Active learning with physics-informed surrogates achieves comparable accuracy for a glycol heat exchanger digital twin using only one-fifth the high-fidelity simulation trajectories needed by random sampling.
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Physics-based Digital Twins for Integrated Thermal Energy Systems Using Active Learning
Active learning with physics-informed surrogates achieves comparable accuracy for a glycol heat exchanger digital twin using only one-fifth the high-fidelity simulation trajectories needed by random sampling.