CFDAnsatz
CFDAnsatz is a term that has emerged in discussions related to computational fluid dynamics (CFD) and data-driven approaches. It refers to the integration of data-driven methods, such as machine learning or artificial intelligence, into the traditional CFD workflow. This approach aims to leverage the strengths of both data and physics-based simulations to achieve more accurate, efficient, and robust solutions.
Traditional CFD relies on solving complex partial differential equations that govern fluid flow. While powerful, these
The applications of CFDAnsatz are diverse. It can be used for surrogate modeling, where a machine learning
The development and adoption of CFDAnsatz are ongoing, with active research into various methodologies, including deep