Experiment based calibration of $k - \varepsilon$ turbulence model in OpenFOAM package for mountain slope flows using machine learning techniques

We calibrate the $k - \varepsilon$ turbulence model for free surface flows in the channel or on the slope. To calibrate the turbulence model, an experiment is carried out in an inclined rectangular research tray. In the experiment, the pressure values in the flow are measured at different distances from the bottom using a Pitot tube; after transforming data, the flow velocity profile is obtained. The $k - \varepsilon$ turbulence model is calibrated based on experimental data using the Nelder-Mead optimization algorithm. The calibrated turbulence model is then used to calculate the outburst of a lake near the glacier Maliy Azau on the Elbrus (Central Caucasus).