Uncertainty Quantification in Laminated Composites, Dey, Sudip
Автор: Sullivan, T.J. Название: Introduction to Uncertainty Quantification ISBN: 3319233947 ISBN-13(EAN): 9783319233949 Издательство: Springer Рейтинг: Цена: 55890.00 T 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: Chen Название: Stochastic Methods for Modeling and Predicting Complex Dynamical Systems ISBN: 3031222482 ISBN-13(EAN): 9783031222481 Издательство: Springer Рейтинг: Цена: 37260.00 T Наличие на складе: Нет в наличии. Описание: This book enables readers to understand, model, and predict complex dynamical systems using new methods with stochastic tools. The author presents a unique combination of qualitative and quantitative modeling skills, novel efficient computational methods, rigorous mathematical theory, as well as physical intuitions and thinking. An emphasis is placed on the balance between computational efficiency and modeling accuracy, providing readers with ideas to build useful models in practice. Successful modeling of complex systems requires a comprehensive use of qualitative and quantitative modeling approaches, novel efficient computational methods, physical intuitions and thinking, as well as rigorous mathematical theories. As such, mathematical tools for understanding, modeling, and predicting complex dynamical systems using various suitable stochastic tools are presented. Both theoretical and numerical approaches are included, allowing readers to choose suitable methods in different practical situations. The author provides practical examples and motivations when introducing various mathematical and stochastic tools and merges mathematics, statistics, information theory, computational science, and data science. In addition, the author discusses how to choose and apply suitable mathematical tools to several disciplines including pure and applied mathematics, physics, engineering, neural science, material science, climate and atmosphere, ocean science, and many others. Readers will not only learn detailed techniques for stochastic modeling and prediction, but will develop their intuition as well. Important topics in modeling and prediction including extreme events, high-dimensional systems, and multiscale features are discussed.
Автор: Olivier Le Maitre; Omar M Knio Название: Spectral Methods for Uncertainty Quantification ISBN: 9400731922 ISBN-13(EAN): 9789400731929 Издательство: Springer Рейтинг: Цена: 79190.00 T 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.
Автор: Jadamba Название: Uncertainty Quantification In Varia ISBN: 1138626325 ISBN-13(EAN): 9781138626324 Издательство: Taylor&Francis Рейтинг: Цена: 112290.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The primary objective of this book is to present a comprehensive treatment of uncertainty quantification in variational inequalities and some of its generalizations emerging from various network, economic, and engineering models. Some of the developed techniques also apply to machine learning, neural networks, and related fields.
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: 174130.00 T 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: Mircea Grigoriu Название: Stochastic Systems ISBN: 1447159489 ISBN-13(EAN): 9781447159483 Издательство: Springer Рейтинг: Цена: 200260.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book offers accurate, efficient methods for solving stochastic equations, with a focus on formulating equations that apply to problems in engineering and applied sciences. Numerous examples illustrate essential theoretical concepts, models and methods.
Автор: Todd Simmermacher; Scott Cogan; Babak Moaveni; Cos Название: Topics in Model Validation and Uncertainty Quantification, Volume 5 ISBN: 146146563X ISBN-13(EAN): 9781461465638 Издательство: Springer Рейтинг: Цена: 243800.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
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 Рейтинг: Цена: 191550.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
Автор: H. Sezer Atamturktur; Babak Moaveni; Costas Papadi Название: Model Validation and Uncertainty Quantification, Volume 3 ISBN: 3319386077 ISBN-13(EAN): 9783319386072 Издательство: Springer Рейтинг: Цена: 156720.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
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: 200260.00 T 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.
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