发表机构
Clemson University（克莱姆森大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文通过DNS数据评估LES-FMDF中三种亚格子混合模型在高压下的表现，发现混合频率是导致预测偏差的关键因素。
AI 中文摘要
本文针对大涡模拟-滤波质量密度函数（LES-FMDF）方法中使用的滤波质量密度函数输运方程中的条件标量扩散（CSD）项的分子混合模型，与空间发展射流的直接数值模拟（DNS）进行了对比评估。建立了湍流混合槽道射流（$C_{7}H_{16} / O_2$ 和 $C_{7}H_{16} / Air$）的DNS数据库。该公式包括可压缩形式的控制方程、广义多组分扩散模型、三次真实气体状态方程和真实物性模型。模拟在广泛的初始压力范围（$1 atm < P_0 < 100 atm$）和基于射流宽度的雷诺数850和1300下进行。从模拟中在流场内多个空间位置获得了不同滤波宽度下的混合分数FMDF。从DNS计算了FMDF精确输运方程中的CSD项。对交互交换平均（IEM）、修正卷曲（MC）和映射闭合（MAPPING）混合模型进行了先验分析。在高压下，DNS测量的CSD与模型预测之间存在显著偏差。偏差来源被确定为模型中使用的混合频率。研究了混合频率的重要性及其随压力和扩散模型的变化。本工作的主要目标是评估上述混合模型在大压力流动中的适用性，并确定预测偏差的原因。
英文摘要
Molecular mixing models for the conditional scalar diffusion (CSD) term in the filtered mass density function (FMDF) transport equation used in Large Eddy Simulation (LES-FMDF) approach are evaluated against direct numerical simulation (DNS) of spatially evolving jets. A database of DNS of turbulent mixing slot jets of $C_{7}H_{16} / O_2$ and $C_{7}H_{16} / Air$ is developed. The formulation includes the compressible form of the governing equations, a generalized multicomponent diffusion model, a cubic real gas equation of state and realistic property models. Simulations are conducted over a wide range of initial pressures ($1 atm < P_0 < 100 atm$) and jet width based Reynolds numbers of 850 and 1300. FMDF of mixture fraction at various filter widths are obtained from the simulation at several spatial locations within the flow. The CSD term in the exact transport equation of FMDF is calculated from the DNS. An \textit{a priori} analysis of Interaction by Exchange of Mean (IEM), Modified Curl (MC) and Mapping Closure (MAPPING) mixing models for CSD is conducted. At high pressures, significant deviations are observed between the CSD measured from the DNS and those predicted by the models. The source of the deviations is determined to be the mixing frequency used in the models. The significance of the mixing frequency and its variation with change in pressure and diffusion models is studied. The primary objective of this work is to assess the applicability of aforementioned mixing models to flows at large pressures and determine the causes for deviation in prediction.
Journal refJournal of Turbulence, 19:8, 683-715 (2018)
DOI：10.1080/14685248.2018.1498590
