Euler Bernoulli Beam

The Euler-Bernoulli beam model is a fundamental framework for analyzing the bending behavior of slender beams under various loads, with primary objectives of predicting deflection and stress. Current research focuses on enhancing the model's accuracy and applicability through data-driven approaches, such as physics-informed neural networks and Gaussian processes, and leveraging machine learning for tasks like parameter identification and inverse problem solving in complex beam systems. These advancements improve the model's utility in diverse fields, including structural health monitoring, particle accelerator beam steering, and robotics, enabling more accurate simulations and improved control strategies.