摘要
用一维火焰分析并构建火焰面数据库,基于稳态层流火焰面(SLFM)模型分析不同化学反应机理对火焰面数据库及模拟结果的影响。基于大涡模拟(LES)程序AECSC(aero engine combustor simulation code)软件,SLFM模型结合DRG(direct relation graph)方法简化机理、Smooke机理、GRI 3.0详细机理模拟高雷诺数甲烷射流Flame D、E、F火焰,其中GRI 3.0机理的温度平均值和脉动值与实验数据最接近。相比LES-概率密度函数输运方程湍流燃烧(TPDF)模型,LES-SLFM方法计算速度快,整体精度接近TPDF计算结果。对化学机理影响火焰面数据库,从而影响模拟时间和精度的原因进行了系统分析。LES-SLFM模型结合详细机理速度快、精度合适,未来可以进一步用燃烧室算例检验,具有应用的潜力和发展价值。
The effects of different chemical reaction mechanisms on the flame surface database and simulation results based on the steady laminar flamelet model(SLFM) were analyzed by using onedimensional flame analysis and constructing a flamelet database. Based on the large eddy simulation(LES)program AECSC(aero engine combustor simulation code) software, the SLFM model was combined with DRG(direct relation graph) method simplified mechanism, Smooke mechanism, and GRI 3.0 detailed mechanism to simulate Flame D, E, and F jet flames, among which the average temperature and pulsation values of GRI 3.0 mechanism were the closest to the experimental data. The LES-SLFM model was faster and had comparable overall accuracy compared with the LES and probability density functional transport equation turbulent combustion(TPDF) models. The chemical mechanism affected the flamelet database and thus the time and accuracy of the simulation. The LES-SLFM model combined with the detailed mechanism was fast and had suitable accuracy, which should be further tested in the combusor simulation,presenting potential and value for future applications.
作者
王方
蔡江涛
张健
金捷
WANG Fang;CAI Jiangtao;ZHANG Jian;JIN Jie(Aeroengine Numerical Simulation Research Center,School of Energy and Power Engineering,Beihang University,Beijing 100191,China;Jiangxi Research Institute of Beihang University,Nanchang 330096,China;Chengdu Innovation Research Institute on Aircraft Power,Beihang University,Chengdu 611930,China;Institute for Aero Engine,Tsinghua University,Beijing 100084,China)
出处
《航空动力学报》
EI
CAS
CSCD
北大核心
2022年第11期2465-2478,共14页
Journal of Aerospace Power
基金
国家自然科学基金(91741125)
国家科技重大专项(2017-Ⅰ-0004-0005)。