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Assessing impacts of discrepancies in model parameters on autoignition model performance: A case study using butanol

机译：评估模型参数差异对自燃模型性能的影响：使用丁醇的案例研究

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摘要

Side-by-side comparison of detailed kinetic models using a new tool to aid recognition of species structures reveals significant discrepancies in the published rates of many reactions and thermochemistry of many species. We present a first automated assessment of the impact of these varying parameters on observable quantities of interest-in this case, autoignition delay-using literature experimental data. A recent kinetic model for the isomers of butanol was imported into a common database. Individual reaction rate and thermodynamic parameters of species were varied using values encountered in combustion models from recent literature. The effects of over 1600 alternative parameters were considered. Separately, experimental data were collected from recent publications and converted into the standard YAML-based ChemKED format. The Cantera-based model validation tool, PyTeCK, was used to automatically simulate autoignition using the generated models and experimental data, to judge the performance of the models. Taken individually, most of the parameter substitutions have little effect on the overall model performance, although a handful have quite large effects, and are investigated more thoroughly. Additionally, models varying multiple parameters simultaneously were evolved using a genetic algorithm to give fastest and slowest autoignition delay times, showing that changes exceeding a factor of 10 in ignition delay time are possible by cherry-picking from only accepted, published parameters. All data and software used in this study are available openly. (C) 2017 The Combustion Institute. Published by Elsevier Inc. All rights reserved.
机译：使用新工具帮助识别物种结构的详细动力学模型的并排比较显示，许多物种的许多反应和热化学的公布速率存在显着差异。我们提出了对这些可变参数对可观察到的感兴趣量的影响的首次自动评估-在这种情况下，是使用文献实验数据进行的自动点火延迟。丁醇异构体的最新动力学模型已导入一个公共数据库。使用最新文献中的燃烧模型中遇到的值来改变物种的个体反应速率和热力学参数。考虑了超过1600个替代参数的影响。另外，从最近的出版物中收集了实验数据，并将其转换为基于YAML的标准ChemKED格式。基于Cantera的模型验证工具PyTeCK用于使用生成的模型和实验数据自动模拟自燃，以判断模型的性能。单独考虑，大多数参数替换对整体模型性能几乎没有影响，尽管少数几个具有相当大的影响，并且进行了更彻底的研究。此外，使用遗传算法对同时改变多个参数的模型进行了演化，以给出最快和最慢的自动点火延迟时间，这表明，仅从已接受的公开参数中挑选樱桃，就可以使点火延迟时间的变化超过10倍。本研究中使用的所有数据和软件均可公开获得。 （C）2017燃烧研究所。由Elsevier Inc.出版。保留所有权利。

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