Multifidelity TDNN with physics-informed residual learning improves railway-bogie response prediction across untested operating scenarios.
Read the original at arxiv.org→arXiv:2609.12018v1 Announce Type: new Abstract: Railway engineers need simulation models that predict vehicle responses across operating scenarios that cannot be tested exhaustively. Agreement with representative...
Original headline: "Toward Reliable Railway-Bogie Response Prediction Using Multifidelity TDNN and Physics-Informed Residual Learning"
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- Sep 14, 04:00 UTC arXiv cs.LG lead source Toward Reliable Railway-Bogie Response Prediction Using Multifidelity TDNN and Physics-Informed Residual Learning