👉 The NNF, or Neural Numerical Fluid, is a novel framework that combines elements of neural networks with fluid dynamics to model complex, dynamic systems. Unlike traditional fluid dynamics models that rely heavily on predefined equations and assumptions, the NNF uses deep learning techniques to learn the underlying patterns and behaviors of fluid flows directly from data. This approach allows for more flexible, data-driven modeling that can adapt to a wide range of scenarios and conditions, making it particularly useful in applications where precise physical models are difficult to derive or where real-time predictions are crucial. The NNF bridges the gap between data-driven machine learning and physics-based modeling, offering a powerful tool for simulating and understanding fluid dynamics in various fields such as engineering, meteorology, and oceanography.
