Physics-Based AI-Driven Surrogate Modeling for Structural Displacement Prediction in Mechanical Systems With Limited Sensor Data

Physics-Based AI-Driven Surrogate Modeling for Structural Displacement Prediction in Mechanical Systems With Limited Sensor Data

This study introduces a machine learning (ML)-based surrogate model for finite element analysis, designed to predict structural strain distributions using a minimal number of strategically placed virtual sensors. The proposed approach eliminates the dependency on external force measurements, leverag...

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Bibliographic Details
Main Authors: Ali Hashemi, Javad Beheshti, Mahdieh Mohammadi
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Machine learning
surrogate models
finite element methods
structural dynamics
virtual sensor placement
artificial neural networks
Online Access:https://ieeexplore.ieee.org/document/11084809/
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