Dynamic Loading

Dynamic loading research focuses on understanding and predicting the response of systems to time-varying forces or inputs, encompassing diverse fields from robotics and civil engineering to virtual reality and power systems. Current research employs various machine learning models, including deep neural networks, graph neural networks, and reinforcement learning, to improve prediction accuracy and efficiency, often coupled with physics-informed approaches for enhanced realism. These advancements have significant implications for optimizing autonomous systems, improving structural design and safety, enhancing virtual reality experiences, and optimizing resource allocation in complex networks.