Mesh Adaptation

Mesh adaptation optimizes computational meshes to improve the accuracy and efficiency of numerical simulations, particularly for solving partial differential equations. Current research heavily utilizes machine learning, employing techniques like reinforcement learning, graph neural networks, and neural networks to automate and accelerate mesh refinement and relocation processes, often outperforming traditional methods. These advancements are significant because they reduce computational costs and improve the accuracy of simulations across diverse fields, including fluid dynamics, image processing, and animation, enabling more efficient and effective modeling of complex systems.