Statistical Mechanics-Based Surrogates for Scalar Transport in Channel Flow

Thermal hydraulics, in certain components of nuclear reactor systems, involve complex flow scenarios, such as flows assisted by free jets and stratified leading to turbulent mixing thermal fluctuations. These patterns fluctuations can be extremely critical from a safety standpoint. The component-level lumped approximations (0D) or one-dimensional (1D) models for subsystems analysis codes cannot capture the physics accurately, may introduce large degree modeling uncertainty. On other hand, high-fidelity computational fluid dynamics codes, which provide numerical solutions Navier–Stokes equations, are accurate but computationally intensive, thus used system-wide analysis. An alternate way improve is building reduced-order emulators (CFD) system scale models. One key challenges developing emulator preserve across different-length scales time-scales. This paper presents development reduced-order, non-linear, “Markovian” statistical surrogate scalar transport. method its implementation demonstrated on canonical problem differentially heated channel flow, high-resolution direct simulations (DNS) data development. model relies Kramers–Moyal expansion emulates velocity signal with high accuracy.