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Uncertainty analysis in mechanism reduction via active subspace and transition state analyses

机译:通过活跃子空间和转换状态分析的机制不确定性分析

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摘要

A systematic approach is formulated for the uncertainty analysis of kinetic parameters on combustion characteristics during skeletal reduction. The active subspace method together with sensitivity analysis is first employed to identify extreme low-dimensional active subspace of input parameter space and to facilitate the construction of response surfaces with small size of samples. An intermediate transi-tion state during reduction is then defined such that the uncertainty change arising from uncertainty parameter truncation and reaction coupling during reduction can be decoupled and quantified. The ap-proach is demonstrated in the reduction of a 55-species, 290-reaction dimethyl ether (DME) mechanism, with the rate constants characterized by independent lognormal distribution. Three representative skele -tal mechanisms are identified for the uncertainty analysis, with each of the subsequent reduction yielding significant errors in the single-stage and/or two-stage DME-air auto-ignition process. Results show that sensitivity analysis can reduce the number of kinetic parameters from 290 down to 32, and the active subspace method can further identify a dominant active direction within this 32-dimensional subspace, which greatly facilitates the polynomial fitting for constructing the response surface of the ignition delay times. The uncertainty analysis with the polynomial chaos expansion method shows that the reduction from DME42 with 42 species to DME40 with 40 species has influential effect on the high-temperature reaction pathway; while the reduction from DME55 to DME42 and from DME40 to DME30 mainly affects the low-temperature pathway. In addition, the uncertainty change associated with parameter truncation is shown to be proportional to the change in the most active direction, which could further accelerate uncertainty analysis.(c) 2021 The Combustion Institute. Published by Elsevier Inc. All rights reserved.
机译:系统的方法被配制成骨骼还原过程中的燃烧特性动力学参数的不确定性分析。敏感性分析活性子空间方法一起首先被用来识别的输入参数空间极端低维子空间活跃并促进响应面的与样品的小尺寸的结构。然后在还原过程中的中间跃迁-灰状态被限定为使得还原过程中的不确定性从参数截断和反应所产生的耦合的不确定性改变可以被分离,并且定量。对AP-proach证明在55种,290-反应的二甲醚(DME)机构的减速,具有速率常数,其特征在于独立的对数正态分布。三种代表性skele -tal机制被识别为不确定性分析,与每个随后的还原得到的单级和/或两级DME-空气自动点火过程显著错误。结果表明,灵敏度分析可以从290向下降低动力学参数的数目为32,和有源子空间方法可以在此32维子空间,极大地方便了多项式拟合用于构建的响应面内进一步识别主导活性方向点火延迟时间。与多项式混沌展开法表明,从DME42还原用42种DME40与40种对高温的反应途径有影响效果的不确定性数据;而从DME55到DME42和从DME40到DME30还原主要影响低温途径。此外,参数截断相关的不确定性的变化被示出为正比于最活跃的方向上的变化,这可能进一步加速不确定性分析。(C)2021的燃烧研究所。由elsevier Inc.保留所有权利发布。

著录项

  • 来源
    《Combustion and Flame》 |2021年第5期|135-146|共12页
  • 作者

    Su Xingyu; Ji Weiqi; Ren Zhuyin;

  • 作者单位

    Tsinghua Univ Ctr Combust Energy Beijing 100084 Peoples R China;

    Tsinghua Univ Ctr Combust Energy Beijing 100084 Peoples R China;

    Tsinghua Univ Ctr Combust Energy Beijing 100084 Peoples R China|Tsinghua Univ Inst Aero Engine Beijing 100084 Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Mechanism reduction; Uncertainty quantification; Active subspace; Transition state;

    机译:减少机制;不确定量化;活跃子空间;过渡状态;

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