Combustion simulations with high fidelity turbulence models and detailed chemistry may suffer from high computational power requirements due to the combined cost of time-scale dissipation and small integration steps. Such a limitation can be avoided by employing a hybrid reaction mechanism reduction method called local self-similarity tabulation (LS2T). LS2T directly solves several dominant species reactions and incorporates the effects of other species on dominant ones by data retrieval from pre-calculated tables. This paper demonstrates the application of LS2T method to a 3D combustion simulation of Sandia Flame-D. The combustion simulation uses large eddy simulation as turbulence solver and transported probability density function for species transport, to increase the accuracy of the simulation and avoid the use of any additional reaction model. The results show that by use of LS2T method, it is possible to maintain high accuracy and generate results similar to detailed chemistry of methane combustion while maintaining an acceptable computational effort.

具有高保真度湍流模型和详细化学过程的燃烧模拟可能会因时间尺度耗散和较小的积分步骤的综合成本而承受较高的计算能力要求。通过采用称为局部自相似列表（LS2T）的混合反应机理降低方法，可以避免这种局限性。LS2T直接解决了几种优势种反应，并通过从预先计算的表格中检索数据将其他物种对优势种的影响结合在一起。本文演示了LS2T方法在Sandia Flame-D的3D燃烧模拟中的应用。燃烧模拟使用大涡模拟作为湍流求解器，并利用转移概率密度函数进行物种迁移，以提高模拟的准确性，并避免使用任何其他反应模型。结果表明，通过使用LS2T方法，可以在保持可接受的计算工作量的同时，保持高精度并产生类似于甲烷燃烧详细化学过程的结果。