1st Edition
Data Science in Engineering, Volume 9 Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics 2022
158 Pages
by
River Publishers
Also available as eBook on:
Data Science in Engineering, Volume 9: Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics, 2022, the nineth volume of nine 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... Read more
Preface 1 Model Updating for Nonlinear Dynamic Digital Twins Using Data-Based Inverse Mapping Models 2 Deep Reinforcement Learning for Active Structure Stabilization 3 Estimation of Structural Vibration Modal Properties Using a Spike-Based Computing Paradigm 4 Environmental-Insensitive Damage Features Based on Transmissibility Coherence 5 Transmittance Anomalies for Model-Based Damage Detection with Finite Element-Generated Data and Deep Learning 6 Machine Learning-Based Condition Monitoring with Multibody Dynamics Models for Gear Transmission Faults 7 Structural Damage Detection Framework Using Metaheuristic Algorithms and Optimal Finite Element Modeling 8 On Aspects of Geometry in SHM and Population-Based SHM 9 A Robust PCA-Based Framework for Long-Term Condition Monitoring of Civil Infrastructures 10 Data-Driven Structural Identification for Turbomachinery Blisks 11 Classification of Rail Irregularities from Axle Box Accelerations Using Random Forests and Convolutional Neural Networks 12 Development of a Surrogate Model for Structural Health Monitoring of a UAV Wing Spar 13 On a Description of Aeroplanes and Aeroplane Components Using Irreducible Element Models 14 Input Estimation of Four-DOF Nonlinear Building Using Probabilistic Recurrent Neural Network 15 Simulation-Based Damage Detection for Composite Structures with Machine Learning Techniques 16 Synthesizing Dynamic Time-Series Data for Structures Under Shock Using Generative Adversarial Networks 17 Multilayer Input Deep Learning Applied to Ultrasonic Wavefield Measurements.
Biography
Ramin Madarshahian, Equifax, Boise, USA. Francois Hemez, Lawrence Livermore National Security, Livermore, USA.
