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A novel method to automate FGM progress variable with application to igniting combustion systems
Combustion Theory and Modelling ( IF 1.9 ) Pub Date : 2019-10-15 , DOI: 10.1080/13647830.2019.1673902
Aromal Vasavan 1 , Philip de Goey 1 , Jeroen van Oijen 1
Affiliation  

This paper introduces a new method to formulate reaction progress variables for the application of FGM in combustion systems. The method involves a multiobjective optimisation to find a reaction progress variable that accurately reproduces complex reactive phenomenon of interest. In our current research, the method is applied to igniting non-premixed flames. The optimised progress variable combinations are evaluated for their accuracy in reproducing detailed chemistry results for the ignition of hydrocarbon fuels. Comparisons are made against conventional progress variable formulations used in the literature. The current approach takes into consideration the table resolution and error reduction for the application of FGM in combustion problems. Methods that rely on maximising the smoothness of the manifold or ensuring monotonic increase in progress variables alone are shown to be insufficient to capture ignition. The possibility of optimising the progress variable with emphasis on accurately resolving a particular zone or phase of combustion, such as ignition, while maintaining minimum data loss is demonstrated. Through its application in a number of igniting counterflow flames, the effectiveness of the current method is verified. Progress variables optimised using specific flame databases are shown to accurately reproduce the ignition delays even with moderate variations in boundary conditions of the respective flames.

中文翻译:

一种将 FGM 进程变量自动化并应用于点燃燃烧系统的新方法

本文介绍了一种为 FGM 在燃烧系统中的应用制定反应进程变量的新方法。该方法涉及多目标优化,以找到准确再现感兴趣的复杂反应现象的反应进程变量。在我们目前的研究中,该方法用于点燃非预混火焰。评估优化的进程变量组合在再现碳氢燃料点火的详细化学结果方面的准确性。与文献中使用的常规进度变量公式进行比较。当前的方法考虑了 FGM 在燃烧问题中的应用的表分辨率和误差减少。依赖于最大化流形平滑度或仅确保进程变量单调增加的方法被证明不足以捕获点火。展示了优化进程变量的可能性,重点是准确解析燃烧的特定区域或阶段,例如点火,同时保持最小的数据丢失。通过在多个点燃逆流火焰中的应用,验证了该方法的有效性。显示使用特定火焰数据库优化的进程变量即使在相应火焰的边界条件有适度变化的情况下也能准确再现点火延迟。展示了优化进程变量的可能性,重点是准确解析燃烧的特定区域或阶段,例如点火,同时保持最小的数据丢失。通过在多个点燃逆流火焰中的应用,验证了该方法的有效性。显示使用特定火焰数据库优化的进程变量即使在相应火焰的边界条件有适度变化的情况下也能准确再现点火延迟。展示了优化进程变量的可能性,重点是准确解析燃烧的特定区域或阶段,例如点火,同时保持最小的数据丢失。通过在多个点燃逆流火焰中的应用,验证了该方法的有效性。显示使用特定火焰数据库优化的进程变量即使在相应火焰的边界条件有适度变化的情况下也能准确再现点火延迟。
更新日期:2019-10-15
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