Numerical and experimental comparison of 3D Particle Tracking Velocimetry (PTV) and Particle Image Velocimetry (PIV) accuracy for indoor airflow study

Fu, Sijie; Biwolé, Pascal Henry; Mathis, Christian

doi:10.1016/j.buildenv.2016.02.002

Cited by 21 publications

(6 citation statements)

References 25 publications

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“…Some previous works have used a smoke technique (Calautit and Hughes 2014 ; Wagner and Schreiber 2014 ; Yin et al 2016 ) or particle image velocimeter (PIV) method (Fu et al 2016 ; Li et al 2016a , 2015b ; Reyes et al 2015 ) to visualize the airflow. However, due to the enormous investment cost needed to conduct a PIV experiment in a full-scale chamber, this approach is rarely used (Huang et al 2021 ).…”

Section: Current Assessment Of Airflow and Particle Concentration In ...mentioning

confidence: 99%

Current and potential approaches on assessing airflow and particle dispersion in healthcare facilities: a systematic review

Tan

Wong

Othman

et al. 2022

Environ Sci Pollut Res

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An indoor environment in a hospital building requires a high indoor air quality (IAQ) to overcome patients’ risks of getting wound infections without interrupting the recovery process. However, several problems arose in obtaining a satisfactory IAQ, such as poor ventilation design strategies, insufficient air exchange, improper medical equipment placement and high door opening frequency. This paper presents an overview of various methods used for assessing the IAQ in hospital facilities, especially in an operating room, isolation room, anteroom, postoperative room, inpatient room and dentistry room. This review shows that both experimental and numerical methods demonstrated their advantages in the IAQ assessment. It was revealed that both airflow and particle tracking models could result in different particle dispersion predictions. The model selection should depend on the compatibility of the simulated result with the experimental measurement data. The primary and secondary forces affecting the characteristics of particle dispersion were also discussed in detail. The main contributing forces to the trajectory characteristics of a particle could be attributed to the gravitational force and drag force regardless of particle size. Meanwhile, the additional forces could be considered when there involves temperature gradient, intense light source, submicron particle, etc. The particle size concerned in a healthcare facility should be less than 20 μm as this particle size range showed a closer relationship with the virus load and a higher tendency to remain airborne. Also, further research opportunities that reflect a more realistic approach and improvement in the current assessment approach were proposed.

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Section: Current Assessment Of Airflow and Particle Concentration In ...mentioning

confidence: 99%

Current and potential approaches on assessing airflow and particle dispersion in healthcare facilities: a systematic review

Tan

Wong

Othman

et al. 2022

Environ Sci Pollut Res

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“…Besides, the application of HWA is strictly probe dimensions dependent, viz., it makes the flow dynamic measurement within a highly compact HVAC finned-tube heat exchangers of about 1.5 to 2.0 mm inter-fin spacing impossible. Alternatively, tracer-based optical velocimetry, e.g., PIV and PTV, enables non-intrusive flow velocity detection in a global domain, which allows the realization of flow velocity through the reconstruction of optically sensed tracer particles’ displacements in flow 26 , 46 – 48 .…”

Section: Introductionmentioning

confidence: 99%

SPTV sheds light on flow dynamics of fractal-induced turbulence over a plate-fin array forced convection

Hoi

Ooi

Chew

et al. 2022

Sci Rep

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A 3D stationary particle tracking velocimetry (SPTV) with a unique recursive corrective algorithm has been successfully established to detect the instantaneous regional fluid flow characteristics. The veracity of SPTV is corroborated by conducting actual displacement measurement validation, which gives a maximum percentage deviation of about 0.8%. This supports the accuracy of the current SPTV system in 3D position detection. More importantly, the SPTV detected velocity fluctuations are highly repeatable. In this study, SPTV is proven to be able to express the nature of chaotic fractal grid-induced regional turbulence, namely: the high turbulence intensity attributed to multilength-scale wake interactions, the Kolmogorov’s −5/3 law decay, vortex shedding, and the Gaussian flow undulations immediately leeward of the grid followed by non-Gaussian behaviour further downstream. Moreover, by comparing the flow fields between control no-grid and fractal grid-generated turbulence of a plate-fin array, SPTV reveals vigorous turbulence intensity, smaller regional integral-length-scale, and energetic vortex shedding at higher frequency for the latter, particularly between fins. Thereupon, it allows the unravelling of detailed thermofluid interplays of plate-fin heat sink heat transfer augmentation. The novelty of SPTV lies in its simplicity, use of low-cost off-the-shelf components, and most remarkably, low computational complexity in detecting fundamental characteristics of turbulent fluid flow.

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“…PTV technology [11]- [12] is a common multiphase flow velocity measurement technology, which attracts the attention of many scholars. Fu et al analyzed measurement performances of 3D-PTV and typical 2D-particle image velocimetry (PIV) algorithm on laminar macroscopic flow with three known displacements, and applied two algorithms to the indoor low turbulence experiment generated by low-speed exhaust pipes for comparison [13]. The results show that the 3D-PTV algorithm has better velocity measurement ability than the 2D-PIV algorithm when the tracking particle density is greater than 2 and the particle density increases gradually.…”

Section: Introductionmentioning

confidence: 99%

Oil Phase Velocity Measurement of Oil-Water Two-Phase Flow with Low Velocity and High Water Cut Using the Improved ORB and RANSAC Algorithm

Han

Wang

Yao

et al. 2020

Measurement Science Review

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Velocity is an important parameter for fluid flow characteristics in profile logging. Particle tracking velocimetry (PTV) technology is often used to study the flow characteristics of oil wells with low flow velocity and high water cut, and the key to PTV technology is particle matching. The existing particle matching algorithms of PTV technology do not meet the matching demands of oil drops in the oil phase velocity measurement of oil-water two-phase flow with low velocity and high water cut. To raise the particle matching precision, we improved the particle matching algorithm from the oriented FAST and the rotated BRIEF (ORB) feature description and the random sample consensus (RANSAC) algorithm. The simulation and experiment were carried out. Simulation results show that the improved algorithm not only increases the number of matching points but also reduces the computation. The experiment shows that the improved algorithm in this paper not only reduces the computation of the feature description process, reaching half of the computation amount of the original algorithm, but also increases the number of matching results, thus improving the measurement accuracy of oil phase velocity. Compared with the SIFT algorithm and the ORB algorithm, the improved algorithm has the largest number of matching point pairs. And the variation coefficient of this algorithm is 0.039, which indicates that the algorithm is stable. The mean error of oil phase velocity measurement of the improved algorithm is 1.20 %, and the maximum error is 6.16 %, which is much lower than the maximum error of PTV, which is 25.89 %. The improved algorithm overcomes the high computation cost of the SIFT algorithm and achieves the precision of the SIFT algorithm. Therefore, this study contributes to the improvement of the measurement accuracy of oil phase velocity and provides reliable production logging data for oilfield.

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Numerical and experimental comparison of 3D Particle Tracking Velocimetry (PTV) and Particle Image Velocimetry (PIV) accuracy for indoor airflow study

Cited by 21 publications

References 25 publications

Current and potential approaches on assessing airflow and particle dispersion in healthcare facilities: a systematic review

Current and potential approaches on assessing airflow and particle dispersion in healthcare facilities: a systematic review

SPTV sheds light on flow dynamics of fractal-induced turbulence over a plate-fin array forced convection

Oil Phase Velocity Measurement of Oil-Water Two-Phase Flow with Low Velocity and High Water Cut Using the Improved ORB and RANSAC Algorithm

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