Smart Proxy Modeling Application of Artificial Intelligence & Machine Learning in Computational Fluid Dynamics
- West Virginia Univ., Morgantown, WV (United States)
- National Energy Technology Lab. (NETL), Morgantown, WV (United States)
- Leidos, Inc., Reston, VA (United States)
Smart proxy technology leverages the art of artificial intelligence and machine learning in order to build accurate and very fast proxy models for highly complex numerical simulation models. In this project, smart proxy technology is used to replicate the results of a highly complex single phase CFD simulation with reasonable degree of accuracy while reducing the computational cost associated with such CFD simulations. The CFD model under study simulates the combustion of natural gas under various conditions such as varying natural gas composition and flow rate, inlet air flow rate and temperature, and outlet pressure in a High-Pressure Combustion Facility (B6 Combustor) with more than 4 million simulation cells. Only eight CFD simulation runs were used to create a smart proxy model that replicates the detail distribution of Pressure, Temperature, Nitrogen, Oxygen and Carbon-dioxide concentration in the CFD simulation model in seconds with less than 10% error.
- Research Organization:
- National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)
- Sponsoring Organization:
- USDOE Office of Fossil Energy (FE)
- DOE Contract Number:
- 89243318CFE000003
- OSTI ID:
- 1642460
- Report Number(s):
- NETL-WVU-07-22-2020
- Country of Publication:
- United States
- Language:
- English
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