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${}_4$/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 ${\mathrm{N}\mathrm{O}}_x$ chemistry with only 12 virtual species and 8 virtual reactions with a drastic CPU time reduction compared to detailed chemistry.

基于虚拟化学方法论的NO（一氧化氮）预测的降阶动力学模型[M. Cailler，N。Darabiha和B. Fiorina，开发了虚拟的优化化学方法。适用于碳氢化合物/空气燃烧，燃烧。Flame 211（2020），第281–302页]已开发并应用。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的预测，并与流量控制方程式耦合，而卫星子机制旨在预测污染物的形成。这里采用两种虚拟化学机制：一种用于计算温度和放热速率的主要机制，另一种专用于NO预测的机制。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。开发了一种多区域优化程序，以准确捕获快速和慢速NO化学反应，包括快速，热和再燃烧途径。建议的NO子机制和优化方法应用于CH${}_4$/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，通过与详细化学方法进行直接比较，在二维CFD层流火焰模拟中进一步评估该方法。对二维预混，非预混和部分预混的火焰构型进行了数值研究。在所有情况下，虚拟机制都能公平地捕获温度并${\mathrm{ñ}\mathrm{Ø}}_X$ 与详细的化学方法相比，仅用12种虚拟物质进行的化学反应和8种虚拟反应，可大大减少CPU时间。