scholarly journals Quantitative density measurement of M=2.0 suoersonic flow field around an asymmetric model using background oriented schlieren (BOS) technique

2009 ◽  
Vol 29-1 (2) ◽  
pp. 1309-1309
Author(s):  
Kenta HAMADA ◽  
Hiroko KATO ◽  
Ryusuke NODA ◽  
Masanori OTA ◽  
Kazuo MAENO
Keyword(s):  
Flow Field ◽  
Density Measurement ◽  
Asymmetric Model ◽  
Background Oriented Schlieren

scholarly journals Hybrid Adaptive Wavelet-Based Optical Flow Algorithm for Background Oriented Schlieren (BOS) Experiments

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Xin-yu Zhang ◽  
Li-Ming Wang ◽  
Bin Liu ◽  
Yue Luo ◽  
Xing-cheng Han
Keyword(s):  
Flow Field ◽  
Optical Flow ◽  
Measurement Technology ◽  
Refractive Index Gradient ◽  
Adaptive Wavelet ◽  
Flow Algorithm ◽  
Current Algorithm ◽  
Index Gradient ◽  
Background Oriented Schlieren ◽  
Flow Field Measurement

Quantitative analysis of the flow field is an effective method to study hydrodynamics. As a flow field measurement technology, the Background Oriented Schlieren (BOS) is widely used. However, it is difficult to measure the complex transparent flow field (flow field with large refractive index gradient) using the BOS experiment. In order to overcome this difficulty and improve the accuracy of the BOS experiment, this paper presents a hybrid adaptive wavelet-based optical flow algorithm for the BOS. The current algorithm is a combination of the traditional optical flow algorithm and the wavelet-based optical flow algorithm. By adding the initial value constraints, the adaptive scale constraints, and the adaptive regularization constraints, the algorithm can effectively overcome the above-mentioned difficulty and also improve its accuracy. To further illustrate the feasibility of the proposed method, this paper uses the simulation data, the data of the DNS datasets, and the data of the BOS experiment to verify the performance of the algorithm. The experiment of comparing the proposed algorithm with the existing ones is carried out on the DNS datasets and the data of the BOS experiment. Finally, the proposed method is verified by a practical BOS experiment. The results show that the proposed algorithm can effectively improve the measurement accuracy of displacements.

scholarly journals Extraction of a Weak Flow Field for a Multi-Rotor Unmanned Aerial Vehicle (UAV) Using High-Speed Background-Oriented Schlieren (BOS) Technology

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 43
Author(s):  
Xianglei Liu ◽  
Tongxin Guo ◽  
Pengfei Zhang ◽  
Zhenkai Jia ◽  
Xiaohua Tong
Keyword(s):  
Flow Field ◽  
Unmanned Aerial Vehicle ◽  
High Speed ◽  
Particle Image ◽  
Extraction Methods ◽  
Large Field ◽  
Image Velocimetry ◽  
Combustion Experiment ◽  
Aerial Vehicle ◽  
Background Oriented Schlieren

To optically capture and analyze the structure and changes of the flow field of a weak airflow object with high accuracy, this study proposes novel weak flow field extraction methods based on background-oriented schlieren. First, a fine background pattern texture and a sensor network layout were designed to satisfy the requirement of weak flow field extraction. Second, the image displacement was extracted by calculating the correlation matrix in the frequency domain for a particle image velocimetry algorithm, and further calculations were performed for the density field using Poisson’s equation. Finally, the time series baseline stacking method was proposed to obtain the flow field changes of weak airflow structures. A combustion experiment was conducted to validate the feasibility and accuracy of the proposed method. The results of a quad-rotor unmanned aerial vehicle experiment showed that the clear, uneven, and continuous quantitative laminar flow field could be obtained directly, which overcame the interference of the weak airflow, large field of view, and asymmetrical steady flow.

scholarly journals Numerical Uncertainty in Density Estimation for Background Oriented Schlieren

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Jiacheng Zhang ◽  
Lalit Rajendran ◽  
Sally Bane ◽  
Pavlos Vlachos
Keyword(s):  
Density Gradient ◽  
Systematic Uncertainty ◽  
Density Measurement ◽  
Random Errors ◽  
Target Pattern ◽  
Density Estimates ◽  
Total Uncertainty ◽  
Spatially Resolved ◽  
Background Oriented Schlieren ◽  
Good Agreement

Background Oriented Schlieren (BOS) is an image-based density measurement technique. BOS estimates the density gradient from the apparent distortion of a target pattern viewed through a medium with varying density using cross-correlation, tracking, or optical flow algorithms. The density gradient can then be numerically integrated to yield a spatially resolved estimate of the density [1]. A method was recently proposed to estimate the a-posteriori instantaneous and spatially resolved density uncertainty for BOS [2] and showed good agreement between the propagated uncertainties and the random error. However, the density uncertainty quantification method could not account for the systematic uncertainty in the density field due to the discretization errors introduced during the numerical integration, which could be much larger than the displacement random errors [2]. In this work, we propose a method to estimate the numerical uncertainty introduced by the density integration in BOS measurements, using a Richardson extrapolation framework. A procedure is also introduced to combine this systematic uncertainty with the random uncertainty from the previous work to provide an instantaneous, spatially-resolved total uncertainty on the density  estimates. The method will be tested with synthetic fields and synthetic BOS images.

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