LARCHER , Aurélien

This study presents a novel approach of surface-to-surface (S2S) radiation in the context of an immersed volume method. Radiating facets are reconstructed from the solid-liquid interface. Obstructed view factors are accurately computed while energy balance is ensured through flux correction. The resulting radiative flux is then coupled with a...

Deep Reinforcement Learning (DRL) has recently spread into a range of domains within physics and engineering, with multiple remarkable achievements. Still, much remains to be explored before the capabilities of these methods are well understood. In this paper, we present the first application of DRL to direct shape optimization. We show that,...

Deep reinforcement learning (DRL) has recently been adopted in a wide range of physics and engineering domains for its ability to solve decision-making problems that were previously out of reach due to a combination of non-linearity and high dimensionality. In the last few years, it has spread in the field of computational mechanics, and...