Reduced combustion kinetic mechanisms, instead of detailed ones, are often used in computational fluid dynamics (CFD) simulations for reduced and frequently even affordable computational cost. The criterion for the evaluation of a reduced mechanism usually focuses on its prediction error for the global properties such as the ignition delay time, while ignoring the detailed features of reaction kinetics such as reaction pathways. In our opinion, good reduced mechanisms should have similar predicting behaviors as the detailed ones, and these behaviors include model predictions for specific targets, prediciton error bars, and uncertainty sources for the errors. In this work, a new approach using global sensitivity-based similarity analysis (GSSA) is proposed to compare reduced mechanisms with detailed ones. The similarity coefficient for the reduced mechanism is calculated by similarity method based on Euclidean distance between sensitivity indices of the reduced mechanism and those of the detailed mechanism. The larger the similarity coefficient, the higher the degree of similarity between the reduced and detailed mechanisms. To demonstrate this similarity method, directed relation graph with error propagation (DRGEP) is employed to simplify both the GRI 3.0 mechanism without the NOx chemistry and the JetSurF mechanism consisting of 1459 reactions, resulting in reduced mechanisms with different sizes which can accurately predict the ignition delay times for corresponding fuel mixtures. Similarity analysis is then employed to evaluate these reduced mechanisms. The result shows that the actual reaction kinetic features cannot be replicated by some of the reduced mechanisms. First, the rankings of the important reactions obtained by reduced mechanisms are not consistent with those obtained by the detailed mechanism. Second, by investigating the sensitive reactions, the actual impact of uncertainties in reaction rates on the ignition delay times cannot be presented by reduced mechanisms. The similarity analysis on reduced mechanisms can be used to select a reduced mechanism which shows much better performance to replicate the actual combustion reaction kinetics. GSSA can provide information on the uncertainty sources induced by the reactions parameters of reduced mechanisms for target predicitons, which is important for further reduced model optimization and for the sensitivity analysis of CFD simulations.

在计算流体动力学（CFD）模拟中通常使用降低的燃烧动力学机制（而不是详细的动力学机制）来减少并且通常甚至负担得起的计算成本。评估简化机构的标准通常集中在其对整体特性（如点火延迟时间）的预测误差上，而忽略了反应动力学（如反应路径）的详细特征。我们认为，良好的简化机制应具有与详细机制相似的预测行为，并且这些行为包括针对特定目标的模型预测，前提误差条和误差的不确定性源。在这项工作中，提出了一种使用基于全局敏感性的相似性分析（GSSA）的新方法来比较简化机制与详细机制。缩小机构的相似系数是基于缩小机构的灵敏度指标与详细机构的灵敏度指标之间的欧几里德距离，通过相似度方法来计算的。相似系数越大，简化后的机制与详细机制之间的相似度越高。为了证明这种相似性方法，采用带误差传播的有向关系图（DRGEP）来简化没有NOx化学作用的GRI 3.0机理和由1459个反应组成的JetSurF机理，从而减少了具有不同尺寸的机理，可以准确地预测点火相应燃料混合物的延迟时间。然后采用相似性分析来评估这些简化的机制。结果表明，实际的反应动力学特征不能通过某些简化的机理来复制。首先，通过简化机制获得的重要反应的排名与通过详细机制获得的重要反应的排名不一致。其次，通过研究敏感反应，无法通过简化的机制来表示反应速率不确定性对点火延迟时间的实际影响。还原机理的相似性分析可用于选择还原机理，该还原机理表现出更好的性能来复制实际的燃烧反应动力学。GSSA可以提供有关目标谓词的简化机制的反应参数所引起的不确定性来源的信息，这对于进一步简化模型优化和CFD模拟的敏感性分析非常重要。