TY - JOUR T1 - The Discrete Direct Deconvolution Model in the Large Eddy Simulation of Turbulence AU - Chang , Ning AU - Yuan , Zelong AU - Wang , Yunpeng AU - Wang , Jianchun JO - Communications in Computational Physics VL - 3 SP - 791 EP - 849 PY - 2025 DA - 2025/08 SN - 38 DO - http://doi.org/10.4208/cicp.OA-2024-0075 UR - https://global-sci.org/intro/article_detail/cicp/24316.html KW - Direct deconvolution model, sub-filter scale model, large-eddy simulation. AB -
The discrete direct deconvolution model (D3M) is developed for the large-eddy simulation (LES) of turbulence. The D3M is a discrete approximation of previous direct deconvolution model studied by Chang et al. [”The effect of sub-filter scale dynamics in large eddy simulation of turbulence,” Phys. Fluids 34, 095104 (2022)]. For the first type model D3M-1, the original Gaussian and Helmholtz filters are approximated by local discrete formulation of different orders, and direct inverse of the discrete filter is applied to reconstruct the unfiltered flow field. The inverse of original Gaussian and Helmholtz filters can be also approximated by local discrete formulation, leading to a fully local model D3M-2. Compared to traditional models including the dynamic Smagorinsky model (DSM) and the dynamic mixed model (DMM), the D3M-1 and D3M-2 exhibit much larger correlation coefficients and smaller relative errors in thea priori studies. In the a posteriori validations, both D3M-1 and D3M-2 can accurately predict turbulence statistics, including velocity spectra, probability density functions (PDFs) of sub-filter scale (SFS) stresses and SFS energy flux, as well as time-evolving kinetic energy spectra, momentum thickness, and Reynolds stresses in turbulent mixing layer. D3M-1 and D3M-2 have more advantages in predicting the SFS statistics compared to scale-similarity model (SSM), DSM, and DMM. Thus, the D3M holds potential as an effective SFS modeling approach in turbulence simulations.