Predicting subdifferential switching surface in a steady-state complex heat transfer problem using deep learning

A boundary value problem of complex heat transfer have been considered in the work. A method for determination of a switching surface with subdifferential boundary conditions based on the use of deep learning has been proposed. A method uses a neural network trained on a dataset of numerical solutions of the steady-state complex heat transfer forward problems. The obtained results are verified by comparison with the numerical experiments.