Finite Element Model

Finite element modeling (FEM) is a powerful computational technique used to simulate the behavior of complex systems by dividing them into smaller, simpler elements. Current research focuses on improving FEM's efficiency and accuracy through techniques like physics-informed neural networks, surrogate models (e.g., using DeepONets), and hybrid quantum-classical approaches, addressing challenges such as computational cost and the need for real-time analysis in applications ranging from structural engineering to biomechanics. These advancements enable more accurate and efficient simulations, leading to improved design optimization, predictive modeling, and ultimately, safer and more reliable systems across diverse fields.