Reflector modelization for neutronic diffusion and parameters identification

International Nuclear Information System (INIS)

Argaud, J.P.

1993-04-01

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

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

Prediction of chemical, physical and sensory data from process parameters for frozen cod using multivariate analysis

DEFF Research Database (Denmark)

Bechmann, Iben Ellegaard; Jensen, H.S.; Bøknæs, Niels

1998-01-01

Physical, chemical and sensory quality parameters were determined for 115 cod (Gadus morhua) samples stored under varying frozen storage conditions. Five different process parameters (period of frozen storage, frozen storage. temperature, place of catch, season for catching and state of rigor) were...... varied systematically at two levels. The data obtained were evaluated using the multivariate methods, principal component analysis (PCA) and partial least squares (PLS) regression. The PCA models were used to identify which process parameters were actually most important for the quality of the frozen cod....... PLS models that were able to predict the physical, chemical and sensory quality parameters from the process parameters of the frozen raw material were generated. The prediction abilities of the PLS models were good enough to give reasonable results even when the process parameters were characterised...

Using Perturbed Physics Ensembles and Machine Learning to Select Parameters for Reducing Regional Biases in a Global Climate Model

Science.gov (United States)

Li, S.; Rupp, D. E.; Hawkins, L.; Mote, P.; McNeall, D. J.; Sarah, S.; Wallom, D.; Betts, R. A.

2017-12-01

This study investigates the potential to reduce known summer hot/dry biases over Pacific Northwest in the UK Met Office's atmospheric model (HadAM3P) by simultaneously varying multiple model parameters. The bias-reduction process is done through a series of steps: 1) Generation of perturbed physics ensemble (PPE) through the volunteer computing network weather@home; 2) Using machine learning to train "cheap" and fast statistical emulators of climate model, to rule out regions of parameter spaces that lead to model variants that do not satisfy observational constraints, where the observational constraints (e.g., top-of-atmosphere energy flux, magnitude of annual temperature cycle, summer/winter temperature and precipitation) are introduced sequentially; 3) Designing a new PPE by "pre-filtering" using the emulator results. Steps 1) through 3) are repeated until results are considered to be satisfactory (3 times in our case). The process includes a sensitivity analysis to find dominant parameters for various model output metrics, which reduces the number of parameters to be perturbed with each new PPE. Relative to observational uncertainty, we achieve regional improvements without introducing large biases in other parts of the globe. Our results illustrate the potential of using machine learning to train cheap and fast statistical emulators of climate model, in combination with PPEs in systematic model improvement.

Modelling hydrodynamic parameters to predict flow assisted corrosion

International Nuclear Information System (INIS)

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

1992-01-01

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

It's the parameters, stupid! Moving beyond multi-model and multi-physics approaches to characterize and reduce predictive uncertainty in process-based hydrological models

Science.gov (United States)

Clark, Martyn; Samaniego, Luis; Freer, Jim

2014-05-01

Multi-model and multi-physics approaches are a popular tool in environmental modelling, with many studies focusing on optimally combining output from multiple model simulations to reduce predictive errors and better characterize predictive uncertainty. However, a careful and systematic analysis of different hydrological models reveals that individual models are simply small permutations of a master modeling template, and inter-model differences are overwhelmed by uncertainty in the choice of the parameter values in the model equations. Furthermore, inter-model differences do not explicitly represent the uncertainty in modeling a given process, leading to many situations where different models provide the wrong results for the same reasons. In other cases, the available morphological data does not support the very fine spatial discretization of the landscape that typifies many modern applications of process-based models. To make the uncertainty characterization problem worse, the uncertain parameter values in process-based models are often fixed (hard-coded), and the models lack the agility necessary to represent the tremendous heterogeneity in natural systems. This presentation summarizes results from a systematic analysis of uncertainty in process-based hydrological models, where we explicitly analyze the myriad of subjective decisions made throughout both the model development and parameter estimation process. Results show that much of the uncertainty is aleatory in nature - given a "complete" representation of dominant hydrologic processes, uncertainty in process parameterizations can be represented using an ensemble of model parameters. Epistemic uncertainty associated with process interactions and scaling behavior is still important, and these uncertainties can be represented using an ensemble of different spatial configurations. Finally, uncertainty in forcing data can be represented using ensemble methods for spatial meteorological analysis. Our systematic

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

Estimating Parameters in Physical Models through Bayesian Inversion: A Complete Example

KAUST Repository

Allmaras, Moritz; Bangerth, Wolfgang; Linhart, Jean Marie; Polanco, Javier; Wang, Fang; Wang, Kainan; Webster, Jennifer; Zedler, Sarah

2013-01-01

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

Predictive modeling of coupled multi-physics systems: II. Illustrative application to reactor physics

International Nuclear Information System (INIS)

Cacuci, Dan Gabriel; Badea, Madalina Corina

2014-01-01

Highlights: • We applied the PMCMPS methodology to a paradigm neutron diffusion model. • We underscore the main steps in applying PMCMPS to treat very large coupled systems. • PMCMPS reduces the uncertainties in the optimally predicted responses and model parameters. • PMCMPS is for sequentially treating coupled systems that cannot be treated simultaneously. - Abstract: This work presents paradigm applications to reactor physics of the innovative mathematical methodology for “predictive modeling of coupled multi-physics systems (PMCMPS)” developed by Cacuci (2014). This methodology enables the assimilation of experimental and computational information and computes optimally predicted responses and model parameters with reduced predicted uncertainties, taking fully into account the coupling terms between the multi-physics systems, but using only the computational resources that would be needed to perform predictive modeling on each system separately. The paradigm examples presented in this work are based on a simple neutron diffusion model, chosen so as to enable closed-form solutions with clear physical interpretations. These paradigm examples also illustrate the computational efficiency of the PMCMPS, which enables the assimilation of additional experimental information, with a minimal increase in computational resources, to reduce the uncertainties in predicted responses and best-estimate values for uncertain model parameters, thus illustrating how very large systems can be treated without loss of information in a sequential rather than simultaneous manner

Systematic parameter inference in stochastic mesoscopic modeling

Energy Technology Data Exchange (ETDEWEB)

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

2017-02-01

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

Lumped-parameter models

Energy Technology Data Exchange (ETDEWEB)

Ibsen, Lars Bo; Liingaard, M.

2006-12-15

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

Thermodynamic study of fluid in terms of equation of state containing physical parameters

International Nuclear Information System (INIS)

Khasare, S. B.

2015-01-01

We introduce a simple condition for one mole fluid by considering the thermodynamics of molecules pointing towards the effective potential for the cluster. Efforts are made to estimate new physical parameter f in liquid state using the equation of state containing only two physical parameters such as the hard sphere diameter and binding energy. The temperature dependence of the structural properties and the thermodynamic behavior of the clusters are studied. Computations based on f predict the variation of numbers of particles at the contact point of the molecular cavity (radial distribution function). From the thermodynamic profile of the fluid, the model results are discussed in terms of the cavity due to the closed surface along with suitable energy. The present calculation is based upon the sample thermodynamic data for n-hexanol, such as the ultrasonic wave, density, volume expansion coefficient, and ratio of specific heat in the liquid state, and it is consistent with the thermodynamic relations containing physical parameters such as size and energy. Since the data is restricted to n-hexanol, we avoid giving the physical meaning of f, which is the key parameter studied in the present work. (paper)

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

Science.gov (United States)

Wentworth, Mami Tonoe

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

Effect of long-term physical aging on the kinetic parameters in a common pharmaceutical drug: Flutab

International Nuclear Information System (INIS)

Abu-Sehly, A.A.; Elabbar, A.A.

2011-01-01

Differential scanning calorimetry (DSC) measurements were performed to investigate the effects of long-term physical aging on kinetic parameters of the pharmaceutical drug (Flutab). Kinetics parameters such as activation energy (E) and fragility parameter (m) of the glass transition for aged and rejuvenated glasses were determined using different kinetic models. Evidence of variation of E with temperature is presented. It is shown in this work that natural storage of the drug introduced significant physical aging as indicated by changes in the glass transition temperature, activation energy and fragility parameter.

Parameter Extraction for PSpice Models by means of an Automated Optimization Tool – An IGBT model Study Case

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 behavio...

Modelling of cardiovascular system: development of a hybrid (numerical-physical) model.

Science.gov (United States)

Ferrari, G; Kozarski, M; De Lazzari, C; Górczyńska, K; Mimmo, R; Guaragno, M; Tosti, G; Darowski, M

2003-12-01

Physical models of the circulation are used for research, training and for testing of implantable active and passive circulatory prosthetic and assistance devices. However, in comparison with numerical models, they are rigid and expensive. To overcome these limitations, we have developed a model of the circulation based on the merging of a lumped parameter physical model into a numerical one (producing therefore a hybrid). The physical model is limited to the barest essentials and, in this application, developed to test the principle, it is a windkessel representing the systemic arterial tree. The lumped parameters numerical model was developed in LabVIEW environment and represents pulmonary and systemic circulation (except the systemic arterial tree). Based on the equivalence between hydraulic and electrical circuits, this prototype was developed connecting the numerical model to an electrical circuit--the physical model. This specific solution is valid mainly educationally but permits the development of software and the verification of preliminary results without using cumbersome hydraulic circuits. The interfaces between numerical and electrical circuits are set up by a voltage controlled current generator and a voltage controlled voltage generator. The behavior of the model is analyzed based on the ventricular pressure-volume loops and on the time course of arterial and ventricular pressures and flow in different circulatory conditions. The model can represent hemodynamic relationships in different ventricular and circulatory conditions.

The application of model with lumped parameters for transient condition analyses of NPP

International Nuclear Information System (INIS)

Stankovic, B.; Stevanovic, V.

1985-01-01

The transient behaviour of NPP Krsko during the accident of pressurizer spray valve stuck open has been simulated y lumped parameters model of the PWR coolant system components, developed at the faculty of Mechanical Engineering, University of Belgrade. The elementary volumes which are characterised by the process and state parameters, and by junctions which are characterised by the geometrical and flow parameters are basic structure of physical model. The process parameters obtained by the model RESI, show qualitative agreement with the measured valves, in a degree in which the actions of reactor safety engineered system and emergency core cooling system are adequately modelled; in spite of the elementary physical model structure and only the modelling of thermal process in reactor core and equilibrium conditions of pressurizer and steam generator. The pressurizer pressure and liquid level predicted by the non-equilibrium pressurizer model SOP show good agreement until the HIPS (high pressure pumps) is activated. (author)

Efimov Physics and the Three-Body Parameter within a Two-Channel Framework

DEFF Research Database (Denmark)

Sørensen, Peder Klokmose; V. Fedorov, D.; S. Jensen, A.

2012-01-01

scaling laws. We recover known results for broad Feshbach resonances with small effective range, whereas in the case of narrow resonances we find a distinct non-monotonic behavior of the threshold at which the lowest Efimov trimer merges with the three-body continuum. To address the issue of the physical...... origin of the three-body parameter we provide a physically clear model for the relation between three-body physics and typical two-body atom-atom interactions. Our results demonstrate that experimental information from narrow Feshbach resonances and/or mixed systems are of vital importance to pin down...... the relation of two- and three-body physics in atomic systems....

A Bayesian approach for parameter estimation and prediction using a computationally intensive model

International Nuclear Information System (INIS)

Higdon, Dave; McDonnell, Jordan D; Schunck, Nicolas; Sarich, Jason; Wild, Stefan M

2015-01-01

Bayesian methods have been successful in quantifying uncertainty in physics-based problems in parameter estimation and prediction. In these cases, physical measurements y are modeled as the best fit of a physics-based model η(θ), where θ denotes the uncertain, best input setting. Hence the statistical model is of the form y=η(θ)+ϵ, where ϵ accounts for measurement, and possibly other, error sources. When nonlinearity is present in η(⋅), the resulting posterior distribution for the unknown parameters in the Bayesian formulation is typically complex and nonstandard, requiring computationally demanding computational approaches such as Markov chain Monte Carlo (MCMC) to produce multivariate draws from the posterior. Although generally applicable, MCMC requires thousands (or even millions) of evaluations of the physics model η(⋅). This requirement is problematic if the model takes hours or days to evaluate. To overcome this computational bottleneck, we present an approach adapted from Bayesian model calibration. This approach combines output from an ensemble of computational model runs with physical measurements, within a statistical formulation, to carry out inference. A key component of this approach is a statistical response surface, or emulator, estimated from the ensemble of model runs. We demonstrate this approach with a case study in estimating parameters for a density functional theory model, using experimental mass/binding energy measurements from a collection of atomic nuclei. We also demonstrate how this approach produces uncertainties in predictions for recent mass measurements obtained at Argonne National Laboratory. (paper)

Redundant and physical black hole parameters: Is there an independent physical dilaton charge?

Energy Technology Data Exchange (ETDEWEB)

Hajian, K., E-mail: kamalhajian@ipm.ir; Sheikh-Jabbari, M.M., E-mail: jabbari@theory.ipm.ac.ir

2017-05-10

Black holes as solutions to gravity theories, are generically identified by a set of parameters. Some of these parameters are associated with black hole physical conserved charges, like ADM charges. There can also be some “redundant parameters.” We propose necessary conditions for a parameter to be physical. The conditions are essentially integrability and non-triviality of the charge variations arising from “parametric variations,” variation of the solution with respect to the chosen parameters. In addition, we prove that variation of the redundant parameters which do not meet our criteria do not appear in the first law of thermodynamics. As an interesting application, we show that dilaton moduli are redundant parameters for black hole solutions to Einstein–Maxwell–(Axion)–Dilaton theories, because variations in dilaton moduli would render entropy, mass, electric charges or angular momenta non-integrable. Our results are in contrast with modification of the first law due to scalar charges suggested in Gibbons–Kallosh–Kol paper and its follow-ups. We also briefly discuss implications of our results for the attractor behavior of extremal black holes.

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

International Nuclear Information System (INIS)

LigePza, P.

2005-01-01

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

Predictive modeling of coupled multi-physics systems: I. Theory

International Nuclear Information System (INIS)

Cacuci, Dan Gabriel

2014-01-01

Highlights: • We developed “predictive modeling of coupled multi-physics systems (PMCMPS)”. • PMCMPS reduces predicted uncertainties in predicted model responses and parameters. • PMCMPS treats efficiently very large coupled systems. - Abstract: This work presents an innovative mathematical methodology for “predictive modeling of coupled multi-physics systems (PMCMPS).” This methodology takes into account fully the coupling terms between the systems but requires only the computational resources that would be needed to perform predictive modeling on each system separately. The PMCMPS methodology uses the maximum entropy principle to construct an optimal approximation of the unknown a priori distribution based on a priori known mean values and uncertainties characterizing the parameters and responses for both multi-physics models. This “maximum entropy”-approximate a priori distribution is combined, using Bayes’ theorem, with the “likelihood” provided by the multi-physics simulation models. Subsequently, the posterior distribution thus obtained is evaluated using the saddle-point method to obtain analytical expressions for the optimally predicted values for the multi-physics models parameters and responses along with corresponding reduced uncertainties. Noteworthy, the predictive modeling methodology for the coupled systems is constructed such that the systems can be considered sequentially rather than simultaneously, while preserving exactly the same results as if the systems were treated simultaneously. Consequently, very large coupled systems, which could perhaps exceed available computational resources if treated simultaneously, can be treated with the PMCMPS methodology presented in this work sequentially and without any loss of generality or information, requiring just the resources that would be needed if the systems were treated sequentially

Physical plausibility of cold star models satisfying Karmarkar conditions

Energy Technology Data Exchange (ETDEWEB)

Fuloria, Pratibha [Kumaun University, Physics Dept., Almora (India); Pant, Neeraj [N.D.A., Maths Dept., Khadakwasla, Pune (India)

2017-11-15

In the present article, we have obtained a new well behaved solution to Einstein's field equations in the background of Karmarkar spacetime. The solution has been used for stellar modelling within the demand of current observational evidences. All the physical parameters are well behaved inside the stellar interior and our model satisfies all the required conditions to be physically realizable. The obtained compactness parameter is within the Buchdahl limit, i.e. 2M/R ≤ 8/9. The TOV equation is well maintained inside the fluid spheres. The stability of the models has been further confirmed by using Herrera's cracking method. The models proposed in the present work are compatible with observational data of compact objects 4U1608-52 and PSRJ1903+327. The necessary graphs have been shown to authenticate the physical viability of our models. (orig.)

Physical plausibility of cold star models satisfying Karmarkar conditions

International Nuclear Information System (INIS)

Fuloria, Pratibha; Pant, Neeraj

2017-01-01

In the present article, we have obtained a new well behaved solution to Einstein's field equations in the background of Karmarkar spacetime. The solution has been used for stellar modelling within the demand of current observational evidences. All the physical parameters are well behaved inside the stellar interior and our model satisfies all the required conditions to be physically realizable. The obtained compactness parameter is within the Buchdahl limit, i.e. 2M/R ≤ 8/9. The TOV equation is well maintained inside the fluid spheres. The stability of the models has been further confirmed by using Herrera's cracking method. The models proposed in the present work are compatible with observational data of compact objects 4U1608-52 and PSRJ1903+327. The necessary graphs have been shown to authenticate the physical viability of our models. (orig.)

Physical plausibility of cold star models satisfying Karmarkar conditions

Science.gov (United States)

Fuloria, Pratibha; Pant, Neeraj

2017-11-01

In the present article, we have obtained a new well behaved solution to Einstein's field equations in the background of Karmarkar spacetime. The solution has been used for stellar modelling within the demand of current observational evidences. All the physical parameters are well behaved inside the stellar interior and our model satisfies all the required conditions to be physically realizable. The obtained compactness parameter is within the Buchdahl limit, i.e. 2M/R ≤ 8/9 . The TOV equation is well maintained inside the fluid spheres. The stability of the models has been further confirmed by using Herrera's cracking method. The models proposed in the present work are compatible with observational data of compact objects 4U1608-52 and PSRJ1903+327. The necessary graphs have been shown to authenticate the physical viability of our models.

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

International Nuclear Information System (INIS)

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

2012-01-01

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

Regionalising Parameters of a Conceptual Rainfall-Runoff Model for ...

African Journals Online (AJOL)

IHACRES, a lumped conceptual rainfall-runoff model, was calibrated to six catchments ranging in size from 49km2 to 600 km2 within the upper Tana River basin to obtain a set of model parameters that characterise the hydrological behaviour within the region. Physical catchment attributes indexing topography, soil and ...

Physically Active Men Show Better Semen Parameters than Their Sedentary Counterparts.

Science.gov (United States)

Lalinde-Acevedo, Paula C; Mayorga-Torres, B Jose Manuel; Agarwal, Ashok; du Plessis, Stefan S; Ahmad, Gulfam; Cadavid, Ángela P; Cardona Maya, Walter D

2017-10-01

The quality of semen depends upon several factors such as environment, life style, physical activity, age, and occupation. The aim of this study was to analyze and compare the conventional and functional semen parameters in men practicing vigorous physical activity to those of sedentary men. In this descriptive cross-sectional study, semen samples of 17 physically active men and 15 sedentary men were collected for analysis. Semen analysis was performed according to the World Health Organization (WHO) guidelines, while functional parameters were evaluated by flow cytometry. Results showed that several semen parameters (semen volume, viability, progressive motility, total motility, normal morphology, and moribund cells) were superior in the physically active group in comparison with the sedentary group. Semen parameters such as viability, progressive motility and total motility, as well as the percentage of moribund spermatozoa were significantly different between both groups. However, sperm DNA damage, lipid peroxidation and mitochondrial potential were not significantly different among the groups. Nevertheless, the physical activity shows better semen parameters than sedentary group. Taken together, our results demonstrate that regular physical activity has beneficial impact in sperm fertility parameters and such a life style can enhance the fertility status of men. Copyright© by Royan Institute. All rights reserved.

Redundant and physical black hole parameters: Is there an independent physical dilaton charge?

Directory of Open Access Journals (Sweden)

K. Hajian

2017-05-01

Full Text Available Black holes as solutions to gravity theories, are generically identified by a set of parameters. Some of these parameters are associated with black hole physical conserved charges, like ADM charges. There can also be some “redundant parameters.” We propose necessary conditions for a parameter to be physical. The conditions are essentially integrability and non-triviality of the charge variations arising from “parametric variations,” variation of the solution with respect to the chosen parameters. In addition, we prove that variation of the redundant parameters which do not meet our criteria do not appear in the first law of thermodynamics. As an interesting application, we show that dilaton moduli are redundant parameters for black hole solutions to Einstein–Maxwell–(Axion–Dilaton theories, because variations in dilaton moduli would render entropy, mass, electric charges or angular momenta non-integrable. Our results are in contrast with modification of the first law due to scalar charges suggested in Gibbons–Kallosh–Kol paper [1] and its follow-ups. We also briefly discuss implications of our results for the attractor behavior of extremal black holes.

Acceleration parameters for fluid physics with accelerating bodies

CSIR Research Space (South Africa)

Gledhill, Irvy MA

2016-06-01

Full Text Available to an acceleration parameter that appears to be new in fluid physics, but is known in cosmology. A selection of cases for rectilinear acceleration has been chosen to illustrate the point that this parameter alone does not govern regimes of flow about significantly...

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.

LMJ target implosions: sensitivity of the acceptable gain to physical parameters and simplification of the radiative transport model

International Nuclear Information System (INIS)

Charpin, C.; Bonnefille, M.; Charrier, A.; Giorla, J.; Holstein, P.A.; Malinie, G.

2000-01-01

Our study is in line with the robustness of the LMJ target and the definition of safety margins. It is based on the determination of the 'acceptable gain', defined as 75% of the nominal gain. We have tested the sensitivity of the gain to physical and numerical parameters in the case of deteriorated implosions, i.e. when implosion conditions are not optimized. Moreover, we have simplified the radiative transport model, which enabled us to save a lot of computing time. All our calculations were done with the Lagrangian code FCI2 in a very simplified configuration. (authors)

Experimental determination of some equilibrium parameter of Damavand tokamak by magnetic probe measurements for representing a physical model for plasma vertical movement.

Science.gov (United States)

Farahani, N Darestani; Davani, F Abbasi

2015-10-01

This investigation is about plasma modeling for the control of vertical instabilities in Damavand tokamak. This model is based on online magnetic measurement. The algebraic equation defining the vertical position in this model is based on instantaneous force-balance. Two parameters in this equation, including decay index, n, and lambda, Λ, have been considered as functions of time-varying poloidal field coil currents and plasma current. Then these functions have been used in a code generated for modeling the open loop response of plasma. The main restriction of the suitability analysis of the model is that the experiments always have to be performed in the presence of a control loop for stabilizing vertical position. As a result, open loop response of the system has been identified from closed loop experimental data by nonlinear neural network identification method. The results of comparison of physical model with identified open loop response from closed loop experiments show root mean square error percentage less than 10%. The results are satisfying that the physical model is useful as a Damavand tokamak vertical movement simulator.

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

Physical and numerical modeling of Joule-heated melters

Energy Technology Data Exchange (ETDEWEB)

Eyler, L.L.; Skarda, R.J.; Crowder, R.S. III; Trent, D.S.; Reid, C.R.; Lessor, D.L.

1985-10-01

The Joule-heated ceramic-lined melter is an integral part of the high level waste immobilization process under development by the US Department of Energy. Scaleup and design of this waste glass melting furnace requires an understanding of the relationships between melting cavity design parameters and the furnace performance characteristics such as mixing, heat transfer, and electrical requirements. Developing empirical models of these relationships through actual melter testing with numerous designs would be a very costly and time consuming task. Additionally, the Pacific Northwest Laboratory (PNL) has been developing numerical models that simulate a Joule-heated melter for analyzing melter performance. This report documents the method used and results of this modeling effort. Numerical modeling results are compared with the more conventional, physical modeling results to validate the approach. Also included are the results of numerically simulating an operating research melter at PNL. Physical Joule-heated melters modeling results used for qualiying the simulation capabilities of the melter code included: (1) a melter with a single pair of electrodes and (2) a melter with a dual pair (two pairs) of electrodes. The physical model of the melter having two electrode pairs utilized a configuration with primary and secondary electrodes. The principal melter parameters (the ratio of power applied to each electrode pair, modeling fluid depth, electrode spacing) were varied in nine tests of the physical model during FY85. Code predictions were made for five of these tests. Voltage drops, temperature field data, and electric field data varied in their agreement with the physical modeling results, but in general were judged acceptable. 14 refs., 79 figs., 17 tabs.

Physical and numerical modeling of Joule-heated melters

International Nuclear Information System (INIS)

Eyler, L.L.; Skarda, R.J.; Crowder, R.S. III; Trent, D.S.; Reid, C.R.; Lessor, D.L.

1985-10-01

The Joule-heated ceramic-lined melter is an integral part of the high level waste immobilization process under development by the US Department of Energy. Scaleup and design of this waste glass melting furnace requires an understanding of the relationships between melting cavity design parameters and the furnace performance characteristics such as mixing, heat transfer, and electrical requirements. Developing empirical models of these relationships through actual melter testing with numerous designs would be a very costly and time consuming task. Additionally, the Pacific Northwest Laboratory (PNL) has been developing numerical models that simulate a Joule-heated melter for analyzing melter performance. This report documents the method used and results of this modeling effort. Numerical modeling results are compared with the more conventional, physical modeling results to validate the approach. Also included are the results of numerically simulating an operating research melter at PNL. Physical Joule-heated melters modeling results used for qualiying the simulation capabilities of the melter code included: (1) a melter with a single pair of electrodes and (2) a melter with a dual pair (two pairs) of electrodes. The physical model of the melter having two electrode pairs utilized a configuration with primary and secondary electrodes. The principal melter parameters (the ratio of power applied to each electrode pair, modeling fluid depth, electrode spacing) were varied in nine tests of the physical model during FY85. Code predictions were made for five of these tests. Voltage drops, temperature field data, and electric field data varied in their agreement with the physical modeling results, but in general were judged acceptable. 14 refs., 79 figs., 17 tabs

A stochastic optimization model under modeling uncertainty and parameter certainty for groundwater remediation design-Part I. Model development

Energy Technology Data Exchange (ETDEWEB)

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

2010-04-15

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

Sensitivity of physics parameters for establishment of a burned CANDU full-core model for decommissioning waste characterization

International Nuclear Information System (INIS)

Cho, Dong-Keun; Sun, Gwang-Min; Choi, Jongwon; Hwang, Dong-Hyun; Hwang, Tae-Won; Yang, Ho-Yeon; Park, Dong-Hwan

2011-01-01

The sensitivity of parameters related with reactor physics on the source terms of decommissioning wastes from a CANDU reactor was investigated in order to find a viable, simplified burned core model of a Monte Carlo simulation for decommissioning waste characterization. First, a sensitivity study was performed for the level of nuclide consideration in an irradiated fuel and implicit geometry modeling, the effects of side structural components of the core, and structural supporters for reactive devices. The overall effects for computation memory, calculation time, and accuracy were then investigated with a full-core model. From the results, it was revealed that the level of nuclide consideration and geometry homogenization are not important factors when the ratio of macroscopic neutron absorption cross section (MNAC) relative to a total value exceeded 0.95. The most important factor affecting the neutron flux of the pressure tube was shown to be the structural supporters for reactivity devices, showing an 10% difference. Finally, it was concluded that a bundle-average homogeneous model considering a MNAC of 0.95, which is the simplest model in this study, could be a viable approximate model, with about 25% lower computation memory, 40% faster simulation time, and reasonable engineering accuracy compared with a model with an explicit geometry employing an MNAC of 0.99. (author)

PWR surveillance based on correspondence between empirical models and physical

International Nuclear Information System (INIS)

Zwingelstein, G.; Upadhyaya, B.R.; Kerlin, T.W.

1976-01-01

An on line surveillance method based on the correspondence between empirical models and physicals models is proposed for pressurized water reactors. Two types of empirical models are considered as well as the mathematical models defining the correspondence between the physical and empirical parameters. The efficiency of this method is illustrated for the surveillance of the Doppler coefficient for Oconee I (an 886 MWe PWR) [fr

Experimental kinetic parameters in the thermo-fluid-dynamic modelling of coal combustion

International Nuclear Information System (INIS)

Migliavacca, G.; Perini, M.; Parodi, E.

2001-01-01

The designing and the optimisation of modern and efficient combustion systems are nowadays frequently based on calculation tools for mathematical modelling, which are able to predict the evolution of the process starting from the first principles of physics. Otherwise, in many cases, specific experimental parameters are needed to describe the specific nature of the materials considered in the calculations. It is especially true in the modelling of coal combustion, which is a complex process strongly dependent on the chemical and physical features of the fuel. This paper describes some experimental techniques used to estimate the fundamental kinetic parameters of coal combustion and shows how this data may be introduced in a model calculation to predict the pollutant emissions from a real scale combustion plant [it

A three-dimensional cohesive sediment transport model with data assimilation: Model development, sensitivity analysis and parameter estimation

Science.gov (United States)

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

2018-06-01

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

Some feature of interpretation of tension single pulsed electromagnetic field of the Earth to create the model parameter fields physical properties

Directory of Open Access Journals (Sweden)

Mokritskaya T.P.

2014-12-01

Full Text Available Stochastic analysis of the results of different methods of obtaining and processing of information allows us to solve problems on a qualitatively different level. This is important when creating complex earth models and fields of its parameters, particularly the physical properties. Application of remote sensing methods (geophysical investigations with the registration of a single pulse intensity of the electromagnetic field of the Earth (EIEMPZ seismic profiling, is expanding. Interesting results of the joint interpretation of the results of geophysical and laboratory studies of physical soil. Interesting results of the joint interpretation of the results of geophysical and laboratory studies of physical soil. For the first time a methodology for assessing the state of the soil [3] applied for a joint interpretation of materials determine the field strength EMPZ, seismic profiling, and laboratory techniques. This has allowed to characterize the state of the geological environment and to build a model of inhomogeneous density distribution of fractured rocks at depth. In this paper we made a mathematical analysis of the results of research and talus deposits eluvial clay Taurian series, studied at one of the construction sites southern coast at a depth of 12.0 -25.0 m. Methods of statistical analysis, assessment of homogeneity and symmetrically distributed, rank correlation and multiple regression analysis described in [3]. The analysis of the spatial distribution of areas extrem value of EMPZ, heterogeneity of seismic rigidity. Statistical characteristics of indicators of physical properties reflect the genetic characteristics of the formation and the current state of silty-clay sediments of different genesis.It is proved that the regression model can be applied to interpret the state of the array in the construction of geodynamic model. It is established that the creation of forward-looking (dynamic models for the distribution of the physical

Identification of Physical Parameters for A Hydraulic Robot

DEFF Research Database (Denmark)

Madsen, Henrik; Zhou, Jianjun; Hansen, Lars Henrik

1997-01-01

This paper describes a case study of identifying the physical model of a hydraulic test robot. The obtained model is intended to provide a basis for model-based control of the robot. The physical model is formulated in continuous time and is derived by application of the laws of physics...

On the effect of model parameters on forecast objects

Science.gov (United States)

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

2018-04-01

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

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

Science.gov (United States)

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

2018-06-01

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

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)

Physically-based slope stability modelling and parameter sensitivity: a case study in the Quitite and Papagaio catchments, Rio de Janeiro, Brazil

Science.gov (United States)

de Lima Neves Seefelder, Carolina; Mergili, Martin

2016-04-01

conservative than those yielded with the infinite slope stability model. The sensitivity of AUCROC to variations in the geohydraulic parameters remains small as long as the calculated degree of saturation of the soils is sufficient to result in the prediction of a significant amount of landslide release pixels. Due to the poor sensitivity of AUCROC to variations of the geotechnical and geohydraulic parameters it is hard to optimize the parameters by means of statistics. Instead, the results produced with many different combinations of parameters correspond reasonably well with the distribution of the observed landslide release areas, even though they vary considerably in terms of their conservativeness. Considering the uncertainty inherent in all geotechnical and geohydraulic data, and the impossibility to capture the spatial distribution of the parameters by means of laboratory tests in sufficient detail, we conclude that landslide susceptibility maps yielded by catchment-scale physically-based models should not be interpreted in absolute terms. Building on the assumption that our findings are generally valid, we suggest that efforts to develop better strategies for dealing with the uncertainties in the spatial variation of the key parameters should be given priority in future slope stability modelling efforts.

A stochastic optimization model under modeling uncertainty and parameter certainty for groundwater remediation design--part I. Model development.

Science.gov (United States)

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

2010-04-15

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

A parameter optimization tool for evaluating the physical consistency of the plot-scale water budget of the integrated eco-hydrological model GEOtop in complex terrain

Science.gov (United States)

Bertoldi, Giacomo; Cordano, Emanuele; Brenner, Johannes; Senoner, Samuel; Della Chiesa, Stefano; Niedrist, Georg

2017-04-01

In mountain regions, the plot- and catchment-scale water and energy budgets are controlled by a complex interplay of different abiotic (i.e. topography, geology, climate) and biotic (i.e. vegetation, land management) controlling factors. When integrated, physically-based eco-hydrological models are used in mountain areas, there are a large number of parameters, topographic and boundary conditions that need to be chosen. However, data on soil and land-cover properties are relatively scarce and do not reflect the strong variability at the local scale. For this reason, tools for uncertainty quantification and optimal parameters identification are essential not only to improve model performances, but also to identify most relevant parameters to be measured in the field and to evaluate the impact of different assumptions for topographic and boundary conditions (surface, lateral and subsurface water and energy fluxes), which are usually unknown. In this contribution, we present the results of a sensitivity analysis exercise for a set of 20 experimental stations located in the Italian Alps, representative of different conditions in terms of topography (elevation, slope, aspect), land use (pastures, meadows, and apple orchards), soil type and groundwater influence. Besides micrometeorological parameters, each station provides soil water content at different depths, and in three stations (one for each land cover) eddy covariance fluxes. The aims of this work are: (I) To present an approach for improving calibration of plot-scale soil moisture and evapotranspiration (ET). (II) To identify the most sensitive parameters and relevant factors controlling temporal and spatial differences among sites. (III) Identify possible model structural deficiencies or uncertainties in boundary conditions. Simulations have been performed with the GEOtop 2.0 model, which is a physically-based, fully distributed integrated eco-hydrological model that has been specifically designed for mountain

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...

Moisture removal of paddy by agricultural residues: basic physical parameters and drying kinetics modeling

Directory of Open Access Journals (Sweden)

Saniso, E.

2007-05-01

Full Text Available The objectives of this research were to study basic physical parameters of three agricultural residues that could be used for prediction of paddy drying kinetics using desiccants, to investigate a suitable methodfor moisture reduction of fresh paddy using 3 absorbents, and to modify the drying model of Inoue et al. for determining the evolution of moisture transfer during the drying period. Rice husk, sago palm rachis andcoconut husk were used as moisture desiccants in these experiments. From the results, it was concluded that the apparent density of all adsorbents was a linear function of moisture content whilst an equilibriummoisture content equation following Hendersonís model gave the best fit to the experimental results. From studying the relationship between moisture ratio and drying time under the condition of drying temperaturesof 30, 50 and 70oC, air flow rate of 1.6 m/s and initial moisture content of absorbents of 15, 20 and 27% dry-basis, it was shown that the moisture ratio decreased when drying time increased. In addition, thethin-layer desiccant drying equation following of the Page model can appropriately explain the evolution of moisture content of paddy over the drying time. The diffusion coefficient of all absorbents, which was in therange of 1x10-8 to 6x10-8 m2/h, was relatively dependent on drying temperature and inversely related to drying time. The diffusivity of coconut husk had the highest value compared to the other absorbents.The simulating modified mathematical model to determine drying kinetics of paddy using absorption technique and the simulated results had good relation to the experimental results for all adsorbents.

Physical parameters and biological effects of the LVR-15 epithermal neutron beam

International Nuclear Information System (INIS)

Burian, J.; Marek, M.; Rejchrt, J.; Viererbl, L.; Gambarini, G.; Mares, V.; Vanossi, E.; Judas, L.

2006-01-01

Monitoring of the physical and biological properties of the epithermal neutron beam constructed at the multipurpose LVR-15 nuclear reactor for NCT therapy of brain tumors showed that its physical and biological properties are stable in time and independent on an ad hoc reconfiguration of the reactor core before its therapeutic use. Physical parameters were monitored by measurement of the neutron spectrum, neutron profile, fast neutron kerma rate in tissue and photon absorbed dose, the gel dosimetry was used with the group of standard measurement methods. The RBE of the beam, as evaluated by 3 different biological models, including mouse intestine crypt regeneration assay, germinative zones of the immature rat brain and C6 glioma cells in culture, ranged from 1.70 to 1.99. (author)

Simplified Models for LHC New Physics Searches

CERN Document Server

Alves, Daniele; Arora, Sanjay; Bai, Yang; Baumgart, Matthew; Berger, Joshua; Buckley, Matthew; Butler, Bart; Chang, Spencer; Cheng, Hsin-Chia; Cheung, Clifford; Chivukula, R.Sekhar; Cho, Won Sang; Cotta, Randy; D'Alfonso, Mariarosaria; El Hedri, Sonia; Essig, Rouven; Evans, Jared A.; Fitzpatrick, Liam; Fox, Patrick; Franceschini, Roberto; Freitas, Ayres; Gainer, James S.; Gershtein, Yuri; Gray, Richard; Gregoire, Thomas; Gripaios, Ben; Gunion, Jack; Han, Tao; Haas, Andy; Hansson, Per; Hewett, JoAnne; Hits, Dmitry; Hubisz, Jay; Izaguirre, Eder; Kaplan, Jared; Katz, Emanuel; Kilic, Can; Kim, Hyung-Do; Kitano, Ryuichiro; Koay, Sue Ann; Ko, Pyungwon; Krohn, David; Kuflik, Eric; Lewis, Ian; Lisanti, Mariangela; Liu, Tao; Liu, Zhen; Lu, Ran; Luty, Markus; Meade, Patrick; Morrissey, David; Mrenna, Stephen; Nojiri, Mihoko; Okui, Takemichi; Padhi, Sanjay; Papucci, Michele; Park, Michael; Park, Myeonghun; Perelstein, Maxim; Peskin, Michael; Phalen, Daniel; Rehermann, Keith; Rentala, Vikram; Roy, Tuhin; Ruderman, Joshua T.; Sanz, Veronica; Schmaltz, Martin; Schnetzer, Stephen; Schuster, Philip; Schwaller, Pedro; Schwartz, Matthew D.; Schwartzman, Ariel; Shao, Jing; Shelton, Jessie; Shih, David; Shu, Jing; Silverstein, Daniel; Simmons, Elizabeth; Somalwar, Sunil; Spannowsky, Michael; Spethmann, Christian; Strassler, Matthew; Su, Shufang; Tait, Tim; Thomas, Brooks; Thomas, Scott; Toro, Natalia; Volansky, Tomer; Wacker, Jay; Waltenberger, Wolfgang; Yavin, Itay; Yu, Felix; Zhao, Yue; Zurek, Kathryn

2012-01-01

This document proposes a collection of simplified models relevant to the design of new-physics searches at the LHC and the characterization of their results. Both ATLAS and CMS have already presented some results in terms of simplified models, and we encourage them to continue and expand this effort, which supplements both signature-based results and benchmark model interpretations. A simplified model is defined by an effective Lagrangian describing the interactions of a small number of new particles. Simplified models can equally well be described by a small number of masses and cross-sections. These parameters are directly related to collider physics observables, making simplified models a particularly effective framework for evaluating searches and a useful starting point for characterizing positive signals of new physics. This document serves as an official summary of the results from the "Topologies for Early LHC Searches" workshop, held at SLAC in September of 2010, the purpose of which was to develop a...

Image quality - physical and diagnostic parameters. The radiologist's viewpoint

International Nuclear Information System (INIS)

Stender, H.St.

1985-01-01

The quality of a radiograph is determined by the diagnostic information it provides. This depends upon the visual detection of diagnostically relevant structures. The technical radiographic requirements are dependent upon the physical measurements and the physiological and optical conditions. Such physical factors as spatial resolution, contrast and noise are quantitative measurements, which must be oriented to the qualitative visual characteristics of the radiograph. The influence of subjective perception and complexity of structural noise on the detectability of details and structures particularly demands attention. Since radiographic quality depends upon the detection of diagnostically relevant structure and features, it is important to define these parameters on the basis of extensive radiographic analysis and the corresponding clinical findings. The diagnostically relevant radiographic parameters and image details and critical structures have been worked out for the examination of the lungs, colon, stomach, urinary tract and skeleton. Good image quality requires coordination of the physical-technical parameters with the visual ability of the observer, since only in this way can the diagnostic information be represented with sufficient clarity. (author)

Stochasticity effects on derivation of physical parameters of unresolved star clusters

OpenAIRE

de Meulenaer, Philippe; Narbutis, Donatas; Mineikis, Tadas; Vansevičius, Vladas

2013-01-01

We developed a method for a fast modeling of broad-band UBVRI integrated magnitudes of unresolved star clusters and used it to derive their physical parameters (age, mass, and extinction). The method was applied on M33 galaxy cluster sample and consistency of ages and masses derived from unresolved observations with the values derived from resolved stellar photometry was demonstrated. We found that interstellar extinction causes minor age-extinction degeneracy for the studied sample due to a ...

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

Science.gov (United States)

Abali, B. Emek

2018-04-01

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

A Parameter Identification Method for Helicopter Noise Source Identification and Physics-Based Semi-Empirical Modeling

Science.gov (United States)

Greenwood, Eric, II; Schmitz, Fredric H.

2010-01-01

A new physics-based parameter identification method for rotor harmonic noise sources is developed using an acoustic inverse simulation technique. This new method allows for the identification of individual rotor harmonic noise sources and allows them to be characterized in terms of their individual non-dimensional governing parameters. This new method is applied to both wind tunnel measurements and ground noise measurements of two-bladed rotors. The method is shown to match the parametric trends of main rotor Blade-Vortex Interaction (BVI) noise, allowing accurate estimates of BVI noise to be made for operating conditions based on a small number of measurements taken at different operating conditions.

Sensitivity analysis and calibration of a dynamic physically based slope stability model

Science.gov (United States)

Zieher, Thomas; Rutzinger, Martin; Schneider-Muntau, Barbara; Perzl, Frank; Leidinger, David; Formayer, Herbert; Geitner, Clemens

2017-06-01

Physically based modelling of slope stability on a catchment scale is still a challenging task. When applying a physically based model on such a scale (1 : 10 000 to 1 : 50 000), parameters with a high impact on the model result should be calibrated to account for (i) the spatial variability of parameter values, (ii) shortcomings of the selected model, (iii) uncertainties of laboratory tests and field measurements or (iv) parameters that cannot be derived experimentally or measured in the field (e.g. calibration constants). While systematic parameter calibration is a common task in hydrological modelling, this is rarely done using physically based slope stability models. In the present study a dynamic, physically based, coupled hydrological-geomechanical slope stability model is calibrated based on a limited number of laboratory tests and a detailed multitemporal shallow landslide inventory covering two landslide-triggering rainfall events in the Laternser valley, Vorarlberg (Austria). Sensitive parameters are identified based on a local one-at-a-time sensitivity analysis. These parameters (hydraulic conductivity, specific storage, angle of internal friction for effective stress, cohesion for effective stress) are systematically sampled and calibrated for a landslide-triggering rainfall event in August 2005. The identified model ensemble, including 25 behavioural model runs with the highest portion of correctly predicted landslides and non-landslides, is then validated with another landslide-triggering rainfall event in May 1999. The identified model ensemble correctly predicts the location and the supposed triggering timing of 73.0 % of the observed landslides triggered in August 2005 and 91.5 % of the observed landslides triggered in May 1999. Results of the model ensemble driven with raised precipitation input reveal a slight increase in areas potentially affected by slope failure. At the same time, the peak run-off increases more markedly, suggesting that

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

Errors and parameter estimation in precipitation-runoff modeling: 1. Theory

Science.gov (United States)

Troutman, Brent M.

1985-01-01

Errors in complex conceptual precipitation-runoff models may be analyzed by placing them into a statistical framework. This amounts to treating the errors as random variables and defining the probabilistic structure of the errors. By using such a framework, a large array of techniques, many of which have been presented in the statistical literature, becomes available to the modeler for quantifying and analyzing the various sources of error. A number of these techniques are reviewed in this paper, with special attention to the peculiarities of hydrologic models. Known methodologies for parameter estimation (calibration) are particularly applicable for obtaining physically meaningful estimates and for explaining how bias in runoff prediction caused by model error and input error may contribute to bias in parameter estimation.

Influential input parameters for reflood model of MARS code

Energy Technology Data Exchange (ETDEWEB)

Oh, Deog Yeon; Bang, Young Seok [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)

2012-10-15

Best Estimate (BE) calculation has been more broadly used in nuclear industries and regulations to reduce the significant conservatism for evaluating Loss of Coolant Accident (LOCA). Reflood model has been identified as one of the problems in BE calculation. The objective of the Post BEMUSE Reflood Model Input Uncertainty Methods (PREMIUM) program of OECD/NEA is to make progress the issue of the quantification of the uncertainty of the physical models in system thermal hydraulic codes, by considering an experimental result especially for reflood. It is important to establish a methodology to identify and select the parameters influential to the response of reflood phenomena following Large Break LOCA. For this aspect, a reference calculation and sensitivity analysis to select the dominant influential parameters for FEBA experiment are performed.

Modeling and Extraction of Parameters Based on Physical Effects in Bipolar Transistors

Directory of Open Access Journals (Sweden)

Agnes Nagy

2011-01-01

Full Text Available The rising complexity of electronic systems, the reduction of components size, and the increment of working frequencies demand every time more accurate and stable integrated circuits, which require more precise simulation programs during the design process. PSPICE, widely used to simulate the general behavior of integrated circuits, does not consider many of the physical effects that can be found in real devices. Compact models, HICUM and MEXTRAM, have been developed over recent decades, in order to eliminate this deficiency. This paper presents some of the physical aspects that have not been studied so far, such as the expression of base-emitter voltage, including the emitter emission coefficient effect (n, physical explanation and simulation procedure, as well as a new extraction method for the diffusion potential VDE(T, based on the forward biased base-emitter capacitance, showing excellent agreement between experimental and theoretical results.

Merging physical parameters and laboratory subjective ratings for the soundscape assessment of urban squares.

Science.gov (United States)

Brambilla, Giovanni; Maffei, Luigi; Di Gabriele, Maria; Gallo, Veronica

2013-07-01

An experimental study was carried out in 20 squares in the center of Rome, covering a wide range of different uses, sonic environments, geometry, and architectural styles. Soundwalks along the perimeter of each square were performed during daylight and weekdays taking binaural and video recordings, as well as spot measurements of illuminance. The cluster analysis performed on the physical parameters, not only acoustic, provided two clusters that are in satisfactory agreement with the "a priori" classification. Applying the principal component analysis (PCA) to five physical parameters, two main components were obtained which might be associated to two environmental features, namely, "chaotic/calm" and "open/enclosed." On the basis of these two features, six squares were selected for the laboratory audio-video tests where 32 subjects took part filling in a questionnaire. The PCA performed on the subjective ratings on the sonic environment showed two main components which might be associated to two emotional meanings, namely, "calmness" and "vibrancy." The linear regression modeling between five objective parameters and the mean value of subjective ratings on chaotic/calm and enclosed/open attributes showed a good correlation. Notwithstanding these interesting results being limited to the specific data set, it is worth pointing out that the complexity of the soundscape quality assessment can be more comprehensively examined merging the field measurements of physical parameters with the subjective ratings provided by field and/or laboratory tests.

A physics-based fractional order model and state of energy estimation for lithium ion batteries. Part II: Parameter identification and state of energy estimation for LiFePO4 battery

Science.gov (United States)

Li, Xiaoyu; Pan, Ke; Fan, Guodong; Lu, Rengui; Zhu, Chunbo; Rizzoni, Giorgio; Canova, Marcello

2017-11-01

State of energy (SOE) is an important index for the electrochemical energy storage system in electric vehicles. In this paper, a robust state of energy estimation method in combination with a physical model parameter identification method is proposed to achieve accurate battery state estimation at different operating conditions and different aging stages. A physics-based fractional order model with variable solid-state diffusivity (FOM-VSSD) is used to characterize the dynamic performance of a LiFePO4/graphite battery. In order to update the model parameter automatically at different aging stages, a multi-step model parameter identification method based on the lexicographic optimization is especially designed for the electric vehicle operating conditions. As the battery available energy changes with different applied load current profiles, the relationship between the remaining energy loss and the state of charge, the average current as well as the average squared current is modeled. The SOE with different operating conditions and different aging stages are estimated based on an adaptive fractional order extended Kalman filter (AFEKF). Validation results show that the overall SOE estimation error is within ±5%. The proposed method is suitable for the electric vehicle online applications.

Post-BEMUSE Reflood Model Input Uncertainty Methods (PREMIUM) Benchmark Phase II: Identification of Influential Parameters

International Nuclear Information System (INIS)

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

2015-01-01

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

Parameter optimization for surface flux transport models

Science.gov (United States)

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

2017-11-01

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

Evaluating performances of simplified physically based landslide susceptibility models.

Science.gov (United States)

Capparelli, Giovanna; Formetta, Giuseppe; Versace, Pasquale

2015-04-01

Rainfall induced shallow landslides cause significant damages involving loss of life and properties. Prediction of shallow landslides susceptible locations is a complex task that involves many disciplines: hydrology, geotechnical science, geomorphology, and statistics. Usually to accomplish this task two main approaches are used: statistical or physically based model. This paper presents a package of GIS based models for landslide susceptibility analysis. It was integrated in the NewAge-JGrass hydrological model using the Object Modeling System (OMS) modeling framework. The package includes three simplified physically based models for landslides susceptibility analysis (M1, M2, and M3) and a component for models verifications. It computes eight goodness of fit indices (GOF) by comparing pixel-by-pixel model results and measurements data. Moreover, the package integration in NewAge-JGrass allows the use of other components such as geographic information system tools to manage inputs-output processes, and automatic calibration algorithms to estimate model parameters. The system offers the possibility to investigate and fairly compare the quality and the robustness of models and models parameters, according a procedure that includes: i) model parameters estimation by optimizing each of the GOF index separately, ii) models evaluation in the ROC plane by using each of the optimal parameter set, and iii) GOF robustness evaluation by assessing their sensitivity to the input parameter variation. This procedure was repeated for all three models. The system was applied for a case study in Calabria (Italy) along the Salerno-Reggio Calabria highway, between Cosenza and Altilia municipality. The analysis provided that among all the optimized indices and all the three models, Average Index (AI) optimization coupled with model M3 is the best modeling solution for our test case. This research was funded by PON Project No. 01_01503 "Integrated Systems for Hydrogeological Risk

Effect of Drawer Master Modeling of ZPPR15 Phase A Reactor Physics Experiment on Integral Parameter

International Nuclear Information System (INIS)

Yoo, Jae Woon; Kim, Sang Ji

2011-01-01

As a part of an International-Nuclear Engineering Research Initiative (I-NERI) Project, KAERI and ANL are analyzing the ZPPR-15 reactor physics experiments. The ZPPR-15 experiments were carried out in support of the Integral Fast Reactor (IFR) project. Because of lack of the experimental data, verifying and validating the core neutronics analysis code for metal fueled sodium cooled fast reactors (SFR) has been one of the big concerns. KAERI is developing the metal fuel loaded SFR and plans to construct the demonstration SFR by around 2028. Database built through this project and its result of analysis will play an important role in validating the SFR neutronics characteristics. As the first year work of I-NERI project, KAERI analyzed ZPPR-15 Phase A experiment among four phases (Phase A to D). The effect of a drawer master modeling on the integral parameter was investigated. The approximated benchmark configurations for each loading were constructed to be used for validating a deterministic code

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

DEFF Research Database (Denmark)

Spann, Robert; Roca, Christophe; Kold, David

2017-01-01

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

Quality assessment and artificial neural networks modeling for characterization of chemical and physical parameters of potable water.

Science.gov (United States)

Salari, Marjan; Salami Shahid, Esmaeel; Afzali, Seied Hosein; Ehteshami, Majid; Conti, Gea Oliveri; Derakhshan, Zahra; Sheibani, Solmaz Nikbakht

2018-04-22

Today, due to the increase in the population, the growth of industry and the variety of chemical compounds, the quality of drinking water has decreased. Five important river water quality properties such as: dissolved oxygen (DO), total dissolved solids (TDS), total hardness (TH), alkalinity (ALK) and turbidity (TU) were estimated by parameters such as: electric conductivity (EC), temperature (T), and pH that could be measured easily with almost no costs. Simulate water quality parameters were examined with two methods of modeling include mathematical and Artificial Neural Networks (ANN). Mathematical methods are based on polynomial fitting with least square method and ANN modeling algorithms are feed-forward networks. All conditions/circumstances covered by neural network modeling were tested for all parameters in this study, except for Alkalinity. All optimum ANN models developed to simulate water quality parameters had precision value as R-value close to 0.99. The ANN model extended to simulate alkalinity with R-value equals to 0.82. Moreover, Surface fitting techniques were used to refine data sets. Presented models and equations are reliable/useable tools for studying water quality parameters at similar rivers, as a proper replacement for traditional water quality measuring equipment's. Copyright © 2018 Elsevier Ltd. All rights reserved.

Structural observability analysis and EKF based parameter estimation of building heating models

Directory of Open Access Journals (Sweden)

D.W.U. Perera

2016-07-01

Full Text Available Research for enhanced energy-efficient buildings has been given much recognition in the recent years owing to their high energy consumptions. Increasing energy needs can be precisely controlled by practicing advanced controllers for building Heating, Ventilation, and Air-Conditioning (HVAC systems. Advanced controllers require a mathematical building heating model to operate, and these models need to be accurate and computationally efficient. One main concern associated with such models is the accurate estimation of the unknown model parameters. This paper presents the feasibility of implementing a simplified building heating model and the computation of physical parameters using an off-line approach. Structural observability analysis is conducted using graph-theoretic techniques to analyze the observability of the developed system model. Then Extended Kalman Filter (EKF algorithm is utilized for parameter estimates using the real measurements of a single-zone building. The simulation-based results confirm that even with a simple model, the EKF follows the state variables accurately. The predicted parameters vary depending on the inputs and disturbances.

The spectroscopic orbits and physical parameters of GG Carinae

Science.gov (United States)

Marchiano, P.; Brandi, E.; Muratore, M. F.; Quiroga, C.; Ferrer, O. E.; García, L. G.

2012-04-01

Aims: GG Car is an eclipsing binary classified as a B[e] supergiant star. The aims of our study are to improve the orbital elements of the binary system in order to obtain the actual orbital period of this system. We also compare the spectral energy distribution of the observed fluxes over a wide wavelength range with a model of a circumstellar envelope composed of gas and dust. This fitting allows us to derive the physical parameters of the system and its environment, as well as to obtain an estimation of the distance to GG Car. Methods: We analyzed about 55 optical and near infrared spectrograms taken during 1996-2010. The spectroscopic orbits were obtained by measuring the radial velocities of the blueshifted absorptions of the He I P-Cygni profiles, which are very representative of the orbital motion of both stars. On the other hand, we modeled the spectral energy distribution of GG Car, proposing a simple model of a spherical envelope consisting of a layer close to the central star composed of ionized gas and other outermost layers composed of dust. Its effect on the spectral energy distribution considering a central B-type star is presented. Comparing the model with the observed continuum energy distribution of GG Car, we can derive fundamental parameters of the system, as well as global physical properties of the gas and dust envelope. It is also possible to estimate the distance taking the spectral regions into account where the theoretical data fit the observational data very well and using the set of parameters obtained and the value of the observed flux for different wavelengths. Results: For the first time, we have determined the orbits for both components of the binary through a detailed study of the He I lines, at λλ4471, 5875, 6678, and 7065 Å, thereby obtaining an orbital period of 31.033 days. An eccentric orbit with e = 0.28 and a mass ratio q = 2.2 ± 0.9 were calculated. Comparing the model with the observed continuum energy distribution of

Chemical Abundances and Physical Parameters of H II Regions in the Magellanic Clouds

Science.gov (United States)

Reyes, R. E. C.

The chemical abundances and physical parameters of H II regions are important pa rameters to determine in order to understand how stars and galaxies evolve. The Magellanic Clouds offer us a unique oportunity to persue such studies in low metallicity galaxies. In this contribution we present the results of the photoionization modeling of 5 H II regions in each of the Large Magellanic Cloud (LMC) and Small Magellanic Cloud (SMC) sys tems. Optical data were collected from the literature, complemented by our own observa tions (Carlos Reyes et al. 1998), including UV spectra from the new IUE data ban k and infrared fluxes from the IRAS satellite. The chemical abundances of He, C, N, O, Ne, S, Ar and physical parameters like the densities, the ionized masses, the luminosities, the ionization temperatures , the filling factor and optical depth are determined. A comparison of the abundances of these HII regions with those of typical planetary nebulae and supergiants stars is also presented.

A Fundamental Parameter-Based Calibration Model for an Intrinsic Germanium X-Ray Fluorescence Spectrometer

DEFF Research Database (Denmark)

Christensen, Leif Højslet; Pind, Niels

1982-01-01

A matrix-independent fundamental parameter-based calibration model for an energy-dispersive X-ray fluorescence spectrometer has been developed. This model, which is part of a fundamental parameter approach quantification method, accounts for both the excitation and detection probability. For each...... secondary target a number of relative calibration constants are calculated on the basis of knowledge of the irradiation geometry, the detector specifications, and tabulated fundamental physical parameters. The absolute calibration of the spectrometer is performed by measuring one pure element standard per...

Objective Tuning of Model Parameters in CAM5 Across Different Spatial Resolutions

Science.gov (United States)

Bulaevskaya, V.; Lucas, D. D.

2014-12-01

Parameterizations of physical processes in climate models are highly dependent on the spatial and temporal resolution and must be tuned for each resolution under consideration. At high spatial resolutions, objective methods for parameter tuning are computationally prohibitive. Our work has focused on calibrating parameters in the Community Atmosphere Model 5 (CAM5) for three spatial resolutions: 1, 2, and 4 degrees. Using perturbed-parameter ensembles and uncertainty quantification methodology, we have identified input parameters that minimize discrepancies of energy fluxes simulated by CAM5 across the three resolutions and with respect to satellite observations. We are also beginning to exploit the parameter-resolution relationships to objectively tune parameters in a high-resolution version of CAM5 by leveraging cheaper, low-resolution simulations and statistical models. We will present our approach to multi-resolution climate model parameter tuning, as well as the key findings. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344 and was supported from the DOE Office of Science through the Scientific Discovery Through Advanced Computing (SciDAC) project on Multiscale Methods for Accurate, Efficient, and Scale-Aware Models of the Earth System.

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

Science.gov (United States)

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

2017-01-01

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

Predicting the activity coefficients of free-solvent for concentrated globular protein solutions using independently determined physical parameters.

Directory of Open Access Journals (Sweden)

Devin W McBride

Full Text Available The activity coefficient is largely considered an empirical parameter that was traditionally introduced to correct the non-ideality observed in thermodynamic systems such as osmotic pressure. Here, the activity coefficient of free-solvent is related to physically realistic parameters and a mathematical expression is developed to directly predict the activity coefficients of free-solvent, for aqueous protein solutions up to near-saturation concentrations. The model is based on the free-solvent model, which has previously been shown to provide excellent prediction of the osmotic pressure of concentrated and crowded globular proteins in aqueous solutions up to near-saturation concentrations. Thus, this model uses only the independently determined, physically realizable quantities: mole fraction, solvent accessible surface area, and ion binding, in its prediction. Predictions are presented for the activity coefficients of free-solvent for near-saturated protein solutions containing either bovine serum albumin or hemoglobin. As a verification step, the predictability of the model for the activity coefficient of sucrose solutions was evaluated. The predicted activity coefficients of free-solvent are compared to the calculated activity coefficients of free-solvent based on osmotic pressure data. It is observed that the predicted activity coefficients are increasingly dependent on the solute-solvent parameters as the protein concentration increases to near-saturation concentrations.

Optimization of a Cu CMP process modeling parameters of nanometer integrated circuits

International Nuclear Information System (INIS)

Ruan Wenbiao; Chen Lan; Ma Tianyu; Fang Jingjing; Zhang He; Ye Tianchun

2012-01-01

A copper chemical mechanical polishing (Cu CMP) process is reviewed and analyzed from the view of chemical physics. Three steps Cu CMP process modeling is set up based on the actual process of manufacturing and pattern-density-step-height (PDSH) modeling from MIT. To catch the pattern dependency, a 65 nm testing chip is designed and processed in the foundry. Following the model parameter extraction procedure, the model parameters are extracted and verified by testing data from the 65 nm testing chip. A comparison of results between the model predictions and test data show that the former has the same trend as the latter and the largest deviation is less than 5 nm. Third party testing data gives further evidence to support the great performance of model parameter optimization. Since precise CMP process modeling is used for the design of manufacturability (DFM) checks, critical hotspots are displayed and eliminated, which will assure good yield and production capacity of IC. (semiconductor technology)

Inhalation Exposure Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

M. Wasiolek

2006-06-05

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

Inhalation Exposure Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

M. Wasiolek

2006-01-01

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

LHC Higgs physics beyond the Standard Model

International Nuclear Information System (INIS)

Spannowsky, M.

2007-01-01

The Large Hadron Collider (LHC) at CERN will be able to perform proton collisions at a much higher center-of-mass energy and luminosity than any other collider. Its main purpose is to detect the Higgs boson, the last unobserved particle of the Standard Model, explaining the riddle of the origin of mass. Studies have shown, that for the whole allowed region of the Higgs mass processes exist to detect the Higgs at the LHC. However, the Standard Model cannot be a theory of everything and is not able to provide a complete understanding of physics. It is at most an effective theory up to a presently unknown energy scale. Hence, extensions of the Standard Model are necessary which can affect the Higgs-boson signals. We discuss these effects in two popular extensions of the Standard Model: the Minimal Supersymmetric Standard Model (MSSM) and the Standard Model with four generations (SM4G). Constraints on these models come predominantly from flavor physics and electroweak precision measurements. We show, that the SM4G is still viable and that a fourth generation has strong impact on decay and production processes of the Higgs boson. Furthermore, we study the charged Higgs boson in the MSSM, yielding a clear signal for physics beyond the Standard Model. For small tan β in minimal flavor violation (MFV) no processes for the detection of a charged Higgs boson do exist at the LHC. However, MFV is just motivated by the experimental agreement of results from flavor physics with Standard Model predictions, but not by any basic theoretical consideration. In this thesis, we calculate charged Higgs boson production cross sections beyond the assumption of MFV, where a large number of free parameters is present in the MSSM. We find that the soft-breaking parameters which enhance the charged-Higgs boson production most are just bound to large values, e.g. by rare B-meson decays. Although the charged-Higgs boson cross sections beyond MFV turn out to be sizeable, only a detailed

LHC Higgs physics beyond the Standard Model

Energy Technology Data Exchange (ETDEWEB)

Spannowsky, M.

2007-09-22

The Large Hadron Collider (LHC) at CERN will be able to perform proton collisions at a much higher center-of-mass energy and luminosity than any other collider. Its main purpose is to detect the Higgs boson, the last unobserved particle of the Standard Model, explaining the riddle of the origin of mass. Studies have shown, that for the whole allowed region of the Higgs mass processes exist to detect the Higgs at the LHC. However, the Standard Model cannot be a theory of everything and is not able to provide a complete understanding of physics. It is at most an effective theory up to a presently unknown energy scale. Hence, extensions of the Standard Model are necessary which can affect the Higgs-boson signals. We discuss these effects in two popular extensions of the Standard Model: the Minimal Supersymmetric Standard Model (MSSM) and the Standard Model with four generations (SM4G). Constraints on these models come predominantly from flavor physics and electroweak precision measurements. We show, that the SM4G is still viable and that a fourth generation has strong impact on decay and production processes of the Higgs boson. Furthermore, we study the charged Higgs boson in the MSSM, yielding a clear signal for physics beyond the Standard Model. For small tan {beta} in minimal flavor violation (MFV) no processes for the detection of a charged Higgs boson do exist at the LHC. However, MFV is just motivated by the experimental agreement of results from flavor physics with Standard Model predictions, but not by any basic theoretical consideration. In this thesis, we calculate charged Higgs boson production cross sections beyond the assumption of MFV, where a large number of free parameters is present in the MSSM. We find that the soft-breaking parameters which enhance the charged-Higgs boson production most are just bound to large values, e.g. by rare B-meson decays. Although the charged-Higgs boson cross sections beyond MFV turn out to be sizeable, only a detailed

Constraining new physics models with isotope shift spectroscopy

Science.gov (United States)

Frugiuele, Claudia; Fuchs, Elina; Perez, Gilad; Schlaffer, Matthias

2017-07-01

Isotope shifts of transition frequencies in atoms constrain generic long- and intermediate-range interactions. We focus on new physics scenarios that can be most strongly constrained by King linearity violation such as models with B -L vector bosons, the Higgs portal, and chameleon models. With the anticipated precision, King linearity violation has the potential to set the strongest laboratory bounds on these models in some regions of parameter space. Furthermore, we show that this method can probe the couplings relevant for the protophobic interpretation of the recently reported Be anomaly. We extend the formalism to include an arbitrary number of transitions and isotope pairs and fit the new physics coupling to the currently available isotope shift measurements.

Multiobjective constraints for climate model parameter choices: Pragmatic Pareto fronts in CESM1

Science.gov (United States)

Langenbrunner, B.; Neelin, J. D.

2017-09-01

Global climate models (GCMs) are examples of high-dimensional input-output systems, where model output is a function of many variables, and an update in model physics commonly improves performance in one objective function (i.e., measure of model performance) at the expense of degrading another. Here concepts from multiobjective optimization in the engineering literature are used to investigate parameter sensitivity and optimization in the face of such trade-offs. A metamodeling technique called cut high-dimensional model representation (cut-HDMR) is leveraged in the context of multiobjective optimization to improve GCM simulation of the tropical Pacific climate, focusing on seasonal precipitation, column water vapor, and skin temperature. An evolutionary algorithm is used to solve for Pareto fronts, which are surfaces in objective function space along which trade-offs in GCM performance occur. This approach allows the modeler to visualize trade-offs quickly and identify the physics at play. In some cases, Pareto fronts are small, implying that trade-offs are minimal, optimal parameter value choices are more straightforward, and the GCM is well-functioning. In all cases considered here, the control run was found not to be Pareto-optimal (i.e., not on the front), highlighting an opportunity for model improvement through objectively informed parameter selection. Taylor diagrams illustrate that these improvements occur primarily in field magnitude, not spatial correlation, and they show that specific parameter updates can improve fields fundamental to tropical moist processes—namely precipitation and skin temperature—without significantly impacting others. These results provide an example of how basic elements of multiobjective optimization can facilitate pragmatic GCM tuning processes.

Synthetic Earthquake Statistics From Physical Fault Models for the Lower Rhine Embayment

Science.gov (United States)

Brietzke, G. B.; Hainzl, S.; Zöller, G.

2012-04-01

As of today, seismic risk and hazard estimates mostly use pure empirical, stochastic models of earthquake fault systems tuned specifically to the vulnerable areas of interest. Although such models allow for reasonable risk estimates they fail to provide a link between the observed seismicity and the underlying physical processes. Solving a state-of-the-art fully dynamic description set of all relevant physical processes related to earthquake fault systems is likely not useful since it comes with a large number of degrees of freedom, poor constraints on its model parameters and a huge computational effort. Here, quasi-static and quasi-dynamic physical fault simulators provide a compromise between physical completeness and computational affordability and aim at providing a link between basic physical concepts and statistics of seismicity. Within the framework of quasi-static and quasi-dynamic earthquake simulators we investigate a model of the Lower Rhine Embayment (LRE) that is based upon seismological and geological data. We present and discuss statistics of the spatio-temporal behavior of generated synthetic earthquake catalogs with respect to simplification (e.g. simple two-fault cases) as well as to complication (e.g. hidden faults, geometric complexity, heterogeneities of constitutive parameters).

Large-scale parameter extraction in electrocardiology models through Born approximation

KAUST Repository

He, Yuan

2012-12-04

One of the main objectives in electrocardiology is to extract physical properties of cardiac tissues from measured information on electrical activity of the heart. Mathematically, this is an inverse problem for reconstructing coefficients in electrocardiology models from partial knowledge of the solutions of the models. In this work, we consider such parameter extraction problems for two well-studied electrocardiology models: the bidomain model and the FitzHugh-Nagumo model. We propose a systematic reconstruction method based on the Born approximation of the original nonlinear inverse problem. We describe a two-step procedure that allows us to reconstruct not only perturbations of the unknowns, but also the backgrounds around which the linearization is performed. We show some numerical simulations under various conditions to demonstrate the performance of our method. We also introduce a parameterization strategy using eigenfunctions of the Laplacian operator to reduce the number of unknowns in the parameter extraction problem. © 2013 IOP Publishing Ltd.

Indexes and parameters of activity in solar-terrestrial physics

International Nuclear Information System (INIS)

Minasyants, G.S.; Minasyants, T.M.

2005-01-01

The daily variation of different indexes and parameters of the solar-terrestrial physics at the 23 cycle were considered to find the most important from them for the forecast of geomagnetic activity. The validity of application of the Wolf numbers in quality of the characteristic of solar activity at sunspots is confirmed. The best geo-effective parameter in the arrival of the interplanetary shock from coronal mass ejection to an orbit of the Earth. (author)

Monte Carlo simulation of core physics parameters of the Nigeria Research Reactor-1 (NIRR-1)

Energy Technology Data Exchange (ETDEWEB)

Jonah, S.A. [Reactor Engineering Section, Centre for Energy Research and Training, Ahmadu Bello University, Zaria, P.M.B. 1014 (Nigeria)], E-mail: jonahsa2001@yahoo.com; Liaw, J.R.; Matos, J.E. [RERTR Program, Nuclear Engineering Division, Argonne National Laboratory, 9700 S. Cass Avenue, Argonne, IL 60439 (United States)

2007-12-15

The Monte Carlo N-Particle (MCNP) code, version 4C (MCNP4C) and a set of neutron cross-section data were used to develop an accurate three-dimensional computational model of the Nigeria Research Reactor-1 (NIRR-1). The geometry of the reactor core was modeled as closely as possible including the details of all the fuel elements, reactivity regulators, the control rod, all irradiation channels, and Be reflectors. The following reactor core physics parameters were calculated for the present highly enriched uranium (HEU) core: clean cold core excess reactivity ({rho}{sub ex}), control rod (CR) and shim worth, shut down margin (SDM), neutron flux distributions in the irradiation channels, reactivity feedback coefficients and the kinetics parameters. The HEU input model was validated by experimental data from the final safety analyses report (SAR). The model predicted various key neutronics parameters fairly accurately and the calculated thermal neutron fluxes in the irradiation channels agree with the values obtained by foil activation method. Results indicate that the established Monte Carlo model is an accurate representation of the NIRR-1 HEU core and will be used to perform feasibility for conversion to low enriched uranium (LEU)

Physics of ultrasonic wave propagation in bone and heart characterized using Bayesian parameter estimation

Science.gov (United States)

Anderson, Christian Carl

This Dissertation explores the physics underlying the propagation of ultrasonic waves in bone and in heart tissue through the use of Bayesian probability theory. Quantitative ultrasound is a noninvasive modality used for clinical detection, characterization, and evaluation of bone quality and cardiovascular disease. Approaches that extend the state of knowledge of the physics underpinning the interaction of ultrasound with inherently inhomogeneous and isotropic tissue have the potential to enhance its clinical utility. Simulations of fast and slow compressional wave propagation in cancellous bone were carried out to demonstrate the plausibility of a proposed explanation for the widely reported anomalous negative dispersion in cancellous bone. The results showed that negative dispersion could arise from analysis that proceeded under the assumption that the data consist of only a single ultrasonic wave, when in fact two overlapping and interfering waves are present. The confounding effect of overlapping fast and slow waves was addressed by applying Bayesian parameter estimation to simulated data, to experimental data acquired on bone-mimicking phantoms, and to data acquired in vitro on cancellous bone. The Bayesian approach successfully estimated the properties of the individual fast and slow waves even when they strongly overlapped in the acquired data. The Bayesian parameter estimation technique was further applied to an investigation of the anisotropy of ultrasonic properties in cancellous bone. The degree to which fast and slow waves overlap is partially determined by the angle of insonation of ultrasound relative to the predominant direction of trabecular orientation. In the past, studies of anisotropy have been limited by interference between fast and slow waves over a portion of the range of insonation angles. Bayesian analysis estimated attenuation, velocity, and amplitude parameters over the entire range of insonation angles, allowing a more complete

On the temperature independence of statistical model parameters for cleavage fracture in ferritic steels

Science.gov (United States)

Qian, Guian; Lei, Wei-Sheng; Niffenegger, M.; González-Albuixech, V. F.

2018-04-01

The work relates to the effect of temperature on the model parameters in local approaches (LAs) to cleavage fracture. According to a recently developed LA model, the physical consensus of plastic deformation being a prerequisite to cleavage fracture enforces any LA model of cleavage fracture to observe initial yielding of a volume element as its threshold stress state to incur cleavage fracture in addition to the conventional practice of confining the fracture process zone within the plastic deformation zone. The physical consistency of the new LA model to the basic LA methodology and the differences between the new LA model and other existing models are interpreted. Then this new LA model is adopted to investigate the temperature dependence of LA model parameters using circumferentially notched round tensile specimens. With the published strength data as input, finite element (FE) calculation is conducted for elastic-perfectly plastic deformation and the realistic elastic-plastic hardening, respectively, to provide stress distributions for model calibration. The calibration results in temperature independent model parameters. This leads to the establishment of a 'master curve' characteristic to synchronise the correlation between the nominal strength and the corresponding cleavage fracture probability at different temperatures. This 'master curve' behaviour is verified by strength data from three different steels, providing a new path to calculate cleavage fracture probability with significantly reduced FE efforts.

Estimating Convection Parameters in the GFDL CM2.1 Model Using Ensemble Data Assimilation

Science.gov (United States)

Li, Shan; Zhang, Shaoqing; Liu, Zhengyu; Lu, Lv; Zhu, Jiang; Zhang, Xuefeng; Wu, Xinrong; Zhao, Ming; Vecchi, Gabriel A.; Zhang, Rong-Hua; Lin, Xiaopei

2018-04-01

Parametric uncertainty in convection parameterization is one major source of model errors that cause model climate drift. Convection parameter tuning has been widely studied in atmospheric models to help mitigate the problem. However, in a fully coupled general circulation model (CGCM), convection parameters which impact the ocean as well as the climate simulation may have different optimal values. This study explores the possibility of estimating convection parameters with an ensemble coupled data assimilation method in a CGCM. Impacts of the convection parameter estimation on climate analysis and forecast are analyzed. In a twin experiment framework, five convection parameters in the GFDL coupled model CM2.1 are estimated individually and simultaneously under both perfect and imperfect model regimes. Results show that the ensemble data assimilation method can help reduce the bias in convection parameters. With estimated convection parameters, the analyses and forecasts for both the atmosphere and the ocean are generally improved. It is also found that information in low latitudes is relatively more important for estimating convection parameters. This study further suggests that when important parameters in appropriate physical parameterizations are identified, incorporating their estimation into traditional ensemble data assimilation procedure could improve the final analysis and climate prediction.

Model parameter updating using Bayesian networks

International Nuclear Information System (INIS)

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

2004-01-01

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

The sensitivity of flowline models of tidewater glaciers to parameter uncertainty

Directory of Open Access Journals (Sweden)

E. M. Enderlin

2013-10-01

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

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

Science.gov (United States)

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

2011-12-01

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

PARAMETER ESTIMATION IN BREAD BAKING MODEL

Directory of Open Access Journals (Sweden)

Hadiyanto Hadiyanto

2012-05-01

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

Assessing models for parameters of the Ångström-Prescott formula in China

DEFF Research Database (Denmark)

Liu, Xiaoying; Xu, Yinlong; Zhong, Xiuli

2012-01-01

against the calibrated ones. Models 1, 6 and 7 showed an advantage in keeping the physical meaning of their modeled parameters due to the small magnitude of and the use of the relation of (a + b) versus other variables as a constraint, respectively. All models tended to perform best in zone II and poorest...... () (models 1–2), altitude (model 7), altitude and (model 3), altitude, and latitude (model 4), altitude and latitude (model 5) and annual average air temperature (model 6). It was found that model 7 performed best, followed by models 6, 1, 3, 2 and 4. The better performance of models 7 and 6 and the fact....... This also suggests that applicability of a Rs model is not proportional to its complexity. The common feature of the better performing models suggests that accurate modeling of parameter a is more important than that of b. Therefore, priority should be given to parameter models having higher accuracy for a...

CPU time optimization and precise adjustment of the Geant4 physics parameters for a VARIAN 2100 C/D gamma radiotherapy linear accelerator simulation using GAMOS

Science.gov (United States)

Arce, Pedro; Lagares, Juan Ignacio

2018-02-01

We have verified the GAMOS/Geant4 simulation model of a 6 MV VARIAN Clinac 2100 C/D linear accelerator by the procedure of adjusting the initial beam parameters to fit the percentage depth dose and cross-profile dose experimental data at different depths in a water phantom. Thanks to the use of a wide range of field sizes, from 2  ×  2 cm2 to 40  ×  40 cm2, a small phantom voxel size and high statistics, fine precision in the determination of the beam parameters has been achieved. This precision has allowed us to make a thorough study of the different physics models and parameters that Geant4 offers. The three Geant4 electromagnetic physics sets of models, i.e. Standard, Livermore and Penelope, have been compared to the experiment, testing the four different models of angular bremsstrahlung distributions as well as the three available multiple-scattering models, and optimizing the most relevant Geant4 electromagnetic physics parameters. Before the fitting, a comprehensive CPU time optimization has been done, using several of the Geant4 efficiency improvement techniques plus a few more developed in GAMOS.

Physical model of reactor pulse

International Nuclear Information System (INIS)

Petrovic, A.; Ravnik, M.

2004-01-01

Pulse experiments have been performed at J. Stefan Institute TRIGA reactor since 1991. In total, more than 130 pulses have been performed. Extensive experimental information on the pulse physical characteristics has been accumulated. Fuchs-Hansen adiabatic model has been used for predicting and analysing the pulse parameters. The model is based on point kinetics equation, neglecting the delayed neutrons and assuming constant inserted reactivity in form of step function. Deficiencies of the Fuchs-Hansen model and systematic experimental errors have been observed and analysed. Recently, the pulse model was improved by including the delayed neutrons and time dependence of inserted reactivity. The results explain the observed non-linearity of the pulse energy for high pulses due to finite time of pulse rod withdrawal and the contribution of the delayed neutrons after the prompt part of the pulse. The results of the improved model are in good agreement with experimental results. (author)

Physics Beyond the Standard Model: Supersymmetry

Energy Technology Data Exchange (ETDEWEB)

Nojiri, M.M.; /KEK, Tsukuba /Tsukuba, Graduate U. Adv. Studies /Tokyo U.; Plehn, T.; /Edinburgh U.; Polesello, G.; /INFN, Pavia; Alexander, John M.; /Edinburgh U.; Allanach, B.C.; /Cambridge U.; Barr, Alan J.; /Oxford U.; Benakli, K.; /Paris U., VI-VII; Boudjema, F.; /Annecy, LAPTH; Freitas, A.; /Zurich U.; Gwenlan, C.; /University Coll. London; Jager, S.; /CERN /LPSC, Grenoble

2008-02-01

This collection of studies on new physics at the LHC constitutes the report of the supersymmetry working group at the Workshop 'Physics at TeV Colliders', Les Houches, France, 2007. They cover the wide spectrum of phenomenology in the LHC era, from alternative models and signatures to the extraction of relevant observables, the study of the MSSM parameter space and finally to the interplay of LHC observations with additional data expected on a similar time scale. The special feature of this collection is that while not each of the studies is explicitly performed together by theoretical and experimental LHC physicists, all of them were inspired by and discussed in this particular environment.

Physical parameter determinations of young Ms. Taking advantage of the Virtual Observatory to compare methodologies

Science.gov (United States)

Bayo, A.; Rodrigo, C.; Barrado, D.; Allard, F.

One of the very first steps astronomers working in stellar physics perform to advance in their studies, is to determine the most common/relevant physical parameters of the objects of study (effective temperature, bolometric luminosity, surface gravity, etc.). Different methodologies exist depending on the nature of the data, intrinsic properties of the objects, etc. One common approach is to compare the observational data with theoretical models passed through some simulator that will leave in the synthetic data the same imprint than the observational data carries, and see what set of parameters reproduce the observations best. Even in this case, depending on the kind of data the astronomer has, the methodology changes slightly. After parameters are published, the community tend to quote, praise and criticize them, sometimes paying little attention on whether the possible discrepancies come from the theoretical models, the data themselves or just the methodology used in the analysis. In this work we perform the simple, yet interesting, exercise of comparing the effective temperatures obtained via SED and more detailed spectral fittings (to the same grid of models), of a sample of well known and characterized young M-type objects members to different star forming regions and show how differences in temperature of up to 350 K can be expected just from the difference in methodology/data used. On the other hand we show how these differences are smaller for colder objects even when the complexity of the fit increases like for example introducing differential extinction. To perform this exercise we benefit greatly from the framework offered by the Virtual Observaotry.

SF-FDTD analysis of a predictive physical model for parallel aligned liquid crystal devices

Science.gov (United States)

Márquez, Andrés.; Francés, Jorge; Martínez, Francisco J.; Gallego, Sergi; Alvarez, Mariela L.; Calzado, Eva M.; Pascual, Inmaculada; Beléndez, Augusto

2017-08-01

Recently we demonstrated a novel and simplified model enabling to calculate the voltage dependent retardance provided by parallel aligned liquid crystal devices (PA-LCoS) for a very wide range of incidence angles and any wavelength in the visible. To our knowledge it represents the most simplified approach still showing predictive capability. Deeper insight into the physics behind the simplified model is necessary to understand if the parameters in the model are physically meaningful. Since the PA-LCoS is a black-box where we do not have information about the physical parameters of the device, we cannot perform this kind of analysis using the experimental retardance measurements. In this work we develop realistic simulations for the non-linear tilt of the liquid crystal director across the thickness of the liquid crystal layer in the PA devices. We consider these profiles to have a sine-like shape, which is a good approximation for typical ranges of applied voltage in commercial PA-LCoS microdisplays. For these simulations we develop a rigorous method based on the split-field finite difference time domain (SF-FDTD) technique which provides realistic retardance values. These values are used as the experimental measurements to which the simplified model is fitted. From this analysis we learn that the simplified model is very robust, providing unambiguous solutions when fitting its parameters. We also learn that two of the parameters in the model are physically meaningful, proving a useful reverse-engineering approach, with predictive capability, to probe into internal characteristics of the PA-LCoS device.

Robust estimation of hydrological model parameters

Directory of Open Access Journals (Sweden)

A. Bárdossy

2008-11-01

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

Photovoltaic module parameters acquisition model

Energy Technology Data Exchange (ETDEWEB)

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

2014-09-01

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

Photovoltaic module parameters acquisition model

International Nuclear Information System (INIS)

Cibira, Gabriel; Koščová, Marcela

2014-01-01

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

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

SPOTting model parameters using a ready-made Python package

Science.gov (United States)

Houska, Tobias; Kraft, Philipp; Breuer, Lutz

2015-04-01

optimization methods. Here we see simple algorithms like the MCMC struggling to find the global optimum of the function, while algorithms like SCE-UA and DE-MCZ show their strengths. Thirdly, we apply an uncertainty analysis of a one-dimensional physically based hydrological model build with the Catchment Modelling Framework (CMF). The model is driven by meteorological and groundwater data from a Free Air Carbon Enrichment (FACE) experiment in Linden (Hesse, Germany). Simulation results are evaluated with measured soil moisture data. We search for optimal parameter sets of the van Genuchten-Mualem function and find different equally optimal solutions with some of the algorithms. The case studies reveal that the implemented SPOT methods work sufficiently well. They further show the benefit of having one tool at hand that includes a number of parameter search methods, likelihood functions and a priori parameter distributions within one platform independent package.

Importance theory for lumped-parameter systems

International Nuclear Information System (INIS)

Cady, K.B.; Kenton, M.A.; Ward, J.C.; Piepho, M.G.

1981-01-01

A general sensitivity theory has been developed for nonlinear lumped parameter system simulations. The point of departure is general perturbation theory for nonlinear systems. Importance theory as developed here allows the calculation of the sensitivity of a response function to any physical or design parameter; importance of any equation or term or physical effect in the system model on the response function; variance of the response function caused by the variances and covariances of all physical parameters; and approximate effect on the response function of missing physical phenomena or incorrect parameters

Luminescence model with quantum impact parameter for low energies

International Nuclear Information System (INIS)

Cruz G, H.S.; Michaelian, K.; Galindo U, S.; Martinez D, A.; Belmont M, E.

2000-01-01

The analytical model of induced light production in scintillator materials by energetic ions proposed by Michaelian and Menchaca (M-M) adjusts very well the luminescence substance data in a wide energy interval of the incident ions (10-100 MeV). However at low energies, that is, under to 10 MeV, the experimental deviations of the predictions of M-M model, show that the causes may be certain physical effects, all they important at low energies, which were not considered. We have modified lightly the M-M model using the basic fact that the Quantum mechanics gives to a different limit for the quantum impact parameter instead of the classic approximation. (Author)

Efficient Parameterization for Grey-box Model Identification of Complex Physical Systems

DEFF Research Database (Denmark)

Blanke, Mogens; Knudsen, Morten Haack

2006-01-01

Grey box model identification preserves known physical structures in a model but with limits to the possible excitation, all parameters are rarely identifiable, and different parametrizations give significantly different model quality. Convenient methods to show which parameterizations are the be...... that need be constrained to achieve satisfactory convergence. Identification of nonlinear models for a ship illustrate the concept....

Simplified Models for LHC New Physics Searches

International Nuclear Information System (INIS)

Alves, Daniele; Arkani-Hamed, Nima; Arora, Sanjay; Bai, Yang; Baumgart, Matthew; Berger, Joshua; Butler, Bart; Chang, Spencer; Cheng, Hsin-Chia; Cheung, Clifford; Chivukula, R. Sekhar; Cho, Won Sang; Cotta, Randy; D'Alfonso, Mariarosaria; El Hedri, Sonia; Essig, Rouven; Fitzpatrick, Liam; Fox, Patrick; Franceschini, Roberto

2012-01-01

This document proposes a collection of simplified models relevant to the design of new-physics searches at the LHC and the characterization of their results. Both ATLAS and CMS have already presented some results in terms of simplified models, and we encourage them to continue and expand this effort, which supplements both signature-based results and benchmark model interpretations. A simplified model is defined by an effective Lagrangian describing the interactions of a small number of new particles. Simplified models can equally well be described by a small number of masses and cross-sections. These parameters are directly related to collider physics observables, making simplified models a particularly effective framework for evaluating searches and a useful starting point for characterizing positive signals of new physics. This document serves as an official summary of the results from the 'Topologies for Early LHC Searches' workshop, held at SLAC in September of 2010, the purpose of which was to develop a set of representative models that can be used to cover all relevant phase space in experimental searches. Particular emphasis is placed on searches relevant for the first ∼ 50-500 pb -1 of data and those motivated by supersymmetric models. This note largely summarizes material posted at http://lhcnewphysics.org/, which includes simplified model definitions, Monte Carlo material, and supporting contacts within the theory community. We also comment on future developments that may be useful as more data is gathered and analyzed by the experiments.

Simplified Models for LHC New Physics Searches

Energy Technology Data Exchange (ETDEWEB)

Alves, Daniele; /SLAC; Arkani-Hamed, Nima; /Princeton, Inst. Advanced Study; Arora, Sanjay; /Rutgers U., Piscataway; Bai, Yang; /SLAC; Baumgart, Matthew; /Johns Hopkins U.; Berger, Joshua; /Cornell U., Phys. Dept.; Buckley, Matthew; /Fermilab; Butler, Bart; /SLAC; Chang, Spencer; /Oregon U. /UC, Davis; Cheng, Hsin-Chia; /UC, Davis; Cheung, Clifford; /UC, Berkeley; Chivukula, R.Sekhar; /Michigan State U.; Cho, Won Sang; /Tokyo U.; Cotta, Randy; /SLAC; D' Alfonso, Mariarosaria; /UC, Santa Barbara; El Hedri, Sonia; /SLAC; Essig, Rouven, (ed.); /SLAC; Evans, Jared A.; /UC, Davis; Fitzpatrick, Liam; /Boston U.; Fox, Patrick; /Fermilab; Franceschini, Roberto; /LPHE, Lausanne /Pittsburgh U. /Argonne /Northwestern U. /Rutgers U., Piscataway /Rutgers U., Piscataway /Carleton U. /CERN /UC, Davis /Wisconsin U., Madison /SLAC /SLAC /SLAC /Rutgers U., Piscataway /Syracuse U. /SLAC /SLAC /Boston U. /Rutgers U., Piscataway /Seoul Natl. U. /Tohoku U. /UC, Santa Barbara /Korea Inst. Advanced Study, Seoul /Harvard U., Phys. Dept. /Michigan U. /Wisconsin U., Madison /Princeton U. /UC, Santa Barbara /Wisconsin U., Madison /Michigan U. /UC, Davis /SUNY, Stony Brook /TRIUMF; /more authors..

2012-06-01

This document proposes a collection of simplified models relevant to the design of new-physics searches at the LHC and the characterization of their results. Both ATLAS and CMS have already presented some results in terms of simplified models, and we encourage them to continue and expand this effort, which supplements both signature-based results and benchmark model interpretations. A simplified model is defined by an effective Lagrangian describing the interactions of a small number of new particles. Simplified models can equally well be described by a small number of masses and cross-sections. These parameters are directly related to collider physics observables, making simplified models a particularly effective framework for evaluating searches and a useful starting point for characterizing positive signals of new physics. This document serves as an official summary of the results from the 'Topologies for Early LHC Searches' workshop, held at SLAC in September of 2010, the purpose of which was to develop a set of representative models that can be used to cover all relevant phase space in experimental searches. Particular emphasis is placed on searches relevant for the first {approx} 50-500 pb{sup -1} of data and those motivated by supersymmetric models. This note largely summarizes material posted at http://lhcnewphysics.org/, which includes simplified model definitions, Monte Carlo material, and supporting contacts within the theory community. We also comment on future developments that may be useful as more data is gathered and analyzed by the experiments.

A physics-based probabilistic forecasting model for rainfall-induced shallow landslides at regional scale

Directory of Open Access Journals (Sweden)

S. Zhang

2018-03-01

Full Text Available Conventional outputs of physics-based landslide forecasting models are presented as deterministic warnings by calculating the safety factor (Fs of potentially dangerous slopes. However, these models are highly dependent on variables such as cohesion force and internal friction angle which are affected by a high degree of uncertainty especially at a regional scale, resulting in unacceptable uncertainties of Fs. Under such circumstances, the outputs of physical models are more suitable if presented in the form of landslide probability values. In order to develop such models, a method to link the uncertainty of soil parameter values with landslide probability is devised. This paper proposes the use of Monte Carlo methods to quantitatively express uncertainty by assigning random values to physical variables inside a defined interval. The inequality Fs < 1 is tested for each pixel in n simulations which are integrated in a unique parameter. This parameter links the landslide probability to the uncertainties of soil mechanical parameters and is used to create a physics-based probabilistic forecasting model for rainfall-induced shallow landslides. The prediction ability of this model was tested in a case study, in which simulated forecasting of landslide disasters associated with heavy rainfalls on 9 July 2013 in the Wenchuan earthquake region of Sichuan province, China, was performed. The proposed model successfully forecasted landslides in 159 of the 176 disaster points registered by the geo-environmental monitoring station of Sichuan province. Such testing results indicate that the new model can be operated in a highly efficient way and show more reliable results, attributable to its high prediction accuracy. Accordingly, the new model can be potentially packaged into a forecasting system for shallow landslides providing technological support for the mitigation of these disasters at regional scale.

Modeling theoretical uncertainties in phenomenological analyses for particle physics

Energy Technology Data Exchange (ETDEWEB)

Charles, Jerome [CNRS, Aix-Marseille Univ, Universite de Toulon, CPT UMR 7332, Marseille Cedex 9 (France); Descotes-Genon, Sebastien [CNRS, Univ. Paris-Sud, Universite Paris-Saclay, Laboratoire de Physique Theorique (UMR 8627), Orsay Cedex (France); Niess, Valentin [CNRS/IN2P3, UMR 6533, Laboratoire de Physique Corpusculaire, Aubiere Cedex (France); Silva, Luiz Vale [CNRS, Univ. Paris-Sud, Universite Paris-Saclay, Laboratoire de Physique Theorique (UMR 8627), Orsay Cedex (France); Univ. Paris-Sud, CNRS/IN2P3, Universite Paris-Saclay, Groupe de Physique Theorique, Institut de Physique Nucleaire, Orsay Cedex (France); J. Stefan Institute, Jamova 39, P. O. Box 3000, Ljubljana (Slovenia)

2017-04-15

The determination of the fundamental parameters of the Standard Model (and its extensions) is often limited by the presence of statistical and theoretical uncertainties. We present several models for the latter uncertainties (random, nuisance, external) in the frequentist framework, and we derive the corresponding p values. In the case of the nuisance approach where theoretical uncertainties are modeled as biases, we highlight the important, but arbitrary, issue of the range of variation chosen for the bias parameters. We introduce the concept of adaptive p value, which is obtained by adjusting the range of variation for the bias according to the significance considered, and which allows us to tackle metrology and exclusion tests with a single and well-defined unified tool, which exhibits interesting frequentist properties. We discuss how the determination of fundamental parameters is impacted by the model chosen for theoretical uncertainties, illustrating several issues with examples from quark flavor physics. (orig.)

COMPREHENSIVE CHECK MEASUREMENT OF KEY PARAMETERS ON MODEL BELT CONVEYOR

Directory of Open Access Journals (Sweden)

Vlastimil MONI

2013-07-01

Full Text Available Complex measurements of characteristic parameters realised on a long distance model belt conveyor are described. The main objective was to complete and combine the regular measurements of electric power on drives of belt conveyors operated in Czech opencast mines with measurements of other physical quantities and to gain by this way an image of their mutual relations and relations of quantities derived from them. The paper includes a short description and results of the measurements on an experimental model conveyor with a closed material transport way.

The Hypertrophic Marchigiana: physical and biochemical parameters for meat quality evaluation

Directory of Open Access Journals (Sweden)

F. M. Sarti

2010-04-01

Full Text Available The aim of this study was to evaluate the meat quality of double muscled Marchigiana young bulls characterized by different genotypes for the hypertrophy: normal and mutated (heterozygous. Calpain and calpastatin activities were determined to verify the state of aging meat on a sample of Longissimus thoracis muscle (XIII thoracic rib taken at slaughtering (0h and after 24 hours (24h. After 14 days of aging, another sample of muscle was taken to evaluate physical and chemical parameters of meat quality. The results showed a better meat quality of mutated animals respect normal animals. Another interesting result was the correlation between the biochemical parameters and some physical parameters, such as WBS (Warner Bratzler Shear Force, CL (Cooking loss. These results showed the relationship between the proteolytic activity of calpain system and meat tenderness.

Physically Active Men Show Better Semen Parameters than Their Sedentary Counterparts

OpenAIRE

Lalinde-Acevedo, Paula C.; Mayorga-Torres, B. Jose Manuel; Agarwal, Ashok; du Plessis, Stefan S.; Ahmad, Gulfam; Cadavid, Ángela P.; Cardona Maya, Walter D.

2017-01-01

Background The quality of semen depends upon several factors such as environment, life style, physical activity, age, and occupation. The aim of this study was to analyze and compare the conventional and functional semen parameters in men practicing vigorous physical activity to those of sedentary men. Materials and Methods In this descriptive cross-sectional study, semen samples of 17 physically active men and 15 sedentary men were collected for analysis. Semen analysis was performe...

Characterization of parameters and strategies used by physical therapists in difficult mechanical ventilation weaning

Directory of Open Access Journals (Sweden)

Fabíola Maria Sabino Meireles

2013-03-01

Full Text Available Objective: To characterize the main strategies and parameters used by physical therapists in difficult mechanical ventilation weaning. Methods: Cross-sectional study including all the physical therapists working in adult Intensive Care Units in three public hospitals in Fortaleza-CE. A questionnaire with closed questions related to difficult mechanical ventilation weaning was applied, with either one or multiple answers. The data was treated with descriptive and non-parametric analysis. Results: Among the parameters mostly used by the 56 interviewed physical therapists for the difficult weaning, were found: current volume reduction (26 - 46.4% and desaturation during aspiration (17 - 30.4%. It was observed that 38 (67.9% alternate T-tube and continuous positive airway pressure (CPAP as strategies for difficult weaning, and 28 (50% reported reducing the pressure support. There was no statistical difference between the strategies used in the studied hospitals, neither correlation between strategies and parameters. Conclusion: It was found that physical therapists have been performing similar strategies, which are also shown in the literature, but this is not the case with the parameters. The parameters used are not supported by the literature.

Physics-based statistical model and simulation method of RF propagation in urban environments

Science.gov (United States)

Pao, Hsueh-Yuan; Dvorak, Steven L.

2010-09-14

A physics-based statistical model and simulation/modeling method and system of electromagnetic wave propagation (wireless communication) in urban environments. In particular, the model is a computationally efficient close-formed parametric model of RF propagation in an urban environment which is extracted from a physics-based statistical wireless channel simulation method and system. The simulation divides the complex urban environment into a network of interconnected urban canyon waveguides which can be analyzed individually; calculates spectral coefficients of modal fields in the waveguides excited by the propagation using a database of statistical impedance boundary conditions which incorporates the complexity of building walls in the propagation model; determines statistical parameters of the calculated modal fields; and determines a parametric propagation model based on the statistical parameters of the calculated modal fields from which predictions of communications capability may be made.

Parameter Sensitivity and Laboratory Benchmarking of a Biogeochemical Process Model for Enhanced Anaerobic Dechlorination

Science.gov (United States)

Kouznetsova, I.; Gerhard, J. I.; Mao, X.; Barry, D. A.; Robinson, C.; Brovelli, A.; Harkness, M.; Fisher, A.; Mack, E. E.; Payne, J. A.; Dworatzek, S.; Roberts, J.

2008-12-01

A detailed model to simulate trichloroethene (TCE) dechlorination in anaerobic groundwater systems has been developed and implemented through PHAST, a robust and flexible geochemical modeling platform. The approach is comprehensive but retains flexibility such that models of varying complexity can be used to simulate TCE biodegradation in the vicinity of nonaqueous phase liquid (NAPL) source zones. The complete model considers a full suite of biological (e.g., dechlorination, fermentation, sulfate and iron reduction, electron donor competition, toxic inhibition, pH inhibition), physical (e.g., flow and mass transfer) and geochemical processes (e.g., pH modulation, gas formation, mineral interactions). Example simulations with the model demonstrated that the feedback between biological, physical, and geochemical processes is critical. Successful simulation of a thirty-two-month column experiment with site soil, complex groundwater chemistry, and exhibiting both anaerobic dechlorination and endogenous respiration, provided confidence in the modeling approach. A comprehensive suite of batch simulations was then conducted to estimate the sensitivity of predicted TCE degradation to the 36 model input parameters. A local sensitivity analysis was first employed to rank the importance of parameters, revealing that 5 parameters consistently dominated model predictions across a range of performance metrics. A global sensitivity analysis was then performed to evaluate the influence of a variety of full parameter data sets available in the literature. The modeling study was performed as part of the SABRE (Source Area BioREmediation) project, a public/private consortium whose charter is to determine if enhanced anaerobic bioremediation can result in effective and quantifiable treatment of chlorinated solvent DNAPL source areas. The modelling conducted has provided valuable insight into the complex interactions between processes in the evolving biogeochemical systems

Surrogate based approaches to parameter inference in ocean models

KAUST Repository

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.

Surrogate based approaches to parameter inference in ocean models

KAUST Repository

Knio, Omar

2016-01-01

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.

Neutrino bilarge mixing and flavor physics in the flipped SU(5) model

Energy Technology Data Exchange (ETDEWEB)

Huang Chaoshang; Li Tianjun; Liao Wei E-mail: liaow@ictp.trieste.it

2003-11-24

We have constructed a specific supersymmetric flipped SU(5) GUT model in which bilarge neutrino mixing is incorporated. Because the up-type and down-type quarks in the model are flipped in the representations ten and five with respect to the usual SU(5), the radiatively generated flavor mixing in squark mass matrices due to the large neutrino mixing has a pattern different from those in the conventional SU(5) and SO(10) supersymmetric GUTs. This leads to phenomenological consequences quite different from SU(5) or SO(10) supersymmetric GUT models. That is, it has almost no impact on B physics. On the contrary, the model has effects in top and charm physics as well as lepton physics. In particular, it gives promising prediction on the mass difference, {delta}M{sub D}, of the D-D-bar mixing which for some ranges of the parameter space with large tan{beta} can be at the order of 10{sup 9} {Dirac_h} s{sup -1}, one order of magnitude smaller than the experimental upper bound. In some regions of the parameter space {delta}M{sub D} can saturate the present bound. For these ranges of parameter space, t{yields}u,c+h{sup 0} can reach 10{sup -5}-10{sup -6} which would be observed at the LHC and future {gamma}-{gamma} colliders.

Optimization of Soil Hydraulic Model Parameters Using Synthetic Aperture Radar Data: An Integrated Multidisciplinary Approach

DEFF Research Database (Denmark)

Pauwels, Valentijn; Balenzano, Anna; Satalino, Giuseppe

2009-01-01

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...... 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...

Assessing parameter importance of the Common Land Model based on qualitative and quantitative sensitivity analysis

Directory of Open Access Journals (Sweden)

J. Li

2013-08-01

Full Text Available Proper specification of model parameters is critical to the performance of land surface models (LSMs. Due to high dimensionality and parameter interaction, estimating parameters of an LSM is a challenging task. Sensitivity analysis (SA is a tool that can screen out the most influential parameters on model outputs. In this study, we conducted parameter screening for six output fluxes for the Common Land Model: sensible heat, latent heat, upward longwave radiation, net radiation, soil temperature and soil moisture. A total of 40 adjustable parameters were considered. Five qualitative SA methods, including local, sum-of-trees, multivariate adaptive regression splines, delta test and Morris methods, were compared. The proper sampling design and sufficient sample size necessary to effectively screen out the sensitive parameters were examined. We found that there are 2–8 sensitive parameters, depending on the output type, and about 400 samples are adequate to reliably identify the most sensitive parameters. We also employed a revised Sobol' sensitivity method to quantify the importance of all parameters. The total effects of the parameters were used to assess the contribution of each parameter to the total variances of the model outputs. The results confirmed that global SA methods can generally identify the most sensitive parameters effectively, while local SA methods result in type I errors (i.e., sensitive parameters labeled as insensitive or type II errors (i.e., insensitive parameters labeled as sensitive. Finally, we evaluated and confirmed the screening results for their consistency with the physical interpretation of the model parameters.

Monte Carlo simulation of core physics parameters of the Syrian MNSR reactor

International Nuclear Information System (INIS)

Khattab, K.; Sulieman, I.

2011-01-01

A 3-D neutronic model for the Syrian Miniature Neutron Source Reactor (MNSR) was developed earlier to conduct the reactor neutronic analysis using the MCNP-4C code. The continuous energy neutron cross sections were evaluated from the ENDF/B-VI library. This model is used in this paper to calculate the following reactor core physics parameters: the clean cold core excess reactivity, calibration of the control rod and calculation its shut down margin, calibration of the top beryllium shim plate reflector, the axial neutron flux distributions in the inner and outer irradiation positions and calculations of the prompt neutron life time (ι p ) and the effective delayed neutron fraction ( β e ff). Good agreements are noticed between the calculated and the measured results. These agreements indicate that the established model is an accurate representation of Syrian MNSR core and will be used for other calculations in the future. (author)

Parameter Estimation of Partial Differential Equation Models.

Science.gov (United States)

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

2013-01-01

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

Hybrid Reduced Order Modeling Algorithms for Reactor Physics Calculations

Science.gov (United States)

Bang, Youngsuk

hybrid ROM algorithms which can be readily integrated into existing methods and offer higher computational efficiency and defendable accuracy of the reduced models. For example, the snapshots ROM algorithm is hybridized with the range finding algorithm to render reduction in the state space, e.g. the flux in reactor calculations. In another implementation, the perturbation theory used to calculate first order derivatives of responses with respect to parameters is hybridized with a forward sensitivity analysis approach to render reduction in the parameter space. Reduction at the state and parameter spaces can be combined to render further reduction at the interface between different physics codes in a multi-physics model with the accuracy quantified in a similar manner to the single physics case. Although the proposed algorithms are generic in nature, we focus here on radiation transport models used in support of the design and analysis of nuclear reactor cores. In particular, we focus on replacing the traditional assembly calculations by ROM models to facilitate the generation of homogenized cross-sections for downstream core calculations. The implication is that assembly calculations could be done instantaneously therefore precluding the need for the expensive evaluation of the few-group cross-sections for all possible core conditions. Given the generic natures of the algorithms, we make an effort to introduce the material in a general form to allow non-nuclear engineers to benefit from this work.

Mass balance model parameter transferability on a tropical glacier

Science.gov (United States)

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

2013-04-01

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

Sensitivity analysis of physical/operational parameters in neutron multiplicity counting

International Nuclear Information System (INIS)

Peerani, P.; Marin Ferrer, M.

2007-01-01

In this paper, we perform a sensitivity study on the influence of various physical and operational parameters on the results of neutron multiplicity counting. The purpose is to have a better understanding of the importance of each component and its contribution to the measurement uncertainty. Then we will be able to determine the optimal conditions for the operational parameters and for detector design and as well to point out weaknesses in the knowledge of critical fundamental nuclear data

Physically-Retrieving Cloud and Thermodynamic Parameters from Ultraspectral IR Measurements

Science.gov (United States)

Zhou, Daniel K.; Smith, William L., Sr.; Liu, Xu; Larar, Allen M.; Mango, Stephen A.; Huang, Hung-Lung

2007-01-01

A physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multi-variable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with relatively high accuracy (i.e., error < 1 km). NPOESS Airborne Sounder Testbed Interferometer (NAST-I) retrievals from the Atlantic-THORPEX Regional Campaign are compared with coincident observations obtained from dropsondes and the nadir-pointing Cloud Physics Lidar (CPL). This work was motivated by the need to obtain solutions for atmospheric soundings from infrared radiances observed for every individual field of view, regardless of cloud cover, from future ultraspectral geostationary satellite sounding instruments, such as the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) and the Hyperspectral Environmental Suite (HES). However, this retrieval approach can also be applied to the ultraspectral sounding instruments to fly on Polar satellites, such as the Infrared Atmospheric Sounding Interferometer (IASI) on the European MetOp satellite, the Cross-track Infrared Sounder (CrIS) on the NPOESS Preparatory Project and the following NPOESS series of satellites.

Quality assessment for radiological model parameters

International Nuclear Information System (INIS)

Funtowicz, S.O.

1989-01-01

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

Environmental parameters of the Tennessee River in Alabama. 2: Physical, chemical, and biological parameters. [biological and chemical effects of thermal pollution from nuclear power plants on water quality

Science.gov (United States)

Rosing, L. M.

1976-01-01

Physical, chemical and biological water quality data from five sites in the Tennessee River, two in Guntersville Reservoir and three in Wheeler Reservoir were correlated with climatological data for three annual cycles. Two of the annual cycles are for the years prior to the Browns Ferry Nuclear Power Plant operations and one is for the first 14 months of Plant operations. A comparison of the results of the annual cycles indicates that two distinct physical conditions in the reservoirs occur, one during the warm months when the reservoirs are at capacity and one during the colder winter months when the reservoirs have been drawn-down for water storage during the rainy months and for weed control. The wide variations of physical and chemical parameters to which the biological organisms are subjected on an annual basis control the biological organisms and their population levels. A comparison of the parameters of the site below the Power plant indicates that the heated effluent from the plant operating with two of the three reactors has not had any effect on the organisms at this site. Recommendations given include the development of prediction mathematical models (statistical analysis) for the physical and chemical parameters under specific climatological conditions which affect biological organisms. Tabulated data of chemical analysis of water and organism populations studied is given.

Impact of flavor and Higgs physics on theories beyond the standard model

Energy Technology Data Exchange (ETDEWEB)

Casagrande, Sandro

2013-02-13

Quantum effects of physics beyond the Standard Model receive strong indirect constraints from precisely measured collider observables. In the conceptual part of this thesis, we apply the generic relations between particle interactions in perturbatively unitary theories to calculate one-loop amplitudes for flavor physics. We provide template results applicable for any model of this class. We also investigate example models that are partly and such that are not perturbatively unitary: the Littlest Higgs model and Randall-Sundrum models. The latter have a unique coupling structure, which we cover exhaustively. We find strong constraints on the Randall-Sundrum models and numerically compare those from flavor, electroweak precision, and Higgs physics by performing detailed parameter scans. We observe interesting correlations between flavor observables, and we find that constraints from Higgs production and decays are already competitive.

Impact of flavor and Higgs physics on theories beyond the standard model

International Nuclear Information System (INIS)

Casagrande, Sandro

2013-01-01

Quantum effects of physics beyond the Standard Model receive strong indirect constraints from precisely measured collider observables. In the conceptual part of this thesis, we apply the generic relations between particle interactions in perturbatively unitary theories to calculate one-loop amplitudes for flavor physics. We provide template results applicable for any model of this class. We also investigate example models that are partly and such that are not perturbatively unitary: the Littlest Higgs model and Randall-Sundrum models. The latter have a unique coupling structure, which we cover exhaustively. We find strong constraints on the Randall-Sundrum models and numerically compare those from flavor, electroweak precision, and Higgs physics by performing detailed parameter scans. We observe interesting correlations between flavor observables, and we find that constraints from Higgs production and decays are already competitive.

Intracranial Pressure Response to Non-Penetrating Ballistic Impact: An Experimental Study Using a Pig Physical Head Model and Live Pigs

Science.gov (United States)

Liu, Hai; Kang, Jianyi; Chen, Jing; Li, Guanhua; Li, Xiaoxia; Wang, Jianmin

2012-01-01

This study was conducted to characterize the intracranial pressure response to non-penetrating ballistic impact using a "scalp-skull-brain" pig physical head model and live pigs. Forty-eight ballistic tests targeting the physical head model and anesthetized pigs protected by aramid plates were conducted with standard 9 mm bullets at low (279-297 m/s), moderate (350-372 m/s), and high (409-436 m/s) velocities. Intracranial pressure responses were recorded with pressure sensors embedded in similar brain locations in the physical head model and the anesthetized pigs. Three parameters of intracranial pressure were determined from the measured data: intracranial maximum pressure (Pmax), intracranial maximum pressure impulse (PImax), and the duration of the first positive phase (PPD). The intracranial pressure waves exhibited blast-like characteristics for both the physical model and l live pigs. Of all three parameters, Pmax is most sensitive to impact velocity, with means of 126 kPa (219 kPa), 178 kPa (474 kPa), and 241 kPa (751 kPa) for the physical model (live pigs) for low, moderate, and high impact velocities, respectively. The mean PPD becomes increasingly short as the impact velocity increases, whereas PImax shows the opposite trend. Although the pressure parameters of the physical model were much lower than those of the live pigs, good correlations between the physical model and the live pigs for the three pressure parameters, especially Pmax, were found using linear regression. This investigation suggests that Pmax is a preferred parameter for predicting the severity of the brain injury resulting from behind armor blunt trauma (BABT). PMID:23055817

A Software Toolkit to Study Systematic Uncertainties of the Physics Models of the Geant4 Simulation Package

Science.gov (United States)

Genser, Krzysztof; Hatcher, Robert; Kelsey, Michael; Perdue, Gabriel; Wenzel, Hans; Wright, Dennis H.; Yarba, Julia

2017-10-01

The Geant4 simulation toolkit is used to model interactions between particles and matter. Geant4 employs a set of validated physics models that span a wide range of interaction energies. These models rely on measured cross-sections and phenomenological models with the physically motivated parameters that are tuned to cover many application domains. To study what uncertainties are associated with the Geant4 physics models we have designed and implemented a comprehensive, modular, user-friendly software toolkit that allows the variation of one or more parameters of one or more Geant4 physics models involved in simulation studies. It also enables analysis of multiple variants of the resulting physics observables of interest in order to estimate the uncertainties associated with the simulation model choices. Based on modern event-processing infrastructure software, the toolkit offers a variety of attractive features, e.g. flexible run-time configurable workflow, comprehensive bookkeeping, easy to expand collection of analytical components. Design, implementation technology, and key functionalities of the toolkit are presented in this paper and illustrated with selected results.

Parameter Estimation of Partial Differential Equation Models

KAUST Repository

Xun, Xiaolei

2013-09-01

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

Parameter Estimation for Thurstone Choice Models

Energy Technology Data Exchange (ETDEWEB)

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

2017-04-24

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

Testing physical models for dipolar asymmetry with CMB polarization

Science.gov (United States)

Contreras, D.; Zibin, J. P.; Scott, D.; Banday, A. J.; Górski, K. M.

2017-12-01

The cosmic microwave background (CMB) temperature anisotropies exhibit a large-scale dipolar power asymmetry. To determine whether this is due to a real, physical modulation or is simply a large statistical fluctuation requires the measurement of new modes. Here we forecast how well CMB polarization data from Planck and future experiments will be able to confirm or constrain physical models for modulation. Fitting several such models to the Planck temperature data allows us to provide predictions for polarization asymmetry. While for some models and parameters Planck polarization will decrease error bars on the modulation amplitude by only a small percentage, we show, importantly, that cosmic-variance-limited (and in some cases even Planck) polarization data can decrease the errors by considerably better than the expectation of √{2 } based on simple ℓ-space arguments. We project that if the primordial fluctuations are truly modulated (with parameters as indicated by Planck temperature data) then Planck will be able to make a 2 σ detection of the modulation model with 20%-75% probability, increasing to 45%-99% when cosmic-variance-limited polarization is considered. We stress that these results are quite model dependent. Cosmic variance in temperature is important: combining statistically isotropic polarization with temperature data will spuriously increase the significance of the temperature signal with 30% probability for Planck.

Impact of B physics on model building and vice versa: An example

International Nuclear Information System (INIS)

Matias, Joaquim

2003-01-01

We motivate that the start-up of the B factories has opened a new precision flavour physics era, with an important effect on model building. Using as an example a left-right model with spontaneous CP violation, we will show how the inclusion of the new experimental data on B physics observables, together with the old observables coming from kaon physics, has significantly widened our capacity to strongly constrain the parameter space up to the point to exclude models. On the contrary, using certain hypotheses, mainly concerning isospin, we discuss how theory may help us to 'test' the data on charged, neutral and mixed B → πK decays once experimental errors will be reduced

TU Electric reactor physics model verification: Power reactor benchmark

International Nuclear Information System (INIS)

Willingham, C.E.; Killgore, M.R.

1988-01-01

Power reactor benchmark calculations using the advanced code package CASMO-3/SIMULATE-3 have been performed for six cycles of Prairie Island Unit 1. The reload fuel designs for the selected cycles included gadolinia as a burnable absorber, natural uranium axial blankets and increased water-to-fuel ratio. The calculated results for both startup reactor physics tests (boron endpoints, control rod worths, and isothermal temperature coefficients) and full power depletion results were compared to measured plant data. These comparisons show that the TU Electric reactor physics models accurately predict important measured parameters for power reactors

Physical modeling of spent-nuclear-fuel container

Directory of Open Access Journals (Sweden)

Wang Liping

2012-11-01

Full Text Available A new physical simulation model was developed to simulate the casting process of the ductile iron heavy section spent-nuclear-fuel container. In this physical simulation model, a heating unit with DR24 Fe-Cr-Al heating wires was used to compensate the heat loss across the non-natural surfaces of the sample, and a precise and reliable casting temperature controlling/monitoring system was employed to ensure the thermal behavior of the simulated casting to be similar to the actual casting. Also, a mould system was designed, in which changeable mould materials can be used for both the outside and inside moulds for different applications. The casting test was carried out with the designed mould and the cooling curves of central and edge points at different isothermal planes of the casting were obtained. Results show that for most isothermal planes, the temperature control system can keep the temperature differences within 6 ℃ between the edge points and the corresponding center points, indicating that this new physical simulation model has high simulation accuracy, and the mould developed can be used for optimization of casting parameters of spent-nuclear-fuel container, such as composition of ductile iron, the pouring temperature, the selection of mould material and design of cooling system. In addition, to maintain the spheroidalization of the ductile iron, the force-chilling should be used for the current physical simulation to ensure the solidification of casting in less than 2 h.

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

Science.gov (United States)

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

2015-01-01

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

Variability of dynamic source parameters inferred from kinematic models of past earthquakes

KAUST Repository

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.

Numerical Methods for a Multicomponent Two-Phase Interface Model with Geometric Mean Influence Parameters

KAUST Repository

Kou, Jisheng

2015-07-16

In this paper, we consider an interface model for multicomponent two-phase fluids with geometric mean influence parameters, which is popularly used to model and predict surface tension in practical applications. For this model, there are two major challenges in theoretical analysis and numerical simulation: the first one is that the influence parameter matrix is not positive definite; the second one is the complicated structure of the energy function, which requires us to find out a physically consistent treatment. To overcome these two challenging problems, we reduce the formulation of the energy function by employing a linear transformation and a weighted molar density, and furthermore, we propose a local minimum grand potential energy condition to establish the relation between the weighted molar density and mixture compositions. From this, we prove the existence of the solution under proper conditions and prove the maximum principle of the weighted molar density. For numerical simulation, we propose a modified Newton\\'s method for solving this nonlinear model and analyze its properties; we also analyze a finite element method with a physical-based adaptive mesh-refinement technique. Numerical examples are tested to verify the theoretical results and the efficiency of the proposed methods.

Numerical Methods for a Multicomponent Two-Phase Interface Model with Geometric Mean Influence Parameters

KAUST Repository

Kou, Jisheng; Sun, Shuyu

2015-01-01

In this paper, we consider an interface model for multicomponent two-phase fluids with geometric mean influence parameters, which is popularly used to model and predict surface tension in practical applications. For this model, there are two major challenges in theoretical analysis and numerical simulation: the first one is that the influence parameter matrix is not positive definite; the second one is the complicated structure of the energy function, which requires us to find out a physically consistent treatment. To overcome these two challenging problems, we reduce the formulation of the energy function by employing a linear transformation and a weighted molar density, and furthermore, we propose a local minimum grand potential energy condition to establish the relation between the weighted molar density and mixture compositions. From this, we prove the existence of the solution under proper conditions and prove the maximum principle of the weighted molar density. For numerical simulation, we propose a modified Newton's method for solving this nonlinear model and analyze its properties; we also analyze a finite element method with a physical-based adaptive mesh-refinement technique. Numerical examples are tested to verify the theoretical results and the efficiency of the proposed methods.

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...

Compost mixture influence of interactive physical parameters on microbial kinetics and substrate fractionation.

Science.gov (United States)

Mohajer, Ardavan; Tremier, Anne; Barrington, Suzelle; Teglia, Cecile

2010-01-01

Composting is a feasible biological treatment for the recycling of wastewater sludge as a soil amendment. The process can be optimized by selecting an initial compost recipe with physical properties that enhance microbial activity. The present study measured the microbial O(2) uptake rate (OUR) in 16 sludge and wood residue mixtures to estimate the kinetics parameters of maximum growth rate mu(m) and rate of organic matter hydrolysis K(h), as well as the initial biodegradable organic matter fractions present. The starting mixtures consisted of a wide range of moisture content (MC), waste to bulking agent (BA) ratio (W/BA ratio) and BA particle size, which were placed in a laboratory respirometry apparatus to measure their OUR over 4 weeks. A microbial model based on the activated sludge process was used to calculate the kinetic parameters and was found to adequately reproduced OUR curves over time, except for the lag phase and peak OUR, which was not represented and generally over-estimated, respectively. The maximum growth rate mu(m), was found to have a quadratic relationship with MC and a negative association with BA particle size. As a result, increasing MC up to 50% and using a smaller BA particle size of 8-12 mm was seen to maximize mu(m). The rate of hydrolysis K(h) was found to have a linear association with both MC and BA particle size. The model also estimated the initial readily biodegradable organic matter fraction, MB(0), and the slower biodegradable matter requiring hydrolysis, MH(0). The sum of MB(0) and MH(0) was associated with MC, W/BA ratio and the interaction between these two parameters, suggesting that O(2) availability was a key factor in determining the value of these two fractions. The study reinforced the idea that optimization of the physical characteristics of a compost mixture requires a holistic approach. 2010 Elsevier Ltd. All rights reserved.

Physics-based Inverse Problem to Deduce Marine Atmospheric Boundary Layer Parameters

Science.gov (United States)

2017-03-07

knowledge and capabilities in the use and development of inverse problem techniques to deduce atmospheric parameters. WORK COMPLETED The research completed...please find the Final Technical Report with SF 298 for Dr. Erin E. Hackett’s ONR grant entitled Physics -based Inverse Problem to Deduce Marine...From- To) 07/03/2017 Final Technica l Dec 2012- Dec 2016 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Physics -based Inverse Problem to Deduce Marine

An optimization method for parameters in reactor nuclear physics

International Nuclear Information System (INIS)

Jachic, J.

1982-01-01

An optimization method for two basic problems of Reactor Physics was developed. The first is the optimization of a plutonium critical mass and the bruding ratio for fast reactors in function of the radial enrichment distribution of the fuel used as control parameter. The second is the maximization of the generation and the plutonium burnup by an optimization of power temporal distribution. (E.G.) [pt

Multi-Higgs doublet models: physical parametrization, sum rules and unitarity bounds

Science.gov (United States)

Bento, Miguel P.; Haber, Howard E.; Romão, J. C.; Silva, João P.

2017-11-01

If the scalar sector of the Standard Model is non-minimal, one might expect multiple generations of the hypercharge-1/2 scalar doublet analogous to the generational structure of the fermions. In this work, we examine the structure of a Higgs sector consisting of N Higgs doublets (where N ≥ 2). It is particularly convenient to work in the so-called charged Higgs basis, in which the neutral Higgs vacuum expectation value resides entirely in the first Higgs doublet, and the charged components of remaining N - 1 Higgs doublets are mass-eigenstate fields. We elucidate the interactions of the gauge bosons with the physical Higgs scalars and the Goldstone bosons and show that they are determined by an N × 2 N matrix. This matrix depends on ( N - 1)(2 N - 1) real parameters that are associated with the mixing of the neutral Higgs fields in the charged Higgs basis. Among these parameters, N - 1 are unphysical (and can be removed by rephasing the physical charged Higgs fields), and the remaining 2( N - 1)2 parameters are physical. We also demonstrate a particularly simple form for the cubic interaction and some of the quartic interactions of the Goldstone bosons with the physical Higgs scalars. These results are applied in the derivation of Higgs coupling sum rules and tree-level unitarity bounds that restrict the size of the quartic scalar couplings. In particular, new applications to three Higgs doublet models with an order-4 CP symmetry and with a Z_3 symmetry, respectively, are presented.

Parameter extraction with neural networks

Science.gov (United States)

Cazzanti, Luca; Khan, Mumit; Cerrina, Franco

1998-06-01

In semiconductor processing, the modeling of the process is becoming more and more important. While the ultimate goal is that of developing a set of tools for designing a complete process (Technology CAD), it is also necessary to have modules to simulate the various technologies and, in particular, to optimize specific steps. This need is particularly acute in lithography, where the continuous decrease in CD forces the technologies to operate near their limits. In the development of a 'model' for a physical process, we face several levels of challenges. First, it is necessary to develop a 'physical model,' i.e. a rational description of the process itself on the basis of know physical laws. Second, we need an 'algorithmic model' to represent in a virtual environment the behavior of the 'physical model.' After a 'complete' model has been developed and verified, it becomes possible to do performance analysis. In many cases the input parameters are poorly known or not accessible directly to experiment. It would be extremely useful to obtain the values of these 'hidden' parameters from experimental results by comparing model to data. This is particularly severe, because the complexity and costs associated with semiconductor processing make a simple 'trial-and-error' approach infeasible and cost- inefficient. Even when computer models of the process already exists, obtaining data through simulations may be time consuming. Neural networks (NN) are powerful computational tools to predict the behavior of a system from an existing data set. They are able to adaptively 'learn' input/output mappings and to act as universal function approximators. In this paper we use artificial neural networks to build a mapping from the input parameters of the process to output parameters which are indicative of the performance of the process. Once the NN has been 'trained,' it is also possible to observe the process 'in reverse,' and to extract the values of the inputs which yield outputs

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

Science.gov (United States)

Kang, Ling; Zhou, Liwei

2018-02-01

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

Estimation of Physical Parameters in Linear and Nonlinear Dynamic Systems

DEFF Research Database (Denmark)

Knudsen, Morten

variance and confidence ellipsoid is demonstrated. The relation is based on a new theorem on maxima of an ellipsoid. The procedure for input signal design and physical parameter estimation is tested on a number of examples, linear as well as nonlinear and simulated as well as real processes, and it appears...

The Comparison of Some Physical and Physiological Parameters of Footballers

Science.gov (United States)

Ekinci, Ezgi Samar; Beyleroglu, Malik; Ulukan, Hasan; Konuklar, Ercan; Gürkan, Alper Cenk; Erbay, Adem

2016-01-01

In this study, it's to aim for comparison of some physical and physiological parameters of footballers at "The Erenler Sport Team" and "Didim Municipality Sport Team". Thirty volunteers sportsman from each two teams joined to this research. It measured the values of age, weight, length, flexibility, balance, power of left-right…

Application of regional physically-based landslide early warning model: tuning of the input parameters and validation of the results

Science.gov (United States)

D'Ambrosio, Michele; Tofani, Veronica; Rossi, Guglielmo; Salvatici, Teresa; Tacconi Stefanelli, Carlo; Rosi, Ascanio; Benedetta Masi, Elena; Pazzi, Veronica; Vannocci, Pietro; Catani, Filippo; Casagli, Nicola

2017-04-01

The Aosta Valley region is located in North-West Alpine mountain chain. The geomorphology of the region is characterized by steep slopes, high climatic and altitude (ranging from 400 m a.s.l of Dora Baltea's river floodplain to 4810 m a.s.l. of Mont Blanc) variability. In the study area (zone B), located in Eastern part of Aosta Valley, heavy rainfall of about 800-900 mm per year is the main landslides trigger. These features lead to a high hydrogeological risk in all territory, as mass movements interest the 70% of the municipality areas (mainly shallow rapid landslides and rock falls). An in-depth study of the geotechnical and hydrological properties of hillslopes controlling shallow landslides formation was conducted, with the aim to improve the reliability of deterministic model, named HIRESS (HIgh REsolution Stability Simulator). In particular, two campaigns of on site measurements and laboratory experiments were performed. The data obtained have been studied in order to assess the relationships existing among the different parameters and the bedrock lithology. The analyzed soils in 12 survey points are mainly composed of sand and gravel, with highly variable contents of silt. The range of effective internal friction angle (from 25.6° to 34.3°) and effective cohesion (from 0 kPa to 9.3 kPa) measured and the median ks (10E-6 m/s) value are consistent with the average grain sizes (gravelly sand). The data collected contributes to generate input map of parameters for HIRESS (static data). More static data are: volume weight, residual water content, porosity and grain size index. In order to improve the original formulation of the model, the contribution of the root cohesion has been also taken into account based on the vegetation map and literature values. HIRESS is a physically based distributed slope stability simulator for analyzing shallow landslide triggering conditions in real time and in large areas using parallel computational techniques. The software

Assessing uncertainty and sensitivity of model parameterizations and parameters in WRF affecting simulated surface fluxes and land-atmosphere coupling over the Amazon region

Science.gov (United States)

Qian, Y.; Wang, C.; Huang, M.; Berg, L. K.; Duan, Q.; Feng, Z.; Shrivastava, M. B.; Shin, H. H.; Hong, S. Y.

2016-12-01

This study aims to quantify the relative importance and uncertainties of different physical processes and parameters in affecting simulated surface fluxes and land-atmosphere coupling strength over the Amazon region. We used two-legged coupling metrics, which include both terrestrial (soil moisture to surface fluxes) and atmospheric (surface fluxes to atmospheric state or precipitation) legs, to diagnose the land-atmosphere interaction and coupling strength. Observations made using the Department of Energy's Atmospheric Radiation Measurement (ARM) Mobile Facility during the GoAmazon field campaign together with satellite and reanalysis data are used to evaluate model performance. To quantify the uncertainty in physical parameterizations, we performed a 120 member ensemble of simulations with the WRF model using a stratified experimental design including 6 cloud microphysics, 3 convection, 6 PBL and surface layer, and 3 land surface schemes. A multiple-way analysis of variance approach is used to quantitatively analyze the inter- and intra-group (scheme) means and variances. To quantify parameter sensitivity, we conducted an additional 256 WRF simulations in which an efficient sampling algorithm is used to explore the multiple-dimensional parameter space. Three uncertainty quantification approaches are applied for sensitivity analysis (SA) of multiple variables of interest to 20 selected parameters in YSU PBL and MM5 surface layer schemes. Results show consistent parameter sensitivity across different SA methods. We found that 5 out of 20 parameters contribute more than 90% total variance, and first-order effects dominate comparing to the interaction effects. Results of this uncertainty quantification study serve as guidance for better understanding the roles of different physical processes in land-atmosphere interactions, quantifying model uncertainties from various sources such as physical processes, parameters and structural errors, and providing insights for

Estimation of k-ε parameters using surrogate models and jet-in-crossflow data

Energy Technology Data Exchange (ETDEWEB)

Lefantzi, Sophia [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Ray, Jaideep [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Arunajatesan, Srinivasan [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Dechant, Lawrence [Sandia National Lab. (SNL-CA), Livermore, CA (United States)

2014-11-01

We demonstrate a Bayesian method that can be used to calibrate computationally expensive 3D RANS (Reynolds Av- eraged Navier Stokes) models with complex response surfaces. Such calibrations, conditioned on experimental data, can yield turbulence model parameters as probability density functions (PDF), concisely capturing the uncertainty in the parameter estimates. Methods such as Markov chain Monte Carlo (MCMC) estimate the PDF by sampling, with each sample requiring a run of the RANS model. Consequently a quick-running surrogate is used instead to the RANS simulator. The surrogate can be very difficult to design if the model's response i.e., the dependence of the calibration variable (the observable) on the parameter being estimated is complex. We show how the training data used to construct the surrogate can be employed to isolate a promising and physically realistic part of the parameter space, within which the response is well-behaved and easily modeled. We design a classifier, based on treed linear models, to model the "well-behaved region". This classifier serves as a prior in a Bayesian calibration study aimed at estimating 3 k - ε parameters ( C _μ, C _ε2 , C _ε1 ) from experimental data of a transonic jet-in-crossflow interaction. The robustness of the calibration is investigated by checking its predictions of variables not included in the cal- ibration data. We also check the limit of applicability of the calibration by testing at off-calibration flow regimes. We find that calibration yield turbulence model parameters which predict the flowfield far better than when the nomi- nal values of the parameters are used. Substantial improvements are still obtained when we use the calibrated RANS model to predict jet-in-crossflow at Mach numbers and jet strengths quite different from those used to generate the ex- perimental (calibration) data. Thus the primary reason for poor predictive skill of RANS, when using nominal

Hardrock Elastic Physical Properties: Birch's Seismic Parameter Revisited

Science.gov (United States)

Wu, M.; Milkereit, B.

2014-12-01

Identifying rock composition and properties is imperative in a variety of fields including geotechnical engineering, mining, and petroleum exploration, in order to accurately make any petrophysical calculations. Density is, in particular, an important parameter that allows us to differentiate between lithologies and estimate or calculate other petrophysical properties. It is well established that compressional and shear wave velocities of common crystalline rocks increase with increasing densities (i.e. the Birch and Nafe-Drake relationships). Conventional empirical relations do not take into account S-wave velocity. Physical properties of Fe-oxides and massive sulfides, however, differ significantly from the empirical velocity-density relationships. Currently, acquiring in-situ density data is challenging and problematic, and therefore, developing an approximation for density based on seismic wave velocity and elastic moduli would be beneficial. With the goal of finding other possible or better relationships between density and the elastic moduli, a database of density, P-wave velocity, S-wave velocity, bulk modulus, shear modulus, Young's modulus, and Poisson's ratio was compiled based on a multitude of lab samples. The database is comprised of isotropic, non-porous metamorphic rock. Multi-parameter cross plots of the various elastic parameters have been analyzed in order to find a suitable parameter combination that reduces high density outliers. As expected, the P-wave velocity to S-wave velocity ratios show no correlation with density. However, Birch's seismic parameter, along with the bulk modulus, shows promise in providing a link between observed compressional and shear wave velocities and rock densities, including massive sulfides and Fe-oxides.

Dynamic modeling of physical phenomena for PRAs using neural networks

International Nuclear Information System (INIS)

Benjamin, A.S.; Brown, N.N.; Paez, T.L.

1998-04-01

In most probabilistic risk assessments, there is a set of accident scenarios that involves the physical responses of a system to environmental challenges. Examples include the effects of earthquakes and fires on the operability of a nuclear reactor safety system, the effects of fires and impacts on the safety integrity of a nuclear weapon, and the effects of human intrusions on the transport of radionuclides from an underground waste facility. The physical responses of the system to these challenges can be quite complex, and their evaluation may require the use of detailed computer codes that are very time consuming to execute. Yet, to perform meaningful probabilistic analyses, it is necessary to evaluate the responses for a large number of variations in the input parameters that describe the initial state of the system, the environments to which it is exposed, and the effects of human interaction. Because the uncertainties of the system response may be very large, it may also be necessary to perform these evaluations for various values of modeling parameters that have high uncertainties, such as material stiffnesses, surface emissivities, and ground permeabilities. The authors have been exploring the use of artificial neural networks (ANNs) as a means for estimating the physical responses of complex systems to phenomenological events such as those cited above. These networks are designed as mathematical constructs with adjustable parameters that can be trained so that the results obtained from the networks will simulate the results obtained from the detailed computer codes. The intent is for the networks to provide an adequate simulation of the detailed codes over a significant range of variables while requiring only a small fraction of the computer processing time required by the detailed codes. This enables the authors to integrate the physical response analyses into the probabilistic models in order to estimate the probabilities of various responses

Universally sloppy parameter sensitivities in systems biology models.

Directory of Open Access Journals (Sweden)

Ryan N Gutenkunst

2007-10-01

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

Universally sloppy parameter sensitivities in systems biology models.

Science.gov (United States)

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

2007-10-01

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

Residential Demand Response Behaviour Modeling applied to Cyber-physical Intrusion Detection

DEFF Research Database (Denmark)

Heussen, Kai; Tyge, Emil; Kosek, Anna Magdalena

2017-01-01

by a mix of physical system parameters, exogenous influences, user behaviour and preferences, which can be characterized by unstructured models such as a time-varying finite impulse response. In this study, which is based on field data, it is shown how this characteristic response behaviours can...

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

Directory of Open Access Journals (Sweden)

Jonathan R Karr

2015-05-01

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

Pseudo-dynamic source modelling with 1-point and 2-point statistics of earthquake source parameters

KAUST Repository

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.

Flavor physics in the 3-3-1 models

International Nuclear Information System (INIS)

Pleitez, Vicente

2013-01-01

Full text: Flavor Physics is entering in a new precision era that will allow to uncover new physics scenarios at the TeV scale if they really do exist. We will discuss flavor changing neutral currents (FCNC) processes in the context of the minimal 3-3-1 model. In particular, we show that in this model, these processes do not impose necessarily strong constraints on the mass of the Z' of the model if we also consider the neutral scalar contributions to such processes, like the neutral meson mass differences and their rare semi-leptonic decays. We first obtain numerical values for all the mixing matrices of the model i.e., the unitary matrices that rotate the left- and right-handed quarks in each charge sector and give the correct mass of all the quarks and the CKM mixing matrix. Then, we find that there is a range of parameters in which the neutral scalar contributions to these processes may interfere with those of the Z', implying that this vector boson may be lighter than it has been thought. The model with right-handed neutrino will also brief discussed. (author)

Definition and solution of a stochastic inverse problem for the Manning's n parameter field in hydrodynamic models

Science.gov (United States)

Butler, T.; Graham, L.; Estep, D.; Dawson, C.; Westerink, J. J.

2015-04-01

The uncertainty in spatially heterogeneous Manning's n fields is quantified using a novel formulation and numerical solution of stochastic inverse problems for physics-based models. The uncertainty is quantified in terms of a probability measure and the physics-based model considered here is the state-of-the-art ADCIRC model although the presented methodology applies to other hydrodynamic models. An accessible overview of the formulation and solution of the stochastic inverse problem in a mathematically rigorous framework based on measure theory is presented. Technical details that arise in practice by applying the framework to determine the Manning's n parameter field in a shallow water equation model used for coastal hydrodynamics are presented and an efficient computational algorithm and open source software package are developed. A new notion of "condition" for the stochastic inverse problem is defined and analyzed as it relates to the computation of probabilities. This notion of condition is investigated to determine effective output quantities of interest of maximum water elevations to use for the inverse problem for the Manning's n parameter and the effect on model predictions is analyzed.

Rotating Parabolic-Reflector Antenna Target in SAR Data: Model, Characteristics, and Parameter Estimation

Directory of Open Access Journals (Sweden)

Bin Deng

2013-01-01

Full Text Available Parabolic-reflector antennas (PRAs, usually possessing rotation, are a particular type of targets of potential interest to the synthetic aperture radar (SAR community. This paper is aimed to investigate PRA’s scattering characteristics and then to extract PRA’s parameters from SAR returns, for supporting image interpretation and target recognition. We at first obtain both closed-form and numeric solutions to PRA’s backscattering by geometrical optics (GO, physical optics, and graphical electromagnetic computation, respectively. Based on the GO solution, a migratory scattering center model is at first presented for representing the movement of the specular point with aspect angle, and then a hybrid model, named the migratory/micromotion scattering center (MMSC model, is proposed for characterizing a rotating PRA in the SAR geometry, which incorporates PRA’s rotation into its migratory scattering center model. Additionally, we in detail analyze PRA’s radar characteristics on radar cross-section, high-resolution range profiles, time-frequency distribution, and 2D images, which also confirm the models proposed. A maximal likelihood estimator is developed for jointly solving the MMSC model for PRA’s multiple parameters by optimization. By exploiting the aforementioned characteristics, the coarse parameter estimation guarantees convergency upon global minima. The signatures recovered can be favorably utilized for SAR image interpretation and target recognition.

ANALYSIS THE DIURNAL VARIATIONS ON SELECTED PHYSICAL AND PHYSIOLOGICAL PARAMETERS

Directory of Open Access Journals (Sweden)

A. MAHABOOBJAN

2010-12-01

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

Physical model for membrane protrusions during spreading

International Nuclear Information System (INIS)

Chamaraux, F; Ali, O; Fourcade, B; Keller, S; Bruckert, F

2008-01-01

During cell spreading onto a substrate, the kinetics of the contact area is an observable quantity. This paper is concerned with a physical approach to modeling this process in the case of ameboid motility where the membrane detaches itself from the underlying cytoskeleton at the leading edge. The physical model we propose is based on previous reports which highlight that membrane tension regulates cell spreading. Using a phenomenological feedback loop to mimic stress-dependent biochemistry, we show that the actin polymerization rate can be coupled to the stress which builds up at the margin of the contact area between the cell and the substrate. In the limit of small variation of membrane tension, we show that the actin polymerization rate can be written in a closed form. Our analysis defines characteristic lengths which depend on elastic properties of the membrane–cytoskeleton complex, such as the membrane–cytoskeleton interaction, and on molecular parameters, the rate of actin polymerization. We discuss our model in the case of axi-symmetric and non-axi-symmetric spreading and we compute the characteristic time scales as a function of fundamental elastic constants such as the strength of membrane–cytoskeleton adherence

A Physics-Inspired Mechanistic Model of Migratory Movement Patterns in Birds.

Science.gov (United States)

Revell, Christopher; Somveille, Marius

2017-08-29

In this paper, we introduce a mechanistic model of migratory movement patterns in birds, inspired by ideas and methods from physics. Previous studies have shed light on the factors influencing bird migration but have mainly relied on statistical correlative analysis of tracking data. Our novel method offers a bottom up explanation of population-level migratory movement patterns. It differs from previous mechanistic models of animal migration and enables predictions of pathways and destinations from a given starting location. We define an environmental potential landscape from environmental data and simulate bird movement within this landscape based on simple decision rules drawn from statistical mechanics. We explore the capacity of the model by qualitatively comparing simulation results to the non-breeding migration patterns of a seabird species, the Black-browed Albatross (Thalassarche melanophris). This minimal, two-parameter model was able to capture remarkably well the previously documented migration patterns of the Black-browed Albatross, with the best combination of parameter values conserved across multiple geographically separate populations. Our physics-inspired mechanistic model could be applied to other bird and highly-mobile species, improving our understanding of the relative importance of various factors driving migration and making predictions that could be useful for conservation.

Chemical abundances and physical parameters of RR Lyrae stars

International Nuclear Information System (INIS)

Manduca, A.

1980-01-01

A grid of model stellar atmospheres has been calculated with a range of physical parameters which effectively cover RR Lyrae stars over all phases of their pulsation cycle. The models, calculated with the computer program MARCS, are flux-constant and include the effects of convection and line blanketing. Synthetic spectra were calculated for these models from 3000 A to 9600 A at 0.1 A resolution using the computer program SSG. These spectra were used directly in the applications below and were also used to computer theoretical colors on the UBVR, Stromgren uvby, and Walraven systems for the models. The uvby colors were used in determinations of effective temperature and surface gravity from photometry by various observers. The models, synthetic spectra, and colors were then applied to the problems detailed below. The data collected by Freeman and Rodgers (1975) for 25 RR Lyrae stars in ω Cen was reanalyzed with an alternative, synthetic spectrum approach to the calibration of their theoretical relations. The results confirm a wide range in calcium abundance for the stars in the cluster but at much lower values than reported by Freeman and Rodgers: a range of [Ca/H] = -1.0 to -1.9 was found. A theoretical calibration was performed for the ΔS system of determining metal abundances for RR Lyrae stars. The results support the existing empirical calibration of Butler in the range [Fe/H] = -0.6 to -2.2 and indicate how the calibration should be extrapolated to even lower metal abundances. For higher metal abundances, however, our calibration yields [Fe/H] values lower than Butler by as much as 0.4. Possible explanations of this discrepancy are investigated and the implications are discussed

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.

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

Science.gov (United States)

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

2009-05-01

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

Physically-based modelling of polycrystalline semiconductor devices

International Nuclear Information System (INIS)

Lee, S.

2000-01-01

Thin-film technology using polycrystalline semiconductors has been widely applied to active-matrix-addressed liquid crystal displays (AMLCDs) where thin-film transistors act as digital pixel switches. Research and development is in progress to integrate the driver circuits around the peripheral of the display, resulting in significant cost reduction of connections between rows and columns and the peripheral circuitry. For this latter application, where for instance it is important to control the greyscale voltage level delivered to the pixel, an understanding of device behaviour is required so that models can be developed for analogue circuit simulation. For this purpose, various analytical models have been developed based on that of Seto who considered the effect of monoenergetic trap states and grain boundaries in polycrystalline materials but not the contribution of the grains to the electrical properties. The principal aim of this thesis is to describe the use of a numerical device simulator (ATLAS) as a tool to investigate the physics of the trapping process involved in the device operation, which additionally takes into account the effect of multienergetic trapping levels and the contribution of the grain into the modelling. A study of the conventional analytical models is presented, and an alternative approach is introduced which takes into account the grain regions to enhance the accuracy of the analytical modelling. A physically-based discrete-grain-boundary model and characterisation method are introduced to study the effects of the multienergetic trap states on the electrical characteristics of poly-TFTs using CdSe devices as the experimental example, and the electrical parameters such as the density distribution of the trapping states are extracted. The results show excellent agreement between the simulation and experimental data. The limitations of this proposed physical model are also studied and discussed. (author)

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

Science.gov (United States)

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

1995-01-01

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

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

International Nuclear Information System (INIS)

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

2010-01-01

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

A physics-based probabilistic forecasting model for rainfall-induced shallow landslides at regional scale

Science.gov (United States)

Zhang, Shaojie; Zhao, Luqiang; Delgado-Tellez, Ricardo; Bao, Hongjun

2018-03-01

Conventional outputs of physics-based landslide forecasting models are presented as deterministic warnings by calculating the safety factor (Fs) of potentially dangerous slopes. However, these models are highly dependent on variables such as cohesion force and internal friction angle which are affected by a high degree of uncertainty especially at a regional scale, resulting in unacceptable uncertainties of Fs. Under such circumstances, the outputs of physical models are more suitable if presented in the form of landslide probability values. In order to develop such models, a method to link the uncertainty of soil parameter values with landslide probability is devised. This paper proposes the use of Monte Carlo methods to quantitatively express uncertainty by assigning random values to physical variables inside a defined interval. The inequality Fs soil mechanical parameters and is used to create a physics-based probabilistic forecasting model for rainfall-induced shallow landslides. The prediction ability of this model was tested in a case study, in which simulated forecasting of landslide disasters associated with heavy rainfalls on 9 July 2013 in the Wenchuan earthquake region of Sichuan province, China, was performed. The proposed model successfully forecasted landslides in 159 of the 176 disaster points registered by the geo-environmental monitoring station of Sichuan province. Such testing results indicate that the new model can be operated in a highly efficient way and show more reliable results, attributable to its high prediction accuracy. Accordingly, the new model can be potentially packaged into a forecasting system for shallow landslides providing technological support for the mitigation of these disasters at regional scale.

The application of model with lumped parameters for transient condition analyses of NPP; Primena modela sa koncentrisanim parametrima za analize pelaznih stanja nukleane elektrane

Energy Technology Data Exchange (ETDEWEB)

Stankovic, B [Institut GOSA, Beograd (Yugoslavia); Stevanovic, V [Masinski fakultet, Beograd (Yugoslavia)

1985-07-01

The transient behaviour of NPP Krsko during the accident of pressurizer spray valve stuck open has been simulated y lumped parameters model of the PWR coolant system components, developed at the faculty of Mechanical Engineering, University of Belgrade. The elementary volumes which are characterised by the process and state parameters, and by junctions which are characterised by the geometrical and flow parameters are basic structure of physical model. The process parameters obtained by the model RESI, show qualitative agreement with the measured valves, in a degree in which the actions of reactor safety engineered system and emergency core cooling system are adequately modelled; in spite of the elementary physical model structure and only the modelling of thermal process in reactor core and equilibrium conditions of pressurizer and steam generator. The pressurizer pressure and liquid level predicted by the non-equilibrium pressurizer model SOP show good agreement until the HIPS (high pressure pumps) is activated. (author)

First-order exchange coefficient coupling for simulating surface water-groundwater interactions: Parameter sensitivity and consistency with a physics-based approach

Science.gov (United States)

Ebel, B.A.; Mirus, B.B.; Heppner, C.S.; VanderKwaak, J.E.; Loague, K.

2009-01-01

Distributed hydrologic models capable of simulating fully-coupled surface water and groundwater flow are increasingly used to examine problems in the hydrologic sciences. Several techniques are currently available to couple the surface and subsurface; the two most frequently employed approaches are first-order exchange coefficients (a.k.a., the surface conductance method) and enforced continuity of pressure and flux at the surface-subsurface boundary condition. The effort reported here examines the parameter sensitivity of simulated hydrologic response for the first-order exchange coefficients at a well-characterized field site using the fully coupled Integrated Hydrology Model (InHM). This investigation demonstrates that the first-order exchange coefficients can be selected such that the simulated hydrologic response is insensitive to the parameter choice, while simulation time is considerably reduced. Alternatively, the ability to choose a first-order exchange coefficient that intentionally decouples the surface and subsurface facilitates concept-development simulations to examine real-world situations where the surface-subsurface exchange is impaired. While the parameters comprising the first-order exchange coefficient cannot be directly estimated or measured, the insensitivity of the simulated flow system to these parameters (when chosen appropriately) combined with the ability to mimic actual physical processes suggests that the first-order exchange coefficient approach can be consistent with a physics-based framework. Copyright ?? 2009 John Wiley & Sons, Ltd.

Parameter Sensitivity of High–Order Equivalent Circuit Models Of Turbine Generator

Directory of Open Access Journals (Sweden)

T. Niewierowicz–Swiecicka

2010-01-01

Full Text Available This work shows the results of a parametric sensitivity analysis applied to a state–space representation of high–order two–axis equivalent circuits (ECs of a turbo generator (150 MVA, 120 MW, 13.8 kV y 50 Hz. The main purpose of this study is to evaluate each parameter impact on the transient response of the analyzed two–axis models –d–axis ECs with one to five damper branches and q–axis ECs from one to four damper branches–. The parametric sensitivity concept is formulated in a general context and the sensibility function is established from the generator response to a short circuit condition. Results ponder the importance played by each parameter in the model behavior. The algorithms were design within MATLAB® environment. The study gives way to conclusions on electromagnetic aspects of solid rotor synchronous generators that have not been previously studied. The methodology presented here can be applied to any other physical system.

Evaluating performance of simplified physically based models for shallow landslide susceptibility

Directory of Open Access Journals (Sweden)

G. Formetta

2016-11-01

Full Text Available Rainfall-induced shallow landslides can lead to loss of life and significant damage to private and public properties, transportation systems, etc. Predicting locations that might be susceptible to shallow landslides is a complex task and involves many disciplines: hydrology, geotechnical science, geology, hydrogeology, geomorphology, and statistics. Two main approaches are commonly used: statistical or physically based models. Reliable model applications involve automatic parameter calibration, objective quantification of the quality of susceptibility maps, and model sensitivity analyses. This paper presents a methodology to systemically and objectively calibrate, verify, and compare different models and model performance indicators in order to identify and select the models whose behavior is the most reliable for particular case studies.The procedure was implemented in a package of models for landslide susceptibility analysis and integrated in the NewAge-JGrass hydrological model. The package includes three simplified physically based models for landslide susceptibility analysis (M1, M2, and M3 and a component for model verification. It computes eight goodness-of-fit indices by comparing pixel-by-pixel model results and measurement data. The integration of the package in NewAge-JGrass uses other components, such as geographic information system tools, to manage input–output processes, and automatic calibration algorithms to estimate model parameters. The system was applied for a case study in Calabria (Italy along the Salerno–Reggio Calabria highway, between Cosenza and Altilia. The area is extensively subject to rainfall-induced shallow landslides mainly because of its complex geology and climatology. The analysis was carried out considering all the combinations of the eight optimized indices and the three models. Parameter calibration, verification, and model performance assessment were performed by a comparison with a detailed landslide

Potential of X-Band TerraSAR-X and COSMO-SkyMed SAR Data for the Assessment of Physical Soil Parameters

Directory of Open Access Journals (Sweden)

Azza Gorrab

2015-01-01

Full Text Available The aim of this paper is to analyze the potential of X-band SAR measurements (COSMO-SkyMed and TerraSAR-X made over bare soils for the estimation of soil moisture and surface geometry parameters at a semi-arid site in Tunisia (North Africa. Radar signals acquired with different configurations (HH and VV polarizations, incidence angles of 26° and 36° are statistically compared with ground measurements (soil moisture and roughness parameters. The radar measurements are found to be highly sensitive to the various soil parameters of interest. A linear relationship is determined for the radar signals as a function of volumetric soil moisture, and a logarithmic correlation is observed between the radar signals and three surface roughness parameters: the root mean square height (Hrms, the parameter Zs = Hrms2/l (where l is the correlation length and the parameter Zg = Hrms × (Hrms/lα (where α is the power of the surface height correlation function. The highest dynamic sensitivity is observed for Zg at high incidence angles. Finally, the performance of different physical and semi-empirical backscattering models (IEM, Baghdadi-calibrated IEM and Dubois models is compared with SAR measurements. The results provide an indication of the limits of validity of the IEM and Dubois models, for various radar configurations and roughness conditions. Considerable improvements in the IEM model performance are observed using the Baghdadi-calibrated version of this model.

Numerical Modeling of Piezoelectric Transducers Using Physical Parameters

NARCIS (Netherlands)

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

Exploiting intrinsic fluctuations to identify model parameters.

Science.gov (United States)

Zimmer, Christoph; Sahle, Sven; Pahle, Jürgen

2015-04-01

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

Simultaneous fitting of statistical-model parameters to symmetric and asymmetric fission cross sections

International Nuclear Information System (INIS)

Mancusi, D; Charity, R J; Cugnon, J

2013-01-01

The de-excitation of compound nuclei has been successfully described for several decades by means of statistical models. However, accurate predictions require some fine-tuning of the model parameters. This task can be simplified by studying several entrance channels, which populate different regions of the parameter space of the compound nucleus. Fusion reactions play an important role in this strategy because they minimise the uncertainty on the entrance channel by fixing mass, charge and excitation energy of the compound nucleus. If incomplete fusion is negligible, the only uncertainty on the compound nucleus comes from the spin distribution. However, some de-excitation channels, such as fission, are quite sensitive to spin. Other entrance channels can then be used to discriminate between equivalent parameter sets. The focus of this work is on fission and intermediate-mass-fragment emission cross sections of compound nuclei with 70 70 ≲ A ≲ 240. 240. The statistical de-excitation model is GEMINI++. The choice of the observables is natural in the framework of GEMINI++, which describes fragment emission using a fissionlike formalism. Equivalent parameter sets for fusion reactions can be resolved using the spallation entrance channel. This promising strategy can lead to the identification of a minimal set of physical ingredients necessary for a unified quantitative description of nuclear de-excitation.

Excellence in Physics Education Award: Modeling Theory for Physics Instruction

Science.gov (United States)

Hestenes, David

2014-03-01

All humans create mental models to plan and guide their interactions with the physical world. Science has greatly refined and extended this ability by creating and validating formal scientific models of physical things and processes. Research in physics education has found that mental models created from everyday experience are largely incompatible with scientific models. This suggests that the fundamental problem in learning and understanding science is coordinating mental models with scientific models. Modeling Theory has drawn on resources of cognitive science to work out extensive implications of this suggestion and guide development of an approach to science pedagogy and curriculum design called Modeling Instruction. Modeling Instruction has been widely applied to high school physics and, more recently, to chemistry and biology, with noteworthy results.

Numerical tools for musical instruments acoustics: analysing nonlinear physical models using continuation of periodic solutions

OpenAIRE

Karkar , Sami; Vergez , Christophe; Cochelin , Bruno

2012-01-01

International audience; We propose a new approach based on numerical continuation and bifurcation analysis for the study of physical models of instruments that produce self- sustained oscillation. Numerical continuation consists in following how a given solution of a set of equations is modified when one (or several) parameter of these equations are allowed to vary. Several physical models (clarinet, saxophone, and violin) are formulated as nonlinear dynamical systems, whose periodic solution...

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

Efficient Ensemble State-Parameters Estimation Techniques in Ocean Ecosystem Models: Application to the North Atlantic

Science.gov (United States)

El Gharamti, M.; Bethke, I.; Tjiputra, J.; Bertino, L.

2016-02-01

Given the recent strong international focus on developing new data assimilation systems for biological models, we present in this comparative study the application of newly developed state-parameters estimation tools to an ocean ecosystem model. It is quite known that the available physical models are still too simple compared to the complexity of the ocean biology. Furthermore, various biological parameters remain poorly unknown and hence wrong specifications of such parameters can lead to large model errors. Standard joint state-parameters augmentation technique using the ensemble Kalman filter (Stochastic EnKF) has been extensively tested in many geophysical applications. Some of these assimilation studies reported that jointly updating the state and the parameters might introduce significant inconsistency especially for strongly nonlinear models. This is usually the case for ecosystem models particularly during the period of the spring bloom. A better handling of the estimation problem is often carried out by separating the update of the state and the parameters using the so-called Dual EnKF. The dual filter is computationally more expensive than the Joint EnKF but is expected to perform more accurately. Using a similar separation strategy, we propose a new EnKF estimation algorithm in which we apply a one-step-ahead smoothing to the state. The new state-parameters estimation scheme is derived in a consistent Bayesian filtering framework and results in separate update steps for the state and the parameters. Unlike the classical filtering path, the new scheme starts with an update step and later a model propagation step is performed. We test the performance of the new smoothing-based schemes against the standard EnKF in a one-dimensional configuration of the Norwegian Earth System Model (NorESM) in the North Atlantic. We use nutrients profile (up to 2000 m deep) data and surface partial CO2 measurements from Mike weather station (66o N, 2o E) to estimate

Parameter identification of process simulation models as a means for knowledge acquisition and technology transfer

Science.gov (United States)

Batzias, Dimitris F.; Ifanti, Konstantina

2012-12-01

Process simulation models are usually empirical, therefore there is an inherent difficulty in serving as carriers for knowledge acquisition and technology transfer, since their parameters have no physical meaning to facilitate verification of the dependence on the production conditions; in such a case, a 'black box' regression model or a neural network might be used to simply connect input-output characteristics. In several cases, scientific/mechanismic models may be proved valid, in which case parameter identification is required to find out the independent/explanatory variables and parameters, which each parameter depends on. This is a difficult task, since the phenomenological level at which each parameter is defined is different. In this paper, we have developed a methodological framework under the form of an algorithmic procedure to solve this problem. The main parts of this procedure are: (i) stratification of relevant knowledge in discrete layers immediately adjacent to the layer that the initial model under investigation belongs to, (ii) design of the ontology corresponding to these layers, (iii) elimination of the less relevant parts of the ontology by thinning, (iv) retrieval of the stronger interrelations between the remaining nodes within the revised ontological network, and (v) parameter identification taking into account the most influential interrelations revealed in (iv). The functionality of this methodology is demonstrated by quoting two representative case examples on wastewater treatment.

Physical and JIT Model Based Hybrid Modeling Approach for Building Thermal Load Prediction

Science.gov (United States)

Iino, Yutaka; Murai, Masahiko; Murayama, Dai; Motoyama, Ichiro

Energy conservation in building fields is one of the key issues in environmental point of view as well as that of industrial, transportation and residential fields. The half of the total energy consumption in a building is occupied by HVAC (Heating, Ventilating and Air Conditioning) systems. In order to realize energy conservation of HVAC system, a thermal load prediction model for building is required. This paper propose a hybrid modeling approach with physical and Just-in-Time (JIT) model for building thermal load prediction. The proposed method has features and benefits such as, (1) it is applicable to the case in which past operation data for load prediction model learning is poor, (2) it has a self checking function, which always supervises if the data driven load prediction and the physical based one are consistent or not, so it can find if something is wrong in load prediction procedure, (3) it has ability to adjust load prediction in real-time against sudden change of model parameters and environmental conditions. The proposed method is evaluated with real operation data of an existing building, and the improvement of load prediction performance is illustrated.

Modeling Parameters of Reliability of Technological Processes of Hydrocarbon Pipeline Transportation

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

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

2014-01-01

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

Statistical physics of pairwise probability models

Directory of Open Access Journals (Sweden)

Yasser Roudi

2009-11-01

Full Text Available Statistical models for describing the probability distribution over the states of biological systems are commonly used for dimensional reduction. Among these models, pairwise models are very attractive in part because they can be fit using a reasonable amount of data: knowledge of the means and correlations between pairs of elements in the system is sufficient. Not surprisingly, then, using pairwise models for studying neural data has been the focus of many studies in recent years. In this paper, we describe how tools from statistical physics can be employed for studying and using pairwise models. We build on our previous work on the subject and study the relation between different methods for fitting these models and evaluating their quality. In particular, using data from simulated cortical networks we study how the quality of various approximate methods for inferring the parameters in a pairwise model depends on the time bin chosen for binning the data. We also study the effect of the size of the time bin on the model quality itself, again using simulated data. We show that using finer time bins increases the quality of the pairwise model. We offer new ways of deriving the expressions reported in our previous work for assessing the quality of pairwise models.

Establishing statistical models of manufacturing parameters

International Nuclear Information System (INIS)

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

1991-01-01

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

Parameter Uncertainty on AGCM-simulated Tropical Cyclones

Science.gov (United States)

He, F.

2015-12-01

This work studies the parameter uncertainty on tropical cyclone (TC) simulations in Atmospheric General Circulation Models (AGCMs) using the Reed-Jablonowski TC test case, which is illustrated in Community Atmosphere Model (CAM). It examines the impact from 24 parameters across the physical parameterization schemes that represent the convection, turbulence, precipitation and cloud processes in AGCMs. The one-at-a-time (OAT) sensitivity analysis method first quantifies their relative importance on TC simulations and identifies the key parameters to the six different TC characteristics: intensity, precipitation, longwave cloud radiative forcing (LWCF), shortwave cloud radiative forcing (SWCF), cloud liquid water path (LWP) and ice water path (IWP). Then, 8 physical parameters are chosen and perturbed using the Latin-Hypercube Sampling (LHS) method. The comparison between OAT ensemble run and LHS ensemble run shows that the simulated TC intensity is mainly affected by the parcel fractional mass entrainment rate in Zhang-McFarlane (ZM) deep convection scheme. The nonlinear interactive effect among different physical parameters is negligible on simulated TC intensity. In contrast, this nonlinear interactive effect plays a significant role in other simulated tropical cyclone characteristics (precipitation, LWCF, SWCF, LWP and IWP) and greatly enlarge their simulated uncertainties. The statistical emulator Extended Multivariate Adaptive Regression Splines (EMARS) is applied to characterize the response functions for nonlinear effect. Last, we find that the intensity uncertainty caused by physical parameters is in a degree comparable to uncertainty caused by model structure (e.g. grid) and initial conditions (e.g. sea surface temperature, atmospheric moisture). These findings suggest the importance of using the perturbed physics ensemble (PPE) method to revisit tropical cyclone prediction under climate change scenario.

Studies of the Impact of Magnetic Field Uncertainties on Physics Parameters of the Mu2e Experiment

Energy Technology Data Exchange (ETDEWEB)

Bradascio, Federica [Pisa U.

2016-01-01

The Mu2e experiment at Fermilab will search for a signature of charged lepton flavor violation, an effect prohibitively too small to be observed within the Standard Model of particle physics. Therefore, its observation is a signal of new physics. The signature that Mu2e will search for is the ratio of the rate of neutrinoless coherent conversion of muons into electrons in the field of a nucleus, relative to the muon capture rate by the nucleus. The conversion process is an example of charged lepton flavor violation. This experiment aims at a sensitivity of four orders of magnitude higher than previous related experiments. The desired sensitivity implies highly demanding requirements of accuracy in the design and conduct of the experiment. It is therefore important to investigate the tolerance of the experiment to instrumental uncertainties and provide specifications that the design and construction must meet. This is the core of the work reported in this thesis. The design of the experiment is based on three superconducting solenoid magnets. The most important uncertainties in the magnetic field of the solenoids can arise from misalignments of the Transport Solenoid, which transfers the beam from the muon production area to the detector area and eliminates beam-originating backgrounds. In this thesis, the field uncertainties induced by possible misalignments and their impact on the physics parameters of the experiment are examined. The physics parameters include the muon and pion stopping rates and the scattering of beam electrons off the capture target, which determine the signal, intrinsic background and late-arriving background yields, respectively. Additionally, a possible test of the Transport Solenoid alignment with low momentum electrons is examined, as an alternative option to measure its field with conventional probes, which is technically difficult due to mechanical interference. Misalignments of the Transport Solenoid were simulated using standard

Some tests for parameter constancy in cointegrated VAR-models

DEFF Research Database (Denmark)

Hansen, Henrik; Johansen, Søren

1999-01-01

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

Edge Modeling by Two Blur Parameters in Varying Contrasts.

Science.gov (United States)

Seo, Suyoung

2018-06-01

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

Simplified Physics Based Models Research Topical Report on Task #2

Energy Technology Data Exchange (ETDEWEB)

Mishra, Srikanta; Ganesh, Priya

2014-10-31

We present a simplified-physics based approach, where only the most important physical processes are modeled, to develop and validate simplified predictive models of CO2 sequestration in deep saline formation. The system of interest is a single vertical well injecting supercritical CO2 into a 2-D layered reservoir-caprock system with variable layer permeabilities. We use a set of well-designed full-physics compositional simulations to understand key processes and parameters affecting pressure propagation and buoyant plume migration. Based on these simulations, we have developed correlations for dimensionless injectivity as a function of the slope of fractional-flow curve, variance of layer permeability values, and the nature of vertical permeability arrangement. The same variables, along with a modified gravity number, can be used to develop a correlation for the total storage efficiency within the CO2 plume footprint. Similar correlations are also developed to predict the average pressure within the injection reservoir, and the pressure buildup within the caprock.

THE EFFECTS OF PHYSICAL TRAINING ON CARDIOVASCULAR PARAMETERS AND REDUCTION OF VISCERAL FATTY TISSUE

Directory of Open Access Journals (Sweden)

Todorka Savic

2007-12-01

Full Text Available Regular physical activity and good physical condition are widely accepted as factors that reduce all-cause mortality and improve a number of health outcomes.The aim of this study was to investigate the effects of aerobic exercise training on cardiovascular parameters and reduction of visceral obesity in patients with stable coronary artery disease participating in a cardiovascular rehabilitation exercise program. Fifty-two patients with stable coronary heart disease who had been accepted into the outpatient Phase II cardiovascular rehabilitation program at the Institute for Treatment and Rehabilitation of Cardiovascular Diseases Niska Banja, Nis, Serbia,were recruited for this study. All patients were divided into two groups: group with stable coronary heart disease who had regular aerobic physical training during 6weeks and control without physical training. There were not significant differences in body weight, body mass index, waist circumference and waist /hip ratio in start and at the end of physical training program. Physical training did not reduce the above mentioned parameters after 6 weeks. There were not significant differences in systolic and diastolic blood pressure at the beginning and at the end of the observed period.In group with physical training, a significant reduction of systolic and diastolic blood pressure after cardiovascular rehabilitation were reported (p<0.05. In patients with moderate aerobic physical training, a significant decrease in the heart rate was registered after the 6-week follow-up (p<0.05, while heart rate was significantly lower in this group compared to group with sedentary lifestyle (p<0.05. The effects of the 6-week cardiovascular rehabilitation on lipid parameters is visible only in slight reduction of triglyceride values in group with physical training (p<0.05. The concentration of triglycerides were significantly lower in this group compared to sedentary patients after the 6-week follow-up (p<0

SITE-94. Chemical and physical transport parameters for SITE-94

Energy Technology Data Exchange (ETDEWEB)

Andersson, Karin [Chalmers Univ. of Technology, Goeteborg (Sweden). Technical Environmental Planning

1996-02-01

Important parameters are the interactions of radionuclides with solid surfaces, parameters describing the geometrical conditions like porosity, data on water composition (ionic strength, pH, redox conditions, complex formers etc) and data on the solids that may be of importance to the water and radionuclide chemistry. In this report some of these data of relevance for the Aespoe site are discussed. Based on a literature survey, sorption data as well as values for some other parameters have been selected for rock, fracture fillings and bentonite relevant to the chemical conditions in and around a repository at Aespoe. A comparison to data used for earlier, site-specific as well as general, safety assessments of underground repositories has been performed. The data are recommendations for modelling of radionuclide release from a hypothetical high level waste repository at Aespoe. Since the data to a large extent are not based on experimental measurements, more accurate predictions may be expected if more experimental data are available. Before such studies are performed for a specific site, a variational analysis in order to evaluate the importance of the single parameters is recommended. After such a study, the key parameters may be investigated in detail and the modelling can be expected to be more accurate what concerns influence of single parameters. However, the uncertainty in conceptual areas like how to model accurately the long term hydrology of the site etc still remains. 32 refs.

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

Science.gov (United States)

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

2016-07-08

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

Kinetic parameters for source driven systems

International Nuclear Information System (INIS)

Dulla, S.; Ravetto, P.; Carta, M.; D'Angelo, A.

2006-01-01

The definition of the characteristic kinetic parameters of a subcritical source-driven system constitutes an interesting problem in reactor physics with important consequences for practical applications. Consistent and physically meaningful values of the parameters allow to obtain accurate results from kinetic simulation tools and to correctly interpret kinetic experiments. For subcritical systems a preliminary problem arises for the adoption of a suitable weighting function to be used in the projection procedure to derive a point model. The present work illustrates a consistent factorization-projection procedure which leads to the definition of the kinetic parameters in a straightforward manner. The reactivity term is introduced coherently with the generalized perturbation theory applied to the source multiplication factor ks, which is thus given a physical role in the kinetic model. The effective prompt lifetime is introduced on the assumption that a neutron generation can be initiated by both the fission process and the source emission. Results are presented for simplified configurations to fully comprehend the physical features and for a more complicated highly decoupled system treated in transport theory. (authors)

Predicted infiltration for sodic/saline soils from reclaimed coastal areas: sensitivity to model parameters.

Science.gov (United States)

Liu, Dongdong; She, Dongli; Yu, Shuang'en; Shao, Guangcheng; Chen, Dan

2014-01-01

This study was conducted to assess the influences of soil surface conditions and initial soil water content on water movement in unsaturated sodic soils of reclaimed coastal areas. Data was collected from column experiments in which two soils from a Chinese coastal area reclaimed in 2007 (Soil A, saline) and 1960 (Soil B, nonsaline) were used, with bulk densities of 1.4 or 1.5 g/cm(3). A 1D-infiltration model was created using a finite difference method and its sensitivity to hydraulic related parameters was tested. The model well simulated the measured data. The results revealed that soil compaction notably affected the water retention of both soils. Model simulations showed that increasing the ponded water depth had little effect on the infiltration process, since the increases in cumulative infiltration and wetting front advancement rate were small. However, the wetting front advancement rate increased and the cumulative infiltration decreased to a greater extent when θ₀ was increased. Soil physical quality was described better by the S parameter than by the saturated hydraulic conductivity since the latter was also affected by the physical chemical effects on clay swelling occurring in the presence of different levels of electrolytes in the soil solutions of the two soils.

Predicted Infiltration for Sodic/Saline Soils from Reclaimed Coastal Areas: Sensitivity to Model Parameters

Directory of Open Access Journals (Sweden)

Dongdong Liu

2014-01-01

Full Text Available This study was conducted to assess the influences of soil surface conditions and initial soil water content on water movement in unsaturated sodic soils of reclaimed coastal areas. Data was collected from column experiments in which two soils from a Chinese coastal area reclaimed in 2007 (Soil A, saline and 1960 (Soil B, nonsaline were used, with bulk densities of 1.4 or 1.5 g/cm3. A 1D-infiltration model was created using a finite difference method and its sensitivity to hydraulic related parameters was tested. The model well simulated the measured data. The results revealed that soil compaction notably affected the water retention of both soils. Model simulations showed that increasing the ponded water depth had little effect on the infiltration process, since the increases in cumulative infiltration and wetting front advancement rate were small. However, the wetting front advancement rate increased and the cumulative infiltration decreased to a greater extent when θ0 was increased. Soil physical quality was described better by the S parameter than by the saturated hydraulic conductivity since the latter was also affected by the physical chemical effects on clay swelling occurring in the presence of different levels of electrolytes in the soil solutions of the two soils.

The Goddard Snow Radiance Assimilation Project: An Integrated Snow Radiance and Snow Physics Modeling Framework for Snow/cold Land Surface Modeling

Science.gov (United States)

Kim, E.; Tedesco, M.; Reichle, R.; Choudhury, B.; Peters-Lidard C.; Foster, J.; Hall, D.; Riggs, G.

2006-01-01

Microwave-based retrievals of snow parameters from satellite observations have a long heritage and have so far been generated primarily by regression-based empirical "inversion" methods based on snapshots in time. Direct assimilation of microwave radiance into physical land surface models can be used to avoid errors associated with such retrieval/inversion methods, instead utilizing more straightforward forward models and temporal information. This approach has been used for years for atmospheric parameters by the operational weather forecasting community with great success. Recent developments in forward radiative transfer modeling, physical land surface modeling, and land data assimilation are converging to allow the assembly of an integrated framework for snow/cold lands modeling and radiance assimilation. The objective of the Goddard snow radiance assimilation project is to develop such a framework and explore its capabilities. The key elements of this framework include: a forward radiative transfer model (FRTM) for snow, a snowpack physical model, a land surface water/energy cycle model, and a data assimilation scheme. In fact, multiple models are available for each element enabling optimization to match the needs of a particular study. Together these form a modular and flexible framework for self-consistent, physically-based remote sensing and water/energy cycle studies. In this paper we will describe the elements and the integration plan. All modules will operate within the framework of the Land Information System (LIS), a land surface modeling framework with data assimilation capabilities running on a parallel-node computing cluster. Capabilities for assimilation of snow retrieval products are already under development for LIS. We will describe plans to add radiance-based assimilation capabilities. Plans for validation activities using field measurements will also be discussed.

Environmental Transport Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

M. A. Wasiolek

2003-06-27

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

Environmental Transport Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

Wasiolek, M. A.

2003-01-01

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

Parameter estimation in stochastic rainfall-runoff models

DEFF Research Database (Denmark)

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

2006-01-01

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

Influence of buildings geometrical and physical parameters on thermal cooling load

International Nuclear Information System (INIS)

Melo, C.

1980-09-01

A more accurate method to evaluate the thermal cooling load in buildings and to analyze the influence of geometrical and physical parameters on air conditioning calculations is presented. The sensitivity of the cooling load, considering the thermal capacity of the materials, was simulated in a computer for several different situations. (Author) [pt

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)

Method for extracting relevant electrical parameters from graphene field-effect transistors using a physical model

International Nuclear Information System (INIS)

Boscá, A.; Pedrós, J.; Martínez, J.; Calle, F.

2015-01-01

Due to its intrinsic high mobility, graphene has proved to be a suitable material for high-speed electronics, where graphene field-effect transistor (GFET) has shown excellent properties. In this work, we present a method for extracting relevant electrical parameters from GFET devices using a simple electrical characterization and a model fitting. With experimental data from the device output characteristics, the method allows to calculate parameters such as the mobility, the contact resistance, and the fixed charge. Differentiated electron and hole mobilities and direct connection with intrinsic material properties are some of the key aspects of this method. Moreover, the method output values can be correlated with several issues during key fabrication steps such as the graphene growth and transfer, the lithographic steps, or the metalization processes, providing a flexible tool for quality control in GFET fabrication, as well as a valuable feedback for improving the material-growth process

Method for extracting relevant electrical parameters from graphene field-effect transistors using a physical model

Energy Technology Data Exchange (ETDEWEB)

Boscá, A., E-mail: alberto.bosca@upm.es [Instituto de Sistemas Optoelectrónicos y Microtecnología, Universidad Politécnica de Madrid, Madrid 28040 (Spain); Dpto. de Ingeniería Electrónica, E.T.S.I. de Telecomunicación, Universidad Politécnica de Madrid, Madrid 28040 (Spain); Pedrós, J. [Instituto de Sistemas Optoelectrónicos y Microtecnología, Universidad Politécnica de Madrid, Madrid 28040 (Spain); Campus de Excelencia Internacional, Campus Moncloa UCM-UPM, Madrid 28040 (Spain); Martínez, J. [Instituto de Sistemas Optoelectrónicos y Microtecnología, Universidad Politécnica de Madrid, Madrid 28040 (Spain); Dpto. de Ciencia de Materiales, E.T.S.I de Caminos, Canales y Puertos, Universidad Politécnica de Madrid, Madrid 28040 (Spain); Calle, F. [Instituto de Sistemas Optoelectrónicos y Microtecnología, Universidad Politécnica de Madrid, Madrid 28040 (Spain); Dpto. de Ingeniería Electrónica, E.T.S.I. de Telecomunicación, Universidad Politécnica de Madrid, Madrid 28040 (Spain); Campus de Excelencia Internacional, Campus Moncloa UCM-UPM, Madrid 28040 (Spain)

2015-01-28

Due to its intrinsic high mobility, graphene has proved to be a suitable material for high-speed electronics, where graphene field-effect transistor (GFET) has shown excellent properties. In this work, we present a method for extracting relevant electrical parameters from GFET devices using a simple electrical characterization and a model fitting. With experimental data from the device output characteristics, the method allows to calculate parameters such as the mobility, the contact resistance, and the fixed charge. Differentiated electron and hole mobilities and direct connection with intrinsic material properties are some of the key aspects of this method. Moreover, the method output values can be correlated with several issues during key fabrication steps such as the graphene growth and transfer, the lithographic steps, or the metalization processes, providing a flexible tool for quality control in GFET fabrication, as well as a valuable feedback for improving the material-growth process.

ADAPTIVE MESH REFINEMENT SIMULATIONS OF GALAXY FORMATION: EXPLORING NUMERICAL AND PHYSICAL PARAMETERS

International Nuclear Information System (INIS)

Hummels, Cameron B.; Bryan, Greg L.

2012-01-01

We carry out adaptive mesh refinement cosmological simulations of Milky Way mass halos in order to investigate the formation of disk-like galaxies in a Λ-dominated cold dark matter model. We evolve a suite of five halos to z = 0 and find a gas disk formation in each; however, in agreement with previous smoothed particle hydrodynamics simulations (that did not include a subgrid feedback model), the rotation curves of all halos are centrally peaked due to a massive spheroidal component. Our standard model includes radiative cooling and star formation, but no feedback. We further investigate this angular momentum problem by systematically modifying various simulation parameters including: (1) spatial resolution, ranging from 1700 to 212 pc; (2) an additional pressure component to ensure that the Jeans length is always resolved; (3) low star formation efficiency, going down to 0.1%; (4) fixed physical resolution as opposed to comoving resolution; (5) a supernova feedback model that injects thermal energy to the local cell; and (6) a subgrid feedback model which suppresses cooling in the immediate vicinity of a star formation event. Of all of these, we find that only the last (cooling suppression) has any impact on the massive spheroidal component. In particular, a simulation with cooling suppression and feedback results in a rotation curve that, while still peaked, is considerably reduced from our standard runs.

Evaluation of SCS-CN method using a fully distributed physically based coupled surface-subsurface flow model

Science.gov (United States)

Shokri, Ali

2017-04-01

The hydrological cycle contains a wide range of linked surface and subsurface flow processes. In spite of natural connections between surface water and groundwater, historically, these processes have been studied separately. The current trend in hydrological distributed physically based model development is to combine distributed surface water models with distributed subsurface flow models. This combination results in a better estimation of the temporal and spatial variability of the interaction between surface and subsurface flow. On the other hand, simple lumped models such as the Soil Conservation Service Curve Number (SCS-CN) are still quite common because of their simplicity. In spite of the popularity of the SCS-CN method, there have always been concerns about the ambiguity of the SCS-CN method in explaining physical mechanism of rainfall-runoff processes. The aim of this study is to minimize these ambiguity by establishing a method to find an equivalence of the SCS-CN solution to the DrainFlow model, which is a fully distributed physically based coupled surface-subsurface flow model. In this paper, two hypothetical v-catchment tests are designed and the direct runoff from a storm event are calculated by both SCS-CN and DrainFlow models. To find a comparable solution to runoff prediction through the SCS-CN and DrainFlow, the variance between runoff predictions by the two models are minimized by changing Curve Number (CN) and initial abstraction (Ia) values. Results of this study have led to a set of lumped model parameters (CN and Ia) for each catchment that is comparable to a set of physically based parameters including hydraulic conductivity, Manning roughness coefficient, ground surface slope, and specific storage. Considering the lack of physical interpretation in CN and Ia is often argued as a weakness of SCS-CN method, the novel method in this paper gives a physical explanation to CN and Ia.

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...

V2676 Oph: Estimating Physical Parameters of a Moderately Fast Nova

Science.gov (United States)

Raj, A.; Pavana, M.; Kamath, U. S.; Anupama, G. C.; Walter, F. M.

2018-03-01

Using our previously reported observations, we derive some physical parameters of the moderately fast nova V2676 Oph 2012 #1. The best-fit Cloudy model of the nebular spectrum obtained on 2015 May 8 shows a hot white dwarf source with TBB≍1.0×105 K having a luminosity of 1.0×1038 erg/s. Our abundance analysis shows that the ejecta are significantly enhanced relative to solar, He/H=2.14, O/H=2.37, S/H=6.62 and Ar/H=3.25. The ejecta mass is estimated to be 1.42×10-5 M⊙. The nova showed a pronounced dust formation phase after 90 d from discovery. The J-H and H-K colors were very large as compared to other molecule- and dust-forming novae in recent years. The dust temperature and mass at two epochs have been estimated from spectral energy distribution fits to infrared photometry.

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

International Nuclear Information System (INIS)

Christensen, L.H.; Pind, N.

1982-01-01

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

Modeling of physical fitness of young karatyst on the pre basic training

Directory of Open Access Journals (Sweden)

V. A. Galimskyi

2014-09-01

Full Text Available Purpose : to develop a program of physical fitness for the correction of the pre basic training on the basis of model performance. Material: 57 young karate sportsmen of 9-11 years old took part in the research. Results : the level of general and special physical preparedness of young karate 9-11 years old was determined. Classes in the control group occurred in the existing program for yous sports school Muay Thai (Thailand boxing. For the experimental group has developed a program of selective development of general and special physical qualities of model-based training sessions. Special program contains 6 direction: 1. Development of static and dynamic balance; 2. Development of vestibular stability (precision movements after rotation; 3. Development rate movements; 4. The development of the capacity for rapid restructuring movements; 5. Development capabilities to differentiate power and spatial parameters of movement; 6. Development of the ability to perform jumping movements of rotation. Development of special physical qualities continued to work to improve engineering complex shock motions on the place and with movement. Conclusions : the use of selective development of special physical qualities based models of training sessions has a significant performance advantage over the control group.

A simulation of water pollution model parameter estimation

Science.gov (United States)

Kibler, J. F.

1976-01-01

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

Identification of ecosystem parameters by SDE-modelling

DEFF Research Database (Denmark)

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

An integrated approach for the knowledge discovery in computer simulation models with a multi-dimensional parameter space

Energy Technology Data Exchange (ETDEWEB)

Khawli, Toufik Al; Eppelt, Urs; Hermanns, Torsten [RWTH Aachen University, Chair for Nonlinear Dynamics, Steinbachstr. 15, 52047 Aachen (Germany); Gebhardt, Sascha [RWTH Aachen University, Virtual Reality Group, IT Center, Seffenter Weg 23, 52074 Aachen (Germany); Kuhlen, Torsten [Forschungszentrum Jülich GmbH, Institute for Advanced Simulation (IAS), Jülich Supercomputing Centre (JSC), Wilhelm-Johnen-Straße, 52425 Jülich (Germany); Schulz, Wolfgang [Fraunhofer, ILT Laser Technology, Steinbachstr. 15, 52047 Aachen (Germany)

2016-06-08

In production industries, parameter identification, sensitivity analysis and multi-dimensional visualization are vital steps in the planning process for achieving optimal designs and gaining valuable information. Sensitivity analysis and visualization can help in identifying the most-influential parameters and quantify their contribution to the model output, reduce the model complexity, and enhance the understanding of the model behavior. Typically, this requires a large number of simulations, which can be both very expensive and time consuming when the simulation models are numerically complex and the number of parameter inputs increases. There are three main constituent parts in this work. The first part is to substitute the numerical, physical model by an accurate surrogate model, the so-called metamodel. The second part includes a multi-dimensional visualization approach for the visual exploration of metamodels. In the third part, the metamodel is used to provide the two global sensitivity measures: i) the Elementary Effect for screening the parameters, and ii) the variance decomposition method for calculating the Sobol indices that quantify both the main and interaction effects. The application of the proposed approach is illustrated with an industrial application with the goal of optimizing a drilling process using a Gaussian laser beam.

Physical Modeling of the Polyfrequency Filter-Compensating Device Based on the Capacitor-Coil

Science.gov (United States)

Butyrin, P. A.; Gusev, G. G.; Mikheev, D. V.; Shakirzianov, F. N.

2017-12-01

The paper presents the results of physical modeling and experimental study of the frequency characteristics of the polyfrequency filter-compensating device (PFCD) based on a capacitor-coil. The amplitude- frequency and phase-frequency characteristics of the physical PFCD model were constructed and its equivalent parameters were identified. The feasibility of a PFCD in the form of a single technical device with high technical and economic characteristics was experimentally proven. In the paper, recommendations for practical applications of the capacitor-coil-based PFCD are made and the advantages of the device over known standard passive filter-compensating devices are evaluated.

Spatio-temporal modeling of nonlinear distributed parameter systems

CERN Document Server

Li, Han-Xiong

2011-01-01

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

Models for estimating photosynthesis parameters from in situ production profiles

Science.gov (United States)

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

2017-12-01

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

Global and photospheric physical parameters of active dwarf stars

International Nuclear Information System (INIS)

Pettersen, B.R.

1983-01-01

Physical parameters (temperature, luminosity, radius, mass and chemical abundance) of the photospheres of red dwarf flare stars and spotted stars are determined for quiescent conditions. The interrelations between these quantities are compared to the results of theoretical investigation for low mass stars. The evolutionary state of flare stars is discussed. Observational results from spectroscopic and photometric methods to determine the rotation of active dwarfs are reviewed. The possibilities of global oscillations in dwarf stars are considered and preliminary results of a photometric search for oscillation in red dwarf luminosities are presented. (orig.)

The strong interactions beyond the standard model of particle physics

Energy Technology Data Exchange (ETDEWEB)

Bergner, Georg [Muenster Univ. (Germany). Inst. for Theoretical Physics

2016-11-01

SuperMUC is one of the most convenient high performance machines for our project since it offers a high performance and flexibility regarding different applications. This is of particular importance for investigations of new theories, where on the one hand the parameters and systematic uncertainties have to be estimated in smaller simulations and on the other hand a large computational performance is needed for the estimations of the scale at zero temperature. Our project is just the first investigation of the new physics beyond the standard model of particle physics and we hope to proceed with our studies towards more involved Technicolour candidates, supersymmetric QCD, and extended supersymmetry.

Identification of parameters of discrete-continuous models

International Nuclear Information System (INIS)

Cekus, Dawid; Warys, Pawel

2015-01-01

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

Identification of parameters of discrete-continuous models

Energy Technology Data Exchange (ETDEWEB)

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

2015-03-10

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

Identifying the connective strength between model parameters and performance criteria

Directory of Open Access Journals (Sweden)

B. Guse

2017-11-01

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

Agricultural and Environmental Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

Kaylie Rasmuson; Kurt Rautenstrauch

2003-01-01

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

Comparison of parameters of bone profile and homocysteine in physically active and non-active postmenopausal females.

Science.gov (United States)

Tariq, Sundus; Lone, Khalid Parvez; Tariq, Saba

2016-01-01

Optimal physical activity is important in attaining a peak bone mass. Physically active women have better bone mineral density and reduce fracture risk as compared to females living a sedentary life. The objective of this study was to compare parameters of bone profile and serum homocysteine levels in physically active and non-active postmenopausal females. In this cross sectional study postmenopausal females between 50-70 years of age were recruited and divided into two groups: Physically inactive (n=133) performing light physical activity and Physically active (n=34) performing moderate physical activity. Physical activity (in metabolic equivalents), bone mineral density and serum homocysteine levels were assessed. Spearman's rho correlation was applied to observe correlations. Two independent sample t test and Mann Whitney U test were applied to compare groups. P-value ≤ 0.05 was taken statistically significant. Parameters of bone profile were significantly higher and serum homocysteine levels were significantly lower in postmenopausal females performing moderate physical activity as compared to females performing light physical activity. Homocysteine was not significantly related to T-score and Z-score in both groups. Improving physical activity could be beneficial for improving the quality of bone, decreasing fracture risk and decreasing serum homocysteine levels.

Brownian motion model with stochastic parameters for asset prices

Science.gov (United States)

Ching, Soo Huei; Hin, Pooi Ah

2013-09-01

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

A study on the intrusion model by physical modeling

Energy Technology Data Exchange (ETDEWEB)

Kim, Jung Yul; Kim, Yoo Sung; Hyun, Hye Ja [Korea Inst. of Geology Mining and Materials, Taejon (Korea, Republic of)

1995-12-01

In physical modeling, the actual phenomena of seismic wave propagation are directly measured like field survey and furthermore the structure and physical properties of subsurface can be known. So the measured datasets from physical modeling can be very desirable as input data to test the efficiency of various inversion algorithms. An underground structure formed by intrusion, which can be often seen in seismic section for oil exploration, is investigated by physical modeling. The model is characterized by various types of layer boundaries with steep dip angle. Therefore, this physical modeling data are very available not only to interpret seismic sections for oil exploration as a case history, but also to develop data processing techniques and estimate the capability of software such as migration, full waveform inversion. (author). 5 refs., 18 figs.

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.

Physical Protection System Design Analysis against Insider Threat based on Game Theoretic Modeling

Energy Technology Data Exchange (ETDEWEB)

Kim, Kyo-Nam; Suh, Young-A; Yim, Man-Sung [KAIST, Daejeon (Korea, Republic of); Schneider, Erich [The University of Texas, Austin (United States)

2015-05-15

This study explores the use of game-theoretic modeling of physical protection analysis by incorporating the implications of an insider threat. The defender-adversary interaction along with the inclusion of an insider is demonstrated using a simplified test case problem at an experimental fast reactor system. Non-detection probability and travel time are used as a baseline of physical protection parameters in this model. As one of the key features of the model is its ability to choose among security upgrades given the constraints of a budget, the study also performed cost benefit analysis for security upgrades options. In this study, we analyzed the expected adversarial path and security upgrades with a limited budget with insider threat modeled as increasing the non-detection probability. Our test case problem categorized three types of adversary paths assisted by the insider and derived the largest insider threat in terms of the budget for security upgrades. More work needs to be done to incorporate complex dimensions of insider threats, which include but are not limited to: a more realistic mapping of insider threat, accounting for information asymmetry between the adversary, insider, and defenders, and assignment of more pragmatic parameter values.

Physical Protection System Design Analysis against Insider Threat based on Game Theoretic Modeling

International Nuclear Information System (INIS)

Kim, Kyo-Nam; Suh, Young-A; Yim, Man-Sung; Schneider, Erich

2015-01-01

This study explores the use of game-theoretic modeling of physical protection analysis by incorporating the implications of an insider threat. The defender-adversary interaction along with the inclusion of an insider is demonstrated using a simplified test case problem at an experimental fast reactor system. Non-detection probability and travel time are used as a baseline of physical protection parameters in this model. As one of the key features of the model is its ability to choose among security upgrades given the constraints of a budget, the study also performed cost benefit analysis for security upgrades options. In this study, we analyzed the expected adversarial path and security upgrades with a limited budget with insider threat modeled as increasing the non-detection probability. Our test case problem categorized three types of adversary paths assisted by the insider and derived the largest insider threat in terms of the budget for security upgrades. More work needs to be done to incorporate complex dimensions of insider threats, which include but are not limited to: a more realistic mapping of insider threat, accounting for information asymmetry between the adversary, insider, and defenders, and assignment of more pragmatic parameter values

A study on physics parameters and flux behaviour for a fast critical facility using ''Baker'' model

International Nuclear Information System (INIS)

Abu-Leilah, M.M.; Hussein, A.Z.; Gaafar, M.A.; Hamouda, I.F.

1983-01-01

Comparative study was performed to emphasize the effects of using different nuclear data systems and methods on the various parameters of the fast reactor. Multigroup libraries as 11 (ANL-5800) and 26 (BNAB-64) energy group systems of nuclear data constants were used in the present work. The calculations were carried out for both infinite dilution (self-shielding factor F= 1) and self-shielded cross sections. Various computer codes were elaborated and derived to meet the conditional requirements for such calculations. The important output of these calculations are the neutron spectra, neutron balance, fission and capture rate distributions, critical mass, breeding ratio in each region and total breeding ratio of the reactor. Five different cases of study were considered employing two systems of constants, infinite dilution and self-shielded cross-sections and treating stainless steel of the reactor as to be substituted by iron. Moreover, calculations have been concerned for averaged one group nuclear data constants which were condensed from the 11 and 26 group systems. Comparisons of the multigroup results with those of the group were made. The condensation process for averaging to one group was done to estimate the effect of such physical simplification on the calculated parameters. The present work results have been compared with many published works. Fair agreements are obtained, which varified the consistance and completeness of the methods implemented and used

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

Science.gov (United States)

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

2012-05-21

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

Model of cosmology and particle physics at an intermediate scale

International Nuclear Information System (INIS)

Bastero-Gil, M.; Di Clemente, V.; King, S. F.

2005-01-01

We propose a model of cosmology and particle physics in which all relevant scales arise in a natural way from an intermediate string scale. We are led to assign the string scale to the intermediate scale M * ∼10 13 GeV by four independent pieces of physics: electroweak symmetry breaking; the μ parameter; the axion scale; and the neutrino mass scale. The model involves hybrid inflation with the waterfall field N being responsible for generating the μ term, the right-handed neutrino mass scale, and the Peccei-Quinn symmetry breaking scale. The large scale structure of the Universe is generated by the lightest right-handed sneutrino playing the role of a coupled curvaton. We show that the correct curvature perturbations may be successfully generated providing the lightest right-handed neutrino is weakly coupled in the seesaw mechanism, consistent with sequential dominance

Research on physical and chemical parameters of coolant in Light-Water Reactors

Energy Technology Data Exchange (ETDEWEB)

Reis, Isabela C.; Mesquita, Amir Z., E-mail: icr@cdtn.br, E-mail: amir@cdtn.br [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEM-MG), Belo Horizonte, MG (Brazil)

2015-07-01

The coolant radiochemical monitoring of light-water reactors, both power reactor as research reactors is one most important tasks of the system safe operation. The last years have increased the interest in the coolant chemical studying to optimize the process, to minimize the corrosion, to ensure the primary system materials integrity, and to reduce the workers exposure radiation. This paper has the objective to present the development project in Nuclear Technology Development Center (CDTN), which aims to simulate the primary water physical-chemical parameters of light-water-reactors (LWR). Among these parameters may be cited: the temperature, the pressure, the pH, the electric conductivity, and the boron concentration. It is also being studied the adverse effects that these parameters can result in the reactor integrity. The project also aims the mounting of a system to control and monitoring of temperature, electric conductivity, and pH of water in the Installation of Test in Accident Conditions (ITCA), located in the Thermal-Hydraulic Laboratory at CDTN. This facility was widely used in the years 80/90 for commissioning of several components that were installed in Angra 2 containment. In the test, the coolant must reproduce the physical and chemical conditions of the primary. It is therefore fundamental knowledge of the main control parameters of the primary cooling water from PWR reactors. Therefore, this work is contributing, with the knowledge and the reproduction with larger faithfulness of the reactors coolant in the experimental circuits. (author)

Lumped-parameter Model of a Bucket Foundation

DEFF Research Database (Denmark)

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

2009-01-01

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

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)

A summary report on the search for current technologies and developers to develop depth profiling/physical parameter end effectors

International Nuclear Information System (INIS)

Nguyen, Q.H.

1994-01-01

This report documents the search strategies and results for available technologies and developers to develop tank waste depth profiling/physical parameter sensors. Sources searched include worldwide research reports, technical papers, journals, private industries, and work at Westinghouse Hanford Company (WHC) at Richland site. Tank waste physical parameters of interest are: abrasiveness, compressive strength, corrosiveness, density, pH, particle size/shape, porosity, radiation, settling velocity, shear strength, shear wave velocity, tensile strength, temperature, viscosity, and viscoelasticity. A list of related articles or sources for each physical parameters is provided

A summary report on the search for current technologies and developers to develop depth profiling/physical parameter end effectors

Energy Technology Data Exchange (ETDEWEB)

Nguyen, Q.H.

1994-09-12

This report documents the search strategies and results for available technologies and developers to develop tank waste depth profiling/physical parameter sensors. Sources searched include worldwide research reports, technical papers, journals, private industries, and work at Westinghouse Hanford Company (WHC) at Richland site. Tank waste physical parameters of interest are: abrasiveness, compressive strength, corrosiveness, density, pH, particle size/shape, porosity, radiation, settling velocity, shear strength, shear wave velocity, tensile strength, temperature, viscosity, and viscoelasticity. A list of related articles or sources for each physical parameters is provided.

Sound Synthesis of Objects Swinging through Air Using Physical Models

Directory of Open Access Journals (Sweden)

Rod Selfridge

2017-11-01

Full Text Available A real-time physically-derived sound synthesis model is presented that replicates the sounds generated as an object swings through the air. Equations obtained from fluid dynamics are used to determine the sounds generated while exposing practical parameters for a user or game engine to vary. Listening tests reveal that for the majority of objects modelled, participants rated the sounds from our model as plausible as actual recordings. The sword sound effect performed worse than others, and it is speculated that one cause may be linked to the difference between expectations of a sound and the actual sound for a given object.

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.

Pre-Service Physics Teachers' Argumentation in a Model Rocketry Physics Experience

Science.gov (United States)

Gürel, Cem; Süzük, Erol

2017-01-01

This study investigates the quality of argumentation developed by a group of pre-service physics teachers' (PSPT) as an indicator of subject matter knowledge on model rocketry physics. The structure of arguments and scientific credibility model was used as a design framework in the study. The inquiry of model rocketry physics was employed in…

Modelling of nonhomogeneous atmosphere in NPP containment using lumped-parameter model based on CFD calculations

International Nuclear Information System (INIS)

Kljenak, I.; Mavko, B.; Babic, M.

2005-01-01

steam, air and helium were injected during different phases of the experiment. The thermal-hydraulic behaviour was determined by the dominant physical phenomena: gas injection, steam condensation, heat transfer and buoyant flow. During certain phases of the experiment, intermediate steady states were reached when the steam condensation rate became equal to the steam injection rate, with boundary conditions remaining constant. In the proposed work, steady states were simulated independently by applying the approach described above. The code CFX4.4 was used as a CFD code, whereas the code CONTAIN was used as a lumped-parameter code. The simulation with the CFX code was performed with a two-dimensional axisymmetric model of the TOSQAN vessel. The proposed work may be considered as a first step towards development of a suitable methodology for modelling nonhomogeneous atmosphere in NPP containments with lumped-parameter codes. (authors)

The mobilisation model and parameter sensitivity

International Nuclear Information System (INIS)

Blok, B.M.

1993-12-01

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

Rail vehicle dynamic response to a nonlinear physical 'in-service' model of its secondary suspension hydraulic dampers

Science.gov (United States)

Wang, W. L.; Zhou, Z. R.; Yu, D. S.; Qin, Q. H.; Iwnicki, S.

2017-10-01

A full nonlinear physical 'in-service' model was built for a rail vehicle secondary suspension hydraulic damper with shim-pack-type valves. In the modelling process, a shim pack deflection theory with an equivalent-pressure correction factor was proposed, and a Finite Element Analysis (FEA) approach was applied. Bench test results validated the damper model over its full velocity range and thus also proved that the proposed shim pack deflection theory and the FEA-based parameter identification approach are effective. The validated full damper model was subsequently incorporated into a detailed vehicle dynamics simulation to study how its key in-service parameter variations influence the secondary-suspension-related vehicle system dynamics. The obtained nonlinear physical in-service damper model and the vehicle dynamic response characteristics in this study could be used in the product design optimization and nonlinear optimal specifications of high-speed rail hydraulic dampers.

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

Science.gov (United States)

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

2014-09-01

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

The fitting parameters extraction of conversion model of the low dose rate effect in bipolar devices

International Nuclear Information System (INIS)

Bakerenkov, Alexander

2011-01-01

The Enhanced Low Dose Rate Sensitivity (ELDRS) in bipolar devices consists of in base current degradation of NPN and PNP transistors increase as the dose rate is decreased. As a result of almost 20-year studying, the some physical models of effect are developed, being described in detail. Accelerated test methods, based on these models use in standards. The conversion model of the effect, that allows to describe the inverse S-shaped excess base current dependence versus dose rate, was proposed. This paper presents the problem of conversion model fitting parameters extraction.

Estimating model parameters for an impact-produced shock-wave simulation: Optimal use of partial data with the extended Kalman filter

International Nuclear Information System (INIS)

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

2006-01-01

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

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

Green roof rainfall-runoff modelling: is the comparison between conceptual and physically based approaches relevant?

Science.gov (United States)

Versini, Pierre-Antoine; Tchiguirinskaia, Ioulia; Schertzer, Daniel

2017-04-01

Green roofs are commonly considered as efficient tools to mitigate urban runoff as they can store precipitation, and consequently provide retention and detention performances. Designed as a compromise between water holding capacity, weight and hydraulic conductivity, their substrate is usually an artificial media differentiating significantly from a traditional soil. In order to assess green roofs hydrological performances, many models have been developed. Classified into two categories (conceptual and physically based), they are usually applied to reproduce the discharge of a particular monitored green roof considered as homogeneous. Although the resulted simulations could be satisfactory, the question of robustness and consistency of the calibrated parameters is often not addressed. Here, a modeling framework has been developed to assess the efficiency and the robustness of both modelling approaches (conceptual and physically based) in reproducing green roof hydrological behaviour. SWMM and VS2DT models have been used for this purpose. This work also benefits from an experimental setup where several green roofs differentiated by their substrate thickness and vegetation cover are monitored. Based on the data collected for several rainfall events, it has been studied how the calibrated parameters are effectively linked to their physical properties and how they can vary from one green roof configuration to another. Although both models reproduce correctly the observed discharges in most of the cases, their calibrated parameters exhibit a high inconsistency. For a same green roof configuration, these parameters can vary significantly from one rainfall event to another, even if they are supposed to be linked to the green roof characteristics (roughness, residual moisture content for instance). They can also be different from one green roof configuration to another although the implemented substrate is the same. Finally, it appears very difficult to find any

Flare parameters inferred from a 3D loop model data base

Science.gov (United States)

Cuambe, Valente A.; Costa, J. E. R.; Simões, P. J. A.

2018-06-01

We developed a data base 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, we built a large data base 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 data base was constructed based on general properties of known solar flares and convolved with instrumental resolution to replicate the observations from the Nobeyama radio polarimeter spectra and Nobeyama radioheliograph (NoRH) brightness maps. Observed spectra and brightness distribution maps are easily compared with the modelled spectra and images in the data base, indicating a possible range of solutions. The parameter search efficiency in this finite data base is discussed. 8 out of 10 parameters analysed for 1000 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.

Investigation on Insar Time Series Deformation Model Considering Rheological Parameters for Soft Clay Subgrade Monitoring

Science.gov (United States)

Xing, X.; Yuan, Z.; Chen, L. F.; Yu, X. Y.; Xiao, L.

2018-04-01

The stability control is one of the major technical difficulties in the field of highway subgrade construction engineering. Building deformation model is a crucial step for InSAR time series deformation monitoring. Most of the InSAR deformation models for deformation monitoring are pure empirical mathematical models, without considering the physical mechanism of the monitored object. In this study, we take rheology into consideration, inducing rheological parameters into traditional InSAR deformation models. To assess the feasibility and accuracy for our new model, both simulation and real deformation data over Lungui highway (a typical highway built on soft clay subgrade in Guangdong province, China) are investigated with TerraSAR-X satellite imagery. In order to solve the unknows of the non-linear rheological model, three algorithms: Gauss-Newton (GN), Levenberg-Marquarat (LM), and Genetic Algorithm (GA), are utilized and compared to estimate the unknown parameters. Considering both the calculation efficiency and accuracy, GA is chosen as the final choice for the new model in our case study. Preliminary real data experiment is conducted with use of 17 TerraSAR-X Stripmap images (with a 3-m resolution). With the new deformation model and GA aforementioned, the unknown rheological parameters over all the high coherence points are obtained and the LOS deformation (the low-pass component) sequences are generated.

Models and parameters for environmental radiological assessments

International Nuclear Information System (INIS)

Miller, C.W.

1983-01-01

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

Comparison of Parameter Identification Techniques

Directory of Open Access Journals (Sweden)

Eder Rafael

2016-01-01

Full Text Available Model-based control of mechatronic systems requires excellent knowledge about the physical behavior of each component. For several types of components of a system, e.g. mechanical or electrical ones, the dynamic behavior can be described by means of a mathematic model consisting of a set of differential equations, difference equations and/or algebraic constraint equations. The knowledge of a realistic mathematic model and its parameter values is essential to represent the behaviour of a mechatronic system. Frequently it is hard or impossible to obtain all required values of the model parameters from the producer, so an appropriate parameter estimation technique is required to compute missing parameters. A manifold of parameter identification techniques can be found in the literature, but their suitability depends on the mathematic model. Previous work dealt with the automatic assembly of mathematical models of serial and parallel robots with drives and controllers within the dynamic multibody simulation code HOTINT as fully-fledged mechatronic simulation. Several parameters of such robot models were identified successfully by our embedded algorithm. The present work proposes an improved version of the identification algorithm with higher performance. The quality of the identified parameter values and the computation effort are compared with another standard technique.

The effects of physical training on cardiovascular parameters, lipid disorders and endothelial function

Directory of Open Access Journals (Sweden)

Ranković Goran

2012-01-01

Full Text Available Bacground/Aim. Regular physical activity is widely accepted as factor that reduces all-cause mortality and improves a number of health outcomes. The aim of this study was to investigate the effects of aerobic exercise training on cardiovascular parameters, lipid profile and endothelial function in patients with stable coronary artery disease (CAD. Methods. The study included seventy patients with stable CAD. All the patients were divided into two groups: the group I - 33 patients with CAD and with regular aerobic physical training during cardiovascular rehabilitation program phase II for 3 weeks in our rehabilitation center and 3 weeks after that in their home setting, and the group II (control - 37 patients with CAD and sedentary lifestyle. Exercise training consisted of continual aerobic exercise for 45 minutes on a treadmill, room bicycle or walking, three times a week. We determined lipid and cardiovascular parameters and nitric oxide (NO concentration at the beginning and after a six-week of training. Results. There were no significant differences in body weight, waist circumference and waist/hip ratio at the start and at the end of physical training program. Physical training significantly reduced body mass index after six weeks compared to the initial and control values. Physical training significantly reduced systolic and diastolic blood pressure and heart rate after a six-week training period (p < 0.05. Heart rate was significantly lower after a training period as compared to the control (p < 0.05. A significant reduction of triglyceride and increased high density lipoprotein cholesterol (HDL-C concentration after cardiovascular rehabilitation were registered (p < 0.05. The concentration of triglycerides was significantly lower while NO and HDL-C were higher after six weeks in the exercise training group (p < 0.05. Conclusion. Dynamic training can improve blood pressure in patients with moderate to severe hypertension and reduce the

A Software Toolkit to Study Systematic Uncertainties of the Physics Models of the Geant4 Simulation Package

CERN Document Server

Genser, Krzysztof; Perdue, Gabriel; Wenzel, Hans; Yarba, Julia; Kelsey, Michael; Wright, Dennis H

2016-01-01

The Geant4 toolkit is used to model interactions between particles and matter. Geant4 employs a set of validated physics models that span a wide range of interaction energies. These models are tuned to cover a large variety of possible applications. This raises the critical question of what uncertainties are associated with the Geant4 physics model, or group of models, involved in a simulation project. To address the challenge, we have designed and implemented a comprehen- sive, modular, user-friendly software toolkit that allows the variation of one or more parameters of one or more Geant4 physics models involved in simulation studies. It also enables analysis of multiple variants of the resulting physics observables of interest in order to estimate the uncertain- ties associated with the simulation model choices. Key functionalities of the toolkit are presented in this paper and are illustrated with selected results.

Parameter Estimation of Nonlinear Models in Forestry.

OpenAIRE

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

1999-01-01

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

Capturing the complex behavior of hydraulic fracture stimulation through multi-physics modeling, field-based constraints, and model reduction

Science.gov (United States)

Johnson, S.; Chiaramonte, L.; Cruz, L.; Izadi, G.

2016-12-01

Advances in the accuracy and fidelity of numerical methods have significantly improved our understanding of coupled processes in unconventional reservoirs. However, such multi-physics models are typically characterized by many parameters and require exceptional computational resources to evaluate systems of practical importance, making these models difficult to use for field analyses or uncertainty quantification. One approach to remove these limitations is through targeted complexity reduction and field data constrained parameterization. For the latter, a variety of field data streams may be available to engineers and asset teams, including micro-seismicity from proximate sites, well logs, and 3D surveys, which can constrain possible states of the reservoir as well as the distributions of parameters. We describe one such workflow, using the Argos multi-physics code and requisite geomechanical analysis to parameterize the underlying models. We illustrate with a field study involving a constraint analysis of various field data and details of the numerical optimizations and model reduction to demonstrate how complex models can be applied to operation design in hydraulic fracturing operations, including selection of controllable completion and fluid injection design properties. The implication of this work is that numerical methods are mature and computationally tractable enough to enable complex engineering analysis and deterministic field estimates and to advance research into stochastic analyses for uncertainty quantification and value of information applications.

Wind Farm Decentralized Dynamic Modeling With Parameters

DEFF Research Database (Denmark)

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

2010-01-01

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

Physical model of the contact resistivity of metal-graphene junctions

Energy Technology Data Exchange (ETDEWEB)

Chaves, Ferney A., E-mail: ferneyalveiro.chaves@uab.cat; Jiménez, David [Departament d' Enginyeria Electrònica, Escola d' Enginyeria, Universitat Autònoma de Barcelona, Campus UAB, 08193 Bellaterra, Barcelona (Spain); Cummings, Aron W. [ICN2–Institut Català de Nanociència i Nanotecnologia, Campus UAB, 08193 Bellaterra, Barcelona (Spain); Roche, Stephan [ICN2–Institut Català de Nanociència i Nanotecnologia, Campus UAB, 08193 Bellaterra, Barcelona (Spain); ICREA, Institució Catalana de Recerca i Estudis Avançats, 08070 Barcelona (Spain)

2014-04-28

While graphene-based technology shows great promise for a variety of electronic applications, including radio-frequency devices, the resistance of the metal-graphene contact is a technological bottleneck for the realization of viable graphene electronics. One of the most important factors in determining the resistance of a metal-graphene junction is the contact resistivity. Despite the large number of experimental works that exist in the literature measuring the contact resistivity, a simple model of it is still lacking. In this paper, we present a comprehensive physical model for the contact resistivity of these junctions, based on the Bardeen Transfer Hamiltonian method. This model unveils the role played by different electrical and physical parameters in determining the specific contact resistivity, such as the chemical potential of interaction, the work metal-graphene function difference, and the insulator thickness between the metal and graphene. In addition, our model reveals that the contact resistivity is strongly dependent on the bias voltage across the metal-graphene junction. This model is applicable to a wide variety of graphene-based electronic devices and thus is useful for understanding how to optimize the contact resistance in these systems.

Physical model of the contact resistivity of metal-graphene junctions

International Nuclear Information System (INIS)

Chaves, Ferney A.; Jiménez, David; Cummings, Aron W.; Roche, Stephan

2014-01-01

While graphene-based technology shows great promise for a variety of electronic applications, including radio-frequency devices, the resistance of the metal-graphene contact is a technological bottleneck for the realization of viable graphene electronics. One of the most important factors in determining the resistance of a metal-graphene junction is the contact resistivity. Despite the large number of experimental works that exist in the literature measuring the contact resistivity, a simple model of it is still lacking. In this paper, we present a comprehensive physical model for the contact resistivity of these junctions, based on the Bardeen Transfer Hamiltonian method. This model unveils the role played by different electrical and physical parameters in determining the specific contact resistivity, such as the chemical potential of interaction, the work metal-graphene function difference, and the insulator thickness between the metal and graphene. In addition, our model reveals that the contact resistivity is strongly dependent on the bias voltage across the metal-graphene junction. This model is applicable to a wide variety of graphene-based electronic devices and thus is useful for understanding how to optimize the contact resistance in these systems

Optimizing incomplete sample designs for item response model parameters

NARCIS (Netherlands)

van der Linden, Willem J.

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

Development of the physical model

International Nuclear Information System (INIS)

Liu Zunqi; Morsy, Samir

2001-01-01

Full text: The Physical Model was developed during Program 93+2 as a technical tool to aid enhanced information analysis and now is an integrated part of the Department's on-going State evaluation process. This paper will describe the concept of the Physical Model, including its objectives, overall structure and the development of indicators with designated strengths, followed by a brief description of using the Physical Model in implementing the enhanced information analysis. The work plan for expansion and update of the Physical Model is also presented at the end of the paper. The development of the Physical Model is an attempt to identify, describe and characterize every known process for carrying out each step necessary for the acquisition of weapons-usable material, i.e., all plausible acquisition paths for highly enriched uranium (HEU) and separated plutonium (Pu). The overall structure of the Physical Model has a multilevel arrangement. It includes at the top level all the main steps (technologies) that may be involved in the nuclear fuel cycle from the source material production up to the acquisition of weapons-usable material, and then beyond the civilian fuel cycle to the development of nuclear explosive devices (weaponization). Each step is logically interconnected with the preceding and/or succeeding steps by nuclear material flows. It contains at its lower levels every known process that is associated with the fuel cycle activities presented at the top level. For example, uranium enrichment is broken down into three branches at the second level, i.e., enrichment of UF 6 , UCl 4 and U-metal respectively; and then further broken down at the third level into nine processes: gaseous diffusion, gas centrifuge, aerodynamic, electromagnetic, molecular laser (MLIS), atomic vapor laser (AVLIS), chemical exchange, ion exchange and plasma. Narratives are presented at each level, beginning with a general process description then proceeding with detailed

Improved ERO modelling for spectroscopy of physically and chemically assisted eroded beryllium from the JET-ILW

Directory of Open Access Journals (Sweden)

D. Borodin

2016-12-01

Full Text Available Physical and chemical assisted physical sputtering were characterised by the BeI and BeII line and BeD band emission in the observation chord measuring the sightline integrated emission in front of the inner beryllium limiter at the torus midplane. The 3D local transport and plasma-surface interaction Monte-Carlo modelling (ERO code [18] is a key for the interpretation of the observations in the vicinity of the shaped solid Be limiter. The plasma parameter variation (density scan in limiter regime has provided a useful material for the simulation benchmark. The improved background plasma parameters input, the new analytical expression for particle tracking in the sheath region and implementation of the BeD release into ERO has helped to clarify some deviations between modelling and experiments encountered in the previous studies [4,5]. Reproducing the observations provides additional confidence in our ‘ERO-min’ fit for the physical sputtering yields for the plasma-wetted areas based on simulated data.

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

Methodology and results of investigations of physical parameters of high-temperature reactors

International Nuclear Information System (INIS)

Cherepnin, Yu.S.; Chertkov, Yu.B.

1995-01-01

A physical investigations of reactors of stand complexes Baikal-1 and IGR have been carrying out more 30 years. Measuring methods of the physical investigations were divided into 2 groups: 1) methods for measuring of reactivity effects; 2) methods for measuring relative and absolute values of neutron flux and power release. The physical investigations on the reactors IVG-1 and IGR were carryied out under following conditions: during physical starts-up of regular variants of reactor cores; during energy starts-up of the reactors; before beginning of new loop chanel tests of the reactors; during research hot starts-up of the reactors the physical parameters were controled. The most full and authentic information about studied reactor have been providing by physical investigations. In 1984 physical investigations were carryied out on the IGR reactor and then the hot start-up of the mostest power and mostest large on fuel loading loop chanel was carryied out. This chanel contained 6 fuel assemblies with the summary fuel loading 3,06 kilogrammes of uranium and it was calculated for power equal to 20 MW. In 1988 the physical investigations for selection of project process chanels destined for new water cooled reactor core were carryied out. In 1993 the neutron-physical calculation on possibility of tests for the rector Nerva fuel element was carryied out. 9 refs., 4 figs

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

Predictive sensor based x-ray calibration using a physical model

International Nuclear Information System (INIS)

Fuente, Matias de la; Lutz, Peter; Wirtz, Dieter C.; Radermacher, Klaus

2007-01-01

Many computer assisted surgery systems are based on intraoperative x-ray images. To achieve reliable and accurate results these images have to be calibrated concerning geometric distortions, which can be distinguished between constant distortions and distortions caused by magnetic fields. Instead of using an intraoperative calibration phantom that has to be visible within each image resulting in overlaying markers, the presented approach directly takes advantage of the physical background of the distortions. Based on a computed physical model of an image intensifier and a magnetic field sensor, an online compensation of distortions can be achieved without the need of an intraoperative calibration phantom. The model has to be adapted once to each specific image intensifier through calibration, which is based on an optimization algorithm systematically altering the physical model parameters, until a minimal error is reached. Once calibrated, the model is able to predict the distortions caused by the measured magnetic field vector and build an appropriate dewarping function. The time needed for model calibration is not yet optimized and takes up to 4 h on a 3 GHz CPU. In contrast, the time needed for distortion correction is less than 1 s and therefore absolutely acceptable for intraoperative use. First evaluations showed that by using the model based dewarping algorithm the distortions of an XRII with a 21 cm FOV could be significantly reduced. The model was able to predict and compensate distortions by approximately 80% to a remaining error of 0.45 mm (max) (0.19 mm rms)

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

Science.gov (United States)

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

2017-12-01

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

Robust Parameter and Signal Estimation in Induction Motors

DEFF Research Database (Denmark)

Børsting, H.

This thesis deals with theories and methods for robust parameter and signal estimation in induction motors. The project originates in industrial interests concerning sensor-less control of electrical drives. During the work, some general problems concerning estimation of signals and parameters...... in nonlinear systems, have been exposed. The main objectives of this project are: - analysis and application of theories and methods for robust estimation of parameters in a model structure, obtained from knowledge of the physics of the induction motor. - analysis and application of theories and methods...... for robust estimation of the rotor speed and driving torque of the induction motor based only on measurements of stator voltages and currents. Only contimuous-time models have been used, which means that physical related signals and parameters are estimated directly and not indirectly by some discrete...

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

African Journals Online (AJOL)

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

Literature Review of Dredging Physical Models

Science.gov (United States)

This U.S. Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory, special report presents a review of dredging physical ...model studies with the goal of understanding the most current state of dredging physical modeling, understanding conditions of similitude used in past...studies, and determining whether the flow field around a dredging operation has been quantified. Historical physical modeling efforts have focused on

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

Science.gov (United States)

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

2014-05-20

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

Modelling of intermittent microwave convective drying: parameter sensitivity

Directory of Open Access Journals (Sweden)

Zhang Zhijun

2017-06-01

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

Instream Physical Habitat Modelling Types

DEFF Research Database (Denmark)

Conallin, John; Boegh, Eva; Krogsgaard, Jørgen

2010-01-01

The introduction of the EU Water Framework Directive (WFD) is providing member state water resource managers with significant challenges in relation to meeting the deadline for 'Good Ecological Status' by 2015. Overall, instream physical habitat modelling approaches have advantages and disadvanta......The introduction of the EU Water Framework Directive (WFD) is providing member state water resource managers with significant challenges in relation to meeting the deadline for 'Good Ecological Status' by 2015. Overall, instream physical habitat modelling approaches have advantages...... suit their situations. This paper analyses the potential of different methods available for water managers to assess hydrological and geomorphological impacts on the habitats of stream biota, as requested by the WFD. The review considers both conventional and new advanced research-based instream...... physical habitat models. In parametric and non-parametric regression models, model assumptions are often not satisfied and the models are difficult to transfer to other regions. Research-based methods such as the artificial neural networks and individual-based modelling have promising potential as water...

Retrospective forecast of ETAS model with daily parameters estimate

Science.gov (United States)

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

2016-04-01

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

Models in Physics, Models for Physics Learning, and Why the Distinction May Matter in the Case of Electric Circuits

Science.gov (United States)

Hart, Christina

2008-01-01

Models are important both in the development of physics itself and in teaching physics. Historically, the consensus models of physics have come to embody particular ontological assumptions and epistemological commitments. Educators have generally assumed that the consensus models of physics, which have stood the test of time, will also work well…

Parameter identification in multinomial processing tree models

NARCIS (Netherlands)

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

2010-01-01

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

Fast neutron reactor noise analysis: beginning failure detection and physical parameter estimation

International Nuclear Information System (INIS)

Le Guillou, G.

1975-01-01

The analysis of the signals fluctuations coming from a power nuclear reactor (a breeder), by correlation methods and spectral analysis has two principal applications: on line estimation of physical parameters (reactivity coefficients); beginning failures (little boiling, abnormal mechanic vibrations). These two applications give important informations to the reactor core control and permit a good diagnosis [fr

Methods, Devices and Computer Program Products Providing for Establishing a Model for Emulating a Physical Quantity Which Depends on at Least One Input Parameter, and Use Thereof

DEFF Research Database (Denmark)

2014-01-01

The present invention proposes methods, devices and computer program products. To this extent, there is defined a set X including N distinct parameter values x_i for at least one input parameter x, N being an integer greater than or equal to 1, first measured the physical quantity Pm1 for each...

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)

Adherence to a pedometer-based physical activity intervention following kidney transplant and impact on metabolic parameters.

Science.gov (United States)

Lorenz, Elizabeth C; Amer, Hatem; Dean, Patrick G; Stegall, Mark D; Cosio, Fernando G; Cheville, Andrea L

2015-06-01

The majority of kidney transplant recipients die from cardiovascular events. Physical activity may be a modifiable risk factor for cardiovascular disease following transplant. The goal of our study was to examine adherence to a physical activity intervention following kidney transplant and its impact on metabolic parameters. All patients who received a kidney transplant at our center between 12/2010 and 12/2011 received usual care (n = 162), while patients transplanted between 12/2011 and 1/2013 received a 90-day pedometer-based physical activity intervention (n = 145). Metabolic parameters were assessed at four and 12 months post-transplant. Baseline demographics and clinical management were similar between cohorts. Adherence to the prescription was 36.5%. Patients in the physical activity cohort had lower systolic and diastolic blood pressure four months post-transplant compared to the usual care cohort (122 ± 18 vs. 126 ± 16 mmHg, p = 0.049 and 73 ± 10 vs. 77 ± 9, p = 0.004) and less impaired fasting glucose (20.7% vs. 30.9%, p = 0.04). Twelve-month outcomes were not different between cohorts. Over one-third of our cohort adhered to a pedometer-based physical activity intervention following kidney transplant, and the intervention was associated with improved metabolic parameters. Further study of post-transplant exercise interventions and methods to optimize long-term adherence are needed. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Physical-Socio-Economic Modeling of Climate Change

Science.gov (United States)

Chamberlain, R. G.; Vatan, F.

2008-12-01

/information operations model. Each of these models focuses on part of the overall picture while; each contributes information about its area of expertise to a common pool and draws from that pool and the feedbacks from the other models as needed. Existing high-quality physical models are based on analysis of the dynamic interactions of atmospheric, land, and ocean processes. The demographic model tracks the civilian demographics needed by the other models. The populations of neighborhood group age-gender cohorts are affected by births, deaths, aging, and migration. This model provides labor supply and product demand curves to the economic model. The political model focuses on political actors and describes how they use their clout to seek their goals. Clout is derived from civilian support, the formal and informal alliances that actors make with each other, military strength, wealth, and control of information. It considers how they are constrained by their cultural heritage. It deals with shifting alliances. The economic model determines local and international prices and production quantities for a small number of products, including imports and exports and black markets; wages, jobs, and unemployment for a small number of labor categories; capital, growth, and inflation; resource usage and pollution. The media/information operations model addresses the effects of the control and content of inter- group and intra-group communications-and the side effects of these on other groups. This model will consist of rules (probably a large number of them) detailing the effects of media/information operations of various kinds on civilian parameters used in the other models, such as political goals, concern saliencies, and shapes of supply and demand curves.

Correlation and prediction of osmotic coefficient and water activity of aqueous electrolyte solutions by a two-ionic parameter model

International Nuclear Information System (INIS)

Pazuki, G.R.

2005-01-01

In this study, osmotic coefficients and water activities in aqueous solutions have been modeled using a new approach based on the Pitzer model. This model contains two physically significant ionic parameters regarding ionic solvation and the closest distance of approach between ions in a solution. The proposed model was evaluated by estimating the osmotic coefficients of nine electrolytes in aqueous solutions. The obtained results showed that the model is suitable for predicting the osmotic coefficients in aqueous electrolyte solutions. Using adjustable parameters, which have been calculated from regression between the experimental osmotic coefficient and the results of this model, the water activity coefficients of aqueous solutions were calculated. The average absolute relative deviations of the osmotic coefficients between the experimental data and the calculated results were in agreement

Lumped-parameters equivalent circuit for condenser microphones modeling.

Science.gov (United States)

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

2017-10-01

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

Impact of moderator history on physics parameters in pressurized water reactors

International Nuclear Information System (INIS)

Mosteller, R.D.

1988-01-01

The magnitude of differential reactivity effects that result from spectral differences in different portions of a pressurized water (PWR) core is studied, and it is shown that these effects can be correlated very well with the local moderator history. The impact of these differences on physics parameters such as axial offset, isothermal moderator temperature coefficient, and differential control rod worth is shown to be significant for two PWRs of considerably different design

A unified dislocation density-dependent physical-based constitutive model for cold metal forming

Science.gov (United States)

Schacht, K.; Motaman, A. H.; Prahl, U.; Bleck, W.

2017-10-01

Dislocation-density-dependent physical-based constitutive models of metal plasticity while are computationally efficient and history-dependent, can accurately account for varying process parameters such as strain, strain rate and temperature; different loading modes such as continuous deformation, creep and relaxation; microscopic metallurgical processes; and varying chemical composition within an alloy family. Since these models are founded on essential phenomena dominating the deformation, they have a larger range of usability and validity. Also, they are suitable for manufacturing chain simulations since they can efficiently compute the cumulative effect of the various manufacturing processes by following the material state through the entire manufacturing chain and also interpass periods and give a realistic prediction of the material behavior and final product properties. In the physical-based constitutive model of cold metal plasticity introduced in this study, physical processes influencing cold and warm plastic deformation in polycrystalline metals are described using physical/metallurgical internal variables such as dislocation density and effective grain size. The evolution of these internal variables are calculated using adequate equations that describe the physical processes dominating the material behavior during cold plastic deformation. For validation, the model is numerically implemented in general implicit isotropic elasto-viscoplasticity algorithm as a user-defined material subroutine (UMAT) in ABAQUS/Standard and used for finite element simulation of upsetting tests and a complete cold forging cycle of case hardenable MnCr steel family.

Analysis of Modeling Parameters on Threaded Screws.

Energy Technology Data Exchange (ETDEWEB)

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

2015-06-01

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

Parameter Estimates in Differential Equation Models for Chemical Kinetics

Science.gov (United States)

Winkel, Brian

2011-01-01

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

Simultaneous inference for model averaging of derived parameters

DEFF Research Database (Denmark)

Jensen, Signe Marie; Ritz, Christian

2015-01-01

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

Parameter identification in the logistic STAR model

DEFF Research Database (Denmark)

Ekner, Line Elvstrøm; Nejstgaard, Emil

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

Regionalization of SWAT Model Parameters for Use in Ungauged Watersheds

Directory of Open Access Journals (Sweden)

Indrajeet Chaubey

2010-11-01

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

Soil-related Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

A. J. Smith

2003-01-01

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

Inverse modeling for seawater intrusion in coastal aquifers: Insights about parameter sensitivities, variances, correlations and estimation procedures derived from the Henry problem

Science.gov (United States)

Sanz, E.; Voss, C.I.

2006-01-01

Inverse modeling studies employing data collected from the classic Henry seawater intrusion problem give insight into several important aspects of inverse modeling of seawater intrusion problems and effective measurement strategies for estimation of parameters for seawater intrusion. Despite the simplicity of the Henry problem, it embodies the behavior of a typical seawater intrusion situation in a single aquifer. Data collected from the numerical problem solution are employed without added noise in order to focus on the aspects of inverse modeling strategies dictated by the physics of variable-density flow and solute transport during seawater intrusion. Covariances of model parameters that can be estimated are strongly dependent on the physics. The insights gained from this type of analysis may be directly applied to field problems in the presence of data errors, using standard inverse modeling approaches to deal with uncertainty in data. Covariance analysis of the Henry problem indicates that in order to generally reduce variance of parameter estimates, the ideal places to measure pressure are as far away from the coast as possible, at any depth, and the ideal places to measure concentration are near the bottom of the aquifer between the center of the transition zone and its inland fringe. These observations are located in and near high-sensitivity regions of system parameters, which may be identified in a sensitivity analysis with respect to several parameters. However, both the form of error distribution in the observations and the observation weights impact the spatial sensitivity distributions, and different choices for error distributions or weights can result in significantly different regions of high sensitivity. Thus, in order to design effective sampling networks, the error form and weights must be carefully considered. For the Henry problem, permeability and freshwater inflow can be estimated with low estimation variance from only pressure or only

The Early Eocene equable climate problem: can perturbations of climate model parameters identify possible solutions?

Science.gov (United States)

Sagoo, Navjit; Valdes, Paul; Flecker, Rachel; Gregoire, Lauren J

2013-10-28

Geological data for the Early Eocene (56-47.8 Ma) indicate extensive global warming, with very warm temperatures at both poles. However, despite numerous attempts to simulate this warmth, there are remarkable data-model differences in the prediction of these polar surface temperatures, resulting in the so-called 'equable climate problem'. In this paper, for the first time an ensemble with a perturbed climate-sensitive model parameters approach has been applied to modelling the Early Eocene climate. We performed more than 100 simulations with perturbed physics parameters, and identified two simulations that have an optimal fit with the proxy data. We have simulated the warmth of the Early Eocene at 560 ppmv CO2, which is a much lower CO2 level than many other models. We investigate the changes in atmospheric circulation, cloud properties and ocean circulation that are common to these simulations and how they differ from the remaining simulations in order to understand what mechanisms contribute to the polar warming. The parameter set from one of the optimal Early Eocene simulations also produces a favourable fit for the last glacial maximum boundary climate and outperforms the control parameter set for the present day. Although this does not 'prove' that this model is correct, it is very encouraging that there is a parameter set that creates a climate model able to simulate well very different palaeoclimates and the present-day climate. Interestingly, to achieve the great warmth of the Early Eocene this version of the model does not have a strong future climate change Charney climate sensitivity. It produces a Charney climate sensitivity of 2.7(°)C, whereas the mean value of the 18 models in the IPCC Fourth Assessment Report (AR4) is 3.26(°)C±0.69(°)C. Thus, this value is within the range and below the mean of the models included in the AR4.

Inhalation Exposure Input Parameters for the Biosphere Model

Energy Technology Data Exchange (ETDEWEB)

K. Rautenstrauch

2004-09-10

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

Inhalation Exposure Input Parameters for the Biosphere Model

International Nuclear Information System (INIS)

K. Rautenstrauch

2004-01-01

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

Ionic polymer-metal composite torsional sensor: physics-based modeling and experimental validation

Science.gov (United States)

Aidi Sharif, Montassar; Lei, Hong; Khalid Al-Rubaiai, Mohammed; Tan, Xiaobo

2018-07-01

Ionic polymer-metal composites (IPMCs) have intrinsic sensing and actuation properties. Typical IPMC sensors are in the shape of beams and only respond to stimuli acting along beam-bending directions. Rod or tube-shaped IPMCs have been explored as omnidirectional bending actuators or sensors. In this paper, physics-based modeling is studied for a tubular IPMC sensor under pure torsional stimulus. The Poisson–Nernst–Planck model is used to describe the fundamental physics within the IPMC, where it is hypothesized that the anion concentration is coupled to the sum of shear strains induced by the torsional stimulus. Finite element simulation is conducted to solve for the torsional sensing response, where some of the key parameters are identified based on experimental measurements using an artificial neural network. Additional experimental results suggest that the proposed model is able to capture the torsional sensing dynamics for different amplitudes and rates of the torsional stimulus.

Modeling and Parameter Estimation of a Small Wind Generation System

Directory of Open Access Journals (Sweden)

Carlos A. Ramírez Gómez

2013-11-01

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

Improving weather predictability by including land-surface model parameter uncertainty

Science.gov (United States)

Orth, Rene; Dutra, Emanuel; Pappenberger, Florian

2016-04-01

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

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

Science.gov (United States)

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

2012-12-01

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

Laser thermal effect on silicon nitride ceramic based on thermo-chemical reaction with temperature-dependent thermo-physical parameters

International Nuclear Information System (INIS)

Pan, A.F.; Wang, W.J.; Mei, X.S.; Wang, K.D.; Zhao, W.Q.; Li, T.Q.

2016-01-01

Highlights: • A two-dimensional thermo-chemical reaction model is creatively built. • Thermal conductivity and heat capacity of β-Si_3N_4 are computed accurately. • The appropriate thermo-chemical reaction rate is fitted and reaction element length is set to assure the constringency. • The deepest ablated position was not the center of the ablated area due to plasma absorption. • The simulation results demonstrate the thermo-chemical process cant be simplified to be physical phase transition. - Abstract: In this study, a two-dimensional thermo-chemical reaction model with temperature-dependent thermo-physical parameters on Si_3N_4 with 10 ns laser was developed to investigate the ablated size, volume and surface morphology after single pulse. For model parameters, thermal conductivity and heat capacity of β-Si_3N_4 were obtained from first-principles calculations. Thermal-chemical reaction rate was fitted by collision theory, and then, reaction element length was deduced using the relationship between reaction rate and temperature distribution. Furthermore, plasma absorption related to energy loss was approximated as a function of electron concentration in Si_3N_4. It turned out that theoretical ablated volume and radius increased and then remained constant with increasing laser energy, and the maximum ablated depth was not in the center of the ablated zone. Moreover, the surface maximum temperature of Si_3N_4 was verified to be above 3000 K within pulse duration, and it was much higher than its thermal decomposition temperature of 1800 K, which indicated that Si_3N_4 was not ablated directly above the thermal decomposition temperature. Meanwhile, the single pulse ablation of Si_3N_4 was performed at different powers using a TEM_0_0 10 ns pulse Nd:YAG laser to validate the model. The model showed a satisfactory consistence between the experimental data and numerical predictions, presenting a new modeling technology that may significantly increase the

Physics Based Modeling of Compressible Turbulance

Science.gov (United States)

2016-11-07

AFRL-AFOSR-VA-TR-2016-0345 PHYSICS -BASED MODELING OF COMPRESSIBLE TURBULENCE PARVIZ MOIN LELAND STANFORD JUNIOR UNIV CA Final Report 09/13/2016...on the AFOSR project (FA9550-11-1-0111) entitled: Physics based modeling of compressible turbulence. The period of performance was, June 15, 2011...by ANSI Std. Z39.18 Page 1 of 2FORM SF 298 11/10/2016https://livelink.ebs.afrl.af.mil/livelink/llisapi.dll PHYSICS -BASED MODELING OF COMPRESSIBLE

Hybrid artificial bee colony algorithm for parameter optimization of five-parameter bidirectional reflectance distribution function model.

Science.gov (United States)

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

2017-11-20

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

Evaluating climate model performance with various parameter sets using observations over the recent past

Directory of Open Access Journals (Sweden)

M. F. Loutre

2011-05-01

Full Text Available Many sources of uncertainty limit the accuracy of climate projections. Among them, we focus here on the parameter uncertainty, i.e. the imperfect knowledge of the values of many physical parameters in a climate model. Therefore, we use LOVECLIM, a global three-dimensional Earth system model of intermediate complexity and vary several parameters within a range based on the expert judgement of model developers. Nine climatic parameter sets and three carbon cycle parameter sets are selected because they yield present-day climate simulations coherent with observations and they cover a wide range of climate responses to doubled atmospheric CO₂ concentration and freshwater flux perturbation in the North Atlantic. Moreover, they also lead to a large range of atmospheric CO₂ concentrations in response to prescribed emissions. Consequently, we have at our disposal 27 alternative versions of LOVECLIM (each corresponding to one parameter set that provide very different responses to some climate forcings. The 27 model versions are then used to illustrate the range of responses provided over the recent past, to compare the time evolution of climate variables over the time interval for which they are available (the last few decades up to more than one century and to identify the outliers and the "best" versions over that particular time span. For example, between 1979 and 2005, the simulated global annual mean surface temperature increase ranges from 0.24 °C to 0.64 °C, while the simulated increase in atmospheric CO₂ concentration varies between 40 and 50 ppmv. Measurements over the same period indicate an increase in global annual mean surface temperature of 0.45 °C (Brohan et al., 2006 and an increase in atmospheric CO₂ concentration of 44 ppmv (Enting et al., 1994; GLOBALVIEW-CO2, 2006. Only a few parameter sets yield simulations that reproduce the observed key variables of the climate system over the last

Hydrological model parameter dimensionality is a weak measure of prediction uncertainty

Science.gov (United States)

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

2015-04-01

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

Parameter identification and global sensitivity analysis of Xin'anjiang model using meta-modeling approach

Directory of Open Access Journals (Sweden)

Xiao-meng Song

2013-01-01

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

Marching on in anything: solving electromagnetic field equations with a varying physical parameter

NARCIS (Netherlands)

Tijhuis, A.G.; Zwamborn, A.P.M.; Smith, P.D.; Cloude, S.R.

2002-01-01

In this paper, we consider the determination of electromagnetic fields for a (large) number of values of a physical parameter. We restrict ourselves to the case where the linear system originates from one or more integral equations. We apply an iterative procedure based on the minimization of an

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....

Band parameters of phosphorene

DEFF Research Database (Denmark)

Lew Yan Voon, L. C.; Wang, J.; Zhang, Y.

2015-01-01

Phosphorene is a two-dimensional nanomaterial with a direct band-gap at the Brillouin zone center. In this paper, we present a recently derived effective-mass theory of the band structure in the presence of strain and electric field, based upon group theory. Band parameters for this theory...... are computed using a first-principles theory based upon the generalized-gradient approximation to the density-functional theory. These parameters and Hamiltonian will be useful for modeling physical properties of phosphorene....

Semiparametric modeling: Correcting low-dimensional model error in parametric models

International Nuclear Information System (INIS)

Berry, Tyrus; Harlim, John

2016-01-01

In this paper, a semiparametric modeling approach is introduced as a paradigm for addressing model error arising from unresolved physical phenomena. Our approach compensates for model error by learning an auxiliary dynamical model for the unknown parameters. Practically, the proposed approach consists of the following steps. Given a physics-based model and a noisy data set of historical observations, a Bayesian filtering algorithm is used to extract a time-series of the parameter values. Subsequently, the diffusion forecast algorithm is applied to the retrieved time-series in order to construct the auxiliary model for the time evolving parameters. The semiparametric forecasting algorithm consists of integrating the existing physics-based model with an ensemble of parameters sampled from the probability density function of the diffusion forecast. To specify initial conditions for the diffusion forecast, a Bayesian semiparametric filtering method that extends the Kalman-based filtering framework is introduced. In difficult test examples, which introduce chaotically and stochastically evolving hidden parameters into the Lorenz-96 model, we show that our approach can effectively compensate for model error, with forecasting skill comparable to that of the perfect model.

Physical and Chemical Environmental Abstraction Model

International Nuclear Information System (INIS)