👉 A tagged fluid is a computational model used in fluid dynamics simulations, particularly for complex and multiphase flows. It combines the principles of fluid dynamics with machine learning techniques, where "tags" are learned features or descriptors that capture the essential characteristics of the fluid and its interactions with other phases (such as gas, liquid, or solid). These tags are generated during the training process and help the model to better understand and predict the behavior of fluids in various scenarios, such as turbulence, phase transitions, and interfacial phenomena. By incorporating these learned features, tagged fluid models can achieve higher accuracy and efficiency compared to traditional physics-based models, especially in cases where detailed physical equations are challenging to formulate or computationally expensive.
