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Modeling subfilter soot-turbulence interactions in Large Eddy Simulation: An a priori study
Proceedings of the Combustion Institute ( IF 5.3 ) Pub Date : 2020-10-24 , DOI: 10.1016/j.proci.2020.06.386
Lukas Berger , Achim Wick , Antonio Attili , Michael E. Mueller , Heinz Pitsch

A new LES model for subfilter soot-turbulence interactions is developed based on an a priori analysis using large-scale DNS data of temporally evolving non premixed n-heptane jet flames at a jet Reynolds number of 15,000. In this work, soot formation is modeled in LES by solving explicit transport equations for soot moments, and the unclosed filtered soot moment source terms are closed by a presumed PDF approach. Due to the strong intermittency of soot fields, a previous modeling approach assumes the presumed PDF to be bimodal accounting for sooting and non-sooting subfilter regions but neglects any sub-structure of the soot distribution. In this work, the modeling framework is improved by a new presumed PDF model that explicitly accounts for the sub-structure of the sooting mode, which is modeled by a log-normal distribution. The previous and new models are assessed by means of their prediction of the filtered source terms and the filtered intermittency, and the log-normal distribution is found to significantly reduce modeling errors, in particular, for the coagulation source term. Introducing a log-normal distribution for the PDF of the sooting mode involves a large amount of additional model parameters, such as the width of the distribution and correlation coefficients among different soot moments, so model assumptions to reduce the number of model parameters are discussed by means of the DNS data. The conclusions are found to be robust with respect to a variation in the global Damköhler number in the DNS datasets. The final model formulation only requires solving two additional transport equations in LES compared to previous models, while significantly improved model predictions are obtained for the coagulation source term which is import for predicting the number of soot particles.



中文翻译:

在大涡模拟中对子过滤器烟尘-湍流相互作用进行建模:先验研究

基于先验分析,使用时间上演化的非预混合n的大规模DNS数据,基于先验分析,开发了用于子过滤器烟尘-湍流相互作用的新LES模型。-庚烷喷射火焰,喷射雷诺数为15,000。在这项工作中,通过求解烟灰矩的显式输运方程,在LES中对烟灰形成进行建模,并通过假定的PDF方法关闭未封闭的过滤后的烟灰矩源项。由于煤烟场之间的强烈间歇性,以前的建模方法假定假定的PDF是考虑煤烟和非煤烟子过滤器区域的双峰分析,但忽略了煤烟分布的任何子结构。在这项工作中,建模框架通过新的假定PDF模型进行了改进,该模型明确说明了烟ot模式的子结构,该模型通过对数正态分布进行建模。通过对过滤后的源项和过滤后的间歇性进行预测,可以评估以前的模型和新模型,发现对数正态分布可以显着减少建模误差,尤其是对于凝结源而言。为烟灰模式的PDF引入对数正态分布会涉及大量其他模型参数,例如分布宽度和不同烟灰矩之间的相关系数,因此,我们讨论了减少模型参数数量的模型假设DNS数据的方式。对于DNS数据集中全局Damköhler数的变化,发现结论是可靠的。与以前的模型相比,最终的模型公式仅需要求解LES中的两个附加运输方程,而对于凝结源项则获得了显着改善的模型预测,这对于预测烟灰颗粒的数量至关重要。

更新日期:2020-10-29
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