Wake Model

Wake models aim to mathematically represent and predict the flow disturbances downstream of an object, such as a wind turbine or a cylinder in a fluid. Current research focuses on improving model accuracy and efficiency using various techniques, including artificial intelligence-driven symbolic regression, deep reinforcement learning with dynamic feature extraction, and graph neural networks operating on unstructured meshes. These advancements are crucial for optimizing wind farm design and operation, enhancing flow control strategies, and improving the understanding of complex fluid dynamics in various applications.