CFD-solver-agnostic deep reinforcement learning framework for computational fluid dynamics on HPC platforms

2D CFD simulation of NACA0012 at 5° AoA using SST k-ω model. Mesh convergence included.

Automated calibration of RANS turbulence models for hypersonic flows using SciML. Achieved 26% RMSE reduction at Mach 14.

Real meteorological data (temperature, pressure, precipitation) were obtained from İSKİ. Eddy diffusivity, Monin-Obukhov length, and turbulence intensity were calculated from existing data and added to the dataset. Using 289,000 data points and 27 features, RF, SVM, LSTM, and CNN models were developed. LSTM achieved 98%, CNN 91% accuracy.