Quantification of Uncertainty: Improving Efficiency and Technology: Quiet Selected Contributions, D`Elia Marta, Gunzburger Max, Rozza Gianluigi
Автор: D`Elia Marta, Gunzburger Max, Rozza Gianluigi Название: Quantification of Uncertainty: Improving Efficiency and Technology: Quiet Selected Contributions ISBN: 3030487202 ISBN-13(EAN): 9783030487201 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book explores four guiding themes - reduced order modelling, high dimensional problems, efficient algorithms, and applications - by reviewing recent algorithmic and mathematical advances and the development of new research directions for uncertainty quantification in the context of partial differential equations with random inputs.
Автор: Wang, Yan Название: Uncertainty Quantification In Multiscale Materials Modeling ISBN: 0081029411 ISBN-13(EAN): 9780081029411 Издательство: Elsevier Science Рейтинг: Цена: 314410.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Uncertainty Quantification in Multiscale Materials Modeling provides a complete overview of uncertainty quantification (UQ) in computational materials science. It provides practical tools and methods along with examples of their application to problems in materials modeling. UQ methods are applied to various multiscale models ranging from the nanoscale to macroscale. This book presents a thorough synthesis of the state-of-the-art in UQ methods for materials modeling, including Bayesian inference, surrogate modeling, random fields, interval analysis, and sensitivity analysis, providing insight into the unique characteristics of models framed at each scale, as well as common issues in modeling across scales.
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: 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: 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: Barthorpe Robert, Platz Roland, Lopez Israel Название: Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 35th Imac, a Conference and Exposition on Structural Dynamics 2017 ISBN: 3319855034 ISBN-13(EAN): 9783319855035 Издательство: Springer Рейтинг: Цена: 186330.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Chapter1. Lateral vibration attenuation of a beam with piezo-elastic supports subject to varying axial tensile and compressive loads.- Chapter2. Correlation of Non-contact Full-Field Dynamic Strain Measurements with Finite Element Predictions.- Chapter3. Nonlinear Prediction Surfaces for the Estimation of Structural Response of Naval Vessels.- Chapter4. A Case Study in Predictive Modeling Beyond the Calibration Domain.- Chapter5. A Brief Overview of Code and Solution Verification in Numerical Simulation.- Chapter6. Robust Optimization of Shunted Piezoelectric Transducers for Vibration Attenuation Considering Dierent Values of Electromechanical Coupling.- Chapter7. Parameter estimation and uncertainty quantification of mass loaded bushings using model updating.- Chapter8. Vibroacoustic modelling of piano soundboards through analytical approaches in frequency and time domains.- Chapter9. Combined Experimental and Numerical Investigation of Vibro-mechanical Properties of Varnished Wood for Stringed Instruments.- Chapter10. Towards robust sustainable system design - An engineering inspired approach.- Chapter11. Linear Parameter-Varying (LPV) buckling control of an imperfect beam-column subject to time-varying axial loads.- Chapter12. Quantification and Evaluation of Uncertainty in the MathematicalModelling of a Suspension Strut using Bayesian Model Validation Approach.- Chapter13. Unsupervised Novelty Detection Techniques for Structural Damage Localization: A Comparative Study.- Chapter14. Global load path adaption in a simple kinematic load-bearing structure to compensate uncertainty of misalignment due to changing stiffness conditions of the structure's supports.- Chapter15. Assessment of Uncertainty Quantification of Bolted Joint Performance.- Chapter16. Sensitivity Analysis and Bayesian Calibration for 2014 Sandia Verification and Validation Challenge Problem.- Chapter17. Non-probabilistic uncertainty evaluation in the concept phase for airplane landing gear design.- Chapter18. Modular Analysis of Complex Systems with Numerically Described Multidimensional Probability Distributions.- Chapter19. Methods for Component Mode Synthesis Model Generation for UncertaintyQuantification.- Chapter20. Parameterization of Large Variability using the Hyper-Dual Meta-Model.- Chapter21. Similitude Analysis of the Frequency Response Function for Scaled Structures.- Chapter22. MPUQ-b: Bootstrapping based Modal Parameter Uncertainty Quantification - Fundamental Principles.- Chapter23. MPUQ-b: Bootstrapping based Modal Parameter Uncertainty Quantification - Methodology and Application.- Chapter24. Evaluation of Truck-Induced Vibrations for a Multi-Beam Highway Bridge.- Chapter25. Innovations and Info-Gaps: An Overview.- Chapter26. Bayesian optimal experimental design using asymptotic approximations.- Chapter27. Surrogate-Based Approach to Calculate the Bayes Factor.- Chapter28. Vibrational Model Updating of Electric Motor Stator for Vibration and Noise Prediction.- Chapter29. A Comparison of Computer-Vision-Based Structural Dynamics Characterizations.- Chapter30. Sequential Gauss-Newton MCMC Algorithm for High-Dimensional Bayesian Model Updating.- Chapter31. Model Calibration with Big Data.- Chapter32. Towards Reducing Prediction Uncertainties in Human Spine Finite Element Response: In-vivo Characterization of Growth and Spine Morphology.- Chapter33. Structural Damage Detection Using Convolutional Neural Networks.- Chapter34. Experimental model validation of an aero-engine casing assembly.- Chapter35. Damage Detection in Railway Bridges under Moving Train Load.- Chapter36. Multi-Fidelity Calibration of Input-Dependent Model Parameters.- Chapter37. Empirically Improving Model Adequacy in Scientific Computing.- Chapter38. Mixed geometrical-material sensitivity analysis for the study of complex phenomena in musical acoustics.- Chapter39. Experimental Examples for Identification of Structural Systems Using Degree of Freedom-Bas
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: Shi Jin; Lorenzo Pareschi Название: Uncertainty Quantification for Hyperbolic and Kinetic Equations ISBN: 3030097900 ISBN-13(EAN): 9783030097905 Издательство: Springer Рейтинг: Цена: 102480.00 T Наличие на складе: 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.
Автор: Sullivan, T.j. Название: Introduction to uncertainty quantification ISBN: 3319794787 ISBN-13(EAN): 9783319794785 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.
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: Robert Barthorpe Название: Model Validation and Uncertainty Quantification, Volume 3 ISBN: 3030120740 ISBN-13(EAN): 9783030120740 Издательство: Springer Рейтинг: Цена: 186330.00 T Наличие на складе: Поставка под заказ. 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
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.
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