Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
A Sensitivity Analysis Method For Determining Simulation Model Output Degradation In Response To Physical System Alteration
Download A Sensitivity Analysis Method For Determining Simulation Model Output Degradation In Response To Physical System Alteration full books in PDF, epub, and Kindle. Read online A Sensitivity Analysis Method For Determining Simulation Model Output Degradation In Response To Physical System Alteration ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis A Sensitivity Analysis Method for Determining Simulation Model Output Degradation in Response to Physical System Alteration by : Lissa Galbraith
Download or read book A Sensitivity Analysis Method for Determining Simulation Model Output Degradation in Response to Physical System Alteration written by Lissa Galbraith and published by . This book was released on 1984 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis 2021 International Conference on Big Data Analytics for Cyber-Physical System in Smart City by : Mohammed Atiquzzaman
Download or read book 2021 International Conference on Big Data Analytics for Cyber-Physical System in Smart City written by Mohammed Atiquzzaman and published by Springer Nature. This book was released on 2022-01-01 with total page 1157 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers a selection of peer-reviewed papers presented at the third Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2021) conference, held in Shanghai, China, on Nov. 27, 2021. The contributions, prepared by an international team of scientists and engineers, cover the latest advances made in the field of machine learning, and big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.
Book Synopsis The nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology, Volume I by : Dan Gabriel Cacuci
Download or read book The nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology, Volume I written by Dan Gabriel Cacuci and published by Springer Nature. This book was released on 2022-07-19 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: The computational models of physical systems comprise parameters, independent and dependent variables. Since the physical processes themselves are seldom known precisely and since most of the model parameters stem from experimental procedures which are also subject to imprecisions, the results predicted by these models are also imprecise, being affected by the uncertainties underlying the respective model. The functional derivatives (also called “sensitivities”) of results (also called “responses”) produced by mathematical/computational models are needed for many purposes, including: (i) understanding the model by ranking the importance of the various model parameters; (ii) performing “reduced-order modeling” by eliminating unimportant parameters and/or processes; (iii) quantifying the uncertainties induced in a model response due to model parameter uncertainties; (iv) performing “model validation,” by comparing computations to experiments to address the question “does the model represent reality?” (v) prioritizing improvements in the model; (vi) performing data assimilation and model calibration as part of forward “predictive modeling” to obtain best-estimate predicted results with reduced predicted uncertainties; (vii) performing inverse “predictive modeling”; (viii) designing and optimizing the system. This 3-Volume monograph describes a comprehensive adjoint sensitivity analysis methodology, developed by the author, which enables the efficient and exact computation of arbitrarily high-order sensitivities of model responses in large-scale systems comprising many model parameters. The qualifier “comprehensive” is employed to highlight that the model parameters considered within the framework of this methodology also include the system’s uncertain boundaries and internal interfaces in phase-space. The model’s responses can be either scalar-valued functionals of the model’s parameters and state variables (e.g., as customarily encountered in optimization problems) or general function-valued responses. Since linear operators admit bona-fide adjoint operators, responses of models that are linear in the state functions (i.e., dependent variables) can depend simultaneously on both the forward and the adjoint state functions. Hence, the sensitivity analysis of such responses warrants the treatment of linear systems in their own right, rather than treating them as particular cases of nonlinear systems. This is in contradistinction to responses for nonlinear systems, which can depend only on the forward state functions, since nonlinear operators do not admit bona-fide adjoint operators (only a linearized form of a nonlinear operator may admit an adjoint operator). Thus, Volume 1 of this book presents the mathematical framework of the nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Systems (abbreviated as “nth-CASAM-L”), which is conceived for the most efficient computation of exactly obtained mathematical expressions of arbitrarily-high-order (nth-order) sensitivities of a generic system response with respect to all of the parameters underlying the respective forward/adjoint systems. Volume 2 of this book presents the application of the nth-CASAM-L to perform a fourth-order sensitivity and uncertainty analysis of an OECD/NEA reactor physics benchmark which is representative of a large-scale model comprises many (21,976) uncertain parameters, thereby amply illustrating the unique potential of the nth-CASAM-L to enable the exact and efficient computation of chosen high-order response sensitivities to model parameters. Volume 3 of this book presents the “nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems” (abbreviation: nth-CASAM-N) for the practical, efficient, and exact computation of arbitrarily-high order sensitivities of responses to model parameters for systems that are also nonlinear in their underlying state functions. Such computations are not feasible with any other methodology. The application of the nth-CASAM-L and the nth-CASAM-N overcomes the so-called “curse of dimensionality” in sensitivity and uncertainty analysis, thus revolutionizing all of the fields of activities which require accurate computation of response sensitivities. Since this monograph includes many illustrative, fully worked-out, paradigm problems, it can serve as a textbook or as supplementary reading for graduate courses in academic departments in the natural sciences and engineering.
Book Synopsis Sensitivity and Uncertainty Analysis, Volume II by : Dan G. Cacuci
Download or read book Sensitivity and Uncertainty Analysis, Volume II written by Dan G. Cacuci and published by CRC Press. This book was released on 2005-05-16 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: As computer-assisted modeling and analysis of physical processes have continued to grow and diversify, sensitivity and uncertainty analyses have become indispensable scientific tools. Sensitivity and Uncertainty Analysis. Volume I: Theory focused on the mathematical underpinnings of two important methods for such analyses: the Adjoint Sensitivity Analysis Procedure and the Global Adjoint Sensitivity Analysis Procedure. This volume concentrates on the practical aspects of performing these analyses for large-scale systems. The applications addressed include two-phase flow problems, a radiative convective model for climate simulations, and large-scale models for numerical weather prediction.
Book Synopsis Bulletin of the Atomic Scientists by :
Download or read book Bulletin of the Atomic Scientists written by and published by . This book was released on 1961-05 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Bulletin of the Atomic Scientists is the premier public resource on scientific and technological developments that impact global security. Founded by Manhattan Project Scientists, the Bulletin's iconic "Doomsday Clock" stimulates solutions for a safer world.
Book Synopsis Sensitivity & Uncertainty Analysis, Volume 1 by : Dan G. Cacuci
Download or read book Sensitivity & Uncertainty Analysis, Volume 1 written by Dan G. Cacuci and published by CRC Press. This book was released on 2003-05-28 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: As computer-assisted modeling and analysis of physical processes have continued to grow and diversify, sensitivity and uncertainty analyses have become indispensable investigative scientific tools in their own right. While most techniques used for these analyses are well documented, there has yet to appear a systematic treatment of the method based
Book Synopsis Sensitivity Analysis in Practice by : Andrea Saltelli
Download or read book Sensitivity Analysis in Practice written by Andrea Saltelli and published by John Wiley & Sons. This book was released on 2004-07-16 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sensitivity analysis should be considered a pre-requisite for statistical model building in any scientific discipline where modelling takes place. For a non-expert, choosing the method of analysis for their model is complex, and depends on a number of factors. This book guides the non-expert through their problem in order to enable them to choose and apply the most appropriate method. It offers a review of the state-of-the-art in sensitivity analysis, and is suitable for a wide range of practitioners. It is focussed on the use of SIMLAB – a widely distributed freely-available sensitivity analysis software package developed by the authors – for solving problems in sensitivity analysis of statistical models. Other key features: Provides an accessible overview of the current most widely used methods for sensitivity analysis. Opens with a detailed worked example to explain the motivation behind the book. Includes a range of examples to help illustrate the concepts discussed. Focuses on implementation of the methods in the software SIMLAB - a freely-available sensitivity analysis software package developed by the authors. Contains a large number of references to sources for further reading. Authored by the leading authorities on sensitivity analysis.
Book Synopsis Design Sensitivity Analysis by : Lisa G. Stanley
Download or read book Design Sensitivity Analysis written by Lisa G. Stanley and published by SIAM. This book was released on 2002-01-01 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an understandable introduction to one approach to design sensitivity computation and illustrates some of the important mathematical and computational issues inherent in using the sensitivity equation method (SEM) for partial differential equations. The authors use basic models to illustrate the computational issues that one might encounter when applying the SEM in a laboratory or research setting, while providing an overview of applications and computational issues regarding sensitivity calculations performed by way of continuous sensitivity equation methods (CSEM).
Book Synopsis Sensitivity Analysis in Linear Systems by : Assem Deif
Download or read book Sensitivity Analysis in Linear Systems written by Assem Deif and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: A text surveying perturbation techniques and sensitivity analysis of linear systems is an ambitious undertaking, considering the lack of basic comprehensive texts on the subject. A wide-ranging and global coverage of the topic is as yet missing, despite the existence of numerous monographs dealing with specific topics but generally of use to only a narrow category of people. In fact, most works approach this subject from the numerical analysis point of view. Indeed, researchers in this field have been most concerned with this topic, although engineers and scholars in all fields may find it equally interesting. One can state, without great exaggeration, that a great deal of engineering work is devoted to testing systems' sensitivity to changes in design parameters. As a rule, high-sensitivity elements are those which should be designed with utmost care. On the other hand, as the mathematical modelling serving for the design process is usually idealized and often inaccurately formulated, some unforeseen alterations may cause the system to behave in a slightly different manner. Sensitivity analysis can help the engineer innovate ways to minimize such system discrepancy, since it starts from the assumption of such a discrepancy between the ideal and the actual system.
Book Synopsis The Nth-order Comprehensive Adjoint Sensitivity Analysis Methodology by : Dan Gabriel Cacuci
Download or read book The Nth-order Comprehensive Adjoint Sensitivity Analysis Methodology written by Dan Gabriel Cacuci and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The computational models of physical systems comprise parameters, independent and dependent variables. Since the physical processes themselves are seldom known precisely and since most of the model parameters stem from experimental procedures which are also subject to imprecisions, the results predicted by these models are also imprecise, being affected by the uncertainties underlying the respective model. The functional derivatives (also called "sensitivities") of results (also called "responses") produced by mathematical/computational models are needed for many purposes, including: (i) understanding the model by ranking the importance of the various model parameters; (ii) performing "reduced-order modeling" by eliminating unimportant parameters and/or processes; (iii) quantifying the uncertainties induced in a model response due to model parameter uncertainties; (iv) performing "model validation," by comparing computations to experiments to address the question "does the model represent reality?" prioritizing improvements in the model; (vi) performing data assimilation and model calibration as part of forward "predictive modeling" to obtain best-estimate predicted results with reduced predicted uncertainties; (vii) performing inverse "predictive modeling" designing and optimizing the system. This 3-Volume monograph describes a comprehensive adjoint sensitivity analysis methodology, developed by the author, which enables the efficient and exact computation of arbitrarily high-order sensitivities of model responses in large-scale systems comprising many model parameters. The qualifier "comprehensive" is employed to highlight that the model parameters considered within the framework of this methodology also include the systems uncertain boundaries and internal interfaces in phase-space. The models responses can be either scalar-valued functionals of the models parameters and state variables (e.g., as customarily encountered in optimization problems) or general function-valued responses. Since linear operators admit bona-fide adjoint operators, responses of models that are linear in the state functions (i.e., dependent variables) can depend simultaneously on both the forward and the adjoint state functions. Hence, the sensitivity analysis of such responses warrants the treatment of linear systems in their own right, rather than treating them as particular cases of nonlinear systems. This is in contradistinction to responses for nonlinear systems, which can depend only on the forward state functions, since nonlinear operators do not admit bona-fide adjoint operators (only a linearized form of a nonlinear operator may admit an adjoint operator). Thus, Volume 1 of this book presents the mathematical framework of the nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Systems (abbreviated as "nth-CASAM-L"), which is conceived for the most efficient computation of exactly obtained mathematical expressions of arbitrarily-high-order (nth-order) sensitivities of a generic system response with respect to all of the parameters underlying the respective forward/adjoint systems. Volume 2 of this book presents the application of the nth-CASAM-L to perform a fourth-order sensitivity and uncertainty analysis of an OECD/NEA reactor physics benchmark which is representative of a large-scale model comprises many (21,976) uncertain parameters, thereby amply illustrating the unique potential of the nth-CASAM-L to enable the exact and efficient computation of chosen high-order response sensitivities to model parameters. Volume 3 of this book presents the "nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems" (abbreviation: nth-CASAM-N) for the practical, efficient, and exact computation of arbitrarily-high order sensitivities of responses to model parameters for systems that are also nonlinear in their underlying state functions. Such computations are not feasible with any other methodology. The application of the nth-CASAM-L and the nth-CASAM-N overcomes the so-called "curse of dimensionality" in sensitivity and uncertainty analysis, thus revolutionizing all of the fields of activities which require accurate computation of response sensitivities. Since this monograph includes many illustrative, fully worked-out, paradigm problems, it can serve as a textbook or as supplementary reading for graduate courses in academic departments in the natural sciences and engineering.
Book Synopsis Global Sensitivity Analysis by : Andrea Saltelli
Download or read book Global Sensitivity Analysis written by Andrea Saltelli and published by John Wiley & Sons. This book was released on 2008-02-28 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex mathematical and computational models are used in all areas of society and technology and yet model based science is increasingly contested or refuted, especially when models are applied to controversial themes in domains such as health, the environment or the economy. More stringent standards of proofs are demanded from model-based numbers, especially when these numbers represent potential financial losses, threats to human health or the state of the environment. Quantitative sensitivity analysis is generally agreed to be one such standard. Mathematical models are good at mapping assumptions into inferences. A modeller makes assumptions about laws pertaining to the system, about its status and a plethora of other, often arcane, system variables and internal model settings. To what extent can we rely on the model-based inference when most of these assumptions are fraught with uncertainties? Global Sensitivity Analysis offers an accessible treatment of such problems via quantitative sensitivity analysis, beginning with the first principles and guiding the reader through the full range of recommended practices with a rich set of solved exercises. The text explains the motivation for sensitivity analysis, reviews the required statistical concepts, and provides a guide to potential applications. The book: Provides a self-contained treatment of the subject, allowing readers to learn and practice global sensitivity analysis without further materials. Presents ways to frame the analysis, interpret its results, and avoid potential pitfalls. Features numerous exercises and solved problems to help illustrate the applications. Is authored by leading sensitivity analysis practitioners, combining a range of disciplinary backgrounds. Postgraduate students and practitioners in a wide range of subjects, including statistics, mathematics, engineering, physics, chemistry, environmental sciences, biology, toxicology, actuarial sciences, and econometrics will find much of use here. This book will prove equally valuable to engineers working on risk analysis and to financial analysts concerned with pricing and hedging.
Book Synopsis The nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology, Volume II by : Dan Gabriel Cacuci
Download or read book The nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology, Volume II written by Dan Gabriel Cacuci and published by Springer Nature. This book was released on 2023-04-26 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text describes a comprehensive adjoint sensitivity analysis methodology (nth-CASAM), developed by the author, which enablesthe efficient and exact computation of arbitrarily high-order functional derivatives of model responses to model parameters in large-scale systems. The nth-CASAM framework is set in linearly increasing Hilbert spaces, each of state-function-dimensionality, as opposed to exponentially increasing parameter-dimensional spaces, thereby overcoming the so-called “curse of dimensionality” in sensitivity and uncertainty analysis. The nth-CASAM is applicable to any model; the larger the number of model parameters, the more efficient the nth-CASAM becomes for computing arbitrarily high-order response sensitivities. The book will be helpful to those working in the fields of sensitivity analysis, uncertainty quantification, model validation, optimization, data assimilation, model calibration, sensor fusion, reduced-order modelling, inverse problems and predictive modelling. This Volume Two, the second of three, presents the large-scale application of the nth-CASAM to perform a representative fourth-order sensitivity analysis of the Polyethylene-Reflected Plutonium benchmark described in the Nuclear Energy Agency (NEA) International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook. This benchmark is modeled mathematically by the Boltzmann particle transport equation, involving 21,976 imprecisely-known parameters, the numerical solution of which requires representative large-scale computations. The sensitivity analysis presented in this volume is the most comprehensive ever performed in the field of reactor physics and the results presented in this book prove, perhaps counter-intuitively, that many of the 4th-order sensitivities are much larger than the corresponding 3rd-order ones, which are, in turn, much larger than the 2nd-order ones, all of which are much larger than the 1st-order sensitivities. Currently, the nth-CASAM is the only known methodology which enables such large-scale computations of exactly obtained expressions of arbitrarily-high-order response sensitivities.
Book Synopsis Sensitivity Analysis by : Andrea Saltelli
Download or read book Sensitivity Analysis written by Andrea Saltelli and published by John Wiley & Sons. This book was released on 2000-10-03 with total page 515 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sensitivity analysis is used to ascertain how a given model output depends upon the input parameters. This is an important method for checking the quality of a given model, as well as a powerful tool for checking the robustness and reliability of its analysis. The topic is acknowledged as essential for good modelling practice, and is an implicit part of any modelling field. · Offers an accessible introduction to sensitivity analysis · Covers all the latest research · Illustrates concepts with numerous examples, applications and case studies · Includes contributions form the leading researchers active in developing strategies for sensitivity analysis The principles of sensitivity analysis area carefully described, and suitable methods for approaching many types of problems are given. The book introduces the modeller to the entire causal assessment chain, from data to predictions, whilst explaining the impact of source uncertainties and framing assumptions. A 'hitch-hiker's guide' is included to allow the more experienced reader to readily access specific applications. Modellers from a wide range of disciplines, including biostatistics, economics, environmental impact assessment, chemistry and engineering will benefit greatly form the numerous examples and applications.
Book Synopsis Sensitivity Analysis and Model Identification in Simulation Studies by : Vincent James Cogliano
Download or read book Sensitivity Analysis and Model Identification in Simulation Studies written by Vincent James Cogliano and published by . This book was released on 1982 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Scientific and Technical Aerospace Reports by :
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1983 with total page 1368 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Numerical Methods in Sensitivity Analysis and Shape Optimization by : Emmanuel Laporte
Download or read book Numerical Methods in Sensitivity Analysis and Shape Optimization written by Emmanuel Laporte and published by Birkhäuser. This book was released on 2012-01-19 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sensitivity analysis and optimal shape design are key issues in engineering that have been affected by advances in numerical tools currently available. This book, and its supplementary online files, presents basic optimization techniques that can be used to compute the sensitivity of a given design to local change, or to improve its performance by local optimization of these data. The relevance and scope of these techniques have improved dramatically in recent years because of progress in discretization strategies, optimization algorithms, automatic differentiation, software availability, and the power of personal computers. Numerical Methods in Sensitivity Analysis and Shape Optimization will be of interest to graduate students involved in mathematical modeling and simulation, as well as engineers and researchers in applied mathematics looking for an up-to-date introduction to optimization techniques, sensitivity analysis, and optimal design.
Book Synopsis The Application of Uncertainty Quantification (UQ) and Sensitivity Analysis (SA) Methodologies to Engineering Models and Mechanical Experiments by : Justin Matthew Hughes
Download or read book The Application of Uncertainty Quantification (UQ) and Sensitivity Analysis (SA) Methodologies to Engineering Models and Mechanical Experiments written by Justin Matthew Hughes and published by . This book was released on 2016 with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding the effects of uncertainty on modeling has seen an increased focus as engineering disciplines rely more heavily on computational modeling of complex physical processes to predict system performance and make informed engineering decisions. These computational methods often use simplified models and assumptions with models calibrated using uncertain, averaged experimental data. This commonplace method ignores the effects of uncertainty on the variation of modeling output. Qualitatively, uncertainty is the possibility of error existing from experiment to experiment, from model to model, or from experiment to model. Quantitatively, uncertainty quantification (UQ) methodologies seek to determine the how variable an engineering system is when subjected to variation in the factors that control it. Often performed in conjunction, sensitivity analysis (SA) methods seek to describe what model factor contributes the most to variation in model output. UQ and SA methodologies were employed in the analysis of the Modified Embedded Atom Method (MEAM) model for a pure aluminum, a microstructure sensitive fatigue crack growth model for polycarbonate, and the MultiStage Fatigue (MSF) model for AZ31 magnesium alloy. For the MEAM model, local uncertainty and sensitivity measures were investigated for the purpose of improving model calibrations. In polycarbonate fatigue crack growth, a Monte Carlo method is implemented in code and employed to investigate how variations in model input factors effect fatigue crack growth predictions. Lastly, in the analysis of fatigue life predictions with the MSF model for AZ31, the expected fatigue performance range due to variation in experimental parameters is investigated using both Monte Carlo Simple Random Sampling (MCSRS) methods and the estimation of first order effects indices using the Fourier Amplitude Sensitivity Test (FAST) method.
