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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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11084809/ |
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