Finite Element

Finite element analysis (FEA) is a powerful computational technique for simulating physical phenomena by dividing a system into smaller elements, solving equations within each, and assembling the results. Current research emphasizes integrating FEA with machine learning, particularly using graph neural networks and physics-informed neural networks (PINNs), to accelerate simulations, improve accuracy for complex geometries, and reduce computational costs. This hybrid approach is proving valuable in diverse applications, including structural mechanics, material design, and biomechanics, by enabling faster design iterations and more efficient analysis of complex systems.