The present research proposes a new memory-efficient method using diffusion models to inject turbulent inflow conditions into large eddy simulation and direct numerical simulation for various flow problems. A guided diffusion model was trained on decaying homogeneous isotropic turbulence samples, characterized by different turbulent kinetic energy levels and integral length scales. Samples generated by the diffusion model accurately reproduce turbulence statistics, such as the energy spectrum and the two-point autocorrelation functions, while preserving the ability to generate instantaneous three-dimensional velocity fields with detailed fluctuations. Physical representativeness is also evaluated by injecting the synthetic samples into a free domain (i.e., without any wall boundary) through an inlet boundary condition. The method demonstrates promising results regarding energy spectrum, spatial correlation, turbulent kinetic energy level, and integral length scales without increasing the development distance as compared to a library-based method.
Boxho et al. (Fri,) studied this question.