Strong shear turbulence dynamic grid adaptive simulation method coupled with RSM series model

By combining the Vreman dynamic coefficient and the shear layer adaptive length scale, dynamically adjusting the grid scale, and reconstructing the Reynolds stress tensor and turbulent viscosity, the problems of high computational cost and insufficient accuracy in strong shear turbulent flows are solved, and efficient and accurate flow simulation is achieved.

CN120706315APending Publication Date: 2025-09-26BEIHANG UNIV
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Patent Information

Application Number
CN202510838207.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-06-23
Publication Date
2025-09-26

AI Technical Summary

Technical Problem

Existing technologies have high computational costs and insufficient accuracy in simulating strong shear turbulent flows, and it is difficult to effectively capture complex flow structures under sparse grids. This is especially true in aircraft engines and gas turbines, where there are problems of high computational costs and low prediction accuracy.

Method used

Combining the Vreman dynamic coefficient and the shear layer adaptive length scale, the scale-related function is constructed by integrating the turbulent energy spectrum, the grid scale is dynamically adjusted, the Reynolds stress tensor and turbulent viscosity are reconstructed, and grid adaptive simulation is achieved.

Benefits of technology

It significantly improves the simulation accuracy and computational efficiency of strong shear turbulent flows, reduces computational costs, and can better capture complex flow structures, making it suitable for low-cost and high-precision simulations in engineering flows.

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Abstract

The invention discloses a strong shear turbulence dynamic grid adaptive simulation method coupled with an RSM series model. The method mainly comprises the following steps: step 1, judging whether a shielding function is applied or not; step 2, calculating a Vman dynamic coefficient; step 3, identifying the self-adaptive length scale of the shear layer; 4, constructing a scale-related adjustment function based on the turbulence energy spectrum integral coupling RSM series model; 5, reconstructing a Reynolds stress tensor and turbulence viscosity by using an adjustment function; and 6, performing turbulence simulation by using the reconstructed Reynolds stress tensor and turbulence viscosity. According to the method, the size of a local grid is identified by constructing a Vman dynamic coefficient, the length scale of the local grid is jointly determined in combination with the length scale of the shear layer adaptive sub-grid, and then the scale correlation function is constructed through the turbulence energy spectrum integral to reconstruct the turbulence viscosity, so that grid adaptive simulation is realized; an effective numerical simulation method is provided for solving low-consumption and high-precision simulation of strong shear turbulence in a complex engineering flow problem.
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