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Model Validation and Uncertainty Quantification, Volume 3

Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics 2023

  • Conference proceedings
  • © 2024

Overview

Editors:
  1. Roland Platz

    1. Mechanical Engineering and Mechatronics, TH Deggendorf, Weißenburg i. Bay., Germany

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    You can also search for this editor in PubMed   Google Scholar

  2. Garrison Flynn

    1. Los Alamos National Laboratory, Santa Fe, USA

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    You can also search for this editor in PubMed   Google Scholar

  3. Kyle Neal

    1. Sandia National Laboratories, Albuquerque, USA

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    You can also search for this editor in PubMed   Google Scholar

  4. Scott Ouellette

    1. Los Alamos National Laboratory, Santa Fe, USA

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Included in the following conference series:

Conference proceedings info: SEM 2023.

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Table of contents (33 papers)

  1. Front Matter

    Pages i-ix
    Download chapter PDF

  2. Introducing a Round-Robin Challenge to Quantify Model Form Uncertainty in Passive and Active Vibration Isolation

    • Roland Platz, Xinyue Xu, Sez Atamturktur
    Pages 1-4

  3. An Uncertainty-Aware Measure of Model Calibration Flexibility

    • Xinyue Xu, Yang Yu, Roland Platz, Sez Atamturktur
    Pages 5-8

  4. Quantifying Model Form Uncertainty in Spring-Mass-Damper Systems

    • Rileigh Bandy, Rebecca Morrison
    Pages 9-19

  5. Event Detection Using Floor Vibrations with a Probabilistic Framework

    • Yohanna MejiaCruz, Juan M. Caicedo, Zhaoshuo Jiang, Jean M. Franco
    Pages 21-26

  6. Advancing Model Credibility for Linked Multi-physics Surrogate Models Within a Coupled Digital Engineering Workflow of Nuclear Deterrence Systems

    • Sofie W. Schunk, Shane McMurray, Jake A. Gonzales
    Pages 27-32

  7. Estimating the Effect of Noise on Various ARMA-Based Damage-Sensitive Features

    • Emmett Lepp, Thomas Matarazzo
    Pages 33-39

  8. Bayesian Model Updating for System and Damage Identification of Bridges Using Synthetic and Field Test Data

    • Niloofar Malekghaini, Farid Ghahari, Hamed Ebrahimian, Vinayak Sachidanandam, Eric Ahlberg, Matthew Bowers et al.
    Pages 41-44

  9. Static and Dynamic Characterization of a Vibration Decoupling Element Based on a Metamaterial Structure

    • Alessandro Annessi, Valentina Zega, Paolo Chiariotti, Milena Martarelli, Paolo Castellini
    Pages 45-55

  10. Incorporating Uncertainty in Mechanics-Based Synthetic Data Generation for Deep Learning–Based Structural Monitoring

    • M. Cheraghzade, M. Roohi
    Pages 57-65

  11. Aerodynamic Load Estimation in Wind Turbine Drivetrains Using a Bayesian Data Assimilation Approach

    • Mohammad Valikhani, Vahid Jahangiri, Hamed Ebrahimian, Sauro Liberatore, Babak Moaveni, Eric Hines
    Pages 67-71

  12. Rail Roughness Profile Identification from Vibration Data via Mixing of Reduced-Order Train Models and Bayesian Filtering

    • Charikleia D. Stoura, Konstantinos E. Tatsis, Eleni N. Chatzi
    Pages 73-79

  13. Optimal Sensor Placement for Developing Reliable Digital Twins of Structures

    • Tulay Ercan, Costas Papadimitriou
    Pages 81-83

  14. DataSEA: Mature, Modern Data Management Enabling Sustainable Data Strategy

    • Justin Wu, Stephen C. Jackson
    Pages 85-88

  15. Optimal Sensor Placement Considering Operational Sensor Failures for Structural Health Monitoring Applications

    • Mayank Chadha, Yichao Yang, Zhen Hu, Michael D. Todd
    Pages 89-92

  16. Sequential Harmonic Component Tracking for Underdetermined Blind Source Separation in a Multitarget Tracking Framework

    • Romain Delabeye, Martin Ghienne, Jean-Luc Dion
    Pages 93-100

  17. Physics-Based Corrosion Reliability Analysis of Miter Gates Using Multi-scale Simulations and Adaptive Surrogate Modeling

    • Guofeng Qian, Zhen Hu, Michael D. Todd
    Pages 101-105

  18. Adaptive Randomized Sketching for Dynamic Nonsmooth Optimization

    • Robert J. Baraldi, Evelyn Herberg, Drew P. Kouri, Harbir Antil
    Pages 107-116

  19. Predicting Nonlinear Structural Dynamic Response of ODE Systems Using Constrained Gaussian Process Regression

    • Yishuang Wang, Yang Yu, Xinyue Xu, Sez Atamturktur
    Pages 117-122

  20. Probabilistic Model Updating for Structural Health Monitoring Using a Likelihood-Free Bayesian Inference Method

    • Jice Zeng, Michael D. Todd, Zhen Hu
    Pages 123-125
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Other volumes

  1. Advancement of Optical Methods and Fracture and Fatigue, Volume 3

  2. Dynamic Environments Testing, Volume 7

  3. Challenges in Mechanics of Biological Systems and Materials, Thermomechanics and Infrared Imaging, Time Dependent Materials and Residual Stress, Volume 2

  4. Model Validation and Uncertainty Quantification, Volume 3

  5. Dynamic Behavior of Materials, Volume 1

  6. Data Science in Engineering, Volume 10

  7. Dynamic Substructures, Volume 4

  8. Mechanics of Composite, Hybrid and Multifunctional Materials, Volume 5

  9. Sensors & Instrumentation and Aircraft/Aerospace Testing Techniques, Volume 8

  10. Nonlinear Structures & Systems, Volume 1

  11. Dynamics of Civil Structures, Volume 2

  12. Computer Vision & Laser Vibrometry, Volume 6

  13. Topics in Modal Analysis & Parameter Identification, Volume 9

  14. Additive and Advanced Manufacturing, Inverse Problem Methodologies and Machine Learning and Data Science, Volume 4

  15. Special Topics in Structural Dynamics & Experimental Techniques, Volume 5

Keywords

About this book

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

Editors and Affiliations

  • Mechanical Engineering and Mechatronics, TH Deggendorf, Weißenburg i. Bay., Germany

    Roland Platz

  • Los Alamos National Laboratory, Santa Fe, USA

    Garrison Flynn, Scott Ouellette

  • Sandia National Laboratories, Albuquerque, USA

    Kyle Neal

About the editors

Roland Platz–Deggendorf Institute of Technology, Weißenburg, Bavaria, Germany; Garrison Flynn–Los Alamos National Laboratory, Santa Fe, NM, USA; Kyle Neal–Sandia National Laboratories, Albuquerque, NM, USA; Scott Ouellette–Los Alamos National Laboratory, Santa Fe, NM, USA

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