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Data Science in Engineering, Volume 10

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

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Ramin Madarshahian

    1. Kount, an Equifax company, Boise, USA

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. François Hemez

    1. Kount, an Equifax company, Oakland, USA

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

Included in the following conference series:

Conference proceedings info: SEM 2023.

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Table of contents (24 papers)

  1. Front Matter

    Pages i-viii
    Download chapter PDF

  2. Output-Only Versus Direct Input-Output Structural Condition Monitoring Methods

    • M. Mousavi, A. H. Gandomi
    Pages 1-3

  3. Construction Noise Cancellation with Feedback Active Control Using Machine Learning

    • Alireza Mostafavi, Young-Jin Cha
    Pages 5-10

  4. Simulation Error Influence on Damage Identification Classifiers Trained by Numerical Data

    • P. Seventekidis, D. Giagopoulos, J. Koutsoupakis
    Pages 11-25

  5. Synthetic Thermal Image Data Generation Using Attention-Based Generative Adversarial Network for Concrete Internal Damage Segmentation

    • Rahmat Ali, Young-Jin Cha
    Pages 27-33

  6. Principal Component Analysis of Monitoring Data of a High-Rise Building: The Case Study of Palazzo Lombardia

    • F. Lucà, H. Gholibeiki, S. Manzoni, E. Mola, S. Pavoni, M. Vanali
    Pages 35-42

  7. On Quantifying Data Normalisation via Cointegration with Topological Methods

    • T. Gowdridge, N. Dervilis, E. J. Cross, K. Worden
    Pages 43-52

  8. Better Together: Using Multi-Task Learning to Improve Feature Selection Within Structural Datasets

    • S. C. Bee, E. Papatheou, M. Haywood-Alexander, R. S. Mills, L. A. Bull, K. Worden et al.
    Pages 53-61

  9. A Meta-Learning Approach to Population-Based Modelling of Structures

    • G. Tsialiamanis, N. Dervilis, D. J. Wagg, K. Worden
    Pages 63-71

  10. Towards Physics-Based Metrics for Transfer Learning in Dynamics

    • J. Poole, P. Gardner, N. Dervilis, J. H. Mclean, T. J. Rogers, K. Worden
    Pages 73-81

  11. Automatic Selection of Optimal Structures for Population-Based Structural Health Monitoring

    • Tingna Wang, Keith Worden, David J. Wagg, Elizabeth J. Cross, Andrew E. Maguire, Weijiang Lin
    Pages 83-93

  12. A Population Form via Hierarchical Bayesian Modelling of the FRF

    • T. A. Dardeno, L. A. Bull, N. Dervilis, K. Worden
    Pages 95-103

  13. High-Rate Structural Health Monitoring: Part-II Embedded System Design

    • Austin Downey, Jason D. Bakos
    Pages 105-108

  14. High-Rate Structural Health Monitoring: Part-III Algorithms

    • Simon Laflamme, Chao Hu
    Pages 109-111

  15. Damage Quantification Under High-Rate Dynamic Loading and Data Augmentation Using Generative Adversarial Network

    • Celso T. do Cabo, Nicholas A. Valente, Zhu Mao
    Pages 113-120

  16. Optimal Contact-Impact Force Model Selection for Damage Detection in Ball Bearings

    • J. Koutsoupakis, D. Giagopoulos, P. Seventekidis
    Pages 121-127

  17. Optimal Fiber-Optic Sensor Placement Framework for Structural Health Monitoring of an Aircraft’s Wing Spar

    • Adrielly Hokama Razzini, Michael D. Todd, Iddo Kressel, Yoav Ofir, Moshe Tur
    Pages 129-132

  18. Online Backpropagation of Recurrent Neural Network for Forecasting Nonstationary Structural Responses

    • Zhymir Thompson, Alex Vereen, Austin Downey, Jason D. Bakos, Jacob Dodson, Adriane G. Moura
    Pages 133-137

  19. State Space Reconstruction from Embeddings of Partial Observables in Structural Dynamic Systems for Structure-Preserving Data-Driven Methods

    • David A. Najera-Flores, Michael D. Todd
    Pages 139-141

  20. Physics-Informed Data-Driven Reduced-Order Model for Turbomachinery Blisks

    • Sean T. Kelly, Bogdan I. Epureanu
    Pages 143-146
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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

Data Science in Engineering, Volume 10: Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics, 2023, the tenth 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 Data Science in Engineering, including papers on:

  • Novel Data-driven Analysis Methods
  • Deep Learning Gaussian Process Analysis
  • Real-time Video-based Analysis
  • Applications to Nonlinear Dynamics and Damage Detection
  • High-rate Structural Monitoring and Prognostics

Editors and Affiliations

  • Kount, an Equifax company, Boise, USA

    Ramin Madarshahian

  • Kount, an Equifax company, Oakland, USA

    François Hemez

About the editors

Ramin Madarshahian–Company: Kount, an Equifax company, Boise, ID, USA ;Francois Hemez–Lawrence Livermore National Laboratory, Livermore, CA, USA

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