LEADER 04434nam 22006495 450 001 9910254309203321 005 20200704074130.0 010 $a3-319-54339-3 024 7 $a10.1007/978-3-319-54339-0 035 $a(CKB)3850000000027366 035 $a(DE-He213)978-3-319-54339-0 035 $a(MiAaPQ)EBC6312469 035 $a(MiAaPQ)EBC5595591 035 $a(Au-PeEL)EBL5595591 035 $a(OCoLC)985361180 035 $z(PPN)258852186 035 $a(PPN)200512897 035 $a(EXLCZ)993850000000027366 100 $a20170424d2017 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aUncertainty Quantification $eAn Accelerated Course with Advanced Applications in Computational Engineering /$fby Christian Soize 205 $a1st ed. 2017. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2017. 215 $a1 online resource (XXII, 329 p. 110 illus., 86 illus. in color.) 225 1 $aInterdisciplinary Applied Mathematics,$x0939-6047 ;$v47 311 $a3-319-54338-5 320 $aIncludes bibliographical references and index. 327 $aFundamental Notions in Stochastic Modeling of Uncertainties and their Propagation in Computational Models -- Elements of Probability Theory -- Markov Process and Stochastic Differential Equation -- MCMC Methods for Generating Realizations and for Estimating the Mathematical Expectation of Nonlinear Mappings of Random Vectors -- Fundamental Probabilistic Tools for Stochastic Modeling of Uncertainties -- Brief Overview of Stochastic Solvers for the Propagation of Uncertainties -- Fundamental Tools for Statistical Inverse Problems -- Uncertainty Quantification in Computational Structural Dynamics and Vibroacoustics -- Robust Analysis with Respect to the Uncertainties for Analysis, Updating, Optimization, and Design -- Random Fields and Uncertainty Quantification in Solid Mechanics of Continuum Media. 330 $aThis book presents the fundamental notions and advanced mathematical tools in the stochastic modeling of uncertainties and their quantification for large-scale computational models in sciences and engineering. In particular, it focuses in parametric uncertainties, and non-parametric uncertainties with applications from the structural dynamics and vibroacoustics of complex mechanical systems, from micromechanics and multiscale mechanics of heterogeneous materials. Resulting from a course developed by the author, the book begins with a description of the fundamental mathematical tools of probability and statistics that are directly useful for uncertainty quantification. It proceeds with a well carried out description of some basic and advanced methods for constructing stochastic models of uncertainties, paying particular attention to the problem of calibrating and identifying a stochastic model of uncertainty when experimental data is available. < This book is intended to be a graduate-level textbook for students as well as professionals interested in the theory, computation, and applications of risk and prediction in science and engineering fields. 410 0$aInterdisciplinary Applied Mathematics,$x0939-6047 ;$v47 606 $aComputer mathematics 606 $aApplied mathematics 606 $aEngineering mathematics 606 $aProbabilities 606 $aComputational Science and Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/M14026 606 $aMathematical and Computational Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T11006 606 $aProbability Theory and Stochastic Processes$3https://scigraph.springernature.com/ontologies/product-market-codes/M27004 615 0$aComputer mathematics. 615 0$aApplied mathematics. 615 0$aEngineering mathematics. 615 0$aProbabilities. 615 14$aComputational Science and Engineering. 615 24$aMathematical and Computational Engineering. 615 24$aProbability Theory and Stochastic Processes. 676 $a519.2 700 $aSoize$b Christian$4aut$4http://id.loc.gov/vocabulary/relators/aut$029246 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910254309203321 996 $aUncertainty quantification$91560479 997 $aUNINA