crossrefMachine Learning: Science and Technology2026-07-08
An interpretable convolutional neural network framework for fluid dynamics
Kwame Agyei-Baah, Muhammad Rizwanur Rahman, Edward R Smith
Abstract Modelling fluid dynamics with machine learning (ML) has advanced rapidly, yet most data driven approaches remain opaque because they rely on complex architectures to capture nonlinear flow behaviour. This lack of interpretability limits the reliability and hinders the un…