Application Of Particle Image Velocimetry Research Articles

Particle image based simultaneous velocity and particle concentration measurement

The aim of this study is the expansion of the application of particle image velocimetry (PIV) to include the determination of particle concentration within the visualized area, in addition to velocity analysis. The assessment of particle concentration is valuable in various lab-scale experiments involving particle dispersion. Additionally, it plays a crucial role in evaluating the quality of PIV images. The research investigates two particle image-based concentration techniques: the exponential averaging-based sliding method and the Voronoi cell-based method on the particle images. The exponential averaging method provides a straightforward approach, utilizing a constant length scale for sliding average application to particle images. However, this method may result in broadened interfaces or a ‘marker-shot’ effect at low concentrations, making it less suitable for scenarios involving highly non-uniform particle distributions, such as concentrated jet emissions into ambient environments. Consequently, detecting interfaces in such cases requires additional effort for reliable results. In contrast, the Voronoi cell-based technique offers the advantage of spatially adaptive resolution, making it well-suited for variable concentration distributions and situations where interface detection is crucial. To comprehensively evaluate the performance of these techniques, a synthetic test case was generated to simulate a diffusion problem featuring an initial step in concentration distribution. Both the exponential averaging and Voronoi cell-based methods were applied and compared using this synthetic test case. Additionally, the effect of particle–particle overlap is analyzed theoretically and experimentally with uniform concentration and comparison with particle counter measurements. A modified Voronoi method is introduced, providing flexibility in capturing a wide range of concentration regions and features. An example experimental scenario involving a turbulent puff was considered demonstrating the application of the developed methods. The results demonstrate that the Voronoi method effectively captures small structures with high concentrations while providing reliable results in regions with low concentrations.

High-resolution velocity determination from particle images via neural networks with optical flow velocimetry regularization

Particle image velocimetry (PIV) and optical flow velocimetry (OFV) are important velocity measurement methods in the field of fluid dynamics. Nevertheless, the conventional cross correlation-based PIV method is beset by diminished resolution, while the OFV method exhibits computational sluggishness and susceptibility to noise. These constraints have somewhat delimited the applicability of PIV and OFV techniques. Recent attempts have introduced deep learning-based methods for analyzing PIV images, offering high-resolution velocity fields with computational efficiency, but their accuracy needs improvement. This study proposes four neural networks based on the well-established FlowNetS. They incorporate two distinct velocity constraints, namely, first-order velocity smoothing regularization and second-order grad (curl)–grad (div) regularization. In the networks, these constraints are used either independently or in combination with optical flow conservation (OFC). The performances of the networks have been assessed on six different flow configurations, and the results show that the network with the second-order regularization markedly outperforms the original network across all flows, demonstrating an enhanced capacity to capture larger-scale vortices. The network with the first-order regularization also exhibits superior performance compared to the original network except in the case of cylinder flow. Unexpectedly, the introduction of the OFC constraints results in a decline in network performance. This anomaly may stem from the network's inherent capability to capture optical flow features, rendering the OFC constraint less effective in providing guidance. In summary, this study underscores the substantial potential of neural networks incorporated with judicious physical constraints in PIV applications, enabling the determination of high-resolution, high-accuracy flow fields.

Intercomparison of surface velocimetry techniques for drone-based marine current characterization

Mapping tidal currents is important for a variety of coastal and marine applications. Deriving current maps from in-situ measurements is difficult due to spatio-temporal separation of measurement points. Therefore, low-cost remote sensing tools such as drone-based surface velocimetry are attractive. Previous application of particle image velocimetry to tidal current measurements demonstrated that accuracy depends on site and environmental conditions. This study compares surface velocimetry techniques across a range of these conditions. Various open-source tools and image pre-processing methods were applied to six sets of videos and validation data that cover a variety of site and weather conditions. When wind-driven ripples are present in imagery, it was found a short-wave celerity inversion performed best, with mean absolute percentage error (MAPE) of 5–6% compared to surface drifters. During lower wind speeds, current-advected surface features are visible and techniques which track these work best, of which the most appropriate technique depends on specifics of the collected imagery; MAPEs of 9–21% were obtained. This work has quantified accuracy and demonstrated that surface current maps can be obtained from drones under both high and low wind speeds and at a variety of sites. By following these suggested approaches, practitioners can use drones as a current mapping tool at coastal and offshore sites with confidence in the outputs.

The Influence of a Manifold Structure on the Measurement Results of a PIV Flowmeter

The application of particle image velocimetry (PIV) technology for monitoring natural gas flow is a new method of flow measurement. Since the principle of this technology was proposed, there are still some potential issues. This article investigates the influence of a manifold structure on the measurement results of a PIV flowmeter. A comparison is performed between concentric and eccentric manifold structures, using a circular straight pipe as reference, in terms of the measurement error of the PIV flowmeter and the internal flow state of the natural gas. The results demonstrate that the manifold structure significantly affects the measurement reliability of the PIV flowmeter, especially the eccentric manifold structure. Under flow conditions ranging from 100 to 600 m3/h, the maximum measurement errors caused by the concentric and eccentric manifold structures are 2.49% and 3.05%, respectively, which show a noticeable increase compared to the maximum measurement error of 2.08% observed for the circular straight pipe. Additionally, the influence of the manifold structure on the downstream flow field is also evident, as the eccentric manifold structure increases the turbulence intensity of the downstream fluid by nearly twofold. The addition of a rectifier can effectively improve the flow state and enhance the measurement reliability of the PIV flowmeter. For the concentric manifold structure under the condition of a 600 m3/h flow rate, the inclusion of a rectifier produces highly accurate measurement results, similar to those obtained by an ultrasonic flowmeter, with an error value close to zero. This study provides technical support for further promoting the practical application of PIV flowmeters.

Meta-Lens Particle Image Velocimetry.

Fluid flow behavior is visualized through particle image velocimetry (PIV) for understanding and studying experimental fluid dynamics. However, traditional PIV methods require multiple cameras and conventional lens systems for image acquisition to resolve multi-dimensional velocity fields. In turn, it introduces complexity to the entire system. Meta-lenses are advanced flat optical devices composed of artificial nanoantenna arrays. It can manipulate the wavefront of light with the advantages of ultrathin, compact, and no spherical aberration. Meta-lenses offer novel functionalities and promise to replace traditional optical imaging systems. Here, a binocular meta-lens PIV technique is proposed, where a pair of GaN meta-lenses are fabricated on one substrate and integrated with a imagingsensor to form a compact binocular PIV system. The meta-lens weigh only 116mg, much lighter than commercial lenses. The3Dvelocity field can be obtained by the binocular disparity and particle image displacement information of fluid flow. The measurement error of vortex-ring diameter is ≈1.25% experimentally validates via a Reynolds-number (Re) 2000 vortex-ring. This work demonstrates a new development trend for the PIV technique for rejuvenating traditional flow diagnostic tools toward a more compact, easy-to-deploy technique. It enables further miniaturization and low-power systems for portable, field-use, and space-constrained PIV applications.

An Improved Convolutional Neural Network for Particle Image Velocimetry

With the wide application of Particle Image Velocimetry (PIV) technology in various engineering and research fields, the requirements for the accuracy, computational efficiency, and robustness of PIV algorithms are increasing. Although traditional algorithms have wide applicability, they suffer from low accuracy, large computational cost, and poor robustness. Recently, deep learning algorithms have provided new solutions, especially, convolutional neural networks with different structures, which have achieved good performance on synthetic PIV datasets. This paper proposes a structural improvement scheme for PIV convolutional neural network models. Experiments verify that the proposed method can significantly optimize the performance of the model on synthetic PIV datasets, providing a novel approach for improving other convolutional neural networks for PIV analysis.

Optical flow for particle images with optimization based on a priori knowledge of the flow

This paper proposes a new optical flow (OF) method for particle image velocimetry applications. The proposed method is based on the use of an a priori sparse knowledge of the flow. A particular insight is given to the optimization derivation based on an image-independent method. Two alternatives are introduced. The first one uses particle-tracking velocimetry estimates as subpixel information to describe the finest velocity scales. The expected true displacements related to the motion of the individual particles are used as anchors for the optimization procedure when the density of the particles is large enough. Alternatively, the second method solves the well-known median problem based on new image-independent functions in areas of low particle density. Studies have been carried out on synthetic images to characterize the error and analyze the impact of image parameters (particle density, particle size, or noise) on the methods. The new methods are compared with a reference method against synthetic data: two Lamb-Oseen vortex rings and a 3D Turbulent Homogeneous and Isotropic flow. The results show that the performances of the new method exceed those of the reference method in almost all tested cases, except for images with particles of relatively small size. It is notably shown that the new method is less dependent on the particle density and the noise embedded in the images than other OF estimators.

Application of Particle Image Velocimetry and Computational Fluid Dynamics Methods for Analysis of Natural Convection over a Horizontal Heating Source

The objective of this article is to address the challenges associated with visualizing air flow over a heating source in an open laboratory environment. The study uses a combination of experimental visualization and numerical simulation techniques to generate a 3D model of the air flow and heat transfer between the heating source and the environment via natural convection. The Particle Image Velocimetry method is used to experimentally visualize the air flow, which is known for its benefits of high speed and accuracy, and for its ability to avoid disturbing the flow of the fluid being investigated. The data obtained from this experimental method are used as input for numerical simulations using the Ansys Fluent program. The numerical simulations identify air vortices and other elements that disrupt the airflow in the laboratory environment. The resulting 3D model accurately represents the actual situation in the laboratory and could be further optimized by adjusting parameters such as the output of the heater and the heating source temperature. These parameters play a crucial role in ensuring thermal comfort in the laboratory environment, which is of utmost importance for user comfort. In conclusion, the study provides valuable insights into the visualization of air flow over a heating source and demonstrates the effectiveness of combining experimental and numerical simulation techniques to generate accurate 3D models of air flow and heat transfer.

Dynamic Analysis of the Coracohumeral Ligament Using Ultra-Sonography in Shoulder Contracture.

The coracohumeral ligament (CHL) is related to the range of motion of the shoulder joint. The evaluation of the CHL using ultrasonography (US) has been reported on the elastic modulus and thickness of the CHL, but no dynamic evaluation method has been established. We aimed to quantify the movement of the CHL by applying Particle Image Velocimetry (PIV), a technique used in the field of fluid engineering, to cases of shoulder contracture using the US. The subjects were eight patients, with 16 shoulders. The coracoid process was identified from the body surface, and a long-axis US image of the CHL parallel to the subscapularis tendon was drawn. The shoulder joint was moved from 0 degrees of internal/external rotation to 60 degrees of internal rotation at a rhythm of one reciprocation every 2 s. The velocity of the CHL movement was quantified by the PIV method. The mean magnitude velocity of CHL was significantly faster on the healthy side. The maximum magnitude velocity was significantly faster on the healthy side. The results suggest that the PIV method is helpful as a dynamic evaluation method, and in patients with shoulder contracture, the CHL velocity was significantly decreased.

Application of particle image velocimetry on velocity distribution in 5 × 5 rod bundle channel under rolling motion

The Floating Nuclear Power Plant (FNPP) would be in rolling motion during operation. The rolling motion will introduce fluctuated inertial force periodically, resulting in periodic thermal and hydraulic parameters variation, and may threaten the reactor's safety. An experimental investigation was conducted to study the influence of rolling motion on flow characteristics to measure the flow field in 5 × 5 rod bundles by Particle Image Velocimetry (PIV) under rolling motion. Results show that the rolling motion can cause a strong secondary flow. The rolling motion has little effect on the central sub-channels but significantly influences the external sub-channels. When the Reynolds number is low, the external sub-channels will periodically backflow. This study shows that the flow field affected by rolling motion differs from the pulsating flow. The applicability of using pulsating flow to study the effects of rolling motion needs further evaluation, and the results can provide a reference for numerical simulations.

The frost heave characteristics of a coarse-grained volcanic soil quantified by particle image velocimetry

The increasing use of the seasonally frozen and permafrost regions for civil engineering constructions and the effects of global warming on these regions have stimulated research on the behaviors of frozen soils. In the present study, the frost heave characteristics of a coarse-grained soil with volcanic nature was experimentally investigated. A large soil tank model was established in laboratory for this purpose. The effects of temperature boundary, external water supply, and water transfer type on the frost heave characteristics of the volcanic soil were studied, through a series of frost heave tests. The particle image velocimetry (PIV) technique was used to quantify the full field deformation of the soil specimen. The results suggest that temperature gradient inside the soil specimen is the driving force for the migration of pore water and vapor. The largest increment in water content generally agrees well with the frost penetration depth. The contribution of vapor to the frost heave of the soil specimen is typically small. The applied seeding method, selected subset size, image-object space calibration, and calculation processes ensured accurate PIV results. Discussions regarding the presented experimental investigation and the employment of PIV technique for quantifying frozen soil deformation are summarized. These findings and discussions can provide valuable insights into the frost heave behavior of the studied soil in particular, as well as promote the application of PIV for frozen soil engineering.

Assessment of the potential of radiography and ultrasonography to record flow dynamics in cohesive sediments (mud)

The possible use of both radiography and ultrasonography to visualise flow dynamics in cohesive sediments, also known as fluid mud, has been assessed. Ultimately, these techniques are intended to enable the application of Particle Image Velocimetry (PIV) in experimental fluid dynamics using such fluid mud. This research takes into account the specific requirements arising from this objective. Those requirements are primarily penetration depth, adequate frame rate and the preference not to seed with tracer particles. The evaluation of both techniques is elaborated in detail based the properties of mud originating from the Port of Zeebrugge (Belgium). The assessment of radiography starts with a chemical element analysis of the fluid mud, the results of which are used to determine the attenuation for high-energy electromagnetic radiation. Using various research software, the maximum thickness of the mud layer could be determined as a function of the maximum recordable flow velocities for different radiation sources. However, for the flow velocities expected in nautical research experiments, these thicknesses proved insufficient. Supplemented by the results of a particle size distribution analysis, it is found that high frequency ultrasound radiation will scatter in mud. In case of a great number of scatterers, the scattered ultrasound waves will interact, eventually resulting in speckle images, which are ideally suited for tracking. These findings were confirmed in a test setup with a standard medical ultrasound scanner. The penetration depth of ultrasonography with standard medical equipment is also limited. However, since ultrasonography is based on reflection, this is less of an issue compared to radiography, for which full penetration of the mud layer is required. Ultrasonography is therefore suggested as the preferred technique for the intended application.

Particle Image Velocimetry in a High-Speed Short-Duration Turbine Rig

AbstractThis article presents the implementation of a particle image velocimetry (PIV) into the high-speed short-duration rotating turbine facility of the von Karman Institute. The advantage of PIV as a whole-field measurement is emphasized in such circumstances for which the use of optical technique can drastically reduce the number of tests and the need for multiple intrusive expensive probes, ultimately lowering the testing cost. Practical solutions were demonstrated that address various challenges for the effective application of PIV. An endoscope delivered the laser sheet to the region of interest and a plano-concave window provided optical access for the measurement in the annular test section. Sub-micron scale oil droplets were seeded into the main flow through custom-made probes located upstream of the nozzle guide vane and into a pipeline supplying rim seal purge flow. A high-speed laser system and a high-speed camera were synchronized at 1 kHz sampling rate. Complementary measurements and dedicated image processing were performed to ensure the synchronization of the PIV images with the rotor position that was monitored through an encoder. The region of interest was the blade-to-blade plane at the 58% span turbine exit on a rectangular field of view covering approximately one rotor pitch and 0.15 rotor axial chord from the rotor trailing edge. Phase-locked-average velocity fields are obtained from PIV and compared against steady-state Reynolds-averaged Navier–Stokes (RANS) simulations along with four-hole probe measurement results. Together with uncertainty analysis, the results demonstrate the promising robustness and accuracy of PIV. A practical guideline for PIV application in such kinds of turbine test rigs is provided as a conclusion of the paper.

Fluorescent particle image velocimetry using atomized liquid particles

Aerosolized fluorescent particles of Kiton Red 620 dye in a water/glycol fluid are generated using a Venturi-type atomizer and shown to provide effective flow seeding for fluorescent particle image velocimetry (PIV), which can mitigate the detrimental effects of laser reflections from surfaces. Ninety two percent of particles by number concentration were found to be <1 μm in diameter, an acceptable size threshold for gas-flow PIV purposes. A PIV application was conducted in a wind tunnel (freestream velocity U ∞ = 27 m s−1), using the particles for measurement of the boundary layer flow approaching a forward-facing step (approach boundary layer momentum thickness Reynolds number of . Particles were generated from solutions with dye molar concentrations of and mol l−1, and PIV images were obtained for both elastic Mie scattering and filtered, Stokes-shifted fluorescent light. Raw images indicate that the fluorescence yield of the mol l−1 solution provides PIV images with high contrast, even in the near-surface regions where Mie scattering image contrast is highly affected by surface reflections. Boundary layer profiles are processed in the region of adverse pressure gradient leading up to the forward-facing step, where the fluorescent PIV was found to perform comparably to the most optimized Mie scattering PIV; both approaches obtained data as near to the wall as 30 μm, or two viscous wall units in our flow of interest. These results indicate that the new seeding method holds promise for near-surface measurement applications with more complicated three-dimensional geometries, where it is impossible to arrange PIV cameras to reject surface-scattered light.

Particle image velocimetry and digital image correlation for determining the elasticity modulus in wood

Several non-destructive testing techniques have been improved and tested in recent years. The non-destructive testing techniques using particle image velocimetry (PIV) and digital image correlation (DIC) differ from conventional testing techniques, as they allow making measurements indirectly. In this study, the elastic modulus in wood beams of Eucalyptus grandis and Pinus oocarpa were determined using PIV and DIC. The application of PIV and DIC techniques occurred during the static bending tests, when the displacements were also measured by the conventional method. The applied load values allowed calculating the elasticity modulus. In all regions of analysis, the mean values of the elasticity modulus found by the DIC, PIV and conventional method are statistically equivalent. It is concluded that the PIV and DIC testing techniques can be used to determine mechanical properties of wood.

Study on Aqueous Humour Hydrodynamics of Glaucoma Condition Using 3D Printed Model and Particle Image Velocimetry (PIV)

This study aims to explore the knowledge on fluid flow properties of the aqueous humour (AH), specifically on the anterior segment (AS) of the human eye for a medical condition called Glaucoma. The research objectives are to study on fluid flow characteristics of velocity and pressure of the AH on the AS of the eye using enlarged 3D printed model and computational analysis, and also to analyse the suitability of the 3D generated anterior AS in fluid flow analysis application on particle image velocimetry (PIV). Using polyvinyl alcohol (PVA) as a water-soluble 3D printing filament, a 3D model of the AS of the human eye was generated with SolidWorks 2018 and printed using Creality Ender 3. This printed model serves as the pattern for silicon rubber mould production using vacuum casting process. Analysis of AH flow hydrodynamics are conducted with computational analysis using ANSYS Workbench 19.2. Key findings support that use of PVA material suite the creation of specific shapes and patterns for 3D modelling applications alike, and silicon rubber moulding creates a non-reactive and long-lasting mould for PIV applications. Computational analysis findings support the use of the generated model for PIV applications. Overall, the study successfully supports the use of 3D printed model for PIV application and future work that can be induced include direct experimentation of the mould with PIV.

Considerations When Applying Large-Scale PIV and PTV for Determining River Flow Velocity

Large-scale image velocimetry is a novel approach for non-contact remote sensing of flow in rivers. Research within this topic has largely focussed on developing specific aspects of the image velocimetry work-flow, or alternatively, testing specific tools or software using case studies. This has resulted in the development of a multitude of techniques, with varying practice being employed between groups, and authorities. As such, for those new to image velocimetry, it may be hard to decipher which methods are suited for particular challenges. This research collates, synthesises, and presents current understanding related to the application of particle image velocimetry (PIV) and particle tracking velocimetry (PTV) approaches in a fluvial setting. The image velocimetry work-flow is compartmentalised into sub-systems of: capture optimisation, pre-processing, processing, and post-processing. The focus of each section is to provide examples from the wider literature for best practice, or where this is not possible, to provide an overview of the theoretical basis and provide examples to use as precedence and inform decision making. We present literature from a range of sources from across the hydrology and remote sensing literature to suggest circumstances in which specific approaches are best applied. For most sub-systems, there is clear research or precedence indicating how to best perform analysis. However, there are some stages in the process that are not conclusive with one set method and require user intuition or further research. For example, the role of external environmental conditions on the performance of image velocimetry being a key aspect that is currently lacking research. Further understanding in areas that are lacking, such as environmental challenges, is vital if image velocimetry is to be used as a method for the extraction of river flow information across the range of hydro-geomorphic conditions.

Life Cycle of Shallow Marine Cumulus Clouds From Geostationary Satellite Observations

AbstractAn analysis of the life cycle of shallow marine cumulus clouds is presented based on geostationary observations by the Spinning Enhanced Visible and InfraRed Imager aboard Meteosat Second Generation (MSG‐SEVIRI). Trajectories of about 250,000 individual shallow marine cumulus clouds have been derived by applying Particle Image Velocimetry to the Satellite Application Facility on Climate Monitoring CLoud property dAtAset using SEVIRI for a region in the trade wind zone centered around the Canary Islands in August 2015. The temporal evolution of the physical properties of these clouds allows to characterize cloud development and to infer the distribution of cloud life time and cloud extent. In the derived data set, the life time distribution follows a double power law with most clouds existing on a time scale of tens of minutes. The cloud physical properties, available during daytime, are analyzed along the cloud tracks. Relative time series of cloud extent, cloud water path, cloud droplet effective radius at cloud top, cloud optical thickness, and cloud droplet number concentration for clouds in two temporal ranges reveal conditions that can be attributed to long‐lasting clouds. Clouds of a certain horizontal extent and cloud top height as well as cloud droplet radius show longer life times if they are optically more dense, i.e., have a higher droplet number concentration. Furthermore, the investigation of the content of liquid cloud water regarding cloud life time and cloud extent shows that small short‐living clouds significantly contribute to cloud radiative effects.

Study on Plant Growth and Nutrient Uptake under Different Aeration Intensity in Hydroponics with the Application of Particle Image Velocimetry

Aeration is considered beneficial for hydroponics. However, little information is available on the effects of aeration, and even less on solutions that use bubble flow and their agronomic effects. In this study, the effects of aeration intensity on plants were studied through cultivation experiments and flow field visualization. It was found that the growth of plants did not increase linearly with an increase in aeration intensity. From the results of this study, when the aeration intensity was within the low range (0.07–0.15 L·L−1 NS·min−1), increasing the aeration intensity increased the plant growth. However, after the aeration intensity reached a certain extent (0.15–1.18 L·L−1 NS·min−1), some indicators did not change significantly. When the aeration intensity continued to increase (1.18–2.35 L·L−1 NS·min−1), growth began to decrease. These results show that for increasing dissolved oxygen and promoting plant growth, the rule is not “the higher the aeration intensity, the better”. There is a reasonable range of aeration intensity within which crops grow normally and rapidly. In addition, increasing the aeration intensity means increasing energy utilization and operating costs. In actual hydroponics production, it is very important to find a reasonable aeration intensity range.

Development and application of particle image velocimetry in ship field

This paper briefly introduces particle image velocimetry (PIV) technology and summarizes the R&D of algorithms for PIV technology and its application and development in ship fields, including research into the flow fields around surface ships and underwater vehicles, as well as ship air flow fields. Finally, the development of PIV technology for ship fields is proposed. In terms of the speed measurement hardware system, PIV algorithms and ship flow field research, several problems requiring further study are put forward, providing new ideas for ship flow field research, and the development and application of PIV technology in ship fields is described. This study has certain reference and guiding significance for future research on flow field performance optimization.