湍流非预混火焰中烟炱粒径分布演化的双变量多矩分段法大涡模拟
Large Eddy Simulation of the evolution of the soot size distribution in turbulent nonpremixed flames using the Bivariate Multi-Moment Sectional Method
AI总结：
提出双变量多矩分段法（BMMSM）耦合大涡模拟，高效模拟湍流非预混火焰中烟炱粒径分布从单峰到双峰的演化，仅需八段即可准确预测，计算成本比HMOM高约44%。
摘要：
本文开发了一种联合体积-表面积形式的多矩分段法（MMSM），用于描述湍流反应流中烟炱粒径分布的演化。双变量MMSM（即BMMSM）在每个分段中考虑三个统计矩，包括每段的总烟炱数密度、总烟炱体积和总烟炱表面积。沿体积坐标采用线性剖面来重建每个分段内的粒径分布，该分布沿表面积坐标加权一个δ函数。表面积的闭合假设一次颗粒直径恒定，因此每段内的表面积与体积之比恒定。与单变量前身严格球形的假设相比，BMMSM中引入新变量使得能够描述烟炱的分形聚集形态。BMMSM在一维层流烟炱火焰的模拟中能够再现双峰烟炱粒径分布，与实验测量结果一致。为了展示其在湍流反应流中的性能，BMMSM与大涡模拟框架耦合，模拟了一个实验室规模的湍流非预混射流火焰。计算结果与可用的烟炱粒径分布实验测量结果进行了验证，表明BMMSM能够再现火焰下游粒径分布从单峰向双峰演化的过程。总体而言，改变分段数量对结果影响有限，仅用八个分段（共24个自由度）即可获得准确结果。还研究了使用不同烟炱统计模型（HMOM）的影响。使用BMMSM的总计算成本仅比HMOM高约44%。新公式为湍流反应流中的烟炱粒径分布提供了一种计算高效的方法。
英文摘要：
A joint volume-surface formalism of the Multi-Moment Sectional Method (MMSM) is developed to describe the evolution of soot size distribution in turbulent reacting flows. The bivariate MMSM (or BMMSM) considers three statistical moments per section, including the total soot number density, total soot volume, and total soot surface area per section. A linear profile along the volume coordinate is considered to reconstruct the size distribution within each section, which weights a delta function along the surface coordinate. The closure for the surface considers that the primary particle diameter is constant so the surface/volume ratio constant within each section. The inclusion of the new variable in BMMSM allows for the description of soot's fractal aggregate morphology compared to the strictly spherical assumption of its univariate predecessor. BMMSM is shown to reproduce bimodal soot size distributions in simulations of one-dimensional laminar sooting flames as in experimental measurements. To demonstrate its performance in turbulent reacting flows, BMMSM is coupled to a Large Eddy Simulation framework to simulate a laboratory-scale turbulent nonpremixed jet flame. Computational results are validated against available experimental measurements of soot size distribution, showing the ability of BMMSM to reproduce the evolution of the size distribution from unimodal to bimodal moving downstream in the flame. In general, varying the number of sections has limited influence on results, and accurate results are obtained with as few as eight sections so 24 total degrees of freedom. The impact of using a different statistical model for soot (HMOM) is also investigated. The total computational cost of using BMMSM as low as approximately 44% more than the cost of HMOM. The new formulation results in a computationally efficient approach for the soot size distribution in turbulent reacting flows.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
