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arXiv Machine Learning By Haoze Zhang, Han Li, Ke Xiao, Yangchen Xu, Runze Mao, Zhi X. Chen

Thermodynamics-Informed Input Reparameterization for Neural Prediction of Real-Fluid Thermodynamic Properties in Supercritical Combustion

Read the original on arXiv Machine Learning →

arXiv:2607. 19241v1 Announce Type: new Abstract: Real-fluid thermodynamic property evaluation is a major computational cost in supercritical combustion simulations.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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