A fully automated strategy is discussed to construct reduced chemistry suitable for the numerical simulation of stationary combustion systems of large dimension, such as auto-thermal reforming (ATR) of natural gas for syngas production. Because of computing limitations in terms of space and time resolution, three-dimensional simulations of an ATR unit cannot be addressed with detailed chemistry. A procedure is proposed to automatically derive optimised and reduced chemical schemes under specific ATR operating conditions. A stochastic model problem is first designed to probe the dynamical response of a detailed chemical scheme, over a large range of chemical compositions of the mixture. Reference composition space trajectories are built, featuring turbulent micro-mixing and reactions. Following these trajectories, the chemical response is analysed using directed relation graphs with error propagation combined with quasi-steady state hypothesis, to reduce the number of species and elementary reactions. Then, the time evolution of the model problem is coupled with a genetic algorithm, to optimise on the fly the chemical rates of the reduced kinetics, according to the reference composition space trajectories. The accuracy of the reduced scheme is monitored with a fitness function and the results are tested against the reference detailed chemistry.

讨论了一种完全自动化的策略，以构建适用于大尺寸固定式燃烧系统的数值模拟的还原化学反应，例如用于合成气生产的天然气的自动热重整（ATR）。由于空间和时间分辨率方面的计算限制，ATR单元的三维模拟无法用详细的化学方法解决。提出了一种程序，可以在特定的ATR操作条件下自动得出优化和简化的化学方案。首先设计一个随机模型问题，以研究混合物的大范围化学成分下详细化学方案的动力学响应。建立参考成分空间轨迹，以湍流微混合和反应为特征。遵循这些轨迹，化学反应使用带有误差传播的有向关系图结合准稳态假设进行分析，以减少种类和基本反应的数量。然后，将模型问题的时间演化与遗传算法结合起来，根据参考成分空间轨迹动态地对还原动力学的化学速率进行优化。使用适应度函数监控简化方案的准确性，并根据参考详细化学测试结果。根据参考组成空间轨迹。使用适应度函数监控简化方案的准确性，并根据参考详细化学测试结果。根据参考组成空间轨迹。使用适应度函数监控简化方案的准确性，并根据参考详细化学测试结果。