystal display) and LED (light emitting diode) screens. The color profile model of a screen is based on the Grassmann’s Law of additive color mixture. Mathematically the problem is to evaluate unknown parameters (numerical coefficients) of the matrix transformation between different color spaces. Several methods of evaluation of these screen profile coefficients were developed. These methods are based either on processing of some colorimetric measurements or on processing of technical documentation data.
Modeling transmission parameters of polymer microstructured fibers for applications in FTTH networks
Gdula, P.; Welikow, K.; Szczepański, P.; Buczyński, R.; Piramidowicz, R.
2011-10-01
This paper is focused on selected aspects of designing and modeling of transmission parameters of plastic optical fibers (POFs), considered in the context of their potential applications in optical access networks and, specifically, in Fiber-To- The-Home (FTTH) systems. The survey of state-of-the-art solutions is presented and possibility of improving transmission properties of POFs by microstructurization is discussed on the basis of the first results of numerical modeling. In particular, the microstructured POF was designed supporting propagation of limited number of modes while keeping relatively large mode area and, simultaneously, significantly lowered bending losses.
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Grbovic Vesna
2016-12-01
Full Text Available The purpose of this study was to assess the correlation between health-related quality of life (HRQoL and clinically relevant osteodensitometric and biochemical parameters in postmenopausal osteoporotic women. Bone mineral density (BMD and T scores of the lumbar vertebrae and femoral neck were assessed in 100 osteoporotic women (56 without previous fractures and 44 with previous fractures using dual x-ray absorptiometry. The Fracture Risk Assessment Tool (FRAX index for major osteoporotic and hip fractures was calculated based on demographic data and hip BMD. Venous blood samples were taken from each subject for biochemical analysis (serum calcium, phosphorus, alkaline phosphatase and vitamin D levels. HRQoL was assessed using the QUALEFFO-41 questionnaire (domains: Health perception, Pain, and Physical, Social and Mental function. Basic participant characteristics (age, menopause length, body mass index, smoking habits, hereditary tendency towards fracture, fracture history correlated with some of the QUALEFFO-41 domains, but the correlation coefficients were low (r<0.3, except in the case of the correlation between Pain and fracture history (r=0.638. Of the six variables included in the multiple regression model, fracture history was shown to be the most significant predictor with respect to the following three QUALEFFO-41 domains: Pain (b=20.511, Social function (b=2.548 and Health perception (b=3.185. Correlation analysis showed that after adjustment for basic characteristics, BMD and T score of the femoral neck and Pain (r=0.331 and r=0.449, respectively, Social function (r=0.422 and r=0.419 and Health perception (r=0.434 for T score of the femoral neck exhibited the strongest correlations. Vitamin D was negatively correlated with Mental function, while the other biochemical parameters exhibited variable correlations with the QUALEFFO- 41 domains (r≈0.2-0.5. Our study confirmed the previously established relationship between BMD of the
Screening key parameters related to passive system performance based on Analytic Hierarchy Process
International Nuclear Information System (INIS)
Ma, Guohang; Yu, Yu; Huang, Xiong; Peng, Yuan; Ma, Nan; Shan, Zuhua; Niu, Fenglei; Wang, Shengfei
2015-01-01
Highlights: • An improved AHP method is presented for screening key parameters used in passive system reliability analysis. • We take the special bottom parameters as criterion for calculation and the abrupt change of the results are verified. • Combination weights are also affected by uncertainty of input parameters. - Abstract: Passive safety system is widely used in the new generation nuclear power plant (NPP) designs such as AP1000 to improve the reactor safety benefitting from its simple construction and less request for human intervene. However, the functional failure induced by uncertainty in the system thermal–hydraulic (T–H) performance becomes one of the main contributors to system operational failure since the system operates based on natural circulation, which should be considered in the system reliability evaluation. In order to improve the calculation efficiency the key parameters which significantly affect the system T–H characteristics can be screened and then be analyzed in detail. The Analytical Hierarchy Process (AHP) is one of the efficient methods to analyze the influence of the parameters on a passive system based on the experts’ experience. The passive containment cooling system (PCCS) in AP1000 is one of the typical passive safety systems, nevertheless too many parameters need to be analyzed and the T–H model itself is more complicated, so the traditional AHP method should be mended to use for screening key parameters efficiently. In this paper, we adapt the improved method in hierarchy construction and experts’ opinions integration, some parameters at the bottom justly in the traditional hierarchy are studied as criterion layer in improved AHP, the rationality of the method and the effect of abrupt change with the data are verified. The passive containment cooling system (PCCS) in AP1000 is evaluated as an example, and four key parameters are selected from 49 inputs
Sensitivity testing practice on pre-processing parameters in hard and soft coupled modeling
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Z. Ignaszak
2010-01-01
Full Text Available This paper pays attention to the problem of practical applicability of coupled modeling with the use of hard and soft models types and necessity of adapted to that models data base possession. The data base tests results for cylindrical 30 mm diameter casting made of AlSi7Mg alloy were presented. In simulation tests that were applied the Calcosoft system with CAFE (Cellular Automaton Finite Element module. This module which belongs to „multiphysics” models enables structure prediction of complete casting with division of columnar and equiaxed crystals zones of -phase. Sensitivity tests of coupled model on the particular values parameters changing were made. On these basis it was determined the relations of CET (columnar-to-equaiaxed transition zone position influence. The example of virtual structure validation based on real structure with CET zone location and grain size was shown.
Pseudo-dynamic source modelling with 1-point and 2-point statistics of earthquake source parameters
Song, S. G.
2013-12-24
Ground motion prediction is an essential element in seismic hazard and risk analysis. Empirical ground motion prediction approaches have been widely used in the community, but efficient simulation-based ground motion prediction methods are needed to complement empirical approaches, especially in the regions with limited data constraints. Recently, dynamic rupture modelling has been successfully adopted in physics-based source and ground motion modelling, but it is still computationally demanding and many input parameters are not well constrained by observational data. Pseudo-dynamic source modelling keeps the form of kinematic modelling with its computational efficiency, but also tries to emulate the physics of source process. In this paper, we develop a statistical framework that governs the finite-fault rupture process with 1-point and 2-point statistics of source parameters in order to quantify the variability of finite source models for future scenario events. We test this method by extracting 1-point and 2-point statistics from dynamically derived source models and simulating a number of rupture scenarios, given target 1-point and 2-point statistics. We propose a new rupture model generator for stochastic source modelling with the covariance matrix constructed from target 2-point statistics, that is, auto- and cross-correlations. Our sensitivity analysis of near-source ground motions to 1-point and 2-point statistics of source parameters provides insights into relations between statistical rupture properties and ground motions. We observe that larger standard deviation and stronger correlation produce stronger peak ground motions in general. The proposed new source modelling approach will contribute to understanding the effect of earthquake source on near-source ground motion characteristics in a more quantitative and systematic way.
Optimization of cryogenic cooled EDM process parameters using grey relational analysis
International Nuclear Information System (INIS)
Kumar, S Vinoth; Kumar, M Pradeep
2014-01-01
This paper presents an experimental investigation on cryogenic cooling of liquid nitrogen (LN 2 ) copper electrode in the electrical discharge machining (EDM) process. The optimization of the EDM process parameters, such as the electrode environment (conventional electrode and cryogenically cooled electrode in EDM), discharge current, pulse on time, gap voltage on material removal rate, electrode wear, and surface roughness on machining of AlSiCp metal matrix composite using multiple performance characteristics on grey relational analysis was investigated. The L 18 orthogonal array was utilized to examine the process parameters, and the optimal levels of the process parameters were identified through grey relational analysis. Experimental data were analyzed through analysis of variance. Scanning electron microscopy analysis was conducted to study the characteristics of the machined surface.
New trends in parameter identification for mathematical models
Leitão, Antonio; Zubelli, Jorge
2018-01-01
The Proceedings volume contains 16 contributions to the IMPA conference “New Trends in Parameter Identification for Mathematical Models”, Rio de Janeiro, Oct 30 – Nov 3, 2017, integrating the “Chemnitz Symposium on Inverse Problems on Tour”. This conference is part of the “Thematic Program on Parameter Identification in Mathematical Models” organized at IMPA in October and November 2017. One goal is to foster the scientific collaboration between mathematicians and engineers from the Brazialian, European and Asian communities. Main topics are iterative and variational regularization methods in Hilbert and Banach spaces for the stable approximate solution of ill-posed inverse problems, novel methods for parameter identification in partial differential equations, problems of tomography , solution of coupled conduction-radiation problems at high temperatures, and the statistical solution of inverse problems with applications in physics.
He, Li-hong; Wang, Hai-yan; Lei, Xiang-dong
2016-02-01
Model based on vegetation ecophysiological process contains many parameters, and reasonable parameter values will greatly improve simulation ability. Sensitivity analysis, as an important method to screen out the sensitive parameters, can comprehensively analyze how model parameters affect the simulation results. In this paper, we conducted parameter sensitivity analysis of BIOME-BGC model with a case study of simulating net primary productivity (NPP) of Larix olgensis forest in Wangqing, Jilin Province. First, with the contrastive analysis between field measurement data and the simulation results, we tested the BIOME-BGC model' s capability of simulating the NPP of L. olgensis forest. Then, Morris and EFAST sensitivity methods were used to screen the sensitive parameters that had strong influence on NPP. On this basis, we also quantitatively estimated the sensitivity of the screened parameters, and calculated the global, the first-order and the second-order sensitivity indices. The results showed that the BIOME-BGC model could well simulate the NPP of L. olgensis forest in the sample plot. The Morris sensitivity method provided a reliable parameter sensitivity analysis result under the condition of a relatively small sample size. The EFAST sensitivity method could quantitatively measure the impact of simulation result of a single parameter as well as the interaction between the parameters in BIOME-BGC model. The influential sensitive parameters for L. olgensis forest NPP were new stem carbon to new leaf carbon allocation and leaf carbon to nitrogen ratio, the effect of their interaction was significantly greater than the other parameter' teraction effect.
Shamshirband, Shahaboddin; Banjanovic-Mehmedovic, Lejla; Bosankic, Ivan; Kasapovic, Suad; Abdul Wahab, Ainuddin Wahid Bin
2016-01-01
Intelligent Transportation Systems rely on understanding, predicting and affecting the interactions between vehicles. The goal of this paper is to choose a small subset from the larger set so that the resulting regression model is simple, yet have good predictive ability for Vehicle agent speed relative to Vehicle intruder. The method of ANFIS (adaptive neuro fuzzy inference system) was applied to the data resulting from these measurements. The ANFIS process for variable selection was implemented in order to detect the predominant variables affecting the prediction of agent speed relative to intruder. This process includes several ways to discover a subset of the total set of recorded parameters, showing good predictive capability. The ANFIS network was used to perform a variable search. Then, it was used to determine how 9 parameters (Intruder Front sensors active (boolean), Intruder Rear sensors active (boolean), Agent Front sensors active (boolean), Agent Rear sensors active (boolean), RSSI signal intensity/strength (integer), Elapsed time (in seconds), Distance between Agent and Intruder (m), Angle of Agent relative to Intruder (angle between vehicles °), Altitude difference between Agent and Intruder (m)) influence prediction of agent speed relative to intruder. The results indicated that distance between Vehicle agent and Vehicle intruder (m) and angle of Vehicle agent relative to Vehicle Intruder (angle between vehicles °) is the most influential parameters to Vehicle agent speed relative to Vehicle intruder.
Temporal variation and scaling of parameters for a monthly hydrologic model
Deng, Chao; Liu, Pan; Wang, Dingbao; Wang, Weiguang
2018-03-01
The temporal variation of model parameters is affected by the catchment conditions and has a significant impact on hydrological simulation. This study aims to evaluate the seasonality and downscaling of model parameter across time scales based on monthly and mean annual water balance models with a common model framework. Two parameters of the monthly model, i.e., k and m, are assumed to be time-variant at different months. Based on the hydrological data set from 121 MOPEX catchments in the United States, we firstly analyzed the correlation between parameters (k and m) and catchment properties (NDVI and frequency of rainfall events, α). The results show that parameter k is positively correlated with NDVI or α, while the correlation is opposite for parameter m, indicating that precipitation and vegetation affect monthly water balance by controlling temporal variation of parameters k and m. The multiple linear regression is then used to fit the relationship between ε and the means and coefficient of variations of parameters k and m. Based on the empirical equation and the correlations between the time-variant parameters and NDVI, the mean annual parameter ε is downscaled to monthly k and m. The results show that it has lower NSEs than these from model with time-variant k and m being calibrated through SCE-UA, while for several study catchments, it has higher NSEs than that of the model with constant parameters. The proposed method is feasible and provides a useful tool for temporal scaling of model parameter.
Importance of hydrological parameters in contaminant transport modeling in a terrestrial environment
International Nuclear Information System (INIS)
Tsuduki, Katsunori; Matsunaga, Takeshi
2007-01-01
A grid type multi-layered distributed parameter model for calculating discharge in a watershed was described. Model verification with our field observation resulted in different sets of hydrological parameter values, all of which reproduced the observed discharge. The effect of those varied hydrological parameters on contaminant transport calculation was examined and discussed by simulation of event water transfer. (author)
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.
Van Dyke, Michael B.
2013-01-01
Present preliminary work using lumped parameter models to approximate dynamic response of electronic units to random vibration; Derive a general N-DOF model for application to electronic units; Illustrate parametric influence of model parameters; Implication of coupled dynamics for unit/board design; Demonstrate use of model to infer printed wiring board (PWB) dynamics from external chassis test measurement.
A New Ensemble of Perturbed-Input-Parameter Simulations by the Community Atmosphere Model
Energy Technology Data Exchange (ETDEWEB)
Covey, C; Brandon, S; Bremer, P T; Domyancis, D; Garaizar, X; Johannesson, G; Klein, R; Klein, S A; Lucas, D D; Tannahill, J; Zhang, Y
2011-10-27
Uncertainty quantification (UQ) is a fundamental challenge in the numerical simulation of Earth's weather and climate, and other complex systems. It entails much more than attaching defensible error bars to predictions: in particular it includes assessing low-probability but high-consequence events. To achieve these goals with models containing a large number of uncertain input parameters, structural uncertainties, etc., raw computational power is needed. An automated, self-adapting search of the possible model configurations is also useful. Our UQ initiative at the Lawrence Livermore National Laboratory has produced the most extensive set to date of simulations from the US Community Atmosphere Model. We are examining output from about 3,000 twelve-year climate simulations generated with a specialized UQ software framework, and assessing the model's accuracy as a function of 21 to 28 uncertain input parameter values. Most of the input parameters we vary are related to the boundary layer, clouds, and other sub-grid scale processes. Our simulations prescribe surface boundary conditions (sea surface temperatures and sea ice amounts) to match recent observations. Fully searching this 21+ dimensional space is impossible, but sensitivity and ranking algorithms can identify input parameters having relatively little effect on a variety of output fields, either individually or in nonlinear combination. Bayesian statistical constraints, employing a variety of climate observations as metrics, also seem promising. Observational constraints will be important in the next step of our project, which will compute sea surface temperatures and sea ice interactively, and will study climate change due to increasing atmospheric carbon dioxide.
Parameter optimization method for the water quality dynamic model based on data-driven theory.
Liang, Shuxiu; Han, Songlin; Sun, Zhaochen
2015-09-15
Parameter optimization is important for developing a water quality dynamic model. In this study, we applied data-driven method to select and optimize parameters for a complex three-dimensional water quality model. First, a data-driven model was developed to train the response relationship between phytoplankton and environmental factors based on the measured data. Second, an eight-variable water quality dynamic model was established and coupled to a physical model. Parameter sensitivity analysis was investigated by changing parameter values individually in an assigned range. The above results served as guidelines for the control parameter selection and the simulated result verification. Finally, using the data-driven model to approximate the computational water quality model, we employed the Particle Swarm Optimization (PSO) algorithm to optimize the control parameters. The optimization routines and results were analyzed and discussed based on the establishment of the water quality model in Xiangshan Bay (XSB). Copyright © 2015 Elsevier Ltd. All rights reserved.
Variability of dynamic source parameters inferred from kinematic models of past earthquakes
Causse, M.
2013-12-24
We analyse the scaling and distribution of average dynamic source properties (fracture energy, static, dynamic and apparent stress drops) using 31 kinematic inversion models from 21 crustal earthquakes. Shear-stress histories are computed by solving the elastodynamic equations while imposing the slip velocity of a kinematic source model as a boundary condition on the fault plane. This is achieved using a 3-D finite difference method in which the rupture kinematics are modelled with the staggered-grid-split-node fault representation method of Dalguer & Day. Dynamic parameters are then estimated from the calculated stress-slip curves and averaged over the fault plane. Our results indicate that fracture energy, static, dynamic and apparent stress drops tend to increase with magnitude. The epistemic uncertainty due to uncertainties in kinematic inversions remains small (ϕ ∼ 0.1 in log10 units), showing that kinematic source models provide robust information to analyse the distribution of average dynamic source parameters. The proposed scaling relations may be useful to constrain friction law parameters in spontaneous dynamic rupture calculations for earthquake source studies, and physics-based near-source ground-motion prediction for seismic hazard and risk mitigation.
Resting metabolic rate in Italians : relation with body composition and anthropometric parameters
Lorenzo, de A.; Andreoli, A.; Bertoli, S.; Testolin, G.; Oriani, G.; Deurenberg, P.
2000-01-01
The objectives of this study were to obtain values for resting metabolic rate in Italians in relation to parameters of body composition, and to compare them to predicted values using the FAO/WHO/UNU equation. We performed a cross-sectional observational study of 131 healthy subjects (46 males and 85
Citation parameters of contact lens-related articles published in the ophthalmic literature.
Cardona, Genís; Sanz, Joan P
2014-09-01
This study aimed at exploring the citation parameters of contact lenses articles published in the Ophthalmology thematic category of the Journal Citation Reports (JCR). The Thompson Reuters Web of Science database was accessed to record bibliometric information and citation parameters of all journals listed under the Ophthalmology area of the 2011 JCR edition, including the journals with main publication interests in the contact lens field. In addition, the same database was used to unveil all contact lens-related articles published in 2011 in the same thematic area, whereupon differences in citation parameters between those articles published in contact lens and non-contact lens-related journals were explored. Significant differences in some bibliometric indicators such as half-life and overall citation count were found between contact lens-related journals (shorter half-life and fewer citations) and the median values for the Ophthalmology thematic area of the JCR. Visual examination of all Ophthalmology journals uncovered a total of 156 contact lens-related articles, published in 28 different journals, with 27 articles each for Contact Lens & Anterior Eye, Eye & Contact Lens, and Optometry and Vision Science. Significant differences in citation parameters were encountered between those articles published in contact lens and non-contact lens source journals. These findings, which disclosed contact lenses to be a fertile area of research, may be of interest to researchers and institutions. Differences in bibliometric indicators are of relevance to avoid unwanted bias when conducting between- and within-discipline comparisons of articles, journals, and researchers.
Serum Visfatin in Relation to Some Parameters of Iron Metabolism in ...
African Journals Online (AJOL)
1Visfatin is an adipokine mainly synthesized and secreted in visceral fat. Visfatin was found to have important proinflammatory and immunomodulating properties. The aim of the present work was to clarify the relation between plasma visfatin, some parameters of iron metabolism and insulin resistance in altered glucose ...
Directory of Open Access Journals (Sweden)
Aleshkina О.Yu.
2013-12-01
Full Text Available Objective: to determine the relation of linear parameters of the anterior cranial fossa with dimensional facial characteristics of the human skull in various craniotypes. Research Material: 100 adult skulls divided into three craniotypes have been used. Methods. Craniotopometry has been used for the measurement of the average values and the correlation model construction. Results. It has been revealed that the most significant correlation has been observed in the parameters of fleksibasilar craniotypes, in medio- and platybasilar craniotypes the multidirectional dependence of the studied parameters has been characterized as of moderate and mild degree. Conclusion. Results of research are necessary theoretical base for possible use by clinical physicians in elaboration of tactics of stereotaksichesky approach to tumoral or other pathological processes in the field of front and brain departments of a skull.
DEFF Research Database (Denmark)
Thorup, Jørgen Mogens; Kvist, Kolja; Clasen-Linde, Erik
2013-01-01
The fertility potential of boys with cryptorchidism may be related to the number of adult dark spermatogonia per tubular transverse section in testicular biopsies taken at orchiopexy. Placental-like alkaline phosphatase positive gonocytes in testes within year 1 of life indicate preserved ability...... for germ cell transformation. We related these parameters to the total number of tubular germ cells and other factors associated with fertility potential....
An Algorithm for Intelligent Sorting of CT-Related Dose Parameters
Cook, Tessa S.; Zimmerman, Stefan L.; Steingall, Scott R.; Boonn, William W.; Kim, Woojin
2011-01-01
Imaging centers nationwide are seeking innovative means to record and monitor computed tomography (CT)-related radiation dose in light of multiple instances of patient overexposure to medical radiation. As a solution, we have developed RADIANCE, an automated pipeline for extraction, archival, and reporting of CT-related dose parameters. Estimation of whole-body effective dose from CT dose length product (DLP)—an indirect estimate of radiation dose—requires anatomy-specific conversion factors ...
Carey, W.P.; Simon, Andrew
1984-01-01
Simulation of upland-soil erosion by the Precipitation-Runoff Modeling System currently requires the user to estimate two rainfall detachment parameters and three hydraulic detachmment paramenters. One rainfall detachment parameter can be estimated from rainfall simulator tests. A reformulation of the rainfall detachment equation allows the second parameter to be computed directly. The three hydraulic detachment parameters consist of one exponent and two coefficients. The initial value of the exponent is generally set equal to 1.5. The two coefficients are functions of the soil 's resistance to erosion and one of the two also accounts for sediment delivery processes not simulated in the model. Initial estimates of these parameters can be derived from other modeling studies or from published empirical relations. (USGS)
A flexible, interactive software tool for fitting the parameters of neuronal models
Directory of Open Access Journals (Sweden)
Péter eFriedrich
2014-07-01
Full Text Available The construction of biologically relevant neuronal models as well as model-based analysis of experimental data often requires the simultaneous fitting of multiple model parameters, so that the behavior of the model in a certain paradigm matches (as closely as possible the corresponding output of a real neuron according to some predefined criterion. Although the task of model optimization is often computationally hard, and the quality of the results depends heavily on technical issues such as the appropriate choice (and implementation of cost functions and optimization algorithms, no existing program provides access to the best available methods while also guiding the user through the process effectively. Our software, called Optimizer, implements a modular and extensible framework for the optimization of neuronal models, and also features a graphical interface which makes it easy for even non-expert users to handle many commonly occurring scenarios. Meanwhile, educated users can extend the capabilities of the program and customize it according to their needs with relatively little effort. Optimizer has been developed in Python, takes advantage of open-source Python modules for nonlinear optimization, and interfaces directly with the NEURON simulator to run the models. Other simulators are supported through an external interface. We have tested the program on several different types of problem of varying complexity, using different model classes. As targets, we used simulated traces from the same or a more complex model class, as well as experimental data. We successfully used Optimizer to determine passive parameters and conductance densities in compartmental models, and to fit simple (adaptive exponential integrate-and-fire neuronal models to complex biological data. Our detailed comparisons show that Optimizer can handle a wider range of problems, and delivers equally good or better performance than any other existing neuronal model fitting
Constructing Approximate Confidence Intervals for Parameters with Structural Equation Models
Cheung, Mike W. -L.
2009-01-01
Confidence intervals (CIs) for parameters are usually constructed based on the estimated standard errors. These are known as Wald CIs. This article argues that likelihood-based CIs (CIs based on likelihood ratio statistics) are often preferred to Wald CIs. It shows how the likelihood-based CIs and the Wald CIs for many statistics and psychometric…
Transformations among CE–CVM model parameters for ...
Indian Academy of Sciences (India)
Unknown
(CECs) of a higher order system in terms of those of the lower order subsystems and to an independent set of parameters which exclusively represent interactions of the higher order systems. Such a procedure is presen- ted in detail in this communication. Furthermore, the details of transformations required to express the ...
Determining Relative Importance and Effective Settings for Genetic Algorithm Control Parameters.
Mills, K L; Filliben, J J; Haines, A L
2015-01-01
Setting the control parameters of a genetic algorithm to obtain good results is a long-standing problem. We define an experiment design and analysis method to determine relative importance and effective settings for control parameters of any evolutionary algorithm, and we apply this method to a classic binary-encoded genetic algorithm (GA). Subsequently, as reported elsewhere, we applied the GA, with the control parameter settings determined here, to steer a population of cloud-computing simulators toward behaviors that reveal degraded performance and system collapse. GA-steered simulators could serve as a design tool, empowering system engineers to identify and mitigate low-probability, costly failure scenarios. In the existing GA literature, we uncovered conflicting opinions and evidence regarding key GA control parameters and effective settings to adopt. Consequently, we designed and executed an experiment to determine relative importance and effective settings for seven GA control parameters, when applied across a set of numerical optimization problems drawn from the literature. This paper describes our experiment design, analysis, and results. We found that crossover most significantly influenced GA success, followed by mutation rate and population size and then by rerandomization point and elite selection. Selection method and the precision used within the chromosome to represent numerical values had least influence. Our findings are robust over 60 numerical optimization problems.
Modelling decremental ramps using 2- and 3-parameter "critical power" models.
Morton, R Hugh; Billat, Veronique
2013-01-01
The "Critical Power" (CP) model of human bioenergetics provides a valuable way to identify both limits of tolerance to exercise and mechanisms that underpin that tolerance. It applies principally to cycling-based exercise, but with suitable adjustments for analogous units it can be applied to other exercise modalities; in particular to incremental ramp exercise. It has not yet been applied to decremental ramps which put heavy early demand on the anaerobic energy supply system. This paper details cycling-based bioenergetics of decremental ramps using 2- and 3-parameter CP models. It derives equations that, for an individual of known CP model parameters, define those combinations of starting intensity and decremental gradient which will or will not lead to exhaustion before ramping to zero; and equations that predict time to exhaustion on those decremental ramps that will. These are further detailed with suitably chosen numerical and graphical illustrations. These equations can be used for parameter estimation from collected data, or to make predictions when parameters are known.
Three-dimensional FEM model of FBGs in PANDA fibers with experimentally determined model parameters
Lindner, Markus; Hopf, Barbara; Koch, Alexander W.; Roths, Johannes
2017-04-01
A 3D-FEM model has been developed to improve the understanding of multi-parameter sensing with Bragg gratings in attached or embedded polarization maintaining fibers. The material properties of the fiber, especially Young's modulus and Poisson's ratio of the fiber's stress applying parts, are crucial for accurate simulations, but are usually not provided by the manufacturers. A methodology is presented to determine the unknown parameters by using experimental characterizations of the fiber and iterative FEM simulations. The resulting 3D-Model is capable of describing the change in birefringence of the free fiber when exposed to longitudinal strain. In future studies the 3D-FEM model will be employed to study the interaction of PANDA fibers with the surrounding materials in which they are embedded.
Local sensitivity analyses and identifiable parameter subsets were used to describe numerical constraints of a hypoxia model for bottom waters of the northern Gulf of Mexico. The sensitivity of state variables differed considerably with parameter changes, although most variables ...
On 4-degree-of-freedom biodynamic models of seated occupants: Lumped-parameter modeling
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.
Jastrzembski, Tiffany S.; Charness, Neil
2009-01-01
The authors estimate weighted mean values for nine information processing parameters for older adults using the Card, Moran, and Newell (1983) Model Human Processor model. The authors validate a subset of these parameters by modeling two mobile phone tasks using two different phones and comparing model predictions to a sample of younger (N = 20; Mage = 20) and older (N = 20; Mage = 69) adults. Older adult models fit keystroke-level performance at the aggregate grain of analysis extremely well (R = 0.99) and produced equivalent fits to previously validated younger adult models. Critical path analyses highlighted points of poor design as a function of cognitive workload, hardware/software design, and user characteristics. The findings demonstrate that estimated older adult information processing parameters are valid for modeling purposes, can help designers understand age-related performance using existing interfaces, and may support the development of age-sensitive technologies. PMID:18194048
Vernon, Ian; Liu, Junli; Goldstein, Michael; Rowe, James; Topping, Jen; Lindsey, Keith
2018-01-02
Many mathematical models have now been employed across every area of systems biology. These models increasingly involve large numbers of unknown parameters, have complex structure which can result in substantial evaluation time relative to the needs of the analysis, and need to be compared to observed data of various forms. The correct analysis of such models usually requires a global parameter search, over a high dimensional parameter space, that incorporates and respects the most important sources of uncertainty. This can be an extremely difficult task, but it is essential for any meaningful inference or prediction to be made about any biological system. It hence represents a fundamental challenge for the whole of systems biology. Bayesian statistical methodology for the uncertainty analysis of complex models is introduced, which is designed to address the high dimensional global parameter search problem. Bayesian emulators that mimic the systems biology model but which are extremely fast to evaluate are embeded within an iterative history match: an efficient method to search high dimensional spaces within a more formal statistical setting, while incorporating major sources of uncertainty. The approach is demonstrated via application to a model of hormonal crosstalk in Arabidopsis root development, which has 32 rate parameters, for which we identify the sets of rate parameter values that lead to acceptable matches between model output and observed trend data. The multiple insights into the model's structure that this analysis provides are discussed. The methodology is applied to a second related model, and the biological consequences of the resulting comparison, including the evaluation of gene functions, are described. Bayesian uncertainty analysis for complex models using both emulators and history matching is shown to be a powerful technique that can greatly aid the study of a large class of systems biology models. It both provides insight into model behaviour
Atmospheric parameters, spectral indexes and their relation to CPV spectral performance
Energy Technology Data Exchange (ETDEWEB)
Núñez, Rubén, E-mail: ruben.nunez@ies-def.upm.es; Antón, Ignacio, E-mail: ruben.nunez@ies-def.upm.es; Askins, Steve, E-mail: ruben.nunez@ies-def.upm.es; Sala, Gabriel, E-mail: ruben.nunez@ies-def.upm.es [Instituto de Energía Solar - Universidad Politécnica de Madrid, Instituto de Energía Solar, ETSI Telecomunicación, Ciudad Universitaria 28040 Madrid (Spain)
2014-09-26
Air Mass and atmosphere components (basically aerosol (AOD) and precipitable water (PW)) define the absorption of the sunlight that arrive to Earth. Radiative models such as SMARTS or MODTRAN use these parameters to generate an equivalent spectrum. However, complex and expensive instruments (as AERONET network devices) are needed to obtain AOD and PW. On the other hand, the use of isotype cells is a convenient way to characterize spectrally a place for CPV considering that they provide the photocurrent of the different internal subcells individually. Crossing data from AERONET station and a Tri-band Spectroheliometer, a model that correlates Spectral Mismatch Ratios and atmospheric parameters is proposed. Considering the amount of stations of AERONET network, this model may be used to estimate the spectral influence on energy performance of CPV systems close to all the stations worldwide.
Directory of Open Access Journals (Sweden)
O.A. Awopeju
2017-12-01
Full Text Available The study investigated the invariance properties of one, two and three parame-ter logistic item response theory models. It examined the best fit among one parameter logistic (1PL, two-parameter logistic (2PL and three-parameter logistic (3PL IRT models for SSCE, 2008 in Mathematics. It also investigated the degree of invariance of the IRT models based item difficulty parameter estimates in SSCE in Mathematics across different samples of examinees and examined the degree of invariance of the IRT models based item discrimination estimates in SSCE in Mathematics across different samples of examinees. In order to achieve the set objectives, 6000 students (3000 males and 3000 females were drawn from the population of 35262 who wrote the 2008 paper 1 Senior Secondary Certificate Examination (SSCE in Mathematics organized by National Examination Council (NECO. The item difficulty and item discrimination parameter estimates from CTT and IRT were tested for invariance using BLOG MG 3 and correlation analysis was achieved using SPSS version 20. The research findings were that two parameter model IRT item difficulty and discrimination parameter estimates exhibited invariance property consistently across different samples and that 2-parameter model was suitable for all samples of examinees unlike one-parameter model and 3-parameter model.
Numerical Modeling of Piezoelectric Transducers Using Physical Parameters
Cappon, H.; Keesman, K.J.
2012-01-01
Design of ultrasonic equipment is frequently facilitated with numerical models. These numerical models, however, need a calibration step, because usually not all characteristics of the materials used are known. Characterization of material properties combined with numerical simulations and
DEFF Research Database (Denmark)
Møller, S.; Sternberg, Claus; Poulsen, L. K.
1995-01-01
species-specific hybridizations with fluorescence-labelled ribosomal probes to estimate the single-cell concentration of RNA. By automated analysis of digitized images of stained cells, we determined four independent growth rate-related parameters: cellular RNA and DNA contents, cell volume......, and the frequency of dividing cells in a cell population. These parameters were used to compare physiological states of liquid-suspended and surfacegrowing Pseudomonas putida KT2442 in chemostat cultures. The major finding is that the correlation between substrate availability and cellular growth rate found...
Relation between the conditions of helium ion implantation and helium void equilibrium parameters
International Nuclear Information System (INIS)
Neklyudov, I.M.; Rybalko, V.F.; Ruzhitskij, V.V.; Tolstolutskaya, G.D.
1981-01-01
The conditions of helium thermodynamic equilibrium in a system of voids produced by helium ion bombardment of a metal sample are studied. As an initial equation for description of the equilibrium the Clapeyron equation was used. The equation is obtained relating basic parameters of helium voids (average diameter and density) to irradiation parameters (dose, ion energy (straggling)) and properties of the metal (surface tension coefficient, yield strength). Comparison of the calculations with experimental data on helium in nickel found in literature shows that the equation yields satisfactory resutls for the dose range 1.10 16 -1x10 17 cm -2 and temperatures T [ru
Use of multilevel modeling for determining optimal parameters of heat supply systems
Stennikov, V. A.; Barakhtenko, E. A.; Sokolov, D. V.
2017-07-01
The problem of finding optimal parameters of a heat-supply system (HSS) is in ensuring the required throughput capacity of a heat network by determining pipeline diameters and characteristics and location of pumping stations. Effective methods for solving this problem, i.e., the method of stepwise optimization based on the concept of dynamic programming and the method of multicircuit optimization, were proposed in the context of the hydraulic circuit theory developed at Melentiev Energy Systems Institute (Siberian Branch, Russian Academy of Sciences). These methods enable us to determine optimal parameters of various types of piping systems due to flexible adaptability of the calculation procedure to intricate nonlinear mathematical models describing features of used equipment items and methods of their construction and operation. The new and most significant results achieved in developing methodological support and software for finding optimal parameters of complex heat supply systems are presented: a new procedure for solving the problem based on multilevel decomposition of a heat network model that makes it possible to proceed from the initial problem to a set of interrelated, less cumbersome subproblems with reduced dimensionality; a new algorithm implementing the method of multicircuit optimization and focused on the calculation of a hierarchical model of a heat supply system; the SOSNA software system for determining optimum parameters of intricate heat-supply systems and implementing the developed methodological foundation. The proposed procedure and algorithm enable us to solve engineering problems of finding the optimal parameters of multicircuit heat supply systems having large (real) dimensionality, and are applied in solving urgent problems related to the optimal development and reconstruction of these systems. The developed methodological foundation and software can be used for designing heat supply systems in the Central and the Admiralty regions in
Development of simple kinetic models and parameter estimation for ...
African Journals Online (AJOL)
PANCHIGA
2016-09-28
Sep 28, 2016 ... by methanol. In this study, the unstructured models based on growth kinetic equation, fed-batch mass balance and constancy of cell and protein yields were developed and constructed following the substrates, glycerol and methanol. The growth model on glycerol is mostly published while the growth model ...
Parameter study of a model for NOx emissions from PFBC
DEFF Research Database (Denmark)
Jensen, Anker Degn; Johnsson, Jan Erik
1996-01-01
Simulations with a mathematical model of a pressurized bubbling fluidized bed combustor (PFBC) combined with a kinetic model for NO formation and reduction are presented and discussed. The kinetic model for NO formation and reduction considers NO and NH3 as the fixed nitrogen species, and include...
Kinetic models and parameters estimation study of biomass and ...
African Journals Online (AJOL)
The growth kinetics and modeling of ethanol production from inulin by Pichia caribbica (KC977491) were studied in a batch system. Unstructured models were proposed using the logistic equation for growth, the Luedeking-Piret equation for ethanol production and modified Leudeking-Piret model for substrate consumption.
Kinetic models and parameters estimation study of biomass and ...
African Journals Online (AJOL)
compaq
2017-01-11
Jan 11, 2017 ... The growth kinetics and modeling of ethanol production from inulin by Pichia caribbica (KC977491) were studied in a batch system. Unstructured models were proposed using the logistic equation for growth, the Luedeking-Piret equation for ethanol production and modified Leudeking-Piret model for.
Parameter estimation of electricity spot models from futures prices
Aihara, ShinIchi; Bagchi, Arunabha; Imreizeeq, E.S.N.; Walter, E.
We consider a slight perturbation of the Schwartz-Smith model for the electricity futures prices and the resulting modified spot model. Using the martingale property of the modified price under the risk neutral measure, we derive the arbitrage free model for the spot and futures prices. We estimate
Characterization of PV panel and global optimization of its model parameters using genetic algorithm
International Nuclear Information System (INIS)
Ismail, M.S.; Moghavvemi, M.; Mahlia, T.M.I.
2013-01-01
Highlights: • Genetic Algorithm optimization ability had been utilized to extract parameters of PV panel model. • Effect of solar radiation and temperature variations was taken into account in fitness function evaluation. • We used Matlab-Simulink to simulate operation of the PV-panel to validate results. • Different cases were analyzed to ascertain which of them gives more accurate results. • Accuracy and applicability of this approach to be used as a valuable tool for PV modeling were clearly validated. - Abstract: This paper details an improved modeling technique for a photovoltaic (PV) module; utilizing the optimization ability of a genetic algorithm, with different parameters of the PV module being computed via this approach. The accurate modeling of any PV module is incumbent upon the values of these parameters, as it is imperative in the context of any further studies concerning different PV applications. Simulation, optimization and the design of the hybrid systems that include PV are examples of these applications. The global optimization of the parameters and the applicability for the entire range of the solar radiation and a wide range of temperatures are achievable via this approach. The Manufacturer’s Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module. The results of single-diode and two-diode models are evaluated in order to ascertain which of them are more accurate. Other cases are also analyzed in this paper for the purpose of comparison. The Matlab–Simulink environment is used to simulate the operation of the PV module, depending on the extracted parameters. The results of the simulation are compared with the Data Sheet information, which is obtained via experimentation in order to validate the reliability of the approach. Three types of PV modules
Xi, Qing; Li, Zhao-Fu; Luo, Chuan
2014-05-01
Sensitivity analysis of hydrology and water quality parameters has a great significance for integrated model's construction and application. Based on AnnAGNPS model's mechanism, terrain, hydrology and meteorology, field management, soil and other four major categories of 31 parameters were selected for the sensitivity analysis in Zhongtian river watershed which is a typical small watershed of hilly region in the Taihu Lake, and then used the perturbation method to evaluate the sensitivity of the parameters to the model's simulation results. The results showed that: in the 11 terrain parameters, LS was sensitive to all the model results, RMN, RS and RVC were generally sensitive and less sensitive to the output of sediment but insensitive to the remaining results. For hydrometeorological parameters, CN was more sensitive to runoff and sediment and relatively sensitive for the rest results. In field management, fertilizer and vegetation parameters, CCC, CRM and RR were less sensitive to sediment and particulate pollutants, the six fertilizer parameters (FR, FD, FID, FOD, FIP, FOP) were particularly sensitive for nitrogen and phosphorus nutrients. For soil parameters, K is quite sensitive to all the results except the runoff, the four parameters of the soil's nitrogen and phosphorus ratio (SONR, SINR, SOPR, SIPR) were less sensitive to the corresponding results. The simulation and verification results of runoff in Zhongtian watershed show a good accuracy with the deviation less than 10% during 2005- 2010. Research results have a direct reference value on AnnAGNPS model's parameter selection and calibration adjustment. The runoff simulation results of the study area also proved that the sensitivity analysis was practicable to the parameter's adjustment and showed the adaptability to the hydrology simulation in the Taihu Lake basin's hilly region and provide reference for the model's promotion in China.
Parameter Uncertainty for Aircraft Aerodynamic Modeling using Recursive Least Squares
Grauer, Jared A.; Morelli, Eugene A.
2016-01-01
A real-time method was demonstrated for determining accurate uncertainty levels of stability and control derivatives estimated using recursive least squares and time-domain data. The method uses a recursive formulation of the residual autocorrelation to account for colored residuals, which are routinely encountered in aircraft parameter estimation and change the predicted uncertainties. Simulation data and flight test data for a subscale jet transport aircraft were used to demonstrate the approach. Results showed that the corrected uncertainties matched the observed scatter in the parameter estimates, and did so more accurately than conventional uncertainty estimates that assume white residuals. Only small differences were observed between batch estimates and recursive estimates at the end of the maneuver. It was also demonstrated that the autocorrelation could be reduced to a small number of lags to minimize computation and memory storage requirements without significantly degrading the accuracy of predicted uncertainty levels.
Order parameter model for unstable multilane traffic flow
Lubashevsky, Ihor A.; Mahnke, Reinhard
1999-01-01
We discuss a phenomenological approach to the description of unstable vehicle motion on multilane highways that explains in a simple way the observed sequence of the phase transitions "free flow -> synchronized motion -> jam" as well as the hysteresis in the transition "free flow synchronized motion". We introduce a new variable called order parameter that accounts for possible correlations in the vehicle motion at different lanes. So, it is principally due to the "many-body" effects in the ...
Connecting Global to Local Parameters in Barred Galaxy Models
Indian Academy of Sciences (India)
R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22
The velocity and the angular velocity units are 10 km/s and 10 km/s/kpc, respectively while G is equal to unity. Our test particle is a star of mass = 1. Therefore, the energy unit (per unit mass) is 100(km/s)2. In these units the values of the parameters are α = 12 kpc,b = 2,cb = 1.5 kpc,Md = 9500 and Mb = 3000. It is evident that ...
Aturan Asosiasi Dengan Standar Storet Pada Model Prediksi Parameter Pendukung Uji Kualitas Air Baku
Directory of Open Access Journals (Sweden)
Diana Purwitasari
2015-04-01
Full Text Available Raw Water (Air Baku laboratory analysis is testing physical, chemical and bacteriological characteristicsof water to ensure that water supply is clean, safe and ready for drinking water quality. Analyzing raw water quality in laboratorium needs more time. The proposed system could shorten the laboratory processing time by analyzing daily water production log. Association ruleinthe proposed system was used to generate relation model of water characteristicsfrom the data log provided by local government owned water utilities (PDAM, Perusahaan Daerah Air Minum. The data was transformed first from numerical data into categorical data using STOrage and RETrieval Data Warehouse (STORETstandard.Generated model needs to be simplified because some prediction rules could have the same interpretation. The generated parameter prediction modelwas sufficient to be used as the supporting data for any local policy made related to water supply and sanitationwithout additional costs from standard lab testing of water quality. Some water quality values of chemical characteristics need lab testing. Given the missing values of several chemical characteristics, the generated parameter prediction model still could give better accuracy of 80%-95%. Since PDAM staffmanually validated the generated model, the experiments used small data set.
Sun, Guodong; Peng, Fei; Mu, Mu
2017-12-01
Model parameter errors are an important cause of uncertainty in soil moisture simulation. In this study, a conditional nonlinear optimal perturbation related to parameter (CNOP-P) approach and a sophisticated land surface model (the Common Land Model, CoLM) are employed in four regions in China to explore extent of uncertainty in soil moisture simulations due to model parameter errors. The CNOP-P approach facilitates calculation of the upper bounds of uncertainty due to parameter errors and investigation of the nonlinear effects of parameter combination on uncertainties in simulation and prediction. The range of uncertainty for simulated soil moisture was found to be from 0.04 to 0.58 m3 m-3. Based on the CNOP-P approach, a new approach is applied to explore a relatively sensitive and important parameter combination for soil moisture simulations and predictions. It is found that the relatively sensitive parameter combination is region- and season-dependent. Furthermore, the results show that simulation of soil moisture could be improved if the errors in these important parameter combinations are reduced. In four study regions, the average extent of improvement (61.6%) in simulating soil moisture using the new approach based on the CNOP-P is larger than that (53.4%) using the one-at-a-time (OAT) approach. These results indicate that simulation and prediction of soil moisture is improved by considering the nonlinear effects of important physical parameter combinations. In addition, the new approach based on the CNOP-P is found to be an effective method to discern the nonlinear effects of important physical parameter combinations on numerical simulation and prediction.
DEFF Research Database (Denmark)
Suárez, Carlos Gómez; Reigosa, Paula Diaz; Iannuzzo, Francesco
2016-01-01
An original tool for parameter extraction of PSpice models has been released, enabling a simple parameter identification. A physics-based IGBT model is used to demonstrate that the optimization tool is capable of generating a set of parameters which predicts the steady-state and switching behavior...
Oxygen-18 content of modern vegetal organic matter in Senegal; relation with climatic parameters
International Nuclear Information System (INIS)
Fall, M.; Faye, A.; Aranyossy, J.F.; Saos, J.L.
1993-01-01
In Senegal, precipitations present a latitudinal repartition from 1700 mm/year in the south to 300 mm/year in the north. In this context, isotope study of Acacia albida tree-rings, sampled across the rainfall gradient, evidence significant correlation between δ 18 O in wood and relative humidity which is directly related to the rainfall, and inversely related to the temperature. Indeed, the Acacia rings δ 18 O contains a climatic information reflecting local climate parameters. (author). 18 refs, 5 figs
Estimation of temporal gait parameters using Bayesian models on acceleration signals.
López-Nava, I H; Muñoz-Meléndez, A; Pérez Sanpablo, A I; Alessi Montero, A; Quiñones Urióstegui, I; Núñez Carrera, L
2016-01-01
The purpose of this study is to develop a system capable of performing calculation of temporal gait parameters using two low-cost wireless accelerometers and artificial intelligence-based techniques as part of a larger research project for conducting human gait analysis. Ten healthy subjects of different ages participated in this study and performed controlled walking tests. Two wireless accelerometers were placed on their ankles. Raw acceleration signals were processed in order to obtain gait patterns from characteristic peaks related to steps. A Bayesian model was implemented to classify the characteristic peaks into steps or nonsteps. The acceleration signals were segmented based on gait events, such as heel strike and toe-off, of actual steps. Temporal gait parameters, such as cadence, ambulation time, step time, gait cycle time, stance and swing phase time, simple and double support time, were estimated from segmented acceleration signals. Gait data-sets were divided into two groups of ages to test Bayesian models in order to classify the characteristic peaks. The mean error obtained from calculating the temporal gait parameters was 4.6%. Bayesian models are useful techniques that can be applied to classification of gait data of subjects at different ages with promising results.
Calibration of parameters of water supply network model using genetic algorithm
Boczar, Tomasz; Adamikiewicz, Norbert; Stanisławski, Włodzimierz
2017-10-01
Computer simulation models of water supply networks are commonly applied in the water industry. As part of the research works, results of which are presented in the paper, OFF-LINE and ON-LINE calibration of water supply network model parameters using two methods was carried out and compared. The network skeleton was developed in the Epanet software. For optimization two types of dependent variables were subjected: the pressure on the node and volume flow in the network section. The first calibration method regards to application of the genetic algorithm, which is a build in plugin - "Epanet Calibrator". The second method was related to the use of function ga, which is implemented in the MATLAB toolbox Genetic Algorithm and Direct Search. The possibilities of application of these algorithms to solve the issue of optimizing the parameters of the created model of water supply network in both cases: OFF-LINE and ON-LINE calibration was examined. An analysis of the effectiveness of the considered algorithms for different values of configuration parameters was performed. Based on the achieved results it was stated that application of the ga algorithm gives higher correlation of the calibrated values to the empirical data.
DEFF Research Database (Denmark)
Frontczak, Monika Joanna
The main objective of the Ph.D. study was to examine occupants’ perception of comfort and self-estimated job performance in non-industrial buildings (homes and offices), in particular how building occupants understand comfort and which parameters, not necessarily related to indoor environments...... and storage, noise level and visual privacy. However, if job performance is considered, then satisfaction with the main indoor environmental parameters should be addressed first as they affected self-estimated job performance to the highest extent. The present study showed that overall satisfaction...... with personal workspace affected significantly the self-estimated job performance. Increasing overall satisfaction with the personal workspace by about 15% would correspond to an increase of self-estimated job performance by 3.7%. Among indoor environmental parameters and building features, satisfaction...
Age-related changes of the diffusion tensor imaging parameters of the normal cervical spinal cord
Energy Technology Data Exchange (ETDEWEB)
Wang, Kun, E-mail: medsciwangkun@126.com [Orthopedics Department, Changhai Hospital Affiliated to Second Military Medical University, Shanghai (China); Song, Qingxin; Zhang, Fan; Chen, Zhi; Hou, Canglong; Tang, Yixing [Orthopedics Department, Changhai Hospital Affiliated to Second Military Medical University, Shanghai (China); Chen, Shiyue [Radiology Department, Changhai Hospital Affiliated to Second Military Medical University, Shanghai (China); Hao, Qiang, E-mail: haoqiang@189.cn [Radiology Department, Changhai Hospital Affiliated to Second Military Medical University, Shanghai (China); Shen, Hongxing, E-mail: shenhxgk@126.com [Orthopedics Department, Changhai Hospital Affiliated to Second Military Medical University, Shanghai (China)
2014-12-15
Highlights: • It is essential to determine the DTI parameters in the whole CSC. • To analyze DTI parameters in all intervertebral space levels of the CSC. • To study the impact of age on these parameters in healthy Chinese subjects. • Provide better insights in factors that could bias the diagnosis of CSC pathologies. - Abstract: Background: The diffusion tensor imaging (DTI) parameters of the cervical spinal cord (CSC) changes with age. However, previous studies only examined specific CSC areas. Objectives: To analyze the DTI parameters in all intervertebral space levels of the whole normal CSC and to study the impact of age on these parameters in a Chinese population. Methods: Thirty-six healthy subjects aged 20–77 years were recruited. DTI parameters were calculated for gray matter (GM) and white matter (WM) funiculi in all the CSC intervertebral spaces (C1/2-C6/7). Age-related changes of DTI parameters were analyzed for the GM and WM funiculi. Results: Fractional anisotropy (FA) and mean diffusivity (MD) were lower in GM than in WM. MD and FA values were lower in the WM in the lower CSC compared with the upper CSC (all P < 0.05), but no difference was observed in GM. In ventral funiculi, MD increased with age, while FA decreased (all P < 0.001). In lateral and dorsal funiculi, MD and FA decreased with age (all P < 0.001). In GM, MD and FA decreased with age (all P < 0.001). Significant age-related changes were observed in FA and MD from GM and WM funiculi. FA was correlated with age in all funiculi (ventral: r = −0.733; lateral: r = −0.468; dorsal: r = −0.607; GM: r = −0.724; all P < 0.01). Conclusion: Important changes in MD and FA were observed with advancing age at all levels of CSC in Chinese patients. DTI parameters may be useful to assess CSC pathology, but the influence of age and segments need to be taken into account in diagnosis.
Age-related changes of the diffusion tensor imaging parameters of the normal cervical spinal cord
International Nuclear Information System (INIS)
Wang, Kun; Song, Qingxin; Zhang, Fan; Chen, Zhi; Hou, Canglong; Tang, Yixing; Chen, Shiyue; Hao, Qiang; Shen, Hongxing
2014-01-01
Highlights: • It is essential to determine the DTI parameters in the whole CSC. • To analyze DTI parameters in all intervertebral space levels of the CSC. • To study the impact of age on these parameters in healthy Chinese subjects. • Provide better insights in factors that could bias the diagnosis of CSC pathologies. - Abstract: Background: The diffusion tensor imaging (DTI) parameters of the cervical spinal cord (CSC) changes with age. However, previous studies only examined specific CSC areas. Objectives: To analyze the DTI parameters in all intervertebral space levels of the whole normal CSC and to study the impact of age on these parameters in a Chinese population. Methods: Thirty-six healthy subjects aged 20–77 years were recruited. DTI parameters were calculated for gray matter (GM) and white matter (WM) funiculi in all the CSC intervertebral spaces (C1/2-C6/7). Age-related changes of DTI parameters were analyzed for the GM and WM funiculi. Results: Fractional anisotropy (FA) and mean diffusivity (MD) were lower in GM than in WM. MD and FA values were lower in the WM in the lower CSC compared with the upper CSC (all P < 0.05), but no difference was observed in GM. In ventral funiculi, MD increased with age, while FA decreased (all P < 0.001). In lateral and dorsal funiculi, MD and FA decreased with age (all P < 0.001). In GM, MD and FA decreased with age (all P < 0.001). Significant age-related changes were observed in FA and MD from GM and WM funiculi. FA was correlated with age in all funiculi (ventral: r = −0.733; lateral: r = −0.468; dorsal: r = −0.607; GM: r = −0.724; all P < 0.01). Conclusion: Important changes in MD and FA were observed with advancing age at all levels of CSC in Chinese patients. DTI parameters may be useful to assess CSC pathology, but the influence of age and segments need to be taken into account in diagnosis
An approach to measure parameter sensitivity in watershed hydrologic modeling
U.S. Environmental Protection Agency — Abstract Hydrologic responses vary spatially and temporally according to watershed characteristics. In this study, the hydrologic models that we developed earlier...
Weibull Parameters Estimation Based on Physics of Failure Model
DEFF Research Database (Denmark)
Kostandyan, Erik; Sørensen, John Dalsgaard
2012-01-01
Reliability estimation procedures are discussed for the example of fatigue development in solder joints using a physics of failure model. The accumulated damage is estimated based on a physics of failure model, the Rainflow counting algorithm and the Miner’s rule. A threshold model is used...... for degradation modeling and failure criteria determination. The time dependent accumulated damage is assumed linearly proportional to the time dependent degradation level. It is observed that the deterministic accumulated damage at the level of unity closely estimates the characteristic fatigue life of Weibull...
The features of radiation induced lung fibrosis related with dosimetric parameters
International Nuclear Information System (INIS)
Oh, Young-Taek; Noh, O Kyu; Jang, Hyunsoo; Chun, Mison; Park, Kyung Joo; Park, Kwang Joo; Kim, Mi-Hwa; Park, Hae-Jin
2012-01-01
Background and purpose: Radiation induced lung fibrosis (RILF) is a major complication after lung irradiation and is very important for long term quality of life and could result in fatal respiratory insufficiency. However, there has been little information on dosimetric parameters for radiotherapy planning in the aspect of RILF. The features of RILF related with dosimetric parameters were evaluated. Methods and materials: Forty-eight patients with non-small cell lung carcinoma who underwent post-operative radiation therapy (PORT) without adjuvant chemotherapy were analyzed. The degree of lung fibrosis was estimated by fibrosis volume and the dosimetric parameters were calculated from the plan of 3-dimensional conformal radiotherapy. Results: The fibrosis volume and V-dose as dosimetric parameters showed significant correlation and the correlation coefficient ranged from 0.602 to 0.683 (P < 0.01). The degree of the correlation line was steeper as the dose increase and threshold dose was not found. Mean lung dose (MLD) showed strong correlation with fibrosis volume (correlation coefficient = 0.726, P < 0.01). Conclusions: The fibrosis volume is continuously increased with V-dose as the reference dose increases. MLD is useful as a single parameter for comparing rival plans in the aspect of RILF.
Farhat, I. A. H.; Alpha, C.; Gale, E.; Atia, D. Y.; Stein, A.; Isakovic, A. F.
The scaledown of magnetic tunnel junctions (MTJ) and related nanoscale spintronics devices poses unique challenges for energy optimization of their performance. We demonstrate the dependence of the switching current on the scaledown variable, while considering the influence of geometric parameters of MTJ, such as the free layer thickness, tfree, lateral size of the MTJ, w, and the anisotropy parameter of the MTJ. At the same time, we point out which values of the saturation magnetization, Ms, and anisotropy field, Hk, can lead to lowering the switching current and overall decrease of the energy needed to operate an MTJ. It is demonstrated that scaledown via decreasing the lateral size of the MTJ, while allowing some other parameters to be unconstrained, can improve energy performance by a measurable factor, shown to be the function of both geometric and physical parameters above. Given the complex interdependencies among both families of parameters, we developed a particle swarm optimization (PSO) algorithm that can simultaneously lower energy of operation and the switching current density. Results we obtained in scaledown study and via PSO optimization are compared to experimental results. Support by Mubadala-SRC 2012-VJ-2335 is acknowledged, as are staff at Cornell-CNF and BNL-CFN.
The Effect of Nondeterministic Parameters on Shock-Associated Noise Prediction Modeling
Dahl, Milo D.; Khavaran, Abbas
2010-01-01
Engineering applications for aircraft noise prediction contain models for physical phenomenon that enable solutions to be computed quickly. These models contain parameters that have an uncertainty not accounted for in the solution. To include uncertainty in the solution, nondeterministic computational methods are applied. Using prediction models for supersonic jet broadband shock-associated noise, fixed model parameters are replaced by probability distributions to illustrate one of these methods. The results show the impact of using nondeterministic parameters both on estimating the model output uncertainty and on the model spectral level prediction. In addition, a global sensitivity analysis is used to determine the influence of the model parameters on the output, and to identify the parameters with the least influence on model output.
Parameter Estimation and Prediction of a Nonlinear Storage Model: an algebraic approach
Doeswijk, T.G.; Keesman, K.J.
2005-01-01
Generally, parameters that are nonlinear in system models are estimated by nonlinear least-squares optimization algorithms. In this paper, if a nonlinear discrete-time model with a polynomial quotient structure in input, output, and parameters, a method is proposed to re-parameterize the model such
Identification of the 1PL Model with Guessing Parameter: Parametric and Semi-Parametric Results
San Martin, Ernesto; Rolin, Jean-Marie; Castro, Luis M.
2013-01-01
In this paper, we study the identification of a particular case of the 3PL model, namely when the discrimination parameters are all constant and equal to 1. We term this model, 1PL-G model. The identification analysis is performed under three different specifications. The first specification considers the abilities as unknown parameters. It is…
Directory of Open Access Journals (Sweden)
Céline Bonnyaud
Full Text Available The timed up and go test (TUG is a functional test which is increasingly used to evaluate patients with stroke. The outcome measured is usually global TUG performance-time. Assessment of spatiotemporal and kinematic parameters during the Oriented gait and Turn sub-tasks of the TUG would provide a better understanding of the mechanisms underlying patients' performance and therefore may help to guide rehabilitation. The aim of this study was thus to determine the spatiotemporal and kinematic parameters which were most related to the walking and turning sub-tasks of TUG performance in stroke patients.29 stroke patients carried out the TUG test which was recorded using an optoelectronic system in two conditions: spontaneous and standardized condition (standardized foot position and instructed to turn towards the paretic side. They also underwent a clinical assessment. Stepwise regression was used to determine the parameters most related to Oriented gait and Turn sub-tasks. Relationships between explanatory parameters of Oriented gait and Turn performance and clinical scales were evaluated using Spearman correlations.Step length and cadence explained 82% to 95% of the variance for the walking sub-tasks in both conditions. Percentage single support phase and contralateral swing phase (depending on the condition respectively explained 27% and 56% of the variance during the turning sub-task in the spontaneous and standardized conditions.Step length, cadence, percentage of paretic single support phase and non-paretic swing phase, as well as dynamic stability were the main parameters related to TUG performance and they should be targeted in rehabilitation.
HMM filtering and parameter estimation of an electricity spot price model
International Nuclear Information System (INIS)
Erlwein, Christina; Benth, Fred Espen; Mamon, Rogemar
2010-01-01
In this paper we develop a model for electricity spot price dynamics. The spot price is assumed to follow an exponential Ornstein-Uhlenbeck (OU) process with an added compound Poisson process. In this way, the model allows for mean-reversion and possible jumps. All parameters are modulated by a hidden Markov chain in discrete time. They are able to switch between different economic regimes representing the interaction of various factors. Through the application of reference probability technique, adaptive filters are derived, which in turn, provide optimal estimates for the state of the Markov chain and related quantities of the observation process. The EM algorithm is applied to find optimal estimates of the model parameters in terms of the recursive filters. We implement this self-calibrating model on a deseasonalised series of daily spot electricity prices from the Nordic exchange Nord Pool. On the basis of one-step ahead forecasts, we found that the model is able to capture the empirical characteristics of Nord Pool spot prices. (author)
Stochastic models and reliability parameter estimation applicable to nuclear power plant safety
International Nuclear Information System (INIS)
Mitra, S.P.
1979-01-01
A set of stochastic models and related estimation schemes for reliability parameters are developed. The models are applicable for evaluating reliability of nuclear power plant systems. Reliability information is extracted from model parameters which are estimated from the type and nature of failure data that is generally available or could be compiled in nuclear power plants. Principally, two aspects of nuclear power plant reliability have been investigated: (1) The statistical treatment of inplant component and system failure data; (2) The analysis and evaluation of common mode failures. The model inputs are failure data which have been classified as either the time type of failure data or the demand type of failure data. Failures of components and systems in nuclear power plant are, in general, rare events.This gives rise to sparse failure data. Estimation schemes for treating sparse data, whenever necessary, have been considered. The following five problems have been studied: 1) Distribution of sparse failure rate component data. 2) Failure rate inference and reliability prediction from time type of failure data. 3) Analyses of demand type of failure data. 4) Common mode failure model applicable to time type of failure data. 5) Estimation of common mode failures from 'near-miss' demand type of failure data
Acosta Santamaría, Víctor Andrés; Malvè, M; Duizabo, A; Mena Tobar, A; Gallego Ferrer, G; García Aznar, J M; Doblaré, M; Ochoa, I
2013-11-01
The application of three-dimensional (3D) biomaterials to facilitate the adhesion, proliferation, and differentiation of cells has been widely studied for tissue engineering purposes. The fabrication methods used to improve the mechanical response of the scaffold produce complex and non regular structures. Apart from the mechanical aspect, the fluid behavior in the inner part of the scaffold should also be considered. Parameters such as permeability (k) or wall shear stress (WSS) are important aspects in the provision of nutrients, the removal of metabolic waste products or the mechanically-induced differentiation of cells attached in the trabecular network of the scaffolds. Experimental measurements of these parameters are not available in all labs. However, fluid parameters should be known prior to other types of experiments. The present work compares an experimental study with a computational fluid dynamics (CFD) methodology to determine the related fluid parameters (k and WSS) of complex non regular poly(L-lactic acid) scaffolds based only on the treatment of microphotographic images obtained with a microCT (μCT). The CFD analysis shows similar tendencies and results with low relative difference compared to those of the experimental study, for high flow rates. For low flow rates the accuracy of this prediction reduces. The correlation between the computational and experimental results validates the robustness of the proposed methodology.
Connecting Global to Local Parameters in Barred Galaxy Models
Indian Academy of Sciences (India)
R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22
Abstract. We present connections between global and local parame- ters in a realistic dynamical model, describing motion in a barred galaxy. Expanding the global model in the vicinity of a stable Lagrange point, we find the potential of a two-dimensional perturbed harmonic oscillator, which describes local motion near the ...
Mathematical modelling in blood coagulation : simulation and parameter estimation
W.J.H. Stortelder (Walter); P.W. Hemker (Piet); H.C. Hemker
1997-01-01
textabstractThis paper describes the mathematical modelling of a part of the blood coagulation mechanism. The model includes the activation of factor X by a purified enzyme from Russel's Viper Venom (RVV), factor V and prothrombin, and also comprises the inactivation of the products formed. In this
Personalization of models with many model parameters: an efficient sensitivity analysis approach.