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Physics-informed Multiple-Input Operators for efficient dynamic response prediction of structures
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DOI：10.1016/j.engappai.2025.112703.png)
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Abstract
En 中文
• Proposed MIONet for real-time structural response prediction under dynamic loading. • Outperforms GRU-based DeepONet in capturing continuous temporal dynamics. • Enforces physics via dynamic equilibrium matrix constraints. • Achieves accuracy >95% and 100 × speedup in dynamic response prediction.
Keywords:
Multiple-input operators
Physics-informed neural operators
Finite element modeling
Dynamic loading
Schur complement
Translation and rotation
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