Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Download Uncertainty Quantification Of Simulation Codes Based On Experimental Data full books in PDF, epub, and Kindle. Read online Uncertainty Quantification Of Simulation Codes Based On Experimental Data ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
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 : 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 : 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 : Trent Michael Russi
Publisher :
ISBN 13 :
Total Pages : 352 pages
Book Rating : 4.:/5 (769 download)
Download or read book Uncertainty Quantification with Experimental Data and Complex System Models written by Trent Michael Russi and published by . This book was released on 2010 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation discusses uncertainty quantication as posed in the Data Collaboration framework. Data Collaboration is a methodology for combining experimental data and system models to induce constraints on a set of uncertain system parameters. The framework is summarized, including outlines of notation and techniques. The main techniques include polynomial optimization and surrogate modeling to ascertain the consistency of all data and models as well as propagate uncertainty in the form of a model prediction. One of the main methods of Data Collaboration is using techniques of nonconvex quadratically constrained quadratic programming to provide both lower and upper bounds on the various objectives. The Lagrangian dual of the NQCQP provides both an outer bound to the optimal objective as well as Lagrange multipliers. These multipliers act as sensitivity measures relaying the effects of changes to the parameter constraint bounds on the optimal objective. These multipliers are rewritten to provide the sensitivity to uncertainty in the response prediction with respect to uncertainty in the parameters and experimental data. It is often of interest to find a vector of parameters that is both feasible and representative of the current community work and knowledge. This is posed as the problem of finding the minimal number of parameters that must deviate from their literature value to achieve concurrence with all experimental data constraints. This problem is heuristically solved using the l1-norm in place of the cardinality function. A lower bound on the objective is provided through an NQCQP formulation. In order to use the NQCQP techniques, the system models need to have quadratic forms. When they do not have quadratic forms, surrogate models are fitted. Surrogate modeling can be difficult for complex models with large numbers of parameters and long simulation times because of the amount of evaluation-time required to make a good fit. New techniques are developed for searching for an active subspace of the parameters, and subsequently creating an experiment design on the active subspace that adheres to the original parameter constraints. The active subspace can have a dimension signicantly lower than the original parameter dimension thereby reducing the computational complexity of generating the surrogate model. The technique is demonstrated on several examples from combustion chemistry and biology. Several other applications of the Data Collaboration framework are presented. They are used to demonstrate the complexity of describing a high dimensional feasible set of parameter values as constrained by experimental data. Approximating the feasible set can lead to a simple description, but the predictive capability of such a set is significantly reduced compared to the actual feasible set. This is demonstrated on an example from combustion chemistry.
Author : H. Sezer Atamturktur
Publisher : Springer
ISBN 13 : 3319152246
Total Pages : 361 pages
Book Rating : 4.3/5 (191 download)
Download or read book Model Validation and Uncertainty Quantification, Volume 3 written by H. Sezer Atamturktur and published by Springer. This book was released on 2015-04-25 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model Validation and Uncertainty Quantification, Volume 3. Proceedings of the 33rd IMAC, A Conference and Exposition on Balancing Simulation and Testing, 2015, the third volume of ten from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Structural Dynamics, including papers on: Uncertainty Quantification & Model Validation Uncertainty Propagation in Structural Dynamics Bayesian & Markov Chain Monte Carlo Methods Practical Applications of MVUQ Advances in MVUQ & Model Updating
Author : Roland Platz
Publisher : Springer Nature
ISBN 13 : 3031370031
Total Pages : 208 pages
Book Rating : 4.0/5 (313 download)
Download or read book Model Validation and Uncertainty Quantification, Volume 3 written by Roland Platz and published by Springer Nature. This book was released on 2023-10-06 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics, 2023, the third volume of ten from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Model Validation and Uncertainty Quantification, including papers on: Introduction of Uncertainty Quantification Uncertainty Quantification in Dynamics Model Form Uncertainty and Selection incl. Round Robin Challenge Sensor and Information Fusion Virtual Sensing, Certification, and Real-Time Monitoring Surrogate Modeling
Author : Frank Graziani
Publisher : Springer Science & Business Media
ISBN 13 : 3540773622
Total Pages : 336 pages
Book Rating : 4.5/5 (47 download)
Download or read book Computational Methods in Transport: Verification and Validation written by Frank Graziani and published by Springer Science & Business Media. This book was released on 2008-08-09 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: The focus of this book deals with a cross cutting issue affecting all transport disciplines, whether it be photon, neutron, charged particle or neutrino transport. That is, verification and validation. In this book, we learn what the astrophysicist, atmospheric scientist, mathematician or nuclear engineer do to assess the accuracy of their code. What convergence studies, what error analysis, what problems do each field use to ascertain the accuracy of their transport simulations.
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 : 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 : Robert Barthorpe
Publisher : Springer
ISBN 13 : 3319747932
Total Pages : 303 pages
Book Rating : 4.3/5 (197 download)
Download or read book Model Validation and Uncertainty Quantification, Volume 3 written by Robert Barthorpe and published by Springer. This book was released on 2018-07-30 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 36th IMAC, A Conference and Exposition on Structural Dynamics, 2018, the third volume of nine from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Model Validation and Uncertainty Quantification, including papers on: Uncertainty Quantification in Material Models Uncertainty Propagation in Structural Dynamics Practical Applications of MVUQ Advances in Model Validation & Uncertainty Quantification: Model Updating Model Validation & Uncertainty Quantification: Industrial Applications Controlling Uncertainty Uncertainty in Early Stage Design Modeling of Musical Instruments Overview of Model Validation and Uncertainty
Author : Roger Ghanem
Publisher : Springer
ISBN 13 : 9783319123844
Total Pages : 0 pages
Book Rating : 4.1/5 (238 download)
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.
Author : Hugh W. Coleman
Publisher : Wiley-Interscience
ISBN 13 :
Total Pages : 304 pages
Book Rating : 4.3/5 (91 download)
Download or read book Experimentation and Uncertainty Analysis for Engineers written by Hugh W. Coleman and published by Wiley-Interscience. This book was released on 1999 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now, in the only manual available with direct applications to the design and analysis of engineering experiments, respected authors Hugh Coleman and Glenn Steele have thoroughly updated their bestselling title to include the new methodologies being used by the United States and International standards committee groups.
Download or read book Uncertainty Quantification Tools for Multiphase Gas-Solid Flow Simulations Using Mfix written by and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational fluid dynamics (CFD) has been widely studied and used in the scientific community and in the industry. Various models were proposed to solve problems in different areas. However, all models deviate from reality. Uncertainty quantification (UQ) process evaluates the overall uncertainties associated with the prediction of quantities of interest. In particular it studies the propagation of input uncertainties to the outputs of the models so that confidence intervals can be provided for the simulation results. In the present work, a non-intrusive quadrature-based uncertainty quantification (QBUQ) approach is proposed. The probability distribution function (PDF) of the system response can be then reconstructed using extended quadrature method of moments (EQMOM) and extended conditional quadrature method of moments (ECQMOM). The report first explains the theory of QBUQ approach, including methods to generate samples for problems with single or multiple uncertain input parameters, low order statistics, and required number of samples. Then methods for univariate PDF reconstruction (EQMOM) and multivariate PDF reconstruction (ECQMOM) are explained. The implementation of QBUQ approach into the open-source CFD code MFIX is discussed next. At last, QBUQ approach is demonstrated in several applications. The method is first applied to two examples: a developing flow in a channel with uncertain viscosity, and an oblique shock problem with uncertain upstream Mach number. The error in the prediction of the moment response is studied as a function of the number of samples, and the accuracy of the moments required to reconstruct the PDF of the system response is discussed. The QBUQ approach is then demonstrated by considering a bubbling fluidized bed as example application. The mean particle size is assumed to be the uncertain input parameter. The system is simulated with a standard two-fluid model with kinetic theory closures for the particulate phase implemented into MFIX. The effect of uncertainty on the disperse-phase volume fraction, on the phase velocities and on the pressure drop inside the fluidized bed are examined, and the reconstructed PDFs are provided for the three quantities studied. Then the approach is applied to a bubbling fluidized bed with two uncertain parameters, particle-particle and particle-wall restitution coefficients. Contour plots of the mean and standard deviation of solid volume fraction, solid phase velocities and gas pressure are provided. The PDFs of the response are reconstructed using EQMOM with appropriate kernel density functions. The simulation results are compared to experimental data provided by the 2013 NETL small-scale challenge problem. Lastly, the proposed procedure is demonstrated by considering a riser of a circulating fluidized bed as an example application. The mean particle size is considered to be the uncertain input parameter. Contour plots of the mean and standard deviation of solid volume fraction, solid phase velocities, and granular temperature are provided. Mean values and confidence intervals of the quantities of interest are compared to the experiment results. The univariate and bivariate PDF reconstructions of the system response are performed using EQMOM and ECQMOM.
Author : Marina L. Gavrilova
Publisher : Springer Science & Business Media
ISBN 13 : 3540340750
Total Pages : 1268 pages
Book Rating : 4.5/5 (43 download)
Download or read book Computational Science and Its Applications - ICCSA 2006 written by Marina L. Gavrilova and published by Springer Science & Business Media. This book was released on 2006 with total page 1268 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Subrata Chakraborty
Publisher : Springer Science & Business Media
ISBN 13 : 8132207572
Total Pages : 1322 pages
Book Rating : 4.1/5 (322 download)
Download or read book Proceedings of the International Symposium on Engineering under Uncertainty: Safety Assessment and Management (ISEUSAM - 2012) written by Subrata Chakraborty and published by Springer Science & Business Media. This book was released on 2013-03-12 with total page 1322 pages. Available in PDF, EPUB and Kindle. Book excerpt: International Symposium on Engineering under Uncertainty: Safety Assessment and Management (ISEUSAM - 2012) is organized by Bengal Engineering and Science University, India during the first week of January 2012 at Kolkata. The primary aim of ISEUSAM 2012 is to provide a platform to facilitate the discussion for a better understanding and management of uncertainty and risk, encompassing various aspects of safety and reliability of engineering systems. The conference received an overwhelming response from national as well as international scholars, experts and delegates from different parts of the world. Papers received from authors of several countries including Australia, Canada, China, Germany, Italy, UAE, UK and USA, besides India. More than two hundred authors have shown their interest in the symposium. The Proceedings presents ninety two high quality papers which address issues of uncertainty encompassing various fields of engineering, i.e. uncertainty analysis and modelling, structural reliability, geotechnical engineering, vibration control, earthquake engineering, environmental engineering, stochastic dynamics, transportation system, system identification and damage assessment, and infrastructure engineering.
Author : National Research Council
Publisher : National Academies Press
ISBN 13 : 0309256348
Total Pages : 144 pages
Book Rating : 4.3/5 (92 download)
Download or read book Assessing the Reliability of Complex Models written by National Research Council and published by National Academies Press. This book was released on 2012-07-26 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in computing hardware and algorithms have dramatically improved the ability to simulate complex processes computationally. Today's simulation capabilities offer the prospect of addressing questions that in the past could be addressed only by resource-intensive experimentation, if at all. Assessing the Reliability of Complex Models recognizes the ubiquity of uncertainty in computational estimates of reality and the necessity for its quantification. As computational science and engineering have matured, the process of quantifying or bounding uncertainties in a computational estimate of a physical quality of interest has evolved into a small set of interdependent tasks: verification, validation, and uncertainty of quantification (VVUQ). In recognition of the increasing importance of computational simulation and the increasing need to assess uncertainties in computational results, the National Research Council was asked to study the mathematical foundations of VVUQ and to recommend steps that will ultimately lead to improved processes. Assessing the Reliability of Complex Models discusses changes in education of professionals and dissemination of information that should enhance the ability of future VVUQ practitioners to improve and properly apply VVUQ methodologies to difficult problems, enhance the ability of VVUQ customers to understand VVUQ results and use them to make informed decisions, and enhance the ability of all VVUQ stakeholders to communicate with each other. This report is an essential resource for all decision and policy makers in the field, students, stakeholders, UQ experts, and VVUQ educators and practitioners.
