Описание: Modeling and Tools.- Stick-slip oscillations in a stochastic multiphysics system.- Coupled lateral-torsional drill-string with uncertainties.- Processes.- Uncertainty quantification in subsea lifting operations.- Data Analysis and Identification.- Uncertainty Quantification in risk modeling: the case of customs supply chain.- Uncertainty analysis and estimation.- Uncertainty propagation in wind turbine blade load actions.- Optimization.- Uncertainty Quantification of Pareto Fronts.- Author Index.
Описание: Modeling and Tools.- Stick-slip oscillations in a stochastic multiphysics system.- Coupled lateral-torsional drill-string with uncertainties.- Processes.- Uncertainty quantification in subsea lifting operations.- Data Analysis and Identification.- Uncertainty Quantification in risk modeling: the case of customs supply chain.- Uncertainty analysis and estimation.- Uncertainty propagation in wind turbine blade load actions.- Optimization.- Uncertainty Quantification of Pareto Fronts.- Author Index.
Описание: This proceedings book covers a wide range of topics related to uncertainty analysis and its application in various fields of engineering and science. It explores uncertainties in numerical simulations for soil liquefaction potential, the toughness properties of construction materials, experimental tests on cyclic liquefaction potential, and the estimation of geotechnical engineering properties for aerogenerator foundation design. Additionally, the book delves into uncertainties in concrete compressive strength, bio-inspired shape optimization using isogeometric analysis, stochastic damping in rotordynamics, and the hygro-thermal properties of raw earth building materials. It also addresses dynamic analysis with uncertainties in structural parameters, reliability-based design optimization of steel frames, and calibration methods for models with dependent parameters. The book further explores mechanical property characterization in 3D printing, stochastic analysis in computational simulations, probability distribution in branching processes, data assimilation in ocean circulation modeling, uncertainty quantification in climate prediction, and applications of uncertainty quantification in decision problems and disaster management. This comprehensive collection provides insights into the challenges and solutions related to uncertainty in various scientific and engineering contexts.
Описание: Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 37th IMAC, A Conference and Exposition on Structural Dynamics, 2019, the third volume of eight 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:Inverse Problems and Uncertainty QuantificationControlling UncertaintyValidation of Models for Operating EnvironmentsModel Validation & Uncertainty Quantification: Decision MakingUncertainty Quantification in Structural DynamicsUncertainty in Early Stage DesignComputational and Uncertainty Quantification Tools
Описание: 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 ModelsUncertainty Propagation in Structural DynamicsPractical Applications of MVUQAdvances in Model Validation & Uncertainty Quantification: Model UpdatingModel Validation & Uncertainty Quantification: Industrial ApplicationsControlling UncertaintyUncertainty in Early Stage DesignModeling of Musical InstrumentsOverview of Model Validation and Uncertainty
Описание: 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.
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: 23508.00 р. 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: 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.
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: 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: 28732.00 р. 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: 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.
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