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Quantifying uncertainty in kinetic simulation of engine autoignition

机译:量化发动机自燃的动力学模拟中的不确定性

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Combustion chemistry models have been developed with inherent uncertainties in them. Whether a model that is developed using fundamental combustion experiments is capable to reproduce practical combustion processes within typical levels of measurement uncertainty is an open question. This paper quantifies the uncertainty of engine autoignition simulation using the uncertainties in the selected chemical kinetic model and then minimizes the model prediction uncertainty using various experiments. The method adopts a deterministic framework of uncertainty quantification, termed bound-to-bound data collaboration, and applies it to simulate the autoignition of n-pentane in a standard octane rating experiment. The results show that simulation of the end-gas autoignition using a comprehensively tested n-pentane model coupled with a two-zone engine combustion model yields an uncertainty substantially higher than that of engine experiment (as indicated by the cycle-to-cycle variation of the autoignition timing measurement). In-cylinder thermochemical conditions are found to be less important than the kinetic parameters in determining the model uncertainty. The large model uncertainty can be reduced by constraining the simulation with consistent experimental data and their measurement uncertainties, including those from fundamental experiments that measure ignition delays, species concentrations, flame speeds, and more significantly from autoignition experiments in well-calibrated engines. (C) 2020 The Combustion Institute. Published by Elsevier Inc. All rights reserved.
机译:燃烧化学模型已经发展出具有固有的不确定性。使用基本燃烧实验开发的模型是否能够在典型的测量水平范围内重现实际的燃烧过程,是一个开放的问题。本文使用所选化学动力学模型中的不确定性来定量发动机自燃仿真的不确定性,然后使用各种实验最小化模型预测不确定性。该方法采用确定性的不确定量化框架,称为绑定到绑定的数据协作,并应用其在标准辛烷值额定实验中模拟正戊烷的自燃。结果表明,使用与双区发动机燃烧模型耦合的综合测试的N-戊烷模型的终端气体自燃产生的不确定性基本上高于发动机实验的不确定性(如通过循环到循环变化所示)自动计时测量)。圆柱体的热化学条件被发现比确定模型不确定性的动力学参数更重要。通过限制具有一致的实验数据的模拟及其测量不确定性,可以减少大型模型不确定度,包括从良好校准的发动机中的自燃实验中测量点火延迟,物种浓度,火焰速度,并且更显着的基本实验。 (c)2020燃烧研究所。由elsevier Inc.出版的所有权利保留。

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