Uncertainty Quantification

Uncertainty Quantification

Author: Ralph C. Smith

Publisher: SIAM

Published: 2013-12-02

Total Pages: 400

ISBN-13: 161197321X

DOWNLOAD EBOOK

The field of uncertainty quantification is evolving rapidly because of increasing emphasis on models that require quantified uncertainties for large-scale applications, novel algorithm development, and new computational architectures that facilitate implementation of these algorithms. Uncertainty Quantification: Theory, Implementation, and Applications provides readers with the basic concepts, theory, and algorithms necessary to quantify input and response uncertainties for simulation models arising in a broad range of disciplines. The book begins with a detailed discussion of applications where uncertainty quantification is critical for both scientific understanding and policy. It then covers concepts from probability and statistics, parameter selection techniques, frequentist and Bayesian model calibration, propagation of uncertainties, quantification of model discrepancy, surrogate model construction, and local and global sensitivity analysis. The author maintains a complementary web page where readers can find data used in the exercises and other supplementary material.


Uncertainty Quantification

Uncertainty Quantification

Author: Ralph C. Smith

Publisher: SIAM

Published: 2024-09-13

Total Pages: 571

ISBN-13: 1611977843

DOWNLOAD EBOOK

Uncertainty quantification serves a fundamental role when establishing the predictive capabilities of simulation models. This book provides a comprehensive and unified treatment of the mathematical, statistical, and computational theory and methods employed to quantify uncertainties associated with models from a wide range of applications. Expanded and reorganized, the second edition includes advances in the field and provides a comprehensive sensitivity analysis and uncertainty quantification framework for models from science and engineering. It contains new chapters on random field representations, observation models, parameter identifiability and influence, active subspace analysis, and statistical surrogate models, and a completely revised chapter on local sensitivity analysis. Other updates to the second edition are the inclusion of over 100 exercises and many new examples — several of which include data — and UQ Crimes listed throughout the text to identify common misconceptions and guide readers entering the field. Uncertainty Quantification: Theory, Implementation, and Applications, Second Edition is intended for advanced undergraduate and graduate students as well as researchers in mathematics, statistics, engineering, physical and biological sciences, operations research, and computer science. Readers are assumed to have a basic knowledge of probability, linear algebra, differential equations, and introductory numerical analysis. The book can be used as a primary text for a one-semester course on sensitivity analysis and uncertainty quantification or as a supplementary text for courses on surrogate and reduced-order model construction and parameter identifiability analysis.


Handbook of Uncertainty Quantification

Handbook of Uncertainty Quantification

Author: Roger Ghanem

Publisher: Springer

Published: 2016-05-08

Total Pages: 0

ISBN-13: 9783319123844

DOWNLOAD EBOOK

The topic of Uncertainty Quantification (UQ) has witnessed massive developments in response to the promise of achieving risk mitigation through scientific prediction. It has led to the integration of ideas from mathematics, statistics and engineering being used to lend credence to predictive assessments of risk but also to design actions (by engineers, scientists and investors) that are consistent with risk aversion. The objective of this Handbook is to facilitate the dissemination of the forefront of UQ ideas to their audiences. We recognize that these audiences are varied, with interests ranging from theory to application, and from research to development and even execution.


Model Validation and Uncertainty Quantification, Volume 3

Model Validation and Uncertainty Quantification, Volume 3

Author: H. Sezer Atamturktur

Publisher: Springer Science & Business Media

Published: 2014-04-11

Total Pages: 419

ISBN-13: 3319045520

DOWNLOAD EBOOK

This third volume of eight from the IMAC - XXXII Conference, brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Structural Dynamics, including papers on: Linear Systems Substructure Modelling Adaptive Structures Experimental Techniques Analytical Methods Damage Detection Damping of Materials & Members Modal Parameter Identification Modal Testing Methods System Identification Active Control Modal Parameter Estimation Processing Modal Data


Model Validation and Uncertainty Quantification, Volume 3

Model Validation and Uncertainty Quantification, Volume 3

Author: Robert Barthorpe

Publisher: Springer

Published: 2018-07-30

Total Pages: 303

ISBN-13: 3319747932

DOWNLOAD EBOOK

Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 36th IMAC, A Conference and Exposition on Structural Dynamics, 2018, the third volume of nine from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Model Validation and Uncertainty Quantification, including papers on: Uncertainty Quantification in Material Models Uncertainty Propagation in Structural Dynamics Practical Applications of MVUQ Advances in Model Validation & Uncertainty Quantification: Model Updating Model Validation & Uncertainty Quantification: Industrial Applications Controlling Uncertainty Uncertainty in Early Stage Design Modeling of Musical Instruments Overview of Model Validation and Uncertainty


Uncertainty Quantification in Multiscale Materials Modeling

Uncertainty Quantification in Multiscale Materials Modeling

Author: Yan Wang

Publisher: Woodhead Publishing

Published: 2020-03-12

Total Pages: 604

ISBN-13: 0081029411

DOWNLOAD EBOOK

Uncertainty Quantification in Multiscale Materials Modeling provides a complete overview of uncertainty quantification (UQ) in computational materials science. It provides practical tools and methods along with examples of their application to problems in materials modeling. UQ methods are applied to various multiscale models ranging from the nanoscale to macroscale. This book presents a thorough synthesis of the state-of-the-art in UQ methods for materials modeling, including Bayesian inference, surrogate modeling, random fields, interval analysis, and sensitivity analysis, providing insight into the unique characteristics of models framed at each scale, as well as common issues in modeling across scales.


Multifaceted Uncertainty Quantification

Multifaceted Uncertainty Quantification

Author: Isaac Elishakoff

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2024-09-23

Total Pages: 384

ISBN-13: 3111354237

DOWNLOAD EBOOK

The book exposes three alternative and competing approaches to uncertainty analysis in engineering. It is composed of some essays on various sub-topics like random vibrations, probabilistic reliability, fuzzy-sets-based analysis, unknown-but-bounded variables, stochastic linearization, possible difficulties with stochastic analysis of structures.


The Uncertainty Analysis of Model Results

The Uncertainty Analysis of Model Results

Author: Eduard Hofer

Publisher: Springer

Published: 2018-05-02

Total Pages: 355

ISBN-13: 3319762974

DOWNLOAD EBOOK

This book is a practical guide to the uncertainty analysis of computer model applications. Used in many areas, such as engineering, ecology and economics, computer models are subject to various uncertainties at the level of model formulations, parameter values and input data. Naturally, it would be advantageous to know the combined effect of these uncertainties on the model results as well as whether the state of knowledge should be improved in order to reduce the uncertainty of the results most effectively. The book supports decision-makers, model developers and users in their argumentation for an uncertainty analysis and assists them in the interpretation of the analysis results.


Nuclear Data Needs for Generation IV Nuclear Energy Systems

Nuclear Data Needs for Generation IV Nuclear Energy Systems

Author: P. Rullhusen

Publisher: World Scientific

Published: 2006

Total Pages: 300

ISBN-13: 9812773401

DOWNLOAD EBOOK

This volume presents recent progress in the improvement of the nuclear database needed for the development of Generation IV nuclear energy systems. The Generation IV International Forum (GIF) identified six advanced concepts for sustainable nuclear energy production at competitive prices and with advanced safety, with special attention to nuclear non-proliferation and physical protection issues, minimization of long-lived radiotoxic waste, and optimum natural resource utilization System groups have been established for studying these concepts in detail, and nuclear data are an inherent part of these studies. This book reviews the work recently performed for the development of these systems. The contributions include an up-to-date overview of recent achievements in sensitivity analysis, model calculations, estimates of uncertainties, and the present status of nuclear databases with regard to their applications to Generation IV systems. In the workshop, special attention was given to the identification of nuclear data needs from sensitivity analysis of benchmark experiments and the treatment of uncertainties. The proceedings contain overviews of several experimental program and recent results of interest for the development of Generation IV systems. Contents: Nuclear Data Needs for Generation IV Systems: Future of Nuclear Energy and the Role of Nuclear Data (P Finck); Nuclear Data Needs for Generation IV Nuclear Energy Systems OCo Summary of US Workshop (T A Taiwo & H S Khalil); Innovative Fuel Types for Minor Actinides Transmutation (D Haas et al.); Benchmarks, Sensitivity Calculations, Uncertainties: Sensitivity of Advanced Reactor and Fuel Cycle Performance Parameters to Nuclear Data Uncertainties (G Aliberti et al.); Computer Model of an Error Propagation Through Micro-Campaign of Fast Neutron Gas Cooled Nuclear Reactor (E Ivanov); Generating Covariance Data with Nuclear Models (A J Koning); Experiments: INL Capabilities for Nuclear Data Measurements Using the Argonne Intense Pulsed Neutron Source Facility (J D Cole et al.); Cross-Section Measurements in the Fast Neutron Energy Range (A Plompen); Recent Measurements of Neutron Capture Cross Sections for Minor Actinides by an JNC and Kyoto University Group (H Harada et al.); Evaluated Data Libraries: Nuclear Data Evaluation for Generation IV (G Nogu re et al.); Improved Evaluations of Neutron-Induced Reactions on Americium Isotopes (P Talou et al.); and several other important contributions. Readership: Graduate students and nuclear physicists interested in experimental nuclear physics, nuclear reactions modeling, and reactor physics, especially the development of Generation IV reactors."