Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Adaptive Sparse Polynomial Chaos Expansions For Uncertainty Propagation And Sensitivity Analysis
Download Adaptive Sparse Polynomial Chaos Expansions For Uncertainty Propagation And Sensitivity Analysis full books in PDF, epub, and Kindle. Read online Adaptive Sparse Polynomial Chaos Expansions For Uncertainty Propagation And Sensitivity Analysis ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Adaptive Sparse Polynomial Chaos Expansions for Uncertainty Propagation and Sensitivity Analysis by : Géraud Blatman
Download or read book Adaptive Sparse Polynomial Chaos Expansions for Uncertainty Propagation and Sensitivity Analysis written by Géraud Blatman and published by . This book was released on 2009 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cette thèse s'insère dans le contexte générale de la propagation d'incertitudes et de l'analyse de sensibilité de modèles de simulation numérique, en vue d'applications industrielles. Son objectif est d'effectuer de telles études en minimisant le nombre d'évaluations du modèle, potentiellement coûteuses. Le présent travail repose sur une approximation de la réponse du modèle sur la base du chaos polynomial (CP), qui permet de réaliser des post-traitements à un coût de calcul négligeable. Toutefois, l'ajustement du CP peut nécessiter un nombre conséquent d'appels au modèle si ce dernier dépend d'un nombre élevé de paramètres (e.g. supérieur à 10). Pour contourner ce problème, on propose deux algorithmes pour ne sélectionner qu'un faible nombre de termes importants dans la représentation par CP, à savoir une procédure de régression pas-à-pas et une procédure basée sur la méthode de Least Angle Regression (LAR). Le faible nombre de coefficients associés aux CP creux obtenus peuvent ainsi être déterminés à partir d'un nombre réduit d'évaluations du modèle. Les méthodes sont validées sur des cas-tests académiques de mécanique, puis appliquées sur le cas industriel de l'analyse d'intégrité d'une cuve de réacteur à eau pressurisée. Les résultats obtenus confirment l'efficacité des méthodes proposées pour traiter les problèmes de propagation d'incertitudes et d'analyse de sensibilité en grande dimension.
Book Synopsis Sparse Polynomial Chaos Expansions for Uncertainty Propagation and Sensitivity Analysis by : Bruno Sudret
Download or read book Sparse Polynomial Chaos Expansions for Uncertainty Propagation and Sensitivity Analysis written by Bruno Sudret and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Meteorological Tsunamis: The U.S. East Coast and Other Coastal Regions by : Ivica Vilibić
Download or read book Meteorological Tsunamis: The U.S. East Coast and Other Coastal Regions written by Ivica Vilibić and published by Springer. This book was released on 2014-11-16 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book encompasses a set of papers on meteorological tsunamis covering various aspects on this rare but potentially destructive multiresonant phenomenon. Altogether an editorial and 15 contributions are part of this book; eight of the contributions deal with different aspects of meteotsunamis along the U.S. East Coast and in the region of the Great Lakes, including one paper introducing a new methodology in meteotsunami research. Seven more papers are documenting meteotsunamis in various coastal areas of the world oceans. All continents, except Antarctica, have been covered, with the authors representing 11 countries. Previously Published in Natural Hazards, Volume 74, No. 1, 2014
Book Synopsis Handbook of Uncertainty Quantification by : Roger Ghanem
Download or read book Handbook of Uncertainty Quantification written by Roger Ghanem and published by Springer. This book was released on 2016-05-08 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Approximation Theory and Analytic Inequalities by : Themistocles M. Rassias
Download or read book Approximation Theory and Analytic Inequalities written by Themistocles M. Rassias and published by Springer Nature. This book was released on 2021-07-21 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: This contributed volume focuses on various important areas of mathematics in which approximation methods play an essential role. It features cutting-edge research on a wide spectrum of analytic inequalities with emphasis on differential and integral inequalities in the spirit of functional analysis, operator theory, nonlinear analysis, variational calculus, featuring a plethora of applications, making this work a valuable resource. The reader will be exposed to convexity theory, polynomial inequalities, extremal problems, prediction theory, fixed point theory for operators, PDEs, fractional integral inequalities, multidimensional numerical integration, Gauss–Jacobi and Hermite–Hadamard type inequalities, Hilbert-type inequalities, and Ulam’s stability of functional equations. Contributions have been written by eminent researchers, providing up-to-date information and several results which may be useful to a wide readership including graduate students and researchers working in mathematics, physics, economics, operational research, and their interconnections.
Book Synopsis Spectral Methods for Uncertainty Quantification by : Olivier Le Maitre
Download or read book Spectral Methods for Uncertainty Quantification written by Olivier Le Maitre and published by Springer Science & Business Media. This book was released on 2010-03-11 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with the application of spectral methods to problems of uncertainty propagation and quanti?cation in model-based computations. It speci?cally focuses on computational and algorithmic features of these methods which are most useful in dealing with models based on partial differential equations, with special att- tion to models arising in simulations of ?uid ?ows. Implementations are illustrated through applications to elementary problems, as well as more elaborate examples selected from the authors’ interests in incompressible vortex-dominated ?ows and compressible ?ows at low Mach numbers. Spectral stochastic methods are probabilistic in nature, and are consequently rooted in the rich mathematical foundation associated with probability and measure spaces. Despite the authors’ fascination with this foundation, the discussion only - ludes to those theoretical aspects needed to set the stage for subsequent applications. The book is authored by practitioners, and is primarily intended for researchers or graduate students in computational mathematics, physics, or ?uid dynamics. The book assumes familiarity with elementary methods for the numerical solution of time-dependent, partial differential equations; prior experience with spectral me- ods is naturally helpful though not essential. Full appreciation of elaborate examples in computational ?uid dynamics (CFD) would require familiarity with key, and in some cases delicate, features of the associated numerical methods. Besides these shortcomings, our aim is to treat algorithmic and computational aspects of spectral stochastic methods with details suf?cient to address and reconstruct all but those highly elaborate examples.
Book Synopsis Optimization Under Uncertainty with Applications to Aerospace Engineering by : Massimiliano Vasile
Download or read book Optimization Under Uncertainty with Applications to Aerospace Engineering written by Massimiliano Vasile and published by Springer Nature. This book was released on 2021-02-15 with total page 573 pages. Available in PDF, EPUB and Kindle. Book excerpt: In an expanding world with limited resources, optimization and uncertainty quantification have become a necessity when handling complex systems and processes. This book provides the foundational material necessary for those who wish to embark on advanced research at the limits of computability, collecting together lecture material from leading experts across the topics of optimization, uncertainty quantification and aerospace engineering. The aerospace sector in particular has stringent performance requirements on highly complex systems, for which solutions are expected to be optimal and reliable at the same time. The text covers a wide range of techniques and methods, from polynomial chaos expansions for uncertainty quantification to Bayesian and Imprecise Probability theories, and from Markov chains to surrogate models based on Gaussian processes. The book will serve as a valuable tool for practitioners, researchers and PhD students.
Book Synopsis Construction Reliability by : Julien Baroth
Download or read book Construction Reliability written by Julien Baroth and published by John Wiley & Sons. This book was released on 2013-02-07 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides answers to the following problems: how to identify the most probable critical failures; how to describe and use data-concerning materials that are either heterogeneous, time-variant, or space-variant; how to quantify the reliability and lifetime of a system; how to use feedback information to actualize reliability results; and how to optimize an inspection politic or a maintenance strategy. Numerous authors from public research centers and firms propose a synthesis of methods, both new and well-known, and offer numerous examples concerning dams, geotechnical study, and structures from nuclear and civil engineering.
Book Synopsis Advanced Computational Electromagnetic Methods by : Wenhua Yu
Download or read book Advanced Computational Electromagnetic Methods written by Wenhua Yu and published by Artech House. This book was released on 2015-03-01 with total page 597 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new resource covers the latest developments in computational electromagnetic methods, with emphasis on cutting-edge applications. This book is designed to extend existing literature to the latest development in computational electromagnetic methods, which are of interest to readers in both academic and industrial areas. The topics include advanced techniques in MoM, FEM and FDTD, spectral domain method, GPU and Phi hardware acceleration, metamaterials, frequency and time domain integral equations, and statistics methods in bio-electromagnetics.
Book Synopsis Proceedings of the 2nd International Conference on Mechanical System Dynamics by : Xiaoting Rui
Download or read book Proceedings of the 2nd International Conference on Mechanical System Dynamics written by Xiaoting Rui and published by Springer Nature. This book was released on with total page 4383 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Risk and Reliability in Geotechnical Engineering by : Kok-Kwang Phoon
Download or read book Risk and Reliability in Geotechnical Engineering written by Kok-Kwang Phoon and published by CRC Press. This book was released on 2018-10-09 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Establishes Geotechnical Reliability as Fundamentally Distinct from Structural Reliability Reliability-based design is relatively well established in structural design. Its use is less mature in geotechnical design, but there is a steady progression towards reliability-based design as seen in the inclusion of a new Annex D on "Reliability of Geotechnical Structures" in the third edition of ISO 2394. Reliability-based design can be viewed as a simplified form of risk-based design where different consequences of failure are implicitly covered by the adoption of different target reliability indices. Explicit risk management methodologies are required for large geotechnical systems where soil and loading conditions are too varied to be conveniently slotted into a few reliability classes (typically three) and an associated simple discrete tier of target reliability indices. Provides Realistic Practical Guidance Risk and Reliability in Geotechnical Engineering makes these reliability and risk methodologies more accessible to practitioners and researchers by presenting soil statistics which are necessary inputs, by explaining how calculations can be carried out using simple tools, and by presenting illustrative or actual examples showcasing the benefits and limitations of these methodologies. With contributions from a broad international group of authors, this text: Presents probabilistic models suited for soil parameters Provides easy-to-use Excel-based methods for reliability analysis Connects reliability analysis to design codes (including LRFD and Eurocode 7) Maximizes value of information using Bayesian updating Contains efficient reliability analysis methods Accessible To a Wide Audience Risk and Reliability in Geotechnical Engineering presents all the "need-to-know" information for a non-specialist to calculate and interpret the reliability index and risk of geotechnical structures in a realistic and robust way. It suits engineers, researchers, and students who are interested in the practical outcomes of reliability and risk analyses without going into the intricacies of the underlying mathematical theories.
Book Synopsis Proceedings of the 5th International Symposium on Uncertainty Quantification and Stochastic Modelling by : José Eduardo Souza De Cursi
Download or read book Proceedings of the 5th International Symposium on Uncertainty Quantification and Stochastic Modelling written by José Eduardo Souza De Cursi and published by Springer Nature. This book was released on 2020-08-19 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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).
Book Synopsis Computational Science – ICCS 2018 by : Yong Shi
Download or read book Computational Science – ICCS 2018 written by Yong Shi and published by Springer. This book was released on 2018-06-11 with total page 892 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 10860, 10861 and 10862 constitutes the proceedings of the 18th International Conference on Computational Science, ICCS 2018, held in Wuxi, China, in June 2018. The total of 155 full and 66 short papers presented in this book set was carefully reviewed and selected from 404 submissions. The papers were organized in topical sections named: Part I: ICCS Main Track Part II: Track of Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Track of Agent-Based Simulations, Adaptive Algorithms and Solvers; Track of Applications of Matrix Methods in Artificial Intelligence and Machine Learning; Track of Architecture, Languages, Compilation and Hardware Support for Emerging ManYcore Systems; Track of Biomedical and Bioinformatics Challenges for Computer Science; Track of Computational Finance and Business Intelligence; Track of Computational Optimization, Modelling and Simulation; Track of Data, Modeling, and Computation in IoT and Smart Systems; Track of Data-Driven Computational Sciences; Track of Mathematical-Methods-and-Algorithms for Extreme Scale; Track of Multiscale Modelling and Simulation Part III: Track of Simulations of Flow and Transport: Modeling, Algorithms and Computation; Track of Solving Problems with Uncertainties; Track of Teaching Computational Science; Poster Papers
Book Synopsis Efficient Algorithms for Uncertainty Quantification Using Polynomial Chaos Expansion and Its Applications to Composite Structures by : Mishal Thapa
Download or read book Efficient Algorithms for Uncertainty Quantification Using Polynomial Chaos Expansion and Its Applications to Composite Structures written by Mishal Thapa and published by . This book was released on 2019 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty Quantification (UQ) deals with the study of variation in the response due to the presence of uncertainties in input parameters and governing models. Among the prevalent probabilistic techniques for UQ, non-intrusive Polynomial Chaos Expansion (PCE) has become more popular recently due to its mean square convergence property and ability to integrate deterministic codes as black-box. However, the number of basis terms in the expansion increases exponentially with the number of random inputs - 'curse of dimensionality,' and demands a huge number of function evaluations. Hence, this dissertation has attempted to extensively explore new robust algorithms for PCE while maintaining a proper balance between accuracy and computational efficiency. At first, a new non-intrusive method for PCE called Polynomial Chaos Decomposition with Differentiation (PCDD) is developed. The PCDD utilizes higher-order sensitivities of the responses and requires samples equal to the number of basis terms only. Secondly, the PCDD is utilized to develop a stochastic multi-scale modeling framework for composite structures since the response of composites is hugely influenced by the uncertainties existing at different scales such as micro-scale and macro-scale. Another framework for stochastic progressive failure analysis (PFA) of composites is also developed that allows performing global sensitivity analysis (GSA) to identify the relative importance of random inputs as a post-processing step. To further reduce the number of samples and make the stochastic problem more tractable, an adaptive L2-minimization algorithm that allows basis adaptivity along with sequential adaptive sampling is developed. Finally, an adaptive algorithm to obtain sparse PCE models with L1-minimization and sequential sampling is also proposed for high-dimensional problems. The L1-minimization is capable of solving the under-determined system when the number of samples is minuscule. It is also advantageous in terms of computational storage and memory because of its ability to provide a sparse solution. In general, the overarching goal of obtaining high-fidelity stochastic response models while maintaining a balance between accuracy and computational cost was successfully achieved by the novel algorithms developed in this dissertation. Furthermore, the invaluable information obtained with PCE for composite structures highlighted the benefits of its implementation in engineering problems.
Book Synopsis Statistical Methods for QTL Mapping by : Zehua Chen
Download or read book Statistical Methods for QTL Mapping written by Zehua Chen and published by CRC Press. This book was released on 2013-11-01 with total page 944 pages. Available in PDF, EPUB and Kindle. Book excerpt: While numerous advanced statistical approaches have recently been developed for quantitative trait loci (QTL) mapping, the methods are scattered throughout the literature. Statistical Methods for QTL Mapping brings together many recent statistical techniques that address the data complexity of QTL mapping. After introducing basic genetics topics and statistical principles, the author discusses the principles of quantitative genetics, general statistical issues of QTL mapping, commonly used one-dimensional QTL mapping approaches, and multiple interval mapping methods. He then explains how to use a feature selection approach to tackle a QTL mapping problem with dense markers. The book also provides comprehensive coverage of Bayesian models and MCMC algorithms and describes methods for multi-trait QTL mapping and eQTL mapping, including meta-trait methods and multivariate sequential procedures. This book emphasizes the modern statistical methodology for QTL mapping as well as the statistical issues that arise during this process. It gives the necessary biological background for statisticians without training in genetics and, likewise, covers statistical thinking and principles for geneticists. Written primarily for geneticists and statisticians specializing in QTL mapping, the book can also be used as a supplement in graduate courses or for self-study by PhD students working on QTL mapping projects.
Book Synopsis Framework for Analysis and Identification of Nonlinear Distributed Parameter Systems using Bayesian Uncertainty Quantification based on Generalized Polynomial Chaos by : Janya-anurak, Chettapong
Download or read book Framework for Analysis and Identification of Nonlinear Distributed Parameter Systems using Bayesian Uncertainty Quantification based on Generalized Polynomial Chaos written by Janya-anurak, Chettapong and published by KIT Scientific Publishing. This book was released on 2017-04-04 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this work, the Uncertainty Quantification (UQ) approaches combined systematically to analyze and identify systems. The generalized Polynomial Chaos (gPC) expansion is applied to reduce the computational effort. The framework using gPC based on Bayesian UQ proposed in this work is capable of analyzing the system systematically and reducing the disagreement between the model predictions and the measurements of the real processes to fulfill user defined performance criteria.
Book Synopsis Advances in Hydroinformatics by : Philippe Gourbesville
Download or read book Advances in Hydroinformatics written by Philippe Gourbesville and published by Springer Nature. This book was released on 2020-07-25 with total page 1056 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features a collection of extended papers based on presentations given at the SimHydro 2019 conference, held in Sophia Antipolis in June 2019 with the support of French Hydrotechnic Society (SHF), focusing on “Which models for extreme situations and crisis management?” Hydraulics and related disciplines are frequently applied in extreme situations that need to be understood accurately before implementing actions and defining appropriate mitigation measures. However, in such situations currently used models may be partly irrelevant due to factors like the new physical phenomena involved, the scale of the processes, and the hypothesis included in the different numerical tools. The availability of computational resources and new capacities like GPU offers modellers the opportunity to explore various approaches to provide information for decision-makers. At the same time, the topic of crisis management has sparked interest from stakeholders who need to share a common understanding of a situation. Hydroinfomatics tools can provide essential information in crises; however, the design and integration of models in decision-support systems require further development and the engagement of various communities, such as first responders. In this context, methodologies, guidelines and standards are more and more in demand in order to ensure that the systems developed are efficient and sustainable. Exploring both the limitations and performance of current models, this book presents the latest developments based on new numerical schemes, high-performance computing, multiphysics and multiscale methods, as well as better integration of field-scale model data. As such, it will appeal to practitioners, stakeholders, researchers and engineers active in this field.
