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Sensitivity And Uncertainty Analysis Volume Ii


Sensitivity And Uncertainty Analysis Volume Ii
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Sensitivity And Uncertainty Analysis Volume Ii


Sensitivity And Uncertainty Analysis Volume Ii
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Author : Dan G. Cacuci
language : en
Publisher: CRC Press
Release Date : 2005-05-16

Sensitivity And Uncertainty Analysis Volume Ii written by Dan G. Cacuci and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-05-16 with Mathematics categories.


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.



Sensitivity Uncertainty Analysis


Sensitivity Uncertainty Analysis
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Author : Dan G. Cacuci
language : en
Publisher: Chapman and Hall/CRC
Release Date : 2003-05-28

Sensitivity Uncertainty Analysis written by Dan G. Cacuci and has been published by Chapman and Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-05-28 with Mathematics categories.


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 on adjoint operators, which is applicable to a much wider variety of problems than methods traditionally used in control theory. This book fills that gap, focusing on the mathematical underpinnings of the Adjoint Sensitivity Analysis Procedure (ASAP) and the use of deterministically obtained sensitivities for subsequent uncertainty analysis.



Sensitivity Uncertainty Analysis Volume 1


Sensitivity Uncertainty Analysis Volume 1
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Author : Dan G. Cacuci
language : en
Publisher: CRC Press
Release Date : 2003-05-28

Sensitivity Uncertainty Analysis Volume 1 written by Dan G. Cacuci and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-05-28 with Mathematics categories.


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



The Second Order Adjoint Sensitivity Analysis Methodology


The Second Order Adjoint Sensitivity Analysis Methodology
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Author : Dan Gabriel Cacuci
language : en
Publisher: CRC Press
Release Date : 2018-02-19

The Second Order Adjoint Sensitivity Analysis Methodology written by Dan Gabriel Cacuci and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-19 with Mathematics categories.


The Second-Order Adjoint Sensitivity Analysis Methodology generalizes the First-Order Theory presented in the author’s previous books published by CRC Press. This breakthrough has many applications in sensitivity and uncertainty analysis, optimization, data assimilation, model calibration, and reducing uncertainties in model predictions. The book has many illustrative examples that will help readers understand the complexity of the subject and will enable them to apply this methodology to problems in their own fields. Highlights: • Covers a wide range of needs, from graduate students to advanced researchers • Provides a text positioned to be the primary reference for high-order sensitivity and uncertainty analysis • Applies to all fields involving numerical modeling, optimization, quantification of sensitivities in direct and inverse problems in the presence of uncertainties. About the Author: Dan Gabriel Cacuci is a South Carolina SmartState Endowed Chair Professor and the Director of the Center for Nuclear Science and Energy, Department of Mechanical Engineering at the University of South Carolina. He has a Ph.D. in Applied Physics, Mechanical and Nuclear Engineering from Columbia University. He is also the recipient of many awards including four honorary doctorates, the Ernest Orlando Lawrence Memorial award from the U.S. Dept. of Energy and the Arthur Holly Compton, Eugene P. Wigner and the Glenn Seaborg Awards from the American Nuclear Society.



Nuclear Systems Volume Ii


Nuclear Systems Volume Ii
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Author : Neil E. Todreas
language : en
Publisher: CRC Press
Release Date : 2021-12-13

Nuclear Systems Volume Ii written by Neil E. Todreas and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-13 with Science categories.


This book provides advanced coverage of a wide variety of thermal fluid systems and technologies in nuclear power plants, including discussions of the latest reactor designs and their thermal/fluid technologies. Beyond the thermal hydraulic design and analysis of the core of a nuclear reactor, the book covers other components of nuclear power plants, such as the pressurizer, containment, and the entire primary coolant system. Placing more emphasis on the appropriate models for small-scale resolution of the velocity and temperature fields through computational fluid mechanics, the book shows how this enhances the accuracy of predicted operating conditions in nuclear plants. It introduces considerations of the laws of scaling and uncertainty analysis, along with a wider coverage of the phenomena encountered during accidents. FEATURES Discusses fundamental ideas for various modeling approaches for the macro- and microscale flow conditions in reactors Covers specific design considerations, such as natural convection and core reliability Enables readers to better understand the importance of safety considerations in thermal engineering and analysis of modern nuclear plants Features end-of-chapter problems Includes a solutions manual for adopting instructors This book serves as a textbook for advanced undergraduate and graduate students taking courses in nuclear engineering and studying thermal/hydraulic systems in nuclear power plants.



Sensitivity Analysis In Earth Observation Modelling


Sensitivity Analysis In Earth Observation Modelling
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Author : George P. Petropoulos
language : en
Publisher: Elsevier
Release Date : 2016-10-07

Sensitivity Analysis In Earth Observation Modelling written by George P. Petropoulos and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-07 with Science categories.


Sensitivity Analysis in Earth Observation Modeling highlights the state-of-the-art in ongoing research investigations and new applications of sensitivity analysis in earth observation modeling. In this framework, original works concerned with the development or exploitation of diverse methods applied to different types of earth observation data or earth observation-based modeling approaches are included. An overview of sensitivity analysis methods and principles is provided first, followed by examples of applications and case studies of different sensitivity/uncertainty analysis implementation methods, covering the full spectrum of sensitivity analysis techniques, including operational products. Finally, the book outlines challenges and future prospects for implementation in earth observation modeling. Information provided in this book is of practical value to readers looking to understand the principles of sensitivity analysis in earth observation modeling, the level of scientific maturity in the field, and where the main limitations or challenges are in terms of improving our ability to implement such approaches in a wide range of applications. Readers will also be informed on the implementation of sensitivity/uncertainty analysis on operational products available at present, on global and continental scales. All of this information is vital in the selection process of the most appropriate sensitivity analysis method to implement. - Outlines challenges and future prospects of sensitivity analysis implementation in earth observation modeling - Provides readers with a roadmap for directing future efforts - Includes case studies with applications from different regions around the globe, helping readers to explore strengths and weaknesses of the different methods in earth observation modeling - Presents a step-by-step guide, providing the principles of each method followed by the application of variants, making the reference easy to use and follow



Sensitivity Analysis


Sensitivity Analysis
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Author : Emanuele Borgonovo
language : en
Publisher: Springer
Release Date : 2017-04-19

Sensitivity Analysis written by Emanuele Borgonovo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-19 with Business & Economics categories.


This book is an expository introduction to the methodology of sensitivity analysis of model output. It is primarily intended for investigators, students and researchers that are familiar with mathematical models but are less familiar with the techniques for performing their sensitivity analysis. A variety of sensitivity methods have been developed over the years. This monograph helps the analyst in her/his first exploration of this world. The main goal is to foster the recognition of the crucial role of sensitivity analysis methods as the techniques that allow us to gain insights from quantitative models. Also, exercising rigor in performing sensitivity analysis becomes increasingly relevant both to decision makers and modelers. The book helps the analyst in structuring her/his sensitivity analysis quest properly, so as to obtain the correct answer to the corresponding managerial question. The first part of the book covers Deterministic Methods, including Tornado Diagrams; One-Way Sensitivity Analysis; Differentiation-Based Methods and Local Sensitivity Analysis with Constraints. The second part looks at Probabilistic Methods, including Regression-Based methods, Variance-Based Methods, and Distribution-Based methods. The final section looks at Applications, including capital budgeting, sensitivity analysis in climate change modelling and in the risk assessment of a lunar space mission.



Aerospace System Analysis And Optimization In Uncertainty


Aerospace System Analysis And Optimization In Uncertainty
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Author : Loïc Brevault
language : en
Publisher: Springer Nature
Release Date : 2020-08-26

Aerospace System Analysis And Optimization In Uncertainty written by Loïc Brevault and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-26 with Mathematics categories.


Spotlighting the field of Multidisciplinary Design Optimization (MDO), this book illustrates and implements state-of-the-art methodologies within the complex process of aerospace system design under uncertainties. The book provides approaches to integrating a multitude of components and constraints with the ultimate goal of reducing design cycles. Insights on a vast assortment of problems are provided, including discipline modeling, sensitivity analysis, uncertainty propagation, reliability analysis, and global multidisciplinary optimization. The extensive range of topics covered include areas of current open research. This Work is destined to become a fundamental reference for aerospace systems engineers, researchers, as well as for practitioners and engineers working in areas of optimization and uncertainty. Part I is largely comprised of fundamentals. Part II presents methodologies for single discipline problems with a review of existing uncertainty propagation, reliability analysis, and optimization techniques. Part III is dedicated to the uncertainty-based MDO and related issues. Part IV deals with three MDO related issues: the multifidelity, the multi-objective optimization and the mixed continuous/discrete optimization and Part V is devoted to test cases for aerospace vehicle design.



Design Sensitivity Analysis Of Structural Systems


Design Sensitivity Analysis Of Structural Systems
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Author : Vadim Komkov
language : en
Publisher: Academic Press
Release Date : 1986-05-01

Design Sensitivity Analysis Of Structural Systems written by Vadim Komkov and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986-05-01 with Technology & Engineering categories.


The book is organized into four chapters. The first three treat distinct types of design variables, and the fourth presents a built-up structure formulation that combines the other three. The first chapter treats finite-dimensional problems, in which the state variable is a finite-dimensional vector of structure displacements and the design parameters. The structual state equations are matrix equations for static response, vibration, and buckling of structures and matrix differential equations for transient dynamic response of structures, which design variables appearing in the coefficient matrices.



Uncertainty Quantification And Predictive Computational Science


Uncertainty Quantification And Predictive Computational Science
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Author : Ryan G. McClarren
language : en
Publisher: Springer
Release Date : 2018-11-23

Uncertainty Quantification And Predictive Computational Science written by Ryan G. McClarren and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-23 with Science categories.


This textbook teaches the essential background and skills for understanding and quantifying uncertainties in a computational simulation, and for predicting the behavior of a system under those uncertainties. It addresses a critical knowledge gap in the widespread adoption of simulation in high-consequence decision-making throughout the engineering and physical sciences. Constructing sophisticated techniques for prediction from basic building blocks, the book first reviews the fundamentals that underpin later topics of the book including probability, sampling, and Bayesian statistics. Part II focuses on applying Local Sensitivity Analysis to apportion uncertainty in the model outputs to sources of uncertainty in its inputs. Part III demonstrates techniques for quantifying the impact of parametric uncertainties on a problem, specifically how input uncertainties affect outputs. The final section covers techniques for applying uncertainty quantification to make predictions under uncertainty, including treatment of epistemic uncertainties. It presents the theory and practice of predicting the behavior of a system based on the aggregation of data from simulation, theory, and experiment. The text focuses on simulations based on the solution of systems of partial differential equations and includes in-depth coverage of Monte Carlo methods, basic design of computer experiments, as well as regularized statistical techniques. Code references, in python, appear throughout the text and online as executable code, enabling readers to perform the analysis under discussion. Worked examples from realistic, model problems help readers understand the mechanics of applying the methods. Each chapter ends with several assignable problems. Uncertainty Quantification and Predictive Computational Science fills the growing need for a classroom text for senior undergraduate and early-career graduate students in the engineering and physical sciences and supports independent study by researchers and professionals who must include uncertainty quantification and predictive science in the simulations they develop and/or perform.