Statistical models for thermal ageing of steel materials in nuclear power plants
International Nuclear Information System (INIS)
Persoz, M.
1996-01-01
Some category of steel materials in nuclear power plants may be subjected to thermal ageing, whose extent depends on the steel chemical composition and the ageing parameters, i.e. temperature and duration. This ageing affects the 'impact strength' of the materials, which is a mechanical property. In order to assess the residual lifetime of these components, a probabilistic study has been launched, which takes into account the scatter over the input parameters of the mechanical model. Predictive formulae for estimating the impact strength of aged materials are important input data of the model. A data base has been created with impact strength results obtained from an ageing program in laboratory and statistical treatments have been undertaken. Two kinds of model have been developed, with non linear regression methods (PROC NLIN, available in SAS/STAT). The first one, using a hyperbolic tangent function, is partly based on physical considerations, and the second one, of an exponential type, is purely statistically built. The difficulties consist in selecting the significant parameters and attributing initial values to the coefficients, which is a requirement of the NLIN procedure. This global statistical analysis has led to general models that are unction of the chemical variables and the ageing parameters. These models are as precise (if not more) as local models that had been developed earlier for some specific values of ageing temperature and ageing duration. This paper describes the data and the methodology used to build the models and analyses the results given by the SAS system. (author)
Developing Statistical Evaluation Model of Introduction Effect of MSW Thermal Recycling
Aoyama, Makoto; Kato, Takeyoshi; Suzuoki, Yasuo
For the effective utilization of municipal solid waste (MSW) through a thermal recycling, new technologies, such as an incineration plant using a Molten Carbonate Fuel Cell (MCFC), are being developed. The impact of new technologies should be evaluated statistically for various municipalities, so that the target of technological development or potential cost reduction due to the increased cumulative number of installed system can be discussed. For this purpose, we developed a model for discussing the impact of new technologies, where a statistical mesh data set was utilized to estimate the heat demand around the incineration plant. This paper examines a case study by using a developed model, where a conventional type and a MCFC type MSW incineration plant is compared in terms of the reduction in primary energy and the revenue by both electricity and heat supply. Based on the difference in annual revenue, we calculate the allowable investment in MCFC-type MSW incineration plant in addition to conventional plant. The results suggest that allowable investment can be about 30 millions yen/(t/day) in small municipalities, while it is only 10 millions yen/(t/day) in large municipalities. The sensitive analysis shows the model can be useful for discussing the difference of impact of material recycling of plastics on thermal recycling technologies.
Statistical modeling of an integrated boiler for coal fired thermal power plant
Directory of Open Access Journals (Sweden)
Sreepradha Chandrasekharan
2017-06-01
Full Text Available The coal fired thermal power plants plays major role in the power production in the world as they are available in abundance. Many of the existing power plants are based on the subcritical technology which can produce power with the efficiency of around 33%. But the newer plants are built on either supercritical or ultra-supercritical technology whose efficiency can be up to 50%. Main objective of the work is to enhance the efficiency of the existing subcritical power plants to compensate for the increasing demand. For achieving the objective, the statistical modeling of the boiler units such as economizer, drum and the superheater are initially carried out. The effectiveness of the developed models is tested using analysis methods like R2 analysis and ANOVA (Analysis of Variance. The dependability of the process variable (temperature on different manipulated variables is analyzed in the paper. Validations of the model are provided with their error analysis. Response surface methodology (RSM supported by DOE (design of experiments are implemented to optimize the operating parameters. Individual models along with the integrated model are used to study and design the predictive control of the coal-fired thermal power plant. Keywords: Chemical engineering, Applied mathematics
Statistical modeling of an integrated boiler for coal fired thermal power plant.
Chandrasekharan, Sreepradha; Panda, Rames Chandra; Swaminathan, Bhuvaneswari Natrajan
2017-06-01
The coal fired thermal power plants plays major role in the power production in the world as they are available in abundance. Many of the existing power plants are based on the subcritical technology which can produce power with the efficiency of around 33%. But the newer plants are built on either supercritical or ultra-supercritical technology whose efficiency can be up to 50%. Main objective of the work is to enhance the efficiency of the existing subcritical power plants to compensate for the increasing demand. For achieving the objective, the statistical modeling of the boiler units such as economizer, drum and the superheater are initially carried out. The effectiveness of the developed models is tested using analysis methods like R 2 analysis and ANOVA (Analysis of Variance). The dependability of the process variable (temperature) on different manipulated variables is analyzed in the paper. Validations of the model are provided with their error analysis. Response surface methodology (RSM) supported by DOE (design of experiments) are implemented to optimize the operating parameters. Individual models along with the integrated model are used to study and design the predictive control of the coal-fired thermal power plant.
Lattice ellipsoidal statistical BGK model for thermal non-equilibrium flows
Meng, Jianping; Zhang, Yonghao; Hadjiconstantinou, Nicolas G.; Radtke, Gregg A.; Shan, Xiaowen
2013-03-01
A thermal lattice Boltzmann model is constructed on the basis of the ellipsoidal statistical Bhatnagar-Gross-Krook (ES-BGK) collision operator via the Hermite moment representation. The resulting lattice ES-BGK model uses a single distribution function and features an adjustable Prandtl number. Numerical simulations show that using a moderate discrete velocity set, this model can accurately recover steady and transient solutions of the ES-BGK equation in the slip-flow and early transition regimes in the small Mach number limit that is typical of microscale problems of practical interest. In the transition regime in particular, comparisons with numerical solutions of the ES-BGK model, direct Monte Carlo and low-variance deviational Monte Carlo simulations show good accuracy for values of the Knudsen number up to approximately 0.5. On the other hand, highly non-equilibrium phenomena characterized by high Mach numbers, such as viscous heating and force-driven Poiseuille flow for large values of the driving force, are more difficult to capture quantitatively in the transition regime using discretizations chosen with computational efficiency in mind such as the one used here, although improved accuracy is observed as the number of discrete velocities is increased.
International Nuclear Information System (INIS)
Yokoyama, Masayuki
2014-01-01
A statistical approach is proposed to predict thermal diffusivity profiles as a transport “model” in fusion plasmas. It can provide regression expressions for the ion and electron heat diffusivities (χ i and χ e ), separately, to construct their radial profiles. An approach that this letter is proposing outstrips the conventional scaling laws for the global confinement time (τ E ) since it also deals with profiles (temperature, density, heating depositions etc.). This approach has become possible with the analysis database accumulated by the extensive application of the integrated transport analysis suite to experiment data. In this letter, TASK3D-a analysis database for high-ion-temperature (high-T i ) plasmas in the LHD (Large Helical Device) is used as an example to describe an approach. (author)
International Nuclear Information System (INIS)
Pham, Binh T.; Hawkes, Grant L.; Einerson, Jeffrey J.
2014-01-01
As part of the High Temperature Reactors (HTR) R and D program, a series of irradiation tests, designated as Advanced Gas-cooled Reactor (AGR), have been defined to support development and qualification of fuel design, fabrication process, and fuel performance under normal operation and accident conditions. The AGR tests employ fuel compacts placed in a graphite cylinder shrouded by a steel capsule and instrumented with thermocouples (TC) embedded in graphite blocks enabling temperature control. While not possible to obtain by direct measurements in the tests, crucial fuel conditions (e.g., temperature, neutron fast fluence, and burnup) are calculated using core physics and thermal modeling codes. This paper is focused on AGR test fuel temperature predicted by the ABAQUS code's finite element-based thermal models. The work follows up on a previous study, in which several statistical analysis methods were adapted, implemented in the NGNP Data Management and Analysis System (NDMAS), and applied for qualification of AGR-1 thermocouple data. Abnormal trends in measured data revealed by the statistical analysis are traced to either measuring instrument deterioration or physical mechanisms in capsules that may have shifted the system thermal response. The main thrust of this work is to exploit the variety of data obtained in irradiation and post-irradiation examination (PIE) for assessment of modeling assumptions. As an example, the uneven reduction of the control gas gap in Capsule 5 found in the capsule metrology measurements in PIE helps identify mechanisms other than TC drift causing the decrease in TC readings. This suggests a more physics-based modification of the thermal model that leads to a better fit with experimental data, thus reducing model uncertainty and increasing confidence in the calculated fuel temperatures of the AGR-1 test
Energy Technology Data Exchange (ETDEWEB)
Pham, Binh T., E-mail: Binh.Pham@inl.gov [Human Factor, Controls and Statistics Department, Nuclear Science and Technology, Idaho National Laboratory, Idaho Falls, ID 83415 (United States); Hawkes, Grant L. [Thermal Science and Safety Analysis Department, Nuclear Science and Technology, Idaho National Laboratory, Idaho Falls, ID 83415 (United States); Einerson, Jeffrey J. [Human Factor, Controls and Statistics Department, Nuclear Science and Technology, Idaho National Laboratory, Idaho Falls, ID 83415 (United States)
2014-05-01
As part of the High Temperature Reactors (HTR) R and D program, a series of irradiation tests, designated as Advanced Gas-cooled Reactor (AGR), have been defined to support development and qualification of fuel design, fabrication process, and fuel performance under normal operation and accident conditions. The AGR tests employ fuel compacts placed in a graphite cylinder shrouded by a steel capsule and instrumented with thermocouples (TC) embedded in graphite blocks enabling temperature control. While not possible to obtain by direct measurements in the tests, crucial fuel conditions (e.g., temperature, neutron fast fluence, and burnup) are calculated using core physics and thermal modeling codes. This paper is focused on AGR test fuel temperature predicted by the ABAQUS code's finite element-based thermal models. The work follows up on a previous study, in which several statistical analysis methods were adapted, implemented in the NGNP Data Management and Analysis System (NDMAS), and applied for qualification of AGR-1 thermocouple data. Abnormal trends in measured data revealed by the statistical analysis are traced to either measuring instrument deterioration or physical mechanisms in capsules that may have shifted the system thermal response. The main thrust of this work is to exploit the variety of data obtained in irradiation and post-irradiation examination (PIE) for assessment of modeling assumptions. As an example, the uneven reduction of the control gas gap in Capsule 5 found in the capsule metrology measurements in PIE helps identify mechanisms other than TC drift causing the decrease in TC readings. This suggests a more physics-based modification of the thermal model that leads to a better fit with experimental data, thus reducing model uncertainty and increasing confidence in the calculated fuel temperatures of the AGR-1 test.
Statistical and thermal physics with computer applications
Gould, Harvey
2010-01-01
This textbook carefully develops the main ideas and techniques of statistical and thermal physics and is intended for upper-level undergraduate courses. The authors each have more than thirty years' experience in teaching, curriculum development, and research in statistical and computational physics. Statistical and Thermal Physics begins with a qualitative discussion of the relation between the macroscopic and microscopic worlds and incorporates computer simulations throughout the book to provide concrete examples of important conceptual ideas. Unlike many contemporary texts on the
Sampling, Probability Models and Statistical Reasoning Statistical
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 1; Issue 5. Sampling, Probability Models and Statistical Reasoning Statistical Inference. Mohan Delampady V R Padmawar. General Article Volume 1 Issue 5 May 1996 pp 49-58 ...
Diffeomorphic Statistical Deformation Models
DEFF Research Database (Denmark)
Hansen, Michael Sass; Hansen, Mads/Fogtman; Larsen, Rasmus
2007-01-01
In this paper we present a new method for constructing diffeomorphic statistical deformation models in arbitrary dimensional images with a nonlinear generative model and a linear parameter space. Our deformation model is a modified version of the diffeomorphic model introduced by Cootes et al....... The modifications ensure that no boundary restriction has to be enforced on the parameter space to prevent folds or tears in the deformation field. For straightforward statistical analysis, principal component analysis and sparse methods, we assume that the parameters for a class of deformations lie on a linear...... with ground truth in form of manual expert annotations, and compared to Cootes's model. We anticipate applications in unconstrained diffeomorphic synthesis of images, e.g. for tracking, segmentation, registration or classification purposes....
Availability statistics for thermal power plants
International Nuclear Information System (INIS)
1989-01-01
Denmark, Finland and Sweden have adopted almost the same methods of recording and calculation of availability data. For a number of years comparable availability and outage data for thermal power have been summarized and published in one report. The purpose of the report now presented for 1989 containing general statistical data is to produce basic information on existing kinds of thermal power in the countries concerned. With this information as a basis additional and more detailed information can be exchanged in direct contacts between bodies in the above mentioned countries according to forms established for that purpose. The report includes fossil steam power, nuclear power and gas turbines. The information is presented in separate diagrams for each country, but for plants burning fossil fuel also in a joint NORDEL statistics with data grouped according to type of fuel used. The grouping of units into classes of capacity has been made in accordance with the classification adopted by UNIPEDE/WEC. Values based on energy have been adopted as basic availability data. The same applies to the preference made in the definitions outlined by UNIPEDE and UNIPEDE/WEC. Some data based on time have been included to make possible comparisons with certain international values and for further illustration of the performance. For values given in the report, the definitions in the NORDEL document ''Concepts of Availability for Thermal Power, September 1977'', have been applied. (author)
Statistical and thermal physics an introduction
Hoch, Michael JR
2011-01-01
""When I started reading Michael J.R. Hoch's book Statistical and Thermal Physics: An Introduction I thought to myself that this is another book the same as a large group of others with similar content. … But during my reading this unjustified belief changed. … The main reason for this change was the way of information presentation: … the way of presentation is designed so that the reader receives only the information that is necessary to give the essence of the problem. … this book will provide an introduction to the subject especially for those who are interested in basic or applied physics.
Availability statistics for thermal power plants
International Nuclear Information System (INIS)
1990-01-01
Denmark, Finland and Sweden have adopted almost the same methods of recording and calculation of availability data. For a number of years comparable availability and outage data for thermal power have been summarized and published in one report. The purpose of the report now presented for 1990 containing general statistical data is to produce basic information on existing kinds of thermal power in the countries concerned. With this information as a basis additional and more detailed information can be exchanged in direct contacts between bodies in the above mentioned countries according to forms established for that purpose. The report includes fossil steam power, nuclear power and gas turbines. The information is presented in separate diagrams for each country, but for plants burning fossil fuel also in a joint NORDEL statistics with data grouped according to type of fuel used. The grouping of units into classes of capacity has been made in accordance with the classification adopted by UNIPEDE/WEC. Values based on energy have been adopted as basic availability data. The same applied to the preference made in the definitions outlined by UNIPEDE and UNIPEDE/WEC. Some data based on time have been included to make possible comparisons with certain international values and for futher illustration of the performance. (au)
Exclusion statistics and integrable models
International Nuclear Information System (INIS)
Mashkevich, S.
1998-01-01
The definition of exclusion statistics, as given by Haldane, allows for a statistical interaction between distinguishable particles (multi-species statistics). The thermodynamic quantities for such statistics ca be evaluated exactly. The explicit expressions for the cluster coefficients are presented. Furthermore, single-species exclusion statistics is realized in one-dimensional integrable models. The interesting questions of generalizing this correspondence onto the higher-dimensional and the multi-species cases remain essentially open
Statistical mechanics of microscopically thin thermalized shells
Kosmrlj, Andrej
Recent explosion in fabrication of microscopically thin free standing structures made from graphene and other two-dimensional materials has led to a renewed interest in the mechanics of such structures in presence of thermal fluctuations. Since late 1980s it has been known that for flat solid sheets thermal fluctuations effectively increase the bending rigidity and reduce the bulk and shear moduli in a scale-dependent fashion. However, much is still unknown about the mechanics of thermalized flat sheets of complex geometries and about the mechanics of thermalized shells with non-zero background curvature. In this talk I will present recent development in the mechanics of thermalized ribbons, spherical shells and cylindrical tubes. Long ribbons are found to behave like hybrids between flat sheets with renormalized elastic constants and semi-flexible polymers, and these results can be used to predict the mechanics of graphene kirigami structures. Contrary to the anticipated behavior for ribbons, the non-zero background curvature of shells leads to remarkable novel phenomena. In shells, thermal fluctuations effectively generate negative surface tension, which can significantly reduce the critical buckling pressure for spherical shells and the critical axial load for cylindrical tubes. For large shells this thermally generated load becomes big enough to spontaneously crush spherical shells and cylindrical tubes even in the absence of external loads. I will comment on the relevance for crushing of microscopic shells (viral capsids, bacteria, microcapsules) due to osmotic shocks and for crushing of nanotubes.
Exclusion statistics and integrable models
International Nuclear Information System (INIS)
Mashkevich, S.
1998-01-01
The definition of exclusion statistics that was given by Haldane admits a 'statistical interaction' between distinguishable particles (multispecies statistics). For such statistics, thermodynamic quantities can be evaluated exactly; explicit expressions are presented here for cluster coefficients. Furthermore, single-species exclusion statistics is realized in one-dimensional integrable models of the Calogero-Sutherland type. The interesting questions of generalizing this correspondence to the higher-dimensional and the multispecies cases remain essentially open; however, our results provide some hints as to searches for the models in question
Thermalized solutions, statistical mechanics and turbulence
Indian Academy of Sciences (India)
2015-02-20
Feb 20, 2015 ... In this study, we examine the intriguing connection between turbulence and equilibrium statistical mechanics. There are several recent works which emphasize this connection. Thus in the last ... Current Issue : Vol. 90, Issue 6.
Statistical Model of Extreme Shear
DEFF Research Database (Denmark)
Larsen, Gunner Chr.; Hansen, Kurt Schaldemose
2004-01-01
In order to continue cost-optimisation of modern large wind turbines, it is important to continously increase the knowledge on wind field parameters relevant to design loads. This paper presents a general statistical model that offers site-specific prediction of the probability density function...... by a model that, on a statistically consistent basis, describe the most likely spatial shape of an extreme wind shear event. Predictions from the model have been compared with results from an extreme value data analysis, based on a large number of high-sampled full-scale time series measurements...... are consistent, given the inevitabel uncertainties associated with model as well as with the extreme value data analysis. Keywords: Statistical model, extreme wind conditions, statistical analysis, turbulence, wind loading, statistical analysis, turbulence, wind loading, wind shear, wind turbines....
Thermal conductivity model for nanofiber networks
Zhao, Xinpeng; Huang, Congliang; Liu, Qingkun; Smalyukh, Ivan I.; Yang, Ronggui
2018-02-01
Understanding thermal transport in nanofiber networks is essential for their applications in thermal management, which are used extensively as mechanically sturdy thermal insulation or high thermal conductivity materials. In this study, using the statistical theory and Fourier's law of heat conduction while accounting for both the inter-fiber contact thermal resistance and the intrinsic thermal resistance of nanofibers, an analytical model is developed to predict the thermal conductivity of nanofiber networks as a function of their geometric and thermal properties. A scaling relation between the thermal conductivity and the geometric properties including volume fraction and nanofiber length of the network is revealed. This model agrees well with both numerical simulations and experimental measurements found in the literature. This model may prove useful in analyzing the experimental results and designing nanofiber networks for both high and low thermal conductivity applications.
Thermal conductivity model for nanofiber networks
Energy Technology Data Exchange (ETDEWEB)
Zhao, Xinpeng [Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, USA; Huang, Congliang [Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, USA; School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221116, China; Liu, Qingkun [Department of Physics, University of Colorado, Boulder, Colorado 80309, USA; Smalyukh, Ivan I. [Department of Physics, University of Colorado, Boulder, Colorado 80309, USA; Materials Science and Engineering Program, University of Colorado, Boulder, Colorado 80309, USA; Yang, Ronggui [Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, USA; Materials Science and Engineering Program, University of Colorado, Boulder, Colorado 80309, USA; Buildings and Thermal Systems Center, National Renewable Energy Laboratory, Golden, Colorado 80401, USA
2018-02-28
Understanding thermal transport in nanofiber networks is essential for their applications in thermal management, which are used extensively as mechanically sturdy thermal insulation or high thermal conductivity materials. In this study, using the statistical theory and Fourier's law of heat conduction while accounting for both the inter-fiber contact thermal resistance and the intrinsic thermal resistance of nanofibers, an analytical model is developed to predict the thermal conductivity of nanofiber networks as a function of their geometric and thermal properties. A scaling relation between the thermal conductivity and the geometric properties including volume fraction and nanofiber length of the network is revealed. This model agrees well with both numerical simulations and experimental measurements found in the literature. This model may prove useful in analyzing the experimental results and designing nanofiber networks for both high and low thermal conductivity applications.
Statistical modeling for degradation data
Lio, Yuhlong; Ng, Hon; Tsai, Tzong-Ru
2017-01-01
This book focuses on the statistical aspects of the analysis of degradation data. In recent years, degradation data analysis has come to play an increasingly important role in different disciplines such as reliability, public health sciences, and finance. For example, information on products’ reliability can be obtained by analyzing degradation data. In addition, statistical modeling and inference techniques have been developed on the basis of different degradation measures. The book brings together experts engaged in statistical modeling and inference, presenting and discussing important recent advances in degradation data analysis and related applications. The topics covered are timely and have considerable potential to impact both statistics and reliability engineering.
Energy Technology Data Exchange (ETDEWEB)
Ping, Tso Chin [Malaya Univ., Kuala Lumpur (Malaysia)
1984-12-01
The phenomenon of thermal explosion arises in several important safety problems, yet scientists are still baffled by its origin. This article reviews some of the models that have been proposed to explain the phenomenon.
International Nuclear Information System (INIS)
Tso Chin Ping
1984-01-01
The phenomenon of thermal explosion arises in several important safety problems, yet scientists are still baffled by its origin. This article reviews some of the models that have been proposed to explain the phenomenon. (author)
Statistical modelling with quantile functions
Gilchrist, Warren
2000-01-01
Galton used quantiles more than a hundred years ago in describing data. Tukey and Parzen used them in the 60s and 70s in describing populations. Since then, the authors of many papers, both theoretical and practical, have used various aspects of quantiles in their work. Until now, however, no one put all the ideas together to form what turns out to be a general approach to statistics.Statistical Modelling with Quantile Functions does just that. It systematically examines the entire process of statistical modelling, starting with using the quantile function to define continuous distributions. The author shows that by using this approach, it becomes possible to develop complex distributional models from simple components. A modelling kit can be developed that applies to the whole model - deterministic and stochastic components - and this kit operates by adding, multiplying, and transforming distributions rather than data.Statistical Modelling with Quantile Functions adds a new dimension to the practice of stati...
A Statistical Programme Assignment Model
DEFF Research Database (Denmark)
Rosholm, Michael; Staghøj, Jonas; Svarer, Michael
When treatment effects of active labour market programmes are heterogeneous in an observable way across the population, the allocation of the unemployed into different programmes becomes a particularly important issue. In this paper, we present a statistical model designed to improve the present...... duration of unemployment spells may result if a statistical programme assignment model is introduced. We discuss several issues regarding the plementation of such a system, especially the interplay between the statistical model and case workers....
Statistical analysis of thermal conductivity of nanofluid containing ...
Indian Academy of Sciences (India)
Thermal conductivity measurements of nanofluids were analysed via two-factor completely randomized design and comparison of data means is carried out with Duncan's multiple-range test. Statistical analysis of experimental data show that temperature and weight fraction have a reasonable impact on the thermal ...
Human Thermal Model Evaluation Using the JSC Human Thermal Database
Bue, Grant; Makinen, Janice; Cognata, Thomas
2012-01-01
Human thermal modeling has considerable long term utility to human space flight. Such models provide a tool to predict crew survivability in support of vehicle design and to evaluate crew response in untested space environments. It is to the benefit of any such model not only to collect relevant experimental data to correlate it against, but also to maintain an experimental standard or benchmark for future development in a readily and rapidly searchable and software accessible format. The Human thermal database project is intended to do just so; to collect relevant data from literature and experimentation and to store the data in a database structure for immediate and future use as a benchmark to judge human thermal models against, in identifying model strengths and weakness, to support model development and improve correlation, and to statistically quantify a model s predictive quality. The human thermal database developed at the Johnson Space Center (JSC) is intended to evaluate a set of widely used human thermal models. This set includes the Wissler human thermal model, a model that has been widely used to predict the human thermoregulatory response to a variety of cold and hot environments. These models are statistically compared to the current database, which contains experiments of human subjects primarily in air from a literature survey ranging between 1953 and 2004 and from a suited experiment recently performed by the authors, for a quantitative study of relative strength and predictive quality of the models.
Thermal fatigue. Materials modelling
International Nuclear Information System (INIS)
Siegele, D.; Fingerhuth, J.; Mrovec, M.
2012-01-01
In the framework of the ongoing joint research project 'Thermal Fatigue - Basics of the system-, outflow- and material-characteristics of piping under thermal fatigue' funded by the German Federal Ministry of Education and Research (BMBF) fundamental numerical and experimental investigations on the material behavior under transient thermal-mechanical stress conditions (high cycle fatigue V HCF and low cycle fatigue - LCF) are carried out. The primary objective of the research is the further development of simulation methods applied in safety evaluations of nuclear power plant components. In this context the modeling of crack initiation and growth inside the material structure induced by varying thermal loads are of particular interest. Therefore, three scientific working groups organized in three sub-projects of the joint research project are dealing with numerical modeling and simulation at different levels ranging from atomistic to micromechanics and continuum mechanics, and in addition corresponding experimental data for the validation of the numerical results and identification of the parameters of the associated material models are provided. The present contribution is focused on the development and experimental validation of material models and methods to characterize the damage evolution and the life cycle assessment as a result of thermal cyclic loading. The individual purposes of the subprojects are as following: - Material characterization, Influence of temperature and surface roughness on fatigue endurances, biaxial thermo-mechanical behavior, experiments on structural behavior of cruciform specimens and scatter band analysis (IfW Darmstadt) - Life cycle assessment with micromechanical material models (MPA Stuttgart) - Life cycle assessment with atomistic and damage-mechanical material models associated with material tests under thermal fatigue (Fraunhofer IWM, Freiburg) - Simulation of fatigue crack growth, opening and closure of a short crack under
Tropical geometry of statistical models.
Pachter, Lior; Sturmfels, Bernd
2004-11-16
This article presents a unified mathematical framework for inference in graphical models, building on the observation that graphical models are algebraic varieties. From this geometric viewpoint, observations generated from a model are coordinates of a point in the variety, and the sum-product algorithm is an efficient tool for evaluating specific coordinates. Here, we address the question of how the solutions to various inference problems depend on the model parameters. The proposed answer is expressed in terms of tropical algebraic geometry. The Newton polytope of a statistical model plays a key role. Our results are applied to the hidden Markov model and the general Markov model on a binary tree.
Statistical Model of Extreme Shear
DEFF Research Database (Denmark)
Hansen, Kurt Schaldemose; Larsen, Gunner Chr.
2005-01-01
In order to continue cost-optimisation of modern large wind turbines, it is important to continuously increase the knowledge of wind field parameters relevant to design loads. This paper presents a general statistical model that offers site-specific prediction of the probability density function...... by a model that, on a statistically consistent basis, describes the most likely spatial shape of an extreme wind shear event. Predictions from the model have been compared with results from an extreme value data analysis, based on a large number of full-scale measurements recorded with a high sampling rate...
Statistical Models for Social Networks
Snijders, Tom A. B.; Cook, KS; Massey, DS
2011-01-01
Statistical models for social networks as dependent variables must represent the typical network dependencies between tie variables such as reciprocity, homophily, transitivity, etc. This review first treats models for single (cross-sectionally observed) networks and then for network dynamics. For
Sensometrics: Thurstonian and Statistical Models
DEFF Research Database (Denmark)
Christensen, Rune Haubo Bojesen
. sensR is a package for sensory discrimination testing with Thurstonian models and ordinal supports analysis of ordinal data with cumulative link (mixed) models. While sensR is closely connected to the sensometrics field, the ordinal package has developed into a generic statistical package applicable......This thesis is concerned with the development and bridging of Thurstonian and statistical models for sensory discrimination testing as applied in the scientific discipline of sensometrics. In sensory discrimination testing sensory differences between products are detected and quantified by the use...... and sensory discrimination testing in particular in a series of papers by advancing Thurstonian models for a range of sensory discrimination protocols in addition to facilitating their application by providing software for fitting these models. The main focus is on identifying Thurstonian models...
Classical model of intermediate statistics
International Nuclear Information System (INIS)
Kaniadakis, G.
1994-01-01
In this work we present a classical kinetic model of intermediate statistics. In the case of Brownian particles we show that the Fermi-Dirac (FD) and Bose-Einstein (BE) distributions can be obtained, just as the Maxwell-Boltzmann (MD) distribution, as steady states of a classical kinetic equation that intrinsically takes into account an exclusion-inclusion principle. In our model the intermediate statistics are obtained as steady states of a system of coupled nonlinear kinetic equations, where the coupling constants are the transmutational potentials η κκ' . We show that, besides the FD-BE intermediate statistics extensively studied from the quantum point of view, we can also study the MB-FD and MB-BE ones. Moreover, our model allows us to treat the three-state mixing FD-MB-BE intermediate statistics. For boson and fermion mixing in a D-dimensional space, we obtain a family of FD-BE intermediate statistics by varying the transmutational potential η BF . This family contains, as a particular case when η BF =0, the quantum statistics recently proposed by L. Wu, Z. Wu, and J. Sun [Phys. Lett. A 170, 280 (1992)]. When we consider the two-dimensional FD-BE statistics, we derive an analytic expression of the fraction of fermions. When the temperature T→∞, the system is composed by an equal number of bosons and fermions, regardless of the value of η BF . On the contrary, when T=0, η BF becomes important and, according to its value, the system can be completely bosonic or fermionic, or composed both by bosons and fermions
International Nuclear Information System (INIS)
Weissman, P.R.; Kieffer, H.H.
1987-01-01
The past year was one of tremendous activity because of the appearance of Halley's Comet. Observations of the comet were collected from a number of sources and compared with the detailed predictions of the comet thermal modeling program. Spacecraft observations of key physical parameters for cometary nucleus were incorporated into the thermal model and new cases run. These results have led to a much better understanding of physical processes on the nucleus and have pointed the way for further improvements to the modeling program. A model for the large-scale structure of cometary nuclei was proposed in which comets were envisioned as loosely bound agglomerations of smaller icy planetesimals, essentially a rubble pile of primordial dirty snowballs. In addition, a study of the physical history of comets was begun, concentrating on processes during formation and in the Oort cloud which would alter the volatile and nonvolatile materials in cometary nuclei from their pristine state before formation
Textual information access statistical models
Gaussier, Eric
2013-01-01
This book presents statistical models that have recently been developed within several research communities to access information contained in text collections. The problems considered are linked to applications aiming at facilitating information access:- information extraction and retrieval;- text classification and clustering;- opinion mining;- comprehension aids (automatic summarization, machine translation, visualization).In order to give the reader as complete a description as possible, the focus is placed on the probability models used in the applications
Improved model for statistical alignment
Energy Technology Data Exchange (ETDEWEB)
Miklos, I.; Toroczkai, Z. (Zoltan)
2001-01-01
The statistical approach to molecular sequence evolution involves the stochastic modeling of the substitution, insertion and deletion processes. Substitution has been modeled in a reliable way for more than three decades by using finite Markov-processes. Insertion and deletion, however, seem to be more difficult to model, and thc recent approaches cannot acceptably deal with multiple insertions and deletions. A new method based on a generating function approach is introduced to describe the multiple insertion process. The presented algorithm computes the approximate joint probability of two sequences in 0(13) running time where 1 is the geometric mean of the sequence lengths.
Energy Technology Data Exchange (ETDEWEB)
Buscheck, T., LLNL
1998-04-29
This chapter describes the physical processes and natural and engineered system conditions that affect thermal-hydrological (T-H) behavior in the unsaturated zone (UZ) at Yucca Mountain and how these effects are represented in mathematical and numerical models that are used to predict T-H conditions in the near field, altered zone, and engineered barrier system (EBS), and on waste package (WP) surfaces.
Rectenna thermal model development
Kadiramangalam, Murall; Alden, Adrian; Speyer, Daniel
1992-01-01
Deploying rectennas in space requires adapting existing designs developed for terrestrial applications to the space environment. One of the major issues in doing so is to understand the thermal performance of existing designs in the space environment. Toward that end, a 3D rectenna thermal model has been developed, which involves analyzing shorted rectenna elements and finite size rectenna element arrays. A shorted rectenna element is a single element whose ends are connected together by a material of negligible thermal resistance. A shorted element is a good approximation to a central element of a large array. This model has been applied to Brown's 2.45 GHz rectenna design. Results indicate that Brown's rectenna requires redesign or some means of enhancing the heat dissipation in order for the diode temperature to be maintained below 200 C above an output power density of 620 W/sq.m. The model developed in this paper is very general and can be used for the analysis and design of any type of rectenna design of any frequency.
Active Learning with Statistical Models.
1995-01-01
Active Learning with Statistical Models ASC-9217041, NSF CDA-9309300 6. AUTHOR(S) David A. Cohn, Zoubin Ghahramani, and Michael I. Jordan 7. PERFORMING...TERMS 15. NUMBER OF PAGES Al, MIT, Artificial Intelligence, active learning , queries, locally weighted 6 regression, LOESS, mixtures of gaussians...COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES A.I. Memo No. 1522 January 9. 1995 C.B.C.L. Paper No. 110 Active Learning with
A statistical model for instable thermodynamical systems
International Nuclear Information System (INIS)
Sommer, Jens-Uwe
2003-01-01
A generic model is presented for statistical systems which display thermodynamic features in contrast to our everyday experience, such as infinite and negative heat capacities. Such system are instable in terms of classical equilibrium thermodynamics. Using our statistical model, we are able to investigate states of instable systems which are undefined in the framework of equilibrium thermodynamics. We show that a region of negative heat capacity in the adiabatic environment, leads to a first order like phase transition when the system is coupled to a heat reservoir. This phase transition takes place without a phase coexistence. Nevertheless, all intermediate states are stable due to fluctuations. When two instable system are brought in thermal contact, the temperature of the composed system is lower than the minimum temperature of the individual systems. Generally, the equilibrium states of instable system cannot be simply decomposed into equilibrium states of the individual systems. The properties of instable system depend on the environment, ensemble equivalence is broken
Thermal and statistical properties of nuclei and nuclear systems
International Nuclear Information System (INIS)
Moretto, L.G.; Wozniak, G.J.
1989-07-01
The term statistical decay, statistical or thermodynamic equilibrium, thermalization, temperature, etc., have been used in nuclear physics since the introduction of the compound nucleus (CN) concept, and they are still used, perhaps even more frequently, in the context of intermediate- and high-energy heavy-ion reactions. Unfortunately, the increased popularity of these terms has not made them any clearer, and more often than not one encounters sweeping statements about the alleged statisticity of a nuclear process where the ''statistical'' connotation is a more apt description of the state of the speaker's mind than of the nuclear reaction. It is our goal, in this short set of lectures, to set at least some ideas straight on this broad and beautiful subject, on the one hand by clarifying some fundamental concepts, on the other by presenting some interesting applications to actual physical cases. 74 refs., 38 figs
Statistical modeling of geopressured geothermal reservoirs
Ansari, Esmail; Hughes, Richard; White, Christopher D.
2017-06-01
Identifying attractive candidate reservoirs for producing geothermal energy requires predictive models. In this work, inspectional analysis and statistical modeling are used to create simple predictive models for a line drive design. Inspectional analysis on the partial differential equations governing this design yields a minimum number of fifteen dimensionless groups required to describe the physics of the system. These dimensionless groups are explained and confirmed using models with similar dimensionless groups but different dimensional parameters. This study models dimensionless production temperature and thermal recovery factor as the responses of a numerical model. These responses are obtained by a Box-Behnken experimental design. An uncertainty plot is used to segment the dimensionless time and develop a model for each segment. The important dimensionless numbers for each segment of the dimensionless time are identified using the Boosting method. These selected numbers are used in the regression models. The developed models are reduced to have a minimum number of predictors and interactions. The reduced final models are then presented and assessed using testing runs. Finally, applications of these models are offered. The presented workflow is generic and can be used to translate the output of a numerical simulator into simple predictive models in other research areas involving numerical simulation.
GIGMF - A statistical model program
International Nuclear Information System (INIS)
Vladuca, G.; Deberth, C.
1978-01-01
The program GIGMF computes the differential and integrated statistical model cross sections for the reactions proceeding through a compound nuclear stage. The computational method is based on the Hauser-Feshbach-Wolfenstein theory, modified to include the modern version of Tepel et al. Although the program was written for a PDP-15 computer, with 16K high speed memory, many reaction channels can be taken into account with the following restrictions: the pro ectile spin must be less than 2, the maximum spin momenta of the compound nucleus can not be greater than 10. These restrictions are due solely to the storage allotments and may be easily relaxed. The energy of the impinging particle, the target and projectile masses, the spin and paritjes of the projectile, target, emergent and residual nuclei the maximum orbital momentum and transmission coefficients for each reaction channel are the input parameters of the program. (author)
Statistical approach to thermal evolution of neutron stars
International Nuclear Information System (INIS)
Beznogov, M V; Yakovlev, D G
2015-01-01
Studying thermal evolution of neutron stars (NSs) is one of a few ways to investigate the properties of superdense matter in their cores. We study the cooling of isolated NSs (INSs) and deep crustal heating of transiently accreting NSs in X-ray transients (XRTs, binary systems with low-mass companions). Currently, nearly 50 of such NSs are observed, and one can apply statistical methods to analyze the whole dataset. We propose a method for such analysis based on thermal evolution theory for individual stars and on averaging the results over NS mass distributions. We calculate the distributions of INSs and accreting NSs (ANSs) in XRTs over cooling and heating diagrams respectively. Comparing theoretical and observational distributions one can infer information on physical properties of superdense matter and on mass distributions of INSs and ANSs. (paper)
Thermal equilibrium and statistical thermometers in special relativity.
Cubero, David; Casado-Pascual, Jesús; Dunkel, Jörn; Talkner, Peter; Hänggi, Peter
2007-10-26
There is an intense debate in the recent literature about the correct generalization of Maxwell's velocity distribution in special relativity. The most frequently discussed candidate distributions include the Jüttner function as well as modifications thereof. Here we report results from fully relativistic one-dimensional molecular dynamics simulations that resolve the ambiguity. The numerical evidence unequivocally favors the Jüttner distribution. Moreover, our simulations illustrate that the concept of "thermal equilibrium" extends naturally to special relativity only if a many-particle system is spatially confined. They make evident that "temperature" can be statistically defined and measured in an observer frame independent way.
Thermal activation in statistical clusters of magnetic nanoparticles
International Nuclear Information System (INIS)
Hovorka, O
2017-01-01
This article presents a kinetic Monte-Carlo study of thermally activated magnetisation dynamics in clusters of statistically distributed magnetic nanoparticles. The structure of clusters is assumed to be of fractal nature, consistently with recent observations of magnetic particle aggregation in cellular environments. The computed magnetisation relaxation decay and frequency-dependent hysteresis loops are seen to significantly depend on the fractal dimension of aggregates, leading to accelerated magnetisation relaxation and reduction in the size of hysteresis loops as the fractal dimension increases from one-dimensional-like to three-dimensional-like clusters. Discussed are implications for applications in nanomedicine, such as magnetic hyperthermia or magnetic particle imaging. (paper)
A study on the advanced statistical core thermal design methodology
International Nuclear Information System (INIS)
Lee, Seung Hyuk
1992-02-01
A statistical core thermal design methodology for generating the limit DNBR and the nominal DNBR is proposed and used in assessing the best-estimate thermal margin in a reactor core. Firstly, the Latin Hypercube Sampling Method instead of the conventional Experimental Design Technique is utilized as an input sampling method for a regression analysis to evaluate its sampling efficiency. Secondly and as a main topic, the Modified Latin Hypercube Sampling and the Hypothesis Test Statistics method is proposed as a substitute for the current statistical core thermal design method. This new methodology adopts 'a Modified Latin Hypercube Sampling Method' which uses the mean values of each interval of input variables instead of random values to avoid the extreme cases that arise in the tail areas of some parameters. Next, the independence between the input variables is verified through 'Correlation Coefficient Test' for statistical treatment of their uncertainties. And the distribution type of DNBR response is determined though 'Goodness of Fit Test'. Finally, the limit DNBR with one-sided 95% probability and 95% confidence level, DNBR 95/95 ' is estimated. The advantage of this methodology over the conventional statistical method using Response Surface and Monte Carlo simulation technique lies in its simplicity of the analysis procedure, while maintaining the same level of confidence in the limit DNBR result. This methodology is applied to the two cases of DNBR margin calculation. The first case is the application to the determination of the limit DNBR where the DNBR margin is determined by the difference between the nominal DNBR and the limit DNBR. The second case is the application to the determination of the nominal DNBR where the DNBR margin is determined by the difference between the lower limit value of the nominal DNBR and the CHF correlation limit being used. From this study, it is deduced that the proposed methodology gives a good agreement in the DNBR results
Statistical modeling of Earth's plasmasphere
Veibell, Victoir
The behavior of plasma near Earth's geosynchronous orbit is of vital importance to both satellite operators and magnetosphere modelers because it also has a significant influence on energy transport, ion composition, and induced currents. The system is highly complex in both time and space, making the forecasting of extreme space weather events difficult. This dissertation examines the behavior and statistical properties of plasma mass density near geosynchronous orbit by using both linear and nonlinear models, as well as epoch analyses, in an attempt to better understand the physical processes that precipitates and drives its variations. It is shown that while equatorial mass density does vary significantly on an hourly timescale when a drop in the disturbance time scale index ( Dst) was observed, it does not vary significantly between the day of a Dst event onset and the day immediately following. It is also shown that increases in equatorial mass density were not, on average, preceded or followed by any significant change in the examined solar wind or geomagnetic variables, including Dst, despite prior results that considered a few selected events and found a notable influence. It is verified that equatorial mass density and and solar activity via the F10.7 index have a strong correlation, which is stronger over longer timescales such as 27 days than it is over an hourly timescale. It is then shown that this connection seems to affect the behavior of equatorial mass density most during periods of strong solar activity leading to large mass density reactions to Dst drops for high values of F10.7. It is also shown that equatorial mass density behaves differently before and after events based on the value of F10.7 at the onset of an equatorial mass density event or a Dst event, and that a southward interplanetary magnetic field at onset leads to slowed mass density growth after event onset. These behavioral differences provide insight into how solar and geomagnetic
Probing NWP model deficiencies by statistical postprocessing
DEFF Research Database (Denmark)
Rosgaard, Martin Haubjerg; Nielsen, Henrik Aalborg; Nielsen, Torben S.
2016-01-01
The objective in this article is twofold. On one hand, a Model Output Statistics (MOS) framework for improved wind speed forecast accuracy is described and evaluated. On the other hand, the approach explored identifies unintuitive explanatory value from a diagnostic variable in an operational....... Based on the statistical model candidates inferred from the data, the lifted index NWP model diagnostic is consistently found among the NWP model predictors of the best performing statistical models across sites....
The effective thermal conductivity of porous media based on statistical self-similarity
International Nuclear Information System (INIS)
Kou Jianlong; Wu Fengmin; Lu Hangjun; Xu Yousheng; Song Fuquan
2009-01-01
A fractal model is presented based on the thermal-electrical analogy technique and statistical self-similarity of fractal saturated porous media. A dimensionless effective thermal conductivity of saturated fractal porous media is studied by the relationship between the dimensionless effective thermal conductivity and the geometrical parameters of porous media with no empirical constant. Through this study, it is shown that the dimensionless effective thermal conductivity decreases with the increase of porosity (φ) and pore area fractal dimension (D f ) when k s /k g >1. The opposite trends is observed when k s /k g t ). The model predictions are compared with existing experimental data and the results show that they are in good agreement with existing experimental data.
Statistical Modelling of the Soil Dielectric Constant
Usowicz, Boguslaw; Marczewski, Wojciech; Bogdan Usowicz, Jerzy; Lipiec, Jerzy
2010-05-01
The dielectric constant of soil is the physical property being very sensitive on water content. It funds several electrical measurement techniques for determining the water content by means of direct (TDR, FDR, and others related to effects of electrical conductance and/or capacitance) and indirect RS (Remote Sensing) methods. The work is devoted to a particular statistical manner of modelling the dielectric constant as the property accounting a wide range of specific soil composition, porosity, and mass density, within the unsaturated water content. Usually, similar models are determined for few particular soil types, and changing the soil type one needs switching the model on another type or to adjust it by parametrization of soil compounds. Therefore, it is difficult comparing and referring results between models. The presented model was developed for a generic representation of soil being a hypothetical mixture of spheres, each representing a soil fraction, in its proper phase state. The model generates a serial-parallel mesh of conductive and capacitive paths, which is analysed for a total conductive or capacitive property. The model was firstly developed to determine the thermal conductivity property, and now it is extended on the dielectric constant by analysing the capacitive mesh. The analysis is provided by statistical means obeying physical laws related to the serial-parallel branching of the representative electrical mesh. Physical relevance of the analysis is established electrically, but the definition of the electrical mesh is controlled statistically by parametrization of compound fractions, by determining the number of representative spheres per unitary volume per fraction, and by determining the number of fractions. That way the model is capable covering properties of nearly all possible soil types, all phase states within recognition of the Lorenz and Knudsen conditions. In effect the model allows on generating a hypothetical representative of
Statistical modelling of fish stocks
DEFF Research Database (Denmark)
Kvist, Trine
1999-01-01
for modelling the dynamics of a fish population is suggested. A new approach is introduced to analyse the sources of variation in age composition data, which is one of the most important sources of information in the cohort based models for estimation of stock abundancies and mortalities. The approach combines...... and it is argued that an approach utilising stochastic differential equations might be advantagous in fish stoch assessments....
Statistical lung model for microdosimetry
International Nuclear Information System (INIS)
Fisher, D.R.; Hadley, R.T.
1984-03-01
To calculate the microdosimetry of plutonium in the lung, a mathematical description is needed of lung tissue microstructure that defines source-site parameters. Beagle lungs were expanded using a glutaraldehyde fixative at 30 cm water pressure. Tissue specimens, five microns thick, were stained with hematoxylin and eosin then studied using an image analyzer. Measurements were made along horizontal lines through the magnified tissue image. The distribution of air space and tissue chord lengths and locations of epithelial cell nuclei were recorded from about 10,000 line scans. The distribution parameters constituted a model of lung microstructure for predicting the paths of random alpha particle tracks in the lung and the probability of traversing biologically sensitive sites. This lung model may be used in conjunction with established deposition and retention models for determining the microdosimetry in the pulmonary lung for a wide variety of inhaled radioactive materials
A statistical mechanical model for equilibrium ionization
International Nuclear Information System (INIS)
Macris, N.; Martin, P.A.; Pule, J.
1990-01-01
A quantum electron interacts with a classical gas of hard spheres and is in thermal equilibrium with it. The interaction is attractive and the electron can form a bound state with the classical particles. It is rigorously shown that in a well defined low density and low temperature limit, the ionization probability for the electron tends to the value predicted by the Saha formula for thermal ionization. In this regime, the electron is found to be in a statistical mixture of a bound and a free state. (orig.)
Statistical modelling for ship propulsion efficiency
DEFF Research Database (Denmark)
Petersen, Jóan Petur; Jacobsen, Daniel J.; Winther, Ole
2012-01-01
This paper presents a state-of-the-art systems approach to statistical modelling of fuel efficiency in ship propulsion, and also a novel and publicly available data set of high quality sensory data. Two statistical model approaches are investigated and compared: artificial neural networks...
Actuarial statistics with generalized linear mixed models
Antonio, K.; Beirlant, J.
2007-01-01
Over the last decade the use of generalized linear models (GLMs) in actuarial statistics has received a lot of attention, starting from the actuarial illustrations in the standard text by McCullagh and Nelder [McCullagh, P., Nelder, J.A., 1989. Generalized linear models. In: Monographs on Statistics
Spherical Process Models for Global Spatial Statistics
Jeong, Jaehong; Jun, Mikyoung; Genton, Marc G.
2017-01-01
Statistical models used in geophysical, environmental, and climate science applications must reflect the curvature of the spatial domain in global data. Over the past few decades, statisticians have developed covariance models that capture
Statistical Models and Methods for Lifetime Data
Lawless, Jerald F
2011-01-01
Praise for the First Edition"An indispensable addition to any serious collection on lifetime data analysis and . . . a valuable contribution to the statistical literature. Highly recommended . . ."-Choice"This is an important book, which will appeal to statisticians working on survival analysis problems."-Biometrics"A thorough, unified treatment of statistical models and methods used in the analysis of lifetime data . . . this is a highly competent and agreeable statistical textbook."-Statistics in MedicineThe statistical analysis of lifetime or response time data is a key tool in engineering,
Statistics and the shell model
International Nuclear Information System (INIS)
Weidenmueller, H.A.
1985-01-01
Starting with N. Bohr's paper on compound-nucleus reactions, we confront regular dynamical features and chaotic motion in nuclei. The shell-model and, more generally, mean-field theories describe average nuclear properties which are thus identified as regular features. The fluctuations about the average show chaotic behaviour of the same type as found in classical chaotic systems upon quantisation. These features are therefore generic and quite independent of the specific dynamics of the nucleus. A novel method to calculate fluctuations is discussed, and the results of this method are described. (orig.)
Modeling of Thermal Barrier Coatings
Ferguson, B. L.; Petrus, G. J.; Krauss, T. M.
1992-01-01
The project examined the effectiveness of studying the creep behavior of thermal barrier coating system through the use of a general purpose, large strain finite element program, NIKE2D. Constitutive models implemented in this code were applied to simulate thermal-elastic and creep behavior. Four separate ceramic-bond coat interface geometries were examined in combination with a variety of constitutive models and material properties. The reason for focusing attention on the ceramic-bond coat interface is that prior studies have shown that cracking occurs in the ceramic near interface features which act as stress concentration points. The model conditions examined include: (1) two bond coat coefficient of thermal expansion curves; (2) the creep coefficient and creep exponent of the bond coat for steady state creep; (3) the interface geometry; and (4) the material model employed to represent the bond coat, ceramic, and superalloy base.
Lumped Thermal Household Model
DEFF Research Database (Denmark)
Biegel, Benjamin; Andersen, Palle; Stoustrup, Jakob
2013-01-01
pump portfolio. Following, we illustrate two disadvantages of individual models, namely that it requires much computational effort to optimize over a large portfolio, and second that it is difficult to accurately model the houses in certain time periods due to local disturbances. Finally, we propose...
Bayesian models: A statistical primer for ecologists
Hobbs, N. Thompson; Hooten, Mevin B.
2015-01-01
Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods—in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach.Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. This unique book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals.This primer enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management.Presents the mathematical and statistical foundations of Bayesian modeling in language accessible to non-statisticiansCovers basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and moreDeemphasizes computer coding in favor of basic principlesExplains how to write out properly factored statistical expressions representing Bayesian models
Statistical Model-Based Face Pose Estimation
Institute of Scientific and Technical Information of China (English)
GE Xinliang; YANG Jie; LI Feng; WANG Huahua
2007-01-01
A robust face pose estimation approach is proposed by using face shape statistical model approach and pose parameters are represented by trigonometric functions. The face shape statistical model is firstly built by analyzing the face shapes from different people under varying poses. The shape alignment is vital in the process of building the statistical model. Then, six trigonometric functions are employed to represent the face pose parameters. Lastly, the mapping function is constructed between face image and face pose by linearly relating different parameters. The proposed approach is able to estimate different face poses using a few face training samples. Experimental results are provided to demonstrate its efficiency and accuracy.
Uncertainty the soul of modeling, probability & statistics
Briggs, William
2016-01-01
This book presents a philosophical approach to probability and probabilistic thinking, considering the underpinnings of probabilistic reasoning and modeling, which effectively underlie everything in data science. The ultimate goal is to call into question many standard tenets and lay the philosophical and probabilistic groundwork and infrastructure for statistical modeling. It is the first book devoted to the philosophy of data aimed at working scientists and calls for a new consideration in the practice of probability and statistics to eliminate what has been referred to as the "Cult of Statistical Significance". The book explains the philosophy of these ideas and not the mathematics, though there are a handful of mathematical examples. The topics are logically laid out, starting with basic philosophy as related to probability, statistics, and science, and stepping through the key probabilistic ideas and concepts, and ending with statistical models. Its jargon-free approach asserts that standard methods, suc...
Automated statistical modeling of analytical measurement systems
International Nuclear Information System (INIS)
Jacobson, J.J.
1992-01-01
The statistical modeling of analytical measurement systems at the Idaho Chemical Processing Plant (ICPP) has been completely automated through computer software. The statistical modeling of analytical measurement systems is one part of a complete quality control program used by the Remote Analytical Laboratory (RAL) at the ICPP. The quality control program is an integration of automated data input, measurement system calibration, database management, and statistical process control. The quality control program and statistical modeling program meet the guidelines set forth by the American Society for Testing Materials and American National Standards Institute. A statistical model is a set of mathematical equations describing any systematic bias inherent in a measurement system and the precision of a measurement system. A statistical model is developed from data generated from the analysis of control standards. Control standards are samples which are made up at precise known levels by an independent laboratory and submitted to the RAL. The RAL analysts who process control standards do not know the values of those control standards. The object behind statistical modeling is to describe real process samples in terms of their bias and precision and, to verify that a measurement system is operating satisfactorily. The processing of control standards gives us this ability
Topology for statistical modeling of petascale data.
Energy Technology Data Exchange (ETDEWEB)
Pascucci, Valerio (University of Utah, Salt Lake City, UT); Mascarenhas, Ajith Arthur; Rusek, Korben (Texas A& M University, College Station, TX); Bennett, Janine Camille; Levine, Joshua (University of Utah, Salt Lake City, UT); Pebay, Philippe Pierre; Gyulassy, Attila (University of Utah, Salt Lake City, UT); Thompson, David C.; Rojas, Joseph Maurice (Texas A& M University, College Station, TX)
2011-07-01
This document presents current technical progress and dissemination of results for the Mathematics for Analysis of Petascale Data (MAPD) project titled 'Topology for Statistical Modeling of Petascale Data', funded by the Office of Science Advanced Scientific Computing Research (ASCR) Applied Math program. Many commonly used algorithms for mathematical analysis do not scale well enough to accommodate the size or complexity of petascale data produced by computational simulations. The primary goal of this project is thus to develop new mathematical tools that address both the petascale size and uncertain nature of current data. At a high level, our approach is based on the complementary techniques of combinatorial topology and statistical modeling. In particular, we use combinatorial topology to filter out spurious data that would otherwise skew statistical modeling techniques, and we employ advanced algorithms from algebraic statistics to efficiently find globally optimal fits to statistical models. This document summarizes the technical advances we have made to date that were made possible in whole or in part by MAPD funding. These technical contributions can be divided loosely into three categories: (1) advances in the field of combinatorial topology, (2) advances in statistical modeling, and (3) new integrated topological and statistical methods.
Statistical modelling of citation exchange between statistics journals.
Varin, Cristiano; Cattelan, Manuela; Firth, David
2016-01-01
Rankings of scholarly journals based on citation data are often met with scepticism by the scientific community. Part of the scepticism is due to disparity between the common perception of journals' prestige and their ranking based on citation counts. A more serious concern is the inappropriate use of journal rankings to evaluate the scientific influence of researchers. The paper focuses on analysis of the table of cross-citations among a selection of statistics journals. Data are collected from the Web of Science database published by Thomson Reuters. Our results suggest that modelling the exchange of citations between journals is useful to highlight the most prestigious journals, but also that journal citation data are characterized by considerable heterogeneity, which needs to be properly summarized. Inferential conclusions require care to avoid potential overinterpretation of insignificant differences between journal ratings. Comparison with published ratings of institutions from the UK's research assessment exercise shows strong correlation at aggregate level between assessed research quality and journal citation 'export scores' within the discipline of statistics.
Daily precipitation statistics in regional climate models
DEFF Research Database (Denmark)
Frei, Christoph; Christensen, Jens Hesselbjerg; Déqué, Michel
2003-01-01
An evaluation is undertaken of the statistics of daily precipitation as simulated by five regional climate models using comprehensive observations in the region of the European Alps. Four limited area models and one variable-resolution global model are considered, all with a grid spacing of 50 km...
Infinite Random Graphs as Statistical Mechanical Models
DEFF Research Database (Denmark)
Durhuus, Bergfinnur Jøgvan; Napolitano, George Maria
2011-01-01
We discuss two examples of infinite random graphs obtained as limits of finite statistical mechanical systems: a model of two-dimensional dis-cretized quantum gravity defined in terms of causal triangulated surfaces, and the Ising model on generic random trees. For the former model we describe a ...
Matrix Tricks for Linear Statistical Models
Puntanen, Simo; Styan, George PH
2011-01-01
In teaching linear statistical models to first-year graduate students or to final-year undergraduate students there is no way to proceed smoothly without matrices and related concepts of linear algebra; their use is really essential. Our experience is that making some particular matrix tricks very familiar to students can substantially increase their insight into linear statistical models (and also multivariate statistical analysis). In matrix algebra, there are handy, sometimes even very simple "tricks" which simplify and clarify the treatment of a problem - both for the student and
International Nuclear Information System (INIS)
Barbeito, Inés; Zaragoza, Sonia; Tarrío-Saavedra, Javier; Naya, Salvador
2017-01-01
Highlights: • Intelligent web platform development for energy efficiency management in buildings. • Controlling and supervising thermal comfort and energy consumption in buildings. • Statistical quality control procedure to deal with autocorrelated data. • Open source alternative using R software. - Abstract: In this paper, a case study of performing a reliable statistical procedure to evaluate the quality of HVAC systems in buildings using data retrieved from an ad hoc big data web energy platform is presented. The proposed methodology based on statistical quality control (SQC) is used to analyze the real state of thermal comfort and energy efficiency of the offices of the company FRIDAMA (Spain) in a reliable way. Non-conformities or alarms, and the actual assignable causes of these out of control states are detected. The capability to meet specification requirements is also analyzed. Tools and packages implemented in the open-source R software are employed to apply the different procedures. First, this study proposes to fit ARIMA time series models to CTQ variables. Then, the application of Shewhart and EWMA control charts to the time series residuals is proposed to control and monitor thermal comfort and energy consumption in buildings. Once thermal comfort and consumption variability are estimated, the implementation of capability indexes for autocorrelated variables is proposed to calculate the degree to which standards specifications are met. According with case study results, the proposed methodology has detected real anomalies in HVAC installation, helping to detect assignable causes and to make appropriate decisions. One of the goals is to perform and describe step by step this statistical procedure in order to be replicated by practitioners in a better way.
Statistical physics of pairwise probability models
DEFF Research Database (Denmark)
Roudi, Yasser; Aurell, Erik; Hertz, John
2009-01-01
(dansk abstrakt findes ikke) 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...
Distributions with given marginals and statistical modelling
Fortiana, Josep; Rodriguez-Lallena, José
2002-01-01
This book contains a selection of the papers presented at the meeting `Distributions with given marginals and statistical modelling', held in Barcelona (Spain), July 17-20, 2000. In 24 chapters, this book covers topics such as the theory of copulas and quasi-copulas, the theory and compatibility of distributions, models for survival distributions and other well-known distributions, time series, categorical models, definition and estimation of measures of dependence, monotonicity and stochastic ordering, shape and separability of distributions, hidden truncation models, diagonal families, orthogonal expansions, tests of independence, and goodness of fit assessment. These topics share the use and properties of distributions with given marginals, this being the fourth specialised text on this theme. The innovative aspect of the book is the inclusion of statistical aspects such as modelling, Bayesian statistics, estimation, and tests.
Aspects of statistical model for multifragmentation
International Nuclear Information System (INIS)
Bhattacharyya, P.; Das Gupta, S.; Mekjian, A. Z.
1999-01-01
We deal with two different aspects of an exactly soluble statistical model of fragmentation. First we show, using zero range force and finite temperature Thomas-Fermi theory, that a common link can be found between finite temperature mean field theory and the statistical fragmentation model. We show the latter naturally arises in the spinodal region. Next we show that although the exact statistical model is a canonical model and uses temperature, microcanonical results which use constant energy rather than constant temperature can also be obtained from the canonical model using saddle-point approximation. The methodology is extremely simple to implement and at least in all the examples studied in this work is very accurate. (c) 1999 The American Physical Society
Energy Technology Data Exchange (ETDEWEB)
Band, D.L.
1986-12-01
The infrared, optical and x-ray continua from radio quiet active galactic nuclei (AGN) are explained by a compact non-thermal source surrounding a thermal ultraviolet emitter, presumably the accretion disk around a supermassive black hole. The ultraviolet source is observed as the ''big blue bump.'' The flat (..cap alpha.. approx. = .7) hard x-ray spectrum results from the scattering of thermal ultraviolet photons by the flat, low energy end of an electron distribution ''broken'' by Compton losses; the infrared through soft x-ray continuum is the synchrotron radiation of the steep, high energy end of the electron distribution. Quantitative fits to specific AGN result in models which satisfy the variability constraints but require electron (re)acceleration throughout the source. 11 refs., 1 fig.
Statistical Compression for Climate Model Output
Hammerling, D.; Guinness, J.; Soh, Y. J.
2017-12-01
Numerical climate model simulations run at high spatial and temporal resolutions generate massive quantities of data. As our computing capabilities continue to increase, storing all of the data is not sustainable, and thus is it important to develop methods for representing the full datasets by smaller compressed versions. We propose a statistical compression and decompression algorithm based on storing a set of summary statistics as well as a statistical model describing the conditional distribution of the full dataset given the summary statistics. We decompress the data by computing conditional expectations and conditional simulations from the model given the summary statistics. Conditional expectations represent our best estimate of the original data but are subject to oversmoothing in space and time. Conditional simulations introduce realistic small-scale noise so that the decompressed fields are neither too smooth nor too rough compared with the original data. Considerable attention is paid to accurately modeling the original dataset-one year of daily mean temperature data-particularly with regard to the inherent spatial nonstationarity in global fields, and to determining the statistics to be stored, so that the variation in the original data can be closely captured, while allowing for fast decompression and conditional emulation on modest computers.
Statistical analysis of thermal conductivity of nanofluid containing ...
Indian Academy of Sciences (India)
Administrator
four temperatures for thermal conductivity of pristine. MWCNTs ... MWCNTs. In other words, the augmentation of the ... TiO2 nanofluid, means with different letters are significantly different .... Chen L and Xie H 2010 Thermochim Acta 497 67.
Performance modeling, loss networks, and statistical multiplexing
Mazumdar, Ravi
2009-01-01
This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of understanding the phenomenon of statistical multiplexing. The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the important ideas of Palm distributions associated with traffic models and their role in performance measures. Also presented are recent ideas of large buffer, and many sources asymptotics that play an important role in understanding statistical multiplexing. I
Simple statistical model for branched aggregates
DEFF Research Database (Denmark)
Lemarchand, Claire; Hansen, Jesper Schmidt
2015-01-01
, given that it already has bonds with others. The model is applied here to asphaltene nanoaggregates observed in molecular dynamics simulations of Cooee bitumen. The variation with temperature of the probabilities deduced from this model is discussed in terms of statistical mechanics arguments....... The relevance of the statistical model in the case of asphaltene nanoaggregates is checked by comparing the predicted value of the probability for one molecule to have exactly i bonds with the same probability directly measured in the molecular dynamics simulations. The agreement is satisfactory......We propose a statistical model that can reproduce the size distribution of any branched aggregate, including amylopectin, dendrimers, molecular clusters of monoalcohols, and asphaltene nanoaggregates. It is based on the conditional probability for one molecule to form a new bond with a molecule...
Advances in statistical models for data analysis
Minerva, Tommaso; Vichi, Maurizio
2015-01-01
This edited volume focuses on recent research results in classification, multivariate statistics and machine learning and highlights advances in statistical models for data analysis. The volume provides both methodological developments and contributions to a wide range of application areas such as economics, marketing, education, social sciences and environment. The papers in this volume were first presented at the 9th biannual meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in September 2013 at the University of Modena and Reggio Emilia, Italy.
Structured statistical models of inductive reasoning.
Kemp, Charles; Tenenbaum, Joshua B
2009-01-01
Everyday inductive inferences are often guided by rich background knowledge. Formal models of induction should aim to incorporate this knowledge and should explain how different kinds of knowledge lead to the distinctive patterns of reasoning found in different inductive contexts. This article presents a Bayesian framework that attempts to meet both goals and describes [corrected] 4 applications of the framework: a taxonomic model, a spatial model, a threshold model, and a causal model. Each model makes probabilistic inferences about the extensions of novel properties, but the priors for the 4 models are defined over different kinds of structures that capture different relationships between the categories in a domain. The framework therefore shows how statistical inference can operate over structured background knowledge, and the authors argue that this interaction between structure and statistics is critical for explaining the power and flexibility of human reasoning.
Model for neural signaling leap statistics
International Nuclear Information System (INIS)
Chevrollier, Martine; Oria, Marcos
2011-01-01
We present a simple model for neural signaling leaps in the brain considering only the thermodynamic (Nernst) potential in neuron cells and brain temperature. We numerically simulated connections between arbitrarily localized neurons and analyzed the frequency distribution of the distances reached. We observed qualitative change between Normal statistics (with T 37.5 0 C, awaken regime) and Levy statistics (T = 35.5 0 C, sleeping period), characterized by rare events of long range connections.
Statistical models based on conditional probability distributions
International Nuclear Information System (INIS)
Narayanan, R.S.
1991-10-01
We present a formulation of statistical mechanics models based on conditional probability distribution rather than a Hamiltonian. We show that it is possible to realize critical phenomena through this procedure. Closely linked with this formulation is a Monte Carlo algorithm, in which a configuration generated is guaranteed to be statistically independent from any other configuration for all values of the parameters, in particular near the critical point. (orig.)
Model for neural signaling leap statistics
Chevrollier, Martine; Oriá, Marcos
2011-03-01
We present a simple model for neural signaling leaps in the brain considering only the thermodynamic (Nernst) potential in neuron cells and brain temperature. We numerically simulated connections between arbitrarily localized neurons and analyzed the frequency distribution of the distances reached. We observed qualitative change between Normal statistics (with T = 37.5°C, awaken regime) and Lévy statistics (T = 35.5°C, sleeping period), characterized by rare events of long range connections.
Model for neural signaling leap statistics
Energy Technology Data Exchange (ETDEWEB)
Chevrollier, Martine; Oria, Marcos, E-mail: oria@otica.ufpb.br [Laboratorio de Fisica Atomica e Lasers Departamento de Fisica, Universidade Federal da ParaIba Caixa Postal 5086 58051-900 Joao Pessoa, Paraiba (Brazil)
2011-03-01
We present a simple model for neural signaling leaps in the brain considering only the thermodynamic (Nernst) potential in neuron cells and brain temperature. We numerically simulated connections between arbitrarily localized neurons and analyzed the frequency distribution of the distances reached. We observed qualitative change between Normal statistics (with T 37.5{sup 0}C, awaken regime) and Levy statistics (T = 35.5{sup 0}C, sleeping period), characterized by rare events of long range connections.
Growth curve models and statistical diagnostics
Pan, Jian-Xin
2002-01-01
Growth-curve models are generalized multivariate analysis-of-variance models. These models are especially useful for investigating growth problems on short times in economics, biology, medical research, and epidemiology. This book systematically introduces the theory of the GCM with particular emphasis on their multivariate statistical diagnostics, which are based mainly on recent developments made by the authors and their collaborators. The authors provide complete proofs of theorems as well as practical data sets and MATLAB code.
Topology for Statistical Modeling of Petascale Data
Energy Technology Data Exchange (ETDEWEB)
Pascucci, Valerio [Univ. of Utah, Salt Lake City, UT (United States); Levine, Joshua [Univ. of Utah, Salt Lake City, UT (United States); Gyulassy, Attila [Univ. of Utah, Salt Lake City, UT (United States); Bremer, P. -T. [Univ. of Utah, Salt Lake City, UT (United States)
2013-10-31
Many commonly used algorithms for mathematical analysis do not scale well enough to accommodate the size or complexity of petascale data produced by computational simulations. The primary goal of this project is to develop new mathematical tools that address both the petascale size and uncertain nature of current data. At a high level, the approach of the entire team involving all three institutions is based on the complementary techniques of combinatorial topology and statistical modelling. In particular, we use combinatorial topology to filter out spurious data that would otherwise skew statistical modelling techniques, and we employ advanced algorithms from algebraic statistics to efficiently find globally optimal fits to statistical models. The overall technical contributions can be divided loosely into three categories: (1) advances in the field of combinatorial topology, (2) advances in statistical modelling, and (3) new integrated topological and statistical methods. Roughly speaking, the division of labor between our 3 groups (Sandia Labs in Livermore, Texas A&M in College Station, and U Utah in Salt Lake City) is as follows: the Sandia group focuses on statistical methods and their formulation in algebraic terms, and finds the application problems (and data sets) most relevant to this project, the Texas A&M Group develops new algebraic geometry algorithms, in particular with fewnomial theory, and the Utah group develops new algorithms in computational topology via Discrete Morse Theory. However, we hasten to point out that our three groups stay in tight contact via videconference every 2 weeks, so there is much synergy of ideas between the groups. The following of this document is focused on the contributions that had grater direct involvement from the team at the University of Utah in Salt Lake City.
Bayesian models a statistical primer for ecologists
Hobbs, N Thompson
2015-01-01
Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods-in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach. Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probabili
Thermal modelling using discrete vasculature for thermal therapy: a review
Kok, H.P.; Gellermann, J.; van den Berg, C.A.T.; Stauffer, P.R.; Hand, J.W.; Crezee, J.
2013-01-01
Reliable temperature information during clinical hyperthermia and thermal ablation is essential for adequate treatment control, but conventional temperature measurements do not provide 3D temperature information. Treatment planning is a very useful tool to improve treatment quality and substantial progress has been made over the last decade. Thermal modelling is a very important and challenging aspect of hyperthermia treatment planning. Various thermal models have been developed for this purpose, with varying complexity. Since blood perfusion is such an important factor in thermal redistribution of energy in in vivo tissue, thermal simulations are most accurately performed by modelling discrete vasculature. This review describes the progress in thermal modelling with discrete vasculature for the purpose of hyperthermia treatment planning and thermal ablation. There has been significant progress in thermal modelling with discrete vasculature. Recent developments have made real-time simulations possible, which can provide feedback during treatment for improved therapy. Future clinical application of thermal modelling with discrete vasculature in hyperthermia treatment planning is expected to further improve treatment quality. PMID:23738700
Statistical transmutation in doped quantum dimer models.
Lamas, C A; Ralko, A; Cabra, D C; Poilblanc, D; Pujol, P
2012-07-06
We prove a "statistical transmutation" symmetry of doped quantum dimer models on the square, triangular, and kagome lattices: the energy spectrum is invariant under a simultaneous change of statistics (i.e., bosonic into fermionic or vice versa) of the holes and of the signs of all the dimer resonance loops. This exact transformation enables us to define the duality equivalence between doped quantum dimer Hamiltonians and provides the analytic framework to analyze dynamical statistical transmutations. We investigate numerically the doping of the triangular quantum dimer model with special focus on the topological Z(2) dimer liquid. Doping leads to four (instead of two for the square lattice) inequivalent families of Hamiltonians. Competition between phase separation, superfluidity, supersolidity, and fermionic phases is investigated in the four families.
STATISTICAL MODELS OF REPRESENTING INTELLECTUAL CAPITAL
Directory of Open Access Journals (Sweden)
Andreea Feraru
2016-06-01
Full Text Available This article entitled Statistical Models of Representing Intellectual Capital approaches and analyses the concept of intellectual capital, as well as the main models which can support enterprisers/managers in evaluating and quantifying the advantages of intellectual capital. Most authors examine intellectual capital from a static perspective and focus on the development of its various evaluation models. In this chapter we surveyed the classical static models: Sveiby, Edvisson, Balanced Scorecard, as well as the canonical model of intellectual capital. Among the group of static models for evaluating organisational intellectual capital the canonical model stands out. This model enables the structuring of organisational intellectual capital in: human capital, structural capital and relational capital. Although the model is widely spread, it is a static one and can thus create a series of errors in the process of evaluation, because all the three entities mentioned above are not independent from the viewpoint of their contents, as any logic of structuring complex entities requires.
Statistical Validation of Engineering and Scientific Models: Background
International Nuclear Information System (INIS)
Hills, Richard G.; Trucano, Timothy G.
1999-01-01
A tutorial is presented discussing the basic issues associated with propagation of uncertainty analysis and statistical validation of engineering and scientific models. The propagation of uncertainty tutorial illustrates the use of the sensitivity method and the Monte Carlo method to evaluate the uncertainty in predictions for linear and nonlinear models. Four example applications are presented; a linear model, a model for the behavior of a damped spring-mass system, a transient thermal conduction model, and a nonlinear transient convective-diffusive model based on Burger's equation. Correlated and uncorrelated model input parameters are considered. The model validation tutorial builds on the material presented in the propagation of uncertainty tutoriaI and uses the damp spring-mass system as the example application. The validation tutorial illustrates several concepts associated with the application of statistical inference to test model predictions against experimental observations. Several validation methods are presented including error band based, multivariate, sum of squares of residuals, and optimization methods. After completion of the tutorial, a survey of statistical model validation literature is presented and recommendations for future work are made
(ajst) statistical mechanics model for orientational
African Journals Online (AJOL)
Science and Engineering Series Vol. 6, No. 2, pp. 94 - 101. STATISTICAL MECHANICS MODEL FOR ORIENTATIONAL. MOTION OF TWO-DIMENSIONAL RIGID ROTATOR. Malo, J.O. ... there is no translational motion and that they are well separated so .... constant and I is the moment of inertia of a linear rotator. Thus, the ...
Statistical Model Checking for Biological Systems
DEFF Research Database (Denmark)
David, Alexandre; Larsen, Kim Guldstrand; Legay, Axel
2014-01-01
Statistical Model Checking (SMC) is a highly scalable simulation-based verification approach for testing and estimating the probability that a stochastic system satisfies a given linear temporal property. The technique has been applied to (discrete and continuous time) Markov chains, stochastic...
Topology for Statistical Modeling of Petascale Data
Energy Technology Data Exchange (ETDEWEB)
Bennett, Janine Camille [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Pebay, Philippe Pierre [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Pascucci, Valerio [Univ. of Utah, Salt Lake City, UT (United States); Levine, Joshua [Univ. of Utah, Salt Lake City, UT (United States); Gyulassy, Attila [Univ. of Utah, Salt Lake City, UT (United States); Rojas, Maurice [Texas A & M Univ., College Station, TX (United States)
2014-07-01
This document presents current technical progress and dissemination of results for the Mathematics for Analysis of Petascale Data (MAPD) project titled "Topology for Statistical Modeling of Petascale Data", funded by the Office of Science Advanced Scientific Computing Research (ASCR) Applied Math program.
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
Statistical models for optimizing mineral exploration
International Nuclear Information System (INIS)
Wignall, T.K.; DeGeoffroy, J.
1987-01-01
The primary purpose of mineral exploration is to discover ore deposits. The emphasis of this volume is on the mathematical and computational aspects of optimizing mineral exploration. The seven chapters that make up the main body of the book are devoted to the description and application of various types of computerized geomathematical models. These chapters include: (1) the optimal selection of ore deposit types and regions of search, as well as prospecting selected areas, (2) designing airborne and ground field programs for the optimal coverage of prospecting areas, and (3) delineating and evaluating exploration targets within prospecting areas by means of statistical modeling. Many of these statistical programs are innovative and are designed to be useful for mineral exploration modeling. Examples of geomathematical models are applied to exploring for six main types of base and precious metal deposits, as well as other mineral resources (such as bauxite and uranium)
A statistical model for mapping morphological shape
Directory of Open Access Journals (Sweden)
Li Jiahan
2010-07-01
Full Text Available Abstract Background Living things come in all shapes and sizes, from bacteria, plants, and animals to humans. Knowledge about the genetic mechanisms for biological shape has far-reaching implications for a range spectrum of scientific disciplines including anthropology, agriculture, developmental biology, evolution and biomedicine. Results We derived a statistical model for mapping specific genes or quantitative trait loci (QTLs that control morphological shape. The model was formulated within the mixture framework, in which different types of shape are thought to result from genotypic discrepancies at a QTL. The EM algorithm was implemented to estimate QTL genotype-specific shapes based on a shape correspondence analysis. Computer simulation was used to investigate the statistical property of the model. Conclusion By identifying specific QTLs for morphological shape, the model developed will help to ask, disseminate and address many major integrative biological and genetic questions and challenges in the genetic control of biological shape and function.
Statistics of turbulent structures in a thermal plasma jet
Czech Academy of Sciences Publication Activity Database
Hlína, Jan; Šonský, Jiří; Něnička, Václav; Zachar, Andrej
2005-01-01
Roč. 38, - (2005), s. 1760-1768 ISSN 0022-3727 R&D Projects: GA AV ČR(CZ) IAA1057202; GA ČR(CZ) GA202/05/0728 Institutional research plan: CEZ:AV0Z20570509 Keywords : turbulent structures * thermal plasma jet Subject RIV: BL - Plasma and Gas Discharge Physics Impact factor: 1.957, year: 2005
Performance modeling, stochastic networks, and statistical multiplexing
Mazumdar, Ravi R
2013-01-01
This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of introducing an appropriate mathematical framework for modeling and analysis as well as understanding the phenomenon of statistical multiplexing. The models, techniques, and results presented form the core of traffic engineering methods used to design, control and allocate resources in communication networks.The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the importan
Statistical models for competing risk analysis
International Nuclear Information System (INIS)
Sather, H.N.
1976-08-01
Research results on three new models for potential applications in competing risks problems. One section covers the basic statistical relationships underlying the subsequent competing risks model development. Another discusses the problem of comparing cause-specific risk structure by competing risks theory in two homogeneous populations, P1 and P2. Weibull models which allow more generality than the Berkson and Elveback models are studied for the effect of time on the hazard function. The use of concomitant information for modeling single-risk survival is extended to the multiple failure mode domain of competing risks. The model used to illustrate the use of this methodology is a life table model which has constant hazards within pre-designated intervals of the time scale. Two parametric models for bivariate dependent competing risks, which provide interesting alternatives, are proposed and examined
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.
Statistical models of petrol engines vehicles dynamics
Ilie, C. O.; Marinescu, M.; Alexa, O.; Vilău, R.; Grosu, D.
2017-10-01
This paper focuses on studying statistical models of vehicles dynamics. It was design and perform a one year testing program. There were used many same type cars with gasoline engines and different mileage. Experimental data were collected of onboard sensors and those on the engine test stand. A database containing data of 64th tests was created. Several mathematical modelling were developed using database and the system identification method. Each modelling is a SISO or a MISO linear predictive ARMAX (AutoRegressive-Moving-Average with eXogenous inputs) model. It represents a differential equation with constant coefficients. It were made 64th equations for each dependency like engine torque as output and engine’s load and intake manifold pressure, as inputs. There were obtained strings with 64 values for each type of model. The final models were obtained using average values of the coefficients. The accuracy of models was assessed.
Equilibrium statistical mechanics of lattice models
Lavis, David A
2015-01-01
Most interesting and difficult problems in equilibrium statistical mechanics concern models which exhibit phase transitions. For graduate students and more experienced researchers this book provides an invaluable reference source of approximate and exact solutions for a comprehensive range of such models. Part I contains background material on classical thermodynamics and statistical mechanics, together with a classification and survey of lattice models. The geometry of phase transitions is described and scaling theory is used to introduce critical exponents and scaling laws. An introduction is given to finite-size scaling, conformal invariance and Schramm—Loewner evolution. Part II contains accounts of classical mean-field methods. The parallels between Landau expansions and catastrophe theory are discussed and Ginzburg—Landau theory is introduced. The extension of mean-field theory to higher-orders is explored using the Kikuchi—Hijmans—De Boer hierarchy of approximations. In Part III the use of alge...
Statistical shape and appearance models of bones.
Sarkalkan, Nazli; Weinans, Harrie; Zadpoor, Amir A
2014-03-01
When applied to bones, statistical shape models (SSM) and statistical appearance models (SAM) respectively describe the mean shape and mean density distribution of bones within a certain population as well as the main modes of variations of shape and density distribution from their mean values. The availability of this quantitative information regarding the detailed anatomy of bones provides new opportunities for diagnosis, evaluation, and treatment of skeletal diseases. The potential of SSM and SAM has been recently recognized within the bone research community. For example, these models have been applied for studying the effects of bone shape on the etiology of osteoarthritis, improving the accuracy of clinical osteoporotic fracture prediction techniques, design of orthopedic implants, and surgery planning. This paper reviews the main concepts, methods, and applications of SSM and SAM as applied to bone. Copyright © 2013 Elsevier Inc. All rights reserved.
Statistical Models of Adaptive Immune populations
Sethna, Zachary; Callan, Curtis; Walczak, Aleksandra; Mora, Thierry
The availability of large (104-106 sequences) datasets of B or T cell populations from a single individual allows reliable fitting of complex statistical models for naïve generation, somatic selection, and hypermutation. It is crucial to utilize a probabilistic/informational approach when modeling these populations. The inferred probability distributions allow for population characterization, calculation of probability distributions of various hidden variables (e.g. number of insertions), as well as statistical properties of the distribution itself (e.g. entropy). In particular, the differences between the T cell populations of embryonic and mature mice will be examined as a case study. Comparing these populations, as well as proposed mixed populations, provides a concrete exercise in model creation, comparison, choice, and validation.
W-320 Project thermal modeling
Energy Technology Data Exchange (ETDEWEB)
Sathyanarayana, K., Fluor Daniel Hanford
1997-03-18
This report summarizes the results of thermal analysis performed to provide a technical basis in support of Project W-320 to retrieve by sluicing the sludge in Tank 241-C-106 and to transfer into Tank 241-AY-102. Prior theraml evaluations in support of Project W-320 safety analysis assumed the availability of 2000 to 3000 CFM, as provided by Tank Farm Operations, for tank floor cooling channels from the secondary ventilation system. As this flow availability has no technical basis, a detailed Tank 241-AY-102 secondary ventilation and floor coating channel flow model was developed and analysis was performed. The results of the analysis show that only about 150 cfm flow is in floor cooLing channels. Tank 241-AY-102 thermal evaluation was performed to determine the necessary cooling flow for floor cooling channels using W-030 primary ventilation system for different quantities of Tank 241-C-106 sludge transfer into Tank 241-AY-102. These sludge transfers meet different options for the project along with minimum required modification of the ventilation system. Also the results of analysis for the amount of sludge transfer using the current system is presented. The effect of sludge fluffing factor, heat generation rate and its distribution between supernatant and sludge in Tank 241-AY-102 on the amount of sludge transfer from Tank 241-C-106 were evaluated and the results are discussed. Also transient thermal analysis was performed to estimate the time to reach the steady state. For a 2 feet sludge transfer, about 3 months time will be requirad to reach steady state. Therefore, for the purpose of process control, a detailed transient thermal analysis using GOTH Computer Code will be required to determine transient response of the sludge in Tank 241-AY-102. Process control considerations are also discussed to eliminate the potential for a steam bump during retrieval and storage in Tanks 241-C-106 and 241-AY-102 respectively.
Cellular automata and statistical mechanical models
International Nuclear Information System (INIS)
Rujan, P.
1987-01-01
The authors elaborate on the analogy between the transfer matrix of usual lattice models and the master equation describing the time development of cellular automata. Transient and stationary properties of probabilistic automata are linked to surface and bulk properties, respectively, of restricted statistical mechanical systems. It is demonstrated that methods of statistical physics can be successfully used to describe the dynamic and the stationary behavior of such automata. Some exact results are derived, including duality transformations, exact mappings, disorder, and linear solutions. Many examples are worked out in detail to demonstrate how to use statistical physics in order to construct cellular automata with desired properties. This approach is considered to be a first step toward the design of fully parallel, probabilistic systems whose computational abilities rely on the cooperative behavior of their components
Statistical Modelling of Wind Proles - Data Analysis and Modelling
DEFF Research Database (Denmark)
Jónsson, Tryggvi; Pinson, Pierre
The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles.......The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles....
Statistical core design methodology using the VIPRE thermal-hydraulics code
International Nuclear Information System (INIS)
Lloyd, M.W.; Feltus, M.A.
1995-01-01
An improved statistical core design methodology for developing a computational departure from nucleate boiling ratio (DNBR) correlation has been developed and applied in order to analyze the nominal 1.3 DNBR limit on Westinghouse Pressurized Water Reactor (PWR) cores. This analysis, although limited in scope, found that the DNBR limit can be reduced from 1.3 to some lower value and be accurate within an adequate confidence level of 95%, for three particular FSAR operational transients: turbine trip, complete loss of flow, and inadvertent opening of a pressurizer relief valve. The VIPRE-01 thermal-hydraulics code, the SAS/STAT statistical package, and the EPRI/Columbia University DNBR experimental data base were used in this research to develop the Pennsylvania State Statistical Core Design Methodology (PSSCDM). The VIPRE code was used to perform the necessary sensitivity studies and generate the EPRI correlation-calculated DNBR predictions. The SAS package used for these EPRI DNBR correlation predictions from VIPRE as a data set to determine the best fit for the empirical model and to perform the statistical analysis. (author)
Statistical treatment of the thermal behaviour of fast reactor fuel
International Nuclear Information System (INIS)
Russo, S.; Truffert, J.; Martella, T.; Marbach, G.
1981-08-01
In a sodium cooled fast reactor, fuel temperature is an important parameter acting on main characteristics of the project on fuel element and core behaviour. This parameter is important to define boundary conditions of fuel element utilisation. A method of statistical evaluation of temperature and of temperature increase higher than a given value is presented. This evaluation is obtained in the FIEVRE code by a combination of incertainties by means of a Monte Carlo optimized method. An application of FIEVRE code is presented in the case of Rapsodie-Fortissimo fuel at the beginning of refueling at nominal conditions without transient [fr
Logarithmic transformed statistical models in calibration
International Nuclear Information System (INIS)
Zeis, C.D.
1975-01-01
A general type of statistical model used for calibration of instruments having the property that the standard deviations of the observed values increase as a function of the mean value is described. The application to the Helix Counter at the Rocky Flats Plant is primarily from a theoretical point of view. The Helix Counter measures the amount of plutonium in certain types of chemicals. The method described can be used also for other calibrations. (U.S.)
ARSENIC CONTAMINATION IN GROUNDWATER: A STATISTICAL MODELING
Palas Roy; Naba Kumar Mondal; Biswajit Das; Kousik Das
2013-01-01
High arsenic in natural groundwater in most of the tubewells of the Purbasthali- Block II area of Burdwan district (W.B, India) has recently been focused as a serious environmental concern. This paper is intending to illustrate the statistical modeling of the arsenic contaminated groundwater to identify the interrelation of that arsenic contain with other participating groundwater parameters so that the arsenic contamination level can easily be predicted by analyzing only such parameters. Mul...
International Nuclear Information System (INIS)
Robeyns, J.; Parmentier, F.; Peeters, G.
2001-01-01
In the framework of safety analysis for the Belgian nuclear power plants and for the reload compatibility studies, Tractebel Energy Engineering (TEE) has developed, to define a 95/95 DNBR criterion, a statistical thermal design method based on the analytical full statistical approach: the Statistical Thermal Design Procedure (STDP). In that methodology, each DNBR value in the core assemblies is calculated with an adapted CHF (Critical Heat Flux) correlation implemented in the sub-channel code Cobra for core thermal hydraulic analysis. The uncertainties of the correlation are represented by the statistical parameters calculated from an experimental database. The main objective of a sub-channel analysis is to prove that in all class 1 and class 2 situations, the minimum DNBR (Departure from Nucleate Boiling Ratio) remains higher than the Safety Analysis Limit (SAL). The SAL value is calculated from the Statistical Design Limit (SDL) value adjusted with some penalties and deterministic factors. The search of a realistic value for the SDL is the objective of the statistical thermal design methods. In this report, we apply a full statistical approach to define the DNBR criterion or SDL (Statistical Design Limit) with the strict observance of the design criteria defined in the Standard Review Plan. The same statistical approach is used to define the expected number of rods experiencing DNB. (author)
Supo Thermal Model Development II
Energy Technology Data Exchange (ETDEWEB)
Wass, Alexander Joseph [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-07-14
This report describes the continuation of the Computational Fluid Dynamics (CFD) model of the Supo cooling system described in the report, Supo Thermal Model Development1, by Cynthia Buechler. The goal for this report is to estimate the natural convection heat transfer coefficient (HTC) of the system using the CFD results and to compare those results to remaining past operational data. Also, the correlation for determining radiolytic gas bubble size is reevaluated using the larger simulation sample size. The background, solution vessel geometry, mesh, material properties, and boundary conditions are developed in the same manner as the previous report. Although, the material properties and boundary conditions are determined using the appropriate experiment results for each individual power level.
A simple statistical model for geomagnetic reversals
Constable, Catherine
1990-01-01
The diversity of paleomagnetic records of geomagnetic reversals now available indicate that the field configuration during transitions cannot be adequately described by simple zonal or standing field models. A new model described here is based on statistical properties inferred from the present field and is capable of simulating field transitions like those observed. Some insight is obtained into what one can hope to learn from paleomagnetic records. In particular, it is crucial that the effects of smoothing in the remanence acquisition process be separated from true geomagnetic field behavior. This might enable us to determine the time constants associated with the dominant field configuration during a reversal.
Thermal transport in low dimensions from statistical physics to nanoscale heat transfer
2016-01-01
Understanding non-equilibrium properties of classical and quantum many-particle systems is one of the goals of contemporary statistical mechanics. Besides its own interest for the theoretical foundations of irreversible thermodynamics(e.g. of the Fourier's law of heat conduction), this topic is also relevant to develop innovative ideas for nanoscale thermal management with possible future applications to nanotechnologies and effective energetic resources. The first part of the volume (Chapters 1-6) describes the basic models, the phenomenology and the various theoretical approaches to understand heat transport in low-dimensional lattices (1D e 2D). The methods described will include equilibrium and nonequilibrium molecular dynamics simulations, hydrodynamic and kinetic approaches and the solution of stochastic models. The second part (Chapters 7-10) deals with applications to nano and microscale heat transfer, as for instance phononic transport in carbon-based nanomaterials, including the prominent case of na...
DEFF Research Database (Denmark)
Bahman, Amir Sajjad; Ma, Ke; Blaabjerg, Frede
2018-01-01
Detailed thermal dynamics of high power IGBT modules are important information for the reliability analysis and thermal design of power electronic systems. However, the existing thermal models have their limits to correctly predict these complicated thermal behavior in the IGBTs: The typically used...... thermal model based on one-dimensional RC lumps have limits to provide temperature distributions inside the device, moreover some variable factors in the real-field applications like the cooling and heating conditions of the converter cannot be adapted. On the other hand, the more advanced three......-dimensional thermal models based on Finite Element Method (FEM) need massive computations, which make the long-term thermal dynamics difficult to calculate. In this paper, a new lumped three-dimensional thermal model is proposed, which can be easily characterized from FEM simulations and can acquire the critical...
A method for statistical steady state thermal analysis of reactor cores
International Nuclear Information System (INIS)
Whetton, P.A.
1981-01-01
In a previous publication the author presented a method for undertaking statistical steady state thermal analyses of reactor cores. The present paper extends the technique to an assessment of confidence limits for the resulting probability functions which define the probability that a given thermal response value will be exceeded in a reactor core. Establishing such confidence limits is considered an integral part of any statistical thermal analysis and essential if such analysis are to be considered in any regulatory process. In certain applications the use of a best estimate probability function may be justifiable but it is recognised that a demonstrably conservative probability function is required for any regulatory considerations. (orig.)
Studies in the statistical and thermal properties of hadronic matter under some extreme conditions
International Nuclear Information System (INIS)
Chase, K.C.; Mekjian, A.Z.; Bhattacharyya, P.
1997-01-01
The thermal and statistical properties of hadronic matter under some extreme conditions are investigated using an exactly solvable canonical ensemble model. A unified model describing both the fragmentation of nuclei and the thermal properties of hadronic matter is developed. Simple expressions are obtained for quantities such as the hadronic equation of state, specific heat, compressibility, entropy, and excitation energy as a function of temperature and density. These expressions encompass the fermionic aspect of nucleons, such as degeneracy pressure and Fermi energy at low temperatures and the ideal gas laws at high temperatures and low density. Expressions are developed which connect these two extremes with behavior that resembles an ideal Bose gas with its associated Bose condensation. In the thermodynamic limit, an infinite cluster exists below a certain critical condition in a manner similar to the sudden appearance of the infinite cluster in percolation theory. The importance of multiplicity fluctuations is discussed and some recent data from the EOS collaboration on critical point behavior of nuclei can be accounted for using simple expressions obtained from the model. copyright 1997 The American Physical Society
Encoding Dissimilarity Data for Statistical Model Building.
Wahba, Grace
2010-12-01
We summarize, review and comment upon three papers which discuss the use of discrete, noisy, incomplete, scattered pairwise dissimilarity data in statistical model building. Convex cone optimization codes are used to embed the objects into a Euclidean space which respects the dissimilarity information while controlling the dimension of the space. A "newbie" algorithm is provided for embedding new objects into this space. This allows the dissimilarity information to be incorporated into a Smoothing Spline ANOVA penalized likelihood model, a Support Vector Machine, or any model that will admit Reproducing Kernel Hilbert Space components, for nonparametric regression, supervised learning, or semi-supervised learning. Future work and open questions are discussed. The papers are: F. Lu, S. Keles, S. Wright and G. Wahba 2005. A framework for kernel regularization with application to protein clustering. Proceedings of the National Academy of Sciences 102, 12332-1233.G. Corrada Bravo, G. Wahba, K. Lee, B. Klein, R. Klein and S. Iyengar 2009. Examining the relative influence of familial, genetic and environmental covariate information in flexible risk models. Proceedings of the National Academy of Sciences 106, 8128-8133F. Lu, Y. Lin and G. Wahba. Robust manifold unfolding with kernel regularization. TR 1008, Department of Statistics, University of Wisconsin-Madison.
ARSENIC CONTAMINATION IN GROUNDWATER: A STATISTICAL MODELING
Directory of Open Access Journals (Sweden)
Palas Roy
2013-01-01
Full Text Available High arsenic in natural groundwater in most of the tubewells of the Purbasthali- Block II area of Burdwan district (W.B, India has recently been focused as a serious environmental concern. This paper is intending to illustrate the statistical modeling of the arsenic contaminated groundwater to identify the interrelation of that arsenic contain with other participating groundwater parameters so that the arsenic contamination level can easily be predicted by analyzing only such parameters. Multivariate data analysis was done with the collected groundwater samples from the 132 tubewells of this contaminated region shows that three variable parameters are significantly related with the arsenic. Based on these relationships, a multiple linear regression model has been developed that estimated the arsenic contamination by measuring such three predictor parameters of the groundwater variables in the contaminated aquifer. This model could also be a suggestive tool while designing the arsenic removal scheme for any affected groundwater.
Thermal properties. Site descriptive modelling Forsmark - stage 2.2
International Nuclear Information System (INIS)
Back, Paer-Erik; Wrafter, John; Sundberg, Jan; Rosen, L ars
2007-09-01
The lithological data acquired from boreholes and mapping of the rock surface need to be reclassified into thermal rock classes, TRCs. The main reason is to simplify the simulations. The lithological data are used to construct models of the transition between different TRCs, thus describing the spatial statistical structure of each TRC. The result is a set of transition probability models that are used in the simulation of TRCs. The intermediate result of this first stochastic simulation is a number of realisations of the geology, each one equally probable. Based on the thermal data, a spatial statistical thermal model is constructed for each TRC. It consists of a statistical distribution and a variogram for each TRC. These are used in the stochastic simulation of thermal conductivity and the result is a number of equally probable realisations of thermal conductivity for the domain. In the next step, the realisations of TRCs (lithology) and thermal conductivity are merged, i.e. each realisation of geology is filled with simulated thermal conductivity values. The result is a set of realisations of thermal conductivity that considers both the difference in thermal properties between different TRCs, and the variability within each TRC. If the result is desired in a scale different from the simulation scale, i.e. the canister scale, upscaling of the realisations can be performed. The result is a set of equally probable realisations of thermal properties. The presented methodology was applied to rock domain RFM029 and RFM045. The main results are sets of realisations of thermal properties that can be used for further processing, most importantly for statistical analysis and numerical temperature simulations for the design of repository layout (distances between deposition holes). The main conclusions of the thermal modelling are: The choice of scale has a profound influence on the distribution of thermal conductivity values. The variance decreases and the lower tail
Thermal properties. Site descriptive modelling Forsmark - stage 2.2
Energy Technology Data Exchange (ETDEWEB)
Back, Paer-Erik; Wrafter, John; Sundberg, Jan [Geo Innova AB (Sweden); Rosen, L ars [Sweco Viak AB (Sweden)
2007-09-15
The lithological data acquired from boreholes and mapping of the rock surface need to be reclassified into thermal rock classes, TRCs. The main reason is to simplify the simulations. The lithological data are used to construct models of the transition between different TRCs, thus describing the spatial statistical structure of each TRC. The result is a set of transition probability models that are used in the simulation of TRCs. The intermediate result of this first stochastic simulation is a number of realisations of the geology, each one equally probable. Based on the thermal data, a spatial statistical thermal model is constructed for each TRC. It consists of a statistical distribution and a variogram for each TRC. These are used in the stochastic simulation of thermal conductivity and the result is a number of equally probable realisations of thermal conductivity for the domain. In the next step, the realisations of TRCs (lithology) and thermal conductivity are merged, i.e. each realisation of geology is filled with simulated thermal conductivity values. The result is a set of realisations of thermal conductivity that considers both the difference in thermal properties between different TRCs, and the variability within each TRC. If the result is desired in a scale different from the simulation scale, i.e. the canister scale, upscaling of the realisations can be performed. The result is a set of equally probable realisations of thermal properties. The presented methodology was applied to rock domain RFM029 and RFM045. The main results are sets of realisations of thermal properties that can be used for further processing, most importantly for statistical analysis and numerical temperature simulations for the design of repository layout (distances between deposition holes). The main conclusions of the thermal modelling are: The choice of scale has a profound influence on the distribution of thermal conductivity values. The variance decreases and the lower tail
Optimizing refiner operation with statistical modelling
Energy Technology Data Exchange (ETDEWEB)
Broderick, G [Noranda Research Centre, Pointe Claire, PQ (Canada)
1997-02-01
The impact of refining conditions on the energy efficiency of the process and on the handsheet quality of a chemi-mechanical pulp was studied as part of a series of pilot scale refining trials. Statistical models of refiner performance were constructed from these results and non-linear optimization of process conditions were conducted. Optimization results indicated that increasing the ratio of specific energy applied in the first stage led to a reduction of some 15 per cent in the total energy requirement. The strategy can also be used to obtain significant increases in pulp quality for a given energy input. 20 refs., 6 tabs.
Average Nuclear properties based on statistical model
International Nuclear Information System (INIS)
El-Jaick, L.J.
1974-01-01
The rough properties of nuclei were investigated by statistical model, in systems with the same and different number of protons and neutrons, separately, considering the Coulomb energy in the last system. Some average nuclear properties were calculated based on the energy density of nuclear matter, from Weizsscker-Beth mass semiempiric formulae, generalized for compressible nuclei. In the study of a s surface energy coefficient, the great influence exercised by Coulomb energy and nuclear compressibility was verified. For a good adjust of beta stability lines and mass excess, the surface symmetry energy were established. (M.C.K.) [pt
Overview of thermal conductivity models of anisotropic thermal insulation materials
Skurikhin, A. V.; Kostanovsky, A. V.
2017-11-01
Currently, the most of existing materials and substances under elaboration are anisotropic. It makes certain difficulties in the study of heat transfer process. Thermal conductivity of the materials can be characterized by tensor of the second order. Also, the parallelism between the temperature gradient vector and the density of heat flow vector is violated in anisotropic thermal insulation materials (TIM). One of the most famous TIM is a family of integrated thermal insulation refractory material («ITIRM»). The main component ensuring its properties is the «inflated» vermiculite. Natural mineral vermiculite is ground into powder state, fired by gas burner for dehydration, and its precipitate is then compressed. The key feature of thus treated batch of vermiculite is a package structure. The properties of the material lead to a slow heating of manufactured products due to low absorption and high radiation reflection. The maximum of reflection function is referred to infrared spectral region. A review of current models of heat propagation in anisotropic thermal insulation materials is carried out, as well as analysis of their thermal and optical properties. A theoretical model, which allows to determine the heat conductivity «ITIRM», can be useful in the study of thermal characteristics such as specific heat capacity, temperature conductivity, and others. Materials as «ITIRM» can be used in the metallurgy industry, thermal energy and nuclear power-engineering.
Statistical pairwise interaction model of stock market
Bury, Thomas
2013-03-01
Financial markets are a classical example of complex systems as they are compound by many interacting stocks. As such, we can obtain a surprisingly good description of their structure by making the rough simplification of binary daily returns. Spin glass models have been applied and gave some valuable results but at the price of restrictive assumptions on the market dynamics or they are agent-based models with rules designed in order to recover some empirical behaviors. Here we show that the pairwise model is actually a statistically consistent model with the observed first and second moments of the stocks orientation without making such restrictive assumptions. This is done with an approach only based on empirical data of price returns. Our data analysis of six major indices suggests that the actual interaction structure may be thought as an Ising model on a complex network with interaction strengths scaling as the inverse of the system size. This has potentially important implications since many properties of such a model are already known and some techniques of the spin glass theory can be straightforwardly applied. Typical behaviors, as multiple equilibria or metastable states, different characteristic time scales, spatial patterns, order-disorder, could find an explanation in this picture.
Statistical mechanics of the cluster Ising model
International Nuclear Information System (INIS)
Smacchia, Pietro; Amico, Luigi; Facchi, Paolo; Fazio, Rosario; Florio, Giuseppe; Pascazio, Saverio; Vedral, Vlatko
2011-01-01
We study a Hamiltonian system describing a three-spin-1/2 clusterlike interaction competing with an Ising-like antiferromagnetic interaction. We compute free energy, spin-correlation functions, and entanglement both in the ground and in thermal states. The model undergoes a quantum phase transition between an Ising phase with a nonvanishing magnetization and a cluster phase characterized by a string order. Any two-spin entanglement is found to vanish in both quantum phases because of a nontrivial correlation pattern. Nevertheless, the residual multipartite entanglement is maximal in the cluster phase and dependent on the magnetization in the Ising phase. We study the block entropy at the critical point and calculate the central charge of the system, showing that the criticality of the system is beyond the Ising universality class.
Statistical mechanics of the cluster Ising model
Energy Technology Data Exchange (ETDEWEB)
Smacchia, Pietro [SISSA - via Bonomea 265, I-34136, Trieste (Italy); Amico, Luigi [CNR-MATIS-IMM and Dipartimento di Fisica e Astronomia Universita di Catania, C/O ed. 10, viale Andrea Doria 6, I-95125 Catania (Italy); Facchi, Paolo [Dipartimento di Matematica and MECENAS, Universita di Bari, I-70125 Bari (Italy); INFN, Sezione di Bari, I-70126 Bari (Italy); Fazio, Rosario [NEST, Scuola Normale Superiore and Istituto Nanoscienze - CNR, 56126 Pisa (Italy); Center for Quantum Technology, National University of Singapore, 117542 Singapore (Singapore); Florio, Giuseppe; Pascazio, Saverio [Dipartimento di Fisica and MECENAS, Universita di Bari, I-70126 Bari (Italy); INFN, Sezione di Bari, I-70126 Bari (Italy); Vedral, Vlatko [Center for Quantum Technology, National University of Singapore, 117542 Singapore (Singapore); Department of Physics, National University of Singapore, 2 Science Drive 3, Singapore 117542 (Singapore); Department of Physics, University of Oxford, Clarendon Laboratory, Oxford, OX1 3PU (United Kingdom)
2011-08-15
We study a Hamiltonian system describing a three-spin-1/2 clusterlike interaction competing with an Ising-like antiferromagnetic interaction. We compute free energy, spin-correlation functions, and entanglement both in the ground and in thermal states. The model undergoes a quantum phase transition between an Ising phase with a nonvanishing magnetization and a cluster phase characterized by a string order. Any two-spin entanglement is found to vanish in both quantum phases because of a nontrivial correlation pattern. Nevertheless, the residual multipartite entanglement is maximal in the cluster phase and dependent on the magnetization in the Ising phase. We study the block entropy at the critical point and calculate the central charge of the system, showing that the criticality of the system is beyond the Ising universality class.
Statistical modeling to support power system planning
Staid, Andrea
This dissertation focuses on data-analytic approaches that improve our understanding of power system applications to promote better decision-making. It tackles issues of risk analysis, uncertainty management, resource estimation, and the impacts of climate change. Tools of data mining and statistical modeling are used to bring new insight to a variety of complex problems facing today's power system. The overarching goal of this research is to improve the understanding of the power system risk environment for improved operation, investment, and planning decisions. The first chapter introduces some challenges faced in planning for a sustainable power system. Chapter 2 analyzes the driving factors behind the disparity in wind energy investments among states with a goal of determining the impact that state-level policies have on incentivizing wind energy. Findings show that policy differences do not explain the disparities; physical and geographical factors are more important. Chapter 3 extends conventional wind forecasting to a risk-based focus of predicting maximum wind speeds, which are dangerous for offshore operations. Statistical models are presented that issue probabilistic predictions for the highest wind speed expected in a three-hour interval. These models achieve a high degree of accuracy and their use can improve safety and reliability in practice. Chapter 4 examines the challenges of wind power estimation for onshore wind farms. Several methods for wind power resource assessment are compared, and the weaknesses of the Jensen model are demonstrated. For two onshore farms, statistical models outperform other methods, even when very little information is known about the wind farm. Lastly, chapter 5 focuses on the power system more broadly in the context of the risks expected from tropical cyclones in a changing climate. Risks to U.S. power system infrastructure are simulated under different scenarios of tropical cyclone behavior that may result from climate
Acceleration transforms and statistical kinetic models
International Nuclear Information System (INIS)
LuValle, M.J.; Welsher, T.L.; Svoboda, K.
1988-01-01
For a restricted class of problems a mathematical model of microscopic degradation processes, statistical kinetics, is developed and linked through acceleration transforms to the information which can be obtained from a system in which the only observable sign of degradation is sudden and catastrophic failure. The acceleration transforms were developed in accelerated life testing applications as a tool for extrapolating from the observable results of an accelerated life test to the dynamics of the underlying degradation processes. A particular concern of a physicist attempting to interpreted the results of an analysis based on acceleration transforms is determining the physical species involved in the degradation process. These species may be (a) relatively abundant or (b) relatively rare. The main results of this paper are a theorem showing that for an important subclass of statistical kinetic models, acceleration transforms cannot be used to distinguish between cases a and b, and an example showing that in some cases falling outside the restrictions of the theorem, cases a and b can be distinguished by their acceleration transforms
Atmospheric corrosion: statistical validation of models
International Nuclear Information System (INIS)
Diaz, V.; Martinez-Luaces, V.; Guineo-Cobs, G.
2003-01-01
In this paper we discuss two different methods for validation of regression models, applied to corrosion data. One of them is based on the correlation coefficient and the other one is the statistical test of lack of fit. Both methods are used here to analyse fitting of bi logarithmic model in order to predict corrosion for very low carbon steel substrates in rural and urban-industrial atmospheres in Uruguay. Results for parameters A and n of the bi logarithmic model are reported here. For this purpose, all repeated values were used instead of using average values as usual. Modelling is carried out using experimental data corresponding to steel substrates under the same initial meteorological conditions ( in fact, they are put in the rack at the same time). Results of correlation coefficient are compared with the lack of it tested at two different signification levels (α=0.01 and α=0.05). Unexpected differences between them are explained and finally, it is possible to conclude, at least in the studied atmospheres, that the bi logarithmic model does not fit properly the experimental data. (Author) 18 refs
Spherical Process Models for Global Spatial Statistics
Jeong, Jaehong
2017-11-28
Statistical models used in geophysical, environmental, and climate science applications must reflect the curvature of the spatial domain in global data. Over the past few decades, statisticians have developed covariance models that capture the spatial and temporal behavior of these global data sets. Though the geodesic distance is the most natural metric for measuring distance on the surface of a sphere, mathematical limitations have compelled statisticians to use the chordal distance to compute the covariance matrix in many applications instead, which may cause physically unrealistic distortions. Therefore, covariance functions directly defined on a sphere using the geodesic distance are needed. We discuss the issues that arise when dealing with spherical data sets on a global scale and provide references to recent literature. We review the current approaches to building process models on spheres, including the differential operator, the stochastic partial differential equation, the kernel convolution, and the deformation approaches. We illustrate realizations obtained from Gaussian processes with different covariance structures and the use of isotropic and nonstationary covariance models through deformations and geographical indicators for global surface temperature data. To assess the suitability of each method, we compare their log-likelihood values and prediction scores, and we end with a discussion of related research problems.
A statistical mechanical model of economics
Lubbers, Nicholas Edward Williams
Statistical mechanics pursues low-dimensional descriptions of systems with a very large number of degrees of freedom. I explore this theme in two contexts. The main body of this dissertation explores and extends the Yard Sale Model (YSM) of economic transactions using a combination of simulations and theory. The YSM is a simple interacting model for wealth distributions which has the potential to explain the empirical observation of Pareto distributions of wealth. I develop the link between wealth condensation and the breakdown of ergodicity due to nonlinear diffusion effects which are analogous to the geometric random walk. Using this, I develop a deterministic effective theory of wealth transfer in the YSM that is useful for explaining many quantitative results. I introduce various forms of growth to the model, paying attention to the effect of growth on wealth condensation, inequality, and ergodicity. Arithmetic growth is found to partially break condensation, and geometric growth is found to completely break condensation. Further generalizations of geometric growth with growth in- equality show that the system is divided into two phases by a tipping point in the inequality parameter. The tipping point marks the line between systems which are ergodic and systems which exhibit wealth condensation. I explore generalizations of the YSM transaction scheme to arbitrary betting functions to develop notions of universality in YSM-like models. I find that wealth vi condensation is universal to a large class of models which can be divided into two phases. The first exhibits slow, power-law condensation dynamics, and the second exhibits fast, finite-time condensation dynamics. I find that the YSM, which exhibits exponential dynamics, is the critical, self-similar model which marks the dividing line between the two phases. The final chapter develops a low-dimensional approach to materials microstructure quantification. Modern materials design harnesses complex
Homogenized thermal conduction model for particulate foods
Chinesta , Francisco; Torres , Rafael; Ramón , Antonio; Rodrigo , Mari Carmen; Rodrigo , Miguel
2002-01-01
International audience; This paper deals with the definition of an equivalent thermal conductivity for particulate foods. An homogenized thermal model is used to asses the effect of particulate spatial distribution and differences in thermal conductivities. We prove that the spatial average of the conductivity can be used in an homogenized heat transfer model if the conductivity differences among the food components are not very large, usually the highest conductivity ratio between the foods ...
Current algebra, statistical mechanics and quantum models
Vilela Mendes, R.
2017-11-01
Results obtained in the past for free boson systems at zero and nonzero temperatures are revisited to clarify the physical meaning of current algebra reducible functionals which are associated to systems with density fluctuations, leading to observable effects on phase transitions. To use current algebra as a tool for the formulation of quantum statistical mechanics amounts to the construction of unitary representations of diffeomorphism groups. Two mathematical equivalent procedures exist for this purpose. One searches for quasi-invariant measures on configuration spaces, the other for a cyclic vector in Hilbert space. Here, one argues that the second approach is closer to the physical intuition when modelling complex systems. An example of application of the current algebra methodology to the pairing phenomenon in two-dimensional fermion systems is discussed.
Statistical model for OCT image denoising
Li, Muxingzi
2017-08-01
Optical coherence tomography (OCT) is a non-invasive technique with a large array of applications in clinical imaging and biological tissue visualization. However, the presence of speckle noise affects the analysis of OCT images and their diagnostic utility. In this article, we introduce a new OCT denoising algorithm. The proposed method is founded on a numerical optimization framework based on maximum-a-posteriori estimate of the noise-free OCT image. It combines a novel speckle noise model, derived from local statistics of empirical spectral domain OCT (SD-OCT) data, with a Huber variant of total variation regularization for edge preservation. The proposed approach exhibits satisfying results in terms of speckle noise reduction as well as edge preservation, at reduced computational cost.
Boundary between the thermal and statistical polarization regimes in a nuclear spin ensemble
International Nuclear Information System (INIS)
Herzog, B. E.; Cadeddu, D.; Xue, F.; Peddibhotla, P.; Poggio, M.
2014-01-01
As the number of spins in an ensemble is reduced, the statistical fluctuations in its polarization eventually exceed the mean thermal polarization. This transition has now been surpassed in a number of recent nuclear magnetic resonance experiments, which achieve nanometer-scale detection volumes. Here, we measure nanometer-scale ensembles of nuclear spins in a KPF 6 sample using magnetic resonance force microscopy. In particular, we investigate the transition between regimes dominated by thermal and statistical nuclear polarization. The ratio between the two types of polarization provides a measure of the number of spins in the detected ensemble.
Statistical physics of non-thermal phase transitions from foundations to applications
Abaimov, Sergey G
2015-01-01
Statistical physics can be used to better understand non-thermal complex systems—phenomena such as stock-market crashes, revolutions in society and in science, fractures in engineered materials and in the Earth’s crust, catastrophes, traffic jams, petroleum clusters, polymerization, self-organized criticality and many others exhibit behaviors resembling those of thermodynamic systems. In particular, many of these systems possess phase transitions identical to critical or spinodal phenomena in statistical physics. The application of the well-developed formalism of statistical physics to non-thermal complex systems may help to predict and prevent such catastrophes as earthquakes, snow-avalanches and landslides, failure of engineering structures, or economical crises. This book addresses the issue step-by-step, from phenomenological analogies between complex systems and statistical physics to more complex aspects, such as correlations, fluctuation-dissipation theorem, susceptibility, the concept of free ener...
New advances in statistical modeling and applications
Santos, Rui; Oliveira, Maria; Paulino, Carlos
2014-01-01
This volume presents selected papers from the XIXth Congress of the Portuguese Statistical Society, held in the town of Nazaré, Portugal, from September 28 to October 1, 2011. All contributions were selected after a thorough peer-review process. It covers a broad range of papers in the areas of statistical science, probability and stochastic processes, extremes and statistical applications.
Energy Technology Data Exchange (ETDEWEB)
Back, Paer-Erik; Sundberg, Jan [Geo Innova AB (Sweden)
2007-09-15
This report presents a strategy for describing, predicting and visualising the thermal aspects of the site descriptive model. The strategy is an updated version of an earlier strategy applied in all SDM versions during the initial site investigation phase at the Forsmark and Oskarshamn areas. The previous methodology for thermal modelling did not take the spatial correlation fully into account during simulation. The result was that the variability of thermal conductivity in the rock mass was not sufficiently well described. Experience from earlier thermal SDMs indicated that development of the methodology was required in order describe the spatial distribution of thermal conductivity in the rock mass in a sufficiently reliable way, taking both variability within rock types and between rock types into account. A good description of the thermal conductivity distribution is especially important for the lower tail. This tail is important for the design of a repository because it affects the canister spacing. The presented approach is developed to be used for final SDM regarding thermal properties, primarily thermal conductivity. Specific objectives for the strategy of thermal stochastic modelling are: Description: statistical description of the thermal conductivity of a rock domain. Prediction: prediction of thermal conductivity in a specific rock volume. Visualisation: visualisation of the spatial distribution of thermal conductivity. The thermal site descriptive model should include the temperature distribution and thermal properties of the rock mass. The temperature is the result of the thermal processes in the repository area. Determination of thermal transport properties can be made using different methods, such as laboratory investigations, field measurements, modelling from mineralogical composition and distribution, modelling from density logging and modelling from temperature logging. The different types of data represent different scales, which has to be
International Nuclear Information System (INIS)
Back, Paer-Erik; Sundberg, Jan
2007-09-01
This report presents a strategy for describing, predicting and visualising the thermal aspects of the site descriptive model. The strategy is an updated version of an earlier strategy applied in all SDM versions during the initial site investigation phase at the Forsmark and Oskarshamn areas. The previous methodology for thermal modelling did not take the spatial correlation fully into account during simulation. The result was that the variability of thermal conductivity in the rock mass was not sufficiently well described. Experience from earlier thermal SDMs indicated that development of the methodology was required in order describe the spatial distribution of thermal conductivity in the rock mass in a sufficiently reliable way, taking both variability within rock types and between rock types into account. A good description of the thermal conductivity distribution is especially important for the lower tail. This tail is important for the design of a repository because it affects the canister spacing. The presented approach is developed to be used for final SDM regarding thermal properties, primarily thermal conductivity. Specific objectives for the strategy of thermal stochastic modelling are: Description: statistical description of the thermal conductivity of a rock domain. Prediction: prediction of thermal conductivity in a specific rock volume. Visualisation: visualisation of the spatial distribution of thermal conductivity. The thermal site descriptive model should include the temperature distribution and thermal properties of the rock mass. The temperature is the result of the thermal processes in the repository area. Determination of thermal transport properties can be made using different methods, such as laboratory investigations, field measurements, modelling from mineralogical composition and distribution, modelling from density logging and modelling from temperature logging. The different types of data represent different scales, which has to be
A statistical model for predicting muscle performance
Byerly, Diane Leslie De Caix
The objective of these studies was to develop a capability for predicting muscle performance and fatigue to be utilized for both space- and ground-based applications. To develop this predictive model, healthy test subjects performed a defined, repetitive dynamic exercise to failure using a Lordex spinal machine. Throughout the exercise, surface electromyography (SEMG) data were collected from the erector spinae using a Mega Electronics ME3000 muscle tester and surface electrodes placed on both sides of the back muscle. These data were analyzed using a 5th order Autoregressive (AR) model and statistical regression analysis. It was determined that an AR derived parameter, the mean average magnitude of AR poles, significantly correlated with the maximum number of repetitions (designated Rmax) that a test subject was able to perform. Using the mean average magnitude of AR poles, a test subject's performance to failure could be predicted as early as the sixth repetition of the exercise. This predictive model has the potential to provide a basis for improving post-space flight recovery, monitoring muscle atrophy in astronauts and assessing the effectiveness of countermeasures, monitoring astronaut performance and fatigue during Extravehicular Activity (EVA) operations, providing pre-flight assessment of the ability of an EVA crewmember to perform a given task, improving the design of training protocols and simulations for strenuous International Space Station assembly EVA, and enabling EVA work task sequences to be planned enhancing astronaut performance and safety. Potential ground-based, medical applications of the predictive model include monitoring muscle deterioration and performance resulting from illness, establishing safety guidelines in the industry for repetitive tasks, monitoring the stages of rehabilitation for muscle-related injuries sustained in sports and accidents, and enhancing athletic performance through improved training protocols while reducing
Statistical Model Checking of Rich Models and Properties
DEFF Research Database (Denmark)
Poulsen, Danny Bøgsted
in undecidability issues for the traditional model checking approaches. Statistical model checking has proven itself a valuable supplement to model checking and this thesis is concerned with extending this software validation technique to stochastic hybrid systems. The thesis consists of two parts: the first part...... motivates why existing model checking technology should be supplemented by new techniques. It also contains a brief introduction to probability theory and concepts covered by the six papers making up the second part. The first two papers are concerned with developing online monitoring techniques...... systems. The fifth paper shows how stochastic hybrid automata are useful for modelling biological systems and the final paper is concerned with showing how statistical model checking is efficiently distributed. In parallel with developing the theory contained in the papers, a substantial part of this work...
Animal model of thermal injuries
Directory of Open Access Journals (Sweden)
F. Bečić
2003-11-01
Full Text Available Experimental studies of burns require the use of different animal models with the aim to imitate and reproduce pathophysiological conditions. The aim of this work was to establish experimental model of thermal injury.New Zealand rabbits, weighted from 1.8 kg to 2.3 kg, were utilised during our study. Another, also utilized, animal types were laboratory Rattus rats, species Wistar, albino type, females with body weight of about 232 g. All animals were from our own litter (Institute of Pharmacology, Clinical Pharmacology and Toxicology, Faculty of Medicine in Sarajevo. During the experiment, animal were properly situated in adequate cages and rooms, at the controlled temperature (22 ± 2°C, and in the air with normal humidity level. All animals took food and water ad libitum.Rabbits received anesthesia - intravenous pentobarbital sodium in a dose of 60 mg/kg, and then, hair from the upper side of the each rabbit ear was removed and burns were caused by a metal seal in the same manner as in rats. Rats were primarily anesthesied by intraperitoneal pentobarbital sodium in a dose of 35 mg/kg, and then, their hair was removed from the scapula zone (5 cm x 5 cm. Burns were caused by contact with a round metal seal, heated at 80°C in a water bath, during the period of 14 seconds together with contact thermometer control. Round metal seal (radius: 2.5 cm; weight: 100 g; surface: 5 cm2 was just placed on the rat skin without any additional pressure. In order to maintain the microcirculation in the burn wound and to reduce the conversion of partial-thickness skin burns to the burns of the full-thickness skin, all burn wounds were immediately sunk in the 4°C water. Subsequent to that procedure, all animals were individually situated in the proper cages, and left to rest for 4 hours with a constant cautious monitoring of the wound development and animal general state.
Reactor Thermal Hydraulic Numerical Calculation And Modeling
International Nuclear Information System (INIS)
Duong Ngoc Hai; Dang The Ba
2008-01-01
In the paper the results of analysis of thermal hydraulic state models using the numerical codes such as COOLOD, EUREKA and RELAP5 for simulation of the reactor thermal hydraulic states are presented. The calculations, analyses of reactor thermal hydraulic state and safety were implemented using different codes. The received numerical results, which were compared each to other, to experiment measurement of Dalat (Vietnam) research reactor and published results, show their appropriateness and capacity for analyses of different appropriate cases. (author)
A method for statistical steady state thermal analysis of reactor cores
International Nuclear Information System (INIS)
Whetton, P.A.
1980-01-01
This paper presents a method for performing a statistical steady state thermal analysis of a reactor core. The technique is only outlined here since detailed thermal equations are dependent on the core geometry. The method has been applied to a pressurised water reactor core and the results are presented for illustration purposes. Random hypothetical cores are generated using the Monte-Carlo method. The technique shows that by splitting the parameters into two types, denoted core-wise and in-core, the Monte Carlo method may be used inexpensively. The idea of using extremal statistics to characterise the low probability events (i.e. the tails of a distribution) is introduced together with a method of forming the final probability distribution. After establishing an acceptable probability of exceeding a thermal design criterion, the final probability distribution may be used to determine the corresponding thermal response value. If statistical and deterministic (i.e. conservative) thermal response values are compared, information on the degree of pessimism in the deterministic method of analysis may be inferred and the restrictive performance limitations imposed by this method relieved. (orig.)
Kosevich, Yuriy A.; Savin, Alexander V.; Cantarero, Andrés
2013-01-01
We present molecular dynamics simulation of phonon thermal conductivity of semiconductor nanoribbons with an account for phonon quantum statistics. In our semiquantum molecular dynamics simulation, dynamics of the system is described with the use of classical Newtonian equations of motion where the effect of phonon quantum statistics is introduced through random Langevin-like forces with a specific power spectral density (color noise). The color noise describes interaction of the molecular system with the thermostat. The thermal transport of silicon and germanium nanoribbons with atomically smooth (perfect) and rough (porous) edges are studied. We show that the existence of rough (porous) edges and the quantum statistics of phonon change drastically the low-temperature thermal conductivity of the nanoribbon in comparison with that of the perfect nanoribbon with atomically smooth edges and classical phonon dynamics and statistics. The rough-edge phonon scattering and weak anharmonicity of the considered lattice produce a weakly pronounced maximum of thermal conductivity of the nanoribbon at low temperature.
Network Data: Statistical Theory and New Models
2016-02-17
and with environmental scientists at JPL and Emory University to retrieval from NASA MISR remote sensing images aerosol index AOD for air pollution ...Beijing, May, 2013 Beijing Statistics Forum, Beijing, May, 2013 Statistics Seminar, CREST-ENSAE, Paris , March, 2013 Statistics Seminar, University...to retrieval from NASA MISR remote sensing images aerosol index AOD for air pollution monitoring and management. Satellite- retrieved Aerosol Optical
Energy Technology Data Exchange (ETDEWEB)
Sundberg, Jan; Wrafter, John; Laendell, Maerta (Geo Innova AB (Sweden)); Back, Paer-Erik; Rosen, Lars (Sweco AB (Sweden))
2008-11-15
This report present the results of thermal modelling work for the Forsmark area carried out during modelling stage 2.3. The work complements the main modelling efforts carried out during modelling stage 2.2. A revised spatial statistical description of the rock mass thermal conductivity for rock domain RFM045 is the main result of this work. Thermal modelling of domain RFM045 in Forsmark model stage 2.2 gave lower tail percentiles of thermal conductivity that were considered to be conservatively low due to the way amphibolite, the rock type with the lowest thermal conductivity, was modelled. New and previously available borehole data are used as the basis for revised stochastic geological simulations of domain RFM045. By defining two distinct thermal subdomains, these simulations have succeeded in capturing more of the lithological heterogeneity present. The resulting thermal model for rock domain RFM045 is, therefore, considered to be more realistic and reliable than that presented in model stage 2.2. The main conclusions of modelling efforts in model stage 2.3 are: - Thermal modelling indicates a mean thermal conductivity for domain RFM045 at the 5 m scale of 3.56 W/(mK). This is slightly higher than the value of 3.49 W/(mK) derived in model stage 2.2. - The variance decreases and the lower tail percentiles increase as the scale of observation increases from 1 to 5 m. Best estimates of the 0.1 percentile of thermal conductivity for domain RFM045 are 2.24 W/(mK) for the 1 m scale and 2.36 W/(mK) for the 5 m scale. This can be compared with corresponding values for domain RFM029 of 2.30 W/(mK) for the 1 m scale and 2.87 W/(mK)for the 5 m scale. - The reason for the pronounced lower tail in the thermal conductivity distribution for domain RFM045 is the presence of large bodies of the low-conductive amphibolite. - The modelling results for domain RFM029 presented in model stage 2.2 are still applicable. - As temperature increases, the thermal conductivity decreases
Thermal sensation models: a systematic comparison.
Koelblen, B; Psikuta, A; Bogdan, A; Annaheim, S; Rossi, R M
2017-05-01
Thermal sensation models, capable of predicting human's perception of thermal surroundings, are commonly used to assess given indoor conditions. These models differ in many aspects, such as the number and type of input conditions, the range of conditions in which the models can be applied, and the complexity of equations. Moreover, the models are associated with various thermal sensation scales. In this study, a systematic comparison of seven existing thermal sensation models has been performed with regard to exposures including various air temperatures, clothing thermal insulation, and metabolic rate values after a careful investigation of the models' range of applicability. Thermo-physiological data needed as input for some of the models were obtained from a mathematical model for human physiological responses. The comparison showed differences between models' predictions for the analyzed conditions, mostly higher than typical intersubject differences in votes. Therefore, it can be concluded that the choice of model strongly influences the assessment of indoor spaces. The issue of comparing different thermal sensation scales has also been discussed. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Transmutation Fuel Performance Code Thermal Model Verification
Energy Technology Data Exchange (ETDEWEB)
Gregory K. Miller; Pavel G. Medvedev
2007-09-01
FRAPCON fuel performance code is being modified to be able to model performance of the nuclear fuels of interest to the Global Nuclear Energy Partnership (GNEP). The present report documents the effort for verification of the FRAPCON thermal model. It was found that, with minor modifications, FRAPCON thermal model temperature calculation agrees with that of the commercial software ABAQUS (Version 6.4-4). This report outlines the methodology of the verification, code input, and calculation results.
Quantum statistical model for hot dense matter
International Nuclear Information System (INIS)
Rukhsana Kouser; Tasneem, G.; Saleem Shahzad, M.; Shafiq-ur-Rehman; Nasim, M.H.; Amjad Ali
2015-01-01
In solving numerous applied problems, one needs to know the equation of state, photon absorption coefficient and opacity of substances employed. We present a code for absorption coefficient and opacity calculation based on quantum statistical model. A self-consistent method for the calculation of potential is used. By solving Schrödinger equation with self-consistent potential we find energy spectrum of quantum mechanical system and corresponding wave functions. In addition we find mean occupation numbers of electron states and average charge state of the substance studied. The main processes of interaction of radiation with matter included in our opacity calculation are photon absorption in spectral lines (Bound-bound), photoionization (Bound-free), inverse bremsstrahlung (Free-free), Compton and Thomson scattering. Bound-bound line shape function has contribution from natural, Doppler, fine structure, collisional and stark broadening. To illustrate the main features of the code and its capabilities, calculation of average charge state, absorption coefficient, Rosseland and Planck mean and group opacities of aluminum and iron are presented. Results are satisfactorily compared with the published data. (authors)
International Nuclear Information System (INIS)
Qin Fang; Wen Wen; Chen Ji-Sheng
2014-01-01
The thermal and electrical transport properties of an ideal anyon gas within fractional exclusion statistics are studied. By solving the Boltzmann equation with the relaxation-time approximation, the analytical expressions for the thermal and electrical conductivities of a three-dimensional ideal anyon gas are given. The low-temperature expressions for the two conductivities are obtained by using the Sommerfeld expansion. It is found that the Wiedemann—Franz law should be modified by the higher-order temperature terms, which depend on the statistical parameter g for a charged anyon gas. Neglecting the higher-order terms of temperature, the Wiedemann—Franz law is respected, which gives the Lorenz number. The Lorenz number is a function of the statistical parameter g. (condensed matter: electronic structure, electrical, magnetic, and optical properties)
Global thermal models of the lithosphere
Cammarano, F.; Guerri, M.
2017-12-01
Unraveling the thermal structure of the outermost shell of our planet is key for understanding its evolution. We obtain temperatures from interpretation of global shear-velocity (VS) models. Long-wavelength thermal structure is well determined by seismic models and only slightly affected by compositional effects and uncertainties in mineral-physics properties. Absolute temperatures and gradients with depth, however, are not well constrained. Adding constraints from petrology, heat-flow observations and thermal evolution of oceanic lithosphere help to better estimate absolute temperatures in the top part of the lithosphere. We produce global thermal models of the lithosphere at different spatial resolution, up to spherical-harmonics degree 24, and provide estimated standard deviations. We provide purely seismic thermal (TS) model and hybrid models where temperatures are corrected with steady-state conductive geotherms on continents and cooling model temperatures on oceanic regions. All relevant physical properties, with the exception of thermal conductivity, are based on a self-consistent thermodynamical modelling approach. Our global thermal models also include density and compressional-wave velocities (VP) as obtained either assuming no lateral variations in composition or a simple reference 3-D compositional structure, which takes into account a chemically depleted continental lithosphere. We found that seismically-derived temperatures in continental lithosphere fit well, overall, with continental geotherms, but a large variation in radiogenic heat is required to reconcile them with heat flow (long wavelength) observations. Oceanic shallow lithosphere below mid-oceanic ridges and young oceans is colder than expected, confirming the possible presence of a dehydration boundary around 80 km depth already suggested in previous studies. The global thermal models should serve as the basis to move at a smaller spatial scale, where additional thermo-chemical variations
A BRDF statistical model applying to space target materials modeling
Liu, Chenghao; Li, Zhi; Xu, Can; Tian, Qichen
2017-10-01
In order to solve the problem of poor effect in modeling the large density BRDF measured data with five-parameter semi-empirical model, a refined statistical model of BRDF which is suitable for multi-class space target material modeling were proposed. The refined model improved the Torrance-Sparrow model while having the modeling advantages of five-parameter model. Compared with the existing empirical model, the model contains six simple parameters, which can approximate the roughness distribution of the material surface, can approximate the intensity of the Fresnel reflectance phenomenon and the attenuation of the reflected light's brightness with the azimuth angle changes. The model is able to achieve parameter inversion quickly with no extra loss of accuracy. The genetic algorithm was used to invert the parameters of 11 different samples in the space target commonly used materials, and the fitting errors of all materials were below 6%, which were much lower than those of five-parameter model. The effect of the refined model is verified by comparing the fitting results of the three samples at different incident zenith angles in 0° azimuth angle. Finally, the three-dimensional modeling visualizations of these samples in the upper hemisphere space was given, in which the strength of the optical scattering of different materials could be clearly shown. It proved the good describing ability of the refined model at the material characterization as well.
Statistical Challenges in Modeling Big Brain Signals
Yu, Zhaoxia
2017-11-01
Brain signal data are inherently big: massive in amount, complex in structure, and high in dimensions. These characteristics impose great challenges for statistical inference and learning. Here we review several key challenges, discuss possible solutions, and highlight future research directions.
Statistical Challenges in Modeling Big Brain Signals
Yu, Zhaoxia; Pluta, Dustin; Shen, Tong; Chen, Chuansheng; Xue, Gui; Ombao, Hernando
2017-01-01
Brain signal data are inherently big: massive in amount, complex in structure, and high in dimensions. These characteristics impose great challenges for statistical inference and learning. Here we review several key challenges, discuss possible
Statistical Learning Theory: Models, Concepts, and Results
von Luxburg, Ulrike; Schoelkopf, Bernhard
2008-01-01
Statistical learning theory provides the theoretical basis for many of today's machine learning algorithms. In this article we attempt to give a gentle, non-technical overview over the key ideas and insights of statistical learning theory. We target at a broad audience, not necessarily machine learning researchers. This paper can serve as a starting point for people who want to get an overview on the field before diving into technical details.
Online Statistical Modeling (Regression Analysis) for Independent Responses
Made Tirta, I.; Anggraeni, Dian; Pandutama, Martinus
2017-06-01
Regression analysis (statistical analmodelling) are among statistical methods which are frequently needed in analyzing quantitative data, especially to model relationship between response and explanatory variables. Nowadays, statistical models have been developed into various directions to model various type and complex relationship of data. Rich varieties of advanced and recent statistical modelling are mostly available on open source software (one of them is R). However, these advanced statistical modelling, are not very friendly to novice R users, since they are based on programming script or command line interface. Our research aims to developed web interface (based on R and shiny), so that most recent and advanced statistical modelling are readily available, accessible and applicable on web. We have previously made interface in the form of e-tutorial for several modern and advanced statistical modelling on R especially for independent responses (including linear models/LM, generalized linier models/GLM, generalized additive model/GAM and generalized additive model for location scale and shape/GAMLSS). In this research we unified them in the form of data analysis, including model using Computer Intensive Statistics (Bootstrap and Markov Chain Monte Carlo/ MCMC). All are readily accessible on our online Virtual Statistics Laboratory. The web (interface) make the statistical modeling becomes easier to apply and easier to compare them in order to find the most appropriate model for the data.
Thermal modelling of friction stir welding
DEFF Research Database (Denmark)
Schmidt, Henrik Nikolaj Blicher; Hattel, Jesper Henri
2008-01-01
The objective of the present work is to present the basic elements of the thermal modelling of friction stir welding as well as to clarify some of the uncertainties in the literature regarding the different contributions to the heat generation. Some results from a new thermal pseudomechanical model...... in which the temperature-dependent yield stress of the weld material controls the heat generation are also presented....
Phonon model of perovskite thermal capacity
International Nuclear Information System (INIS)
Kesler, Ya.A.; Poloznikova, M.Eh.; Petrov, K.I.
1983-01-01
A model for calculating the temperature curve of thermal capacity of perovskite family crystals on the basis of vibrational spectra is proposed. Different representatives of the perovskite family: cubic SrTiO 3 , tetragonal BaTiO 3 and orthorbombic CaTiO 3 and LaCrO 3 are considered. The total frequency set is used in thermal capacity calcUlations. Comparison of the thermal capacity values of compounds calculated on the basis of the proposed model with the experimental values shows their good agreement. The method is also recommended for other compounds with the perovskite-like structure
CHF predictor derived from a 3D thermal-hydraulic code and an advanced statistical method
International Nuclear Information System (INIS)
Banner, D.; Aubry, S.
2004-01-01
A rod bundle CHF predictor has been determined by using a 3D code (THYC) to compute local thermal-hydraulic conditions at the boiling crisis location. These local parameters have been correlated to the critical heat flux by using an advanced statistical method based on spline functions. The main characteristics of the predictor are presented in conjunction with a detailed analysis of predictions (P/M ratio) in order to prove that the usual safety methodology can be applied with such a predictor. A thermal-hydraulic design criterion is obtained (1.13) and the predictor is compared with the WRB-1 correlation. (author)
International Nuclear Information System (INIS)
Sun, Yanan; Dong, Jizhe; Ding, Lijuan
2017-01-01
Highlights: • A day–ahead wind–thermal unit commitment model is presented. • Wind speed transfer matrix is formed to depict the sequential wind features. • Spinning reserve setting considering wind power accuracy and variation is proposed. • Verified study is performed to check the correctness of the program. - Abstract: The increasing penetration of intermittent wind power affects the secure operation of power systems and leads to a requirement of robust and economic generation scheduling. This paper presents an optimal day–ahead wind–thermal generation scheduling method that considers the statistical and predicted features of wind speeds. In this method, the statistical analysis of historical wind data, which represents the local wind regime, is first implemented. Then, according to the statistical results and the predicted wind power, the spinning reserve requirements for the scheduling period are calculated. Based on the calculated spinning reserve requirements, the wind–thermal generation scheduling is finally conducted. To validate the program, a verified study is performed on a test system. Then, numerical studies to demonstrate the effectiveness of the proposed method are conducted.
Integer Set Compression and Statistical Modeling
DEFF Research Database (Denmark)
Larsson, N. Jesper
2014-01-01
enumeration of elements may be arbitrary or random, but where statistics is kept in order to estimate probabilities of elements. We present a recursive subset-size encoding method that is able to benefit from statistics, explore the effects of permuting the enumeration order based on element probabilities......Compression of integer sets and sequences has been extensively studied for settings where elements follow a uniform probability distribution. In addition, methods exist that exploit clustering of elements in order to achieve higher compression performance. In this work, we address the case where...
Statistical modelling for social researchers principles and practice
Tarling, Roger
2008-01-01
This book explains the principles and theory of statistical modelling in an intelligible way for the non-mathematical social scientist looking to apply statistical modelling techniques in research. The book also serves as an introduction for those wishing to develop more detailed knowledge and skills in statistical modelling. Rather than present a limited number of statistical models in great depth, the aim is to provide a comprehensive overview of the statistical models currently adopted in social research, in order that the researcher can make appropriate choices and select the most suitable model for the research question to be addressed. To facilitate application, the book also offers practical guidance and instruction in fitting models using SPSS and Stata, the most popular statistical computer software which is available to most social researchers. Instruction in using MLwiN is also given. Models covered in the book include; multiple regression, binary, multinomial and ordered logistic regression, log-l...
Linear Mixed Models in Statistical Genetics
R. de Vlaming (Ronald)
2017-01-01
markdownabstractOne of the goals of statistical genetics is to elucidate the genetic architecture of phenotypes (i.e., observable individual characteristics) that are affected by many genetic variants (e.g., single-nucleotide polymorphisms; SNPs). A particular aim is to identify specific SNPs that
Statistical models and methods for reliability and survival analysis
Couallier, Vincent; Huber-Carol, Catherine; Mesbah, Mounir; Huber -Carol, Catherine; Limnios, Nikolaos; Gerville-Reache, Leo
2013-01-01
Statistical Models and Methods for Reliability and Survival Analysis brings together contributions by specialists in statistical theory as they discuss their applications providing up-to-date developments in methods used in survival analysis, statistical goodness of fit, stochastic processes for system reliability, amongst others. Many of these are related to the work of Professor M. Nikulin in statistics over the past 30 years. The authors gather together various contributions with a broad array of techniques and results, divided into three parts - Statistical Models and Methods, Statistical
Xiang-Guo, Meng; Hong-Yi, Fan; Ji-Suo, Wang
2018-04-01
This paper proposes a kind of displaced thermal states (DTS) and explores how this kind of optical field emerges using the entangled state representation. The results show that the DTS can be generated by a coherent state passing through a diffusion channel with the diffusion coefficient ϰ only when there exists κ t = (e^{\\hbar ν /kBT} - 1 )^{-1}. Also, its statistical properties, such as mean photon number, Wigner function and entropy, are investigated.
Thermal conductivity model for nanoporous thin films
Huang, Congliang; Zhao, Xinpeng; Regner, Keith; Yang, Ronggui
2018-03-01
Nanoporous thin films have attracted great interest because of their extremely low thermal conductivity and potential applications in thin thermal insulators and thermoelectrics. Although there are some numerical and experimental studies about the thermal conductivity of nanoporous thin films, a simplified model is still needed to provide a straightforward prediction. In this paper, by including the phonon scattering lifetimes due to film thickness boundary scattering, nanopore scattering and the frequency-dependent intrinsic phonon-phonon scattering, a fitting-parameter-free model based on the kinetic theory of phonon transport is developed to predict both the in-plane and the cross-plane thermal conductivities of nanoporous thin films. With input parameters such as the lattice constants, thermal conductivity, and the group velocity of acoustic phonons of bulk silicon, our model shows a good agreement with available experimental and numerical results of nanoporous silicon thin films. It illustrates that the size effect of film thickness boundary scattering not only depends on the film thickness but also on the size of nanopores, and a larger nanopore leads to a stronger size effect of the film thickness. Our model also reveals that there are different optimal structures for getting the lowest in-plane and cross-plane thermal conductivities.
Geometric modeling in probability and statistics
Calin, Ovidiu
2014-01-01
This book covers topics of Informational Geometry, a field which deals with the differential geometric study of the manifold probability density functions. This is a field that is increasingly attracting the interest of researchers from many different areas of science, including mathematics, statistics, geometry, computer science, signal processing, physics and neuroscience. It is the authors’ hope that the present book will be a valuable reference for researchers and graduate students in one of the aforementioned fields. This textbook is a unified presentation of differential geometry and probability theory, and constitutes a text for a course directed at graduate or advanced undergraduate students interested in applications of differential geometry in probability and statistics. The book contains over 100 proposed exercises meant to help students deepen their understanding, and it is accompanied by software that is able to provide numerical computations of several information geometric objects. The reader...
Challenges in dental statistics: data and modelling
Matranga, D.; Castiglia, P.; Solinas, G.
2013-01-01
The aim of this work is to present the reflections and proposals derived from the first Workshop of the SISMEC STATDENT working group on statistical methods and applications in dentistry, held in Ancona (Italy) on 28th September 2011. STATDENT began as a forum of comparison and discussion for statisticians working in the field of dental research in order to suggest new and improve existing biostatistical and clinical epidemiological methods. During the meeting, we dealt with very important to...
Thermal models pertaining to continental growth
International Nuclear Information System (INIS)
Morgan, P.; Ashwal, L.
1988-01-01
Thermal models are important to understanding continental growth as the genesis, stabilization, and possible recycling of continental crust are closely related to the tectonic processes of the earth which are driven primarily by heat. The thermal energy budget of the earth was slowly decreasing since core formation, and thus the energy driving the terrestrial tectonic engine was decreasing. This fundamental observation was used to develop a logic tree defining the options for continental growth throughout earth history
A statistical model of future human actions
International Nuclear Information System (INIS)
Woo, G.
1992-02-01
A critical review has been carried out of models of future human actions during the long term post-closure period of a radioactive waste repository. Various Markov models have been considered as alternatives to the standard Poisson model, and the problems of parameterisation have been addressed. Where the simplistic Poisson model unduly exaggerates the intrusion risk, some form of Markov model may have to be introduced. This situation may well arise for shallow repositories, but it is less likely for deep repositories. Recommendations are made for a practical implementation of a computer based model and its associated database. (Author)
Thermal model of spent fuel transport cask
International Nuclear Information System (INIS)
Ahmed, E.E.M.; Rahman, F.A.; Sultan, G.F.; Khalil, E.E.
1996-01-01
The investigation provides a theoretical model to represent the thermal behaviour of the spent fuel elements when transported in a dry shipping cask under normal transport conditions. The heat transfer process in the spent fuel elements and within the cask are modeled which include the radiant heat transfer within the cask and the heat transfer by thermal conduction within the spent fuel element. The model considers the net radiant method for radiant heat transfer process from the inner most heated element to the surrounding spent elements. The heat conduction through fuel interior, fuel-clad interface and on clad surface are also presented. (author) 6 figs., 9 refs
Enhanced surrogate models for statistical design exploiting space mapping technology
DEFF Research Database (Denmark)
Koziel, Slawek; Bandler, John W.; Mohamed, Achmed S.
2005-01-01
We present advances in microwave and RF device modeling exploiting Space Mapping (SM) technology. We propose new SM modeling formulations utilizing input mappings, output mappings, frequency scaling and quadratic approximations. Our aim is to enhance circuit models for statistical analysis...
Statistical models of shape optimisation and evaluation
Davies, Rhodri; Taylor, Chris
2014-01-01
Deformable shape models have wide application in computer vision and biomedical image analysis. This book addresses a key issue in shape modelling: establishment of a meaningful correspondence between a set of shapes. Full implementation details are provided.
Analytical modeling for thermal errors of motorized spindle unit
Liu, Teng; Gao, Weiguo; Zhang, Dawei; Zhang, Yifan; Chang, Wenfen; Liang, Cunman; Tian, Yanling
2017-01-01
Modeling method investigation about spindle thermal errors is significant for spindle thermal optimization in design phase. To accurately analyze the thermal errors of motorized spindle unit, this paper assumes approximately that 1) spindle linear thermal error on axial direction is ascribed to shaft thermal elongation for its heat transfer from bearings, and 2) spindle linear thermal errors on radial directions and angular thermal errors are attributed to thermal variations of bearing relati...
Borsboom, D.; Haig, B.D.
2013-01-01
Unlike most other statistical frameworks, Bayesian statistical inference is wedded to a particular approach in the philosophy of science (see Howson & Urbach, 2006); this approach is called Bayesianism. Rather than being concerned with model fitting, this position in the philosophy of science
Statistical Tests for Mixed Linear Models
Khuri, André I; Sinha, Bimal K
2011-01-01
An advanced discussion of linear models with mixed or random effects. In recent years a breakthrough has occurred in our ability to draw inferences from exact and optimum tests of variance component models, generating much research activity that relies on linear models with mixed and random effects. This volume covers the most important research of the past decade as well as the latest developments in hypothesis testing. It compiles all currently available results in the area of exact and optimum tests for variance component models and offers the only comprehensive treatment for these models a
Statistical model predictions for p+p and Pb+Pb collisions at LHC
Kraus, I.; Cleymans, J.; Oeschler, H.; Redlich, K.; Wheaton, S.
2009-01-01
Particle production in p+p and central collisions at LHC is discussed in the context of the statistical thermal model. For heavy-ion collisions, predictions of various particle ratios are presented. The sensitivity of several ratios on the temperature and the baryon chemical potential is studied in
Statistical modelling of traffic safety development
DEFF Research Database (Denmark)
Christens, Peter
2004-01-01
there were 6861 injury trafficc accidents reported by the police, resulting in 4519 minor injuries, 3946 serious injuries, and 431 fatalities. The general purpose of the research was to improve the insight into aggregated road safety methodology in Denmark. The aim was to analyse advanced statistical methods......, that were designed to study developments over time, including effects of interventions. This aim has been achieved by investigating variations in aggregated Danish traffic accident series and by applying state of the art methodologies to specific case studies. The thesis comprises an introduction...
Statistical image processing and multidimensional modeling
Fieguth, Paul
2010-01-01
Images are all around us! The proliferation of low-cost, high-quality imaging devices has led to an explosion in acquired images. When these images are acquired from a microscope, telescope, satellite, or medical imaging device, there is a statistical image processing task: the inference of something - an artery, a road, a DNA marker, an oil spill - from imagery, possibly noisy, blurry, or incomplete. A great many textbooks have been written on image processing. However this book does not so much focus on images, per se, but rather on spatial data sets, with one or more measurements taken over
Fluctuations and correlations in statistical models of hadron production
International Nuclear Information System (INIS)
Gorenstein, M. I.
2012-01-01
An extension of the standard concept of the statistical ensembles is suggested. Namely, the statistical ensembles with extensive quantities fluctuating according to an externally given distribution are introduced. Applications in the statistical models of multiple hadron production in high energy physics are discussed.
Analysis and Evaluation of Statistical Models for Integrated Circuits Design
Directory of Open Access Journals (Sweden)
Sáenz-Noval J.J.
2011-10-01
Full Text Available Statistical models for integrated circuits (IC allow us to estimate the percentage of acceptable devices in the batch before fabrication. Actually, Pelgrom is the statistical model most accepted in the industry; however it was derived from a micrometer technology, which does not guarantee reliability in nanometric manufacturing processes. This work considers three of the most relevant statistical models in the industry and evaluates their limitations and advantages in analog design, so that the designer has a better criterion to make a choice. Moreover, it shows how several statistical models can be used for each one of the stages and design purposes.
Model Comparison for Electron Thermal Transport
Moses, Gregory; Chenhall, Jeffrey; Cao, Duc; Delettrez, Jacques
2015-11-01
Four electron thermal transport models are compared for their ability to accurately and efficiently model non-local behavior in ICF simulations. Goncharov's transport model has accurately predicted shock timing in implosion simulations but is computationally slow and limited to 1D. The iSNB (implicit Schurtz Nicolai Busquet electron thermal transport method of Cao et al. uses multigroup diffusion to speed up the calculation. Chenhall has expanded upon the iSNB diffusion model to a higher order simplified P3 approximation and a Monte Carlo transport model, to bridge the gap between the iSNB and Goncharov models while maintaining computational efficiency. Comparisons of the above models for several test problems will be presented. This work was supported by Sandia National Laboratory - Albuquerque and the University of Rochester Laboratory for Laser Energetics.
Modeling of uncertainties in statistical inverse problems
International Nuclear Information System (INIS)
Kaipio, Jari
2008-01-01
In all real world problems, the models that tie the measurements to the unknowns of interest, are at best only approximations for reality. While moderate modeling and approximation errors can be tolerated with stable problems, inverse problems are a notorious exception. Typical modeling errors include inaccurate geometry, unknown boundary and initial data, properties of noise and other disturbances, and simply the numerical approximations of the physical models. In principle, the Bayesian approach to inverse problems, in which all uncertainties are modeled as random variables, is capable of handling these uncertainties. Depending on the type of uncertainties, however, different strategies may be adopted. In this paper we give an overview of typical modeling errors and related strategies within the Bayesian framework.
Interpretation of commonly used statistical regression models.
Kasza, Jessica; Wolfe, Rory
2014-01-01
A review of some regression models commonly used in respiratory health applications is provided in this article. Simple linear regression, multiple linear regression, logistic regression and ordinal logistic regression are considered. The focus of this article is on the interpretation of the regression coefficients of each model, which are illustrated through the application of these models to a respiratory health research study. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.
Statistical modeling and extrapolation of carcinogenesis data
International Nuclear Information System (INIS)
Krewski, D.; Murdoch, D.; Dewanji, A.
1986-01-01
Mathematical models of carcinogenesis are reviewed, including pharmacokinetic models for metabolic activation of carcinogenic substances. Maximum likelihood procedures for fitting these models to epidemiological data are discussed, including situations where the time to tumor occurrence is unobservable. The plausibility of different possible shapes of the dose response curve at low doses is examined, and a robust method for linear extrapolation to low doses is proposed and applied to epidemiological data on radiation carcinogenesis
Plan Recognition using Statistical Relational Models
2014-08-25
corresponding undirected model can be significantly more complex since there is no closed form solution for the maximum-likelihood set of parameters unlike in...algorithm did not scale to larger training sets, and the overall results are still not competitive with BALPs. 5In directed models, a closed form solution...opinions of ARO, DARPA, NSF or any other government agency. References Albrecht DW, Zukerman I, Nicholson AE. Bayesian models for keyhole plan
Multivariate statistical modelling based on generalized linear models
Fahrmeir, Ludwig
1994-01-01
This book is concerned with the use of generalized linear models for univariate and multivariate regression analysis. Its emphasis is to provide a detailed introductory survey of the subject based on the analysis of real data drawn from a variety of subjects including the biological sciences, economics, and the social sciences. Where possible, technical details and proofs are deferred to an appendix in order to provide an accessible account for non-experts. Topics covered include: models for multi-categorical responses, model checking, time series and longitudinal data, random effects models, and state-space models. Throughout, the authors have taken great pains to discuss the underlying theoretical ideas in ways that relate well to the data at hand. As a result, numerous researchers whose work relies on the use of these models will find this an invaluable account to have on their desks. "The basic aim of the authors is to bring together and review a large part of recent advances in statistical modelling of m...
Modelling and Control of Thermal System
Directory of Open Access Journals (Sweden)
Vratislav Hladky
2014-01-01
Full Text Available Work presented here deals with the modelling of thermal processes in a thermal system consisting of direct and indirect heat exchangers. The overal thermal properties of the medium and the system itself such as liquid mixing or heat capacity are shortly analysed and their features required for modelling are reasoned and therefore simplified or neglected. Special attention is given to modelling heat losses radiated into the surroundings through the walls as they are the main issue of the effective work with the heat systems. Final part of the paper proposes several ways of controlling the individual parts’ temperatures as well as the temperature of the system considering heating elements or flowage rate as actuators.
Oubei, Hassan M.
2017-06-16
In this Letter, we use laser beam intensity fluctuation measurements to model and describe the statistical properties of weak temperature-induced turbulence in underwater wireless optical communication (UWOC) channels. UWOC channels with temperature gradients are modeled by the generalized gamma distribution (GGD) with an excellent goodness of fit to the measured data under all channel conditions. Meanwhile, thermally uniform channels are perfectly described by the simple gamma distribution which is a special case of GGD. To the best of our knowledge, this is the first model that comprehensively describes both thermally uniform and gradient-based UWOC channels.
Statistical Modelling of Extreme Rainfall in Taiwan
L-F. Chu (Lan-Fen); M.J. McAleer (Michael); C-C. Chang (Ching-Chung)
2012-01-01
textabstractIn this paper, the annual maximum daily rainfall data from 1961 to 2010 are modelled for 18 stations in Taiwan. We fit the rainfall data with stationary and non-stationary generalized extreme value distributions (GEV), and estimate their future behaviour based on the best fitting model.
Statistical Modelling of Extreme Rainfall in Taiwan
L. Chu (LanFen); M.J. McAleer (Michael); C-H. Chang (Chu-Hsiang)
2013-01-01
textabstractIn this paper, the annual maximum daily rainfall data from 1961 to 2010 are modelled for 18 stations in Taiwan. We fit the rainfall data with stationary and non-stationary generalized extreme value distributions (GEV), and estimate their future behaviour based on the best fitting model.
Fluctuations in the thermal superfluid model for heated spherical nuclei
International Nuclear Information System (INIS)
Nguyen Dinhdang; Nguyen Zuythang
1990-01-01
The effect of the non-vanishing thermal pairing gap due to statistical fluctuations is investigated by calculating fluctuations of selected observables such as the energy and particle number fluctuations, the nuclear level density, the level density parameter and the specific heat within the framework of the thermal nuclear superfluid model. In numerical calculations for heated spherical nuclei 58 Ni, 142 Sm and 208 Pb the realistic single-particle energy spectra defined in the Woods-Saxon potential are used. It is found that the results obtained with the non-vanishing thermal average pairing gap can yield an adequate estimate of the true fluctuations in the finite heating non-rotating nuclear systems. (author)
On the Logical Development of Statistical Models.
1983-12-01
1978). "Modelos con parametros variables en el analisis de series temporales " Questiio, 4, 2, 75-87. [25] Seal, H. L. (1967). "The historical...example, a classical state-space representation of a simple time series model is: yt = it + ut Ut = *It-I + Ct (2.2) ut and et are independent normal...on its past values is displayed in the structural equation. This approach has been particularly useful in time series models. For example, model (2.2
A Noise Robust Statistical Texture Model
DEFF Research Database (Denmark)
Hilger, Klaus Baggesen; Stegmann, Mikkel Bille; Larsen, Rasmus
2002-01-01
Appearance Models segmentation framework. This is accomplished by augmenting the model with an estimate of the covariance of the noise present in the training data. This results in a more compact model maximising the signal-to-noise ratio, thus favouring subspaces rich on signal, but low on noise......This paper presents a novel approach to the problem of obtaining a low dimensional representation of texture (pixel intensity) variation present in a training set after alignment using a Generalised Procrustes analysis.We extend the conventional analysis of training textures in the Active...
Hayslett, H T
1991-01-01
Statistics covers the basic principles of Statistics. The book starts by tackling the importance and the two kinds of statistics; the presentation of sample data; the definition, illustration and explanation of several measures of location; and the measures of variation. The text then discusses elementary probability, the normal distribution and the normal approximation to the binomial. Testing of statistical hypotheses and tests of hypotheses about the theoretical proportion of successes in a binomial population and about the theoretical mean of a normal population are explained. The text the
Simple Spreadsheet Thermal Models for Cryogenic Applications
Nash, Alfred
1995-01-01
Self consistent circuit analog thermal models that can be run in commercial spreadsheet programs on personal computers have been created to calculate the cooldown and steady state performance of cryogen cooled Dewars. The models include temperature dependent conduction and radiation effects. The outputs of the models provide temperature distribution and Dewar performance information. these models have been used to analyze the SIRTF Telescope Test Facility (STTF). The facility has been brought on line for its first user, the Infrared Telescope Technology Testbed (ITTT), for the Space Infrared Telescope Facility (SIRTF) at JPL. The model algorithm as well as a comparison between the models' predictions and actual performance of this facility will be presented.
12th Workshop on Stochastic Models, Statistics and Their Applications
Rafajłowicz, Ewaryst; Szajowski, Krzysztof
2015-01-01
This volume presents the latest advances and trends in stochastic models and related statistical procedures. Selected peer-reviewed contributions focus on statistical inference, quality control, change-point analysis and detection, empirical processes, time series analysis, survival analysis and reliability, statistics for stochastic processes, big data in technology and the sciences, statistical genetics, experiment design, and stochastic models in engineering. Stochastic models and related statistical procedures play an important part in furthering our understanding of the challenging problems currently arising in areas of application such as the natural sciences, information technology, engineering, image analysis, genetics, energy and finance, to name but a few. This collection arises from the 12th Workshop on Stochastic Models, Statistics and Their Applications, Wroclaw, Poland.
Materials Informatics: Statistical Modeling in Material Science.
Yosipof, Abraham; Shimanovich, Klimentiy; Senderowitz, Hanoch
2016-12-01
Material informatics is engaged with the application of informatic principles to materials science in order to assist in the discovery and development of new materials. Central to the field is the application of data mining techniques and in particular machine learning approaches, often referred to as Quantitative Structure Activity Relationship (QSAR) modeling, to derive predictive models for a variety of materials-related "activities". Such models can accelerate the development of new materials with favorable properties and provide insight into the factors governing these properties. Here we provide a comparison between medicinal chemistry/drug design and materials-related QSAR modeling and highlight the importance of developing new, materials-specific descriptors. We survey some of the most recent QSAR models developed in materials science with focus on energetic materials and on solar cells. Finally we present new examples of material-informatic analyses of solar cells libraries produced from metal oxides using combinatorial material synthesis. Different analyses lead to interesting physical insights as well as to the design of new cells with potentially improved photovoltaic parameters. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Electrical and thermal modeling of railguns
International Nuclear Information System (INIS)
Kerrisk, J.F.
1984-01-01
Electrical and thermal modeling of railguns at Los Alamos has been done for two purposes: (1) to obtain detailed information about the behavior of specific railgun components such as the rails, and (2) to predict overall performance of railgun tests. Detailed electrical and thermal modeling has concentrated on calculations of the inductance and surface current distribution of long parallel conductors in the high-frequency limit and on calculations of current and thermal diffusion in rails. Inductance calculations for various rail cross sections and for magnetic flux compression generators (MFCG) have been done. Inductance and current distribution results were compared with experimental measurements. Twodimensional calculations of current and thermal diffusion in rail cross sections have been done; predictions of rail heating and melting as a function of rail size and total current have been made. An overall performance model of a railgun and power supply has been developed and used to design tests at Los Alamos. The lumped-parameter circuit model uses results from the detailed inductance and current diffusion calculations along with other circuit component models to predict rail current and projectile acceleration, velocity, and position as a function of time
Introduction to statistical modelling: linear regression.
Lunt, Mark
2015-07-01
In many studies we wish to assess how a range of variables are associated with a particular outcome and also determine the strength of such relationships so that we can begin to understand how these factors relate to each other at a population level. Ultimately, we may also be interested in predicting the outcome from a series of predictive factors available at, say, a routine clinic visit. In a recent article in Rheumatology, Desai et al. did precisely that when they studied the prediction of hip and spine BMD from hand BMD and various demographic, lifestyle, disease and therapy variables in patients with RA. This article aims to introduce the statistical methodology that can be used in such a situation and explain the meaning of some of the terms employed. It will also outline some common pitfalls encountered when performing such analyses. © The Author 2013. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Latent domain models for statistical machine translation
Hoàng, C.
2017-01-01
A data-driven approach to model translation suffers from the data mismatch problem and demands domain adaptation techniques. Given parallel training data originating from a specific domain, training an MT system on the data would result in a rather suboptimal translation for other domains. But does
Behavioral and statistical models of educational inequality
DEFF Research Database (Denmark)
Holm, Anders; Breen, Richard
2016-01-01
This paper addresses the question of how students and their families make educational decisions. We describe three types of behavioral model that might underlie decision-making and we show that they have consequences for what decisions are made. Our study thus has policy implications if we wish...
Statistical modelling of fine red wine production
Directory of Open Access Journals (Sweden)
María Rosa Castro
2010-01-01
Full Text Available Producing wine is a very important economic activity in the province of San Juan in Argentina; it is therefore most important to predict production regarding the quantity of raw material needed. This work was aimed at obtaining a model relating kilograms of crushed grape to the litres of wine so produced. Such model will be used for predicting precise future values and confidence intervals for determined quantities of crushed grapes. Data from a vineyard in the province of San Juan was thus used in this work. The sampling coefficient of correlation was calculated and a dispersion diagram was then constructed; this indicated a li- neal relationship between the litres of wine obtained and the kilograms of crushed grape. Two lineal models were then adopted and variance analysis was carried out because the data came from normal populations having the same variance. The most appropriate model was obtained from this analysis; it was validated with experimental values, a good approach being obtained.
Statistical models of global Langmuir mixing
Li, Qing; Fox-Kemper, Baylor; Breivik, Øyvind; Webb, Adrean
2017-05-01
The effects of Langmuir mixing on the surface ocean mixing may be parameterized by applying an enhancement factor which depends on wave, wind, and ocean state to the turbulent velocity scale in the K-Profile Parameterization. Diagnosing the appropriate enhancement factor online in global climate simulations is readily achieved by coupling with a prognostic wave model, but with significant computational and code development expenses. In this paper, two alternatives that do not require a prognostic wave model, (i) a monthly mean enhancement factor climatology, and (ii) an approximation to the enhancement factor based on the empirical wave spectra, are explored and tested in a global climate model. Both appear to reproduce the Langmuir mixing effects as estimated using a prognostic wave model, with nearly identical and substantial improvements in the simulated mixed layer depth and intermediate water ventilation over control simulations, but significantly less computational cost. Simpler approaches, such as ignoring Langmuir mixing altogether or setting a globally constant Langmuir number, are found to be deficient. Thus, the consequences of Stokes depth and misaligned wind and waves are important.
Sampling, Probability Models and Statistical Reasoning -RE ...
Indian Academy of Sciences (India)
random sampling allows data to be modelled with the help of probability ... g based on different trials to get an estimate of the experimental error. ... research interests lie in the .... if e is indeed the true value of the proportion of defectives in the.
Statistical Model Checking for Product Lines
DEFF Research Database (Denmark)
ter Beek, Maurice H.; Legay, Axel; Lluch Lafuente, Alberto
2016-01-01
average cost of products (in terms of the attributes of the products’ features) and the probability of features to be (un)installed at runtime. The product lines must be modelled in QFLan, which extends the probabilistic feature-oriented language PFLan with novel quantitative constraints among features...
A Statistical Model for Energy Intensity
Directory of Open Access Journals (Sweden)
Marjaneh Issapour
2012-12-01
Full Text Available A promising approach to improve scientific literacy in regards to global warming and climate change is using a simulation as part of a science education course. The simulation needs to employ scientific analysis of actual data from internationally accepted and reputable databases to demonstrate the reality of the current climate change situation. One of the most important criteria for using a simulation in a science education course is the fidelity of the model. The realism of the events and consequences modeled in the simulation is significant as well. Therefore, all underlying equations and algorithms used in the simulation must have real-world scientific basis. The "Energy Choices" simulation is one such simulation. The focus of this paper is the development of a mathematical model for "Energy Intensity" as a part of the overall system dynamics in "Energy Choices" simulation. This model will define the "Energy Intensity" as a function of other independent variables that can be manipulated by users of the simulation. The relationship discovered by this research will be applied to an algorithm in the "Energy Choices" simulation.
Structured Statistical Models of Inductive Reasoning
Kemp, Charles; Tenenbaum, Joshua B.
2009-01-01
Everyday inductive inferences are often guided by rich background knowledge. Formal models of induction should aim to incorporate this knowledge and should explain how different kinds of knowledge lead to the distinctive patterns of reasoning found in different inductive contexts. This article presents a Bayesian framework that attempts to meet…
Numerical modeling of the autumnal thermal bar
Tsydenov, Bair O.
2018-03-01
The autumnal riverine thermal bar of Kamloops Lake has been simulated using atmospheric data from December 1, 2015, to January 4, 2016. The nonhydrostatic 2.5D mathematical model developed takes into account the diurnal variability of the heat fluxes and wind on the lake surface. The average values for shortwave and longwave radiation and latent and sensible heat fluxes were 19.7 W/m2, - 95.9 W/m2, - 11.8 W/m2, and - 32.0 W/m2 respectively. Analysis of the wind regime data showed prevailing easterly winds and maximum speed of 11 m/s on the 8th and 19th days. Numerical experiments with different boundary conditions at the lake surface were conducted to evaluate effects of variable heat flux and wind stress. The results of modeling demonstrated that the variable heat flux affects the process of thermal bar evolution, especially during the lengthy night cooling. However, the wind had the greatest impact on the behavior of the autumnal thermal bar: The easterly winds contributed to an earlier appearance of the thermal bar, but the strong winds generating the intensive circulations (the velocity of the upper lake flow increased to 6 cm/s) may destroy the thermal bar front.
Statistical Analysis and Modelling of Olkiluoto Structures
International Nuclear Information System (INIS)
Hellae, P.; Vaittinen, T.; Saksa, P.; Nummela, J.
2004-11-01
Posiva Oy is carrying out investigations for the disposal of the spent nuclear fuel at the Olkiluoto site in SW Finland. The investigations have focused on the central part of the island. The layout design of the entire repository requires characterization of notably larger areas and must rely at least at the current stage on borehole information from a rather sparse network and on the geophysical soundings providing information outside and between the holes. In this work, the structural data according to the current version of the Olkiluoto bedrock model is analyzed. The bedrock model relies much on the borehole data although results of the seismic surveys and, for example, pumping tests are used in determining the orientation and continuation of the structures. Especially in the analysis, questions related to the frequency of structures and size of the structures are discussed. The structures observed in the boreholes are mainly dipping gently to the southeast. About 9 % of the sample length belongs to structures. The proportion is higher in the upper parts of the rock. The number of fracture and crushed zones seems not to depend greatly on the depth, whereas the hydraulic features concentrate on the depth range above -100 m. Below level -300 m, the hydraulic conductivity occurs in connection of fractured zones. Especially the hydraulic features, but also fracture and crushed zones often occur in groups. The frequency of the structure (area of structures per total volume) is estimated to be of the order of 1/100m. The size of the local structures was estimated by calculating the intersection of the zone to the nearest borehole where the zone has not been detected. Stochastic models using the Fracman software by Golder Associates were generated based on the bedrock model data complemented with the magnetic ground survey data. The seismic surveys (from boreholes KR5, KR13, KR14, and KR19) were used as alternative input data. The generated models were tested by
Interacting dark energy model and thermal stability
Energy Technology Data Exchange (ETDEWEB)
Bhandari, Pritikana; Haldar, Sourav; Chakraborty, Subenoy [Jadavpur University, Department of Mathematics, Kolkata, West Bengal (India)
2017-12-15
In the background of the homogeneous and isotropic FLRW model, the thermodynamics of the interacting DE fluid is investigated in the present work. By studying the thermodynamical parameters, namely the heat capacities and the compressibilities, both thermal and mechanical stability are discussed and the restrictions on the equation of state parameter of the dark fluid are analyzed. (orig.)
Interacting dark energy model and thermal stability
International Nuclear Information System (INIS)
Bhandari, Pritikana; Haldar, Sourav; Chakraborty, Subenoy
2017-01-01
In the background of the homogeneous and isotropic FLRW model, the thermodynamics of the interacting DE fluid is investigated in the present work. By studying the thermodynamical parameters, namely the heat capacities and the compressibilities, both thermal and mechanical stability are discussed and the restrictions on the equation of state parameter of the dark fluid are analyzed. (orig.)
Modeling statistical properties of written text.
Directory of Open Access Journals (Sweden)
M Angeles Serrano
Full Text Available Written text is one of the fundamental manifestations of human language, and the study of its universal regularities can give clues about how our brains process information and how we, as a society, organize and share it. Among these regularities, only Zipf's law has been explored in depth. Other basic properties, such as the existence of bursts of rare words in specific documents, have only been studied independently of each other and mainly by descriptive models. As a consequence, there is a lack of understanding of linguistic processes as complex emergent phenomena. Beyond Zipf's law for word frequencies, here we focus on burstiness, Heaps' law describing the sublinear growth of vocabulary size with the length of a document, and the topicality of document collections, which encode correlations within and across documents absent in random null models. We introduce and validate a generative model that explains the simultaneous emergence of all these patterns from simple rules. As a result, we find a connection between the bursty nature of rare words and the topical organization of texts and identify dynamic word ranking and memory across documents as key mechanisms explaining the non trivial organization of written text. Our research can have broad implications and practical applications in computer science, cognitive science and linguistics.
Advanced data analysis in neuroscience integrating statistical and computational models
Durstewitz, Daniel
2017-01-01
This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level, and theoretical neuroscientists with a limited background in statistics. It reviews almost all areas of applied statistics, from basic statistical estimation and test theory, linear and nonlinear approaches for regression and classification, to model selection and methods for dimensionality reduction, density estimation and unsupervised clustering. Its focus, however, is linear and nonlinear time series analysis from a dynamical systems perspective, based on which it aims to convey an understanding also of the dynamical mechanisms that could have generated observed time series. Further, it integrates computational modeling of behavioral and neural dynamics with statistical estimation and hypothesis testing. This way computational models in neuroscience are not only explanat ory frameworks, but become powerfu...
IEEE Std 101-1987: IEEE guide for the statistical analysis of thermal life test data
International Nuclear Information System (INIS)
Anon.
1992-01-01
This revision of IEEE Std 101-1972 describes statistical analyses for data from thermally accelerated aging tests. It explains the basis and use of statistical calculations for an engineer or scientist. Accelerated test procedures usually call for a number of specimens to be aged at each of several temperatures appreciably above normal operating temperatures. High temperatures are chosen to produce specimen failures (according to specified failure criteria) in typically one week to one year. The test objective is to determine the dependence of median life on temperature from the data, and to estimate, by extrapolation, the median life to be expected at service temperature. This guide presents methods for analyzing such data and for comparing test data on different materials
Statistically Based Morphodynamic Modeling of Tracer Slowdown
Borhani, S.; Ghasemi, A.; Hill, K. M.; Viparelli, E.
2017-12-01
Tracer particles are used to study bedload transport in gravel-bed rivers. One of the advantages associated with using of tracer particles is that they allow for direct measures of the entrainment rates and their size distributions. The main issue in large scale studies with tracer particles is the difference between tracer stone short term and long term behavior. This difference is due to the fact that particles undergo vertical mixing or move to less active locations such as bars or even floodplains. For these reasons the average virtual velocity of tracer particle decreases in time, i.e. the tracer slowdown. In summary, tracer slowdown can have a significant impact on the estimation of bedload transport rate or long term dispersal of contaminated sediment. The vast majority of the morphodynamic models that account for the non-uniformity of the bed material (tracer and not tracer, in this case) are based on a discrete description of the alluvial deposit. The deposit is divided in two different regions; the active layer and the substrate. The active layer is a thin layer in the topmost part of the deposit whose particles can interact with the bed material transport. The substrate is the part of the deposit below the active layer. Due to the discrete representation of the alluvial deposit, active layer models are not able to reproduce tracer slowdown. In this study we try to model the slowdown of tracer particles with the continuous Parker-Paola-Leclair morphodynamic framework. This continuous, i.e. not layer-based, framework is based on a stochastic description of the temporal variation of bed surface elevation, and of the elevation specific particle entrainment and deposition. Particle entrainment rates are computed as a function of the flow and sediment characteristics, while particle deposition is estimated with a step length formulation. Here we present one of the first implementation of the continuum framework at laboratory scale, its validation against
Links to sources of cancer-related statistics, including the Surveillance, Epidemiology and End Results (SEER) Program, SEER-Medicare datasets, cancer survivor prevalence data, and the Cancer Trends Progress Report.
Model calculation of thermal conductivity in antiferromagnets
Energy Technology Data Exchange (ETDEWEB)
Mikhail, I.F.I., E-mail: ifi_mikhail@hotmail.com; Ismail, I.M.M.; Ameen, M.
2015-11-01
A theoretical study is given of thermal conductivity in antiferromagnetic materials. The study has the advantage that the three-phonon interactions as well as the magnon phonon interactions have been represented by model operators that preserve the important properties of the exact collision operators. A new expression for thermal conductivity has been derived that involves the same terms obtained in our previous work in addition to two new terms. These two terms represent the conservation and quasi-conservation of wavevector that occur in the three-phonon Normal and Umklapp processes respectively. They gave appreciable contributions to the thermal conductivity and have led to an excellent quantitative agreement with the experimental measurements of the antiferromagnet FeCl{sub 2}. - Highlights: • The Boltzmann equations of phonons and magnons in antiferromagnets have been studied. • Model operators have been used to represent the magnon–phonon and three-phonon interactions. • The models possess the same important properties as the exact operators. • A new expression for the thermal conductivity has been derived. • The results showed a good quantitative agreement with the experimental data of FeCl{sub 2}.
Functional summary statistics for the Johnson-Mehl model
DEFF Research Database (Denmark)
Møller, Jesper; Ghorbani, Mohammad
The Johnson-Mehl germination-growth model is a spatio-temporal point process model which among other things have been used for the description of neurotransmitters datasets. However, for such datasets parametric Johnson-Mehl models fitted by maximum likelihood have yet not been evaluated by means...... of functional summary statistics. This paper therefore invents four functional summary statistics adapted to the Johnson-Mehl model, with two of them based on the second-order properties and the other two on the nuclei-boundary distances for the associated Johnson-Mehl tessellation. The functional summary...... statistics theoretical properties are investigated, non-parametric estimators are suggested, and their usefulness for model checking is examined in a simulation study. The functional summary statistics are also used for checking fitted parametric Johnson-Mehl models for a neurotransmitters dataset....
Statistical modelling in biostatistics and bioinformatics selected papers
Peng, Defen
2014-01-01
This book presents selected papers on statistical model development related mainly to the fields of Biostatistics and Bioinformatics. The coverage of the material falls squarely into the following categories: (a) Survival analysis and multivariate survival analysis, (b) Time series and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling. Innovations in statistical modelling are presented throughout each of the four areas, with some intriguing new ideas on hierarchical generalized non-linear models and on frailty models with structural dispersion, just to mention two examples. The contributors include distinguished international statisticians such as Philip Hougaard, John Hinde, Il Do Ha, Roger Payne and Alessandra Durio, among others, as well as promising newcomers. Some of the contributions have come from researchers working in the BIO-SI research programme on Biostatistics and Bioinformatics, centred on the Universities of Limerick and Galway in Ireland and fu...
A new thermal conductivity model for nanofluids
Energy Technology Data Exchange (ETDEWEB)
Koo, Junemoo; Kleinstreuer, Clement [Department of Mechanical and Aerospace Engineering (United States)], E-mail: ck@eos.ncsu.edu
2004-12-15
In a quiescent suspension, nanoparticles move randomly and thereby carry relatively large volumes of surrounding liquid with them. This micro-scale interaction may occur between hot and cold regions, resulting in a lower local temperature gradient for a given heat flux compared with the pure liquid case. Thus, as a result of Brownian motion, the effective thermal conductivity, k{sub eff}, which is composed of the particles' conventional static part and the Brownian motion part, increases to result in a lower temperature gradient for a given heat flux. To capture these transport phenomena, a new thermal conductivity model for nanofluids has been developed, which takes the effects of particle size, particle volume fraction and temperature dependence as well as properties of base liquid and particle phase into consideration by considering surrounding liquid traveling with randomly moving nanoparticles.The strong dependence of the effective thermal conductivity on temperature and material properties of both particle and carrier fluid was attributed to the long impact range of the interparticle potential, which influences the particle motion. In the new model, the impact of Brownian motion is more effective at higher temperatures, as also observed experimentally. Specifically, the new model was tested with simple thermal conduction cases, and demonstrated that for a given heat flux, the temperature gradient changes significantly due to a variable thermal conductivity which mainly depends on particle volume fraction, particle size, particle material and temperature. To improve the accuracy and versatility of the k{sub eff}model, more experimental data sets are needed.
Statistical Characterization of 18650-Format Lithium-Ion Cell Thermal Runaway Energy Distributions
Walker, William Q.; Rickman, Steven; Darst, John; Finegan, Donal; Bayles, Gary; Darcy, Eric
2017-01-01
Effective thermal management systems, designed to handle the impacts of thermal runaway (TR) and to prevent cell-to-cell propagation, are key to safe operation of lithium-ion (Li-ion) battery assemblies. Critical factors for optimizing these systems include the total energy released during a single cell TR event and the fraction of the total energy that is released through the cell casing vs. through the ejecta material. A unique calorimeter was utilized to examine the TR behavior of a statistically significant number of 18650-format Li-ion cells with varying manufacturers, chemistries, and capacities. The calorimeter was designed to contain the TR energy in a format conducive to discerning the fractions of energy released through the cell casing vs. through the ejecta material. Other benefits of this calorimeter included the ability to rapidly test of large quantities of cells and the intentional minimization of secondary combustion effects. High energy (270 Wh/kg) and moderate energy (200 Wh/kg) 18650 cells were tested. Some of the cells had an imbedded short circuit (ISC) device installed to aid in the examination of TR mechanisms under more realistic conditions. Other variations included cells with bottom vent (BV) features and cells with thin casings (0.22 1/4m). After combining the data gathered with the calorimeter, a statistical approach was used to examine the probability of certain TR behavior, and the associated energy distributions, as a function of capacity, venting features, cell casing thickness and temperature.
A transient model to the thermal detonation
International Nuclear Information System (INIS)
Karachalios, K.
1987-04-01
The model calculates the escalation dynamics and the long time behavior of thermal detonation waves depending on the initial and boundary conditions (data of the premixture, ignition at a solid wall or at an open end, etc.). Especially, for a given mixture and a certain fragmentation behavior more than one stable steady-state cases resulted, depending on the applied ignition energy. Investigations showed a very good consistency between the transient model and a steady-state model which is based on the same physical description and includes an additional stability criterion. Also the influence of effects such as e.g. non-homogeneous coolant heating, spherical instead of plane wave propagation and inhomogeneities of the premixture on the development of the wave were investigated. Comparison calculations with large scale experiments showed that they can be well explained by means of the thermal detonation theory, especially considering the transient phase of the wave development. (orig./HP) [de
Thermal modelling of a torpedo-car
International Nuclear Information System (INIS)
Verdeja-Gonzalez, L. F.; Barbes-Fernandez, M. F.; Gonzalez-Ojeda, R.; Castillo, G. A.; Colas, R.
2005-01-01
A two-dimensional finite element model for computing the temperature distribution in a torpedo-car holding pig iron is described in this work. The model determines the temperature gradients in steady and transient conditions whiting the different parts that constitute the systems, which are considered to be the steel casing, refractory lining, liquid iron, slag and air. Heat transfer within the main fluid phases (iron and air) is computed assuming an apparent thermal conductivity term incorporating the contribution from convention and radiation, and it is affected by the dimensions of the vessel. Thermal gradients within the constituents of the torpedo-car are used to calculate heat losses during operation. It was found that the model required the incorporate of a region within the iron-refractory interface to reproduce thermographic data recorded during operation; the heat transfer coefficient of this interface was found to be equal to 30 Wm''-2K''-1. (Author) 11 refs
Thermal modelling of Advanced LIGO test masses
International Nuclear Information System (INIS)
Wang, H; Dovale Álvarez, M; Mow-Lowry, C M; Freise, A; Blair, C; Brooks, A; Kasprzack, M F; Ramette, J; Meyers, P M; Kaufer, S; O’Reilly, B
2017-01-01
High-reflectivity fused silica mirrors are at the epicentre of today’s advanced gravitational wave detectors. In these detectors, the mirrors interact with high power laser beams. As a result of finite absorption in the high reflectivity coatings the mirrors suffer from a variety of thermal effects that impact on the detectors’ performance. We propose a model of the Advanced LIGO mirrors that introduces an empirical term to account for the radiative heat transfer between the mirror and its surroundings. The mechanical mode frequency is used as a probe for the overall temperature of the mirror. The thermal transient after power build-up in the optical cavities is used to refine and test the model. The model provides a coating absorption estimate of 1.5–2.0 ppm and estimates that 0.3 to 1.3 ppm of the circulating light is scattered onto the ring heater. (paper)
Petersson, K M; Nichols, T E; Poline, J B; Holmes, A P
1999-01-01
Functional neuroimaging (FNI) provides experimental access to the intact living brain making it possible to study higher cognitive functions in humans. In this review and in a companion paper in this issue, we discuss some common methods used to analyse FNI data. The emphasis in both papers is on assumptions and limitations of the methods reviewed. There are several methods available to analyse FNI data indicating that none is optimal for all purposes. In order to make optimal use of the methods available it is important to know the limits of applicability. For the interpretation of FNI results it is also important to take into account the assumptions, approximations and inherent limitations of the methods used. This paper gives a brief overview over some non-inferential descriptive methods and common statistical models used in FNI. Issues relating to the complex problem of model selection are discussed. In general, proper model selection is a necessary prerequisite for the validity of the subsequent statistical inference. The non-inferential section describes methods that, combined with inspection of parameter estimates and other simple measures, can aid in the process of model selection and verification of assumptions. The section on statistical models covers approaches to global normalization and some aspects of univariate, multivariate, and Bayesian models. Finally, approaches to functional connectivity and effective connectivity are discussed. In the companion paper we review issues related to signal detection and statistical inference. PMID:10466149
Multiscale Modeling of UHTC: Thermal Conductivity
Lawson, John W.; Murry, Daw; Squire, Thomas; Bauschlicher, Charles W.
2012-01-01
We are developing a multiscale framework in computational modeling for the ultra high temperature ceramics (UHTC) ZrB2 and HfB2. These materials are characterized by high melting point, good strength, and reasonable oxidation resistance. They are candidate materials for a number of applications in extreme environments including sharp leading edges of hypersonic aircraft. In particular, we used a combination of ab initio methods, atomistic simulations and continuum computations to obtain insights into fundamental properties of these materials. Ab initio methods were used to compute basic structural, mechanical and thermal properties. From these results, a database was constructed to fit a Tersoff style interatomic potential suitable for atomistic simulations. These potentials were used to evaluate the lattice thermal conductivity of single crystals and the thermal resistance of simple grain boundaries. Finite element method (FEM) computations using atomistic results as inputs were performed with meshes constructed on SEM images thereby modeling the realistic microstructure. These continuum computations showed the reduction in thermal conductivity due to the grain boundary network.
International Nuclear Information System (INIS)
2005-01-01
For the years 2004 and 2005 the figures shown in the tables of Energy Review are partly preliminary. The annual statistics published in Energy Review are presented in more detail in a publication called Energy Statistics that comes out yearly. Energy Statistics also includes historical time-series over a longer period of time (see e.g. Energy Statistics, Statistics Finland, Helsinki 2004.) The applied energy units and conversion coefficients are shown in the back cover of the Review. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in GDP, energy consumption and electricity consumption, Carbon dioxide emissions from fossile fuels use, Coal consumption, Consumption of natural gas, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices in heat production, Fuel prices in electricity production, Price of electricity by type of consumer, Average monthly spot prices at the Nord pool power exchange, Total energy consumption by source and CO 2 -emissions, Supplies and total consumption of electricity GWh, Energy imports by country of origin in January-June 2003, Energy exports by recipient country in January-June 2003, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Price of natural gas by type of consumer, Price of electricity by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes, precautionary stock fees and oil pollution fees
Mixed deterministic statistical modelling of regional ozone air pollution
Kalenderski, Stoitchko
2011-03-17
We develop a physically motivated statistical model for regional ozone air pollution by separating the ground-level pollutant concentration field into three components, namely: transport, local production and large-scale mean trend mostly dominated by emission rates. The model is novel in the field of environmental spatial statistics in that it is a combined deterministic-statistical model, which gives a new perspective to the modelling of air pollution. The model is presented in a Bayesian hierarchical formalism, and explicitly accounts for advection of pollutants, using the advection equation. We apply the model to a specific case of regional ozone pollution-the Lower Fraser valley of British Columbia, Canada. As a predictive tool, we demonstrate that the model vastly outperforms existing, simpler modelling approaches. Our study highlights the importance of simultaneously considering different aspects of an air pollution problem as well as taking into account the physical bases that govern the processes of interest. © 2011 John Wiley & Sons, Ltd..
Statistical model of stress corrosion cracking based on extended
Indian Academy of Sciences (India)
The mechanism of stress corrosion cracking (SCC) has been discussed for decades. Here I propose a model of SCC reflecting the feature of fracture in brittle manner based on the variational principle under approximately supposed thermal equilibrium. In that model the functionals are expressed with extended forms of ...
A Model of Statistics Performance Based on Achievement Goal Theory.
Bandalos, Deborah L.; Finney, Sara J.; Geske, Jenenne A.
2003-01-01
Tests a model of statistics performance based on achievement goal theory. Both learning and performance goals affected achievement indirectly through study strategies, self-efficacy, and test anxiety. Implications of these findings for teaching and learning statistics are discussed. (Contains 47 references, 3 tables, 3 figures, and 1 appendix.)…
Kolmogorov complexity, pseudorandom generators and statistical models testing
Czech Academy of Sciences Publication Activity Database
Šindelář, Jan; Boček, Pavel
2002-01-01
Roč. 38, č. 6 (2002), s. 747-759 ISSN 0023-5954 R&D Projects: GA ČR GA102/99/1564 Institutional research plan: CEZ:AV0Z1075907 Keywords : Kolmogorov complexity * pseudorandom generators * statistical models testing Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.341, year: 2002
Statistical properties of several models of fractional random point processes
Bendjaballah, C.
2011-08-01
Statistical properties of several models of fractional random point processes have been analyzed from the counting and time interval statistics points of view. Based on the criterion of the reduced variance, it is seen that such processes exhibit nonclassical properties. The conditions for these processes to be treated as conditional Poisson processes are examined. Numerical simulations illustrate part of the theoretical calculations.
INDIVIDUAL BASED MODELLING APPROACH TO THERMAL ...
Diadromous fish populations in the Pacific Northwest face challenges along their migratory routes from declining habitat quality, harvest, and barriers to longitudinal connectivity. Changes in river temperature regimes are producing an additional challenge for upstream migrating adult salmon and steelhead, species that are sensitive to absolute and cumulative thermal exposure. Adult salmon populations have been shown to utilize cold water patches along migration routes when mainstem river temperatures exceed thermal optimums. We are employing an individual based model (IBM) to explore the costs and benefits of spatially-distributed cold water refugia for adult migrating salmon. Our model, developed in the HexSim platform, is built around a mechanistic behavioral decision tree that drives individual interactions with their spatially explicit simulated environment. Population-scale responses to dynamic thermal regimes, coupled with other stressors such as disease and harvest, become emergent properties of the spatial IBM. Other model outputs include arrival times, species-specific survival rates, body energetic content, and reproductive fitness levels. Here, we discuss the challenges associated with parameterizing an individual based model of salmon and steelhead in a section of the Columbia River. Many rivers and streams in the Pacific Northwest are currently listed as impaired under the Clean Water Act as a result of high summer water temperatures. Adverse effec
International Nuclear Information System (INIS)
2001-01-01
For the year 2000, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy Review appear in more detail from the publication Energiatilastot - Energy Statistics issued annually, which also includes historical time series over a longer period (see e.g. Energiatilastot 1999, Statistics Finland, Helsinki 2000, ISSN 0785-3165). The inside of the Review's back cover shows the energy units and the conversion coefficients used for them. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in the volume of GNP and energy consumption, Changes in the volume of GNP and electricity, Coal consumption, Natural gas consumption, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices for heat production, Fuel prices for electricity production, Carbon dioxide emissions from the use of fossil fuels, Total energy consumption by source and CO 2 -emissions, Electricity supply, Energy imports by country of origin in 2000, Energy exports by recipient country in 2000, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Average electricity price by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes and precautionary stock fees on oil products
International Nuclear Information System (INIS)
2000-01-01
For the year 1999 and 2000, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy Review appear in more detail from the publication Energiatilastot - Energy Statistics issued annually, which also includes historical time series over a longer period (see e.g., Energiatilastot 1998, Statistics Finland, Helsinki 1999, ISSN 0785-3165). The inside of the Review's back cover shows the energy units and the conversion coefficients used for them. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in the volume of GNP and energy consumption, Changes in the volume of GNP and electricity, Coal consumption, Natural gas consumption, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices for heat production, Fuel prices for electricity production, Carbon dioxide emissions, Total energy consumption by source and CO 2 -emissions, Electricity supply, Energy imports by country of origin in January-March 2000, Energy exports by recipient country in January-March 2000, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Average electricity price by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes and precautionary stock fees on oil products
International Nuclear Information System (INIS)
1999-01-01
For the year 1998 and the year 1999, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy Review appear in more detail from the publication Energiatilastot - Energy Statistics issued annually, which also includes historical time series over a longer period (see e.g. Energiatilastot 1998, Statistics Finland, Helsinki 1999, ISSN 0785-3165). The inside of the Review's back cover shows the energy units and the conversion coefficients used for them. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in the volume of GNP and energy consumption, Changes in the volume of GNP and electricity, Coal consumption, Natural gas consumption, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices for heat production, Fuel prices for electricity production, Carbon dioxide emissions, Total energy consumption by source and CO 2 -emissions, Electricity supply, Energy imports by country of origin in January-June 1999, Energy exports by recipient country in January-June 1999, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Average electricity price by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes and precautionary stock fees on oil products
Improving statistical reasoning theoretical models and practical implications
Sedlmeier, Peter
1999-01-01
This book focuses on how statistical reasoning works and on training programs that can exploit people''s natural cognitive capabilities to improve their statistical reasoning. Training programs that take into account findings from evolutionary psychology and instructional theory are shown to have substantially larger effects that are more stable over time than previous training regimens. The theoretical implications are traced in a neural network model of human performance on statistical reasoning problems. This book apppeals to judgment and decision making researchers and other cognitive scientists, as well as to teachers of statistics and probabilistic reasoning.
Statistical validation of normal tissue complication probability models
Xu, Cheng-Jian; van der Schaaf, Arjen; van t Veld, Aart; Langendijk, Johannes A.; Schilstra, Cornelis
2012-01-01
PURPOSE: To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. METHODS AND MATERIALS: A penalized regression method, LASSO (least absolute shrinkage
Some remarks on the statistical model of heavy ion collisions
International Nuclear Information System (INIS)
Koch, V.
2003-01-01
This contribution is an attempt to assess what can be learned from the remarkable success of this statistical model in describing ratios of particle abundances in ultra-relativistic heavy ion collisions
Eigenfunction statistics for Anderson model with Hölder continuous ...
Indian Academy of Sciences (India)
The Institute of Mathematical Sciences, Taramani, Chennai 600 113, India ... Anderson model; Hölder continuous measure; Poisson statistics. ...... [4] Combes J-M, Hislop P D and Klopp F, An optimal Wegner estimate and its application to.
A no extensive statistical model for the nucleon structure function
International Nuclear Information System (INIS)
Trevisan, Luis A.; Mirez, Carlos
2013-01-01
We studied an application of nonextensive thermodynamics to describe the structure function of nucleon, in a model where the usual Fermi-Dirac and Bose-Einstein energy distribution were replaced by the equivalent functions of the q-statistical. The parameters of the model are given by an effective temperature T, the q parameter (from Tsallis statistics), and two chemical potentials given by the corresponding up (u) and down (d) quark normalization in the nucleon.
Strangeness by Thermal Model Simulation at RHIC
Institute of Scientific and Technical Information of China (English)
SHI Xing-Hua; MA Yu-Gang; CAI Xiang-Zhou; CHEN Jin-Hui; MA Guo-Liang; ZHONG Chen
2009-01-01
The local temperature effect on strangeness enhancement in relativistic heavy ion collisions is discussed in the framework of the thermal model in which the K+ /h+ ratio becomes smaller with increasing freeze-out temperature.Considering that most strangeness particles of final-state particles are from the kaon meson,the temperature effect may play a role in strangeness production in hot dense matter where a slightly different temperature distribution in different areas could be produced by jet energy loss.This phenomenon is predicted by thermal model calculation at RHIC energy.The Ε-/φ ratio in central Au+Au collisions at 200 GeV from the thermal model depends on the freeze-out temperature obviously when γs is different.It should be one of the reasons why strangeness enhancements of Ε and φ are different though they include two strange quarks.These results indicate that thermodynamics is an important factor for strangeness production and the strangeness enhancement phenomenon.
Statistical models and NMR analysis of polymer microstructure
Statistical models can be used in conjunction with NMR spectroscopy to study polymer microstructure and polymerization mechanisms. Thus, Bernoullian, Markovian, and enantiomorphic-site models are well known. Many additional models have been formulated over the years for additional situations. Typica...
International Nuclear Information System (INIS)
2003-01-01
For the year 2002, part of the figures shown in the tables of the Energy Review are partly preliminary. The annual statistics of the Energy Review also includes historical time-series over a longer period (see e.g. Energiatilastot 2001, Statistics Finland, Helsinki 2002). The applied energy units and conversion coefficients are shown in the inside back cover of the Review. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in GDP, energy consumption and electricity consumption, Carbon dioxide emissions from fossile fuels use, Coal consumption, Consumption of natural gas, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices in heat production, Fuel prices in electricity production, Price of electricity by type of consumer, Average monthly spot prices at the Nord pool power exchange, Total energy consumption by source and CO 2 -emissions, Supply and total consumption of electricity GWh, Energy imports by country of origin in January-June 2003, Energy exports by recipient country in January-June 2003, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Price of natural gas by type of consumer, Price of electricity by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Excise taxes, precautionary stock fees on oil pollution fees on energy products
International Nuclear Information System (INIS)
2004-01-01
For the year 2003 and 2004, the figures shown in the tables of the Energy Review are partly preliminary. The annual statistics of the Energy Review also includes historical time-series over a longer period (see e.g. Energiatilastot, Statistics Finland, Helsinki 2003, ISSN 0785-3165). The applied energy units and conversion coefficients are shown in the inside back cover of the Review. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in GDP, energy consumption and electricity consumption, Carbon dioxide emissions from fossile fuels use, Coal consumption, Consumption of natural gas, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices in heat production, Fuel prices in electricity production, Price of electricity by type of consumer, Average monthly spot prices at the Nord pool power exchange, Total energy consumption by source and CO 2 -emissions, Supplies and total consumption of electricity GWh, Energy imports by country of origin in January-March 2004, Energy exports by recipient country in January-March 2004, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Price of natural gas by type of consumer, Price of electricity by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Excise taxes, precautionary stock fees on oil pollution fees
International Nuclear Information System (INIS)
2000-01-01
For the year 1999 and 2000, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy also includes historical time series over a longer period (see e.g., Energiatilastot 1999, Statistics Finland, Helsinki 2000, ISSN 0785-3165). The inside of the Review's back cover shows the energy units and the conversion coefficients used for them. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in the volume of GNP and energy consumption, Changes in the volume of GNP and electricity, Coal consumption, Natural gas consumption, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices for heat production, Fuel prices for electricity production, Carbon dioxide emissions, Total energy consumption by source and CO 2 -emissions, Electricity supply, Energy imports by country of origin in January-June 2000, Energy exports by recipient country in January-June 2000, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Average electricity price by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes and precautionary stock fees on oil products
Bayesian networks modeling for thermal error of numerical control machine tools
Institute of Scientific and Technical Information of China (English)
Xin-hua YAO; Jian-zhong FU; Zi-chen CHEN
2008-01-01
The interaction between the heat source location,its intensity,thermal expansion coefficient,the machine system configuration and the running environment creates complex thermal behavior of a machine tool,and also makes thermal error prediction difficult.To address this issue,a novel prediction method for machine tool thermal error based on Bayesian networks (BNs) was presented.The method described causal relationships of factors inducing thermal deformation by graph theory and estimated the thermal error by Bayesian statistical techniques.Due to the effective combination of domain knowledge and sampled data,the BN method could adapt to the change of running state of machine,and obtain satisfactory prediction accuracy.Ex-periments on spindle thermal deformation were conducted to evaluate the modeling performance.Experimental results indicate that the BN method performs far better than the least squares(LS)analysis in terms of modeling estimation accuracy.
Thiessen, Erik D
2017-01-05
Statistical learning has been studied in a variety of different tasks, including word segmentation, object identification, category learning, artificial grammar learning and serial reaction time tasks (e.g. Saffran et al. 1996 Science 274: , 1926-1928; Orban et al. 2008 Proceedings of the National Academy of Sciences 105: , 2745-2750; Thiessen & Yee 2010 Child Development 81: , 1287-1303; Saffran 2002 Journal of Memory and Language 47: , 172-196; Misyak & Christiansen 2012 Language Learning 62: , 302-331). The difference among these tasks raises questions about whether they all depend on the same kinds of underlying processes and computations, or whether they are tapping into different underlying mechanisms. Prior theoretical approaches to statistical learning have often tried to explain or model learning in a single task. However, in many cases these approaches appear inadequate to explain performance in multiple tasks. For example, explaining word segmentation via the computation of sequential statistics (such as transitional probability) provides little insight into the nature of sensitivity to regularities among simultaneously presented features. In this article, we will present a formal computational approach that we believe is a good candidate to provide a unifying framework to explore and explain learning in a wide variety of statistical learning tasks. This framework suggests that statistical learning arises from a set of processes that are inherent in memory systems, including activation, interference, integration of information and forgetting (e.g. Perruchet & Vinter 1998 Journal of Memory and Language 39: , 246-263; Thiessen et al. 2013 Psychological Bulletin 139: , 792-814). From this perspective, statistical learning does not involve explicit computation of statistics, but rather the extraction of elements of the input into memory traces, and subsequent integration across those memory traces that emphasize consistent information (Thiessen and Pavlik
Modelling and simulation of thermal power plants
Energy Technology Data Exchange (ETDEWEB)
Eborn, J.
1998-02-01
Mathematical modelling and simulation are important tools when dealing with engineering systems that today are becoming increasingly more complex. Integrated production and recycling of materials are trends that give rise to heterogenous systems, which are difficult to handle within one area of expertise. Model libraries are an excellent way to package engineering knowledge of systems and units to be reused by those who are not experts in modelling. Many commercial packages provide good model libraries, but they are usually domain-specific and closed. Heterogenous, multi-domain systems requires open model libraries written in general purpose modelling languages. This thesis describes a model database for thermal power plants written in the object-oriented modelling language OMOLA. The models are based on first principles. Subunits describe volumes with pressure and enthalpy dynamics and flows of heat or different media. The subunits are used to build basic units such as pumps, valves and heat exchangers which can be used to build system models. Several applications are described; a heat recovery steam generator, equipment for juice blending, steam generation in a sulphuric acid plant and a condensing steam plate heat exchanger. Model libraries for industrial use must be validated against measured data. The thesis describes how parameter estimation methods can be used for model validation. Results from a case-study on parameter optimization of a non-linear drum boiler model show how the technique can be used 32 refs, 21 figs
Models for probability and statistical inference theory and applications
Stapleton, James H
2007-01-01
This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readersModels for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping.Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and random variables; discrete distributions including binomial, hypergeometric, geometric, and Poisson; continuous, normal, gamma, and conditional distributions; and limit theory. Since limit theory is usually the most difficult topic for readers to master, the author thoroughly discusses mo...
Statistical Model Predictions for p+p and Pb+Pb Collisions at LHC
Kraus, I; Oeschler, H; Redlich, K; Wheaton, S
2009-01-01
Particle production in p+p and central Pb+Pb collisions at LHC is discussed in the context of the statistical thermal model. For heavy-ion collisions, predictions of various particle ratios are presented. The sensitivity of several ratios on the temperature and the baryon chemical potential is studied in detail, and some of them, which are particularly appropriate to determine the chemical freeze-out point experimentally, are indicated. Considering elementary interactions on the other hand, we focus on strangeness production and its possible suppression. Extrapolating the thermal parameters to LHC energy, we present predictions of the statistical model for particle yields in p+p collisions. We quantify the strangeness suppression by the correlation volume parameter and discuss its influence on particle production. We propose observables that can provide deeper insight into the mechanism of strangeness production and suppression at LHC.
IEEE Std 101-1972: IEEE guide for the statistical analysis of thermal life test data
International Nuclear Information System (INIS)
Anon.
1992-01-01
Procedures for estimating the thermal life of electrical insulation systems and materials call for life tests at several temperatures, usually well above the expected normal operating temperature. By the selection of high temperatures for the tests, life of the insulation samples will be terminated, according to some selected failure criterion or criteria, within relatively short times -- typically one week to one year. The result of these thermally accelerated life tests will be a set of data of life values for a corresponding set of temperatures. Usually the data consist of a set of life values for each of two to four (occasionally more) test temperatures, 10 C to 25 C apart. The objective then is to establish from these data the mean life vales at each temperature and the functional dependence of life on temperature, as well as the statistical consistency and the confidence to be attributed to the mean life values and the functional life temperature dependence. The purpose of this guide is to assist in this objective and to give guidance for comparing the results of tests on different materials and of different tests on the same materials
Thermal modelling using discrete vasculature for thermal therapy: A review
Kok, H. Petra; Gellermann, Johanna; van den Berg, Cornelis A. T.; Stauffer, Paul R.; Hand, Jeffrey W.; Crezee, Johannes
2013-01-01
Reliable temperature information during clinical hyperthermia and thermal ablation is essential for adequate treatment control, but conventional temperature measurements do not provide 3D temperature information. Treatment planning is a very useful tool to improve treatment quality, and substantial
Stochastic modeling of thermal fatigue crack growth
Radu, Vasile
2015-01-01
The book describes a systematic stochastic modeling approach for assessing thermal-fatigue crack-growth in mixing tees, based on the power spectral density of temperature fluctuation at the inner pipe surface. It shows the development of a frequency-temperature response function in the framework of single-input, single-output (SISO) methodology from random noise/signal theory under sinusoidal input. The frequency response of stress intensity factor (SIF) is obtained by a polynomial fitting procedure of thermal stress profiles at various instants of time. The method, which takes into account the variability of material properties, and has been implemented in a real-world application, estimates the probabilities of failure by considering a limit state function and Monte Carlo analysis, which are based on the proposed stochastic model. Written in a comprehensive and accessible style, this book presents a new and effective method for assessing thermal fatigue crack, and it is intended as a concise and practice-or...
Hierarchic modeling of heat exchanger thermal hydraulics
International Nuclear Information System (INIS)
Horvat, A.; Koncar, B.
2002-01-01
Volume Averaging Technique (VAT) is employed in order to model the heat exchanger cross-flow as a porous media flow. As the averaging of the transport equations lead to a closure problem, separate relations are introduced to model interphase momentum and heat transfer between fluid flow and the solid structure. The hierarchic modeling is used to calculate the local drag coefficient C d as a function of Reynolds number Re h . For that purpose a separate model of REV is built and DNS of flow through REV is performed. The local values of heat transfer coefficient h are obtained from available literature. The geometry of the simulation domain and boundary conditions follow the geometry of the experimental test section used at U.C.L.A. The calculated temperature fields reveal that the geometry with denser pin-fins arrangement (HX1) heats fluid flow faster. The temperature field in the HX2 exhibits the formation of thermal boundary layer between pin-fins, which has a significant role in overall thermal performance of the heat exchanger. Although presented discrepancies of the whole-section drag coefficient C d are large, we believe that hierarchic modeling is an appropriate strategy for calculation of complex transport phenomena in heat exchanger geometries.(author)
Mars Propellant Liquefaction Modeling in Thermal Desktop
Desai, Pooja; Hauser, Dan; Sutherlin, Steven
2017-01-01
NASAs current Mars architectures are assuming the production and storage of 23 tons of liquid oxygen on the surface of Mars over a duration of 500+ days. In order to do this in a mass efficient manner, an energy efficient refrigeration system will be required. Based on previous analysis NASA has decided to do all liquefaction in the propulsion vehicle storage tanks. In order to allow for transient Martian environmental effects, a propellant liquefaction and storage system for a Mars Ascent Vehicle (MAV) was modeled using Thermal Desktop. The model consisted of a propellant tank containing a broad area cooling loop heat exchanger integrated with a reverse turbo Brayton cryocooler. Cryocooler sizing and performance modeling was conducted using MAV diurnal heat loads and radiator rejection temperatures predicted from a previous thermal model of the MAV. A system was also sized and modeled using an alternative heat rejection system that relies on a forced convection heat exchanger. Cryocooler mass, input power, and heat rejection for both systems were estimated and compared against sizing based on non-transient sizing estimates.
Nonlinear thermal reduced model for Microwave Circuit Analysis
Chang, Christophe; Sommet, Raphael; Quéré, Raymond; Dueme, Ph.
2004-01-01
With the constant increase of transistor power density, electro thermal modeling is becoming a necessity for accurate prediction of device electrical performances. For this reason, this paper deals with a methodology to obtain a precise nonlinear thermal model based on Model Order Reduction of a three dimensional thermal Finite Element (FE) description. This reduced thermal model is based on the Ritz vector approach which ensure the steady state solution in every case. An equi...
Development of irradiated UO2 thermal conductivity model
International Nuclear Information System (INIS)
Lee, Chan Bock; Bang Je-Geon; Kim Dae Ho; Jung Youn Ho
2001-01-01
Thermal conductivity model of the irradiated UO 2 pellet was developed, based upon the thermal diffusivity data of the irradiated UO 2 pellet measured during thermal cycling. The model predicts the thermal conductivity by multiplying such separate correction factors as solid fission products, gaseous fission products, radiation damage and porosity. The developed model was validated by comparison with the variation of the measured thermal diffusivity data during thermal cycling and prediction of other UO 2 thermal conductivity models. Since the developed model considers the effect of gaseous fission products as a separate factor, it can predict variation of thermal conductivity in the rim region of high burnup UO 2 pellet where the fission gases in the matrix are precipitated into bubbles, indicating that decrease of thermal conductivity by bubble precipitation in rim region would be significantly compensated by the enhancing effect of fission gas depletion in the UO 2 matrix. (author)
Investigating the thermal dissociation of viral capsid by lattice model
Chen, Jingzhi; Chevreuil, Maelenn; Combet, Sophie; Lansac, Yves; Tresset, Guillaume
2017-11-01
The dissociation of icosahedral viral capsids was investigated by a homogeneous and a heterogeneous lattice model. In thermal dissociation experiments with cowpea chlorotic mottle virus and probed by small-angle neutron scattering, we observed a slight shrinkage of viral capsids, which can be related to the strengthening of the hydrophobic interaction between subunits at increasing temperature. By considering the temperature dependence of hydrophobic interaction in the homogeneous lattice model, we were able to give a better estimate of the effective charge. In the heterogeneous lattice model, two sets of lattice sites represented different capsid subunits with asymmetric interaction strengths. In that case, the dissociation of capsids was found to shift from a sharp one-step transition to a gradual two-step transition by weakening the hydrophobic interaction between AB and CC subunits. We anticipate that such lattice models will shed further light on the statistical mechanics underlying virus assembly and disassembly.
Right-sizing statistical models for longitudinal data.
Wood, Phillip K; Steinley, Douglas; Jackson, Kristina M
2015-12-01
Arguments are proposed that researchers using longitudinal data should consider more and less complex statistical model alternatives to their initially chosen techniques in an effort to "right-size" the model to the data at hand. Such model comparisons may alert researchers who use poorly fitting, overly parsimonious models to more complex, better-fitting alternatives and, alternatively, may identify more parsimonious alternatives to overly complex (and perhaps empirically underidentified and/or less powerful) statistical models. A general framework is proposed for considering (often nested) relationships between a variety of psychometric and growth curve models. A 3-step approach is proposed in which models are evaluated based on the number and patterning of variance components prior to selection of better-fitting growth models that explain both mean and variation-covariation patterns. The orthogonal free curve slope intercept (FCSI) growth model is considered a general model that includes, as special cases, many models, including the factor mean (FM) model (McArdle & Epstein, 1987), McDonald's (1967) linearly constrained factor model, hierarchical linear models (HLMs), repeated-measures multivariate analysis of variance (MANOVA), and the linear slope intercept (linearSI) growth model. The FCSI model, in turn, is nested within the Tuckerized factor model. The approach is illustrated by comparing alternative models in a longitudinal study of children's vocabulary and by comparing several candidate parametric growth and chronometric models in a Monte Carlo study. (c) 2015 APA, all rights reserved).
Simple models of the thermal structure of the Venusian ionosphere
International Nuclear Information System (INIS)
Whitten, R.C.; Knudsen, W.C.
1980-01-01
Analytical and numerical models of plasma temperatures in the Venusian ionosphere are proposed. The magnitudes of plasma thermal parameters are calculated using thermal-structure data obtained by the Pioneer Venus Orbiter. The simple models are found to be in good agreement with the more detailed models of thermal balance. Daytime and nighttime temperature data along with corresponding temperature profiles are provided
A Stochastic Fractional Dynamics Model of Rainfall Statistics
Kundu, Prasun; Travis, James
2013-04-01
Rainfall varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, that allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is designed to faithfully reflect the scale dependence and is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and times scales. The main restriction is the assumption that the statistics of the precipitation field is spatially homogeneous and isotropic and stationary in time. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and in Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to the second moment statistics of the radar data. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well without any further adjustment. Some data sets containing periods of non-stationary behavior that involves occasional anomalously correlated rain events, present a challenge for the model.
THERMUS—A thermal model package for ROOT
Wheaton, S.; Cleymans, J.; Hauer, M.
2009-01-01
THERMUS is a package of C++ classes and functions allowing statistical-thermal model analyses of particle production in relativistic heavy-ion collisions to be performed within the ROOT framework of analysis. Calculations are possible within three statistical ensembles; a grand-canonical treatment of the conserved charges B, S and Q, a fully canonical treatment of the conserved charges, and a mixed-canonical ensemble combining a canonical treatment of strangeness with a grand-canonical treatment of baryon number and electric charge. THERMUS allows for the assignment of decay chains and detector efficiencies specific to each particle yield, which enables sensible fitting of model parameters to experimental data. Program summaryProgram title: THERMUS, version 2.1 Catalogue identifier: AEBW_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEBW_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 17 152 No. of bytes in distributed program, including test data, etc.: 93 581 Distribution format: tar.gz Programming language: C++ Computer: PC, Pentium 4, 1 GB RAM (not hardware dependent) Operating system: Linux: FEDORA, RedHat, etc. Classification: 17.7 External routines: Numerical Recipes in C [1], ROOT [2] Nature of problem: Statistical-thermal model analyses of heavy-ion collision data require the calculation of both primordial particle densities and contributions from resonance decay. A set of thermal parameters (the number depending on the particular model imposed) and a set of thermalized particles, with their decays specified, is required as input to these models. The output is then a complete set of primordial thermal quantities for each particle, together with the contributions to the final particle yields from resonance decay. In many applications of
The thermal evolution of universe: standard model
International Nuclear Information System (INIS)
Nascimento, L.C.S. do.
1975-08-01
A description of the dynamical evolution of the Universe following a model based on the theory of General Relativity is made. The model admits the Cosmological principle,the principle of Equivalence and the Robertson-Walker metric (of which an original derivation is presented). In this model, the universe is considered as a perfect fluid, ideal and symmetric relatively to the number of particles and antiparticles. The thermodynamic relations deriving from these hypothesis are derived, and from them the several eras of the thermal evolution of the universe are established. Finally, the problems arising from certain specific predictions of the model are studied, and the predictions of the abundances of the elements according to nucleosynthesis and the actual behavior of the universe are analysed in detail. (author) [pt
Variability aware compact model characterization for statistical circuit design optimization
Qiao, Ying; Qian, Kun; Spanos, Costas J.
2012-03-01
Variability modeling at the compact transistor model level can enable statistically optimized designs in view of limitations imposed by the fabrication technology. In this work we propose an efficient variabilityaware compact model characterization methodology based on the linear propagation of variance. Hierarchical spatial variability patterns of selected compact model parameters are directly calculated from transistor array test structures. This methodology has been implemented and tested using transistor I-V measurements and the EKV-EPFL compact model. Calculation results compare well to full-wafer direct model parameter extractions. Further studies are done on the proper selection of both compact model parameters and electrical measurement metrics used in the method.
Linear mixed models a practical guide using statistical software
West, Brady T; Galecki, Andrzej T
2006-01-01
Simplifying the often confusing array of software programs for fitting linear mixed models (LMMs), Linear Mixed Models: A Practical Guide Using Statistical Software provides a basic introduction to primary concepts, notation, software implementation, model interpretation, and visualization of clustered and longitudinal data. This easy-to-navigate reference details the use of procedures for fitting LMMs in five popular statistical software packages: SAS, SPSS, Stata, R/S-plus, and HLM. The authors introduce basic theoretical concepts, present a heuristic approach to fitting LMMs based on bo
Speech emotion recognition based on statistical pitch model
Institute of Scientific and Technical Information of China (English)
WANG Zhiping; ZHAO Li; ZOU Cairong
2006-01-01
A modified Parzen-window method, which keep high resolution in low frequencies and keep smoothness in high frequencies, is proposed to obtain statistical model. Then, a gender classification method utilizing the statistical model is proposed, which have a 98% accuracy of gender classification while long sentence is dealt with. By separation the male voice and female voice, the mean and standard deviation of speech training samples with different emotion are used to create the corresponding emotion models. Then the Bhattacharyya distance between the test sample and statistical models of pitch, are utilized for emotion recognition in speech.The normalization of pitch for the male voice and female voice are also considered, in order to illustrate them into a uniform space. Finally, the speech emotion recognition experiment based on K Nearest Neighbor shows that, the correct rate of 81% is achieved, where it is only 73.85%if the traditional parameters are utilized.
Multiple commodities in statistical microeconomics: Model and market
Baaquie, Belal E.; Yu, Miao; Du, Xin
2016-11-01
A statistical generalization of microeconomics has been made in Baaquie (2013). In Baaquie et al. (2015), the market behavior of single commodities was analyzed and it was shown that market data provides strong support for the statistical microeconomic description of commodity prices. The case of multiple commodities is studied and a parsimonious generalization of the single commodity model is made for the multiple commodities case. Market data shows that the generalization can accurately model the simultaneous correlation functions of up to four commodities. To accurately model five or more commodities, further terms have to be included in the model. This study shows that the statistical microeconomics approach is a comprehensive and complete formulation of microeconomics, and which is independent to the mainstream formulation of microeconomics.
Adaptive Maneuvering Frequency Method of Current Statistical Model
Institute of Scientific and Technical Information of China (English)
Wei Sun; Yongjian Yang
2017-01-01
Current statistical model(CSM) has a good performance in maneuvering target tracking. However, the fixed maneuvering frequency will deteriorate the tracking results, such as a serious dynamic delay, a slowly converging speedy and a limited precision when using Kalman filter(KF) algorithm. In this study, a new current statistical model and a new Kalman filter are proposed to improve the performance of maneuvering target tracking. The new model which employs innovation dominated subjection function to adaptively adjust maneuvering frequency has a better performance in step maneuvering target tracking, while a fluctuant phenomenon appears. As far as this problem is concerned, a new adaptive fading Kalman filter is proposed as well. In the new Kalman filter, the prediction values are amended in time by setting judgment and amendment rules,so that tracking precision and fluctuant phenomenon of the new current statistical model are improved. The results of simulation indicate the effectiveness of the new algorithm and the practical guiding significance.
Modelling diversity in building occupant behaviour: a novel statistical approach
DEFF Research Database (Denmark)
Haldi, Frédéric; Calì, Davide; Andersen, Rune Korsholm
2016-01-01
We propose an advanced modelling framework to predict the scope and effects of behavioural diversity regarding building occupant actions on window openings, shading devices and lighting. We develop a statistical approach based on generalised linear mixed models to account for the longitudinal nat...
A classical statistical model of heavy ion collisions
International Nuclear Information System (INIS)
Schmidt, R.; Teichert, J.
1980-01-01
The use of the computer code TRAJEC which represents the numerical realization of a classical statistical model for heavy ion collisions is described. The code calculates the results of a classical friction model as well as various multi-differential cross sections for heavy ion collisions. INPUT and OUTPUT information of the code are described. Two examples of data sets are given [ru
On an uncorrelated jet model with Bose-Einstein statistics
International Nuclear Information System (INIS)
Bilic, N.; Dadic, I.; Martinis, M.
1978-01-01
Starting from the density of states of an ideal Bose-Einstein gas, an uncorrelated jet model with Bose-Einstein statistics has been formulated. The transition to continuum is based on the Touschek invariant measure. It has been shown that in this model average multiplicity increases logarithmically with total energy, while the inclusive distribution shows ln s violation of scaling. (author)
Complex Data Modeling and Computationally Intensive Statistical Methods
Mantovan, Pietro
2010-01-01
The last years have seen the advent and development of many devices able to record and store an always increasing amount of complex and high dimensional data; 3D images generated by medical scanners or satellite remote sensing, DNA microarrays, real time financial data, system control datasets. The analysis of this data poses new challenging problems and requires the development of novel statistical models and computational methods, fueling many fascinating and fast growing research areas of modern statistics. The book offers a wide variety of statistical methods and is addressed to statistici
Validation of statistical models for creep rupture by parametric analysis
Energy Technology Data Exchange (ETDEWEB)
Bolton, J., E-mail: john.bolton@uwclub.net [65, Fisher Ave., Rugby, Warks CV22 5HW (United Kingdom)
2012-01-15
Statistical analysis is an efficient method for the optimisation of any candidate mathematical model of creep rupture data, and for the comparative ranking of competing models. However, when a series of candidate models has been examined and the best of the series has been identified, there is no statistical criterion to determine whether a yet more accurate model might be devised. Hence there remains some uncertainty that the best of any series examined is sufficiently accurate to be considered reliable as a basis for extrapolation. This paper proposes that models should be validated primarily by parametric graphical comparison to rupture data and rupture gradient data. It proposes that no mathematical model should be considered reliable for extrapolation unless the visible divergence between model and data is so small as to leave no apparent scope for further reduction. This study is based on the data for a 12% Cr alloy steel used in BS PD6605:1998 to exemplify its recommended statistical analysis procedure. The models considered in this paper include a) a relatively simple model, b) the PD6605 recommended model and c) a more accurate model of somewhat greater complexity. - Highlights: Black-Right-Pointing-Pointer The paper discusses the validation of creep rupture models derived from statistical analysis. Black-Right-Pointing-Pointer It demonstrates that models can be satisfactorily validated by a visual-graphic comparison of models to data. Black-Right-Pointing-Pointer The method proposed utilises test data both as conventional rupture stress and as rupture stress gradient. Black-Right-Pointing-Pointer The approach is shown to be more reliable than a well-established and widely used method (BS PD6605).
Directory of Open Access Journals (Sweden)
Masaru Ishizuka
2011-01-01
Full Text Available In recent years, there is a growing demand to have smaller and lighter electronic circuits which have greater complexity, multifunctionality, and reliability. High-density multichip packaging technology has been used in order to meet these requirements. The higher the density scale is, the larger the power dissipation per unit area becomes. Therefore, in the designing process, it has become very important to carry out the thermal analysis. However, the heat transport model in multichip modules is very complex, and its treatment is tedious and time consuming. This paper describes an application of the thermal network method to the transient thermal analysis of multichip modules and proposes a simple model for the thermal analysis of multichip modules as a preliminary thermal design tool. On the basis of the result of transient thermal analysis, the validity of the thermal network method and the simple thermal analysis model is confirmed.
Thermal effects in shales: measurements and modeling
International Nuclear Information System (INIS)
McKinstry, H.A.
1977-01-01
Research is reported concerning thermal and physical measurements and theoretical modeling relevant to the storage of radioactive wastes in a shale. Reference thermal conductivity measurements are made at atmospheric pressure in a commercial apparatus; and equipment for permeability measurements has been developed, and is being extended with respect to measurement ranges. Thermal properties of shales are being determined as a function of temperature and pressures. Apparatus was developed to measure shales in two different experimental configurations. In the first, a disk 15 mm in diameter of the material is measured by a steady state technique using a reference material to measure the heat flow within the system. The sample is sandwiched between two disks of a reference material (single crystal quartz is being used initially as reference material). The heat flow is determined twice in order to determine that steady state conditions prevail; the temperature drop over the two references is measured. When these indicate an equal heat flow, the thermal conductivity of the sample can be calculated from the temperature difference of the two faces. The second technique is for determining effect of temperature in a water saturated shale on a larger scale. Cylindrical shale (or siltstone) specimens that are being studied (large for a laboratory sample) are to be heated electrically at the center, contained in a pressure vessel that will maintain a fixed water pressure around it. The temperature is monitored at many points within the shale sample. The sample dimensions are 25 cm diameter, 20 cm long. A micro computer system has been constructed to monitor 16 thermocouples to record variation of temperature distribution with time
Thermal modelling of a torpedo-car
Energy Technology Data Exchange (ETDEWEB)
Verdeja-Gonzalez, L. F.; Barbes-Fernandez, M. F.; Gonzalez-Ojeda, R.; Castillo, G. A.; Colas, R.
2005-07-01
A two-dimensional finite element model for computing the temperature distribution in a torpedo-car holding pig iron is described in this work. The model determines the temperature gradients in steady and transient conditions whiting the different parts that constitute the systems, which are considered to be the steel casing, refractory lining, liquid iron, slag and air. Heat transfer within the main fluid phases (iron and air) is computed assuming an apparent thermal conductivity term incorporating the contribution from convention and radiation, and it is affected by the dimensions of the vessel. Thermal gradients within the constituents of the torpedo-car are used to calculate heat losses during operation. It was found that the model required the incorporate of a region within the iron-refractory interface to reproduce thermographic data recorded during operation; the heat transfer coefficient of this interface was found to be equal to 30 Wm''-2K''-1. (Author) 11 refs.
Understanding and forecasting polar stratospheric variability with statistical models
Directory of Open Access Journals (Sweden)
C. Blume
2012-07-01
Full Text Available The variability of the north-polar stratospheric vortex is a prominent aspect of the middle atmosphere. This work investigates a wide class of statistical models with respect to their ability to model geopotential and temperature anomalies, representing variability in the polar stratosphere. Four partly nonstationary, nonlinear models are assessed: linear discriminant analysis (LDA; a cluster method based on finite elements (FEM-VARX; a neural network, namely the multi-layer perceptron (MLP; and support vector regression (SVR. These methods model time series by incorporating all significant external factors simultaneously, including ENSO, QBO, the solar cycle, volcanoes, to then quantify their statistical importance. We show that variability in reanalysis data from 1980 to 2005 is successfully modeled. The period from 2005 to 2011 can be hindcasted to a certain extent, where MLP performs significantly better than the remaining models. However, variability remains that cannot be statistically hindcasted within the current framework, such as the unexpected major warming in January 2009. Finally, the statistical model with the best generalization performance is used to predict a winter 2011/12 with warm and weak vortex conditions. A vortex breakdown is predicted for late January, early February 2012.
System model development for nuclear thermal propulsion
International Nuclear Information System (INIS)
Walton, J.T.; Perkins, K.R.; Buksa, J.J.; Worley, B.A.; Dobranich, D.
1992-01-01
A critical enabling technology in the evolutionary development of nuclear thermal propulsion (NTP) is the ability to predict the system performance under a variety of operating conditions. Since October 1991, US (DOE), (DOD) and NASA have initiated critical technology development efforts for NTP systems to be used on Space Exploration Initiative (SEI) missions to the Moon and Mars. This paper presents the strategy and progress of an interagency NASA/DOE/DOD team for NTP system modeling. It is the intent of the interagency team to develop several levels of computer programs to simulate various NTP systems. An interagency team was formed for this task to use the best capabilities available and to assure appropriate peer review. The vision and strategy of the interagency team for developing NTP system models will be discussed in this paper. A review of the progress on the Level 1 interagency model is also presented
Statistical Validation of Normal Tissue Complication Probability Models
Energy Technology Data Exchange (ETDEWEB)
Xu Chengjian, E-mail: c.j.xu@umcg.nl [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schaaf, Arjen van der; Veld, Aart A. van' t; Langendijk, Johannes A. [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schilstra, Cornelis [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Radiotherapy Institute Friesland, Leeuwarden (Netherlands)
2012-09-01
Purpose: To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. Methods and Materials: A penalized regression method, LASSO (least absolute shrinkage and selection operator), was used to build NTCP models for xerostomia after radiation therapy treatment of head-and-neck cancer. Model assessment was based on the likelihood function and the area under the receiver operating characteristic curve. Results: Repeated double cross-validation showed the uncertainty and instability of the NTCP models and indicated that the statistical significance of model performance can be obtained by permutation testing. Conclusion: Repeated double cross-validation and permutation tests are recommended to validate NTCP models before clinical use.
Statistical validation of normal tissue complication probability models.
Xu, Cheng-Jian; van der Schaaf, Arjen; Van't Veld, Aart A; Langendijk, Johannes A; Schilstra, Cornelis
2012-09-01
To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. A penalized regression method, LASSO (least absolute shrinkage and selection operator), was used to build NTCP models for xerostomia after radiation therapy treatment of head-and-neck cancer. Model assessment was based on the likelihood function and the area under the receiver operating characteristic curve. Repeated double cross-validation showed the uncertainty and instability of the NTCP models and indicated that the statistical significance of model performance can be obtained by permutation testing. Repeated double cross-validation and permutation tests are recommended to validate NTCP models before clinical use. Copyright © 2012 Elsevier Inc. All rights reserved.
Shell model in large spaces and statistical spectroscopy
International Nuclear Information System (INIS)
Kota, V.K.B.
1996-01-01
For many nuclear structure problems of current interest it is essential to deal with shell model in large spaces. For this, three different approaches are now in use and two of them are: (i) the conventional shell model diagonalization approach but taking into account new advances in computer technology; (ii) the shell model Monte Carlo method. A brief overview of these two methods is given. Large space shell model studies raise fundamental questions regarding the information content of the shell model spectrum of complex nuclei. This led to the third approach- the statistical spectroscopy methods. The principles of statistical spectroscopy have their basis in nuclear quantum chaos and they are described (which are substantiated by large scale shell model calculations) in some detail. (author)
Computationally efficient statistical differential equation modeling using homogenization
Hooten, Mevin B.; Garlick, Martha J.; Powell, James A.
2013-01-01
Statistical models using partial differential equations (PDEs) to describe dynamically evolving natural systems are appearing in the scientific literature with some regularity in recent years. Often such studies seek to characterize the dynamics of temporal or spatio-temporal phenomena such as invasive species, consumer-resource interactions, community evolution, and resource selection. Specifically, in the spatial setting, data are often available at varying spatial and temporal scales. Additionally, the necessary numerical integration of a PDE may be computationally infeasible over the spatial support of interest. We present an approach to impose computationally advantageous changes of support in statistical implementations of PDE models and demonstrate its utility through simulation using a form of PDE known as “ecological diffusion.” We also apply a statistical ecological diffusion model to a data set involving the spread of mountain pine beetle (Dendroctonus ponderosae) in Idaho, USA.
Growth Curve Models and Applications : Indian Statistical Institute
2017-01-01
Growth curve models in longitudinal studies are widely used to model population size, body height, biomass, fungal growth, and other variables in the biological sciences, but these statistical methods for modeling growth curves and analyzing longitudinal data also extend to general statistics, economics, public health, demographics, epidemiology, SQC, sociology, nano-biotechnology, fluid mechanics, and other applied areas. There is no one-size-fits-all approach to growth measurement. The selected papers in this volume build on presentations from the GCM workshop held at the Indian Statistical Institute, Giridih, on March 28-29, 2016. They represent recent trends in GCM research on different subject areas, both theoretical and applied. This book includes tools and possibilities for further work through new techniques and modification of existing ones. The volume includes original studies, theoretical findings and case studies from a wide range of app lied work, and these contributions have been externally r...
Statistical modelling for recurrent events: an application to sports injuries.
Ullah, Shahid; Gabbett, Tim J; Finch, Caroline F
2014-09-01
Injuries are often recurrent, with subsequent injuries influenced by previous occurrences and hence correlation between events needs to be taken into account when analysing such data. This paper compares five different survival models (Cox proportional hazards (CoxPH) model and the following generalisations to recurrent event data: Andersen-Gill (A-G), frailty, Wei-Lin-Weissfeld total time (WLW-TT) marginal, Prentice-Williams-Peterson gap time (PWP-GT) conditional models) for the analysis of recurrent injury data. Empirical evaluation and comparison of different models were performed using model selection criteria and goodness-of-fit statistics. Simulation studies assessed the size and power of each model fit. The modelling approach is demonstrated through direct application to Australian National Rugby League recurrent injury data collected over the 2008 playing season. Of the 35 players analysed, 14 (40%) players had more than 1 injury and 47 contact injuries were sustained over 29 matches. The CoxPH model provided the poorest fit to the recurrent sports injury data. The fit was improved with the A-G and frailty models, compared to WLW-TT and PWP-GT models. Despite little difference in model fit between the A-G and frailty models, in the interest of fewer statistical assumptions it is recommended that, where relevant, future studies involving modelling of recurrent sports injury data use the frailty model in preference to the CoxPH model or its other generalisations. The paper provides a rationale for future statistical modelling approaches for recurrent sports injury. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Review of computational thermal-hydraulic modeling
International Nuclear Information System (INIS)
Keefer, R.H.; Keeton, L.W.
1995-01-01
Corrosion of heat transfer tubing in nuclear steam generators has been a persistent problem in the power generation industry, assuming many different forms over the years depending on chemistry and operating conditions. Whatever the corrosion mechanism, a fundamental understanding of the process is essential to establish effective management strategies. To gain this fundamental understanding requires an integrated investigative approach that merges technology from many diverse scientific disciplines. An important aspect of an integrated approach is characterization of the corrosive environment at high temperature. This begins with a thorough understanding of local thermal-hydraulic conditions, since they affect deposit formation, chemical concentration, and ultimately corrosion. Computational Fluid Dynamics (CFD) can and should play an important role in characterizing the thermal-hydraulic environment and in predicting the consequences of that environment,. The evolution of CFD technology now allows accurate calculation of steam generator thermal-hydraulic conditions and the resulting sludge deposit profiles. Similar calculations are also possible for model boilers, so that tests can be designed to be prototypic of the heat exchanger environment they are supposed to simulate. This paper illustrates the utility of CFD technology by way of examples in each of these two areas. This technology can be further extended to produce more detailed local calculations of the chemical environment in support plate crevices, beneath thick deposits on tubes, and deep in tubesheet sludge piles. Knowledge of this local chemical environment will provide the foundation for development of mechanistic corrosion models, which can be used to optimize inspection and cleaning schedules and focus the search for a viable fix
Model of thermal conductivity of anisotropic nanodiamond
International Nuclear Information System (INIS)
Dudnik, S.F.; Kalinichenko, A.I.; Strel'nitskij, V.E.
2014-01-01
Dependence of thermal conductivity of nanocrystalline diamond on grain size and shape is theoretically investigated. Nanodiamond is considered as two-phase material composed of diamond grains characterizing by three main dimensions and segregated by thin graphite layers with electron, phonon or hybrid thermal conductivity. Influence of type of thermal conductance and thickness of boundary layer on thermal conductivity of nanodiamond is analyzed. Derived dependences of thermal conductivity on grain dimensions are compared with experimental data
Statistical Model of the 2001 Czech Census for Interactive Presentation
Czech Academy of Sciences Publication Activity Database
Grim, Jiří; Hora, Jan; Boček, Pavel; Somol, Petr; Pudil, Pavel
Vol. 26, č. 4 (2010), s. 1-23 ISSN 0282-423X R&D Projects: GA ČR GA102/07/1594; GA MŠk 1M0572 Grant - others:GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : Interactive statistical model * census data presentation * distribution mixtures * data modeling * EM algorithm * incomplete data * data reproduction accuracy * data mining Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.492, year: 2010 http://library.utia.cas.cz/separaty/2010/RO/grim-0350513.pdf
The Statistical Modeling of the Trends Concerning the Romanian Population
Directory of Open Access Journals (Sweden)
Gabriela OPAIT
2014-11-01
Full Text Available This paper reflects the statistical modeling concerning the resident population in Romania, respectively the total of the romanian population, through by means of the „Least Squares Method”. Any country it develops by increasing of the population, respectively of the workforce, which is a factor of influence for the growth of the Gross Domestic Product (G.D.P.. The „Least Squares Method” represents a statistical technique for to determine the trend line of the best fit concerning a model.
Kellerer-Pirklbauer, Andreas
2016-04-01
Longer data series (e.g. >10 a) of ground temperatures in alpine regions are helpful to improve the understanding regarding the effects of present climate change on distribution and thermal characteristics of seasonal frost- and permafrost-affected areas. Beginning in 2004 - and more intensively since 2006 - a permafrost and seasonal frost monitoring network was established in Central and Eastern Austria by the University of Graz. This network consists of c.60 ground temperature (surface and near-surface) monitoring sites which are located at 1922-3002 m a.s.l., at latitude 46°55'-47°22'N and at longitude 12°44'-14°41'E. These data allow conclusions about general ground thermal conditions, potential permafrost occurrence, trend during the observation period, and regional pattern of changes. Calculations and analyses of several different temperature-related parameters were accomplished. At an annual scale a region-wide statistical significant warming during the observation period was revealed by e.g. an increase in mean annual temperature values (mean, maximum) or the significant lowering of the surface frost number (F+). At a seasonal scale no significant trend of any temperature-related parameter was in most cases revealed for spring (MAM) and autumn (SON). Winter (DJF) shows only a weak warming. In contrast, the summer (JJA) season reveals in general a significant warming as confirmed by several different temperature-related parameters such as e.g. mean seasonal temperature, number of thawing degree days, number of freezing degree days, or days without night frost. On a monthly basis August shows the statistically most robust and strongest warming of all months, although regional differences occur. Despite the fact that the general ground temperature warming during the last decade is confirmed by the field data in the study region, complications in trend analyses arise by temperature anomalies (e.g. warm winter 2006/07) or substantial variations in the winter
Thermal-mechanical deformation modelling of soft tissues for thermal ablation.
Li, Xin; Zhong, Yongmin; Jazar, Reza; Subic, Aleksandar
2014-01-01
Modeling of thermal-induced mechanical behaviors of soft tissues is of great importance for thermal ablation. This paper presents a method by integrating the heating process with thermal-induced mechanical deformations of soft tissues for simulation and analysis of the thermal ablation process. This method combines bio-heat transfer theories, constitutive elastic material law under thermal loads as well as non-rigid motion dynamics to predict and analyze thermal-mechanical deformations of soft tissues. The 3D governing equations of thermal-mechanical soft tissue deformation are discretized by using the finite difference scheme and are subsequently solved by numerical algorithms. Experimental results show that the proposed method can effectively predict the thermal-induced mechanical behaviors of soft tissues, and can be used for the thermal ablation therapy to effectively control the delivered heat energy for cancer treatment.
In-situ measurements of material thermal parameters for accurate LED lamp thermal modelling
Vellvehi, M.; Perpina, X.; Jorda, X.; Werkhoven, R.J.; Kunen, J.M.G.; Jakovenko, J.; Bancken, P.; Bolt, P.J.
2013-01-01
This work deals with the extraction of key thermal parameters for accurate thermal modelling of LED lamps: air exchange coefficient around the lamp, emissivity and thermal conductivity of all lamp parts. As a case study, an 8W retrofit lamp is presented. To assess simulation results, temperature is
Argonne Bubble Experiment Thermal Model Development III
Energy Technology Data Exchange (ETDEWEB)
Buechler, Cynthia Eileen [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2018-01-11
This report describes the continuation of the work reported in “Argonne Bubble Experiment Thermal Model Development” and “Argonne Bubble Experiment Thermal Model Development II”. The experiment was performed at Argonne National Laboratory (ANL) in 2014. A rastered 35 MeV electron beam deposited power in a solution of uranyl sulfate, generating heat and radiolytic gas bubbles. Irradiations were performed at beam power levels between 6 and 15 kW. Solution temperatures were measured by thermocouples, and gas bubble behavior was recorded. The previous report2 described the Monte-Carlo N-Particle (MCNP) calculations and Computational Fluid Dynamics (CFD) analysis performed on the as-built solution vessel geometry. The CFD simulations in the current analysis were performed using Ansys Fluent, Ver. 17.2. The same power profiles determined from MCNP calculations in earlier work were used for the 12 and 15 kW simulations. The primary goal of the current work is to calculate the temperature profiles for the 12 and 15 kW cases using reasonable estimates for the gas generation rate, based on images of the bubbles recorded during the irradiations. Temperature profiles resulting from the CFD calculations are compared to experimental measurements.
Applied systems ecology: models, data, and statistical methods
Energy Technology Data Exchange (ETDEWEB)
Eberhardt, L L
1976-01-01
In this report, systems ecology is largely equated to mathematical or computer simulation modelling. The need for models in ecology stems from the necessity to have an integrative device for the diversity of ecological data, much of which is observational, rather than experimental, as well as from the present lack of a theoretical structure for ecology. Different objectives in applied studies require specialized methods. The best predictive devices may be regression equations, often non-linear in form, extracted from much more detailed models. A variety of statistical aspects of modelling, including sampling, are discussed. Several aspects of population dynamics and food-chain kinetics are described, and it is suggested that the two presently separated approaches should be combined into a single theoretical framework. It is concluded that future efforts in systems ecology should emphasize actual data and statistical methods, as well as modelling.
Analyzing sickness absence with statistical models for survival data
DEFF Research Database (Denmark)
Christensen, Karl Bang; Andersen, Per Kragh; Smith-Hansen, Lars
2007-01-01
OBJECTIVES: Sickness absence is the outcome in many epidemiologic studies and is often based on summary measures such as the number of sickness absences per year. In this study the use of modern statistical methods was examined by making better use of the available information. Since sickness...... absence data deal with events occurring over time, the use of statistical models for survival data has been reviewed, and the use of frailty models has been proposed for the analysis of such data. METHODS: Three methods for analyzing data on sickness absences were compared using a simulation study...... involving the following: (i) Poisson regression using a single outcome variable (number of sickness absences), (ii) analysis of time to first event using the Cox proportional hazards model, and (iii) frailty models, which are random effects proportional hazards models. Data from a study of the relation...
A Review of Modeling Bioelectrochemical Systems: Engineering and Statistical Aspects
Directory of Open Access Journals (Sweden)
Shuai Luo
2016-02-01
Full Text Available Bioelectrochemical systems (BES are promising technologies to convert organic compounds in wastewater to electrical energy through a series of complex physical-chemical, biological and electrochemical processes. Representative BES such as microbial fuel cells (MFCs have been studied and advanced for energy recovery. Substantial experimental and modeling efforts have been made for investigating the processes involved in electricity generation toward the improvement of the BES performance for practical applications. However, there are many parameters that will potentially affect these processes, thereby making the optimization of system performance hard to be achieved. Mathematical models, including engineering models and statistical models, are powerful tools to help understand the interactions among the parameters in BES and perform optimization of BES configuration/operation. This review paper aims to introduce and discuss the recent developments of BES modeling from engineering and statistical aspects, including analysis on the model structure, description of application cases and sensitivity analysis of various parameters. It is expected to serves as a compass for integrating the engineering and statistical modeling strategies to improve model accuracy for BES development.
A thermal model of the economy
Arroyo Colon, Luis Balbino
The motivation for this work came from an interest in Economics (particularly since the 2008 economic downturn) and a desire to use the tools of physics in a field that has not been the subject of great exploration. We propose a model of economics in analogy to thermodynamics and introduce the concept of the Value Multiplier as a fundamental addition to any such model. Firstly, we attempt to make analogies between some economic concepts and fundamental concepts of thermal physics. Then we introduce the value multiplier and justify its existence in our system; the value multiplier allows us to account for some intangible, psychological elements of the value of goods and services. We finally bring all the elements together in a qualitative system. In particular, we attempt to make an analogy with the Keynesian Multiplier that justifies the usefulness of fiscal stimulus in severe economic downturns. ii
Thermal models of pulse electrochemical machining
International Nuclear Information System (INIS)
Kozak, J.
2004-01-01
Pulse electrochemical machining (PECM) provides an economical and effective method for machining high strength, heat-resistant materials into complex shapes such as turbine blades, die, molds and micro cavities. Pulse Electrochemical Machining involves the application of a voltage pulse at high current density in the anodic dissolution process. Small interelectrode gap, low electrolyte flow rate, gap state recovery during the pulse off-times lead to improved machining accuracy and surface finish when compared with ECM using continuous current. This paper presents a mathematical model for PECM and employs this model in a computer simulation of the PECM process for determination of the thermal limitation and energy consumption in PECM. The experimental results and discussion of the characteristics PECM are presented. (authors)
Aquifer thermal-energy-storage modeling
Schaetzle, W. J.; Lecroy, J. E.
1982-09-01
A model aquifer was constructed to simulate the operation of a full size aquifer. Instrumentation to evaluate the water flow and thermal energy storage was installed in the system. Numerous runs injecting warm water into a preconditioned uniform aquifer were made. Energy recoveries were evaluated and agree with comparisons of other limited available data. The model aquifer is simulated in a swimming pool, 18 ft by 4 ft, which was filled with sand. Temperature probes were installed in the system. A 2 ft thick aquifer is confined by two layers of polyethylene. Both the aquifer and overburden are sand. Four well configurations are available. The system description and original tests, including energy recovery, are described.
Thermal Models of the Niger Delta: Implications for Charge Modelling
International Nuclear Information System (INIS)
Ejedawe, J.
2002-01-01
There are generally three main sources of temperature data-BHT data from log headers, production temperature data, and continuo's temperature logs. Analysis of continuous temperature profiles of over 100 wells in the Niger Delta two main thermal models (single leg and dogleg) are defined with occasional occurrence of a modified dogleg model.The dogleg model is characterised by a shallow interval of low geothermal gradient ( 3.0.C/100m). This is characteristically developed onshore area is simple, requiring only consideration of heat transients, modelling in the onshore require modelling programmes with built in modules to handle convective heat flow dissipation in the shallow layer. Current work around methods would involve tweaking of thermal conductivity values to mimic the underlying heat flow process effects, or heat flow mapping above and below the depth of gradient change. These methods allow for more realistic thermal modelling, hydrocarbon type prediction, and also more accurate prediction of temperature prior to drilling and for reservoir rock properties. The regional distribution of the models also impact on regional hydrocarbon distribution pattern in the Niger Delta
New robust statistical procedures for the polytomous logistic regression models.
Castilla, Elena; Ghosh, Abhik; Martin, Nirian; Pardo, Leandro
2018-05-17
This article derives a new family of estimators, namely the minimum density power divergence estimators, as a robust generalization of the maximum likelihood estimator for the polytomous logistic regression model. Based on these estimators, a family of Wald-type test statistics for linear hypotheses is introduced. Robustness properties of both the proposed estimators and the test statistics are theoretically studied through the classical influence function analysis. Appropriate real life examples are presented to justify the requirement of suitable robust statistical procedures in place of the likelihood based inference for the polytomous logistic regression model. The validity of the theoretical results established in the article are further confirmed empirically through suitable simulation studies. Finally, an approach for the data-driven selection of the robustness tuning parameter is proposed with empirical justifications. © 2018, The International Biometric Society.
Berrios, William M.
1992-01-01
The Long Duration Exposure Facility (LDEF) postflight thermal model predicted temperatures were matched to flight temperature data recorded by the Thermal Measurement System (THERM), LDEF experiment P0003. Flight temperatures, recorded at intervals of approximately 112 minutes for the first 390 days of LDEF's 2105 day mission were compared with predictions using the thermal mathematical model (TMM). This model was unverified prior to flight. The postflight analysis has reduced the thermal model uncertainty at the temperature sensor locations from +/- 40 F to +/- 18 F. The improved temperature predictions will be used by the LDEF's principal investigators to calculate improved flight temperatures experienced by 57 experiments located on 86 trays of the facility.
Nordel - Availability statistics for thermal power plants 1995. (Denmark, Finland, Sweden)
International Nuclear Information System (INIS)
1996-01-01
The power companies of Denmark, Finland and Sweden have agreed on almost identical procedures for the recording and analysing of data describing the availability of power producing units over a certain capacity. Since 1975 the data for all three countries have been summarized and published in a joint report. The purpose of this report is to present some basic information about the operation of power producing units in the three countries. Referring to the report, companies or bodies will be able to exchange more detailed information with other companies or bodies in any of the countries. The report includes power producing units using fossil fuels, nuclear power plants and gas turbines. The information is presented separately for each country with a joint NORDEL statistics for units using fossil fuels, arranged in separate groups according to the type of fossil fuel which is used. The grouping of power producing units into classes of capacity has been made in accordance with the classification adopted by UNIPEDE/WEC. The definitions in NORDEL's 'Tillgaenglighetsbegrepp foer vaermekraft' ('The Concept of Availability for Thermal Power'), September 1977, are used in this report. The basic data for the availability are in accordance with the recommendations of UNIPEDE/WEC. (author)
Simple classical model for Fano statistics in radiation detectors
Energy Technology Data Exchange (ETDEWEB)
Jordan, David V. [Pacific Northwest National Laboratory, National Security Division - Radiological and Chemical Sciences Group PO Box 999, Richland, WA 99352 (United States)], E-mail: David.Jordan@pnl.gov; Renholds, Andrea S.; Jaffe, John E.; Anderson, Kevin K.; Rene Corrales, L.; Peurrung, Anthony J. [Pacific Northwest National Laboratory, National Security Division - Radiological and Chemical Sciences Group PO Box 999, Richland, WA 99352 (United States)
2008-02-01
A simple classical model that captures the essential statistics of energy partitioning processes involved in the creation of information carriers (ICs) in radiation detectors is presented. The model pictures IC formation from a fixed amount of deposited energy in terms of the statistically analogous process of successively sampling water from a large, finite-volume container ('bathtub') with a small dipping implement ('shot or whiskey glass'). The model exhibits sub-Poisson variance in the distribution of the number of ICs generated (the 'Fano effect'). Elementary statistical analysis of the model clarifies the role of energy conservation in producing the Fano effect and yields Fano's prescription for computing the relative variance of the IC number distribution in terms of the mean and variance of the underlying, single-IC energy distribution. The partitioning model is applied to the development of the impact ionization cascade in semiconductor radiation detectors. It is shown that, in tandem with simple assumptions regarding the distribution of energies required to create an (electron, hole) pair, the model yields an energy-independent Fano factor of 0.083, in accord with the lower end of the range of literature values reported for silicon and high-purity germanium. The utility of this simple picture as a diagnostic tool for guiding or constraining more detailed, 'microscopic' physical models of detector material response to ionizing radiation is discussed.
Development of 3D statistical mandible models for cephalometric measurements
International Nuclear Information System (INIS)
Kim, Sung Goo; Yi, Won Jin; Hwang, Soon Jung; Choi, Soon Chul; Lee, Sam Sun; Heo, Min Suk; Huh, Kyung Hoe; Kim, Tae Il; Hong, Helen; Yoo, Ji Hyun
2012-01-01
The aim of this study was to provide sex-matched three-dimensional (3D) statistical shape models of the mandible, which would provide cephalometric parameters for 3D treatment planning and cephalometric measurements in orthognathic surgery. The subjects used to create the 3D shape models of the mandible included 23 males and 23 females. The mandibles were segmented semi-automatically from 3D facial CT images. Each individual mandible shape was reconstructed as a 3D surface model, which was parameterized to establish correspondence between different individual surfaces. The principal component analysis (PCA) applied to all mandible shapes produced a mean model and characteristic models of variation. The cephalometric parameters were measured directly from the mean models to evaluate the 3D shape models. The means of the measured parameters were compared with those from other conventional studies. The male and female 3D statistical mean models were developed from 23 individual mandibles, respectively. The male and female characteristic shapes of variation produced by PCA showed a large variability included in the individual mandibles. The cephalometric measurements from the developed models were very close to those from some conventional studies. We described the construction of 3D mandibular shape models and presented the application of the 3D mandibular template in cephalometric measurements. Optimal reference models determined from variations produced by PCA could be used for craniofacial patients with various types of skeletal shape.
Development of 3D statistical mandible models for cephalometric measurements
Energy Technology Data Exchange (ETDEWEB)
Kim, Sung Goo; Yi, Won Jin; Hwang, Soon Jung; Choi, Soon Chul; Lee, Sam Sun; Heo, Min Suk; Huh, Kyung Hoe; Kim, Tae Il [School of Dentistry, Seoul National University, Seoul (Korea, Republic of); Hong, Helen; Yoo, Ji Hyun [Division of Multimedia Engineering, Seoul Women' s University, Seoul (Korea, Republic of)
2012-09-15
The aim of this study was to provide sex-matched three-dimensional (3D) statistical shape models of the mandible, which would provide cephalometric parameters for 3D treatment planning and cephalometric measurements in orthognathic surgery. The subjects used to create the 3D shape models of the mandible included 23 males and 23 females. The mandibles were segmented semi-automatically from 3D facial CT images. Each individual mandible shape was reconstructed as a 3D surface model, which was parameterized to establish correspondence between different individual surfaces. The principal component analysis (PCA) applied to all mandible shapes produced a mean model and characteristic models of variation. The cephalometric parameters were measured directly from the mean models to evaluate the 3D shape models. The means of the measured parameters were compared with those from other conventional studies. The male and female 3D statistical mean models were developed from 23 individual mandibles, respectively. The male and female characteristic shapes of variation produced by PCA showed a large variability included in the individual mandibles. The cephalometric measurements from the developed models were very close to those from some conventional studies. We described the construction of 3D mandibular shape models and presented the application of the 3D mandibular template in cephalometric measurements. Optimal reference models determined from variations produced by PCA could be used for craniofacial patients with various types of skeletal shape.
Models for thermal and mechanical monitoring of power transformers
Energy Technology Data Exchange (ETDEWEB)
Vilaithong, Rummiya
2011-07-01
At present, for economic reasons, there is an increasing emphasis on keeping transformers in service for longer than in the past. A condition-based maintenance using an online monitoring and diagnostic system is one option to ensure reliability of the transformer operation. The key parameters for effectively monitoring equipment can be selected by failure statistics and estimated failure consequences. In this work, two key aspects of transformer condition monitoring are addressed in depth: thermal behaviour and behaviour of on-load tap changers. In the first part of the work, transformer thermal behaviour is studied, focussing on top-oil temperatures. Through online comparison of a measured value of the top-oil temperature and its calculated value, some rapidly developing failures in power transformers such as malfunction of the cooling unit may be detected. Predictions of top-oil temperature can be obtained by means of a mathematical model. Long-term investigations on some dynamic top-oil temperature models are presented for three different types of transformer units. The last-state top-oil temperature, load current, ambient temperature and the operating state of pumps and fans are applied as inputs of the top-oil temperature models. In the fundamental physical models presented, some constant parameters are required and can be estimated using a least-squares optimization technique. Multilayer Feed-forward and Recurrent neural network models are also proposed and investigated. The neural network models are trained with three different Backpropagation training algorithms: Levenberg-Marquardt, Scaled Conjugate Gradient and Automated Bayesian Regularization. The effect of varying operating conditions of the cooling units and the non-steady-state behaviour of loading conditions, as well as ambient temperature are noted. Results show sophisticated temperature prediction is possible using the neural network models that is generally more accurate than with the physical
Statistical sampling and modelling for cork oak and eucalyptus stands
Paulo, M.J.
2002-01-01
This thesis focuses on the use of modern statistical methods to solve problems on sampling, optimal cutting time and agricultural modelling in Portuguese cork oak and eucalyptus stands. The results are contained in five chapters that have been submitted for publication
Two-dimensional models in statistical mechanics and field theory
International Nuclear Information System (INIS)
Koberle, R.
1980-01-01
Several features of two-dimensional models in statistical mechanics and Field theory, such as, lattice quantum chromodynamics, Z(N), Gross-Neveu and CP N-1 are discussed. The problems of confinement and dynamical mass generation are also analyzed. (L.C.) [pt
Statistical Modeling of Energy Production by Photovoltaic Farms
Czech Academy of Sciences Publication Activity Database
Brabec, Marek; Pelikán, Emil; Krč, Pavel; Eben, Kryštof; Musílek, P.
2011-01-01
Roč. 5, č. 9 (2011), s. 785-793 ISSN 1934-8975 Grant - others:GA AV ČR(CZ) M100300904 Institutional research plan: CEZ:AV0Z10300504 Keywords : electrical energy * solar energy * numerical weather prediction model * nonparametric regression * beta regression Subject RIV: BB - Applied Statistics, Operational Research
Model selection for contingency tables with algebraic statistics
Krampe, A.; Kuhnt, S.; Gibilisco, P.; Riccimagno, E.; Rogantin, M.P.; Wynn, H.P.
2009-01-01
Goodness-of-fit tests based on chi-square approximations are commonly used in the analysis of contingency tables. Results from algebraic statistics combined with MCMC methods provide alternatives to the chi-square approximation. However, within a model selection procedure usually a large number of
Syntactic discriminative language model rerankers for statistical machine translation
Carter, S.; Monz, C.
2011-01-01
This article describes a method that successfully exploits syntactic features for n-best translation candidate reranking using perceptrons. We motivate the utility of syntax by demonstrating the superior performance of parsers over n-gram language models in differentiating between Statistical
Using statistical compatibility to derive advanced probabilistic fatigue models
Czech Academy of Sciences Publication Activity Database
Fernández-Canteli, A.; Castillo, E.; López-Aenlle, M.; Seitl, Stanislav
2010-01-01
Roč. 2, č. 1 (2010), s. 1131-1140 E-ISSN 1877-7058. [Fatigue 2010. Praha, 06.06.2010-11.06.2010] Institutional research plan: CEZ:AV0Z20410507 Keywords : Fatigue models * Statistical compatibility * Functional equations Subject RIV: JL - Materials Fatigue, Friction Mechanics
Statistical properties of the nuclear shell-model Hamiltonian
International Nuclear Information System (INIS)
Dias, H.; Hussein, M.S.; Oliveira, N.A. de
1986-01-01
The statistical properties of realistic nuclear shell-model Hamiltonian are investigated in sd-shell nuclei. The probability distribution of the basic-vector amplitude is calculated and compared with the Porter-Thomas distribution. Relevance of the results to the calculation of the giant resonance mixing parameter is pointed out. (Author) [pt
Statistical shape model with random walks for inner ear segmentation
DEFF Research Database (Denmark)
Pujadas, Esmeralda Ruiz; Kjer, Hans Martin; Piella, Gemma
2016-01-01
is required. We propose a new framework for segmentation of micro-CT cochlear images using random walks combined with a statistical shape model (SSM). The SSM allows us to constrain the less contrasted areas and ensures valid inner ear shape outputs. Additionally, a topology preservation method is proposed...
Hierarchical modelling for the environmental sciences statistical methods and applications
Clark, James S
2006-01-01
New statistical tools are changing the way in which scientists analyze and interpret data and models. Hierarchical Bayes and Markov Chain Monte Carlo methods for analysis provide a consistent framework for inference and prediction where information is heterogeneous and uncertain, processes are complicated, and responses depend on scale. Nowhere are these methods more promising than in the environmental sciences.
A Statistical Model for the Estimation of Natural Gas Consumption
Czech Academy of Sciences Publication Activity Database
Vondráček, Jiří; Pelikán, Emil; Konár, Ondřej; Čermáková, Jana; Eben, Kryštof; Malý, Marek; Brabec, Marek
2008-01-01
Roč. 85, c. 5 (2008), s. 362-370 ISSN 0306-2619 R&D Projects: GA AV ČR 1ET400300513 Institutional research plan: CEZ:AV0Z10300504 Keywords : nonlinear regression * gas consumption modeling Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.371, year: 2008
Statistical learning modeling method for space debris photometric measurement
Sun, Wenjing; Sun, Jinqiu; Zhang, Yanning; Li, Haisen
2016-03-01
Photometric measurement is an important way to identify the space debris, but the present methods of photometric measurement have many constraints on star image and need complex image processing. Aiming at the problems, a statistical learning modeling method for space debris photometric measurement is proposed based on the global consistency of the star image, and the statistical information of star images is used to eliminate the measurement noises. First, the known stars on the star image are divided into training stars and testing stars. Then, the training stars are selected as the least squares fitting parameters to construct the photometric measurement model, and the testing stars are used to calculate the measurement accuracy of the photometric measurement model. Experimental results show that, the accuracy of the proposed photometric measurement model is about 0.1 magnitudes.
Workshop on Model Uncertainty and its Statistical Implications
1988-01-01
In this book problems related to the choice of models in such diverse fields as regression, covariance structure, time series analysis and multinomial experiments are discussed. The emphasis is on the statistical implications for model assessment when the assessment is done with the same data that generated the model. This is a problem of long standing, notorious for its difficulty. Some contributors discuss this problem in an illuminating way. Others, and this is a truly novel feature, investigate systematically whether sample re-use methods like the bootstrap can be used to assess the quality of estimators or predictors in a reliable way given the initial model uncertainty. The book should prove to be valuable for advanced practitioners and statistical methodologists alike.
Statistical models describing the energy signature of buildings
DEFF Research Database (Denmark)
Bacher, Peder; Madsen, Henrik; Thavlov, Anders
2010-01-01
Approximately one third of the primary energy production in Denmark is used for heating in buildings. Therefore efforts to accurately describe and improve energy performance of the building mass are very important. For this purpose statistical models describing the energy signature of a building, i...... or varying energy prices. The paper will give an overview of statistical methods and applied models based on experiments carried out in FlexHouse, which is an experimental building in SYSLAB, Risø DTU. The models are of different complexity and can provide estimates of physical quantities such as UA......-values, time constants of the building, and other parameters related to the heat dynamics. A method for selecting the most appropriate model for a given building is outlined and finally a perspective of the applications is given. Aknowledgements to the Danish Energy Saving Trust and the Interreg IV ``Vind i...
Improved air ventilation rate estimation based on a statistical model
International Nuclear Information System (INIS)
Brabec, M.; Jilek, K.
2004-01-01
A new approach to air ventilation rate estimation from CO measurement data is presented. The approach is based on a state-space dynamic statistical model, allowing for quick and efficient estimation. Underlying computations are based on Kalman filtering, whose practical software implementation is rather easy. The key property is the flexibility of the model, allowing various artificial regimens of CO level manipulation to be treated. The model is semi-parametric in nature and can efficiently handle time-varying ventilation rate. This is a major advantage, compared to some of the methods which are currently in practical use. After a formal introduction of the statistical model, its performance is demonstrated on real data from routine measurements. It is shown how the approach can be utilized in a more complex situation of major practical relevance, when time-varying air ventilation rate and radon entry rate are to be estimated simultaneously from concurrent radon and CO measurements
Bayesian Nonparametric Statistical Inference for Shock Models and Wear Processes.
1979-12-01
also note that the results in Section 2 do not depend on the support of F .) This shock model have been studied by Esary, Marshall and Proschan (1973...Barlow and Proschan (1975), among others. The analogy of the shock model in risk and acturial analysis has been given by BUhlmann (1970, Chapter 2... Mathematical Statistics, Vol. 4, pp. 894-906. Billingsley, P. (1968), CONVERGENCE OF PROBABILITY MEASURES, John Wiley, New York. BUhlmann, H. (1970
Statistical and RBF NN models : providing forecasts and risk assessment
Marček, Milan
2009-01-01
Forecast accuracy of economic and financial processes is a popular measure for quantifying the risk in decision making. In this paper, we develop forecasting models based on statistical (stochastic) methods, sometimes called hard computing, and on a soft method using granular computing. We consider the accuracy of forecasting models as a measure for risk evaluation. It is found that the risk estimation process based on soft methods is simplified and less critical to the question w...
A Statistical Model for Synthesis of Detailed Facial Geometry
Golovinskiy, Aleksey; Matusik, Wojciech; Pfister, Hanspeter; Rusinkiewicz, Szymon; Funkhouser, Thomas
2006-01-01
Detailed surface geometry contributes greatly to the visual realism of 3D face models. However, acquiring high-resolution face geometry is often tedious and expensive. Consequently, most face models used in games, virtual reality, or computer vision look unrealistically smooth. In this paper, we introduce a new statistical technique for the analysis and synthesis of small three-dimensional facial features, such as wrinkles and pores. We acquire high-resolution face geometry for people across ...
Statistical modelling of transcript profiles of differentially regulated genes
Directory of Open Access Journals (Sweden)
Sergeant Martin J
2008-07-01
Full Text Available Abstract Background The vast quantities of gene expression profiling data produced in microarray studies, and the more precise quantitative PCR, are often not statistically analysed to their full potential. Previous studies have summarised gene expression profiles using simple descriptive statistics, basic analysis of variance (ANOVA and the clustering of genes based on simple models fitted to their expression profiles over time. We report the novel application of statistical non-linear regression modelling techniques to describe the shapes of expression profiles for the fungus Agaricus bisporus, quantified by PCR, and for E. coli and Rattus norvegicus, using microarray technology. The use of parametric non-linear regression models provides a more precise description of expression profiles, reducing the "noise" of the raw data to produce a clear "signal" given by the fitted curve, and describing each profile with a small number of biologically interpretable parameters. This approach then allows the direct comparison and clustering of the shapes of response patterns between genes and potentially enables a greater exploration and interpretation of the biological processes driving gene expression. Results Quantitative reverse transcriptase PCR-derived time-course data of genes were modelled. "Split-line" or "broken-stick" regression identified the initial time of gene up-regulation, enabling the classification of genes into those with primary and secondary responses. Five-day profiles were modelled using the biologically-oriented, critical exponential curve, y(t = A + (B + CtRt + ε. This non-linear regression approach allowed the expression patterns for different genes to be compared in terms of curve shape, time of maximal transcript level and the decline and asymptotic response levels. Three distinct regulatory patterns were identified for the five genes studied. Applying the regression modelling approach to microarray-derived time course data
WE-A-201-02: Modern Statistical Modeling
Energy Technology Data Exchange (ETDEWEB)
Niemierko, A.
2016-06-15
Chris Marshall: Memorial Introduction Donald Edmonds Herbert Jr., or Don to his colleagues and friends, exemplified the “big tent” vision of medical physics, specializing in Applied Statistics and Dynamical Systems theory. He saw, more clearly than most, that “Making models is the difference between doing science and just fooling around [ref Woodworth, 2004]”. Don developed an interest in chemistry at school by “reading a book” - a recurring theme in his story. He was awarded a Westinghouse Science scholarship and attended the Carnegie Institute of Technology (later Carnegie Mellon University) where his interest turned to physics and led to a BS in Physics after transfer to Northwestern University. After (voluntary) service in the Navy he earned his MS in Physics from the University of Oklahoma, which led him to Johns Hopkins University in Baltimore to pursue a PhD. The early death of his wife led him to take a salaried position in the Physics Department of Colorado College in Colorado Springs so as to better care for their young daughter. There, a chance invitation from Dr. Juan del Regato to teach physics to residents at the Penrose Cancer Hospital introduced him to Medical Physics, and he decided to enter the field. He received his PhD from the University of London (UK) under Prof. Joseph Rotblat, where I first met him, and where he taught himself statistics. He returned to Penrose as a clinical medical physicist, also largely self-taught. In 1975 he formalized an evolving interest in statistical analysis as Professor of Radiology and Head of the Division of Physics and Statistics at the College of Medicine of the University of South Alabama in Mobile, AL where he remained for the rest of his career. He also served as the first Director of their Bio-Statistics and Epidemiology Core Unit working in part on a sickle-cell disease. After retirement he remained active as Professor Emeritus. Don served for several years as a consultant to the Nuclear
WE-A-201-02: Modern Statistical Modeling
International Nuclear Information System (INIS)
Niemierko, A.
2016-01-01
Chris Marshall: Memorial Introduction Donald Edmonds Herbert Jr., or Don to his colleagues and friends, exemplified the “big tent” vision of medical physics, specializing in Applied Statistics and Dynamical Systems theory. He saw, more clearly than most, that “Making models is the difference between doing science and just fooling around [ref Woodworth, 2004]”. Don developed an interest in chemistry at school by “reading a book” - a recurring theme in his story. He was awarded a Westinghouse Science scholarship and attended the Carnegie Institute of Technology (later Carnegie Mellon University) where his interest turned to physics and led to a BS in Physics after transfer to Northwestern University. After (voluntary) service in the Navy he earned his MS in Physics from the University of Oklahoma, which led him to Johns Hopkins University in Baltimore to pursue a PhD. The early death of his wife led him to take a salaried position in the Physics Department of Colorado College in Colorado Springs so as to better care for their young daughter. There, a chance invitation from Dr. Juan del Regato to teach physics to residents at the Penrose Cancer Hospital introduced him to Medical Physics, and he decided to enter the field. He received his PhD from the University of London (UK) under Prof. Joseph Rotblat, where I first met him, and where he taught himself statistics. He returned to Penrose as a clinical medical physicist, also largely self-taught. In 1975 he formalized an evolving interest in statistical analysis as Professor of Radiology and Head of the Division of Physics and Statistics at the College of Medicine of the University of South Alabama in Mobile, AL where he remained for the rest of his career. He also served as the first Director of their Bio-Statistics and Epidemiology Core Unit working in part on a sickle-cell disease. After retirement he remained active as Professor Emeritus. Don served for several years as a consultant to the Nuclear
International Nuclear Information System (INIS)
Weathers, J.B.; Luck, R.; Weathers, J.W.
2009-01-01
The complexity of mathematical models used by practicing engineers is increasing due to the growing availability of sophisticated mathematical modeling tools and ever-improving computational power. For this reason, the need to define a well-structured process for validating these models against experimental results has become a pressing issue in the engineering community. This validation process is partially characterized by the uncertainties associated with the modeling effort as well as the experimental results. The net impact of the uncertainties on the validation effort is assessed through the 'noise level of the validation procedure', which can be defined as an estimate of the 95% confidence uncertainty bounds for the comparison error between actual experimental results and model-based predictions of the same quantities of interest. Although general descriptions associated with the construction of the noise level using multivariate statistics exists in the literature, a detailed procedure outlining how to account for the systematic and random uncertainties is not available. In this paper, the methodology used to derive the covariance matrix associated with the multivariate normal pdf based on random and systematic uncertainties is examined, and a procedure used to estimate this covariance matrix using Monte Carlo analysis is presented. The covariance matrices are then used to construct approximate 95% confidence constant probability contours associated with comparison error results for a practical example. In addition, the example is used to show the drawbacks of using a first-order sensitivity analysis when nonlinear local sensitivity coefficients exist. Finally, the example is used to show the connection between the noise level of the validation exercise calculated using multivariate and univariate statistics.
Energy Technology Data Exchange (ETDEWEB)
Weathers, J.B. [Shock, Noise, and Vibration Group, Northrop Grumman Shipbuilding, P.O. Box 149, Pascagoula, MS 39568 (United States)], E-mail: James.Weathers@ngc.com; Luck, R. [Department of Mechanical Engineering, Mississippi State University, 210 Carpenter Engineering Building, P.O. Box ME, Mississippi State, MS 39762-5925 (United States)], E-mail: Luck@me.msstate.edu; Weathers, J.W. [Structural Analysis Group, Northrop Grumman Shipbuilding, P.O. Box 149, Pascagoula, MS 39568 (United States)], E-mail: Jeffrey.Weathers@ngc.com
2009-11-15
The complexity of mathematical models used by practicing engineers is increasing due to the growing availability of sophisticated mathematical modeling tools and ever-improving computational power. For this reason, the need to define a well-structured process for validating these models against experimental results has become a pressing issue in the engineering community. This validation process is partially characterized by the uncertainties associated with the modeling effort as well as the experimental results. The net impact of the uncertainties on the validation effort is assessed through the 'noise level of the validation procedure', which can be defined as an estimate of the 95% confidence uncertainty bounds for the comparison error between actual experimental results and model-based predictions of the same quantities of interest. Although general descriptions associated with the construction of the noise level using multivariate statistics exists in the literature, a detailed procedure outlining how to account for the systematic and random uncertainties is not available. In this paper, the methodology used to derive the covariance matrix associated with the multivariate normal pdf based on random and systematic uncertainties is examined, and a procedure used to estimate this covariance matrix using Monte Carlo analysis is presented. The covariance matrices are then used to construct approximate 95% confidence constant probability contours associated with comparison error results for a practical example. In addition, the example is used to show the drawbacks of using a first-order sensitivity analysis when nonlinear local sensitivity coefficients exist. Finally, the example is used to show the connection between the noise level of the validation exercise calculated using multivariate and univariate statistics.
Thermal unit availability modeling in a regional simulation model
International Nuclear Information System (INIS)
Yamayee, Z.A.; Port, J.; Robinett, W.
1983-01-01
The System Analysis Model (SAM) developed under the umbrella of PNUCC's System Analysis Committee is capable of simulating the operation of a given load/resource scenario. This model employs a Monte-Carlo simulation to incorporate uncertainties. Among uncertainties modeled is thermal unit availability both for energy simulation (seasonal) and capacity simulations (hourly). This paper presents the availability modeling in the capacity and energy models. The use of regional and national data in deriving the two availability models, the interaction between the two and modifications made to the capacity model in order to reflect regional practices is presented. A sample problem is presented to show the modification process. Results for modeling a nuclear unit using NERC-GADS is presented
Computer modelling of statistical properties of SASE FEL radiation
International Nuclear Information System (INIS)
Saldin, E. L.; Schneidmiller, E. A.; Yurkov, M. V.
1997-01-01
The paper describes an approach to computer modelling of statistical properties of the radiation from self amplified spontaneous emission free electron laser (SASE FEL). The present approach allows one to calculate the following statistical properties of the SASE FEL radiation: time and spectral field correlation functions, distribution of the fluctuations of the instantaneous radiation power, distribution of the energy in the electron bunch, distribution of the radiation energy after monochromator installed at the FEL amplifier exit and the radiation spectrum. All numerical results presented in the paper have been calculated for the 70 nm SASE FEL at the TESLA Test Facility being under construction at DESY
Stochastic geometry, spatial statistics and random fields models and algorithms
2015-01-01
Providing a graduate level introduction to various aspects of stochastic geometry, spatial statistics and random fields, this volume places a special emphasis on fundamental classes of models and algorithms as well as on their applications, for example in materials science, biology and genetics. This book has a strong focus on simulations and includes extensive codes in Matlab and R, which are widely used in the mathematical community. It can be regarded as a continuation of the recent volume 2068 of Lecture Notes in Mathematics, where other issues of stochastic geometry, spatial statistics and random fields were considered, with a focus on asymptotic methods.
RADYN Simulations of Non-thermal and Thermal Models of Ellerman Bombs
Energy Technology Data Exchange (ETDEWEB)
Hong, Jie; Ding, M. D. [School of Astronomy and Space Science, Nanjing University, Nanjing 210023 (China); Carlsson, Mats, E-mail: dmd@nju.edu.cn [Institute of Theoretical Astrophysics, University of Oslo, P.O. Box 1029 Blindern, NO-0315 Oslo (Norway)
2017-08-20
Ellerman bombs (EBs) are brightenings in the H α line wings that are believed to be caused by magnetic reconnection in the lower atmosphere. To study the response and evolution of the chromospheric line profiles, we perform radiative hydrodynamic simulations of EBs using both non-thermal and thermal models. Overall, these models can generate line profiles that are similar to observations. However, in non-thermal models we find dimming in the H α line wings and continuum when the heating begins, while for the thermal models dimming occurs only in the H α line core, and with a longer lifetime. This difference in line profiles can be used to determine whether an EB is dominated by non-thermal heating or thermal heating. In our simulations, if a higher heating rate is applied, then the H α line will be unrealistically strong and there are still no clear UV burst signatures.
RADYN Simulations of Non-thermal and Thermal Models of Ellerman Bombs
Hong, Jie; Carlsson, Mats; Ding, M. D.
2017-08-01
Ellerman bombs (EBs) are brightenings in the Hα line wings that are believed to be caused by magnetic reconnection in the lower atmosphere. To study the response and evolution of the chromospheric line profiles, we perform radiative hydrodynamic simulations of EBs using both non-thermal and thermal models. Overall, these models can generate line profiles that are similar to observations. However, in non-thermal models we find dimming in the Hα line wings and continuum when the heating begins, while for the thermal models dimming occurs only in the Hα line core, and with a longer lifetime. This difference in line profiles can be used to determine whether an EB is dominated by non-thermal heating or thermal heating. In our simulations, if a higher heating rate is applied, then the Hα line will be unrealistically strong and there are still no clear UV burst signatures.
GIA Model Statistics for GRACE Hydrology, Cryosphere, and Ocean Science
Caron, L.; Ivins, E. R.; Larour, E.; Adhikari, S.; Nilsson, J.; Blewitt, G.
2018-03-01
We provide a new analysis of glacial isostatic adjustment (GIA) with the goal of assembling the model uncertainty statistics required for rigorously extracting trends in surface mass from the Gravity Recovery and Climate Experiment (GRACE) mission. Such statistics are essential for deciphering sea level, ocean mass, and hydrological changes because the latter signals can be relatively small (≤2 mm/yr water height equivalent) over very large regions, such as major ocean basins and watersheds. With abundant new >7 year continuous measurements of vertical land motion (VLM) reported by Global Positioning System stations on bedrock and new relative sea level records, our new statistical evaluation of GIA uncertainties incorporates Bayesian methodologies. A unique aspect of the method is that both the ice history and 1-D Earth structure vary through a total of 128,000 forward models. We find that best fit models poorly capture the statistical inferences needed to correctly invert for lower mantle viscosity and that GIA uncertainty exceeds the uncertainty ascribed to trends from 14 years of GRACE data in polar regions.
A Model Fit Statistic for Generalized Partial Credit Model
Liang, Tie; Wells, Craig S.
2009-01-01
Investigating the fit of a parametric model is an important part of the measurement process when implementing item response theory (IRT), but research examining it is limited. A general nonparametric approach for detecting model misfit, introduced by J. Douglas and A. S. Cohen (2001), has exhibited promising results for the two-parameter logistic…
Risk prediction model: Statistical and artificial neural network approach
Paiman, Nuur Azreen; Hariri, Azian; Masood, Ibrahim
2017-04-01
Prediction models are increasingly gaining popularity and had been used in numerous areas of studies to complement and fulfilled clinical reasoning and decision making nowadays. The adoption of such models assist physician's decision making, individual's behavior, and consequently improve individual outcomes and the cost-effectiveness of care. The objective of this paper is to reviewed articles related to risk prediction model in order to understand the suitable approach, development and the validation process of risk prediction model. A qualitative review of the aims, methods and significant main outcomes of the nineteen published articles that developed risk prediction models from numerous fields were done. This paper also reviewed on how researchers develop and validate the risk prediction models based on statistical and artificial neural network approach. From the review done, some methodological recommendation in developing and validating the prediction model were highlighted. According to studies that had been done, artificial neural network approached in developing the prediction model were more accurate compared to statistical approach. However currently, only limited published literature discussed on which approach is more accurate for risk prediction model development.
Modelling of Power Fluxes during Thermal Quenches
International Nuclear Information System (INIS)
Konz, C.; Coster, D. P.; Lackner, K.; Pautasso, G.
2005-01-01
Plasma disruptions, i. e. the sudden loss of magnetic confinement, are unavoidable, at least occasionally, in present day and future tokamaks. The expected energy fluxes to the plasma facing components (PFCs) during disruptions in ITER lie in the range of tens of GW/m''2 for timescales of about a millisecond. Since high energy fluxes can cause severe damage to the PFCs, their design heavily depends on the spatial and temporal distribution of the energy fluxes during disruptions. We investigate the nature of power fluxes during the thermal quench phase of disruptions by means of numerical simulations with the B2 SOLPS fluid code. Based on an ASDEX Upgrade shot, steady-state pre-disruption equilibria are generated which are then subjected to a simulated thermal quench by artificially enhancing the perpendicular transport in the ion and electron channels. The enhanced transport coefficients flows the Rechester and Rosenbluth model (1978) for ergodic transport in a tokamak with destroyed flux surfaces, i. e. χ, D∼const. xT''5/2 where the constants differ by the square root of the mass ratio for ions and electrons. By varying the steady-state neutral puffing rate we can modify the divertor conditions in terms of plasma temperature and density. Our numerical findings indicate that the disruption characteristics depend on the pre disruptive divertor conditions. We study the timescales and the spatial distribution of the divertor power fluxes. The simulated disruptions show rise and decay timescales in the range observed at ASDEX Upgrade. The decay timescale for the central electron temperature of ∼800 μs is typical for non-ITB disruptions. Varying the divertor conditions we find a distinct transition from a regime with symmetric power fluxes to inboard and outboard divertors to a regime where the bulk of the power flux goes to the outboard divertor. This asymmetry in the divertor peak fluxes for the higher puffing case is accompanied by a time delay between the
Statistical model selection with “Big Data”
Directory of Open Access Journals (Sweden)
Jurgen A. Doornik
2015-12-01
Full Text Available Big Data offer potential benefits for statistical modelling, but confront problems including an excess of false positives, mistaking correlations for causes, ignoring sampling biases and selecting by inappropriate methods. We consider the many important requirements when searching for a data-based relationship using Big Data, and the possible role of Autometrics in that context. Paramount considerations include embedding relationships in general initial models, possibly restricting the number of variables to be selected over by non-statistical criteria (the formulation problem, using good quality data on all variables, analyzed with tight significance levels by a powerful selection procedure, retaining available theory insights (the selection problem while testing for relationships being well specified and invariant to shifts in explanatory variables (the evaluation problem, using a viable approach that resolves the computational problem of immense numbers of possible models.
Experimental, statistical, and biological models of radon carcinogenesis
International Nuclear Information System (INIS)
Cross, F.T.
1991-09-01
Risk models developed for underground miners have not been consistently validated in studies of populations exposed to indoor radon. Imprecision in risk estimates results principally from differences between exposures in mines as compared to domestic environments and from uncertainties about the interaction between cigarette-smoking and exposure to radon decay products. Uncertainties in extrapolating miner data to domestic exposures can be reduced by means of a broad-based health effects research program that addresses the interrelated issues of exposure, respiratory tract dose, carcinogenesis (molecular/cellular and animal studies, plus developing biological and statistical models), and the relationship of radon to smoking and other copollutant exposures. This article reviews experimental animal data on radon carcinogenesis observed primarily in rats at Pacific Northwest Laboratory. Recent experimental and mechanistic carcinogenesis models of exposures to radon, uranium ore dust, and cigarette smoke are presented with statistical analyses of animal data. 20 refs., 1 fig
Multimesonic decays of charmonium states in the statistical quark model
International Nuclear Information System (INIS)
Montvay, I.; Toth, J.D.
1978-01-01
The data known at present of multimesonic decays of chi and psi states are fitted in a statistical quark model, in which the matrix elements are assumed to be constant and resonances as well as both strong and second order electromagnetic processes are taken into account. The experimental data are well reproduced by the model. Unknown branching ratios for the rest of multimesonic channels are predicted. The fit leaves about 40% for baryonic and radiative channels in the case of J/psi(3095). The fitted parameters of the J/psi decays are used to predict the mesonic decays of the pseudoscalar eta c. The statistical quark model seems to allow the calculation of competitive multiparticle processes for the studied decays. (D.P.)
Statistical 3D damage accumulation model for ion implant simulators
Hernandez-Mangas, J M; Enriquez, L E; Bailon, L; Barbolla, J; Jaraiz, M
2003-01-01
A statistical 3D damage accumulation model, based on the modified Kinchin-Pease formula, for ion implant simulation has been included in our physically based ion implantation code. It has only one fitting parameter for electronic stopping and uses 3D electron density distributions for different types of targets including compound semiconductors. Also, a statistical noise reduction mechanism based on the dose division is used. The model has been adapted to be run under parallel execution in order to speed up the calculation in 3D structures. Sequential ion implantation has been modelled including previous damage profiles. It can also simulate the implantation of molecular and cluster projectiles. Comparisons of simulated doping profiles with experimental SIMS profiles are presented. Also comparisons between simulated amorphization and experimental RBS profiles are shown. An analysis of sequential versus parallel processing is provided.
Statistical 3D damage accumulation model for ion implant simulators
International Nuclear Information System (INIS)
Hernandez-Mangas, J.M.; Lazaro, J.; Enriquez, L.; Bailon, L.; Barbolla, J.; Jaraiz, M.
2003-01-01
A statistical 3D damage accumulation model, based on the modified Kinchin-Pease formula, for ion implant simulation has been included in our physically based ion implantation code. It has only one fitting parameter for electronic stopping and uses 3D electron density distributions for different types of targets including compound semiconductors. Also, a statistical noise reduction mechanism based on the dose division is used. The model has been adapted to be run under parallel execution in order to speed up the calculation in 3D structures. Sequential ion implantation has been modelled including previous damage profiles. It can also simulate the implantation of molecular and cluster projectiles. Comparisons of simulated doping profiles with experimental SIMS profiles are presented. Also comparisons between simulated amorphization and experimental RBS profiles are shown. An analysis of sequential versus parallel processing is provided
SoS contract verification using statistical model checking
Directory of Open Access Journals (Sweden)
Alessandro Mignogna
2013-11-01
Full Text Available Exhaustive formal verification for systems of systems (SoS is impractical and cannot be applied on a large scale. In this paper we propose to use statistical model checking for efficient verification of SoS. We address three relevant aspects for systems of systems: 1 the model of the SoS, which includes stochastic aspects; 2 the formalization of the SoS requirements in the form of contracts; 3 the tool-chain to support statistical model checking for SoS. We adapt the SMC technique for application to heterogeneous SoS. We extend the UPDM/SysML specification language to express the SoS requirements that the implemented strategies over the SoS must satisfy. The requirements are specified with a new contract language specifically designed for SoS, targeting a high-level English- pattern language, but relying on an accurate semantics given by the standard temporal logics. The contracts are verified against the UPDM/SysML specification using the Statistical Model Checker (SMC PLASMA combined with the simulation engine DESYRE, which integrates heterogeneous behavioral models through the functional mock-up interface (FMI standard. The tool-chain allows computing an estimation of the satisfiability of the contracts by the SoS. The results help the system architect to trade-off different solutions to guide the evolution of the SoS.
Structural reliability in context of statistical uncertainties and modelling discrepancies
International Nuclear Information System (INIS)
Pendola, Maurice
2000-01-01
Structural reliability methods have been largely improved during the last years and have showed their ability to deal with uncertainties during the design stage or to optimize the functioning and the maintenance of industrial installations. They are based on a mechanical modeling of the structural behavior according to the considered failure modes and on a probabilistic representation of input parameters of this modeling. In practice, only limited statistical information is available to build the probabilistic representation and different sophistication levels of the mechanical modeling may be introduced. Thus, besides the physical randomness, other uncertainties occur in such analyses. The aim of this work is triple: 1. at first, to propose a methodology able to characterize the statistical uncertainties due to the limited number of data in order to take them into account in the reliability analyses. The obtained reliability index measures the confidence in the structure considering the statistical information available. 2. Then, to show a methodology leading to reliability results evaluated from a particular mechanical modeling but by using a less sophisticated one. The objective is then to decrease the computational efforts required by the reference modeling. 3. Finally, to propose partial safety factors that are evolving as a function of the number of statistical data available and as a function of the sophistication level of the mechanical modeling that is used. The concepts are illustrated in the case of a welded pipe and in the case of a natural draught cooling tower. The results show the interest of the methodologies in an industrial context. [fr
Model-based analysis of thermal insulation coatings
DEFF Research Database (Denmark)
Kiil, Søren
2014-01-01
Thermal insulation properties of coatings based on selected functional filler materials are investigated. The underlying physics, thermal conductivity of a heterogeneous two-component coating, and porosity and thermal conductivity of hollow spheres (HS) are quantified and a mathematical model for...
Argonne Bubble Experiment Thermal Model Development II
Energy Technology Data Exchange (ETDEWEB)
Buechler, Cynthia Eileen [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-07-01
This report describes the continuation of the work reported in “Argonne Bubble Experiment Thermal Model Development”. The experiment was performed at Argonne National Laboratory (ANL) in 2014. A rastered 35 MeV electron beam deposited power in a solution of uranyl sulfate, generating heat and radiolytic gas bubbles. Irradiations were performed at three beam power levels, 6, 12 and 15 kW. Solution temperatures were measured by thermocouples, and gas bubble behavior was observed. This report will describe the Computational Fluid Dynamics (CFD) model that was developed to calculate the temperatures and gas volume fractions in the solution vessel during the irradiations. The previous report described an initial analysis performed on a geometry that had not been updated to reflect the as-built solution vessel. Here, the as-built geometry is used. Monte-Carlo N-Particle (MCNP) calculations were performed on the updated geometry, and these results were used to define the power deposition profile for the CFD analyses, which were performed using Fluent, Ver. 16.2. CFD analyses were performed for the 12 and 15 kW irradiations, and further improvements to the model were incorporated, including the consideration of power deposition in nearby vessel components, gas mixture composition, and bubble size distribution. The temperature results of the CFD calculations are compared to experimental measurements.
Martin, Justin D.
2017-01-01
This essay presents data from a census of statistics requirements and offerings at all 4-year journalism programs in the United States (N = 369) and proposes a model of a potential course in statistics for journalism majors. The author proposes that three philosophies underlie a statistics course for journalism students. Such a course should (a)…
A statistical model for radar images of agricultural scenes
Frost, V. S.; Shanmugan, K. S.; Holtzman, J. C.; Stiles, J. A.
1982-01-01
The presently derived and validated statistical model for radar images containing many different homogeneous fields predicts the probability density functions of radar images of entire agricultural scenes, thereby allowing histograms of large scenes composed of a variety of crops to be described. Seasat-A SAR images of agricultural scenes are accurately predicted by the model on the basis of three assumptions: each field has the same SNR, all target classes cover approximately the same area, and the true reflectivity characterizing each individual target class is a uniformly distributed random variable. The model is expected to be useful in the design of data processing algorithms and for scene analysis using radar images.
Discrete ellipsoidal statistical BGK model and Burnett equations
Zhang, Yu-Dong; Xu, Ai-Guo; Zhang, Guang-Cai; Chen, Zhi-Hua; Wang, Pei
2018-06-01
A new discrete Boltzmann model, the discrete ellipsoidal statistical Bhatnagar-Gross-Krook (ESBGK) model, is proposed to simulate nonequilibrium compressible flows. Compared with the original discrete BGK model, the discrete ES-BGK has a flexible Prandtl number. For the discrete ES-BGK model in the Burnett level, two kinds of discrete velocity model are introduced and the relations between nonequilibrium quantities and the viscous stress and heat flux in the Burnett level are established. The model is verified via four benchmark tests. In addition, a new idea is introduced to recover the actual distribution function through the macroscopic quantities and their space derivatives. The recovery scheme works not only for discrete Boltzmann simulation but also for hydrodynamic ones, for example, those based on the Navier-Stokes or the Burnett equations.
Statistics of a neuron model driven by asymmetric colored noise.
Müller-Hansen, Finn; Droste, Felix; Lindner, Benjamin
2015-02-01
Irregular firing of neurons can be modeled as a stochastic process. Here we study the perfect integrate-and-fire neuron driven by dichotomous noise, a Markovian process that jumps between two states (i.e., possesses a non-Gaussian statistics) and exhibits nonvanishing temporal correlations (i.e., represents a colored noise). Specifically, we consider asymmetric dichotomous noise with two different transition rates. Using a first-passage-time formulation, we derive exact expressions for the probability density and the serial correlation coefficient of the interspike interval (time interval between two subsequent neural action potentials) and the power spectrum of the spike train. Furthermore, we extend the model by including additional Gaussian white noise, and we give approximations for the interspike interval (ISI) statistics in this case. Numerical simulations are used to validate the exact analytical results for pure dichotomous noise, and to test the approximations of the ISI statistics when Gaussian white noise is included. The results may help to understand how correlations and asymmetry of noise and signals in nerve cells shape neuronal firing statistics.
Spatio-temporal statistical models with applications to atmospheric processes
International Nuclear Information System (INIS)
Wikle, C.K.
1996-01-01
This doctoral dissertation is presented as three self-contained papers. An introductory chapter considers traditional spatio-temporal statistical methods used in the atmospheric sciences from a statistical perspective. Although this section is primarily a review, many of the statistical issues considered have not been considered in the context of these methods and several open questions are posed. The first paper attempts to determine a means of characterizing the semiannual oscillation (SAO) spatial variation in the northern hemisphere extratropical height field. It was discovered that the midlatitude SAO in 500hPa geopotential height could be explained almost entirely as a result of spatial and temporal asymmetries in the annual variation of stationary eddies. It was concluded that the mechanism for the SAO in the northern hemisphere is a result of land-sea contrasts. The second paper examines the seasonal variability of mixed Rossby-gravity waves (MRGW) in lower stratospheric over the equatorial Pacific. Advanced cyclostationary time series techniques were used for analysis. It was found that there are significant twice-yearly peaks in MRGW activity. Analyses also suggested a convergence of horizontal momentum flux associated with these waves. In the third paper, a new spatio-temporal statistical model is proposed that attempts to consider the influence of both temporal and spatial variability. This method is mainly concerned with prediction in space and time, and provides a spatially descriptive and temporally dynamic model
Solar radiation data - statistical analysis and simulation models
Energy Technology Data Exchange (ETDEWEB)
Mustacchi, C; Cena, V; Rocchi, M; Haghigat, F
1984-01-01
The activities consisted in collecting meteorological data on magnetic tape for ten european locations (with latitudes ranging from 42/sup 0/ to 56/sup 0/ N), analysing the multi-year sequences, developing mathematical models to generate synthetic sequences having the same statistical properties of the original data sets, and producing one or more Short Reference Years (SRY's) for each location. The meteorological parameters examinated were (for all the locations) global + diffuse radiation on horizontal surface, dry bulb temperature, sunshine duration. For some of the locations additional parameters were available, namely, global, beam and diffuse radiation on surfaces other than horizontal, wet bulb temperature, wind velocity, cloud type, cloud cover. The statistical properties investigated were mean, variance, autocorrelation, crosscorrelation with selected parameters, probability density function. For all the meteorological parameters, various mathematical models were built: linear regression, stochastic models of the AR and the DAR type. In each case, the model with the best statistical behaviour was selected for the production of a SRY for the relevant parameter/location.
A statistical model for porous structure of rocks
Institute of Scientific and Technical Information of China (English)
JU Yang; YANG YongMing; SONG ZhenDuo; XU WenJing
2008-01-01
The geometric features and the distribution properties of pores in rocks were In-vestigated by means of CT scanning tests of sandstones. The centroidal coordl-nares of pores, the statistic characterristics of pore distance, quantity, size and their probability density functions were formulated in this paper. The Monte Carlo method and the random number generating algorithm were employed to generate two series of random numbers with the desired statistic characteristics and prob-ability density functions upon which the random distribution of pore position, dis-tance and quantity were determined. A three-dimensional porous structural model of sandstone was constructed based on the FLAC3D program and the information of the pore position and distribution that the series of random numbers defined. On the basis of modelling, the Brazil split tests of rock discs were carried out to ex-amine the stress distribution, the pattern of element failure and the inoaculation of failed elements. The simulation indicated that the proposed model was consistent with the realistic porous structure of rock in terms of their statistic properties of pores and geometric similarity. The built-up model disclosed the influence of pores on the stress distribution, failure mode of material elements and the inosculation of failed elements.
A statistical model for porous structure of rocks
Institute of Scientific and Technical Information of China (English)
2008-01-01
The geometric features and the distribution properties of pores in rocks were in- vestigated by means of CT scanning tests of sandstones. The centroidal coordi- nates of pores, the statistic characterristics of pore distance, quantity, size and their probability density functions were formulated in this paper. The Monte Carlo method and the random number generating algorithm were employed to generate two series of random numbers with the desired statistic characteristics and prob- ability density functions upon which the random distribution of pore position, dis- tance and quantity were determined. A three-dimensional porous structural model of sandstone was constructed based on the FLAC3D program and the information of the pore position and distribution that the series of random numbers defined. On the basis of modelling, the Brazil split tests of rock discs were carried out to ex- amine the stress distribution, the pattern of element failure and the inosculation of failed elements. The simulation indicated that the proposed model was consistent with the realistic porous structure of rock in terms of their statistic properties of pores and geometric similarity. The built-up model disclosed the influence of pores on the stress distribution, failure mode of material elements and the inosculation of failed elements.
Bayesian statistic methods and theri application in probabilistic simulation models
Directory of Open Access Journals (Sweden)
Sergio Iannazzo
2007-03-01
Full Text Available Bayesian statistic methods are facing a rapidly growing level of interest and acceptance in the field of health economics. The reasons of this success are probably to be found on the theoretical fundaments of the discipline that make these techniques more appealing to decision analysis. To this point should be added the modern IT progress that has developed different flexible and powerful statistical software framework. Among them probably one of the most noticeably is the BUGS language project and its standalone application for MS Windows WinBUGS. Scope of this paper is to introduce the subject and to show some interesting applications of WinBUGS in developing complex economical models based on Markov chains. The advantages of this approach reside on the elegance of the code produced and in its capability to easily develop probabilistic simulations. Moreover an example of the integration of bayesian inference models in a Markov model is shown. This last feature let the analyst conduce statistical analyses on the available sources of evidence and exploit them directly as inputs in the economic model.
An improved thermal model for the computer code NAIAD
International Nuclear Information System (INIS)
Rainbow, M.T.
1982-12-01
An improved thermal model, based on the concept of heat slabs, has been incorporated as an option into the thermal hydraulic computer code NAIAD. The heat slabs are one-dimensional thermal conduction models with temperature independent thermal properties which may be internal and/or external to the fluid. Thermal energy may be added to or removed from the fluid via heat slabs and passed across the external boundary of external heat slabs at a rate which is a linear function of the external surface temperatures. The code input for the new option has been restructured to simplify data preparation. A full description of current input requirements is presented
Can spatial statistical river temperature models be transferred between catchments?
Jackson, Faye L.; Fryer, Robert J.; Hannah, David M.; Malcolm, Iain A.
2017-09-01
There has been increasing use of spatial statistical models to understand and predict river temperature (Tw) from landscape covariates. However, it is not financially or logistically feasible to monitor all rivers and the transferability of such models has not been explored. This paper uses Tw data from four river catchments collected in August 2015 to assess how well spatial regression models predict the maximum 7-day rolling mean of daily maximum Tw (Twmax) within and between catchments. Models were fitted for each catchment separately using (1) landscape covariates only (LS models) and (2) landscape covariates and an air temperature (Ta) metric (LS_Ta models). All the LS models included upstream catchment area and three included a river network smoother (RNS) that accounted for unexplained spatial structure. The LS models transferred reasonably to other catchments, at least when predicting relative levels of Twmax. However, the predictions were biased when mean Twmax differed between catchments. The RNS was needed to characterise and predict finer-scale spatially correlated variation. Because the RNS was unique to each catchment and thus non-transferable, predictions were better within catchments than between catchments. A single model fitted to all catchments found no interactions between the landscape covariates and catchment, suggesting that the landscape relationships were transferable. The LS_Ta models transferred less well, with particularly poor performance when the relationship with the Ta metric was physically implausible or required extrapolation outside the range of the data. A single model fitted to all catchments found catchment-specific relationships between Twmax and the Ta metric, indicating that the Ta metric was not transferable. These findings improve our understanding of the transferability of spatial statistical river temperature models and provide a foundation for developing new approaches for predicting Tw at unmonitored locations across
Mckim, Stephen A.
2016-01-01
This thesis describes the development and correlation of a thermal model that forms the foundation of a thermal capacitance spacecraft propellant load estimator. Specific details of creating the thermal model for the diaphragm propellant tank used on NASA's Magnetospheric Multiscale spacecraft using ANSYS and the correlation process implemented are presented. The thermal model was correlated to within plus or minus 3 degrees Celsius of the thermal vacuum test data, and was determined sufficient to make future propellant predictions on MMS. The model was also found to be relatively sensitive to uncertainties in applied heat flux and mass knowledge of the tank. More work is needed to improve temperature predictions in the upper hemisphere of the propellant tank where predictions were found to be 2 to 2.5 C lower than the test data. A road map for applying the model to predict propellant loads on the actual MMS spacecraft toward its end of life in 2017-2018 is also presented.
Liu, Feifei; Lan, Fengchong; Chen, Jiqing
2016-07-01
Heat pipe cooling for battery thermal management systems (BTMSs) in electric vehicles (EVs) is growing due to its advantages of high cooling efficiency, compact structure and flexible geometry. Considering the transient conduction, phase change and uncertain thermal conditions in a heat pipe, it is challenging to obtain the dynamic thermal characteristics accurately in such complex heat and mass transfer process. In this paper, a ;segmented; thermal resistance model of a heat pipe is proposed based on thermal circuit method. The equivalent conductivities of different segments, viz. the evaporator and condenser of pipe, are used to determine their own thermal parameters and conditions integrated into the thermal model of battery for a complete three-dimensional (3D) computational fluid dynamics (CFD) simulation. The proposed ;segmented; model shows more precise than the ;non-segmented; model by the comparison of simulated and experimental temperature distribution and variation of an ultra-thin micro heat pipe (UMHP) battery pack, and has less calculation error to obtain dynamic thermal behavior for exact thermal design, management and control of heat pipe BTMSs. Using the ;segmented; model, the cooling effect of the UMHP pack with different natural/forced convection and arrangements is predicted, and the results correspond well to the tests.
Thermalization threshold in models of 1D fermions
Mukerjee, Subroto; Modak, Ranjan; Ramswamy, Sriram
2013-03-01
The question of how isolated quantum systems thermalize is an interesting and open one. In this study we equate thermalization with non-integrability to try to answer this question. In particular, we study the effect of system size on the integrability of 1D systems of interacting fermions on a lattice. We find that for a finite-sized system, a non-zero value of an integrability breaking parameter is required to make an integrable system appear non-integrable. Using exact diagonalization and diagnostics such as energy level statistics and the Drude weight, we find that the threshold value of the integrability breaking parameter scales to zero as a power law with system size. We find the exponent to be the same for different models with its value depending on the random matrix ensemble describing the non-integrable system. We also study a simple analytical model of a non-integrable system with an integrable limit to better understand how a power law emerges.
Thermal modelling of a torpedo-car
Directory of Open Access Journals (Sweden)
Verdeja-González, L. F.
2005-12-01
Full Text Available A two-dimensional finite element model for computing the temperature distribution in a torpedo-car holding pig iron is described in this work. The model determines the temperature gradients in steady and transient conditions within the different parts that constitute the system, which are considered to be the steel casing, refractory lining, liquid iron, slag and air. Heat transfer within the main fluid phases (iron and air is computed assuming an apparent thermal conductivity term incorporating the contribution from convection and radiation, and it is affected by the dimensions of the vessel. Thermal gradients within the constituents of the torpedo-car are used to calculate heat losses during operation. It was found that the model required the incorporation of a region within the iron-refractory interface to reproduce thermographic data recorded during operation; the heat transfer coefficient of this interface was found to be equal to 30 Wm^{-2}K^{-1}.
En este trabajo se describe un modelo bidimensional basado en el método del elemento finito para calcular la distribución de temperaturas en un carro torpedo lleno de arrabio. El modelo determina los gradientes térmicos en condiciones estacionarias y transitorias dentro de las partes que constituyen el sistema considerado, como son cubierta de acero, recubrimientos refractarios, arrabio líquido, escoria y aire. La transferencia de calor en las fases fluidas (arrabio y aire se calcula suponiendo un coeficiente de conductividad térmica aparente que incorpora las contribuciones por convección y radiación y está afectado por las dimensiones del recipiente. El conocimiento de los gradientes térmicos permite calcular las pérdidas de calor durante la operación del carro. Se encontró que el modelo requiere de la incorporación de una región en la intercara hierro-refractario para reproducir la información termográfica recopilada durante pruebas en planta. El
Probing the exchange statistics of one-dimensional anyon models
Greschner, Sebastian; Cardarelli, Lorenzo; Santos, Luis
2018-05-01
We propose feasible scenarios for revealing the modified exchange statistics in one-dimensional anyon models in optical lattices based on an extension of the multicolor lattice-depth modulation scheme introduced in [Phys. Rev. A 94, 023615 (2016), 10.1103/PhysRevA.94.023615]. We show that the fast modulation of a two-component fermionic lattice gas in the presence a magnetic field gradient, in combination with additional resonant microwave fields, allows for the quantum simulation of hardcore anyon models with periodic boundary conditions. Such a semisynthetic ring setup allows for realizing an interferometric arrangement sensitive to the anyonic statistics. Moreover, we show as well that simple expansion experiments may reveal the formation of anomalously bound pairs resulting from the anyonic exchange.
Statistical inference to advance network models in epidemiology.
Welch, David; Bansal, Shweta; Hunter, David R
2011-03-01
Contact networks are playing an increasingly important role in the study of epidemiology. Most of the existing work in this area has focused on considering the effect of underlying network structure on epidemic dynamics by using tools from probability theory and computer simulation. This work has provided much insight on the role that heterogeneity in host contact patterns plays on infectious disease dynamics. Despite the important understanding afforded by the probability and simulation paradigm, this approach does not directly address important questions about the structure of contact networks such as what is the best network model for a particular mode of disease transmission, how parameter values of a given model should be estimated, or how precisely the data allow us to estimate these parameter values. We argue that these questions are best answered within a statistical framework and discuss the role of statistical inference in estimating contact networks from epidemiological data. Copyright © 2011 Elsevier B.V. All rights reserved.
Statistical models of a gas diffusion electrode: II. Current resistent
Energy Technology Data Exchange (ETDEWEB)
Proksch, D B; Winsel, O W
1965-07-01
The authors describe an apparatus for measuring the flow resistance of gas diffusion electrodes which is a mechanical analog of the Wheatstone bridge for measuring electric resistance. The flow resistance of a circular DSK electrode sheet, consisting of two covering layers and a working layer between them, was measured as a function of the gas pressure. While the pressure first was increased and then decreased, a hysteresis occurred, which is discussed and explained by a statistical model of a porous electrode.
A Statistical Model for Soliton Particle Interaction in Plasmas
DEFF Research Database (Denmark)
Dysthe, K. B.; Pécseli, Hans; Truelsen, J.
1986-01-01
A statistical model for soliton-particle interaction is presented. A master equation is derived for the time evolution of the particle velocity distribution as induced by resonant interaction with Korteweg-de Vries solitons. The detailed energy balance during the interaction subsequently determines...... the evolution of the soliton amplitude distribution. The analysis applies equally well for weakly nonlinear plasma waves in a strongly magnetized waveguide, or for ion acoustic waves propagating in one-dimensional systems....
Statistical model of a gas diffusion electrode. III. Photomicrograph study
Energy Technology Data Exchange (ETDEWEB)
Winsel, A W
1965-12-01
A linear section through a gas diffusion electrode produces a certain distribution function of sinews with the pores. From this distribution function some qualities of the pore structure are derived, and an automatic device to determine the distribution function is described. With a statistical model of a gas diffusion electrode the behavior of a DSK electrode is discussed and compared with earlier measurements of the flow resistance of this material.
A statistical model of structure functions and quantum chromodynamics
International Nuclear Information System (INIS)
Mac, E.; Ugaz, E.; Universidad Nacional de Ingenieria, Lima
1989-01-01
We consider a model for the x-dependence of the quark distributions in the proton. Within the context of simple statistical assumptions, we obtain the parton densities in the infinite momentum frame. In a second step lowest order QCD corrections are incorporated to these distributions. Crude, but reasonable, agreement with experiment is found for the F 2 , valence and q, anti q distributions for x> or approx.0.2. (orig.)
Modeling the basic superconductor thermodynamical-statistical characteristics
International Nuclear Information System (INIS)
Palenskis, V.; Maknys, K.
1999-01-01
In accordance with the Landau second-order phase transition and other thermodynamical-statistical relations for superconductors, and using the energy gap as an order parameter in the electron free energy presentation, the fundamental characteristics of electrons, such as the free energy, the total energy, the energy gap, the entropy, and the heat capacity dependences on temperature were obtained. The obtained modeling results, in principle, well reflect the basic low- and high-temperature superconductor characteristics
Environmental radionuclide concentrations: statistical model to determine uniformity of distribution
International Nuclear Information System (INIS)
Cawley, C.N.; Fenyves, E.J.; Spitzberg, D.B.; Wiorkowski, J.; Chehroudi, M.T.
1980-01-01
In the evaluation of data from environmental sampling and measurement, a basic question is whether the radionuclide (or pollutant) is distributed uniformly. Since physical measurements have associated errors, it is inappropriate to consider the measurements alone in this determination. Hence, a statistical model has been developed. It consists of a weighted analysis of variance with subsequent t-tests between weighted and independent means. A computer program to perform the calculations is included
International Nuclear Information System (INIS)
De Oliveira, Z.M.
1980-01-01
A detailed analysis of the simple statistical model description for delayed neutron emission of 87 Br, 137 I, 85 As and 135 Sb has been performed. In agreement with experimental findings, structure in the #betta#-strength function is required to reproduce the envelope of the neutron spectrum from 87 Br. For 85 As and 135 Sb the model is found incapable of simultaneously reproducing envelopes of delayed neutron spectra and neutron branching ratios to excited states in the final nuclei for any choice of #betta#-strength function. The results indicate that partial widths for neutron emission are not compatible with optical-model transmission coefficients. The simple shell model with pairing is shown to qualitatively describe the main features of the #betta#-strength functions for decay of 87 Br and 91 93 95 97 Rb. It is found that the location of apparent resonances in the experimental data are in rough agreement with the location of centroids of strength calculated with this model. An extension of the shell model picture which includes the Gamow-Teller residual interaction is used to investigate decay properties of 84 86 As, 86 92 Br and 88 102 Rb. For a realistic choice of interaction strength, the half lives of these isotopes are fairly well reproduced and semiquantitative agreement with experimental #betta#-strength functions is found. Delayed neutron emission probabilities are reproduced for precursors nearer stability with systematic deviations being observed for the heavier nuclei. Contrary to the assumption of a structureless Gamow-Teller giant resonance as embodied gross theory of #betta#-decay, we find that structures in the tail of the Gamow-Teller giant resonances are expected which strongly influence the decay properties of nuclides in this region
International Nuclear Information System (INIS)
Vanneste, Johan; Bush, John A.; Hickenbottom, Kerri L.; Marks, Christopher A.; Jassby, David
2017-01-01
Development and selection of membranes for membrane distillation (MD) could be accelerated if all performance-determining characteristics of the membrane could be obtained during MD operation without the need to recur to specialized or cumbersome porosity or thermal conductivity measurement techniques. By redefining the thermal efficiency, the Schofield method could be adapted to describe the flux without prior knowledge of membrane porosity, thickness, or thermal conductivity. A total of 17 commercially available membranes were analyzed in terms of flux and thermal efficiency to assess their suitability for application in MD. The thermal-efficiency based model described the flux with an average %RMSE of 4.5%, which was in the same range as the standard deviation on the measured flux. The redefinition of the thermal efficiency also enabled MD to be used as a novel thermal conductivity measurement device for thin porous hydrophobic films that cannot be measured with the conventional laser flash diffusivity technique.
Statistical methods for mechanistic model validation: Salt Repository Project
International Nuclear Information System (INIS)
Eggett, D.L.
1988-07-01
As part of the Department of Energy's Salt Repository Program, Pacific Northwest Laboratory (PNL) is studying the emplacement of nuclear waste containers in a salt repository. One objective of the SRP program is to develop an overall waste package component model which adequately describes such phenomena as container corrosion, waste form leaching, spent fuel degradation, etc., which are possible in the salt repository environment. The form of this model will be proposed, based on scientific principles and relevant salt repository conditions with supporting data. The model will be used to predict the future characteristics of the near field environment. This involves several different submodels such as the amount of time it takes a brine solution to contact a canister in the repository, how long it takes a canister to corrode and expose its contents to the brine, the leach rate of the contents of the canister, etc. These submodels are often tested in a laboratory and should be statistically validated (in this context, validate means to demonstrate that the model adequately describes the data) before they can be incorporated into the waste package component model. This report describes statistical methods for validating these models. 13 refs., 1 fig., 3 tabs
Estimating preferential flow in karstic aquifers using statistical mixed models.
Anaya, Angel A; Padilla, Ingrid; Macchiavelli, Raul; Vesper, Dorothy J; Meeker, John D; Alshawabkeh, Akram N
2014-01-01
Karst aquifers are highly productive groundwater systems often associated with conduit flow. These systems can be highly vulnerable to contamination, resulting in a high potential for contaminant exposure to humans and ecosystems. This work develops statistical models to spatially characterize flow and transport patterns in karstified limestone and determines the effect of aquifer flow rates on these patterns. A laboratory-scale Geo-HydroBed model is used to simulate flow and transport processes in a karstic limestone unit. The model consists of stainless steel tanks containing a karstified limestone block collected from a karst aquifer formation in northern Puerto Rico. Experimental work involves making a series of flow and tracer injections, while monitoring hydraulic and tracer response spatially and temporally. Statistical mixed models (SMMs) are applied to hydraulic data to determine likely pathways of preferential flow in the limestone units. The models indicate a highly heterogeneous system with dominant, flow-dependent preferential flow regions. Results indicate that regions of preferential flow tend to expand at higher groundwater flow rates, suggesting a greater volume of the system being flushed by flowing water at higher rates. Spatial and temporal distribution of tracer concentrations indicates the presence of conduit-like and diffuse flow transport in the system, supporting the notion of both combined transport mechanisms in the limestone unit. The temporal response of tracer concentrations at different locations in the model coincide with, and confirms the preferential flow distribution generated with the SMMs used in the study. © 2013, National Ground Water Association.
A generalized statistical model for the size distribution of wealth
International Nuclear Information System (INIS)
Clementi, F; Gallegati, M; Kaniadakis, G
2012-01-01
In a recent paper in this journal (Clementi et al 2009 J. Stat. Mech. P02037), we proposed a new, physically motivated, distribution function for modeling individual incomes, having its roots in the framework of the κ-generalized statistical mechanics. The performance of the κ-generalized distribution was checked against real data on personal income for the United States in 2003. In this paper we extend our previous model so as to be able to account for the distribution of wealth. Probabilistic functions and inequality measures of this generalized model for wealth distribution are obtained in closed form. In order to check the validity of the proposed model, we analyze the US household wealth distributions from 1984 to 2009 and conclude an excellent agreement with the data that is superior to any other model already known in the literature. (paper)
A generalized statistical model for the size distribution of wealth
Clementi, F.; Gallegati, M.; Kaniadakis, G.
2012-12-01
In a recent paper in this journal (Clementi et al 2009 J. Stat. Mech. P02037), we proposed a new, physically motivated, distribution function for modeling individual incomes, having its roots in the framework of the κ-generalized statistical mechanics. The performance of the κ-generalized distribution was checked against real data on personal income for the United States in 2003. In this paper we extend our previous model so as to be able to account for the distribution of wealth. Probabilistic functions and inequality measures of this generalized model for wealth distribution are obtained in closed form. In order to check the validity of the proposed model, we analyze the US household wealth distributions from 1984 to 2009 and conclude an excellent agreement with the data that is superior to any other model already known in the literature.
Modeling the Thermal Signature of Natural Backgrounds
National Research Council Canada - National Science Library
Gamborg, Marius
2002-01-01
Two measuring stations have been established the purpose being to collect comprehensive databases of thermal signatures of background elements in addition to the prevailing meteorological conditions...
UPPAAL-SMC: Statistical Model Checking for Priced Timed Automata
DEFF Research Database (Denmark)
Bulychev, Petr; David, Alexandre; Larsen, Kim Guldstrand
2012-01-01
on a series of extensions of the statistical model checking approach generalized to handle real-time systems and estimate undecidable problems. U PPAAL - SMC comes together with a friendly user interface that allows a user to specify complex problems in an efficient manner as well as to get feedback...... in the form of probability distributions and compare probabilities to analyze performance aspects of systems. The focus of the survey is on the evolution of the tool – including modeling and specification formalisms as well as techniques applied – together with applications of the tool to case studies....
Statistical mechanics of attractor neural network models with synaptic depression
International Nuclear Information System (INIS)
Igarashi, Yasuhiko; Oizumi, Masafumi; Otsubo, Yosuke; Nagata, Kenji; Okada, Masato
2009-01-01
Synaptic depression is known to control gain for presynaptic inputs. Since cortical neurons receive thousands of presynaptic inputs, and their outputs are fed into thousands of other neurons, the synaptic depression should influence macroscopic properties of neural networks. We employ simple neural network models to explore the macroscopic effects of synaptic depression. Systems with the synaptic depression cannot be analyzed due to asymmetry of connections with the conventional equilibrium statistical-mechanical approach. Thus, we first propose a microscopic dynamical mean field theory. Next, we derive macroscopic steady state equations and discuss the stabilities of steady states for various types of neural network models.
A model independent safeguard against background mismodeling for statistical inference
Energy Technology Data Exchange (ETDEWEB)
Priel, Nadav; Landsman, Hagar; Manfredini, Alessandro; Budnik, Ranny [Department of Particle Physics and Astrophysics, Weizmann Institute of Science, Herzl St. 234, Rehovot (Israel); Rauch, Ludwig, E-mail: nadav.priel@weizmann.ac.il, E-mail: rauch@mpi-hd.mpg.de, E-mail: hagar.landsman@weizmann.ac.il, E-mail: alessandro.manfredini@weizmann.ac.il, E-mail: ran.budnik@weizmann.ac.il [Teilchen- und Astroteilchenphysik, Max-Planck-Institut für Kernphysik, Saupfercheckweg 1, 69117 Heidelberg (Germany)
2017-05-01
We propose a safeguard procedure for statistical inference that provides universal protection against mismodeling of the background. The method quantifies and incorporates the signal-like residuals of the background model into the likelihood function, using information available in a calibration dataset. This prevents possible false discovery claims that may arise through unknown mismodeling, and corrects the bias in limit setting created by overestimated or underestimated background. We demonstrate how the method removes the bias created by an incomplete background model using three realistic case studies.
Thermal expansion and its impacts on thermal transport in the FPU-α-β model
Directory of Open Access Journals (Sweden)
Xiaodong Cao
2015-05-01
Full Text Available We study the impacts of thermal expansion, arising from the asymmetric interparticle potential, on thermal conductance in the FPU-α-β model. A nonmonotonic dependence of the temperature gradient and thermal conductance on the cubic interaction parameter α are shown, which corresponds to the variation of the coefficient of thermal expansion. Three domains with respect to α can be identified. The results are explained based on the detailed analysis of the asymmetry of the interparticle potential. The self-consistent phonon theory, which can capture the effect of thermal expansion, is developed to support our explanation in a quantitative way. Our result would be helpful to understand the issue that whether there exist normal thermal conduction in the FPU-α-β model.
Mathematical modelling of pasta dough dynamic viscosity, thermal conductivity and diffusivity
Directory of Open Access Journals (Sweden)
Andrei Ionuţ SIMION
2015-08-01
Full Text Available This work aimed to study the mathematical variation of three main thermodynamic properties (dynamic viscosity, thermal conductivity and thermal diffusivity of pasta dough obtained by mixing wheat semolina and water with dough humidity and deformation speed (for dynamic viscosity, respectively with dough humidity and temperature (for thermal diffusivity and conductivity. The realized regression analysis of existing graphical data led to the development of mathematical models with a high degree of accuracy. The employed statistical tests (least squares, relative error and analysis of variance revealed that the obtained equations are able to describe and predict the tendency of the dough thermodynamic properties.
Document Categorization with Modified Statistical Language Models for Agglutinative Languages
Directory of Open Access Journals (Sweden)
Tantug
2010-11-01
Full Text Available In this paper, we investigate the document categorization task with statistical language models. Our study mainly focuses on categorization of documents in agglutinative languages. Due to the productive morphology of agglutinative languages, the number of word forms encountered in naturally occurring text is very large. From the language modeling perspective, a large vocabulary results in serious data sparseness problems. In order to cope with this drawback, previous studies in various application areas suggest modified language models based on different morphological units. It is reported that performance improvements can be achieved with these modified language models. In our document categorization experiments, we use standard word form based language models as well as other modified language models based on root words, root words and part-of-speech information, truncated word forms and character sequences. Additionally, to find an optimum parameter set, multiple tests are carried out with different language model orders and smoothing methods. Similar to previous studies on other tasks, our experimental results on categorization of Turkish documents reveal that applying linguistic preprocessing steps for language modeling provides improvements over standard language models to some extent. However, it is also observed that similar level of performance improvements can also be acquired by simpler character level or truncated word form models which are language independent.
A neighborhood statistics model for predicting stream pathogen indicator levels.
Pandey, Pramod K; Pasternack, Gregory B; Majumder, Mahbubul; Soupir, Michelle L; Kaiser, Mark S
2015-03-01
Because elevated levels of water-borne Escherichia coli in streams are a leading cause of water quality impairments in the U.S., water-quality managers need tools for predicting aqueous E. coli levels. Presently, E. coli levels may be predicted using complex mechanistic models that have a high degree of unchecked uncertainty or simpler statistical models. To assess spatio-temporal patterns of instream E. coli levels, herein we measured E. coli, a pathogen indicator, at 16 sites (at four different times) within the Squaw Creek watershed, Iowa, and subsequently, the Markov Random Field model was exploited to develop a neighborhood statistics model for predicting instream E. coli levels. Two observed covariates, local water temperature (degrees Celsius) and mean cross-sectional depth (meters), were used as inputs to the model. Predictions of E. coli levels in the water column were compared with independent observational data collected from 16 in-stream locations. The results revealed that spatio-temporal averages of predicted and observed E. coli levels were extremely close. Approximately 66 % of individual predicted E. coli concentrations were within a factor of 2 of the observed values. In only one event, the difference between prediction and observation was beyond one order of magnitude. The mean of all predicted values at 16 locations was approximately 1 % higher than the mean of the observed values. The approach presented here will be useful while assessing instream contaminations such as pathogen/pathogen indicator levels at the watershed scale.
Efficient Parallel Statistical Model Checking of Biochemical Networks
Directory of Open Access Journals (Sweden)
Paolo Ballarini
2009-12-01
Full Text Available We consider the problem of verifying stochastic models of biochemical networks against behavioral properties expressed in temporal logic terms. Exact probabilistic verification approaches such as, for example, CSL/PCTL model checking, are undermined by a huge computational demand which rule them out for most real case studies. Less demanding approaches, such as statistical model checking, estimate the likelihood that a property is satisfied by sampling executions out of the stochastic model. We propose a methodology for efficiently estimating the likelihood that a LTL property P holds of a stochastic model of a biochemical network. As with other statistical verification techniques, the methodology we propose uses a stochastic simulation algorithm for generating execution samples, however there are three key aspects that improve the efficiency: first, the sample generation is driven by on-the-fly verification of P which results in optimal overall simulation time. Second, the confidence interval estimation for the probability of P to hold is based on an efficient variant of the Wilson method which ensures a faster convergence. Third, the whole methodology is designed according to a parallel fashion and a prototype software tool has been implemented that performs the sampling/verification process in parallel over an HPC architecture.
Statistical models for expert judgement and wear prediction
International Nuclear Information System (INIS)
Pulkkinen, U.
1994-01-01
This thesis studies the statistical analysis of expert judgements and prediction of wear. The point of view adopted is the one of information theory and Bayesian statistics. A general Bayesian framework for analyzing both the expert judgements and wear prediction is presented. Information theoretic interpretations are given for some averaging techniques used in the determination of consensus distributions. Further, information theoretic models are compared with a Bayesian model. The general Bayesian framework is then applied in analyzing expert judgements based on ordinal comparisons. In this context, the value of information lost in the ordinal comparison process is analyzed by applying decision theoretic concepts. As a generalization of the Bayesian framework, stochastic filtering models for wear prediction are formulated. These models utilize the information from condition monitoring measurements in updating the residual life distribution of mechanical components. Finally, the application of stochastic control models in optimizing operational strategies for inspected components are studied. Monte-Carlo simulation methods, such as the Gibbs sampler and the stochastic quasi-gradient method, are applied in the determination of posterior distributions and in the solution of stochastic optimization problems. (orig.) (57 refs., 7 figs., 1 tab.)
Development and evaluation of thermal model reduction algorithms for spacecraft
Deiml, Michael; Suderland, Martin; Reiss, Philipp; Czupalla, Markus
2015-05-01
This paper is concerned with the topic of the reduction of thermal models of spacecraft. The work presented here has been conducted in cooperation with the company OHB AG, formerly Kayser-Threde GmbH, and the Institute of Astronautics at Technische Universität München with the goal to shorten and automatize the time-consuming and manual process of thermal model reduction. The reduction of thermal models can be divided into the simplification of the geometry model for calculation of external heat flows and radiative couplings and into the reduction of the underlying mathematical model. For simplification a method has been developed which approximates the reduced geometry model with the help of an optimization algorithm. Different linear and nonlinear model reduction techniques have been evaluated for their applicability in reduction of the mathematical model. Thereby the compatibility with the thermal analysis tool ESATAN-TMS is of major concern, which restricts the useful application of these methods. Additional model reduction methods have been developed, which account to these constraints. The Matrix Reduction method allows the approximation of the differential equation to reference values exactly expect for numerical errors. The summation method enables a useful, applicable reduction of thermal models that can be used in industry. In this work a framework for model reduction of thermal models has been created, which can be used together with a newly developed graphical user interface for the reduction of thermal models in industry.
Model-generated air quality statistics for application in vegetation response models in Alberta
International Nuclear Information System (INIS)
McVehil, G.E.; Nosal, M.
1990-01-01
To test and apply vegetation response models in Alberta, air pollution statistics representative of various parts of the Province are required. At this time, air quality monitoring data of the requisite accuracy and time resolution are not available for most parts of Alberta. Therefore, there exists a need to develop appropriate air quality statistics. The objectives of the work reported here were to determine the applicability of model generated air quality statistics and to develop by modelling, realistic and representative time series of hourly SO 2 concentrations that could be used to generate the statistics demanded by vegetation response models
Assessment of RANS CFD modelling for pressurised thermal shock analysis
International Nuclear Information System (INIS)
Sander M Willemsen; Ed MJ Komen; Sander Willemsen
2005-01-01
in the cold leg and downcomer. The initial computations were performed using the commonly used porous medium representation for the core and omission of the lower plenum internals. These assumption, however, lead to unrealistic circumferential flow oscillations in the downcomer, and consequently, a wrong prediction of the thermal load on the RPV wall. Therefore, a detailed geometrical model with a refined numerical mesh was used, which suppressed these erroneous oscillations. Furthermore, it was confirmed that an extended k-ε or SST k-ω turbulence model which include turbulence production/destruction terms due to buoyancy has to be used in order to correctly predict the thermal stratification in the cold leg. The measurements in the downcomer show rapidly fluctuating signals, which indicate vigorous turbulent mixing and/or oscillations. It was found that reasonable agreement could be achieved with RANS type turbulence modelling for the prediction of the phenomena occurring in the downcomer. Improvement of these results can be expected from non-statistically averaged turbulent modelling like Large Eddy Simulations. It is concluded that the current RANS models already provide a significant improvement over thermal-hydraulic system code analysis, since three-dimensional effects are predicted and no tuning of the code to expensive experiments is needed. (authors)
Thermal model of the whole element furnace
International Nuclear Information System (INIS)
Cramer, E.R.
1998-01-01
A detailed thermal analysis was performed to calculate temperatures in the whole element test furnace that is used to conduct drying studies of N-Reactor fuel. The purpose of this analysis was to establish the thermal characteristics of the test system and to provide a basis for post-test analysis
The GNASH preequilibrium-statistical nuclear model code
International Nuclear Information System (INIS)
Arthur, E. D.
1988-01-01
The following report is based on materials presented in a series of lectures at the International Center for Theoretical Physics, Trieste, which were designed to describe the GNASH preequilibrium statistical model code and its use. An overview is provided of the code with emphasis upon code's calculational capabilities and the theoretical models that have been implemented in it. Two sample problems are discussed, the first dealing with neutron reactions on 58 Ni. the second illustrates the fission model capabilities implemented in the code and involves n + 235 U reactions. Finally a description is provided of current theoretical model and code development underway. Examples of calculated results using these new capabilities are also given. 19 refs., 17 figs., 3 tabs
The Impact of Statistical Leakage Models on Design Yield Estimation
Directory of Open Access Journals (Sweden)
Rouwaida Kanj
2011-01-01
Full Text Available Device mismatch and process variation models play a key role in determining the functionality and yield of sub-100 nm design. Average characteristics are often of interest, such as the average leakage current or the average read delay. However, detecting rare functional fails is critical for memory design and designers often seek techniques that enable accurately modeling such events. Extremely leaky devices can inflict functionality fails. The plurality of leaky devices on a bitline increase the dimensionality of the yield estimation problem. Simplified models are possible by adopting approximations to the underlying sum of lognormals. The implications of such approximations on tail probabilities may in turn bias the yield estimate. We review different closed form approximations and compare against the CDF matching method, which is shown to be most effective method for accurate statistical leakage modeling.
Schedulability of Herschel revisited using statistical model checking
DEFF Research Database (Denmark)
David, Alexandre; Larsen, Kim Guldstrand; Legay, Axel
2015-01-01
-approximation technique. We can safely conclude that the system is schedulable for varying values of BCET. For the cases where deadlines are violated, we use polyhedra to try to confirm the witnesses. Our alternative method to confirm non-schedulability uses statistical model-checking (SMC) to generate counter...... and blocking times of tasks. Consequently, the method may falsely declare deadline violations that will never occur during execution. This paper is a continuation of previous work of the authors in applying extended timed automata model checking (using the tool UPPAAL) to obtain more exact schedulability...... analysis, here in the presence of non-deterministic computation times of tasks given by intervals [BCET,WCET]. Computation intervals with preemptive schedulers make the schedulability analysis of the resulting task model undecidable. Our contribution is to propose a combination of model checking techniques...
Modeling of Viscosity and Thermal Expansion of Bioactive Glasses
Farid, Saad B. H.
2012-01-01
The behaviors of viscosity and thermal expansion for different compositions of bioactive glasses have been studied. The effect of phosphorous pentoxide as a second glass former in addition to silica was investigated. Consequently, the nonlinear behaviors of viscosity and thermal expansion with respect to the oxide composition have been modeled. The modeling uses published data on bioactive glass compositions with viscosity and thermal expansion. -regression optimization technique has been uti...
Experimental investigation of statistical models describing distribution of counts
International Nuclear Information System (INIS)
Salma, I.; Zemplen-Papp, E.
1992-01-01
The binomial, Poisson and modified Poisson models which are used for describing the statistical nature of the distribution of counts are compared theoretically, and conclusions for application are considered. The validity of the Poisson and the modified Poisson statistical distribution for observing k events in a short time interval is investigated experimentally for various measuring times. The experiments to measure the influence of the significant radioactive decay were performed with 89 Y m (T 1/2 =16.06 s), using a multichannel analyser (4096 channels) in the multiscaling mode. According to the results, Poisson statistics describe the counting experiment for short measuring times (up to T=0.5T 1/2 ) and its application is recommended. However, analysis of the data demonstrated, with confidence, that for long measurements (T≥T 1/2 ) Poisson distribution is not valid and the modified Poisson function is preferable. The practical implications in calculating uncertainties and in optimizing the measuring time are discussed. Differences between the standard deviations evaluated on the basis of the Poisson and binomial models are especially significant for experiments with long measuring time (T/T 1/2 ≥2) and/or large detection efficiency (ε>0.30). Optimization of the measuring time for paired observations yields the same solution for either the binomial or the Poisson distribution. (orig.)
Fast optimization of statistical potentials for structurally constrained phylogenetic models
Directory of Open Access Journals (Sweden)
Rodrigue Nicolas
2009-09-01
Full Text Available Abstract Background Statistical approaches for protein design are relevant in the field of molecular evolutionary studies. In recent years, new, so-called structurally constrained (SC models of protein-coding sequence evolution have been proposed, which use statistical potentials to assess sequence-structure compatibility. In a previous work, we defined a statistical framework for optimizing knowledge-based potentials especially suited to SC models. Our method used the maximum likelihood principle and provided what we call the joint potentials. However, the method required numerical estimations by the use of computationally heavy Markov Chain Monte Carlo sampling algorithms. Results Here, we develop an alternative optimization procedure, based on a leave-one-out argument coupled to fast gradient descent algorithms. We assess that the leave-one-out potential yields very similar results to the joint approach developed previously, both in terms of the resulting potential parameters, and by Bayes factor evaluation in a phylogenetic context. On the other hand, the leave-one-out approach results in a considerable computational benefit (up to a 1,000 fold decrease in computational time for the optimization procedure. Conclusion Due to its computational speed, the optimization method we propose offers an attractive alternative for the design and empirical evaluation of alternative forms of potentials, using large data sets and high-dimensional parameterizations.
Estimating Predictive Variance for Statistical Gas Distribution Modelling
International Nuclear Information System (INIS)
Lilienthal, Achim J.; Asadi, Sahar; Reggente, Matteo
2009-01-01
Recent publications in statistical gas distribution modelling have proposed algorithms that model mean and variance of a distribution. This paper argues that estimating the predictive concentration variance entails not only a gradual improvement but is rather a significant step to advance the field. This is, first, since the models much better fit the particular structure of gas distributions, which exhibit strong fluctuations with considerable spatial variations as a result of the intermittent character of gas dispersal. Second, because estimating the predictive variance allows to evaluate the model quality in terms of the data likelihood. This offers a solution to the problem of ground truth evaluation, which has always been a critical issue for gas distribution modelling. It also enables solid comparisons of different modelling approaches, and provides the means to learn meta parameters of the model, to determine when the model should be updated or re-initialised, or to suggest new measurement locations based on the current model. We also point out directions of related ongoing or potential future research work.
Statistical Downscaling of Temperature with the Random Forest Model
Directory of Open Access Journals (Sweden)
Bo Pang
2017-01-01
Full Text Available The issues with downscaling the outputs of a global climate model (GCM to a regional scale that are appropriate to hydrological impact studies are investigated using the random forest (RF model, which has been shown to be superior for large dataset analysis and variable importance evaluation. The RF is proposed for downscaling daily mean temperature in the Pearl River basin in southern China. Four downscaling models were developed and validated by using the observed temperature series from 61 national stations and large-scale predictor variables derived from the National Center for Environmental Prediction–National Center for Atmospheric Research reanalysis dataset. The proposed RF downscaling model was compared to multiple linear regression, artificial neural network, and support vector machine models. Principal component analysis (PCA and partial correlation analysis (PAR were used in the predictor selection for the other models for a comprehensive study. It was shown that the model efficiency of the RF model was higher than that of the other models according to five selected criteria. By evaluating the predictor importance, the RF could choose the best predictor combination without using PCA and PAR. The results indicate that the RF is a feasible tool for the statistical downscaling of temperature.
Statistics of excitations in the electron glass model
Palassini, Matteo
2011-03-01
We study the statistics of elementary excitations in the classical electron glass model of localized electrons interacting via the unscreened Coulomb interaction in the presence of disorder. We reconsider the long-standing puzzle of the exponential suppression of the single-particle density of states near the Fermi level, by measuring accurately the density of states of charged and electron-hole pair excitations via finite temperature Monte Carlo simulation and zero-temperature relaxation. We also investigate the statistics of large charge rearrangements after a perturbation of the system, which may shed some light on the slow relaxation and glassy phenomena recently observed in a variety of Anderson insulators. In collaboration with Martin Goethe.
Hybrid perturbation methods based on statistical time series models
San-Juan, Juan Félix; San-Martín, Montserrat; Pérez, Iván; López, Rosario
2016-04-01
In this work we present a new methodology for orbit propagation, the hybrid perturbation theory, based on the combination of an integration method and a prediction technique. The former, which can be a numerical, analytical or semianalytical theory, generates an initial approximation that contains some inaccuracies derived from the fact that, in order to simplify the expressions and subsequent computations, not all the involved forces are taken into account and only low-order terms are considered, not to mention the fact that mathematical models of perturbations not always reproduce physical phenomena with absolute precision. The prediction technique, which can be based on either statistical time series models or computational intelligence methods, is aimed at modelling and reproducing missing dynamics in the previously integrated approximation. This combination results in the precision improvement of conventional numerical, analytical and semianalytical theories for determining the position and velocity of any artificial satellite or space debris object. In order to validate this methodology, we present a family of three hybrid orbit propagators formed by the combination of three different orders of approximation of an analytical theory and a statistical time series model, and analyse their capability to process the effect produced by the flattening of the Earth. The three considered analytical components are the integration of the Kepler problem, a first-order and a second-order analytical theories, whereas the prediction technique is the same in the three cases, namely an additive Holt-Winters method.
Bayesian Sensitivity Analysis of Statistical Models with Missing Data.
Zhu, Hongtu; Ibrahim, Joseph G; Tang, Niansheng
2014-04-01
Methods for handling missing data depend strongly on the mechanism that generated the missing values, such as missing completely at random (MCAR) or missing at random (MAR), as well as other distributional and modeling assumptions at various stages. It is well known that the resulting estimates and tests may be sensitive to these assumptions as well as to outlying observations. In this paper, we introduce various perturbations to modeling assumptions and individual observations, and then develop a formal sensitivity analysis to assess these perturbations in the Bayesian analysis of statistical models with missing data. We develop a geometric framework, called the Bayesian perturbation manifold, to characterize the intrinsic structure of these perturbations. We propose several intrinsic influence measures to perform sensitivity analysis and quantify the effect of various perturbations to statistical models. We use the proposed sensitivity analysis procedure to systematically investigate the tenability of the non-ignorable missing at random (NMAR) assumption. Simulation studies are conducted to evaluate our methods, and a dataset is analyzed to illustrate the use of our diagnostic measures.
A statistical model for interpreting computerized dynamic posturography data
Feiveson, Alan H.; Metter, E. Jeffrey; Paloski, William H.
2002-01-01
Computerized dynamic posturography (CDP) is widely used for assessment of altered balance control. CDP trials are quantified using the equilibrium score (ES), which ranges from zero to 100, as a decreasing function of peak sway angle. The problem of how best to model and analyze ESs from a controlled study is considered. The ES often exhibits a skewed distribution in repeated trials, which can lead to incorrect inference when applying standard regression or analysis of variance models. Furthermore, CDP trials are terminated when a patient loses balance. In these situations, the ES is not observable, but is assigned the lowest possible score--zero. As a result, the response variable has a mixed discrete-continuous distribution, further compromising inference obtained by standard statistical methods. Here, we develop alternative methodology for analyzing ESs under a stochastic model extending the ES to a continuous latent random variable that always exists, but is unobserved in the event of a fall. Loss of balance occurs conditionally, with probability depending on the realized latent ES. After fitting the model by a form of quasi-maximum-likelihood, one may perform statistical inference to assess the effects of explanatory variables. An example is provided, using data from the NIH/NIA Baltimore Longitudinal Study on Aging.
Model output statistics applied to wind power prediction
Energy Technology Data Exchange (ETDEWEB)
Joensen, A; Giebel, G; Landberg, L [Risoe National Lab., Roskilde (Denmark); Madsen, H; Nielsen, H A [The Technical Univ. of Denmark, Dept. of Mathematical Modelling, Lyngby (Denmark)
1999-03-01
Being able to predict the output of a wind farm online for a day or two in advance has significant advantages for utilities, such as better possibility to schedule fossil fuelled power plants and a better position on electricity spot markets. In this paper prediction methods based on Numerical Weather Prediction (NWP) models are considered. The spatial resolution used in NWP models implies that these predictions are not valid locally at a specific wind farm. Furthermore, due to the non-stationary nature and complexity of the processes in the atmosphere, and occasional changes of NWP models, the deviation between the predicted and the measured wind will be time dependent. If observational data is available, and if the deviation between the predictions and the observations exhibits systematic behavior, this should be corrected for; if statistical methods are used, this approaches is usually referred to as MOS (Model Output Statistics). The influence of atmospheric turbulence intensity, topography, prediction horizon length and auto-correlation of wind speed and power is considered, and to take the time-variations into account, adaptive estimation methods are applied. Three estimation techniques are considered and compared, Extended Kalman Filtering, recursive least squares and a new modified recursive least squares algorithm. (au) EU-JOULE-3. 11 refs.
Thermal Radiation Effects on Thermal Explosion in Polydisperse Fuel Spray-Probabilistic Model
Directory of Open Access Journals (Sweden)
Ophir Navea
2011-06-01
Full Text Available We investigate the effect of thermal radiation on the dynamics of a thermal explosion of polydisperse fuel spray with a complete description of the chemistry via a single-step two-reactant model of general order. The polydisperse spray is modeled using a Probability Density Function (PDF. The thermal radiation energy exchange between the evaporation surface of the fuel droplets and the burning gas is described using the Marshak boundary conditions. An explicit expression of the critical condition for thermal explosion limit is derived analytically and represents a generalization of the critical parameter of the classical Semenov theory. Because we investigated the model in the range where the temperature is very high, the effect of the thermal radiation is significant.
Geometric model for softwood transverse thermal conductivity. Part I
Hong-mei Gu; Audrey Zink-Sharp
2005-01-01
Thermal conductivity is a very important parameter in determining heat transfer rate and is required for developing of drying models and in industrial operations such as adhesive cure rate. Geometric models for predicting softwood thermal conductivity in the radial and tangential directions were generated in this study based on obervation and measurements of wood...
A temperature dependent slip factor based thermal model for friction
Indian Academy of Sciences (India)
This paper proposes a new slip factor based three-dimensional thermal model to predict the temperature distribution during friction stir welding of 304L stainless steel plates. The proposed model employs temperature and radius dependent heat source to study the thermal cycle, temperature distribution, power required, the ...
Prediction of dimethyl disulfide levels from biosolids using statistical modeling.
Gabriel, Steven A; Vilalai, Sirapong; Arispe, Susanna; Kim, Hyunook; McConnell, Laura L; Torrents, Alba; Peot, Christopher; Ramirez, Mark
2005-01-01
Two statistical models were used to predict the concentration of dimethyl disulfide (DMDS) released from biosolids produced by an advanced wastewater treatment plant (WWTP) located in Washington, DC, USA. The plant concentrates sludge from primary sedimentation basins in gravity thickeners (GT) and sludge from secondary sedimentation basins in dissolved air flotation (DAF) thickeners. The thickened sludge is pumped into blending tanks and then fed into centrifuges for dewatering. The dewatered sludge is then conditioned with lime before trucking out from the plant. DMDS, along with other volatile sulfur and nitrogen-containing chemicals, is known to contribute to biosolids odors. These models identified oxidation/reduction potential (ORP) values of a GT and DAF, the amount of sludge dewatered by centrifuges, and the blend ratio between GT thickened sludge and DAF thickened sludge in blending tanks as control variables. The accuracy of the developed regression models was evaluated by checking the adjusted R2 of the regression as well as the signs of coefficients associated with each variable. In general, both models explained observed DMDS levels in sludge headspace samples. The adjusted R2 value of the regression models 1 and 2 were 0.79 and 0.77, respectively. Coefficients for each regression model also had the correct sign. Using the developed models, plant operators can adjust the controllable variables to proactively decrease this odorant. Therefore, these models are a useful tool in biosolids management at WWTPs.
Thermal modeling: at the crossroads of several subjects of physics
International Nuclear Information System (INIS)
1997-01-01
The modeling of thermal phenomena is of prime importance for the dimensioning of industrial facilities. However, the understanding of thermal processes requires to refer to other subjects of physics like electromagnetism, matter transformation, fluid mechanics, chemistry etc.. The aim of this workshop organized by the industrial electro-thermal engineering section of the French society of thermal engineers is to take stock of current or forthcoming advances in the coupling of thermal engineering codes with electromagnetic, fluid mechanics, chemical and mechanical engineering codes. The modeling of phenomena remains the essential link between the laboratory research of new processes and their industrial developments. From the 9 talks given during this workshop, 2 of them deal with thermal processes in nuclear reactors and fall into the INIS scope and the others concern the modeling of industrial heating or electrical processes and were selected for ETDE. (J.S.)
Sommer, W.T.
2015-01-01
Modelling and monitoring of Aquifer Thermal Energy Storage
Impacts of heterogeneity, thermal interference and bioremediation
Wijbrand Sommer
PhD thesis, Wageningen University, Wageningen, NL (2015)
ISBN 978-94-6257-294-2
Abstract
Aquifer
Quantifying the relevance of adaptive thermal comfort models in moderate thermal climate zones
Hoof, van J.; Hensen, J.L.M.
2007-01-01
Standards governing thermal comfort evaluation are on a constant cycle of revision and public review. One of the main topics being discussed in the latest round was the introduction of an adaptive thermal comfort model, which now forms an optional part of ASHRAE Standard 55. Also on a national
Directory of Open Access Journals (Sweden)
Enrico Zio
2008-01-01
Full Text Available In the present work, the uncertainties affecting the safety margins estimated from thermal-hydraulic code calculations are captured quantitatively by resorting to the order statistics and the bootstrap technique. The proposed framework of analysis is applied to the estimation of the safety margin, with its confidence interval, of the maximum fuel cladding temperature reached during a complete group distribution blockage scenario in a RBMK-1500 nuclear reactor.
Statistical mechanical model of gas adsorption in porous crystals with dynamic moieties.
Simon, Cory M; Braun, Efrem; Carraro, Carlo; Smit, Berend
2017-01-17
Some nanoporous, crystalline materials possess dynamic constituents, for example, rotatable moieties. These moieties can undergo a conformation change in response to the adsorption of guest molecules, which qualitatively impacts adsorption behavior. We pose and solve a statistical mechanical model of gas adsorption in a porous crystal whose cages share a common ligand that can adopt two distinct rotational conformations. Guest molecules incentivize the ligands to adopt a different rotational configuration than maintained in the empty host. Our model captures inflections, steps, and hysteresis that can arise in the adsorption isotherm as a signature of the rotating ligands. The insights disclosed by our simple model contribute a more intimate understanding of the response and consequence of rotating ligands integrated into porous materials to harness them for gas storage and separations, chemical sensing, drug delivery, catalysis, and nanoscale devices. Particularly, our model reveals design strategies to exploit these moving constituents and engineer improved adsorbents with intrinsic thermal management for pressure-swing adsorption processes.
Statistical approach for uncertainty quantification of experimental modal model parameters
DEFF Research Database (Denmark)
Luczak, M.; Peeters, B.; Kahsin, M.
2014-01-01
Composite materials are widely used in manufacture of aerospace and wind energy structural components. These load carrying structures are subjected to dynamic time-varying loading conditions. Robust structural dynamics identification procedure impose tight constraints on the quality of modal models...... represent different complexity levels ranging from coupon, through sub-component up to fully assembled aerospace and wind energy structural components made of composite materials. The proposed method is demonstrated on two application cases of a small and large wind turbine blade........ This paper aims at a systematic approach for uncertainty quantification of the parameters of the modal models estimated from experimentally obtained data. Statistical analysis of modal parameters is implemented to derive an assessment of the entire modal model uncertainty measure. Investigated structures...
Statistical mechanics of sparse generalization and graphical model selection
International Nuclear Information System (INIS)
Lage-Castellanos, Alejandro; Pagnani, Andrea; Weigt, Martin
2009-01-01
One of the crucial tasks in many inference problems is the extraction of an underlying sparse graphical model from a given number of high-dimensional measurements. In machine learning, this is frequently achieved using, as a penalty term, the L p norm of the model parameters, with p≤1 for efficient dilution. Here we propose a statistical mechanics analysis of the problem in the setting of perceptron memorization and generalization. Using a replica approach, we are able to evaluate the relative performance of naive dilution (obtained by learning without dilution, following by applying a threshold to the model parameters), L 1 dilution (which is frequently used in convex optimization) and L 0 dilution (which is optimal but computationally hard to implement). Whereas both L p diluted approaches clearly outperform the naive approach, we find a small region where L 0 works almost perfectly and strongly outperforms the simpler to implement L 1 dilution
Exploiting linkage disequilibrium in statistical modelling in quantitative genomics
DEFF Research Database (Denmark)
Wang, Lei
Alleles at two loci are said to be in linkage disequilibrium (LD) when they are correlated or statistically dependent. Genomic prediction and gene mapping rely on the existence of LD between gentic markers and causul variants of complex traits. In the first part of the thesis, a novel method...... to quantify and visualize local variation in LD along chromosomes in describet, and applied to characterize LD patters at the local and genome-wide scale in three Danish pig breeds. In the second part, different ways of taking LD into account in genomic prediction models are studied. One approach is to use...... the recently proposed antedependence models, which treat neighbouring marker effects as correlated; another approach involves use of haplotype block information derived using the program Beagle. The overall conclusion is that taking LD information into account in genomic prediction models potentially improves...
A statistical model for field emission in superconducting cavities
International Nuclear Information System (INIS)
Padamsee, H.; Green, K.; Jost, W.; Wright, B.
1993-01-01
A statistical model is used to account for several features of performance of an ensemble of superconducting cavities. The input parameters are: the number of emitters/area, a distribution function for emitter β values, a distribution function for emissive areas, and a processing threshold. The power deposited by emitters is calculated from the field emission current and electron impact energy. The model can successfully account for the fraction of tests that reach the maximum field Epk in an ensemble of cavities, for eg, 1-cells at sign 3 GHz or 5-cells at sign 1.5 GHz. The model is used to predict the level of power needed to successfully process cavities of various surface areas with high pulsed power processing (HPP)
International Nuclear Information System (INIS)
Potter, G.L.; Ellsaesser, H.W.; MacCracken, M.C.; Luther, F.M.
1978-06-01
Results from the zonal model indicate quite reasonable agreement with observation in terms of the parameters and processes that influence the radiation and energy balance calculations. The model produces zonal statistics similar to those from general circulation models, and has also been shown to produce similar responses in sensitivity studies. Further studies of model performance are planned, including: comparison with July data; comparison of temperature and moisture transport and wind fields for winter and summer months; and a tabulation of atmospheric energetics. Based on these preliminary performance studies, however, it appears that the zonal model can be used in conjunction with more complex models to help unravel the problems of understanding the processes governing present climate and climate change. As can be seen in the subsequent paper on model sensitivity studies, in addition to reduced cost of computation, the zonal model facilitates analysis of feedback mechanisms and simplifies analysis of the interactions between processes
A Statistical Graphical Model of the California Reservoir System
Taeb, A.; Reager, J. T.; Turmon, M.; Chandrasekaran, V.
2017-11-01
The recent California drought has highlighted the potential vulnerability of the state's water management infrastructure to multiyear dry intervals. Due to the high complexity of the network, dynamic storage changes in California reservoirs on a state-wide scale have previously been difficult to model using either traditional statistical or physical approaches. Indeed, although there is a significant line of research on exploring models for single (or a small number of) reservoirs, these approaches are not amenable to a system-wide modeling of the California reservoir network due to the spatial and hydrological heterogeneities of the system. In this work, we develop a state-wide statistical graphical model to characterize the dependencies among a collection of 55 major California reservoirs across the state; this model is defined with respect to a graph in which the nodes index reservoirs and the edges specify the relationships or dependencies between reservoirs. We obtain and validate this model in a data-driven manner based on reservoir volumes over the period 2003-2016. A key feature of our framework is a quantification of the effects of external phenomena that influence the entire reservoir network. We further characterize the degree to which physical factors (e.g., state-wide Palmer Drought Severity Index (PDSI), average temperature, snow pack) and economic factors (e.g., consumer price index, number of agricultural workers) explain these external influences. As a consequence of this analysis, we obtain a system-wide health diagnosis of the reservoir network as a function of PDSI.
Modeling Thermal Ignition of Energetic Materials
National Research Council Canada - National Science Library
Gerri, Norman J; Berning, Ellen
2004-01-01
This report documents an attempt to computationally simulate the mechanics and thermal regimes created when a threat perforates an armor envelope and comes in contact with stowed energetic material...
MASKED AREAS IN SHEAR PEAK STATISTICS: A FORWARD MODELING APPROACH
International Nuclear Information System (INIS)
Bard, D.; Kratochvil, J. M.; Dawson, W.
2016-01-01
The statistics of shear peaks have been shown to provide valuable cosmological information beyond the power spectrum, and will be an important constraint of models of cosmology in forthcoming astronomical surveys. Surveys include masked areas due to bright stars, bad pixels etc., which must be accounted for in producing constraints on cosmology from shear maps. We advocate a forward-modeling approach, where the impacts of masking and other survey artifacts are accounted for in the theoretical prediction of cosmological parameters, rather than correcting survey data to remove them. We use masks based on the Deep Lens Survey, and explore the impact of up to 37% of the survey area being masked on LSST and DES-scale surveys. By reconstructing maps of aperture mass the masking effect is smoothed out, resulting in up to 14% smaller statistical uncertainties compared to simply reducing the survey area by the masked area. We show that, even in the presence of large survey masks, the bias in cosmological parameter estimation produced in the forward-modeling process is ≈1%, dominated by bias caused by limited simulation volume. We also explore how this potential bias scales with survey area and evaluate how much small survey areas are impacted by the differences in cosmological structure in the data and simulated volumes, due to cosmic variance
International Nuclear Information System (INIS)
Seeliger, D.
1993-01-01
This contribution contains a brief presentation and comparison of the different Statistical Multistep Approaches, presently available for practical nuclear data calculations. (author). 46 refs, 5 figs
A Tensor Statistical Model for Quantifying Dynamic Functional Connectivity.
Zhu, Yingying; Zhu, Xiaofeng; Kim, Minjeong; Yan, Jin; Wu, Guorong
2017-06-01
Functional connectivity (FC) has been widely investigated in many imaging-based neuroscience and clinical studies. Since functional Magnetic Resonance Image (MRI) signal is just an indirect reflection of brain activity, it is difficult to accurately quantify the FC strength only based on signal correlation. To address this limitation, we propose a learning-based tensor model to derive high sensitivity and specificity connectome biomarkers at the individual level from resting-state fMRI images. First, we propose a learning-based approach to estimate the intrinsic functional connectivity. In addition to the low level region-to-region signal correlation, latent module-to-module connection is also estimated and used to provide high level heuristics for measuring connectivity strength. Furthermore, sparsity constraint is employed to automatically remove the spurious connections, thus alleviating the issue of searching for optimal threshold. Second, we integrate our learning-based approach with the sliding-window technique to further reveal the dynamics of functional connectivity. Specifically, we stack the functional connectivity matrix within each sliding window and form a 3D tensor where the third dimension denotes for time. Then we obtain dynamic functional connectivity (dFC) for each individual subject by simultaneously estimating the within-sliding-window functional connectivity and characterizing the across-sliding-window temporal dynamics. Third, in order to enhance the robustness of the connectome patterns extracted from dFC, we extend the individual-based 3D tensors to a population-based 4D tensor (with the fourth dimension stands for the training subjects) and learn the statistics of connectome patterns via 4D tensor analysis. Since our 4D tensor model jointly (1) optimizes dFC for each training subject and (2) captures the principle connectome patterns, our statistical model gains more statistical power of representing new subject than current state
Development of modelling algorithm of technological systems by statistical tests
Shemshura, E. A.; Otrokov, A. V.; Chernyh, V. G.
2018-03-01
The paper tackles the problem of economic assessment of design efficiency regarding various technological systems at the stage of their operation. The modelling algorithm of a technological system was performed using statistical tests and with account of the reliability index allows estimating the level of machinery technical excellence and defining the efficiency of design reliability against its performance. Economic feasibility of its application shall be determined on the basis of service quality of a technological system with further forecasting of volumes and the range of spare parts supply.
New statistical model of inelastic fast neutron scattering
International Nuclear Information System (INIS)
Stancicj, V.
1975-07-01
A new statistical model for treating the fast neutron inelastic scattering has been proposed by using the general expressions of the double differential cross section in impuls approximation. The use of the Fermi-Dirac distribution of nucleons makes it possible to derive an analytical expression of the fast neutron inelastic scattering kernel including the angular momenta coupling. The obtained values of the inelastic fast neutron cross section calculated from the derived expression of the scattering kernel are in a good agreement with the experiments. A main advantage of the derived expressions is in their simplicity for the practical calculations
Steinberg, P. D.; Brener, G.; Duffy, D.; Nearing, G. S.; Pelissier, C.
2017-12-01
Hyperparameterization, of statistical models, i.e. automated model scoring and selection, such as evolutionary algorithms, grid searches, and randomized searches, can improve forecast model skill by reducing errors associated with model parameterization, model structure, and statistical properties of training data. Ensemble Learning Models (Elm), and the related Earthio package, provide a flexible interface for automating the selection of parameters and model structure for machine learning models common in climate science and land cover classification, offering convenient tools for loading NetCDF, HDF, Grib, or GeoTiff files, decomposition methods like PCA and manifold learning, and parallel training and prediction with unsupervised and supervised classification, clustering, and regression estimators. Continuum Analytics is using Elm to experiment with statistical soil moisture forecasting based on meteorological forcing data from NASA's North American Land Data Assimilation System (NLDAS). There Elm is using the NSGA-2 multiobjective optimization algorithm for optimizing statistical preprocessing of forcing data to improve goodness-of-fit for statistical models (i.e. feature engineering). This presentation will discuss Elm and its components, including dask (distributed task scheduling), xarray (data structures for n-dimensional arrays), and scikit-learn (statistical preprocessing, clustering, classification, regression), and it will show how NSGA-2 is being used for automate selection of soil moisture forecast statistical models for North America.
Statistical Models for Inferring Vegetation Composition from Fossil Pollen
Paciorek, C.; McLachlan, J. S.; Shang, Z.
2011-12-01
Fossil pollen provide information about vegetation composition that can be used to help understand how vegetation has changed over the past. However, these data have not traditionally been analyzed in a way that allows for statistical inference about spatio-temporal patterns and trends. We build a Bayesian hierarchical model called STEPPS (Spatio-Temporal Empirical Prediction from Pollen in Sediments) that predicts forest composition in southern New England, USA, over the last two millenia based on fossil pollen. The critical relationships between abundances of tree taxa in the pollen record and abundances in actual vegetation are estimated using modern (Forest Inventory Analysis) data and (witness tree) data from colonial records. This gives us two time points at which both pollen and direct vegetation data are available. Based on these relationships, and incorporating our uncertainty about them, we predict forest composition using fossil pollen. We estimate the spatial distribution and relative abundances of tree species and draw inference about how these patterns have changed over time. Finally, we describe ongoing work to extend the modeling to the upper Midwest of the U.S., including an approach to infer tree density and thereby estimate the prairie-forest boundary in Minnesota and Wisconsin. This work is part of the PalEON project, which brings together a team of ecosystem modelers, paleoecologists, and statisticians with the goal of reconstructing vegetation responses to climate during the last two millenia in the northeastern and midwestern United States. The estimates from the statistical modeling will be used to assess and calibrate ecosystem models that are used to project ecological changes in response to global change.
Statistical molecular design of balanced compound libraries for QSAR modeling.
Linusson, A; Elofsson, M; Andersson, I E; Dahlgren, M K
2010-01-01
A fundamental step in preclinical drug development is the computation of quantitative structure-activity relationship (QSAR) models, i.e. models that link chemical features of compounds with activities towards a target macromolecule associated with the initiation or progression of a disease. QSAR models are computed by combining information on the physicochemical and structural features of a library of congeneric compounds, typically assembled from two or more building blocks, and biological data from one or more in vitro assays. Since the models provide information on features affecting the compounds' biological activity they can be used as guides for further optimization. However, in order for a QSAR model to be relevant to the targeted disease, and drug development in general, the compound library used must contain molecules with balanced variation of the features spanning the chemical space believed to be important for interaction with the biological target. In addition, the assays used must be robust and deliver high quality data that are directly related to the function of the biological target and the associated disease state. In this review, we discuss and exemplify the concept of statistical molecular design (SMD) in the selection of building blocks and final synthetic targets (i.e. compounds to synthesize) to generate information-rich, balanced libraries for biological testing and computation of QSAR models.
Project W-320 thermal hydraulic model benchmarking and baselining
International Nuclear Information System (INIS)
Sathyanarayana, K.
1998-01-01
Project W-320 will be retrieving waste from Tank 241-C-106 and transferring the waste to Tank 241-AY-102. Waste in both tanks must be maintained below applicable thermal limits during and following the waste transfer. Thermal hydraulic process control models will be used for process control of the thermal limits. This report documents the process control models and presents a benchmarking of the models with data from Tanks 241-C-106 and 241-AY-102. Revision 1 of this report will provide a baselining of the models in preparation for the initiation of sluicing
A combined statistical model for multiple motifs search
International Nuclear Information System (INIS)
Gao Lifeng; Liu Xin; Guan Shan
2008-01-01
Transcription factor binding sites (TFBS) play key roles in genebior 6.8 wavelet expression and regulation. They are short sequence segments with definite structure and can be recognized by the corresponding transcription factors correctly. From the viewpoint of statistics, the candidates of TFBS should be quite different from the segments that are randomly combined together by nucleotide. This paper proposes a combined statistical model for finding over-represented short sequence segments in different kinds of data set. While the over-represented short sequence segment is described by position weight matrix, the nucleotide distribution at most sites of the segment should be far from the background nucleotide distribution. The central idea of this approach is to search for such kind of signals. This algorithm is tested on 3 data sets, including binding sites data set of cyclic AMP receptor protein in E.coli, PlantProm DB which is a non-redundant collection of proximal promoter sequences from different species, collection of the intergenic sequences of the whole genome of E.Coli. Even though the complexity of these three data sets is quite different, the results show that this model is rather general and sensible. (general)
Huffman and linear scanning methods with statistical language models.
Roark, Brian; Fried-Oken, Melanie; Gibbons, Chris
2015-03-01
Current scanning access methods for text generation in AAC devices are limited to relatively few options, most notably row/column variations within a matrix. We present Huffman scanning, a new method for applying statistical language models to binary-switch, static-grid typing AAC interfaces, and compare it to other scanning options under a variety of conditions. We present results for 16 adults without disabilities and one 36-year-old man with locked-in syndrome who presents with complex communication needs and uses AAC scanning devices for writing. Huffman scanning with a statistical language model yielded significant typing speedups for the 16 participants without disabilities versus any of the other methods tested, including two row/column scanning methods. A similar pattern of results was found with the individual with locked-in syndrome. Interestingly, faster typing speeds were obtained with Huffman scanning using a more leisurely scan rate than relatively fast individually calibrated scan rates. Overall, the results reported here demonstrate great promise for the usability of Huffman scanning as a faster alternative to row/column scanning.
Statistical Method to Overcome Overfitting Issue in Rational Function Models
Alizadeh Moghaddam, S. H.; Mokhtarzade, M.; Alizadeh Naeini, A.; Alizadeh Moghaddam, S. A.
2017-09-01
Rational function models (RFMs) are known as one of the most appealing models which are extensively applied in geometric correction of satellite images and map production. Overfitting is a common issue, in the case of terrain dependent RFMs, that degrades the accuracy of RFMs-derived geospatial products. This issue, resulting from the high number of RFMs' parameters, leads to ill-posedness of the RFMs. To tackle this problem, in this study, a fast and robust statistical approach is proposed and compared to Tikhonov regularization (TR) method, as a frequently-used solution to RFMs' overfitting. In the proposed method, a statistical test, namely, significance test is applied to search for the RFMs' parameters that are resistant against overfitting issue. The performance of the proposed method was evaluated for two real data sets of Cartosat-1 satellite images. The obtained results demonstrate the efficiency of the proposed method in term of the achievable level of accuracy. This technique, indeed, shows an improvement of 50-80% over the TR.
Study of ATES thermal behavior using a steady flow model
Doughty, C.; Hellstroem, G.; Tsang, C. F.; Claesson, J.
1981-01-01
The thermal behavior of a single well aquifer thermal energy storage system in which buoyancy flow is neglected is studied. A dimensionless formulation of the energy transport equations for the aquifer system is presented, and the key dimensionless parameters are discussed. A simple numerical model is used to generate graphs showing the thermal behavior of the system as a function of these parameters. Some comparisons with field experiments are given to illustrate the use of the dimensionless groups and graphs.
Statistical Agent Based Modelization of the Phenomenon of Drug Abuse
di Clemente, Riccardo; Pietronero, Luciano
2012-07-01
We introduce a statistical agent based model to describe the phenomenon of drug abuse and its dynamical evolution at the individual and global level. The agents are heterogeneous with respect to their intrinsic inclination to drugs, to their budget attitude and social environment. The various levels of drug use were inspired by the professional description of the phenomenon and this permits a direct comparison with all available data. We show that certain elements have a great importance to start the use of drugs, for example the rare events in the personal experiences which permit to overcame the barrier of drug use occasionally. The analysis of how the system reacts to perturbations is very important to understand its key elements and it provides strategies for effective policy making. The present model represents the first step of a realistic description of this phenomenon and can be easily generalized in various directions.
International Nuclear Information System (INIS)
Beck, T.; Bieler, A.; Thomas, N.
2012-01-01
We present structural and thermal model (STM) tests of the BepiColombo laser altimeter (BELA) receiver baffle with emphasis on the correlation of the data with a thermal mathematical model. The test unit is a part of the thermal and optical protection of the BELA instrument being tested under infrared and solar irradiation at University of Bern. An iterative optimization method known as particle swarm optimization has been adapted to adjust the model parameters, mainly the linear conductivity, in such a way that model and test results match. The thermal model reproduces the thermal tests to an accuracy of 4.2 °C ± 3.2 °C in a temperature range of 200 °C after using only 600 iteration steps of the correlation algorithm. The use of this method brings major benefits to the accuracy of the results as well as to the computational time required for the correlation. - Highlights: ► We present model correlations of the BELA receiver baffle to thermal balance tests. ► Adaptive particle swarm optimization has been adapted for the correlation. ► The method improves the accuracy of the correlation and the computational time.
McKim, Stephen A.
2016-01-01
This thesis describes the development and test data validation of the thermal model that is the foundation of a thermal capacitance spacecraft propellant load estimator. Specific details of creating the thermal model for the diaphragm propellant tank used on NASA's Magnetospheric Multiscale spacecraft using ANSYS and the correlation process implemented to validate the model are presented. The thermal model was correlated to within plus or minus 3 degrees Centigrade of the thermal vacuum test data, and was found to be relatively insensitive to uncertainties in applied heat flux and mass knowledge of the tank. More work is needed, however, to refine the thermal model to further improve temperature predictions in the upper hemisphere of the propellant tank. Temperatures predictions in this portion were found to be 2-2.5 degrees Centigrade lower than the test data. A road map to apply the model to predict propellant loads on the actual MMS spacecraft toward its end of life in 2017-2018 is also presented.
Graphene growth process modeling: a physical-statistical approach
Wu, Jian; Huang, Qiang
2014-09-01
As a zero-band semiconductor, graphene is an attractive material for a wide variety of applications such as optoelectronics. Among various techniques developed for graphene synthesis, chemical vapor deposition on copper foils shows high potential for producing few-layer and large-area graphene. Since fabrication of high-quality graphene sheets requires the understanding of growth mechanisms, and methods of characterization and control of grain size of graphene flakes, analytical modeling of graphene growth process is therefore essential for controlled fabrication. The graphene growth process starts with randomly nucleated islands that gradually develop into complex shapes, grow in size, and eventually connect together to cover the copper foil. To model this complex process, we develop a physical-statistical approach under the assumption of self-similarity during graphene growth. The growth kinetics is uncovered by separating island shapes from area growth rate. We propose to characterize the area growth velocity using a confined exponential model, which not only has clear physical explanation, but also fits the real data well. For the shape modeling, we develop a parametric shape model which can be well explained by the angular-dependent growth rate. This work can provide useful information for the control and optimization of graphene growth process on Cu foil.
Statistical program for the data evaluation of a thermal ionization mass spectrometer
Energy Technology Data Exchange (ETDEWEB)
van Raaphorst, J. G.
1978-12-15
A computer program has been written to statistically analyze mass spectrometer measurements. The program tests whether the difference between signal and background intensities is statistically significant, corrects for signal drift in the measured values, and calculates ratios against the main isotope from the corrected intensities. Repeated ratio value measurements are screened for outliers using the Dixon statistical test. Means of ratios and the coefficient of variation are calculated and reported. The computer program is written in Basic and is available for anyone who is interested.
Thermal margin model for transition core of KSNP
International Nuclear Information System (INIS)
Nahm, Kee Yil; Lim, Jong Seon; Park, Sung Kew; Chun, Chong Kuk; Hwang, Sun Tack
2004-01-01
The PLUS7 fuel was developed with mixing vane grids for KSNP. For the transition core partly loaded with the PLUS7 fuels, the procedure to set up the optimum thermal margin model of the transition core was suggested by introducing AOPM concept into the screening method which determines the limiting assembly. According to the procedure, the optimum thermal margin model of the first transition core was set up by using a part of nuclear data for the first transition and the homogeneous core with PLUS7 fuels. The generic thermal margin model of PLUS7 fuel was generated with the AOPM of 138%. The overpower penalties on the first transition core were calculated to be 1.0 and 0.98 on the limiting assembly and the generic thermal margin model, respectively. It is not usual case to impose the overpower penalty on reload cores. It is considered that the lack of channel flow due to the difference of pressure drop between PLUS7 and STD fuels results in the decrease of DNBR. The AOPM of the first transition core is evaluated to be about 135% by using the optimum generic thermal margin model which involves the generic thermal margin model and the total overpower penalty. The STD fuel is not included among limiting assembly candidates in the second transition core, because they have much lower pin power than PLUS7 fuels. The reduced number of STD fuels near the limiting assembly candidates the flow from the limiting assembly to increase the thermal margin for the second transition core. It is expected that cycle specific overpower penalties increase the thermal margin for the transition core. Using the procedure to set up the optimum thermal margin model makes sure that the enhanced thermal margin of PLUS7 fuel can be sufficiently applied to not only the homogeneous core but also the transition core
Hybrid photovoltaic–thermal solar collectors dynamic modeling
International Nuclear Information System (INIS)
Amrizal, N.; Chemisana, D.; Rosell, J.I.
2013-01-01
Highlights: ► A hybrid photovoltaic/thermal dynamic model is presented. ► The model, once calibrated, can predict the power output for any set of climate data. ► The physical electrical model includes explicitly thermal and irradiance dependences. ► The results agree with those obtained through steady-state characterization. ► The model approaches the junction cell temperature through the system energy balance. -- Abstract: A hybrid photovoltaic/thermal transient model has been developed and validated experimentally. The methodology extends the quasi-dynamic thermal model stated in the EN 12975 in order to involve the electrical performance and consider the dynamic behavior minimizing constraints when characterizing the collector. A backward moving average filtering procedure has been applied to improve the model response for variable working conditions. Concerning the electrical part, the model includes the thermal and radiation dependences in its variables. The results revealed that the characteristic parameters included in the model agree reasonably well with the experimental values obtained from the standard steady-state and IV characteristic curve measurements. After a calibration process, the model is a suitable tool to predict the thermal and electrical performance of a hybrid solar collector, for a specific weather data set.
Directory of Open Access Journals (Sweden)
Asif Mahmood
Full Text Available Solar energy is the cleanest, renewable and most abundant source of energy available on earth. The main use of solar energy is to heat and cool buildings, heat water and to generate electricity. There are two types of solar energy collection system, the photovoltaic systems and the solar thermal collectors. The efficiency of any solar thermal system depend on the thermophysical properties of the operating fluids and the geometry/length of the system in which fluid is flowing. In the present research a simplified mathematical model for the solar thermal collectors is considered in the form of non-uniform unsteady stretching surface. The flow is induced by a non-uniform stretching of the porous sheet and the uniform magnetic field is applied in the transverse direction to the flow. The non-Newtonian Maxwell fluid model is utilized for the working fluid along with slip boundary conditions. Moreover the high temperature effect of thermal radiation and temperature dependent thermal conductivity are also included in the present model. The mathematical formulation is carried out through a boundary layer approach and the numerical computations are carried out for cu-water and TiO2-water nanofluids. Results are presented for the velocity and temperature profiles as well as the skin friction coefficient and Nusselt number and the discussion is concluded on the effect of various governing parameters on the motion, temperature variation, velocity gradient and the rate of heat transfer at the boundary. Keywords: Solar energy, Thermal collectors, Maxwell-nanofluid, Thermal radiation, Partial slip, Variable thermal conductivity
Flashover of a vacuum-insulator interface: A statistical model
Directory of Open Access Journals (Sweden)
W. A. Stygar
2004-07-01
Full Text Available We have developed a statistical model for the flashover of a 45° vacuum-insulator interface (such as would be found in an accelerator subject to a pulsed electric field. The model assumes that the initiation of a flashover plasma is a stochastic process, that the characteristic statistical component of the flashover delay time is much greater than the plasma formative time, and that the average rate at which flashovers occur is a power-law function of the instantaneous value of the electric field. Under these conditions, we find that the flashover probability is given by 1-exp(-E_{p}^{β}t_{eff}C/k^{β}, where E_{p} is the peak value in time of the spatially averaged electric field E(t, t_{eff}≡∫[E(t/E_{p}]^{β}dt is the effective pulse width, C is the insulator circumference, k∝exp(λ/d, and β and λ are constants. We define E(t as V(t/d, where V(t is the voltage across the insulator and d is the insulator thickness. Since the model assumes that flashovers occur at random azimuthal locations along the insulator, it does not apply to systems that have a significant defect, i.e., a location contaminated with debris or compromised by an imperfection at which flashovers repeatedly take place, and which prevents a random spatial distribution. The model is consistent with flashover measurements to within 7% for pulse widths between 0.5 ns and 10 μs, and to within a factor of 2 between 0.5 ns and 90 s (a span of over 11 orders of magnitude. For these measurements, E_{p} ranges from 64 to 651 kV/cm, d from 0.50 to 4.32 cm, and C from 4.96 to 95.74 cm. The model is significantly more accurate, and is valid over a wider range of parameters, than the J. C. Martin flashover relation that has been in use since 1971 [J. C. Martin on Pulsed Power, edited by T. H. Martin, A. H. Guenther, and M. Kristiansen (Plenum, New York, 1996]. We have generalized the statistical model to estimate the total-flashover probability of an
A Statistical Model for Regional Tornado Climate Studies.
Directory of Open Access Journals (Sweden)
Thomas H Jagger
Full Text Available Tornado reports are locally rare, often clustered, and of variable quality making it difficult to use them directly to describe regional tornado climatology. Here a statistical model is demonstrated that overcomes some of these difficulties and produces a smoothed regional-scale climatology of tornado occurrences. The model is applied to data aggregated at the level of counties. These data include annual population, annual tornado counts and an index of terrain roughness. The model has a term to capture the smoothed frequency relative to the state average. The model is used to examine whether terrain roughness is related to tornado frequency and whether there are differences in tornado activity by County Warning Area (CWA. A key finding is that tornado reports increase by 13% for a two-fold increase in population across Kansas after accounting for improvements in rating procedures. Independent of this relationship, tornadoes have been increasing at an annual rate of 1.9%. Another finding is the pattern of correlated residuals showing more Kansas tornadoes in a corridor of counties running roughly north to south across the west central part of the state consistent with the dryline climatology. The model is significantly improved by adding terrain roughness. The effect amounts to an 18% reduction in the number of tornadoes for every ten meter increase in elevation standard deviation. The model indicates that tornadoes are 51% more likely to occur in counties served by the CWAs of DDC and GID than elsewhere in the state. Flexibility of the model is illustrated by fitting it to data from Illinois, Mississippi, South Dakota, and Ohio.
A Statistical Model for Regional Tornado Climate Studies.
Jagger, Thomas H; Elsner, James B; Widen, Holly M
2015-01-01
Tornado reports are locally rare, often clustered, and of variable quality making it difficult to use them directly to describe regional tornado climatology. Here a statistical model is demonstrated that overcomes some of these difficulties and produces a smoothed regional-scale climatology of tornado occurrences. The model is applied to data aggregated at the level of counties. These data include annual population, annual tornado counts and an index of terrain roughness. The model has a term to capture the smoothed frequency relative to the state average. The model is used to examine whether terrain roughness is related to tornado frequency and whether there are differences in tornado activity by County Warning Area (CWA). A key finding is that tornado reports increase by 13% for a two-fold increase in population across Kansas after accounting for improvements in rating procedures. Independent of this relationship, tornadoes have been increasing at an annual rate of 1.9%. Another finding is the pattern of correlated residuals showing more Kansas tornadoes in a corridor of counties running roughly north to south across the west central part of the state consistent with the dryline climatology. The model is significantly improved by adding terrain roughness. The effect amounts to an 18% reduction in the number of tornadoes for every ten meter increase in elevation standard deviation. The model indicates that tornadoes are 51% more likely to occur in counties served by the CWAs of DDC and GID than elsewhere in the state. Flexibility of the model is illustrated by fitting it to data from Illinois, Mississippi, South Dakota, and Ohio.
Statistics Based Models for the Dynamics of Chernivtsi Children Disease
Directory of Open Access Journals (Sweden)
Igor G. Nesteruk
2017-10-01
Full Text Available Background. Simple mathematical models of contamination and SIR-model of spreading an infection were used to simulate the time dynamics of the unknown before children disease, which occurred in Chernivtsi (Ukraine. The cause of many cases of alopecia, which began in this city in August 1988 is still not fully clarified. According to the official report of the governmental commission, the last new cases occurred in the middle of November 1988, and the reason of the illness was reported as chemical exogenous intoxication. Later this illness became the name “Chernivtsi chemical disease”. Nevertheless, the significantly increased number of new cases of the local alopecia was registered almost three years and is still not clarified. Objective. The comparison of two different versions of the disease: chemical exogenous intoxication and infection. Identification of the parameters of mathematical models and prediction of the disease development. Methods. Analytical solutions of the contamination models and SIR-model for an epidemic are obtained. The optimal values of parameters with the use of linear regression were found. Results. The optimal values of the models parameters with the use of statistical approach were identified. The calculations showed that the infectious version of the disease is more reliable in comparison with the popular contamination one. The possible date of the epidemic beginning was estimated. Conclusions. The optimal parameters of SIR-model allow calculating the realistic number of victims and other characteristics of possible epidemic. They also show that increased number of cases of local alopecia could be a part of the same epidemic as “Chernivtsi chemical disease”.
Adaptive thermal modeling of Li-ion batteries
Rad, M.S.; Danilov, D.L.; Baghalha, M.; Kazemeini, M.; Notten, P.H.L.
2013-01-01
An accurate thermal model to predict the heat generation in rechargeable batteries is an essential tool for advanced thermal management in high power applications, such as electric vehicles. For such applications, the battery materials’ details and cell design are normally not provided. In this work
Frequency-domain thermal modelling of power semiconductor devices
DEFF Research Database (Denmark)
Ma, Ke; Blaabjerg, Frede; Andresen, Markus
2015-01-01
to correctly predict the device temperatures, especially when considering the thermal grease and heat sink attached to the power semiconductor devices. In this paper, the frequency-domain approach is applied to the modelling of thermal dynamics for power devices. The limits of the existing RC lump...
High power solid state retrofit lamp thermal characterization and modeling
Jakovenko, J.; Formánek, J.; Vladimír, J.; Husák, M.; Werkhoven, R.J.
2012-01-01
Thermal and thermo-mechanical modeling and characterization of solid state lightening (SSL) retrofit LED Lamp are presented in this paper. Paramount Importance is to design SSL lamps for reliability, in which thermal and thermo-mechanical aspects are key points. The main goal is to get a precise 3D
Linear mixed models a practical guide using statistical software
West, Brady T; Galecki, Andrzej T
2014-01-01
Highly recommended by JASA, Technometrics, and other journals, the first edition of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software, Second Edition continues to lead readers step by step through the process of fitting LMMs. This second edition covers additional topics on the application of LMMs that are valuable for data analysts in all fields. It also updates the case studies using the latest versions of the software procedures and provides up-to-date information on the options and features of the software procedures available for fitting LMMs in SAS, SPSS, Stata, R/S-plus, and HLM.New to the Second Edition A new chapter on models with crossed random effects that uses a case study to illustrate software procedures capable of fitting these models Power analysis methods for longitudinal and clustered study designs, including software options for power analyses and suggest...
Corrected Statistical Energy Analysis Model for Car Interior Noise
Directory of Open Access Journals (Sweden)
A. Putra
2015-01-01
Full Text Available Statistical energy analysis (SEA is a well-known method to analyze the flow of acoustic and vibration energy in a complex structure. For an acoustic space where significant absorptive materials are present, direct field component from the sound source dominates the total sound field rather than a reverberant field, where the latter becomes the basis in constructing the conventional SEA model. Such environment can be found in a car interior and thus a corrected SEA model is proposed here to counter this situation. The model is developed by eliminating the direct field component from the total sound field and only the power after the first reflection is considered. A test car cabin was divided into two subsystems and by using a loudspeaker as a sound source, the power injection method in SEA was employed to obtain the corrected coupling loss factor and the damping loss factor from the corrected SEA model. These parameters were then used to predict the sound pressure level in the interior cabin using the injected input power from the engine. The results show satisfactory agreement with the directly measured SPL.
Stochastic Spatial Models in Ecology: A Statistical Physics Approach
Pigolotti, Simone; Cencini, Massimo; Molina, Daniel; Muñoz, Miguel A.
2017-11-01
Ecosystems display a complex spatial organization. Ecologists have long tried to characterize them by looking at how different measures of biodiversity change across spatial scales. Ecological neutral theory has provided simple predictions accounting for general empirical patterns in communities of competing species. However, while neutral theory in well-mixed ecosystems is mathematically well understood, spatial models still present several open problems, limiting the quantitative understanding of spatial biodiversity. In this review, we discuss the state of the art in spatial neutral theory. We emphasize the connection between spatial ecological models and the physics of non-equilibrium phase transitions and how concepts developed in statistical physics translate in population dynamics, and vice versa. We focus on non-trivial scaling laws arising at the critical dimension D = 2 of spatial neutral models, and their relevance for biological populations inhabiting two-dimensional environments. We conclude by discussing models incorporating non-neutral effects in the form of spatial and temporal disorder, and analyze how their predictions deviate from those of purely neutral theories.
Percolation for a model of statistically inhomogeneous random media
International Nuclear Information System (INIS)
Quintanilla, J.; Torquato, S.
1999-01-01
We study clustering and percolation phenomena for a model of statistically inhomogeneous two-phase random media, including functionally graded materials. This model consists of inhomogeneous fully penetrable (Poisson distributed) disks and can be constructed for any specified variation of volume fraction. We quantify the transition zone in the model, defined by the frontier of the cluster of disks which are connected to the disk-covered portion of the model, by defining the coastline function and correlation functions for the coastline. We find that the behavior of these functions becomes largely independent of the specific choice of grade in volume fraction as the separation of length scales becomes large. We also show that the correlation function behaves in a manner similar to that of fractal Brownian motion. Finally, we study fractal characteristics of the frontier itself and compare to similar properties for two-dimensional percolation on a lattice. In particular, we show that the average location of the frontier appears to be related to the percolation threshold for homogeneous fully penetrable disks. copyright 1999 American Institute of Physics
Glass viscosity calculation based on a global statistical modelling approach
Energy Technology Data Exchange (ETDEWEB)
Fluegel, Alex
2007-02-01
A global statistical glass viscosity model was developed for predicting the complete viscosity curve, based on more than 2200 composition-property data of silicate glasses from the scientific literature, including soda-lime-silica container and float glasses, TV panel glasses, borosilicate fiber wool and E type glasses, low expansion borosilicate glasses, glasses for nuclear waste vitrification, lead crystal glasses, binary alkali silicates, and various further compositions from over half a century. It is shown that within a measurement series from a specific laboratory the reported viscosity values are often over-estimated at higher temperatures due to alkali and boron oxide evaporation during the measurement and glass preparation, including data by Lakatos et al. (1972) and the recently published High temperature glass melt property database for process modeling by Seward et al. (2005). Similarly, in the glass transition range many experimental data of borosilicate glasses are reported too high due to phase separation effects. The developed global model corrects those errors. The model standard error was 9-17°C, with R^2 = 0.985-0.989. The prediction 95% confidence interval for glass in mass production largely depends on the glass composition of interest, the composition uncertainty, and the viscosity level. New insights in the mixed-alkali effect are provided.
International Nuclear Information System (INIS)
Zhang, Jinzhao; Segurado, Jacobo; Schneidesch, Christophe
2013-01-01
Since 1980's, Tractebel Engineering (TE) has being developed and applied a multi-physical modelling and safety analyses capability, based on a code package consisting of the best estimate 3D neutronic (PANTHER), system thermal hydraulic (RELAP5), core sub-channel thermal hydraulic (COBRA-3C), and fuel thermal mechanic (FRAPCON/FRAPTRAN) codes. A series of methodologies have been developed to perform and to license the reactor safety analysis and core reload design, based on the deterministic bounding approach. Following the recent trends in research and development as well as in industrial applications, TE has been working since 2010 towards the application of the statistical sensitivity and uncertainty analysis methods to the multi-physical modelling and licensing safety analyses. In this paper, the TE multi-physical modelling and safety analyses capability is first described, followed by the proposed TE best estimate plus statistical uncertainty analysis method (BESUAM). The chosen statistical sensitivity and uncertainty analysis methods (non-parametric order statistic method or bootstrap) and tool (DAKOTA) are then presented, followed by some preliminary results of their applications to FRAPCON/FRAPTRAN simulation of OECD RIA fuel rod codes benchmark and RELAP5/MOD3.3 simulation of THTF tests. (authors)
Viscous and thermal modelling of thermoplastic composites forming process
Guzman, Eduardo; Liang, Biao; Hamila, Nahiene; Boisse, Philippe
2016-10-01
Thermoforming thermoplastic prepregs is a fast manufacturing process. It is suitable for automotive composite parts manufacturing. The simulation of thermoplastic prepreg forming is achieved by alternate thermal and mechanical analyses. The thermal properties are obtained from a mesoscopic analysis and a homogenization procedure. The forming simulation is based on a viscous-hyperelastic approach. The thermal simulations define the coefficients of the mechanical model that depend on the temperature. The forming simulations modify the boundary conditions and the internal geometry of the thermal analyses. The comparison of the simulation with an experimental thermoforming of a part representative of automotive applications shows the efficiency of the approach.
Thermal hydraulic model validation for HOR mixed core fuel management
International Nuclear Information System (INIS)
Gibcus, H.P.M.; Vries, J.W. de; Leege, P.F.A. de
1997-01-01
A thermal-hydraulic core management model has been developed for the Hoger Onderwijsreactor (HOR), a 2 MW pool-type university research reactor. The model was adopted for safety analysis purposes in the framework of HEU/LEU core conversion studies. It is applied in the thermal-hydraulic computer code SHORT (Steady-state HOR Thermal-hydraulics) which is presently in use in designing core configurations and for in-core fuel management. An elaborate measurement program was performed for establishing the core hydraulic characteristics for a variety of conditions. The hydraulic data were obtained with a dummy fuel element with special equipment allowing a.o. direct measurement of the true core flow rate. Using these data the thermal-hydraulic model was validated experimentally. The model, experimental tests, and model validation are discussed. (author)
A Statistical Toolbox For Mining And Modeling Spatial Data
Directory of Open Access Journals (Sweden)
D’Aubigny Gérard
2016-12-01
Full Text Available Most data mining projects in spatial economics start with an evaluation of a set of attribute variables on a sample of spatial entities, looking for the existence and strength of spatial autocorrelation, based on the Moran’s and the Geary’s coefficients, the adequacy of which is rarely challenged, despite the fact that when reporting on their properties, many users seem likely to make mistakes and to foster confusion. My paper begins by a critical appraisal of the classical definition and rational of these indices. I argue that while intuitively founded, they are plagued by an inconsistency in their conception. Then, I propose a principled small change leading to corrected spatial autocorrelation coefficients, which strongly simplifies their relationship, and opens the way to an augmented toolbox of statistical methods of dimension reduction and data visualization, also useful for modeling purposes. A second section presents a formal framework, adapted from recent work in statistical learning, which gives theoretical support to our definition of corrected spatial autocorrelation coefficients. More specifically, the multivariate data mining methods presented here, are easily implementable on the existing (free software, yield methods useful to exploit the proposed corrections in spatial data analysis practice, and, from a mathematical point of view, whose asymptotic behavior, already studied in a series of papers by Belkin & Niyogi, suggests that they own qualities of robustness and a limited sensitivity to the Modifiable Areal Unit Problem (MAUP, valuable in exploratory spatial data analysis.
Statistical mechanics of learning orthogonal signals for general covariance models
International Nuclear Information System (INIS)
Hoyle, David C
2010-01-01
Statistical mechanics techniques have proved to be useful tools in quantifying the accuracy with which signal vectors are extracted from experimental data. However, analysis has previously been limited to specific model forms for the population covariance C, which may be inappropriate for real world data sets. In this paper we obtain new statistical mechanical results for a general population covariance matrix C. For data sets consisting of p sample points in R N we use the replica method to study the accuracy of orthogonal signal vectors estimated from the sample data. In the asymptotic limit of N,p→∞ at fixed α = p/N, we derive analytical results for the signal direction learning curves. In the asymptotic limit the learning curves follow a single universal form, each displaying a retarded learning transition. An explicit formula for the location of the retarded learning transition is obtained and we find marked variation in the location of the retarded learning transition dependent on the distribution of population covariance eigenvalues. The results of the replica analysis are confirmed against simulation
Mommert, M.; Jedicke, R.; Trilling, D. E.
2018-02-01
The majority of known asteroid diameters are derived from thermal-infrared observations. Diameters are derived using asteroid thermal models that approximate their surface temperature distributions and compare the measured thermal-infrared flux with model-dependent predictions. The most commonly used thermal model is the Near-Earth Asteroid Thermal Model (NEATM), which is usually perceived as superior to other models like the Fast-Rotating Model (FRM). We investigate the applicability of the NEATM and the FRM to thermal-infrared observations of Near-Earth Objects using synthetic asteroids with properties based on the real Near-Earth Asteroid (NEA) population. We find the NEATM to provide more accurate diameters and albedos than the FRM in most cases, with a few exceptions. The modeling results are barely affected by the physical properties of the objects, but we find a large impact of the solar phase angle on the modeling results. We conclude that the NEATM provides statistically more robust diameter estimates for NEAs observed at solar phase angles less than ∼65°, while the FRM provides more robust diameter estimates for solar phase angles greater than ∼65°. We estimate that <5% of all NEA diameters and albedos derived up to date are affected by systematic effects that are of the same order of magnitude as the typical thermal model uncertainties. We provide statistical correction functions for diameters and albedos derived using the NEATM and FRM as a function of solar phase angle.
Representation of the contextual statistical model by hyperbolic amplitudes
International Nuclear Information System (INIS)
Khrennikov, Andrei
2005-01-01
We continue the development of a so-called contextual statistical model (here context has the meaning of a complex of physical conditions). It is shown that, besides contexts producing the conventional trigonometric cos-interference, there exist contexts producing the hyperbolic cos-interference. Starting with the corresponding interference formula of total probability we represent such contexts by hyperbolic probabilistic amplitudes or in the abstract formalism by normalized vectors of a hyperbolic analogue of the Hilbert space. There is obtained a hyperbolic Born's rule. Incompatible observables are represented by noncommutative operators. This paper can be considered as the first step towards hyperbolic quantum probability. We also discuss possibilities of experimental verification of hyperbolic quantum mechanics: in physics of elementary particles, string theory as well as in experiments with nonphysical systems, e.g., in psychology, cognitive sciences, and economy
α-ternary decay of Cf isotopes, statistical model
International Nuclear Information System (INIS)
Joseph, Jayesh George; Santhosh, K.P.
2017-01-01
The process of splitting a heavier nucleus to three simultaneous fragments is termed as ternary fission and compared to usual binary fission, it is a rare process. Depending on the nature of third particle either it is called light charged particle (LCP) accompanying fission if it is light or true ternary fission if all three fragments have nearly same mass distributions. After experimental observations in early seventies, initially with a slow pace, now theoretical studies in ternary fission has turned to a hot topic in nuclear decay studies especially in past one decade. Mean while various models have been developed, existing being modified and seeking for new with a hope that it can beam a little more light to the profound nature of nuclear interaction. In this study a statistical method, level density formulation, has been employed
Smooth extrapolation of unknown anatomy via statistical shape models
Grupp, R. B.; Chiang, H.; Otake, Y.; Murphy, R. J.; Gordon, C. R.; Armand, M.; Taylor, R. H.
2015-03-01
Several methods to perform extrapolation of unknown anatomy were evaluated. The primary application is to enhance surgical procedures that may use partial medical images or medical images of incomplete anatomy. Le Fort-based, face-jaw-teeth transplant is one such procedure. From CT data of 36 skulls and 21 mandibles separate Statistical Shape Models of the anatomical surfaces were created. Using the Statistical Shape Models, incomplete surfaces were projected to obtain complete surface estimates. The surface estimates exhibit non-zero error in regions where the true surface is known; it is desirable to keep the true surface and seamlessly merge the estimated unknown surface. Existing extrapolation techniques produce non-smooth transitions from the true surface to the estimated surface, resulting in additional error and a less aesthetically pleasing result. The three extrapolation techniques evaluated were: copying and pasting of the surface estimate (non-smooth baseline), a feathering between the patient surface and surface estimate, and an estimate generated via a Thin Plate Spline trained from displacements between the surface estimate and corresponding vertices of the known patient surface. Feathering and Thin Plate Spline approaches both yielded smooth transitions. However, feathering corrupted known vertex values. Leave-one-out analyses were conducted, with 5% to 50% of known anatomy removed from the left-out patient and estimated via the proposed approaches. The Thin Plate Spline approach yielded smaller errors than the other two approaches, with an average vertex error improvement of 1.46 mm and 1.38 mm for the skull and mandible respectively, over the baseline approach.
Statistical shape modeling based renal volume measurement using tracked ultrasound
Pai Raikar, Vipul; Kwartowitz, David M.
2017-03-01
Autosomal dominant polycystic kidney disease (ADPKD) is the fourth most common cause of kidney transplant worldwide accounting for 7-10% of all cases. Although ADPKD usually progresses over many decades, accurate risk prediction is an important task.1 Identifying patients with progressive disease is vital to providing new treatments being developed and enable them to enter clinical trials for new therapy. Among other factors, total kidney volume (TKV) is a major biomarker predicting the progression of ADPKD. Consortium for Radiologic Imaging Studies in Polycystic Kidney Disease (CRISP)2 have shown that TKV is an early, and accurate measure of cystic burden and likely growth rate. It is strongly associated with loss of renal function.3 While ultrasound (US) has proven as an excellent tool for diagnosing the disease; monitoring short-term changes using ultrasound has been shown to not be accurate. This is attributed to high operator variability and reproducibility as compared to tomographic modalities such as CT and MR (Gold standard). Ultrasound has emerged as one of the standout modality for intra-procedural imaging and with methods for spatial localization has afforded us the ability to track 2D ultrasound in physical space which it is being used. In addition to this, the vast amount of recorded tomographic data can be used to generate statistical shape models that allow us to extract clinical value from archived image sets. In this work, we aim at improving the prognostic value of US in managing ADPKD by assessing the accuracy of using statistical shape model augmented US data, to predict TKV, with the end goal of monitoring short-term changes.
Numerical modeling of aquifer thermal energy storage system
Energy Technology Data Exchange (ETDEWEB)
Kim, Jongchan [Korea Institute of Geoscience and Mineral Resources, Geothermal Resources Department, 92 Gwahang-no, Yuseong-gu, Daejeon 305-350 (Korea, Republic of); Kongju National University, Department of Geoenvironmental Sciences, 182 Singwan-dong, Gongju-si, Chungnam 314-701 (Korea, Republic of); Lee, Youngmin [Korea Institute of Geoscience and Mineral Resources, Geothermal Resources Department, 92 Gwahang-no, Yuseong-gu, Daejeon 305-350 (Korea, Republic of); Yoon, Woon Sang; Jeon, Jae Soo [nexGeo Inc., 134-1 Garak 2-dong, Songpa-gu, Seoul 138-807 (Korea, Republic of); Koo, Min-Ho; Keehm, Youngseuk [Kongju National University, Department of Geoenvironmental Sciences, 182 Singwan-dong, Gongju-si, Chungnam 314-701 (Korea, Republic of)
2010-12-15
The performance of the ATES (aquifer thermal energy storage) system primarily depends on the thermal interference between warm and cold thermal energy stored in an aquifer. Additionally the thermal interference is mainly affected by the borehole distance, the hydraulic conductivity, and the pumping/injection rate. Thermo-hydraulic modeling was performed to identify the thermal interference by three parameters and to estimate the system performance change by the thermal interference. Modeling results indicate that the thermal interference grows as the borehole distance decreases, as the hydraulic conductivity increases, and as the pumping/injection rate increases. The system performance analysis indicates that if {eta} (the ratio of the length of the thermal front to the distance between two boreholes) is lower than unity, the system performance is not significantly affected, but if {eta} is equal to unity, the system performance falls up to {proportional_to}22%. Long term modeling for a factory in Anseong was conducted to test the applicability of the ATES system. When the pumping/injection rate is 100 m{sup 3}/day, system performances during the summer and winter after 3 years of operation are estimated to be {proportional_to}125 kW and {proportional_to}110 kW, respectively. Therefore, 100 m{sup 3}/day of the pumping/injection rate satisfies the energy requirements ({proportional_to}70 kW) for the factory. (author)
Critical, statistical, and thermodynamical properties of lattice models
Energy Technology Data Exchange (ETDEWEB)
Varma, Vipin Kerala
2013-10-15
In this thesis we investigate zero temperature and low temperature properties - critical, statistical and thermodynamical - of lattice models in the contexts of bosonic cold atom systems, magnetic materials, and non-interacting particles on various lattice geometries. We study quantum phase transitions in the Bose-Hubbard model with higher body interactions, as relevant for optical lattice experiments of strongly interacting bosons, in one and two dimensions; the universality of the Mott insulator to superfluid transition is found to remain unchanged for even large three body interaction strengths. A systematic renormalization procedure is formulated to fully re-sum these higher (three and four) body interactions into the two body terms. In the strongly repulsive limit, we analyse the zero and low temperature physics of interacting hard-core bosons on the kagome lattice at various fillings. Evidence for a disordered phase in the Ising limit of the model is presented; in the strong coupling limit, the transition between the valence bond solid and the superfluid is argued to be first order at the tip of the solid lobe.
The statistical multifragmentation model: Origins and recent advances
International Nuclear Information System (INIS)
Donangelo, R.; Souza, S. R.
2016-01-01
We review the Statistical Multifragmentation Model (SMM) which considers a generalization of the liquid-drop model for hot nuclei and allows one to calculate thermodynamic quantities characterizing the nuclear ensemble at the disassembly stage. We show how to determine probabilities of definite partitions of finite nuclei and how to determine, through Monte Carlo calculations, observables such as the caloric curve, multiplicity distributions, heat capacity, among others. Some experimental measurements of the caloric curve confirmed the SMM predictions of over 10 years before, leading to a surge in the interest in the model. However, the experimental determination of the fragmentation temperatures relies on the yields of different isotopic species, which were not correctly calculated in the schematic, liquid-drop picture, employed in the SMM. This led to a series of improvements in the SMM, in particular to the more careful choice of nuclear masses and energy densities, specially for the lighter nuclei. With these improvements the SMM is able to make quantitative determinations of isotope production. We show the application of SMM to the production of exotic nuclei through multifragmentation. These preliminary calculations demonstrate the need for a careful choice of the system size and excitation energy to attain maximum yields.
Critical, statistical, and thermodynamical properties of lattice models
International Nuclear Information System (INIS)
Varma, Vipin Kerala
2013-10-01
In this thesis we investigate zero temperature and low temperature properties - critical, statistical and thermodynamical - of lattice models in the contexts of bosonic cold atom systems, magnetic materials, and non-interacting particles on various lattice geometries. We study quantum phase transitions in the Bose-Hubbard model with higher body interactions, as relevant for optical lattice experiments of strongly interacting bosons, in one and two dimensions; the universality of the Mott insulator to superfluid transition is found to remain unchanged for even large three body interaction strengths. A systematic renormalization procedure is formulated to fully re-sum these higher (three and four) body interactions into the two body terms. In the strongly repulsive limit, we analyse the zero and low temperature physics of interacting hard-core bosons on the kagome lattice at various fillings. Evidence for a disordered phase in the Ising limit of the model is presented; in the strong coupling limit, the transition between the valence bond solid and the superfluid is argued to be first order at the tip of the solid lobe.
Constraining statistical-model parameters using fusion and spallation reactions
Directory of Open Access Journals (Sweden)
Charity Robert J.
2011-10-01
Full Text Available The de-excitation of compound nuclei has been successfully described for several decades by means of statistical models. However, such models involve a large number of free parameters and ingredients that are often underconstrained by experimental data. We show how the degeneracy of the model ingredients can be partially lifted by studying different entrance channels for de-excitation, which populate different regions of the parameter space of the compound nucleus. Fusion reactions, in particular, play an important role in this strategy because they ﬁx three out of four of the compound-nucleus parameters (mass, charge and total excitation energy. The present work focuses on ﬁssion and intermediate-mass-fragment emission cross sections. We prove how equivalent parameter sets for fusion-ﬁssion reactions can be resolved using another entrance channel, namely spallation reactions. Intermediate-mass-fragment emission can be constrained in a similar way. An interpretation of the best-ﬁt IMF barriers in terms of the Wigner energies of the nascent fragments is discussed.
Optimizing DNA assembly based on statistical language modelling.
Fang, Gang; Zhang, Shemin; Dong, Yafei
2017-12-15
By successively assembling genetic parts such as BioBrick according to grammatical models, complex genetic constructs composed of dozens of functional blocks can be built. However, usually every category of genetic parts includes a few or many parts. With increasing quantity of genetic parts, the process of assembling more than a few sets of these parts can be expensive, time consuming and error prone. At the last step of assembling it is somewhat difficult to decide which part should be selected. Based on statistical language model, which is a probability distribution P(s) over strings S that attempts to reflect how frequently a string S occurs as a sentence, the most commonly used parts will be selected. Then, a dynamic programming algorithm was designed to figure out the solution of maximum probability. The algorithm optimizes the results of a genetic design based on a grammatical model and finds an optimal solution. In this way, redundant operations can be reduced and the time and cost required for conducting biological experiments can be minimized. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
Terminal-Dependent Statistical Inference for the FBSDEs Models
Directory of Open Access Journals (Sweden)
Yunquan Song
2014-01-01
Full Text Available The original stochastic differential equations (OSDEs and forward-backward stochastic differential equations (FBSDEs are often used to model complex dynamic process that arise in financial, ecological, and many other areas. The main difference between OSDEs and FBSDEs is that the latter is designed to depend on a terminal condition, which is a key factor in some financial and ecological circumstances. It is interesting but challenging to estimate FBSDE parameters from noisy data and the terminal condition. However, to the best of our knowledge, the terminal-dependent statistical inference for such a model has not been explored in the existing literature. We proposed a nonparametric terminal control variables estimation method to address this problem. The reason why we use the terminal control variables is that the newly proposed inference procedures inherit the terminal-dependent characteristic. Through this new proposed method, the estimators of the functional coefficients of the FBSDEs model are obtained. The asymptotic properties of the estimators are also discussed. Simulation studies show that the proposed method gives satisfying estimates for the FBSDE parameters from noisy data and the terminal condition. A simulation is performed to test the feasibility of our method.
Statistical inference for imperfect maintenance models with missing data
International Nuclear Information System (INIS)
Dijoux, Yann; Fouladirad, Mitra; Nguyen, Dinh Tuan
2016-01-01
The paper considers complex industrial systems with incomplete maintenance history. A corrective maintenance is performed after the occurrence of a failure and its efficiency is assumed to be imperfect. In maintenance analysis, the databases are not necessarily complete. Specifically, the observations are assumed to be window-censored. This situation arises relatively frequently after the purchase of a second-hand unit or in the absence of maintenance record during the burn-in phase. The joint assessment of the wear-out of the system and the maintenance efficiency is investigated under missing data. A review along with extensions of statistical inference procedures from an observation window are proposed in the case of perfect and minimal repair using the renewal and Poisson theories, respectively. Virtual age models are employed to model imperfect repair. In this framework, new estimation procedures are developed. In particular, maximum likelihood estimation methods are derived for the most classical virtual age models. The benefits of the new estimation procedures are highlighted by numerical simulations and an application to a real data set. - Highlights: • New estimation procedures for window-censored observations and imperfect repair. • Extensions of inference methods for perfect and minimal repair with missing data. • Overview of maximum likelihood method with complete and incomplete observations. • Benefits of the new procedures highlighted by simulation studies and real application.
The statistical multifragmentation model: Origins and recent advances
Energy Technology Data Exchange (ETDEWEB)
Donangelo, R., E-mail: donangel@fing.edu.uy [Instituto de Física, Facultad de Ingeniería, Universidad de la República, Julio Herrera y Reissig 565, 11300, Montevideo (Uruguay); Instituto de Física, Universidade Federal do Rio de Janeiro, C.P. 68528, 21941-972 Rio de Janeiro - RJ (Brazil); Souza, S. R., E-mail: srsouza@if.ufrj.br [Instituto de Física, Universidade Federal do Rio de Janeiro, C.P. 68528, 21941-972 Rio de Janeiro - RJ (Brazil); Instituto de Física, Universidade Federal do Rio Grande do Sul, C.P. 15051, 91501-970 Porto Alegre - RS (Brazil)
2016-07-07
We review the Statistical Multifragmentation Model (SMM) which considers a generalization of the liquid-drop model for hot nuclei and allows one to calculate thermodynamic quantities characterizing the nuclear ensemble at the disassembly stage. We show how to determine probabilities of definite partitions of finite nuclei and how to determine, through Monte Carlo calculations, observables such as the caloric curve, multiplicity distributions, heat capacity, among others. Some experimental measurements of the caloric curve confirmed the SMM predictions of over 10 years before, leading to a surge in the interest in the model. However, the experimental determination of the fragmentation temperatures relies on the yields of different isotopic species, which were not correctly calculated in the schematic, liquid-drop picture, employed in the SMM. This led to a series of improvements in the SMM, in particular to the more careful choice of nuclear masses and energy densities, specially for the lighter nuclei. With these improvements the SMM is able to make quantitative determinations of isotope production. We show the application of SMM to the production of exotic nuclei through multifragmentation. These preliminary calculations demonstrate the need for a careful choice of the system size and excitation energy to attain maximum yields.
Statistical Clustering and Compositional Modeling of Iapetus VIMS Spectral Data
Pinilla-Alonso, N.; Roush, T. L.; Marzo, G.; Dalle Ore, C. M.; Cruikshank, D. P.
2009-12-01
It has long been known that the surfaces of Saturn's major satellites are predominantly icy objects [e.g. 1 and references therein]. Since 2004, these bodies have been the subject of observations by the Cassini-VIMS (Visual and Infrared Mapping Spectrometer) experiment [2]. Iapetus has the unique property that the hemisphere centered on the apex of its locked synchronous orbital motion around Saturn has a very low geometrical albedo of 2-6%, while the opposite hemisphere is about 10 times more reflective. The nature and origin of the dark material of Iapetus has remained a question since its discovery [3 and references therein]. The nature of this material and how it is distributed on the surface of this body, can shed new light into the knowledge of the Saturnian system. We apply statistical clustering [4] and theoretical modeling [5,6] to address the surface composition of Iapetus. The VIMS data evaluated were obtained during the second flyby of Iapetus, in September 2007. This close approach allowed VIMS to obtain spectra at relatively high spatial resolution, ~1-22 km/pixel. The data we study sampled the trailing hemisphere and part of the dark leading one. The statistical clustering [4] is used to identify statistically distinct spectra on Iapetus. The composition of these distinct spectra are evaluated using theoretical models [5,6]. We thank Allan Meyer for his help. This research was supported by an appointment to the NASA Postdoctoral Program at the Ames Research Center, administered by Oak Ridge Associated Universities through a contract with NASA. [1] A, Coradini et al., 2009, Earth, Moon & Planets, 105, 289-310. [2] Brown et al., 2004, Space Science Reviews, 115, 111-168. [3] Cruikshank, D. et al Icarus, 2008, 193, 334-343. [4] Marzo, G. et al. 2008, Journal of Geophysical Research, 113, E12, CiteID E12009. [5] Hapke, B. 1993, Theory of reflectance and emittance spectroscopy, Cambridge University Press. [6] Shkuratov, Y. et al. 1999, Icarus, 137, 235-246.
Mahmood, Asif; Aziz, Asim; Jamshed, Wasim; Hussain, Sajid
Solar energy is the cleanest, renewable and most abundant source of energy available on earth. The main use of solar energy is to heat and cool buildings, heat water and to generate electricity. There are two types of solar energy collection system, the photovoltaic systems and the solar thermal collectors. The efficiency of any solar thermal system depend on the thermophysical properties of the operating fluids and the geometry/length of the system in which fluid is flowing. In the present research a simplified mathematical model for the solar thermal collectors is considered in the form of non-uniform unsteady stretching surface. The flow is induced by a non-uniform stretching of the porous sheet and the uniform magnetic field is applied in the transverse direction to the flow. The non-Newtonian Maxwell fluid model is utilized for the working fluid along with slip boundary conditions. Moreover the high temperature effect of thermal radiation and temperature dependent thermal conductivity are also included in the present model. The mathematical formulation is carried out through a boundary layer approach and the numerical computations are carried out for cu-water and TiO2 -water nanofluids. Results are presented for the velocity and temperature profiles as well as the skin friction coefficient and Nusselt number and the discussion is concluded on the effect of various governing parameters on the motion, temperature variation, velocity gradient and the rate of heat transfer at the boundary.
Towards a Statistical Model of Tropical Cyclone Genesis
Fernandez, A.; Kashinath, K.; McAuliffe, J.; Prabhat, M.; Stark, P. B.; Wehner, M. F.
2017-12-01
Tropical Cyclones (TCs) are important extreme weather phenomena that have a strong impact on humans. TC forecasts are largely based on global numerical models that produce TC-like features. Aspects of Tropical Cyclones such as their formation/genesis, evolution, intensification and dissipation over land are important and challenging problems in climate science. This study investigates the environmental conditions associated with Tropical Cyclone Genesis (TCG) by testing how accurately a statistical model can predict TCG in the CAM5.1 climate model. TCG events are defined using TECA software @inproceedings{Prabhat2015teca, title={TECA: Petascale Pattern Recognition for Climate Science}, author={Prabhat and Byna, Surendra and Vishwanath, Venkatram and Dart, Eli and Wehner, Michael and Collins, William D}, booktitle={Computer Analysis of Images and Patterns}, pages={426-436}, year={2015}, organization={Springer}} to extract TC trajectories from CAM5.1. L1-regularized logistic regression (L1LR) is applied to the CAM5.1 output. The predictions have nearly perfect accuracy for data not associated with TC tracks and high accuracy differentiating between high vorticity and low vorticity systems. The model's active variables largely correspond to current hypotheses about important factors for TCG, such as wind field patterns and local pressure minima, and suggests new routes for investigation. Furthermore, our model's predictions of TC activity are competitive with the output of an instantaneous version of Emanuel and Nolan's Genesis Potential Index (GPI) @inproceedings{eman04, title = "Tropical cyclone activity and the global climate system", author = "Kerry Emanuel and Nolan, {David S.}", year = "2004", pages = "240-241", booktitle = "26th Conference on Hurricanes and Tropical Meteorology"}.
Editorial to: Six papers on Dynamic Statistical Models
DEFF Research Database (Denmark)
2014-01-01
statistical methodology and theory for large and complex data sets that included biostatisticians and mathematical statisticians from three faculties at the University of Copenhagen. The satellite meeting took place August 17–19, 2011. Its purpose was to bring together researchers in statistics and related......The following six papers are based on invited lectures at the satellite meeting held at the University of Copenhagen before the 58th World Statistics Congress of the International Statistical Institute in Dublin in 2011. At the invitation of the Bernoulli Society, the satellite meeting...... was organized around the theme “Dynamic Statistical Models” as a part of the Program of Excellence at the University of Copenhagen on “Statistical methods for complex and high dimensional models” (http://statistics.ku.dk/). The Excellence Program in Statistics was a research project to develop and investigate...
Thermal automobile interior model; Thermisches Pkw-Innenraum-Modell
Energy Technology Data Exchange (ETDEWEB)
Flieger, Bjoern; Streblow, Rita; Mueller, Dirk [RWTH Aachen (Germany). E.ON Energieforschungszentrum
2012-11-01
The energy demand of climate-control instruments is an increasingly important focus of study in the automobile industry. The ratio of the energy demand for the engine as opposed to that of other car components will greatly change in the future. Especially for electrical vehicles the auxiliary energy use is very critical because of the limited battery capacity. Thus, the aim of this research project is to investigate means of more efficiently using the available energy by maintaining comfort criteria for all passengers. To realize this, a simulation model of a car interior cabin is being developed with which conclusions can be drawn, under the given boundary conditions, about the air circulation and -states as well as about the resulting energy demand to evaluate the efficiency and the thermal comfort. (orig.)
Modelling thermal plume impacts - Kalpakkam approach
International Nuclear Information System (INIS)
Rao, T.S.; Anup Kumar, B.; Narasimhan, S.V.
2002-01-01
A good understanding of temperature patterns in the receiving waters is essential to know the heat dissipation from thermal plumes originating from coastal power plants. The seasonal temperature profiles of the Kalpakkam coast near Madras Atomic Power Station (MAPS) thermal out fall site are determined and analysed. It is observed that the seasonal current reversal in the near shore zone is one of the major mechanisms for the transport of effluents away from the point of mixing. To further refine our understanding of the mixing and dilution processes, it is necessary to numerically simulate the coastal ocean processes by parameterising the key factors concerned. In this paper, we outline the experimental approach to achieve this objective. (author)
Thermal ripples in model molybdenum disulfide monolayers
Energy Technology Data Exchange (ETDEWEB)
Remsing, Richard C.; Klein, Michael L. [Institute for Computational Molecular Science, Center for the Computational, Design of Functional Layered Materials, and Department of Chemistry, Temple University, 1925 N. 12th St., 19122, Philadelphia, PA (United States); Waghmare, Umesh V. [Theoretical Sciences Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, 560 064, Jakkur, Bangalore (India)
2017-01-15
Molybdenum disulfide (MoS{sub 2}) monolayers have the potential to revolutionize nanotechnology. To reach this potential, it will be necessary to understand the behavior of this two-dimensional (2D) material on large length scales and under thermal conditions. Herein, we use molecular dynamics (MD) simulations to investigate the nature of the rippling induced by thermal fluctuations in monolayers of the 2H and 1T phases of MoS{sub 2}. The 1T phase is found to be more rigid than the 2H phase. Both monolayer phases are predicted to follow long wavelength scaling behavior typical of systems with anharmonic coupling between vibrational modes as predicted by classic theories of membrane-like systems. (copyright 2017 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)
Approach to chemical equilibrium in thermal models
International Nuclear Information System (INIS)
Boal, D.H.
1984-01-01
The experimentally measured (μ - , charged particle)/(μ - ,n) and (p,n/p,p') ratios for the emission of energetic nucleons are used to estimate the time evolution of a system of secondary nucleons produced in a direct interaction of a projectile or captured muon. The values of these ratios indicate that chemical equilibrium is not achieved among the secondary nucleons in noncomposite induced reactions, and this restricts the time scale for the emission of energetic nucleons to be about 0.7 x 10 -23 sec. It is shown that the reason why thermal equilibrium can be reached so rapidly for a particular nucleon species is that the sum of the particle spectra produced in multiple direct reactions looks surprisingly thermal. The rate equations used to estimate the reaction times for muon and nucleon induced reactions are then applied to heavy ion collisions, and it is shown that chemical equilibrium can be reached more rapidly, as one would expect
Development of thermal LED Model | Kapitonov | Journal of ...
African Journals Online (AJOL)
Journal of Fundamental and Applied Sciences ... operating conditions of LEDs at the design stage, taking into account a cooling system in use. ... The created models will allow to reveal unfavorable thermal operating modes for LEDs and, ...
Modelling and analysis of radial thermal stresses and temperature ...
African Journals Online (AJOL)
user
The temperature field, heat transfer rate and thermal stresses were investigated with numerical simulation models using FORTRAN FE (finite element) software. ...... specific heats, International Communications in Heat and Mass Transfer, Vol.
Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance
Wang, Xiao-Yen J.; Fabanich, William Anthony; Schmitz, Paul C.
2014-01-01
This presentation describes the capabilities of three-dimensional thermal power model of advanced stirling radioisotope generator (ASRG). The performance of the ASRG is presented for different scenario, such as Venus flyby with or without the auxiliary cooling system.
Coupled electrochemical thermal modelling of a novel Li-ion battery pack thermal management system
International Nuclear Information System (INIS)
Basu, Suman; Hariharan, Krishnan S.; Kolake, Subramanya Mayya; Song, Taewon; Sohn, Dong Kee; Yeo, Taejung
2016-01-01
Highlights: • Three-dimensional electrochemical thermal model of Li-ion battery pack using computational fluid dynamics (CFD). • Novel pack design for compact liquid cooling based thermal management system. • Simple temperature estimation algorithm for the cells in the pack using the results from the model. • Sensitivity of the thermal performance to contact resistance has been investigated. - Abstract: Thermal management system is of critical importance for a Li-ion battery pack, as high performance and long battery pack life can be simultaneously achieved when operated within a narrow range of temperature around the room temperature. An efficient thermal management system is required to keep the battery temperature in this range, despite widely varying operating conditions. A novel liquid coolant based thermal management system, for 18,650 battery pack has been introduced herein. This system is designed to be compact and economical without compromising safety. A coupled three-dimensional (3D) electrochemical thermal model is constructed for the proposed Li-ion battery pack. The model is used to evaluate the effects of different operating conditions like coolant flow-rate and discharge current on the pack temperature. Contact resistance is found to have the strongest impact on the thermal performance of the pack. From the numerical solution, a simple and novel temperature correlation of predicting the temperatures of all the individual cells given the temperature measurement of one cell is devised and validated with experimental results. Such coefficients have great potential of reducing the sensor requirement and complexity in a large Li-ion battery pack, typical of an electric vehicle.
The issue of statistical power for overall model fit in evaluating structural equation models
Directory of Open Access Journals (Sweden)
Richard HERMIDA
2015-06-01
Full Text Available Statistical power is an important concept for psychological research. However, examining the power of a structural equation model (SEM is rare in practice. This article provides an accessible review of the concept of statistical power for the Root Mean Square Error of Approximation (RMSEA index of overall model fit in structural equation modeling. By way of example, we examine the current state of power in the literature by reviewing studies in top Industrial-Organizational (I/O Psychology journals using SEMs. Results indicate that in many studies, power is very low, which implies acceptance of invalid models. Additionally, we examined methodological situations which may have an influence on statistical power of SEMs. Results showed that power varies significantly as a function of model type and whether or not the model is the main model for the study. Finally, results indicated that power is significantly related to model fit statistics used in evaluating SEMs. The results from this quantitative review imply that researchers should be more vigilant with respect to power in structural equation modeling. We therefore conclude by offering methodological best practices to increase confidence in the interpretation of structural equation modeling results with respect to statistical power issues.
Thermal Properties of West Siberian Sediments in Application to Basin and Petroleum Systems Modeling
Romushkevich, Raisa; Popov, Evgeny; Popov, Yury; Chekhonin, Evgeny; Myasnikov, Artem; Kazak, Andrey; Belenkaya, Irina; Zagranovskaya, Dzhuliya
2016-04-01
Quality of heat flow and rock thermal property data is the crucial question in basin and petroleum system modeling. A number of significant deviations in thermal conductivity values were observed during our integral geothermal study of West Siberian platform reporting that the corrections should be carried out in basin models. The experimental data including thermal anisotropy and heterogeneity measurements were obtained along of more than 15 000 core samples and about 4 500 core plugs. The measurements were performed in 1993-2015 with the optical scanning technique within the Continental Super-Deep Drilling Program (Russia) for scientific super-deep well Tyumenskaya SG-6, parametric super-deep well Yen-Yakhinskaya, and deep well Yarudeyskaya-38 as well as for 13 oil and gas fields in the West Siberia. Variations of the thermal conductivity tensor components in parallel and perpendicular direction to the layer stratification (assessed for 2D anisotropy model of the rock studied), volumetric heat capacity and thermal anisotropy coefficient values and average values of the thermal properties were the subject of statistical analysis for the uppermost deposits aged by: T3-J2 (200-165 Ma); J2-J3 (165-150 Ma); J3 (150-145 Ma); K1 (145-136 Ma); K1 (136-125 Ma); K1-K2 (125-94 Ma); K2-Pg+Ng+Q (94-0 Ma). Uncertainties caused by deviations of thermal conductivity data from its average values were found to be as high as 45 % leading to unexpected errors in the basin heat flow determinations. Also, the essential spatial-temporal variations in the thermal rock properties in the study area is proposed to be taken into account in thermo-hydrodynamic modeling of hydrocarbon recovery with thermal methods. The research work was done with financial support of the Russian Ministry of Education and Science (unique identification number RFMEFI58114X0008).
Coupling of the Models of Human Physiology and Thermal Comfort
Pokorny, J.; Jicha, M.
2013-04-01
A coupled model of human physiology and thermal comfort was developed in Dymola/Modelica. A coupling combines a modified Tanabe model of human physiology and thermal comfort model developed by Zhang. The Coupled model allows predicting the thermal sensation and comfort of both local and overall from local boundary conditions representing ambient and personal factors. The aim of this study was to compare prediction of the Coupled model with the Fiala model prediction and experimental data. Validation data were taken from the literature, mainly from the validation manual of software Theseus-FE [1]. In the paper validation of the model for very light physical activities (1 met) indoor environment with temperatures from 12 °C up to 48 °C is presented. The Coupled model predicts mean skin temperature for cold, neutral and warm environment well. However prediction of core temperature in cold environment is inaccurate and very affected by ambient temperature. Evaluation of thermal comfort in warm environment is supplemented by skin wettedness prediction. The Coupled model is designed for non-uniform and transient environmental conditions; it is also suitable simulation of thermal comfort in vehicles cabins. The usage of the model is limited for very light physical activities up to 1.2 met only.
Coupling of the Models of Human Physiology and Thermal Comfort
Directory of Open Access Journals (Sweden)
Jicha M.
2013-04-01
Full Text Available A coupled model of human physiology and thermal comfort was developed in Dymola/Modelica. A coupling combines a modified Tanabe model of human physiology and thermal comfort model developed by Zhang. The Coupled model allows predicting the thermal sensation and comfort of both local and overall from local boundary conditions representing ambient and personal factors. The aim of this study was to compare prediction of the Coupled model with the Fiala model prediction and experimental data. Validation data were taken from the literature, mainly from the validation manual of software Theseus–FE [1]. In the paper validation of the model for very light physical activities (1 met indoor environment with temperatures from 12 °C up to 48 °C is presented. The Coupled model predicts mean skin temperature for cold, neutral and warm environment well. However prediction of core temperature in cold environment is inaccurate and very affected by ambient temperature. Evaluation of thermal comfort in warm environment is supplemented by skin wettedness prediction. The Coupled model is designed for non-uniform and transient environmental conditions; it is also suitable simulation of thermal comfort in vehicles cabins. The usage of the model is limited for very light physical activities up to 1.2 met only.
Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance
Wang, Xiao-Yen J.; Fabanich, William Anthony; Schmitz, Paul C.
2014-01-01
This paper presents recent thermal model results of the Advanced Stirling Radioisotope Generator (ASRG). The three-dimensional (3D) ASRG thermal power model was built using the Thermal Desktop(trademark) thermal analyzer. The model was correlated with ASRG engineering unit test data and ASRG flight unit predictions from Lockheed Martin's (LM's) I-deas(trademark) TMG thermal model. The auxiliary cooling system (ACS) of the ASRG is also included in the ASRG thermal model. The ACS is designed to remove waste heat from the ASRG so that it can be used to heat spacecraft components. The performance of the ACS is reported under nominal conditions and during a Venus flyby scenario. The results for the nominal case are validated with data from Lockheed Martin. Transient thermal analysis results of ASRG for a Venus flyby with a representative trajectory are also presented. In addition, model results of an ASRG mounted on a Cassini-like spacecraft with a sunshade are presented to show a way to mitigate the high temperatures of a Venus flyby. It was predicted that the sunshade can lower the temperature of the ASRG alternator by 20 C for the representative Venus flyby trajectory. The 3D model also was modified to predict generator performance after a single Advanced Stirling Convertor failure. The geometry of the Microtherm HT insulation block on the outboard side was modified to match deformation and shrinkage observed during testing of a prototypic ASRG test fixture by LM. Test conditions and test data were used to correlate the model by adjusting the thermal conductivity of the deformed insulation to match the post-heat-dump steady state temperatures. Results for these conditions showed that the performance of the still-functioning inboard ACS was unaffected.
The Lattice and Thermal Radiation Conductivity of Thermal Barrier Coatings: Models and Experiments
Zhu, Dongming; Spuckler, Charles M.
2010-01-01
The lattice and radiation conductivity of ZrO2-Y2O3 thermal barrier coatings was evaluated using a laser heat flux approach. A diffusion model has been established to correlate the coating apparent thermal conductivity to the lattice and radiation conductivity. The radiation conductivity component can be expressed as a function of temperature, coating material scattering, and absorption properties. High temperature scattering and absorption of the coating systems can be also derived based on the testing results using the modeling approach. A comparison has been made for the gray and nongray coating models in the plasma-sprayed thermal barrier coatings. The model prediction is found to have a good agreement with experimental observations.
Measurement and model on thermal properties of sintered diamond composites
International Nuclear Information System (INIS)
Moussa, Tala; Garnier, Bertrand; Peerhossaini, Hassan
2013-01-01
Highlights: ► Thermal properties of sintered diamond used for grinding is studied. ► Flash method with infrared temperature measurement is used to investigate. ► Thermal conductivity increases with the amount of diamond. ► It is very sensitive to binder conductivity. ► Results agree with models assuming imperfect contact between matrix and particles. - Abstract: A prelude to the thermal management of grinding processes is measurement of the thermal properties of working materials. Indeed, tool materials must be chosen not only for their mechanical properties (abrasion performance, lifetime…) but also for thermal concerns (thermal conductivity) for efficient cooling that avoids excessive temperatures in the tool and workpiece. Sintered diamond is currently used for grinding tools since it yields higher performances and longer lifetimes than conventional materials (mineral or silicon carbide abrasives), but its thermal properties are not yet well known. Here the thermal conductivity, heat capacity and density of sintered diamond are measured as functions of the diamond content in composites and for two types of metallic binders: hard tungsten-based and soft cobalt-based binders. The measurement technique for thermal conductivity is derived from the flash method. After pulse heating, the temperature of the rear of the sample is measured with a noncontact method (infrared camera). A parameter estimation method associated with a three-layer nonstationary thermal model is used to obtain sample thermal conductivity, heat transfer coefficient and absorbed energy. With the hard metallic binder, the thermal conductivity of sintered diamond increased by up to 64% for a diamond content increasing from 0 to 25%. The increase is much less for the soft binder: 35% for diamond volumes up to 25%. In addition, experimental data were found that were far below the value predicted by conventional analytical models for effective thermal conductivity. A possible explanation
Modeling thermal effects in braking systems of railway vehicles
Directory of Open Access Journals (Sweden)
Milošević Miloš S.
2012-01-01
Full Text Available The modeling of thermal effects has become increasingly important in product design in different transport means, road vehicles, airplanes, railway vehicles, and so forth. The thermal analysis is a very important stage in the study of braking systems, especially of railway vehicles, where it is necessary to brake huge masses, because the thermal load of a braked railway wheel prevails compared to other types of loads. In the braking phase, kinetic energy transforms into thermal energy resulting in intense heating and high temperature states of railway wheels. Thus induced thermal loads determine thermomechanical behavior of the structure of railway wheels. In cases of thermal overloads, which mainly occur as a result of long-term braking on down-grade railroads, the generation of stresses and deformations occurs, whose consequences are the appearance of cracks on the rim of a wheel and the final total wheel defect. The importance to precisely determine the temperature distribution caused by the transfer process of the heat generated during braking due to the friction on contact surfaces of the braking system makes it a challenging research task. Therefore, the thermal analysis of a block-braked solid railway wheel of a 444 class locomotive of the national railway operator Serbian Railways is processed in detail in this paper, using analytical and numerical modeling of thermal effects during long-term braking for maintaining a constant speed on a down-grade railroad.
Development of a statistical oil spill model for risk assessment.
Guo, Weijun
2017-11-01
To gain a better understanding of the impacts from potential risk sources, we developed an oil spill model using probabilistic method, which simulates numerous oil spill trajectories under varying environmental conditions. The statistical results were quantified from hypothetical oil spills under multiple scenarios, including area affected probability, mean oil slick thickness, and duration of water surface exposed to floating oil. The three sub-indices together with marine area vulnerability are merged to compute the composite index, characterizing the spatial distribution of risk degree. Integral of the index can be used to identify the overall risk from an emission source. The developed model has been successfully applied in comparison to and selection of an appropriate oil port construction location adjacent to a marine protected area for Phoca largha in China. The results highlight the importance of selection of candidates before project construction, since that risk estimation from two adjacent potential sources may turn out to be significantly different regarding hydrodynamic conditions and eco-environmental sensitivity. Copyright © 2017. Published by Elsevier Ltd.
Automated robust generation of compact 3D statistical shape models
Vrtovec, Tomaz; Likar, Bostjan; Tomazevic, Dejan; Pernus, Franjo
2004-05-01
Ascertaining the detailed shape and spatial arrangement of anatomical structures is important not only within diagnostic settings but also in the areas of planning, simulation, intraoperative navigation, and tracking of pathology. Robust, accurate and efficient automated segmentation of anatomical structures is difficult because of their complexity and inter-patient variability. Furthermore, the position of the patient during image acquisition, the imaging device and protocol, image resolution, and other factors induce additional variations in shape and appearance. Statistical shape models (SSMs) have proven quite successful in capturing structural variability. A possible approach to obtain a 3D SSM is to extract reference voxels by precisely segmenting the structure in one, reference image. The corresponding voxels in other images are determined by registering the reference image to each other image. The SSM obtained in this way describes statistically plausible shape variations over the given population as well as variations due to imperfect registration. In this paper, we present a completely automated method that significantly reduces shape variations induced by imperfect registration, thus allowing a more accurate description of variations. At each iteration, the derived SSM is used for coarse registration, which is further improved by describing finer variations of the structure. The method was tested on 64 lumbar spinal column CT scans, from which 23, 38, 45, 46 and 42 volumes of interest containing vertebra L1, L2, L3, L4 and L5, respectively, were extracted. Separate SSMs were generated for each vertebra. The results show that the method is capable of reducing the variations induced by registration errors.