Implementation of a Synthetic Turbulent Inlet for turbulent flow simulation in CaNS

Compared to time-evolving turbulence, Direct Numerical Simulations (DNS) require physically consistent velocity boundary conditions, and the computed solution depends strongly on the quality of the prescribed inflow. This work presents one of the available synthetic turbulent inlet generators, specifically Klein's digital filtering algorithm and its implementation in the open-source solver CaNS. The described method uses first- and second-order one-point statistics to generate a turbulent mean and fluctuation field to be imposed at the boundary. The statistics provided can be generated from other simulations or directly from measurements, thus providing a flexible method for inflow generation. The turbulent inlet is employed to perform direct numerical simulations of turbulent channels with inlet/outlet boundary conditions, in order to assess the quality of the artificial inlet in terms of the streamwise length required by turbulence to develop the well-known statistics of fully developed doubly periodic channels, such as those of Kim, Moin and Mansour (1999) at Reτ=180. The method is first developed in Python as a proof of concept, where the residual discrepancies are analysed and traced back to the constant-length-scale approximation of the standard formulation, and subsequently ported to CaNS as a Fortran module.