Stochastic fields with adaptive mesh refinement for high-speed turbulent combustion

被引:0
|
作者
Un, Tin-Hang [1 ]
Navarro-Martinez, Salvador [1 ]
机构
[1] Imperial Coll London, Dept Mech Engn, London SW7 2AZ, England
关键词
Stochastic fields; Joint velocity-species-energy probability; density function; Adaptive mesh refinement; PROBABILITY DENSITY-FUNCTION; LARGE-EDDY SIMULATION; FINITE-RATE CHEMISTRY; PDF METHODS; JET; VELOCITY; MODEL;
D O I
10.1016/j.combustflame.2024.113897
中图分类号
O414.1 [热力学];
学科分类号
摘要
This paper presents a fully compressible joint velocity-species-energy probability density function (PDF) for modelling turbulent reactive flows across all Mach numbers. By incorporating velocities into the PDF, the approach unifies the treatment of non-linear source and turbulent transport terms with minimal model parameters. The PDF transport is solved using Eulerian stochastic fields, leveraging features from existing grid-based solvers like high-order shock-capturing schemes and adaptive mesh refinement. Validation test cases show that the solver achieves the theoretical convergence rate, maintains accuracy across refinement levels, and demonstrates convergence with a moderate number of fields. Additionally, it outperforms the Smagorinsky model by adding dissipation only when necessary. When applied to a supersonic jet flame, the solver reproduces experimental measurements and results from highly-resolved large eddy simulations, demonstrating robustness in supersonic reacting flows with dynamic flow fields and shocklet structures.
引用
收藏
页数:9
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