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Chemical model reduction under uncertainty

机译：不确定性下的化学模型简化

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摘要

A general strategy for analysis and reduction of uncertain chemical kinetic models is presented, and its utility is illustrated in the context of ignition of hydrocarbon fuel-air mixtures. The strategy is based on a deterministic analysis and reduction method which employs computational singular perturbation analysis to generate simplified kinetic mechanisms, starting from a detailed reference mechanism. We model uncertain quantities in the reference mechanism, namely the Arrhenius rate parameters, as random variables with prescribed uncertainty factors. We propagate this uncertainty to obtain the probability of inclusion of each reaction in the simplified mechanism. We propose probabilistic error measures to compare predictions from the uncertain reference and simplified models, based on the comparison of the uncertain dynamics of the state variables, where the mixture entropy is chosen as progress variable. We employ the construction for the simplification of an uncertain mechanism in an n-butane-air mixture homogeneous ignition case, where a 176-species, 1111-reactions detailed kinetic model for the oxidation of n-butane is used with uncertainty factors assigned to each Arrhenius rate pre-exponential coefficient. This illustration is employed to highlight the utility of the construction, and the performance of a family of simplified models produced depending on chosen thresholds on importance and marginal probabilities of the reactions. (C) 2017 The Combustion Institute. Published by Elsevier Inc. All rights reserved.
机译：提出了一种分析和简化不确定化学动力学模型的通用策略，并在点燃烃类燃料-空气混合物的背景下说明了其实用性。该策略基于确定性分析和归约方法，该方法采用计算奇异摄动分析来生成简化的动力学机制，从详细的参考机制开始。我们将参考机制中的不确定量（即Arrhenius速率参数）建模为具有规定不确定性因子的随机变量。我们传播这种不确定性，以获得简化机制中包含每个反应的可能性。基于状态变量的不确定动力学的比较，我们提出了概率误差度量来比较不确定参考和简化模型的预测，其中混合熵被选为进度变量。在正丁烷-空气混合物均质着火情况下，我们采用该构造简化了不确定机制，其中使用了176种，1111种反应的正丁烷氧化详细动力学模型，并为每个模型分配了不确定性因子阿累尼乌斯率指数前系数。该插图用于强调构造的实用性，以及根据所选重要性阈值和反应的边际概率生成的简化模型系列的性能。 （C）2017燃烧研究所。由Elsevier Inc.出版。保留所有权利。

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