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Impact of Kinetic Uncertainties on Accurate Prediction of NO Concentrations in Premixed Alkane-Air Flames

机译：动力学不确定因素对预混合烷烃 - 空气火焰无浓度的准确预测

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摘要

Accurate thermochemical mechanisms that can predict the formation of nitrogen oxides (NO) are important design tools for low-emissions engines. The lack of accurate direct measurements of reaction rates and the associated measurement scatter have resulted in recommended rate parameters for individual chemical reactions that have large uncertainty intervals. In an effort to quantify the impact of these parametric uncertainties on emissions predictions, forward uncertainty propagation is performed with five spectral methods. Sparse grids are identified as the optimal technique to rapidly construct accurate surrogate models. Subsequent polynomial expansions with sparse grids, performed in one-dimensional atmospheric laminar flames for only the 30 uncertain reactions that greatly affect NO formation, produce uncertainty intervals two orders of magnitude larger than nominal predictions. Primary uncertainty sources were identified with reaction pathway analyses to evaluate the contribution of individual formation routes and the uncertainties in prompt NO were found to propagate mostly from the CH chemistry. These results highlight the necessity of a comprehensive approach, using experimental measurements with uncertainty quantification and inference techniques, to reduce uncertainty and develop predictive NO models.
机译：可以预测氮氧化物形成（NO）的准确热化学机制是用于低排放发动机的重要设计工具。对反应速率的准确直接测量和相关的测量散射缺乏导致具有大不确定性间隔的个体化学反应的推荐速率参数。为了量化这些参数不确定因子对排放预测的影响，使用五种光谱方法进行前进的不确定性繁殖。稀疏网格被识别为快速构建准确的代理模型的最佳技术。随后具有稀疏栅格的多项式膨胀，在一维大气层流体中进行，仅为30个不确定的反应在大量影响不影响的30个不确定的反应中，产生不确定的间隔比标称预测大的两个数量级。用反应途径鉴定初级不确定性来源，以评估各个地层路线的贡献，并发现提示的不确定性否则不会从CH化学传播。这些结果突出了使用具有不确定性量化和推理技术的实验测量的综合方法的必要性，以减少不确定性并开发预测的没有模型。

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