瞬态惰性喷雾多相流仿真的降阶模型
A Reduced-order Model for Multiphase Simulation of Transient Inert Sprays
摘要：
在减少运输部门有害温室气体排放的全球努力中，来自可再生能源和碳源的新型生物混合液体燃料由于其高能量密度而可以成为未来推进系统的主要能量形式。对燃烧系统中新燃料候选物的喷雾和混合性能的基本理解对于设计和开发用于先进燃烧概念的燃料是必要的。在燃料设计过程中，需要对大量候选燃料进行筛选，以确定可能的燃料，供进一步详细调查。对于这样的筛选过程，三维（3D）模拟模型在计算上太昂贵，因此不可行。因此，在本文中，我们提出了一个快速，降阶模型（ROM）的惰性喷雾。该模型基于Wan（1997）从三维多相方程导出的横截面平均喷雾（CAS）模型。最初的模型是针对广泛的条件和不同的燃料进行测试的。CAS模型和实验数据之间的差异是通过整合国家的最先进的破碎和蒸发模型。提出了一个适用于蒸发模拟的蒸汽质量分数输运方程。此外，该模型被扩展到考虑多分散液滴的液滴尺寸分布建模常用的假设概率密度函数，如Rosin-Rammler，对数正态分布，和伽马分布。改进的CAS模型能够预测各种条件和燃料的宏观喷雾特性的趋势。CAS模型的计算成本比3D模拟方法低多达6个数量级，具体取决于方法。这使得该模型不仅可用于快速筛选新的候选燃料，而且可用于ROM有用的其他应用。
英文摘要：
In global efforts to reduce harmful greenhouse gas emissions from the transport sector, novel bio-hybrid liquid fuels from renewable energy and carbon sources can be a major form of energy for future propulsion systems due to their high energy density. A fundamental understanding of the spray and mixing performance of the new fuel candidates in combustion systems is necessary to design and develop the fuels for advanced combustion concepts. In the fuel design process, a large number of candidates is required to be screened to arrive at potential fuels for further detailed investigations. For such a screening process, three-dimensional (3D) simulation models are computationally too expensive and hence unfeasible. Therefore, in this paper, we present a fast, reduced-order model (ROM) for inert sprays. The model is based on the cross-sectionally averaged spray (CAS) model derived by Wan (1997) from 3D multiphase equations. The original model was first tested against a wide range of conditions and different fuels. The discrepancies between the CAS model and experimental data are addressed by integrating state-of-the-art breakup and evaporation models. A transport equation for vapor mass fraction is proposed, which is important for evaporation modeling. Furthermore, the model is extended to consider polydisperse droplets by modeling the droplet size distribution by commonly used presumed probability density functions, such as Rosin-Rammler, lognormal, and gamma distributions. The improved CAS model is capable of predicting trends in the macroscopic spray characteristics for a wide range of conditions and fuels. The computational cost of the CAS model is lower than the 3D simulation methods by up to 6 orders of magnitude depending on the method. This enables the model to be used not only for the rapid screening of novel fuel candidates, but also for other applications, where ROMs are useful.
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