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Topics in Model Validation and Uncertainty Quantification, Volume 5, Todd Simmermacher; Scott Cogan; Babak Moaveni; Cos


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Автор: Todd Simmermacher; Scott Cogan; Babak Moaveni; Cos
Название:  Topics in Model Validation and Uncertainty Quantification, Volume 5
ISBN: 9781489996046
Издательство: Springer
Классификация:





ISBN-10: 1489996044
Обложка/Формат: Paperback
Страницы: 264
Вес: 0.62 кг.
Дата издания: 08.02.2015
Серия: Conference Proceedings of the Society for Experimental Mechanics Series
Язык: English
Размер: 279 x 210 x 15
Основная тема: Engineering
Подзаголовок: Proceedings of the 31st IMAC, A Conference on Structural Dynamics, 2013
Ссылка на Издательство: Link
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Поставляется из: Германии
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.


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: 22796.00 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.

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: 26216.00 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.

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: 12196.00 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.

Uncertainty Quantification in Computational Fluid Dynamics

Автор: Hester Bijl; Didier Lucor; Siddhartha Mishra; Chri
Название: Uncertainty Quantification in Computational Fluid Dynamics
ISBN: 3319346660 ISBN-13(EAN): 9783319346663
Издательство: Springer
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Цена: 13415.00 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.


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