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Author : Roger Ghanem,David Higdon,Howman Owhadi
Publisher : Unknown
Page : 128 pages
File Size : 43,6 Mb
Release : 2017
Category : Electronic
ISBN : OCLC:1006819223
Author : Roger Ghanem,David Higdon,Howman Owhadi
Publisher : Springer
Page : 0 pages
File Size : 49,5 Mb
Release : 2016-05-08
Category : Mathematics
ISBN : 331912384X
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.
Author : Faith A. Morrison
Publisher : Cambridge University Press
Page : 389 pages
File Size : 50,8 Mb
Release : 2021-01-07
Category : Computers
ISBN : 9781108478359
Build the skills for determining appropriate error limits for quantities that matter with this essential toolkit. Understand how to handle a complete project and how uncertainty enters into various steps. Provides a systematic, worksheet-based process to determine error limits on measured quantities, and all likely sources of uncertainty are explored, measured or estimated. Features instructions on how to carry out error analysis using Excel and MATLAB®, making previously tedious calculations easy. Whether you are new to the sciences or an experienced engineer, this useful resource provides a practical approach to performing error analysis. Suitable as a text for a junior or senior level laboratory course in aerospace, chemical and mechanical engineering, and for professionals.
Author : Pijush Samui,Dieu Tien Bui,Subrata Chakraborty,Ravinesh C. Deo
Publisher : Butterworth-Heinemann
Page : 590 pages
File Size : 44,7 Mb
Release : 2019-10-05
Category : Computers
ISBN : 9780128165461
Handbook of Probabilistic Models carefully examines the application of advanced probabilistic models in conventional engineering fields. In this comprehensive handbook, practitioners, researchers and scientists will find detailed explanations of technical concepts, applications of the proposed methods, and the respective scientific approaches needed to solve the problem. This book provides an interdisciplinary approach that creates advanced probabilistic models for engineering fields, ranging from conventional fields of mechanical engineering and civil engineering, to electronics, electrical, earth sciences, climate, agriculture, water resource, mathematical sciences and computer sciences. Specific topics covered include minimax probability machine regression, stochastic finite element method, relevance vector machine, logistic regression, Monte Carlo simulations, random matrix, Gaussian process regression, Kalman filter, stochastic optimization, maximum likelihood, Bayesian inference, Bayesian update, kriging, copula-statistical models, and more. Explains the application of advanced probabilistic models encompassing multidisciplinary research Applies probabilistic modeling to emerging areas in engineering Provides an interdisciplinary approach to probabilistic models and their applications, thus solving a wide range of practical problems
Author : T. J. Sullivan
Publisher : Unknown
Page : 342 pages
File Size : 54,7 Mb
Release : 2015
Category : Electronic
ISBN : 3919233948
Author : Christian Soize
Publisher : Springer
Page : 329 pages
File Size : 46,7 Mb
Release : 2017-04-24
Category : Computers
ISBN : 9783319543390
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.
Author : Ralph C. Smith
Publisher : SIAM
Page : 383 pages
File Size : 42,7 Mb
Release : 2013-12-02
Category : Estimation theory
ISBN : 9781611973228
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.
Author : Nicholas J. Higham,Mark R. Dennis,Paul Glendinning,Paul A. Martin,Fadil Santosa,Jared Tanner
Publisher : Princeton University Press
Page : 1014 pages
File Size : 45,9 Mb
Release : 2015-09-09
Category : Mathematics
ISBN : 9780691150390
The must-have compendium on applied mathematics This is the most authoritative and accessible single-volume reference book on applied mathematics. Featuring numerous entries by leading experts and organized thematically, it introduces readers to applied mathematics and its uses; explains key concepts; describes important equations, laws, and functions; looks at exciting areas of research; covers modeling and simulation; explores areas of application; and more. Modeled on the popular Princeton Companion to Mathematics, this volume is an indispensable resource for undergraduate and graduate students, researchers, and practitioners in other disciplines seeking a user-friendly reference book on applied mathematics. Features nearly 200 entries organized thematically and written by an international team of distinguished contributors Presents the major ideas and branches of applied mathematics in a clear and accessible way Explains important mathematical concepts, methods, equations, and applications Introduces the language of applied mathematics and the goals of applied mathematical research Gives a wide range of examples of mathematical modeling Covers continuum mechanics, dynamical systems, numerical analysis, discrete and combinatorial mathematics, mathematical physics, and much more Explores the connections between applied mathematics and other disciplines Includes suggestions for further reading, cross-references, and a comprehensive index
Author : Joachim Gwinner,Baasansuren Jadamba,Akhtar A. Khan,Fabio Raciti
Publisher : CRC Press
Page : 405 pages
File Size : 41,9 Mb
Release : 2021-12-24
Category : Mathematics
ISBN : 9781351857673
Uncertainty Quantification (UQ) is an emerging and extremely active research discipline which aims to quantitatively treat any uncertainty in applied models. The primary objective of Uncertainty Quantification in Variational Inequalities: Theory, Numerics, and Applications is to present a comprehensive treatment of UQ in variational inequalities and some of its generalizations emerging from various network, economic, and engineering models. Some of the developed techniques also apply to machine learning, neural networks, and related fields. Features First book on UQ in variational inequalities emerging from various network, economic, and engineering models Completely self-contained and lucid in style Aimed for a diverse audience including applied mathematicians, engineers, economists, and professionals from academia Includes the most recent developments on the subject which so far have only been available in the research literature
Author : Yan Wang,David L. McDowell
Publisher : Woodhead Publishing
Page : 606 pages
File Size : 43,9 Mb
Release : 2020-03-10
Category : Technology & Engineering
ISBN : 9780081029428
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. Synthesizes available UQ methods for materials modeling Provides practical tools and examples for problem solving in modeling material behavior across various length scales Demonstrates UQ in density functional theory, molecular dynamics, kinetic Monte Carlo, phase field, finite element method, multiscale modeling, and to support decision making in materials design Covers quantum, atomistic, mesoscale, and engineering structure-level modeling and simulation
Author : Rachid Ababou,Juliette Chastanet,Jean-Marie Côme,Manuel Marcoux,Michel Quintard
Publisher : Springer Nature
Page : 103 pages
File Size : 41,6 Mb
Release : 2024-01-21
Category : Computers
ISBN : 9789819962419
This book highlights several methods and quantitative implementations of both probabilistic and fuzzy-based approaches to uncertainty quantification and uncertainty propagation through environmental subsurface pollution models with uncertain input parameters. The book focuses on methods as well as applications in hydrogeology, soil hydrology, groundwater contamination, and related areas (e.g., corrosion of nuclear waste canisters). The methods are illustrated for a broad spectrum of models, from non-differential I/O models to complex PDE solvers, including a novel 3D quasi-analytical model of contaminant transport, and a site-specific computer model of dissolved contaminant migration from a DNAPL (Dense Non Aqueous Phase Liquid) pollution source.
Author : Dinesh K. Aswal,Sanjay Yadav,Toshiyuki Takatsuji,Prem Rachakonda,Harish Kumar
Publisher : Springer Nature
Page : 2504 pages
File Size : 43,8 Mb
Release : 2023-08-23
Category : Technology & Engineering
ISBN : 9789819920747
This handbook provides comprehensive and up-to-date information on the topic of scientific, industrial and legal metrology. It discusses the state-of-art review of various metrological aspects pertaining to redefinition of SI Units and their implications, applications of time and frequency metrology, certified reference materials, industrial metrology, industry 4.0, metrology in additive manufacturing, digital transformations in metrology, soft metrology and cyber security, optics in metrology, nano-metrology, metrology for advanced communication, environmental metrology, metrology in biomedical engineering, legal metrology and global trade, ionizing radiation metrology, advanced techniques in evaluation of measurement uncertainty, etc. The book has contributed chapters from world’s leading metrologists and experts on the diversified metrological theme. The internationally recognized team of editors adopt a consistent and systematic approach and writing style, including ample cross reference among topics, offering readers a user-friendly knowledgebase greater than the sum of its parts, perfect for frequent consultation. Moreover, the content of this volume is highly interdisciplinary in nature, with insights from not only metrology but also mechanical/material science, optics, physics, chemistry, biomedical and more. This handbook is ideal for academic and professional readers in the traditional and emerging areas of metrology and related fields.
Author : Shi Jin,Lorenzo Pareschi
Publisher : Springer
Page : 277 pages
File Size : 51,9 Mb
Release : 2018-03-20
Category : Mathematics
ISBN : 9783319671109
This book explores recent advances in uncertainty quantification for hyperbolic, kinetic, and related problems. The contributions address a range of different aspects, including: polynomial chaos expansions, perturbation methods, multi-level Monte Carlo methods, importance sampling, and moment methods. The interest in these topics is rapidly growing, as their applications have now expanded to many areas in engineering, physics, biology and the social sciences. Accordingly, the book provides the scientific community with a topical overview of the latest research efforts.
Author : Louis J. M. Aslett,Frank P. A. Coolen,Jasper De Bock
Publisher : Springer Nature
Page : 148 pages
File Size : 49,6 Mb
Release : 2022
Category : Electronic
ISBN : 9783030836405
This open access book provides an introduction to uncertainty quantification in engineering. Starting with preliminaries on Bayesian statistics and Monte Carlo methods, followed by material on imprecise probabilities, it then focuses on reliability theory and simulation methods for complex systems. The final two chapters discuss various aspects of aerospace engineering, considering stochastic model updating from an imprecise Bayesian perspective, and uncertainty quantification for aerospace flight modelling. Written by experts in the subject, and based on lectures given at the Second Training School of the European Research and Training Network UTOPIAE (Uncertainty Treatment and Optimization in Aerospace Engineering), which took place at Durham University (United Kingdom) from 2 to 6 July 2018, the book offers an essential resource for students as well as scientists and practitioners.
Author : Stephen Ekwaro-Osire,Aparecido Carlos Gonçalves,Fisseha M. Alemayehu
Publisher : Springer
Page : 277 pages
File Size : 44,9 Mb
Release : 2017-04-25
Category : Technology & Engineering
ISBN : 9783319558523
This book proposes the formulation of an efficient methodology that estimates energy system uncertainty and predicts Remaining Useful Life (RUL) accurately with significantly reduced RUL prediction uncertainty. Renewable and non-renewable sources of energy are being used to supply the demands of societies worldwide. These sources are mainly thermo-chemo-electro-mechanical systems that are subject to uncertainty in future loading conditions, material properties, process noise, and other design parameters.It book informs the reader of existing and new ideas that will be implemented in RUL prediction of energy systems in the future. The book provides case studies, illustrations, graphs, and charts. Its chapters consider engineering, reliability, prognostics and health management, probabilistic multibody dynamical analysis, peridynamic and finite-element modelling, computer science, and mathematics.
