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首页> 外文期刊>Energy & fuels >H Radical Sensitivity-Assisted Automatic Chemical Kinetic Model Reduction for Laminar Flame Chemistry Retaining: A Case Study of Gasoline-DME Mixture under Engine Conditions
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H Radical Sensitivity-Assisted Automatic Chemical Kinetic Model Reduction for Laminar Flame Chemistry Retaining: A Case Study of Gasoline-DME Mixture under Engine Conditions

机译:用于层流火焰化学保留的H自由基辅助化学反应动力学自动还原:以发动机条件下的汽油-DME混合物为例

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摘要

Flame propagation commonly exists in a wide range of engine operating modes. In chemical kinetic model reduction, the prediction of flame speeds must be targeted when engines involve flame propagation. However, the time-consuming nature of 1-D flame code running largely limits the feasibility of trial-and-error type reduction approaches. In this study, an improved automatic reduction scheme is proposed by adding a normalized H radical sensitivity with rate constants. By comparison with flame speed sensitivity, the combination of H radical and flame speed sensitivity can be more accurate to construct the species group relevant to laminar flame chemistry. Then, the newly proposed reduction methodology is applied for the spark ignition-controlled autoignition hybrid combustion (SCHC) with dimethyl ether (DME) as the pilot injection into gasoline, which proves promising in the engine performance by flexible controlling and stabilizing the combustion process. By constructing a new detailed chemical kinetic model for PRF-DME mixtures (348 species), a 143-species skeletal model is developed by considering both ignition and laminar flame. 3D-CFD simulations of experimental SCHC cases show that the detailed and skeletal models can capture the engine phenomena accurately. The results of a 103-species skeletal model reduced without flame speed target indicate that the flame propagation must be emphasized in the SCHC mode.
机译:火焰传播通常存在于多种发动机工作模式中。在化学动力学模型简化中,当发动机涉及火焰传播时,必须针对火焰速度的预测。但是,一维火焰代码运行的耗时性极大地限制了试错类型减少方法的可行性。在这项研究中,通过添加具有速率常数的归一化H自由基敏感性,提出了一种改进的自动还原方案。通过与火焰速度敏感性比较,H自由基和火焰速度敏感性的组合可以更准确地构建与层流火焰化学相关的物种组。然后,将新提出的还原方法应用于以二甲醚(DME)为先导喷射到汽油中的火花点火控制自燃混合燃烧(SCHC),通过灵活地控制和稳定燃烧过程,证明在发动机性能方面很有希望。通过为PRF-DME混合物(348种)构建新的详细化学动力学模型,通过考虑点火和层流火焰,开发了143种骨骼模型。实验性SCHC案例的3D-CFD模拟表明,详细的骨架模型可以准确地捕获发动机现象。在没有火焰速度目标的情况下减少了103种骨骼模型的结果表明,在SCHC模式下必须强调火焰传播。

著录项

  • 来源
    《Energy & fuels》 |2019年第4期|3551-3556|共6页
  • 作者单位

    Univ Calif Berkeley, Dept Mech Engn, Berkeley, CA 94720 USA;

    Tianjin Univ, State Key Lab Engines, Tianjin 300072, Peoples R China;

    Tianjin Univ, State Key Lab Engines, Tianjin 300072, Peoples R China;

    Univ Calif Berkeley, Dept Mech Engn, Berkeley, CA 94720 USA;

    Tianjin Univ, State Key Lab Engines, Tianjin 300072, Peoples R China;

    Univ Calif Berkeley, Dept Mech Engn, Berkeley, CA 94720 USA;

  • 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
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