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扩散火焰烟黑的数值模拟与参数优化

Numerical Simulation and Parameter Optimization of Soot in Diffusion Flame
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摘要 烟黑是燃料燃烧产生颗粒污染物的重要组成部分。火焰中烟黑的形成与多个因素有关,并且各因素对烟黑的影响效果不同。选取烟黑成核速率常数的活化能和指前因子、生长速率常数的活化能和指前因子,以及OH与烟黑颗粒的碰撞率这5个重要因素对烟黑形成的影响进行优化研究。创新性地将正交设计与烟黑模拟相结合,旨在分析各因素对烟黑形成的影响程度,并对这5个因素进行了优化设计。运用正交试验设计方案,对5个因素进行16组数值模拟试验。基于试验结果,应用极差和方差分析进行详细研究。研究结果表明,5个因素对烟黑形成的影响强弱程度依次是:生长速率常数活化能、生长速率常数指前因子、成核速率常数活化能、生长速率常数指前因子、OH和烟黑颗粒的碰撞率。该研究为更加精确、可靠地模拟出烟黑形成提供了指导思想和参考。 Soot is an important component of particulate pollutants produced by fuel combustion.The formation of soot in flame is related to many factors,and each factor has different effects on soot.The activation energy of the nucleation rate constant and the pre-exponential factor,the activation energy of the growth rate constant and the collision rate of the pre-exponential factor,OH and the soot particles were selected to optimize the influences of the formation of soot.The orthogonal design was innovatively combined with soot simulation to analyze the influence of various factors on the formation of soot,and the five factors were optimized for design.Using orthogonal experimental design scheme,16 numerical simulation tests were carried out for five factors.Based on the experimental results,range and variance analysis were used to study in detail.The results show that the influences of the five factors on the formation of soot are in order:growth rate constant activation energy,growth rate constant prefactor,nucleation rate constant activation energy,growth rate constant pre-factor,OH and the collision rate of soot particles.This study provides guidance and reference for more accurate and reliable simulation of soot formation.
作者 谢欣容 刘石 XIE Xinrong;LIU Shi(School of Energy,Power and Mechanical Engineering,North China Electric Power University,Beijing 102206,China)
出处 《自动化仪表》 CAS 2021年第2期40-44,共5页 Process Automation Instrumentation
基金 中央高校基本科研业务基金资助项目(2019QN014)。
关键词 扩散火焰 化学反应动力学 正交试验设计 烟黑模型 数值模拟 均方根误差 极差分析 方差分析 Diffusion flame Chemical reaction kinetics Orthogonal experimental design Soot model Numerical simulation Root mean square error Range analysis Analysis of variance
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