Quadrilateral Mesh

Quadrilateral mesh generation aims to create high-quality meshes composed of quadrilaterals, crucial for accurate numerical simulations in engineering and design. Current research heavily emphasizes automated mesh generation using machine learning, particularly employing reinforcement learning and neural networks (e.g., soft actor-critic, advancing front methods enhanced with supervised and reinforcement learning) to overcome the limitations of traditional methods. These advancements focus on improving mesh quality, minimizing irregular nodes, and handling complex geometries, ultimately accelerating and improving the accuracy of simulations in various fields.