Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Download Uncertainty Quantification For Modular Co Simulation full books in PDF, epub, and Kindle. Read online Uncertainty Quantification For Modular Co Simulation ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Author : Cornelius Steinbrink
Publisher :
ISBN 13 : 9783955990466
Total Pages : 212 pages
Book Rating : 4.9/5 (94 download)
Download or read book Uncertainty Quantification for Modular Co-simulation written by Cornelius Steinbrink and published by . This book was released on 2017 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Kai Gausling
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (113 download)
Download or read book Co-Simulation and Uncertainty Quantification for Field/Circuit Coupled Problems written by Kai Gausling and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Ryan G. McClarren
Publisher : Springer
ISBN 13 : 3319995251
Total Pages : 349 pages
Book Rating : 4.3/5 (199 download)
Download or read book Uncertainty Quantification and Predictive Computational Science written by Ryan G. McClarren and published by Springer. This book was released on 2018-11-23 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Yan Wang
Publisher : Woodhead Publishing Limited
ISBN 13 : 0081029411
Total Pages : 604 pages
Book Rating : 4.0/5 (81 download)
Download or read book Uncertainty Quantification in Multiscale Materials Modeling written by Yan Wang and published by Woodhead Publishing Limited. This book was released on 2020-03-12 with total page 604 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Makarand Vilas Datar
Publisher :
ISBN 13 :
Total Pages : 274 pages
Book Rating : 4.:/5 (891 download)
Download or read book Uncertainty Quantification in Ground Vehicle Dynamics Through High Fidelity Co-simulation written by Makarand Vilas Datar and published by . This book was released on 2009 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Vladimír Mařík
Publisher : Springer
ISBN 13 : 3319646354
Total Pages : 276 pages
Book Rating : 4.3/5 (196 download)
Download or read book Industrial Applications of Holonic and Multi-Agent Systems written by Vladimír Mařík and published by Springer. This book was released on 2017-08-11 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th International Conference on Industrial Applications of Holonic and Multi-Agent Systems, HoloMAS 2017, held in Lyon, France, in August 2017. The 19 revised full papers presented were carefully reviewed and selected from 27 submissions. The papers are organized in the following topical sections: scheduling; knowledge engineering; modeling, simulation and reconfiguration; energy systems;and MAS in various areas.
Author : Anne Remke
Publisher : Springer
ISBN 13 : 3319315595
Total Pages : 221 pages
Book Rating : 4.3/5 (193 download)
Download or read book Measurement, Modelling and Evaluation of Dependable Computer and Communication Systems written by Anne Remke and published by Springer. This book was released on 2016-03-24 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 18th International GI/ITG Conference on Measurement, Modelling and Evaluation of Computing Systems and Dependability and Fault Tolerance, MMB & DFT 2016, held in Münster, Germany, in April 2016. The 12 full papers and 3 short papers included in this volume were carefully reviewed and selected from 23 submissions. The papers deal with the fields of performance evaluation, dependability, and fault-tolerance of computer and communication systems. A relatively new topic of smart grids is also covered.
Author :
Publisher :
ISBN 13 :
Total Pages : 276 pages
Book Rating : 4.:/5 (255 download)
Download or read book Uncertainty Quantification in Simulation Science written by and published by . This book was released on 2006 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Ralph C. Smith
Publisher : SIAM
ISBN 13 : 1611977843
Total Pages : 571 pages
Book Rating : 4.6/5 (119 download)
Download or read book Uncertainty Quantification written by Ralph C. Smith and published by SIAM. This book was released on 2024-09-13 with total page 571 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty quantification serves a fundamental role when establishing the predictive capabilities of simulation models. This book provides a comprehensive and unified treatment of the mathematical, statistical, and computational theory and methods employed to quantify uncertainties associated with models from a wide range of applications. Expanded and reorganized, the second edition includes advances in the field and provides a comprehensive sensitivity analysis and uncertainty quantification framework for models from science and engineering. It contains new chapters on random field representations, observation models, parameter identifiability and influence, active subspace analysis, and statistical surrogate models, and a completely revised chapter on local sensitivity analysis. Other updates to the second edition are the inclusion of over 100 exercises and many new examples — several of which include data — and UQ Crimes listed throughout the text to identify common misconceptions and guide readers entering the field. Uncertainty Quantification: Theory, Implementation, and Applications, Second Edition is intended for advanced undergraduate and graduate students as well as researchers in mathematics, statistics, engineering, physical and biological sciences, operations research, and computer science. Readers are assumed to have a basic knowledge of probability, linear algebra, differential equations, and introductory numerical analysis. The book can be used as a primary text for a one-semester course on sensitivity analysis and uncertainty quantification or as a supplementary text for courses on surrogate and reduced-order model construction and parameter identifiability analysis.
Author : Jan Peter Hessling
Publisher : BoD – Books on Demand
ISBN 13 : 9535132792
Total Pages : 228 pages
Book Rating : 4.5/5 (351 download)
Download or read book Uncertainty Quantification and Model Calibration written by Jan Peter Hessling and published by BoD – Books on Demand. This book was released on 2017-07-05 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty quantification may appear daunting for practitioners due to its inherent complexity but can be intriguing and rewarding for anyone with mathematical ambitions and genuine concern for modeling quality. Uncertainty quantification is what remains to be done when too much credibility has been invested in deterministic analyses and unwarranted assumptions. Model calibration describes the inverse operation targeting optimal prediction and refers to inference of best uncertain model estimates from experimental calibration data. The limited applicability of most state-of-the-art approaches to many of the large and complex calculations made today makes uncertainty quantification and model calibration major topics open for debate, with rapidly growing interest from both science and technology, addressing subtle questions such as credible predictions of climate heating.
Author :
Publisher :
ISBN 13 :
Total Pages : 64 pages
Book Rating : 4.:/5 (951 download)
Download or read book Module-based Hybrid Uncertainty Quantification for Multi-physics Applications written by and published by . This book was released on 2013 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this project we proposed to develop an innovative uncertainty quantification methodology that captures the best of the two competing approaches in UQ, namely, intrusive and non-intrusive approaches. The idea is to develop the mathematics and the associated computational framework and algorithms to facilitate the use of intrusive or non-intrusive UQ methods in different modules of a multi-physics multi-module simulation model in a way that physics code developers for different modules are shielded (as much as possible) from the chores of accounting for the uncertain ties introduced by the other modules. As the result of our research and development, we have produced a number of publications, conference presentations, and a software product.
Author : K. M. Hanson
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (11 download)
Download or read book Uncertainty Quantification of Simulation Codes Based on Experimental Data written by K. M. Hanson and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Fabian Franzelin
Publisher :
ISBN 13 : 9783843936965
Total Pages : pages
Book Rating : 4.9/5 (369 download)
Download or read book Data-Driven Uncertainty Quantification for Large-Scale Simulations written by Fabian Franzelin and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : T. J. Sullivan
Publisher :
ISBN 13 : 9783919233943
Total Pages : 342 pages
Book Rating : 4.2/5 (339 download)
Download or read book Introduction to uncertainty quantification written by T. J. Sullivan and published by . This book was released on 2015 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Luis Chase
Publisher : Nova Science Publishers
ISBN 13 : 9781536148626
Total Pages : 0 pages
Book Rating : 4.1/5 (486 download)
Download or read book Uncertainty Quantification written by Luis Chase and published by Nova Science Publishers. This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent times, polynomial chaos expansion has emerged as a dominant technique to determine the response uncertainties of a system by propagating the uncertainties of the inputs. In this regard, the opening chapter of Uncertainty Quantification: Advances in Research and Applications, an intrusive approach called Galerkin Projection as well as non-intrusive approaches (such as pseudo-spectral projection and linear regression) are discussed.Next, the authors introduce a new methodology to determine the uncertainties of input parameters using CIRCÉ software to overcome the reliance on expert judgment. The goal is to determinate and evaluate the uncertainty bounds for physical models related to reflood model of MARS-KS code Vessel module (coupled with COBRA-TF) using both CIRCÉ and the experimental data of FEBA.Lastly, uncertainties related to rheological model parameters of skeletal muscles are modeled and analyzed, and available data are acquired and fused for hyperelastic constitutive model parameters with Neo-Hookean and Mooney-Rivlin formulations.
Author : Huajie Qian
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (122 download)
Download or read book Uncertainty Quantification in Data-Driven Simulation and Optimization written by Huajie Qian and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We demonstrate how our obtained solutions satisfy statistical feasibility guarantees with light dimension dependence, and how they are asymptotically optimal and thus regarded as the least conservative with respect to the considered reformulation classes.
Author : Flavio Canavero
Publisher : Springer
ISBN 13 : 9783030048693
Total Pages : 0 pages
Book Rating : 4.0/5 (486 download)
Download or read book Uncertainty Modeling for Engineering Applications written by Flavio Canavero and published by Springer. This book was released on 2019-01-16 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of state-of-the-art uncertainty quantification (UQ) methodologies and applications, and covers a wide range of current research, future challenges and applications in various domains, such as aerospace and mechanical applications, structure health and seismic hazard, electromagnetic energy (its impact on systems and humans) and global environmental state change. Written by leading international experts from different fields, the book demonstrates the unifying property of UQ theme that can be profitably adopted to solve problems of different domains. The collection in one place of different methodologies for different applications has the great value of stimulating the cross-fertilization and alleviate the language barrier among areas sharing a common background of mathematical modeling for problem solution. The book is designed for researchers, professionals and graduate students interested in quantitatively assessing the effects of uncertainties in their fields of application. The contents build upon the workshop “Uncertainty Modeling for Engineering Applications” (UMEMA 2017), held in Torino, Italy in November 2017.
