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Oscillating Heat Transfer Prediction in Porous Structures Using Generative AI-Assisted Explainable Machine Learning
Predicting and interpreting thermal performance under oscillating flow in porous structures remains a critical challenge due to the complex coupling between fluid dynamics and geometric features. This study introduces a data-driven wGAN-LBM-Nested_CV framework that integrates generative deep learnin
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