Solid Mechanic

Solid mechanics, the study of how materials deform and fail under stress, seeks to accurately predict material behavior in diverse conditions. Current research heavily emphasizes the development and application of machine learning techniques, particularly neural networks (including graph neural networks, Gaussian processes, and physics-informed neural networks), to improve the efficiency and accuracy of simulations, often focusing on surrogate modeling for computationally expensive problems like fracture prediction and material identification. These advancements are significantly impacting various fields, enabling faster and more reliable simulations for engineering design, materials science, and structural health monitoring.