Workshop on Uncertainty Quantification and Multiscale Materials Modeling - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Workshop on Uncertainty Quantification and Multiscale Materials Modeling write by . This book was released on 2011. Workshop on Uncertainty Quantification and Multiscale Materials Modeling available in PDF, EPUB and Kindle.
Uncertainty Quantification in Multiscale Materials Modeling
Uncertainty Quantification in Multiscale Materials Modeling - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Uncertainty Quantification in Multiscale Materials Modeling write by Yan Wang. This book was released on 2020-03-10. Uncertainty Quantification in Multiscale Materials Modeling available in PDF, EPUB and Kindle. 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
Proceedings of the 5th International Symposium on Uncertainty Quantification and Stochastic Modelling
Proceedings of the 5th International Symposium on Uncertainty Quantification and Stochastic Modelling - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Proceedings of the 5th International Symposium on Uncertainty Quantification and Stochastic Modelling write by José Eduardo Souza De Cursi. This book was released on 2020-08-19. Proceedings of the 5th International Symposium on Uncertainty Quantification and Stochastic Modelling available in PDF, EPUB and Kindle. This proceedings book discusses state-of-the-art research on uncertainty quantification in mechanical engineering, including statistical data concerning the entries and parameters of a system to produce statistical data on the outputs of the system. It is based on papers presented at Uncertainties 2020, a workshop organized on behalf of the Scientific Committee on Uncertainty in Mechanics (Mécanique et Incertain) of the AFM (French Society of Mechanical Sciences), the Scientific Committee on Stochastic Modeling and Uncertainty Quantification of the ABCM (Brazilian Society of Mechanical Sciences) and the SBMAC (Brazilian Society of Applied Mathematics).
Fundamentals of Uncertainty Quantification for Engineers
Fundamentals of Uncertainty Quantification for Engineers - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Fundamentals of Uncertainty Quantification for Engineers write by Yan Wang. This book was released on 2024-10-01. Fundamentals of Uncertainty Quantification for Engineers available in PDF, EPUB and Kindle. Fundamentals of Uncertainty Quantification for Engineers: Methods and Models provides a comprehensive introduction to uncertainty quantification (UQ) accompanied by a wide variety of applied examples, implementation details, and practical exercises to reinforce the concepts outlined in the book. Sections start with a review of the history of probability theory and recent developments of UQ methods in the domains of applied mathematics and data science. Major concepts of probability axioms, conditional probability, and Bayes’ rule are discussed and examples of probability distributions in parametric data analysis, reliability, risk analysis, and materials informatics are included. Random processes, sampling methods, and surrogate modeling techniques including multivariate polynomial regression, Gaussian process regression, multi-fidelity surrogate, support-vector machine, and decision tress are also covered. Methods for model selection, calibration, and validation are introduced next, followed by chapters on sensitivity analysis, stochastic expansion methods, Markov models, and non-probabilistic methods. The book concludes with a chapter describing the methods that can be used to predict UQ in systems, such as Monte Carlo, stochastic expansion, upscaling, Langevin dynamics, and inverse problems, with example applications in multiscale modeling, simulations, and materials design. Introduces all major topics of uncertainty quantification with engineering examples, implementation details, and practical exercises provided in all chapters Features examples from a wide variety of science and engineering disciplines (e.g. aerospace, mechanical, material, manufacturing, multiscale simulation) Discusses materials informatics, sampling methods, surrogate modeling techniques, decision tress, multivariate polynomial regression, and more
Uncertainty Quantification
Uncertainty Quantification - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Uncertainty Quantification write by Christian Soize. This book was released on 2017-04-24. Uncertainty Quantification available in PDF, EPUB and Kindle. 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.
