使用 EPOD 方法改进超声波速度剖面仪的时间分辨率,优化时间分辨率传感器的位置

IF 2.3 3区 工程技术 Q2 ENGINEERING, MECHANICAL Experiments in Fluids Pub Date : 2024-10-25 DOI:10.1007/s00348-024-03903-z
Neetu Tiwari
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引用次数: 0

摘要

超声波速度剖面仪(UVP)可用于颗粒图像测速仪(PIV)无法应用的不透明和多相流。过去几十年来,随着高速摄像机的发展,PIV 的时间分辨率已大大提高,并通过数据驱动方法得到进一步改进。另一方面,UVP 的时间分辨率已经远远低于 PIV,因此很少有改进 UVP 时间分辨率的工作。本研究提出了一种改进 UVP 测量时间分辨率的概念验证,使用的是一种带有优化传感器的扩展正交分解(EPOD)方法。在本研究中,通过将 EPOD 方法与传感器选择方法相结合对其进行了改进,消除了 Discetti 等人 2018 年在 Hosseini 等人 2015 年的原始工作中引入的基于规则的三Σ(\(\sigma\))滤波。在本研究中,使用传感器选择方法优化传感器位置,并使用 EPOD 方法重建时间分辨流场。通过两种传感器选择方法:行列式贪心(DG)和基于贝叶斯行列式的贪心(BDG),使用非时间分辨的 UVP 速度数据优化了沿线的传感器位置。比较了 DG 和 BDG 优化传感器在重建时间分辨流场方面的性能。该技术用两组圆柱体上的流动实验数据进行了演示:第一组是 PIV 数据,这些数据在时域中进行了下采样,并沿一条线采样以模拟 UVP 数据;第二组是在圆柱体尾部进行的实际 UVP 实验数据。研究发现,EPOD 方法的时间分辨重建能力取决于传感器的位置,两种传感器选择方法的结果相似。
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Time resolution improvement of ultrasonic velocity profiler for flow over cylinder using EPOD method with optimally placed time-resolved sensors

Ultrasonic velocity profiler (UVP) can be used for opaque and multiphase flows where particle image velocimetry (PIV) cannot be applied. The time resolution of PIV has greatly improved over the last few decades with the development of high-speed cameras and has been further improved using data-driven approaches. On the other hand, there have been very few works to improve the time resolution of UVP, which is already much lower than that of PIV. This study presents a proof of concept for time resolution improvement of UVP measurement, using an extended proper orthogonal decomposition (EPOD) method with optimized sensors. In this study, the EPOD method is improved by combining it with the sensor selection method, which eliminates the three-sigma (\(\sigma\)) rule-based filtering introduced by Discetti et al. 2018 in the original work of Hosseini et al. 2015. In this study, sensor locations are optimized using sensor selection methods, and time-resolved flow fields are reconstructed using the EPOD method. The sensors’ locations along the line are optimized using non-time-resolved UVP velocity data by two sensor selection methods: determinant greedy (DG) and Bayesian determinant-based greedy (BDG). The performance of DG and BDG-optimized sensors is compared in reconstructing time-resolved flow fields. The technique is demonstrated with two sets of experimental data of flow over a cylinder: first, PIV data, which are down-sampled in the time domain and sampled along a line to mimic the UVP data, and second, actual UVP experimental data conducted in the wake of cylinder. The EPOD method’s time-resolved reconstruction capability was found to depend on the sensors’ location, and both sensor selection methods yielded similar results.

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来源期刊
Experiments in Fluids
Experiments in Fluids 工程技术-工程:机械
CiteScore
5.10
自引率
12.50%
发文量
157
审稿时长
3.8 months
期刊介绍: Experiments in Fluids examines the advancement, extension, and improvement of new techniques of flow measurement. The journal also publishes contributions that employ existing experimental techniques to gain an understanding of the underlying flow physics in the areas of turbulence, aerodynamics, hydrodynamics, convective heat transfer, combustion, turbomachinery, multi-phase flows, and chemical, biological and geological flows. In addition, readers will find papers that report on investigations combining experimental and analytical/numerical approaches.
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