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Systematic errors in mixing measurements using filtered Rayleigh scattering in supersonic flows
Experiments in Fluids ( IF 2.4 ) Pub Date : 2020-05-14 , DOI: 10.1007/s00348-020-02956-0
Vijay Gopal , Luca Maddalena

Abstract When performing non-reacting mixing enhancement experimental studies in supersonic flow, helium is often used as an injectant which serves as a simulant gas for hydrogen fuel. The resulting distribution of helium mole fraction in the binary mixture of air and helium can be quantified using filtered Rayleigh scattering (FRS). The FRS technique requires two independent experiments in supersonic flow, one with helium injection and the other with air injection. The helium mole fraction is retrieved under the key assumptions that the number density profiles and the extent of the Doppler shift that is associated with each of the two independent experiments at the measuring plane are identically the same. This work is centered on the analysis of the impact of a departure from the aforementioned assumptions with the aid of a reduced-order model developed for a canonical rectangular jet in supersonic flow. The results, derived from the implementation of the model, are used to identify key driving phenomena that concurrently contribute to violate the key assumptions and are compared and discussed in the light of available experimental data. Additionally, the analysis suggests that the newly developed model can be used in the design of FRS experiments by minimizing the extent of mismatch in the number density profile and thus reducing the systematic bias error associated with the mixture’s composition measurements. Graphic abstract

中文翻译:

在超音速流动中使用滤波瑞利散射进行混合测量的系统误差

摘要 在超音速流动中进行非反应混合增强实验研究时,氦气通常用作注入剂,用作氢燃料的模拟气体。可以使用过滤瑞利散射 (FRS) 量化空气和氦气二元混合物中氦摩尔分数的最终分布。FRS 技术需要在超音速流动中进行两次独立的实验,一次使用氦气注入,另一次使用空气注入。在关键假设下检索氦摩尔分数,即与测量平面上的两个独立实验中的每一个相关的数密度分布和多普勒频移程度完全相同。这项工作的中心是借助为超音速流中的规范矩形射流开发的降阶模型来分析偏离上述假设的影响。来自模型实施的结果用于识别同时导致违反关键假设的关键驾驶现象,并根据可用的实验数据进行比较和讨论。此外,分析表明,新开发的模型可用于设计 FRS 实验,方法是最大限度地减少数密度分布中的不匹配程度,从而减少与混合物成分测量相关的系统偏差误差。图形摘要 用于识别同时导致违反关键假设的关键驾驶现象,并根据可用的实验数据进行比较和讨论。此外,分析表明,新开发的模型可用于设计 FRS 实验,方法是最大限度地减少数密度分布中的不匹配程度,从而减少与混合物成分测量相关的系统偏差误差。图形摘要 用于识别同时导致违反关键假设的关键驾驶现象,并根据可用的实验数据进行比较和讨论。此外,分析表明,新开发的模型可用于设计 FRS 实验,方法是最大限度地减少数密度分布中的不匹配程度,从而减少与混合物成分测量相关的系统偏差误差。图形摘要 分析表明,新开发的模型可用于 FRS 实验的设计,方法是最大限度地减少数密度分布中的失配程度,从而减少与混合物成分测量相关的系统偏差误差。图形摘要 分析表明,新开发的模型可用于 FRS 实验的设计,方法是最大限度地减少数密度分布中的不匹配程度,从而减少与混合物成分测量相关的系统偏差误差。图形摘要
更新日期:2020-05-14
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