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Possibilities and limitations of the ART-Sample algorithm for reconstruction of 3D temperature fields and the influence of opaque obstacles

机译:重建3D温度场的ART-Sample算法的可能性和局限性以及不透明障碍物的影响

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The need for the measurement of complex, unsteady, three-dimensional (3D) temperature distributions arises in a variety of engineering applications, and tomographic techniques are applied to accomplish this goal. Holographic interferometry (HI), one of the optical methods used for visualizing temperature fields, combined with tomographic reconstruction techniques requires multi-directional interferometric data to recover the 3D information. However, the presence of opaque obstacles (such as solid objects in the flow field and heaters) in the measurement volume, prevents the probing light beams from traversing the entire measurement volume. As a consequence, information on the average value of the field variable will be lost in regions located in the shade of the obstacle. The capability of the ART-Sample tomographic reconstruction method to recover 3D temperature distributions both in unobstructed temperature fields and in the presence of opaque obstacles is discussed in this paper. A computer code for tomographic reconstruction of 3D temperature fields from 2D projections was developed. In the paper, the reconstruction accuracy is discussed quantitatively both without and with obstacles in the measurement volume for a set of phantom functions mimicking realistic temperature distributions. The reconstruction performance is optimized while minimizing the number of irradiation directions (experimental hardware requirements) and computational effort. For the smooth temperature field both with and without obstacles, the reconstructions produced by this algorithm are good, both visually and using quantitative criteria. The results suggest that the location and the size of the obstacle and the number of viewing directions will affect the reconstruction of the temperature field. When the best performance parameters of the ART-Sample algorithm identified in this paper are used to reconstruct the 3D temperature field, the 3D reconstructions with and without obstacle are both excellent, and the obstacle has little influence on the reconstruction. The results indicate that the ART-Sample algorithm can successfully recover instantaneous 3D temperature distributions in the presence of opaque obstacles with only 4 viewing directions.
机译:在各种工程应用中,都需要测量复杂,不稳定的三维(3D)温度分布,并且使用层析成像技术来实现这一目标。全息干涉术(HI)是用于可视化温度场的一种光学方法,与层析成像重建技术相结合,需要多方向干涉数据来恢复3D信息。但是,测量空间中不透明的障碍物(例如流场中的固体物体和加热器)的存在会阻止探测光束穿过整个测量空间。结果,关于场变量平均值的信息将丢失在位于障碍物阴影处的区域中。本文讨论了ART样本层析成像重建方法在无障碍温度场和不透明障碍物存在下恢复3D温度分布的能力。开发了用于从2D投影进行3D温度场的层析成像重建的计算机代码。在本文中,定量地讨论了在模拟量逼近实际温度分布的一组幻像函数的测量体积中是否有障碍的重建精度。优化重建性能,同时最大程度地减少照射方向(实验硬件要求)和计算工作量。对于有障碍物和无障碍物的光滑温度场,无论是在视觉上还是使用定量标准,该算法产生的重建效果都很好。结果表明,障碍物的位置和大小以及观察方向的数量将影响温度场的重建。当使用本文确定的ART-Sample算法的最佳性能参数重建3D温度场时,有障碍物和无障碍物的3D重建都非常好,障碍物对重建的影响很小。结果表明,ART-Sample算法可以在只有4个观察方向的不透明障碍物的存在下成功恢复瞬时3D温度分布。

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