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Seeding Bias in Particle Image Velocimetry Applied to Dual-Mode Scramjet

机译:粒子图像测速技术中的种子偏差应用于双模式超燃冲压发动机

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Uniform seeding is important for particle image velocimetry due to the fact that all velocity data are derived from the movement of particles as fluid tracers. However, in some wind tunnel applications, uniform seeding is not possible due to the severe fouling of windows. One such application is in the University of Virginia Supersonic Combustion Facility. Past particle image velocimetry measurements in this facility have potential velocity bias errors due to nonuniform seeding, since particles were only introduced in the fuel stream and not the freestream of a dual-mode scramjet combustor. The present study seeks to experimentally quantify the velocity bias errors associated with introducing seed particles into a single stream of a fuel and freestream mixing and combusting region of the scramjet flowpath. The velocity bias is quantified by measuring the velocity field at the combustor exit using stereoscopic particle image velocimetry under three seeding scenarios: 1) fuel stream only seeded, 2) fuel and freestream seeded, and 3) freestream only seeded. The case of seeding both the fuel and freestream was taken as the baseline, or most ideal solution. The results indicate that the effect of the seeding bias is relatively small since seeding the fuel only results in an average seeding bias error of 3.7% in mean velocity and 2.5% for the case of freestream only seeded. For the rms velocity, the average error induced by the seeding bias was 6.6 and 4.1%, respectively.
机译:由于所有速度数据均来自作为流体示踪剂的粒子的运动,因此均匀播种对于粒子图像测速非常重要。但是,在某些风洞应用中,由于窗户严重结垢,因此无法均匀播种。一种这样的应用是在弗吉尼亚大学超音速燃烧设施中。该设备中过去的粒子图像测速仪测量由于不均匀的播种而具有潜在的速度偏差误差,因为粒子仅被引入燃料流中,而不被引入双模式超燃冲压燃烧器的自由流中。本研究试图通过实验量化与将种子颗粒引入燃料的单流以及超燃冲压流路的自由流混合和燃烧区域相关的速度偏差误差。在三种播种情况下,通过使用立体粒子图像测速仪测量燃烧室出口处的速度场,可以量化速度偏差:1)仅播种燃料流,2)仅播种燃料和自由流,以及3)仅播种自由流。将燃料和自由流同时播种的情况作为基准或最理想的解决方案。结果表明,播种偏差的影响相对较小,因为播种燃料仅会导致平均速度的平均播种偏差误差为3.7%,仅自由流播种会导致2.5%。对于均方根速度,由种子偏置引起的平均误差分别为6.6%和4.1%。

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