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Uncertainty Quantification in Computational Fluid Dynamics, Hester Bijl; Didier Lucor; Siddhartha Mishra; Chri


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Автор: Hester Bijl; Didier Lucor; Siddhartha Mishra; Chri
Название:  Uncertainty Quantification in Computational Fluid Dynamics
ISBN: 9783319346663
Издательство: Springer
Классификация:





ISBN-10: 3319346660
Обложка/Формат: Paperback
Страницы: 333
Вес: 0.50 кг.
Дата издания: 23.08.2016
Серия: Lecture Notes in Computational Science and Engineering
Язык: English
Размер: 234 x 156 x 19
Основная тема: Mathematics
Ссылка на Издательство: Link
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Поставляется из: Германии
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.


Large-Scale Inverse Problems and Quantification of Uncertainty

Автор: Biegler
Название: Large-Scale Inverse Problems and Quantification of Uncertainty
ISBN: 0470697431 ISBN-13(EAN): 9780470697436
Издательство: Wiley
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Цена: 17733.00 р.
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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.

Multiscale Modeling and Uncertainty Quantification of Materials and Structures

Автор: Manolis Papadrakakis; George Stefanou
Название: Multiscale Modeling and Uncertainty Quantification of Materials and Structures
ISBN: 3319063308 ISBN-13(EAN): 9783319063300
Издательство: Springer
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Цена: 26552.00 р.
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Uncertainty Quantification for Hyperbolic and Kinetic Equations

Автор: Shi Jin; Lorenzo Pareschi
Название: Uncertainty Quantification for Hyperbolic and Kinetic Equations
ISBN: 331967109X ISBN-13(EAN): 9783319671093
Издательство: Springer
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Цена: 13275.00 р.
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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.

Uncertainty Quantification in Computational Fluid Dynamics

Автор: Hester Bijl; Didier Lucor; Siddhartha Mishra; Chri
Название: Uncertainty Quantification in Computational Fluid Dynamics
ISBN: 3319008846 ISBN-13(EAN): 9783319008844
Издательство: Springer
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Цена: 13974.00 р.
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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.

Topics in Model Validation and Uncertainty Quantification, Volume 4

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
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Цена: 26120.00 р.
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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.

Introduction to Uncertainty Quantification

Автор: Sullivan, T.J.
Название: Introduction to Uncertainty Quantification
ISBN: 3319233947 ISBN-13(EAN): 9783319233949
Издательство: Springer
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Цена: 8384.00 р.
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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.

Spectral Methods for Uncertainty Quantification

Автор: Olivier Le Maitre; Omar M Knio
Название: Spectral Methods for Uncertainty Quantification
ISBN: 9048135192 ISBN-13(EAN): 9789048135196
Издательство: Springer
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Цена: 13275.00 р.
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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.

Topics in Model Validation and Uncertainty Quantification, Volume 5

Автор: Todd Simmermacher; Scott Cogan; Babak Moaveni; Cos
Название: Topics in Model Validation and Uncertainty Quantification, Volume 5
ISBN: 1489996044 ISBN-13(EAN): 9781489996046
Издательство: Springer
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Цена: 28732.00 р.
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Описание: Topics in Model Validation and Uncertainty Quantification, Volume : Proceedings of the 31st IMAC, A Conference and Exposition on Structural Dynamics, 2013, the fifth volume of seven from the Conference, brings together contributions to this important area of research and engineering.

Model Validation and Uncertainty Quantification, Volume 3

Автор: H. Sezer Atamturktur; Babak Moaveni; Costas Papadi
Название: Model Validation and Uncertainty Quantification, Volume 3
ISBN: 3319353101 ISBN-13(EAN): 9783319353104
Издательство: Springer
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Цена: 30039.00 р.
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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.

Model Validation and Uncertainty Quantification, Volume 3

Автор: H. Sezer Atamturktur; Babak Moaveni; Costas Papadi
Название: Model Validation and Uncertainty Quantification, Volume 3
ISBN: 3319386077 ISBN-13(EAN): 9783319386072
Издательство: Springer
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Цена: 23508.00 р.
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Описание:

Experimental Validation of the Dual Kalman Filter for Online and Real-time State and Input Estimation.- Comparison of Uncertainty in Passive and Active Vibration Isolation.- Observation DOF's Optimization for Structural Forces Identification.- Nonlinear Structural Finite Element Model Updating using Batch Bayesian Estimation.- A Comparative Assessment of Nonlinear State Estimation Methods for Structural Health Monitoring.- Hierarchical Bayesian Model Updating for Probabilistic Damage Identification.- Nonlinear Structural Finite Element Model Updating Using Stochastic Filtering.- Dispersion-corrected, Operationally Normalized Stabilization Diagrams for Robust Structural Identification.- Online Damage Detection in Plates via Vibration Measurements.- Advanced Modal Analysis of Geometry Consistent Experimental Space-Time Databases in Nonlinear Structural Dynamics.- Comparison of Damage Classification Between Recursive Bayesian Model Selection and Support Vector Machine.- A Comparative Study of Mode Decomposition Techniques to Relate Dynamic Modes Identified Using Parametric and Non-Parametric Methods.- Comparison of Different Approaches for the Model-based Design of Experiments.- Sensitivity Analysis for Test Resource Allocation.- Predictive Validation of Dispersion Models Using a Data Partitioning Methodology.- Experimental Variability on Modal Characteristics of an In-situ Pump.- SICODYN Research Project: Variability and Uncertainty in Structural Dynamics.- Variability of a Bolted Assembly Through an Experimental Modal Analysis.- Bottom-up Calibration of an Industrial Pump Model: Toward a Robust Calibration Paradigm.- Model Validation in Scientific Computing: Considering Robustness to Non-Probabilistic Uncertainty in the Input Parameters.- Robust-optimal Design Using Multifidelity Models.- Robust Modal Test Design Under Epistemic Model Uncertainties.- Clustered Parameters of Calibrated Models when Considering Both Fidelity and Robustness.- Uncertainty Propagation Combining Robust Condensation and Generalized Polynomial Chaos Expansion.- Robust Updating of Operational Boundary Conditions of a Grinding Machine.- Impact of Numerical Model Verification and Validation within FAA Certification.- The Role of Model V&V in the Defining of Specifications.- A Perspective on the Integration of Verification and Validation Into the Decision Making Process.- A MCMC Method for Bayesian System Identification From Large Data Sets.- A MCMC Method for Bayesian System Identification From Large Data Sets.- Reducing MCMC Computational Cost With a Two Layered Bayesian Approach.- Comparison of FRF Correlation Techniques.- Improved Estimation of Frequency Response Covariance.- Cross Orthogonality Check for Structures With Closely Spaced Modes.- Modeling of an Instrumented Building Subjected to Different Ground Motions.- Calibration and Cross-Validation of a Car Component Model Using Repeated Testing.- Structural Dynamics Model Calibration and Validation of a Rectangular Steel Plate Structure.- Human Activity Recognition Using Multinomial Logistic Regression.

Spectral Methods for Uncertainty Quantification

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.
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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.

Recurrence Quantification Analysis

Автор: Charles L. Webber, Jr.; Norbert Marwan
Название: Recurrence Quantification Analysis
ISBN: 3319071548 ISBN-13(EAN): 9783319071541
Издательство: Springer
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Цена: 13275.00 р.
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Описание: The analysis of recurrences in dynamical systems by using recurrence plots and their quantification is still an emerging field.


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