Uncertainty Quantification And Predictive Computational Science

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Uncertainty Quantification and Predictive Computational Science

Ryan G. McClarren
Uncertainty Quantification and Predictive Computational Science Book PDF

Author : Ryan G. McClarren
Publisher : Springer
Page : 345 pages
File Size : 41,7 Mb
Release : 2018-11-23
Category : Science
ISBN : 9783319995250

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Uncertainty Quantification and Predictive Computational Science by Ryan G. McClarren Pdf

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.

Uncertainty Quantification

Ralph C. Smith
Uncertainty Quantification Book PDF

Author : Ralph C. Smith
Publisher : SIAM
Page : 383 pages
File Size : 40,7 Mb
Release : 2013-12-02
Category : Estimation theory
ISBN : 9781611973228

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Uncertainty Quantification by Ralph C. Smith Pdf

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

Christian Soize
Uncertainty Quantification Book PDF

Author : Christian Soize
Publisher : Springer
Page : 329 pages
File Size : 41,8 Mb
Release : 2017-04-24
Category : Computers
ISBN : 9783319543390

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Uncertainty Quantification by Christian Soize Pdf

This book presents the fundamental notions and advanced mathematical tools in the stochastic modeling of uncertainties and their quantification for large-scale computational models in sciences and engineering. In particular, it focuses in parametric uncertainties, and non-parametric uncertainties with applications from the structural dynamics and vibroacoustics of complex mechanical systems, from micromechanics and multiscale mechanics of heterogeneous materials. Resulting from a course developed by the author, the book begins with a description of the fundamental mathematical tools of probability and statistics that are directly useful for uncertainty quantification. It proceeds with a well carried out description of some basic and advanced methods for constructing stochastic models of uncertainties, paying particular attention to the problem of calibrating and identifying a stochastic model of uncertainty when experimental data is available. This book is intended to be a graduate-level textbook for students as well as professionals interested in the theory, computation, and applications of risk and prediction in science and engineering fields.

Uncertainty Quantification in Scientific Computing

Andrew Dienstfrey,Ronald Boisvert
Uncertainty Quantification in Scientific Computing Book PDF

Author : Andrew Dienstfrey,Ronald Boisvert
Publisher : Springer
Page : 320 pages
File Size : 41,7 Mb
Release : 2012-08-11
Category : Computers
ISBN : 9783642326776

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Uncertainty Quantification in Scientific Computing by Andrew Dienstfrey,Ronald Boisvert Pdf

This book constitutes the refereed post-proceedings of the 10th IFIP WG 2.5 Working Conference on Uncertainty Quantification in Scientific Computing, WoCoUQ 2011, held in Boulder, CO, USA, in August 2011. The 24 revised papers were carefully reviewed and selected from numerous submissions. They are organized in the following topical sections: UQ need: risk, policy, and decision making, UQ theory, UQ tools, UQ practice, and hot topics. The papers are followed by the records of the discussions between the participants and the speaker.

Introduction to Uncertainty Quantification

T.J. Sullivan
Introduction to Uncertainty Quantification Book PDF

Author : T.J. Sullivan
Publisher : Springer
Page : 342 pages
File Size : 46,9 Mb
Release : 2015-12-14
Category : Mathematics
ISBN : 9783319233956

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Introduction to Uncertainty Quantification by T.J. Sullivan Pdf

This text provides a framework in which the main objectives of the field of uncertainty quantification (UQ) are defined and an overview of the range of mathematical methods by which they can be achieved. Complete with exercises throughout, the book will equip readers with both theoretical understanding and practical experience of the key mathematical and algorithmic tools underlying the treatment of uncertainty in modern applied mathematics. Students and readers alike are encouraged to apply the mathematical methods discussed in this book to their own favorite problems to understand their strengths and weaknesses, also making the text suitable for a self-study. Uncertainty quantification is a topic of increasing practical importance at the intersection of applied mathematics, statistics, computation and numerous application areas in science and engineering. This text is designed as an introduction to UQ for senior undergraduate and graduate students with a mathematical or statistical background and also for researchers from the mathematical sciences or from applications areas who are interested in the field. T. J. Sullivan was Warwick Zeeman Lecturer at the Mathematics Institute of the University of Warwick, United Kingdom, from 2012 to 2015. Since 2015, he is Junior Professor of Applied Mathematics at the Free University of Berlin, Germany, with specialism in Uncertainty and Risk Quantification.

Computational Uncertainty Quantification for Inverse Problems

Johnathan M. Bardsley
Computational Uncertainty Quantification for Inverse Problems Book PDF

Author : Johnathan M. Bardsley
Publisher : SIAM
Page : 141 pages
File Size : 52,5 Mb
Release : 2018-08-01
Category : Science
ISBN : 9781611975376

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Computational Uncertainty Quantification for Inverse Problems by Johnathan M. Bardsley Pdf

This book is an introduction to both computational inverse problems and uncertainty quantification (UQ) for inverse problems. The book also presents more advanced material on Bayesian methods and UQ, including Markov chain Monte Carlo sampling methods for UQ in inverse problems. Each chapter contains MATLAB? code that implements the algorithms and generates the figures, as well as a large number of exercises accessible to both graduate students and researchers. Computational Uncertainty Quantification for Inverse Problems is intended for graduate students, researchers, and applied scientists. It is appropriate for courses on computational inverse problems, Bayesian methods for inverse problems, and UQ methods for inverse problems.

Cultures of Prediction in Atmospheric and Climate Science

Matthias Heymann,Gabriele Gramelsberger,Martin Mahony
Cultures of Prediction in Atmospheric and Climate Science Book PDF

Author : Matthias Heymann,Gabriele Gramelsberger,Martin Mahony
Publisher : Taylor & Francis
Page : 256 pages
File Size : 43,6 Mb
Release : 2017-06-26
Category : Computers
ISBN : 9781315406299

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Cultures of Prediction in Atmospheric and Climate Science by Matthias Heymann,Gabriele Gramelsberger,Martin Mahony Pdf

In recent decades, science has experienced a revolutionary shift. The development and extensive application of computer modelling and simulation has transformed the knowledge‐making practices of scientific fields as diverse as astro‐physics, genetics, robotics and demography. This epistemic transformation has brought with it a simultaneous heightening of political relevance and a renewal of international policy agendas, raising crucial questions about the nature and application of simulation knowledges throughout public policy. Through a diverse range of case studies, spanning over a century of theoretical and practical developments in the atmospheric and environmental sciences, this book argues that computer modelling and simulation have substantially changed scientific and cultural practices and shaped the emergence of novel ‘cultures of prediction’. Making an innovative, interdisciplinary contribution to understanding the impact of computer modelling on research practice, institutional configurations and broader cultures, this volume will be essential reading for anyone interested in the past, present and future of climate change and the environmental sciences.

Assessing the Reliability of Complex Models

National Research Council,Division on Engineering and Physical Sciences,Board on Mathematical Sciences and Their Applications,Committee on Mathematical Foundations of Verification, Validation, and Uncertainty Quantification
Assessing the Reliability of Complex Models Book PDF

Author : National Research Council,Division on Engineering and Physical Sciences,Board on Mathematical Sciences and Their Applications,Committee on Mathematical Foundations of Verification, Validation, and Uncertainty Quantification
Publisher : National Academies Press
Page : 144 pages
File Size : 50,9 Mb
Release : 2012-07-26
Category : Mathematics
ISBN : 9780309256346

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Assessing the Reliability of Complex Models by National Research Council,Division on Engineering and Physical Sciences,Board on Mathematical Sciences and Their Applications,Committee on Mathematical Foundations of Verification, Validation, and Uncertainty Quantification Pdf

Advances in computing hardware and algorithms have dramatically improved the ability to simulate complex processes computationally. Today's simulation capabilities offer the prospect of addressing questions that in the past could be addressed only by resource-intensive experimentation, if at all. Assessing the Reliability of Complex Models recognizes the ubiquity of uncertainty in computational estimates of reality and the necessity for its quantification. As computational science and engineering have matured, the process of quantifying or bounding uncertainties in a computational estimate of a physical quality of interest has evolved into a small set of interdependent tasks: verification, validation, and uncertainty of quantification (VVUQ). In recognition of the increasing importance of computational simulation and the increasing need to assess uncertainties in computational results, the National Research Council was asked to study the mathematical foundations of VVUQ and to recommend steps that will ultimately lead to improved processes. Assessing the Reliability of Complex Models discusses changes in education of professionals and dissemination of information that should enhance the ability of future VVUQ practitioners to improve and properly apply VVUQ methodologies to difficult problems, enhance the ability of VVUQ customers to understand VVUQ results and use them to make informed decisions, and enhance the ability of all VVUQ stakeholders to communicate with each other. This report is an essential resource for all decision and policy makers in the field, students, stakeholders, UQ experts, and VVUQ educators and practitioners.

Handbook of Uncertainty Quantification

Roger Ghanem,David Higdon,Howman Owhadi
Handbook of Uncertainty Quantification Book PDF

Author : Roger Ghanem,David Higdon,Howman Owhadi
Publisher : Springer
Page : 0 pages
File Size : 44,6 Mb
Release : 2016-05-08
Category : Mathematics
ISBN : 331912384X

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Handbook of Uncertainty Quantification by Roger Ghanem,David Higdon,Howman Owhadi Pdf

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.

Uncertainty Quantification in Computational Science

Sunetra Sarkar,Jeroen A. S. Witteveen
Uncertainty Quantification in Computational Science Book PDF

Author : Sunetra Sarkar,Jeroen A. S. Witteveen
Publisher : World Scientific Publishing Company
Page : 196 pages
File Size : 43,8 Mb
Release : 2016-07-31
Category : Technology & Engineering
ISBN : 9814730572

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Uncertainty Quantification in Computational Science by Sunetra Sarkar,Jeroen A. S. Witteveen Pdf

During the last decade, research in Uncertainty Quantification (UC) has received a tremendous boost, in fluid engineering and coupled structural-fluids systems. New algorithms and adaptive variants have also emerged. This timely compendium overviews in detail the current state of the art of the field, including advances in structural engineering, along with the recent focus on fluids and coupled systems. Such a strong compilation of these vibrant research areas will certainly be an inspirational reference material for the scientific community.

Uncertainty Quantification in Computational Fluid Dynamics

Hester Bijl,Didier Lucor,Siddharta Mishra,Christoph Schwab
Uncertainty Quantification in Computational Fluid Dynamics Book PDF

Author : Hester Bijl,Didier Lucor,Siddharta Mishra,Christoph Schwab
Publisher : Springer
Page : 333 pages
File Size : 50,7 Mb
Release : 2013-11-27
Category : Mathematics
ISBN : 3319008862

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Uncertainty Quantification in Computational Fluid Dynamics by Hester Bijl,Didier Lucor,Siddharta Mishra,Christoph Schwab Pdf

Fluid flows are characterized by uncertain inputs such as random initial data, material and flux coefficients, and boundary conditions. The current volume addresses the pertinent issue of efficiently computing the flow uncertainty, given this initial randomness. It collects seven original review articles that cover improved versions of the Monte Carlo method (the so-called multi-level Monte Carlo method (MLMC)), moment-based stochastic Galerkin methods and modified versions of the stochastic collocation methods that use adaptive stencil selection of the ENO-WENO type in both physical and stochastic space. The methods are also complemented by concrete applications such as flows around aerofoils and rockets, problems of aeroelasticity (fluid-structure interactions), and shallow water flows for propagating water waves. The wealth of numerical examples provide evidence on the suitability of each proposed method as well as comparisons of different approaches.

Uncertainty Quantification in Computational Science

Sunetra Sarkar,Jeroen A S Witteveen
Uncertainty Quantification in Computational Science Book PDF

Author : Sunetra Sarkar,Jeroen A S Witteveen
Publisher : World Scientific
Page : 196 pages
File Size : 51,9 Mb
Release : 2016-08-19
Category : Electronic
ISBN : 9789814730594

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Uncertainty Quantification in Computational Science by Sunetra Sarkar,Jeroen A S Witteveen Pdf

During the last decade, research in Uncertainty Quantification (UC) has received a tremendous boost, in fluid engineering and coupled structural-fluids systems. New algorithms and adaptive variants have also emerged. This timely compendium overviews in detail the current state of the art of the field, including advances in structural engineering, along with the recent focus on fluids and coupled systems. Such a strong compilation of these vibrant research areas will certainly be an inspirational reference material for the scientific community.

14th International Symposium on Process Systems Engineering

Yoshiyuki Yamashita,Manabu Kano
14th International Symposium on Process Systems Engineering Book PDF

Author : Yoshiyuki Yamashita,Manabu Kano
Publisher : Elsevier
Page : 2304 pages
File Size : 53,7 Mb
Release : 2022-06-24
Category : Technology & Engineering
ISBN : 9780323853668

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14th International Symposium on Process Systems Engineering by Yoshiyuki Yamashita,Manabu Kano Pdf

14th International Symposium on Process Systems Engineering, Volume 49 brings together the international community of researchers and engineers interested in computing-based methods in process engineering. The conference highlights the contributions of the PSE community towards the sustainability of modern society and is based on the 2021 event held in Tokyo, Japan, July 1-23, 2021. It contains contributions from academia and industry, establishing the core products of PSE, defining the new and changing scope of our results, and covering future challenges. Plenary and keynote lectures discuss real-world challenges (globalization, energy, environment and health) and contribute to discussions on the widening scope of PSE versus the consolidation of the core topics of PSE. Highlights how the Process Systems Engineering community contributes to the sustainability of modern society Establishes the core products of Process Systems Engineering Defines the future challenges of Process Systems Engineering

Quantification of Uncertainty: Improving Efficiency and Technology

Marta D'Elia,Max Gunzburger,Gianluigi Rozza
Quantification of Uncertainty Improving Efficiency and Technology Book PDF

Author : Marta D'Elia,Max Gunzburger,Gianluigi Rozza
Publisher : Springer Nature
Page : 290 pages
File Size : 50,8 Mb
Release : 2020-07-30
Category : Mathematics
ISBN : 9783030487218

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Quantification of Uncertainty: Improving Efficiency and Technology by Marta D'Elia,Max Gunzburger,Gianluigi Rozza Pdf

This book explores four guiding themes – reduced order modelling, high dimensional problems, efficient algorithms, and applications – by reviewing recent algorithmic and mathematical advances and the development of new research directions for uncertainty quantification in the context of partial differential equations with random inputs. Highlighting the most promising approaches for (near-) future improvements in the way uncertainty quantification problems in the partial differential equation setting are solved, and gathering contributions by leading international experts, the book’s content will impact the scientific, engineering, financial, economic, environmental, social, and commercial sectors.

Recent Advancements in Multi-View Data Analytics

Witold Pedrycz,Shyi-Ming Chen
Recent Advancements in Multi View Data Analytics Book PDF

Author : Witold Pedrycz,Shyi-Ming Chen
Publisher : Springer Nature
Page : 346 pages
File Size : 41,8 Mb
Release : 2022-05-20
Category : Computers
ISBN : 9783030952396

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Recent Advancements in Multi-View Data Analytics by Witold Pedrycz,Shyi-Ming Chen Pdf

This book provides timely studies on multi-view facets of data analytics by covering recent trends in processing and reasoning about data originating from an array of local sources. A multi-view nature of data analytics is encountered when working with a variety of real-world scenarios including clustering, consensus building in decision processes, computer vision, knowledge representation, big data, data streaming, among others. The chapters demonstrate recent pursuits in the methodology, theory, advanced algorithms, and applications of multi-view data analytics and bring new perspectives of data interpretation. The timely book will appeal to a broad readership including both researchers and practitioners interested in gaining exposure to the rapidly growing trend of multi-view data analytics and intelligent systems.