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Assessment of different chemistry reduction methods based on principal component analysis: Comparison of the MG-PCA and score-PCA approaches

机译:基于主成分分析的不同化学还原方法的评估:MG-PCA和Score-PCA方法的比较

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摘要

Two families of PCA based combustion model were recently developed: score-PCA and MG-PCA. This paper presents the first comparative study of the two aftermentioned methods. Both methods are first benchmarked on 1-D laminar flames of hydrogen-air and syngas-air, to verify the consistency of the approaches. The sensitivity to differential diffusion is carefully addressed and a rotation technique is proposed, to allow for using score-PCA with differential diffusion. Then, 2-D flame-turbulence interactions are considered, spanning a wide range of velocity and length scale ratios, to demonstrate the ability of PC-based combustion models to efficiently capture the behavior of different combustion regimes, from flamelet-like flames to distributed reaction regimes.
机译:最近开发了两个基于PCA的燃烧模型家族:score-PCA和MG-PCA。本文介绍了后两种方法的首次比较研究。两种方法都首先以氢-空气和合成气-空气的一维层流为基准,以验证方法的一致性。仔细解决了对微分扩散的敏感性问题,并提出了一种旋转技术,以允许使用带微分扩散的得分PCA。然后,考虑了二维火焰-湍流相互作用,涵盖了广泛的速度和长度比例比,以证明基于PC的燃烧模型能够有效地捕获从小火焰状火焰到分布的不同燃烧状态的行为的能力。反应体系。

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