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分区参数对超声速湍流燃烧动态分区火焰面模拟的影响

EFFECT OF ZONING PARAMETERS ON DYNAMIC ZONE FLAMELET MODELING OF SUPERSONIC TURBULENT COMBUSTION

  • 摘要: 文章基于动态分区火焰面模型(DZFM)和改进延迟分离涡(IDDES)湍流模型对DLR中心支板稳焰的超声速燃烧室进行数值模拟. 对无反应状态燃烧室的模拟准备复现了燃烧室内复杂的波系结构以及中心射流失稳发展过程, 燃烧状态下的模拟结果较好地捕捉了火焰推举、OH基团以及平均温度等火焰结构特征, 由此验证了所采用数值模拟方法的适用性. 此外, 由反应状态标量(OH基)在混合分数空间中的分布可知, 反应标量与混合分数在全场内不满足强相关性. 通过增加流向坐标、马赫数以及燃烧热释放速率作分区参数可显著抑制反应状态标量在混合分数空间内的条件脉动, 其中热释放速率的作用最显著. 进一步对比采用不同多参数分区的DZFM模型所得火焰结构, 发现对于处于预混燃烧状态的支板尾迹区以及高雷诺数剪切层区域火焰, 采用包含燃烧热释放速率、流向坐标以及混合分数作为分区指标的三参数分区DZFM模型可显著提高模型的准确性.

     

    Abstract: This paper presents a numerical simulation of the DLR supersonic combustor stabilized by a central strut, based on the dynamic zone flamelet model (DZFM) and the improved delayed detached eddy simulation (IDDES) turbulence model. The simulation of the combustion chamber under a non-reactive condition reproduces the complex wave structure and instability development of the central jet. The simulation results under the reactive condition successfully capture flame lift-off, OH radicals, average temperature, and other flame structural characteristics, thus validating the suitability of the numerical simulation method used in this study. Furthermore, it is observed from the distribution of reaction scalar (OH radical) in mixture fraction space that, the strong correlation between reaction scalar and mixture fraction is unavailable throughout the entire field. It is found that through introducing multi-zoning parameters such as flow direction coordinates, Mach number, and combustion heat release rate can significantly suppress the conditional fluctuation of the reaction state scalar in the mixed fraction space. Comparing the flame structure obtained by using the DZFM model with different multi-parameter-zoning strategies, it is found that in the tail region of the support plate and the high Reynolds number shear layer area, where the flame is in a premixed combustion state, the three-parameter zoning DZFM model including the combustion heat release rate and Mach number as zoning indicators, can significantly improve the accuracy of the model.

     

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