A reduced order kinetic model for NO (nitric oxide) prediction, based on the virtual chemistry methodology [M. Cailler, N. Darabiha, and B. Fiorina, Development of a virtual optimized chemistry method. Application to hydrocarbon/air combustion, Combust. Flame 211 (2020), pp. 281–302], is developed and applied. Virtual chemistry aims to optimise thermochemical properties and kinetic rate parameters of a network of virtual species and reactions. A virtual main chemical mechanism is dedicated to temperature and heat release prediction and is coupled with the flow governing equations, whereas satellite sub-mechanisms are designed to predict pollutants formation. Two virtual chemistry mechanisms are here employed: a main mechanism for calculating the temperature and heat release rate and a second mechanism dedicated to NO prediction. To recover the chemical structure of multi-mode combustion, both premixed and non-premixed flamelets are included in the learning database used to optimise the virtual NO mechanism. A multi-zone optimisation procedure is developed to accurately capture both fast and slow NO chemistry that include prompt, thermal and reburning pathways. The proposed NO sub-mechanism and optimisation methodology are applied to CH /air combustion. Laminar 1-D premixed and non-premixed flamelet configurations are first tested. The approach is then further assessed in 2-D CFD laminar flame simulations, by providing a direct comparison against detailed chemistry. 2-D premixed, non-premixed and partially premixed flame configurations are numerically investigated. For all cases, the virtual mechanism fairly captures temperature and chemistry with only 12 virtual species and 8 virtual reactions with a drastic CPU time reduction compared to detailed chemistry.

中文翻译：

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预测火焰中 NO 排放的虚拟化学机制

基于虚拟化学方法的 NO（一氧化氮）预测的降阶动力学模型 [M. Cailler、N. Darabiha 和 B. Fiorina，虚拟优化化学方法的开发。应用于碳氢化合物/空气燃烧，燃烧。Flame 211 (2020), pp. 281–302] 已开发和应用。虚拟化学旨在优化虚拟物种和反应网络的热化学性质和动力学速率参数。虚拟的主要化学机制专用于温度和热量释放预测，并与流动控制方程相结合，而卫星子机制旨在预测污染物的形成。这里采用了两种虚拟化学机制：计算温度和放热率的主要机制和专用于 NO 预测的第二种机制。为了恢复多模式燃烧的化学结构，预混和非预混小火焰都包含在用于优化虚拟 NO 机制的学习数据库中。开发了多区域优化程序以准确捕获快速和慢速 NO 化学，包括快速、热和再燃烧途径。提出的 NO 子机制和优化方法适用于 CH/空气燃烧。首先测试层流一维预混和非预混小火焰配置。然后通过提供与详细化学的直接比较，在二维 CFD 层流火焰模拟中进一步评估该方法。二维预混、非预混和部分预混的火焰配置进行了数值研究。对于所有情况，