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Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics, 2023, the third volume of ten 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:
Introduction of Uncertainty Quantification
Uncertainty Quantification in Dynamics
Model Form Uncertainty and Selection incl. Round Robin Challenge
Sensor and Information Fusion
Virtual Sensing, Certification, and Real-Time Monitoring
Surrogate Modeling.
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978-87-438-0637-0 (9788743806370)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Roland Platz, Mechanical Engineering and Mechatronics, TH Deggendorf, Weißenburg i. Bay., Germany. Garrison Flynn, Los Alamos National Laboratory, Santa Fe, USA, Kyle Neal, Sandia National Laboratories, Albuquerque, USA. Scott Ouellette, Los Alamos National Laboratory, Santa Fe, USA.
Preface 1 Introducing a Round-Robin Challenge to Quantify Model Form Uncertainty in Passive and Active Vibration Isolation 2 An Uncertainty-Aware Measure of Model Calibration Flexibility 3 Quantifying Model Form Uncertainty in Spring-Mass-Damper Systems 4 Event Detection Using Floor Vibrations with a Probabilistic Framework 5 Advancing Model Credibility for Linked Multi-physics Surrogate Models Within a Coupled Digital Engineering Workflow of Nuclear Deterrence Systems 6 Estimating the Effect of Noise on Various ARMA-Based Damage-Sensitive Features 7 Bayesian Model Updating for System and Damage Identification of Bridges Using Synthetic and Field Test Data 8 Static and Dynamic Characterization of a Vibration Decoupling Element Based on a Metamaterial Structure 9 Incorporating Uncertainty in Mechanics-Based Synthetic Data Generation for Deep Learning -Based Structural Monitoring 10 Aerodynamic Load Estimation in Wind Turbine Drivetrains Using a Bayesian Data Assimilation Approach 11 Rail Roughness Profile Identification from Vibration Data via Mixing of Reduced-Order Train Models and Bayesian Filtering 12 Optimal Sensor Placement for Developing Reliable Digital Twins of Structures 13 DataSEA: Mature, Modern Data Management Enabling Sustainable Data Strategy 14 Optimal Sensor Placement Considering Operational Sensor Failures for Structural Health Monitoring Applications Mayank Chadha, Yichao Yang, Zhen Hu, and Michael D. Todd 15 Sequential Harmonic Component Tracking for Underdetermined Blind Source Separation in a Multitarget Tracking Framework 16 Physics-Based Corrosion Reliability Analysis of Miter Gates Using Multi-scale Simulations and Adaptive Surrogate Modeling 17 Adaptive Randomized Sketching for Dynamic Nonsmooth Optimization 18 Predicting Nonlinear Structural Dynamic Response of ODE Systems Using Constrained Gaussian Process Regression 19 Probabilistic Model Updating for Structural Health Monitoring Using a Likelihood-Free Bayesian Inference Method 20 Deep Learning for Image Segmentation and Subsurface Damage Detection Based on Full-Field Surface Strains 21 A Spatio-Temporal Model for Response and Distributed Wave Load Estimation on Offshore Wind Turbines 22 Identification of Axial Forces in Structural Rod Members Under Compression by a Modal Approach 23 Digital Twin Output Functions and Statistical Performance Metrics for Engineering Dynamic Applications 24 Next-Generation Non-contact Strain-Sensing Method Using Strain-Sensing Smart Skin (S4) for Static and Dynamic Measurement 25 Online Structural Model Updating for Ship Structures Considering Impact and Fatigue Damage 26 Detuning Optimization of Nonlinear Mistuned Bladed Disks Using a Probabilistic Learning Tool 27 Model-Based Inspection Planning for Large-Scale Structures Using Unmanned Aerial Vehicles 28 The Effect of Temporal Correlations on State Estimation Through Variational Bayesian Inference 29 On the Selection and Validation of Component Damage Models for Prediction of Damage-State Behavior of a Truss Bridge 30 Surrogate Aerodynamics Modeling Applied to Surrogate Structural Dynamical Systems 31 Footbridge Vibration Predictions and Interaction with Walking Load Model Decisions 32 Assembling Uncertainty Effects on the Dynamic Response of Nominally Identical Motorbike Components.