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Analyzing and Tracking Burning Structures in Lean Premixed Hydrogen Flames

机译:分析和跟踪稀混合氢火焰中的燃烧结构

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This paper presents topology-based methods to robustly extract, analyze, and track features defined as subsets of isosurfaces. First, we demonstrate how features identified by thresholding isosurfaces can be defined in terms of the Morse complex. Second, we present a specialized hierarchy that encodes the feature segmentation independent of the threshold while still providing a flexible multiresolution representation. Third, for a given parameter selection, we create detailed tracking graphs representing the complete evolution of all features in a combustion simulation over several hundred time steps. Finally, we discuss a user interface that correlates the tracking information with interactive rendering of the segmented isosurfaces enabling an in-depth analysis of the temporal behavior. We demonstrate our approach by analyzing three numerical simulations of lean hydrogen flames subject to different levels of turbulence. Due to their unstable nature, lean flames burn in cells separated by locally extinguished regions. The number, area, and evolution over time of these cells provide important insights into the impact of turbulence on the combustion process. Utilizing the hierarchy, we can perform an extensive parameter study without reprocessing the data for each set of parameters. The resulting statistics enable scientists to select appropriate parameters and provide insight into the sensitivity of the results with respect to the choice of parameters. Our method allows for the first time to quantitatively correlate the turbulence of the burning process with the distribution of burning regions, properly segmented and selected. In particular, our analysis shows that counterintuitively stronger turbulence leads to larger cell structures, which burn more intensely than expected. This behavior suggests that flames could be stabilized under much leaner conditions than previously anticipated.
机译:本文提出了基于拓扑的方法,可以可靠地提取,分析和跟踪定义为等值面子集的特征。首先,我们演示如何根据摩尔斯复杂度定义由等值面阈值识别的特征。其次,我们提出了一种特殊的层次结构,该结构对与阈值无关的特征分割进行编码,同时仍提供灵活的多分辨率表示。第三,对于给定的参数选择,我们创建了详细的跟踪图,这些图表示了燃烧模拟中数百个时间步长中所有特征的完整演变。最后,我们讨论了一个用户界面,该界面将跟踪信息与分段等值面的交互式渲染相关联,从而可以对时间行为进行深入分析。我们通过分析在不同湍流水平下的贫氢火焰的三个数值模拟来证明我们的方法。由于其不稳定的性质,稀薄的火焰在被局部熄灭区域分隔的细胞中燃烧。这些电池的数量,面积和随时间的演变为了解湍流对燃烧过程的影响提供了重要的见识。利用层次结构,我们可以进行广泛的参数研究,而无需重新处理每组参数的数据。由此产生的统计数据使科学家能够选择适当的参数,并洞悉结果对参数选择的敏感性。我们的方法首次允许将燃烧过程的湍流与燃烧区域的分布进行定量关联,并进行适当的分段和选择。特别是,我们的分析表明,与直觉相反的湍流会导致更大的细胞结构,其燃烧的强度比预期的还要强烈。这种现象表明火焰可以在比以前预期的更稀薄的条件下稳定下来。

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