During the last decade, research in Uncertainty Quantification (UC) has received a tremendous boost, in fluid engineering and coupled structural-fluids systems. New algorithms and adaptive variants have also emerged.
This timely compendium overviews in detail the current state of the art of the field, including advances in structural engineering, along with the recent focus on fluids and coupled systems. Such a strong compilation of these vibrant research areas will certainly be an inspirational reference material for the scientific community.
Автор: T. Simmermacher; Scott Cogan; L.G. Horta; R. Barth Название: Topics in Model Validation and Uncertainty Quantification, Volume 4 ISBN: 1489998667 ISBN-13(EAN): 9781489998668 Издательство: Springer Рейтинг: Цена: 26120.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Topics in Model Validation and Uncertainty Quantification, Volume 4, Proceedings of the 30th IMAC, A Conference and Exposition on Structural Dynamics, 2012, the fourth volume of six from the Conference, brings together 19 contributions to this important area of research and engineering.
Автор: Hester Bijl; Didier Lucor; Siddhartha Mishra; Chri Название: Uncertainty Quantification in Computational Fluid Dynamics ISBN: 3319008846 ISBN-13(EAN): 9783319008844 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: It collects seven original review articles that cover improved versions of the Monte Carlo method (the so-called multi-level Monte Carlo method (MLMC)), moment-based stochastic Galerkin methods and modified versions of the stochastic collocation methods that use adaptive stencil selection of the ENO-WENO type in both physical and stochastic space.
Автор: Sullivan, T.J. Название: Introduction to Uncertainty Quantification ISBN: 3319233947 ISBN-13(EAN): 9783319233949 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This text provides a framework in which the main objectives of the field of uncertainty quantification (UQ) are defined and an overview of the range of mathematical methods by which they can be achieved. Complete with exercises throughout, the book will equip readers with both theoretical understanding and practical experience of the key mathematical and algorithmic tools underlying the treatment of uncertainty in modern applied mathematics. Students and readers alike are encouraged to apply the mathematical methods discussed in this book to their own favorite problems to understand their strengths and weaknesses, also making the text suitable for a self-study.
Uncertainty quantification is a topic of increasing practical importance at the intersection of applied mathematics, statistics, computation and numerous application areas in science and engineering. This text is designed as an introduction to UQ for senior undergraduate and graduate students with a mathematical or statistical background and also for researchers from the mathematical sciences or from applications areas who are interested in the field.
Автор: Hester Bijl; Didier Lucor; Siddhartha Mishra; Chri Название: Uncertainty Quantification in Computational Fluid Dynamics ISBN: 3319346660 ISBN-13(EAN): 9783319346663 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: It collects seven original review articles that cover improved versions of the Monte Carlo method (the so-called multi-level Monte Carlo method (MLMC)), moment-based stochastic Galerkin methods and modified versions of the stochastic collocation methods that use adaptive stencil selection of the ENO-WENO type in both physical and stochastic space.
Автор: Shi Jin; Lorenzo Pareschi Название: Uncertainty Quantification for Hyperbolic and Kinetic Equations ISBN: 331967109X ISBN-13(EAN): 9783319671093 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book explores recent advances in uncertainty quantification for hyperbolic, kinetic, and related problems. The contributions address a range of different aspects, including: polynomial chaos expansions, perturbation methods, multi-level Monte Carlo methods, importance sampling, and moment methods.
Автор: H. Sezer Atamturktur; Babak Moaveni; Costas Papadi Название: Model Validation and Uncertainty Quantification, Volume 3 ISBN: 3319353101 ISBN-13(EAN): 9783319353104 Издательство: Springer Рейтинг: Цена: 30039.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Calibration of System Parameters Under Model Uncertainty.- On the Aggregation and Extrapolation of Uncertainty From Component to System Level Models.- Validation of Strongly Coupled Models: A Framework for Resource Allocation.- Fatigue Monitoring in Metallic Structures Using Vibration Measurements.- Uncertainty Propagation in Experimental Modal Analysis.- Quantification of Prediction Bounds Caused by Model Form Uncertainty.- Composite Fuselage Impact Testing and Simulation: A Model Calibration Exercise.- Noise Sensitivity Evaluation of Autoregressive Features Extracted From Structure Vibration.- Uncertainty Quantification and Integration in Multi-level Problems.- Reliability Quantification of High-speed Naval Vessels Based on SHM Data.- Structural Identification Using Response Measurements Under Base Excitation.- Bayesian FE Model Updating in the Presence of Modeling Errors.- Maintenance Planning Under Uncertainties Using a Continuous-state POMDP Framework.- Achieving Robust Design through Statistical Effect Screening.- Automated Modal Parameter Extraction and Statistical Analysis of the New Carquinez Bridge Response to Ambient Excitations.- Evaluation of a Time Reversal Method with Dynamic Time Warping matching function for human Fall Detection Using Structural Vibrations.- Uncertainty Quantification of Identified Modal Parameters Using the Fisher Information Criterion.- Excitation Related Uncertainty in Ambient Vibration Testing of Bridges.- Experiment-based Validation and Uncertainty Quantification of Coupled Multi-scale Plasticity Models.- Model Calibration and Uncertainty Quantification of A600 Blades.- Validation Assessment for Joint Problem Using an Energy Dissipation Model.- A Bayesian Damage Prognosis Approach Applied to Bearing Failure.- Sensitivity Analysis of Beams Controlled by Shunted Piezoelectric Transducers.- A Principal Component Analysis (PCA) Decomposition Based Validation Metric for use with Full Field Measurement Situations.- FEM Calibration With FRF Damping Equalization.- Evaluating Initial Model for Dynamic Model Updating: Criteria and Application.- Evaluating Convergence of Reduced Order Models Using Nonlinear Normal Modes.- Approximate Bayesian Computation for Finite Element Model Updating.- An Efficient Method for the Quantification of the Frequency Domain Statistical Properties of Short Response Time Series of Dynamic Systems.- Quantifying Uncertainty in Modal Parameters Estimated Using Higher Order Time Domain Algorithms.- Detection of Stress-stiffening Effect on Automotive Components.- Approach to Evaluate Uncertainty in Passive and Active Vibration Reduction.- Project-oriented Validation on a Cantilever Beam Under Vibration Active Control.- Inferring structural variability using modal analysis in a Bayesian framework.- Including SN-Curve Uncertainty in Fatigue Reliability Analyses of Wind Turbines.- Robust Design of Notching Profile under Epistemic Model Uncertainties.- Optimal Selection of Calibration and Validation Test Samples Under Uncertainty.- Uncertainty Quantification in Experimental Structural Dynamics Identification of Composite Material Structures.- Analysis of Numerical Errors in Strongly Coupled Numerical Models.- Robust Expansion of Experimental Mode Shapes Under Epistemic Uncertainties.
Описание: This book focuses on computational methods for large-scale statistical inverse problems and provides an introduction to statistical Bayesian and frequentist methodologies. Recent research advances for approximation methods are discussed, along with Kalman filtering methods and optimization-based approaches to solving inverse problems.
Автор: Olivier Le Maitre; Omar M Knio Название: Spectral Methods for Uncertainty Quantification ISBN: 9400731922 ISBN-13(EAN): 9789400731929 Издательство: Springer Рейтинг: Цена: 11878.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents applications of spectral methods to problems of uncertainty propagation and quantification in model-based computations, focusing on the computational and algorithmic features of these methods most useful in dealing with models based on partial differential equations, in particular models arising in simulations of fluid flows.
