A methodology for improving both performance and measurement errors in PIV

Maceas, M.; Osorio, Andrés F.; Bolanos, Freddy

doi:10.1016/j.flowmeasinst.2020.101846

Cited by 9 publications

(2 citation statements)

References 26 publications

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“…Accurate and efficient measurement of fluid flow velocity in experiments according to the study of M. Maceas et al, Is a PIV application [8]. This application is a non-invasive type of application that can provide an estimate of the flow rate in some area points up to 55%.…”

Section: Sintek Jurnal: Jurnal Ilmiah Teknik Mesinmentioning

confidence: 99%

Effect of Cylinder Surface Roughness to the Distance Formation of Vortex

Heriyani

Mugisidi

Hilmi

2020

sintek. jurnal. ilm. teknik. mesin

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Reduction of cylinder surface resistance can be accomplished by modifying roughness. The surface roughness structure is one of the important parameters which greatly affects the flow of fluid through the cylinder surface. Fluid flow forms a vortex flow pattern with certain characteristics. Therefore, this study aims to analyze the characteristics and effects of fluid flow through the rough surface of the outer wall of the pipe with visualization using Particle Image Velocity (PIV). This research was conducted experimentally at the Faculty of Engineering, UHAMKA. The pipe surface roughness values varied were 0.648 µm and 1.699 µm. The length of the pipe used is 20 cm with a diameter of 2 inches. Measurements are made from the center of the pipe to a distance of 0.16 m. The results show that the surface roughness of the cylinder pipe affects the fluid flow characteristics where the formation of eddies is caused by the addition of the roughness value. The rougher the pipe surface is, the farther the vortex formation will be. The vortex formation closest to the pipe is a pipe with a roughness value of 0.648 µm at a distance of 0.04 m.

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Section: Sintek Jurnal: Jurnal Ilmiah Teknik Mesinmentioning

confidence: 99%

Effect of Cylinder Surface Roughness to the Distance Formation of Vortex

Heriyani

Mugisidi

Hilmi

2020

sintek. jurnal. ilm. teknik. mesin

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“…For non-contact flow measurement techniques, the representative ones are Acoustic Doppler Current Profiler (ADCP) [ 2 ], particle image velocimetry (PIV) [ 3 ], large-scale particle image velocimetry (LSPIV) [ 4 ], feature matching velocimetry (FMV) [ 5 ], optical flow (OF) [ 6 ], and space-time image velocimetry (STIV) [ 7 , 8 , 9 , 10 , 11 ], the last five of which is river surface image velocimetry that uses the movement of artificially added tracer particles or visible "natural" features on the water surface (e.g., eddies, ripples, or other floats) to achieve non-contact measurement of surface velocity distributions. Surface velocity data can be gathered for extended periods of time using image-based velocimetry without the need for hydrographic workers to be on duty.…”

Section: Introductionmentioning

confidence: 99%

Velocity Vector Estimation of Two-Dimensional Flow Field Based on STIV

Yang

Wang

2023

Sensors

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As an important part of hydrometry, river discharge monitoring plays an irreplaceable role in the planning and management of water resources and is an essential element and necessary means of river management. Due to its benefits of simplicity, efficiency and safety, Space-Time Image Velocimetry (STIV) has attracted attention from all around the world. The most crucial component of the STIV is the detection of the Main Orientation of Texture (MOT), and the precision of detection directly affects the results of calculations. However, due to the complicated river flow characteristics and the harsh testing environment in the field, a large amount of noise and interfering textures show up in the space-time images, which affects the detection results of the MOT. In response to the shortage of noise and interference texture, a new non-contact image analysis method is developed. Firstly, Multi-scale Retinex (MSR) is proposed to pre-process the images for contrast enhancement; secondly, a fourth-order Gaussian derivative steerable filter is employed to enhance the structure of the texture; next, based on the probability density distribution function and the orientations of the enhanced images, the noise suppression function and the orientation-filtering function are designed to filter out the noise to highlight the texture. Finally, the Fourier Maximum Angle Analysis (FMAA) is used to filter out the noise further and obtain the clear orientations to achieve the measurement of velocity and discharge. The experimental results show that, compared with the widely used image velocimetry measurements, the accuracy of our method in the average velocity and flow discharge is significantly improved, and the real-time performance is excellent.

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Experimental research on the impact of annular airflow on the spraying flow field: A source control technology of paint mist

Wang

Liu

et al. 2022

Building and Environment

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A methodology for improving both performance and measurement errors in PIV

Cited by 9 publications

References 26 publications

Effect of Cylinder Surface Roughness to the Distance Formation of Vortex

Effect of Cylinder Surface Roughness to the Distance Formation of Vortex

Velocity Vector Estimation of Two-Dimensional Flow Field Based on STIV

Experimental research on the impact of annular airflow on the spraying flow field: A source control technology of paint mist

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