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Automated Chemical Mechanism Generation for Extinction Strain Rates Predictions with Applications in Flame Stabilization and Combustion Instabilities

机译:消光应变速率预测的自动化学机理生成及其在火焰稳定和燃烧不稳定性中的应用

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Despite the massive gains in computing power, predictive CFD codes for combustion - be it DNS or LES - are still constrained to use relatively small chemical kinetic mechanisms. Kinetic mechanisms used for these simulations are generally derived by reducing comprehensive models based on a target variable such as flame-speed or ignition delay that does not necessarily capture the chemistry of flame stabilization and combustion instabilities. In this paper, we generate skeletal kinetic mechanisms for flame stabilization using the Reaction Mechanism Generator (RMG) software, an automated rate-based tool for generating detailed chemical kinetic mechanisms. First, we provide examples of phenomena that scale with the extinction strain rate, highlighting the need for it to be a target variable for mechanisms describing flame stabilization in gas turbines. Next, we develop a skeletal mechanism for methane-air systems consisting of 21 reactive species and 148 reactions, and compare its performance with comprehensive literature models and experimental data. An efficient methane oxy-combustion mechanism is developed as well. We conclude by providing skeletal mechanism generation heuristics for larger fuels such as n-alkanes and show good agreement for extinction strain rate predictions for n-C_5H_(12), n-C_7H_(16), n-C_(10)H_(22), and n-C_(12)H_(26) compared to experimental results and a comprehensive model. The presented heuristics provide a novel and automated procedure to generate skeletal n-alkane mechanisms with about 27-36 reactive species each using the skeletal methane-air mechanism as a sub reaction network.
机译:尽管计算能力获得了巨大的进步,但用于燃烧的预测性CFD代码(无论是DNS还是LES)仍被限制为使用相对较小的化学动力学机制。通常通过基于目标变量(例如火焰速度或点火延迟)简化综合模型来推导用于这些模拟的动力学机制,这些目标变量不一定捕获火焰稳定和燃烧不稳定性的化学性质。在本文中,我们使用反应机理生成器(RMG)软件生成了用于火焰稳定的骨架动力学机理,这是一种基于速率的自动化工具,用于生成详细的化学动力学机理。首先,我们提供了随消光应变率成比例变化的现象的示例,强调了将其作为描述燃气轮机火焰稳定机理的目标变量的必要性。接下来,我们开发了由21个反应物种和148个反应组成的甲烷-空气系统的骨架机制,并将其性能与综合文献模型和实验数据进行了比较。还开发了一种有效的甲烷氧燃烧机理。我们通过提供较大的燃料(例如正构烷烃)的骨架机理启发法得出结论,并为n-C_5H_(12),n-C_7H_(16),n-C_(10)H_(22)的消光应变速率预测显示出良好的一致性,以及n-C_(12)H_(26)与实验结果和综合模型的比较。提出的启发式方法提供了一种新颖的自动化程序,可使用骨架甲烷-空气机制作为副反应网络来生成具有约27-36个反应物种的骨架正构烷烃机制。

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