Model Validation and Uncertainty Quantification, Volume 3, Robert Barthorpe
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: Mcclarren, Ryan G. Название: Uncertainty quantification and predictive computational science ISBN: 3319995243 ISBN-13(EAN): 9783319995243 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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: Hester Bijl; Didier Lucor; Siddhartha Mishra; Chri Название: Uncertainty Quantification in Computational Fluid Dynamics ISBN: 3319008846 ISBN-13(EAN): 9783319008844 Издательство: Springer Рейтинг: Цена: 93160.00 T 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: 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: 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: 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.
Автор: Robert Barthorpe Название: Model Validation and Uncertainty Quantification, Volume 3 ISBN: 3030090787 ISBN-13(EAN): 9783030090784 Издательство: Springer Рейтинг: Цена: 214280.00 T Наличие на складе: Поставка под заказ. 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
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: 102480.00 T 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: Francesco Montomoli Название: Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines ISBN: 3030065529 ISBN-13(EAN): 9783030065522 Издательство: Springer Рейтинг: Цена: 130430.00 T Наличие на складе: Поставка под заказ. Описание: This book introduces design techniques developed to increase the safety of aircraft engines, and demonstrates how the application of stochastic methods can overcome problems in the accurate prediction of engine lift caused by manufacturing error. This in turn addresses the issue of achieving required safety margins when hampered by limits in current design and manufacturing methods. The authors show that avoiding the potential catastrophe generated by the failure of an aircraft engine relies on the prediction of the correct behaviour of microscopic imperfections. This book shows how to quantify the possibility of such failure, and that it is possible to design components that are inherently less risky and more reliable.This new, updated and significantly expanded edition gives an introduction to engine reliability and safety to contextualise this important issue, evaluates newly-proposed methods for uncertainty quantification as applied to jet engines.Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines will be of use to gas turbine manufacturers and designers as well as CFD practitioners, specialists and researchers. Graduate and final year undergraduate students in aerospace or mathematical engineering may also find it of interest.
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: Luis Chase Название: Uncertainty Quantification: Advances in Research and Applications ISBN: 1536148628 ISBN-13(EAN): 9781536148626 Издательство: Nova Science Рейтинг: Цена: 77080.00 T Наличие на складе: Невозможна поставка. Описание: 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 CIRCE 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 CIRCE 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.
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