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The main spatial distribution features of shear rate in a stirred tank operated with five different radial and axial flow impellers were presented with particle image velocimetry (PIV) experiments. Not only the average shear rate in the whole tank but also the local value in vicinity of impeller increases linearly with impeller speed. Furthermore, the shear coefficient (Ks,imp) at the impeller outlet is linearly related to the impeller flow number (Nq) and decreases with the increase of Nq in general at the constant power consumption per unit volume (Pv). During scale-up based on the constant Pv and geometric similarity, CFD results show that the volume-averaged shear rate (γavg) for RDT decreases faster than that of other impellers with the impeller tip velocity (Utip). The novel multi-blade combined (MBC) impeller with the increased height-to-diameter ratio of the stirred tank is able to more effectively improve the distribution uniformity of shear rate at the same Pv after scale-up. These studies provide a data basis for selecting the impeller types and improving the shear rate environment in large-scale stirred tank.

In the two-phase flow particle image velocimetry (PIV) experiment of an object entering water, the mask of non-computed area and the calculation of velocity field in particle images are two key stages. Due to the complexity of the edge of the object in the particle image, the mask calibration is usually performed manually and then the PIV estimation is carried out. We propose a cascaded convolutional neural network (CNN) in this paper to implement end-to-end two-phase flow fluid motion estimation. In the first stage, the image segmentation network U-Net is used to mask the non-computational area of the image and extract the liquid phase. In the second stage, we adopt the improved deep optical flow network, which is known as recurrent allpairs field transforms (RAFT) to calculate velocity field. What’s more, the corresponding datasets are generated for training model parameters. Finally, our approach is tested on synthetic and experimental images. The experimental results indicate that our approach not only reaches accurate segmentation of the calculated liquid phase region, but also achieves a high-precision velocity field calculation. Meanwhile, this cascade CNN model has high efficiency toward real-time estimation.

Two-dimensional thermographic particle image velocimetry (T-PIV) is presented for the in situ measurement in optically accessible internal combustion (IC) engines. Temperature and velocity measurements are combined using thermographic phosphor particles as tracers for PIV. For three commercially available phosphors (BAM:Eu2+, ZnO, and ZnO:Zn), temperature sensitivity, luminescence intensity at high temperatures and laser-fluence dependence were evaluated for phosphor-coated surfaces in a high-temperature cell. ZnO:Zn was identified as the best-suited candidate for engine in-cylinder measurements and further analyzed in the aerosolized state at temperatures up to 775 K to generate calibration data required for signal quantification in engine experiments. T-PIV was successfully applied in the IC engine to simultaneously obtain instantaneous two-dimensional velocity and temperature fields using the intensity-ratio method. Despite a measurement uncertainty (±1σ basis) of only 3.7 K at 317 K (1.2%) to 24.4 K (4.2%) at 575 K, this technique suffers from low signal intensities due to thermal quenching at increasing temperatures, which leads to reduced accuracy as the piston approaches top dead center. Thermographic measurements were successful to visualize local temperature changes due to evaporative cooling after fuel injection. The measured mean gas temperatures agreed well with zero-dimensional simulations that use additional wall-temperature measurements from thermographic phosphor measurements based on the lifetime method as input for heat transfer calculations.

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.

A novel vertical augmentation channel housing a direct-drive cross-flow turbine, with nozzles on both the sides of the turbine, was designed and an optimized configuration was obtained. The geometries of the guide nozzle and the front nozzle were optimized under steady flow conditions. The performance of the cross-flow turbine was analyzed using commercial computational fluid dynamics (CFD) code ANSYS-CFX. The optimized design was then evaluated as a wave energy converter both experimentally and computationally. The waves in the numerical wave tank (NWT) were generated using a piston type wave-maker. The optimized design gave a maximum output power of 13.2 W and an efficiency of 48.31% at a wave height of 0.2 m and wave period of 2.75 s for a rotational speed of 35 rpm. The difference between numerical and experimental efficiencies was within 3.5%. In addition to this, particle image velocimetry was used to study the flow characteristics in the augmentation channel and the turbine. The results show that the CFD code captures the flow in the augmentation channel and around the turbine accurately. The optimized design, which occupies less space than other wave energy converters, can be used to efficiently harness energy from the waves.

In high-speed rotorcraft applications, large sections of a blade undergo reverse flow due to a high advance ratio. Flow separation at the sharp aerodynamic leading edge during reverse flow leads to...

Human milk extraction from the breast is affected by the infant's oral activities. Natural suckling by the infant includes both intraoral vacuum and peripheral oral compression during breastfeeding. However, the contribution of each of these motions to milk extraction at the outlet and at the duct bifurcations is unclear. In this work, we investigated the flow field in a lactating breast model considering bifurcated milk ducts and multiphase breast-infant interactions. A bio-inspired breastfeeding simulator device was utilized to mimic an infant's oral feeding mechanism during breastfeeding and extract the human milk-mimicking Fluid from the transparent and elastic lactating breast phantom during experiments. Using a particle image velocimetry system, we found that the oscillatory flow under vacuum pressure provides a higher velocity field at the outlet compared to that when an infant applies both vacuum and oral compression pressures. Additionally, the intraoral vacuum coordinated with the oral peripheral compression causes stronger vorticities and secondary flows at the adjunction of the bifurcated ducts than the vacuum-only case. Vacuum-only extraction yields an increase in flow velocity at the outlet and could be one of the reasons for nipple pain, whereas infant's oral activities on the breast generated more vortices in the milk duct adjunctions and might cause milk duct clogs. This phenomenon is rationalized based on the validation of a previous in vivo clinical study of milk production compared between commercial pumps and infant suckling. The fact that milk consumption of vacuum-only extraction is less than that of vacuum plus oral compression further explains the effectiveness of applying a natural suckling pattern in human lactation.

This study aims to develop a low-drift air induction (AI) nozzle that meets the requirements of agricultural control unmanned aerial vehicles (UAVs). An AI nozzle was designed and manufactured to satisfy the design goals. The performance of the developed AI nozzle was quantitatively evaluated in terms of injection flow rate, air-to-liquid ratio (ALR), spray angle, and droplet size. The average value of the injection flow rate and the variation over time were measured using a gear-type positive displacement precision flow meter. The spray structure and spray angle were obtained at very high temporal resolution using the single image acquisition function of a two-dimensional particle image velocimetry (PIV) system. The droplet size of the spray was measured using a laser diffraction technique. The injection flow rate of the AI nozzle changes with the pressure recovery characteristics inside the nozzle mixing chamber and affects the dynamic stability of the AI nozzle. The spray angle of the AI nozzle with a flat-fan nozzle tip increases linearly with the injection pressure, and if there is additional consideration for the two-phase flow effect, the prediction equation for the single-phase flow can be applied to estimate the spray angle. The generation of air bubble-containing droplets in AI nozzles is formed by large-diameter ligament disintegration caused by a rolled-up liquid sheet and is larger than that of single-phase flow nozzles. The droplet size (Dv0.5) of the developed AI nozzle was 384 μm, which was smaller than that of a similar commercial AI nozzle. AI nozzle design, manufacturing and performance evaluation technology that satisfies the requirements of agricultural control UAVs, was established through this study.

The crossflow is the key phenomenon in turbulent flow inside rod bundles. In order to establish confidence on application of computational fluid dynamics (CFD) to simulate the crossflow in rod bundles, three Reynolds-Averaged Navier Stokes (RANS) models i.e. the realizable k-e model, the k-ω SST model and the Reynolds stress model (RSM), and the Large Eddy simulations (LES) with the Wall-Adapting Local Eddy-viscosity (WALE) model are validated based on the Particle Image Velocimetry (PIV) flow measurement experiment in a 5 × 5 rod bundle. In order to investigate effects of periodic boundary condition in the gap, the numerical results obtained with four inner subchannels are compared with that obtained with the whole 5 × 5 rod bundle. The results show that periodic boundaries in the gaps produce strong errors far downstream of the spacer grid, and therefore the full 5 × 5 rod bundle should be simulated. Furthermore, it can be concluded, that the realizable k-e model can only provide reasonable results very close to the spacer grid, while the other investigated models are in good agreement with the experimental data in the whole downstream flow in the rod bundle. The LES approach shows superiority to the RANS models.

Effects of fluid dynamics on cells are often studied by growing the cells on the base of cylindrical wells or dishes that are swirled on the horizontal platform of an orbital shaker. The swirling culture medium applies a shear stress to the cells that varies in magnitude and directionality from the center to the edge of the vessel. Computational fluid dynamics methods are used to simulate the flow and hence calculate shear stresses at the base of the well. The shear characteristics at each radial location are then compared with cell behavior at the same position. Previous simulations have generally ignored effects of surface tension and wetting, and results have only occasionally been experimentally validated. We investigated whether such idealized simulations are sufficiently accurate, examining a commonly-used swirling well configuration. The breaking wave predicted by earlier simulations was not seen, and the edge-to-center difference in shear magnitude (but not directionality) almost disappeared, when surface tension and wetting were included. Optical measurements of fluid height and velocity agreed well only with the computational model that incorporated surface tension and wetting. These results demonstrate the importance of including accurate fluid properties in computational models of the swirling well method.

Study on gas–liquid flow in stirred tank with two combinations of dual-impeller (six-bent-bladed turbine (6BT)+six-inclined-blade down-pumping turbine (6ITD), the six-bent-bladed turbine (6BT)+six-inclined-blade up-pumping turbine (6ITU)) was conducted using computational fluid dynamics (CFD) and population balance model (PBM) (CFD-PBM) coupled model. The local bubble size was captured by particle image velocimetry (PIV) measurement. The gas holdup, bubble size distribution and gas–liquid interfacial area were explored at different conditions through numerical simulation. The results showed that the 4 mm bubbles accounted for the largest proportion of 33% at the gas flow rates Q = 0.76 m3⋅h−1 and 22% at Q = 1.52 m3⋅h−1 for combined impeller of 6BT + 6ITU, while the bubbles of 4.7 mm and 5.5 mm were the largest proportion for 6BT + 6ITD combination, i.e. 25% at Q = 0.76 m3⋅h−1 and 22% at Q = 1.52 m3⋅h−1, respectively, which indicated that 6BT + 6ITU could reduce bubble size effectively and promote gas dispersion. In addition, the gas holdup around impellers was increased obviously with the speed compared with gas flow rate. So it was concluded that 6ITU impeller could be more conductive to the bubble dispersion with more uniform bubble size, which embodied the advantages of 6BT + 6ITU combination in gas–liquid mixing.

The investigation of flow field can provide strong theoretical support for improving the flotation performance of fine particles in a cyclonic flotation column. In this study, particle image velocimetry (PIV) is combined with endoscopic measurement and phase discrimination technique to measure the cross section and axial section of gas–liquid two-phase flow field in a lab-scale cyclonic flotation column. The axial, radial, and tangential velocity of both gas and liquid phases are obtained. Based on the PIV experimental data, computational fluid dynamics (CFD)-based numerical models are validated. The results show the good prediction ability of Eulerian–Eulerian multiphase model, Reynolds stress model (RSM), and Tomiyama drag model. Then the simulated results with validated models are displayed to indicate the flow characteristics of the flotation column. The gas concentration is observed to be higher in the center and low on the sides. The gas phase always moves upward, while the liquid phase moves upward at the axis, downward between the axis and the wall, and upward again near the wall. Overall, this study provides an innovative approach for PIV measurement of complex multiphase flow field, and a useful reference for appropriate numerical models selection.

The development of microbubble technology has been widely used in various fields. One of these areas is sterilization technology using microbubbles to speed up and increase the effectiveness of the sterilization process. One example is room sterilization using vaporized ozone gas microbubbles which can minimize the spread of the Covid-19 virus. However, research and development of microbubbles are still not much related to the characterization of their size and hydrodynamic properties. In this study, we propose the development of a continuous characterization of the size of microbubbles using the image analysis method. Image analysis aims to find the displacement vector using particle image velocimetry (PIV) techniques. The Hadamard-Rybczynski equation was used to calculate the size of the microbubbles based on the rising velocity vector of the microbubbles. The image capture process uses an LED light shadow technique to get a brighter and more stable image. The template matching algorithm is used to speed up the displacement vector analysis process used in the PIV technique. The analysis process is carried out in-situ in parallel processing using the python program on the raspberry pi4 unit. The analysis process uses three program services that run parallel, namely recording, pre-processing, and processing services. The measurement process uses three validations, namely pixel validation, template matching algorithm validation, and interrogation window. Bubble size data is displayed in the form of real-time graphs and size distribution histograms online using IoT. The test results show the size distribution of the microbubbles produced has an average of 14.60 µm with a deviation value of 0.11µm. &nbsp, Perkembangan teknologi gelembung mikro telah banyak dimanfaatkan di berbagai bidang. Salah satu bidang tersebut adalah teknologi sterilisasi menggunakan gelembung mikro untuk mempercepat dan meningkatkan efektifitas proses sterilisasi. Salah satu contohnya adalah sterilisasi ruangan menggunakan gelembung mikro gas ozon yang diuapkan yang dapat meminimalisir penyebaran virus Covid19. Akan tetapi penelitian dan pengembangan gelembung mikro masih belum banyak terkait karakterisasi ukuran dan sifat hidrodinamisnya. Dalam penelitian ini mengusulkan pengembangan karakterisasi ukuran gelembung mikro secara kontinyu menggunakan metode analisa citra. Analisa citra bertujuan untuk mencari vektor perpindahan menggunakan teknik particle image velocimetry (PIV). Persamaan Hadamard-Rybczynski digunakan untuk menghitung ukuran gelembung mikro berdasarkan vektor kecepatan naik gelembung mikro. Proses pengambilan citra menggunakan mekanisme teknik bayangan cahaya LED agar mendapatkan citra yang lebih terang dan stabil. Algoritma pencocokan template digunakan untuk mempercepat proses analisa vektor perpindahan yang digunakan dalam teknik PIV. Proses analisa dilakukan in-situ secara paralel menggunakan program python pada unit pengolah raspberry pi4. Proses analisa menggunakan 3 layanan program yang berjalan secara paralel yaitu layanan perekam, pra-pengolah dan pengolah. Proses pengukuran menggunakan 3 validasi yaitu validasi piksel, validasi algoritma pencocokan template dan validasi jendela interograsi. Data ukuran gelembung ditampilkan dalam bentuk grafik realtime dan histogram distribusi ukuran secara daring menggunakan IoT. Hasil pengujian menunjukkan distribusi ukuran gelembung mikro yang dihasilkan memiliki rata-rata 14.60 µm dengan nilai deviasi sebesar 0.11 µm.

Pumped storage units are the main parts in China’s power construction, as a hot issue concerned by the industry. The pump turbine involves the two-way flows and a multiple condition operation, and its operation flow pattern is very complex. The particle image velocimetry (PIV) is a very effective test technique to determine the internal flow field of pump turbines. This paper discusses the key problems of the pump turbine, based on the PIV experiments under typical conditions of the pump turbine, especially for problems such as the S-shape problem, the hump problem, the pressure fluctuation problem and the cavitation problem. In the internal flow fields under typical conditions are determined. The vortices induced and their development are observed in the PIV test. The flow phenomenon is shown at each operating point. The typical problems of the pump turbine are closely related to the vortex distribution in the internal flow field. From the PIV test results under several working conditions and from the comparisons between the optimal condition and the part load condition, it is seen that the vortex distributions are very different. Vortices at the vane-less area between the guide vane and the runner are closely related to the strong pressure pulsation, the first hump and the S-shape curve. From the PIV results of the cavitation working points, it is seen that the flow angle is changed in the vane-less region and the runner leading edge because of the cavitation bubbles and that the flow angle deviates from the optimal setting angle. From the computational fluid dynamics (CFD) result of the second hump working points, it is concluded that the vortex shedding on the runner leading edge is the main cause of the second hump.

Reducing the consumption of secondary flow is of significance to future development of fluidic thrust vectoring (FTV) technology. A new coflow FTV control method based on sweeping jet (SWJ) excitat...

Despite their relative simplicity, single slope solar stills remain one of the most viable solutions to the production of freshwater from saline and non-potable water sources. Over the years, numerous researchers have attempted to improve the yield of single slope solar stills through changes to their geometry and the use of various design modifications. Despite this long history of research, one modification that has not been fully explored is the use of passive baffles to alter the natural convection inside them. Though baffles have frequently been used to suppress natural convection in enclosures, there may also be the opportunity to use them to enhance natural convection. This judicious placement of baffles to enhance the natural convection could potentially improve the yield from single slope solar stills, however it has not been well explored in the literature. To address this issue, this work examined the effect of vertically mounted passive baffles on the natural convection inside a single slope solar still geometry. In this vein, a computational fluid dynamics simulation was conducted for a still containing a baffle, with the results validated experimentally using particle image velocimetry. On this basis, subsequent simulations explored the effect of baffle length and position on stills with cover angles from 10–60°. The results showed that baffles did have a marked influence on the natural convection flow field and could increase the natural convection heat transfer coefficient, which is directly proportional to a solar still’s yield, by up to 20%. It was also found that short baffles enhanced natural convection at low cover angles, while baffles mounted close to the front of a still provided an improvement to the transfer processes over the widest range of conditions. Finally, the work led to the development of a relationship to describe the effect of baffles on natural convection, as shown in Equation (1) , that it is hoped will aid designers of single slope solar stills in the future. (1) N u ' = R a ' 0.188 ∗ AR - 0.29 ∗ cos θ - 0.5 ∗ b B 0.08 ∗ d D 0.09

Trapping, sorting, transportation, and manipulation of synthetic microparticles and biological cells enable investigations in their behavior and properties. Microfluidic techniques like rapid electrokinetic patterning (REP) provide a non-invasive means to probe into the nature of these micro and nanoparticles. The opto-electrically induced nature of a REP micro vortex allows tuning of the trap characteristics in real-time. In this work, we studied the effects of transient optical heating on the induced electrothermal vortex using micro-particle image velocimetry (μ-PIV) and computational modeling. A near infra-red (980 nm) laser beam was focused on a colloidal suspension of 1 μm polystyrene beads sandwiched between two parallel-plate electrodes. The electrodes were subjected to an AC current. The laser spot was scanned back-and-forth in a line, at different frequencies, to create the transient vortex. This phenomenon was also studied with a computational model made using COMSOL Multiphysics. We visualize fluid flow in custom-shaped REP traps by superposing multiple axisymmetric (spot) vortices and discuss the limitations of using superposition in dynamically changing traps.

Purpose: To compare the flow patterns and hemodynamics of the AFX stent-graft and the covered endovascular reconstruction of aortic bifurcation (CERAB) configuration using laser particle image velocimetry (PIV) experiments. Materials and Methods: Two anatomically realistic aortoiliac phantoms were constructed using polydimethylsiloxane polymer. An AFX stent-graft with a transparent cover made with a new method was inserted into one phantom. A CERAB configuration using Atrium’s Avanta V12 with transparent covers made with a previously established method was inserted into the other phantom, both modified stent-grafts were suitable for laser PIV, enabling visualization of the flow fields and quantification of time average wall shear stress (TAWSS), oscillatory shear index (OSI), and relative residence time (RRT). Results: Disturbed flow was observed at the bifurcation region of the AFX, especially at the end systolic velocity (ESV) time-point where recirculation was noticeable due to vortical flow. In contrast, predominantly unidirectional flow was observed at the CERAB bifurcation. These observations were confirmed by the quantified hemodynamic results from PIV analysis where mean TAWSS of 0.078 Pa (range: 0.009–0.242 Pa) was significantly lower in AFX as compared with 0.229 Pa (range: 0.013–0.906 Pa) for CERAB (p−1 (range: 9–3603 Pa−1) in AFX was also significantly higher than 88 Pa−1 (range: 2–840 Pa−1) in CERAB (p=0.0086). Conclusion: In this in vitro study, the flow pattern of a modified AFX stent-graft was found to be more disturbed especially at the end systolic phase, its hemodynamic outcomes less desirable than CERAB configuration. Clinical Relevance: While the AFX stent-graft has an advantage over the CERAB configuration in eliminating radial mismatch, and maintaining the anatomical bifurcation for future endovascular intervention, this in vitro study revealed that the associated lower TAWSS, higher OSI and RRT may predispose to thrombosis and are, thus, less desirable as compared to a CERAB configuration. Further investigation is warranted to confirm whether these findings translate into the clinical setting.

A wide range of problems in applied physics and engineering involve learning physical displacement fields from data. In this paper we propose a deep neural network-based approach for learning displacement fields in an end-to-end manner, focusing on the specific case of particle image velocimetry (PIV), a key approach in experimental fluid dynamics that is of crucial importance in diverse applications such as automotive, aerospace and biomedical engineering. The current state of the art in PIV data processing involves traditional handcrafted models that are subject to limitations including the substantial manual effort required and difficulties in generalizing across conditions. By contrast, the deep learning-based approach introduced in this paper, which is based on a recent optical flow learning architecture known as recurrent all-pairs field transforms, is general, largely automated and provides high spatial resolution. Extensive experiments, including benchmark examples where true gold standards are available for comparison, demonstrate that the proposed approach achieves state-of-the-art accuracy and generalization to new data, relative to both classical approaches and previously proposed optical flow learning schemes. Particle image velocimetry is an imaging technique to determine the velocity components of flow fields, of use in a range of complex engineering problems including in environmental, aerospace and biomedical engineering. A recurrent neural network-based approach for learning displacement fields in an end-to-end manner is applied to this technique and achieves state-of-the-art accuracy and, moreover, allows generalization to new data, eliminating the need for traditional handcrafted models.

Flow-sensitive four-dimensional Cardiovascular Magnetic Resonance Imaging (4D Flow CMR) has increasingly been utilised to characterise patients' blood flow, in association with patiens' state of health and disease, even though spatial and temporal resolutions still constitute a limit. Computational fluid dynamics (CFD) is a powerful tool that could expand these information and, if integrated with experimentally-obtained velocity fields, would enable to derive a large variety of the flow descriptors of interest. However, the accuracy of the flow parameters is highly influenced by the quality of the input data such as the anatomical model and boundary conditions typically derived from medical images including 4D Flow CMR. We previously proposed a novel approach in which 4D Flow CMR and CFD velocity fields are integrated to obtain an Enhanced 4D Flow CMR (EMRI), allowing to overcome the spatial-resolution limitation of 4D Flow CMR, and enable an accurate quantification of flow. In this paper, the proposed approach is validated in a U bend channel, an idealised model of the human aortic arch. The flow patterns were studied with 4D Flow CMR, CFD and EMRI, and compared with high resolution 2D PIV experiments obtained in pulsatile conditions. The main strengths and limitations of 4D Flow CMR and CFD were illustrated by exploiting the accuracy of PIV by comparing against PIV velocity fields. EMRI flow patterns showed a better qualitative and quantitative agreement with PIV results than the other techniques. EMRI enables to overcome the experimental limitations of MRI-based velocity measurements and the modelling simplifications of CFD, allowing an accurate prediction of complex flow patterns observed experimentally, while satisfying mass and momentum balance equations.

In this work, two-dimensional isothermal characteristics of material flow around the cylindrical tool pin during the friction stir welding (FSW) process are investigated by using both experimental and numerical approaches for the wide range of traverse speed (50–110 mm/min) and rotational speed (75–425 rpm) of the tool pin. The experimental results, obtained using particle image velocimetry (PIV) flow visualization technique, are supplemented with the computational fluid dynamics (CFD) modelling based on COMSOL Multiphysics. The rheological behaviour of experimental material with a rheometer yielded as non-Newtonian shear-thinning nature under the broader shearing (10−3–103 s−1) at the room temperature 25 °C. Both experimental and computational characteristics of material flow in terms of local velocity and strain rate profiles complement each other with the best level of accuracy and show an increase in both with increasing rotational speed. During FSW process, two flow zones, namely, rotational and transitional zones, are formed around the tool pin. The rotational zone is symmetric and has 1 mm width around the tool pin at 300 rpm and 50 mm/min. Finally, both PIV and CFD analyses have replicated an industrial process in an efficient manner. PIV technique has been successfully demonstrated for in-situ flow visualization of FSW process and overcoming the issues with earlier tracer-based techniques, but selecting a transparent material is a minor concern. The consistency established between the experimental and CFD results further provides that the CFD approach can efficiently and reliably be used to gain the precise mechanisms of the FSW process and to select the appropriate design and engineering parameters.

To analyze the flow pattern inside a typical wire-plate wet electrostatic precipitator (WESP) and its impact on particle trajectories, particle image velocimetry, and the finite element method were...

The process of functionalization in the field of nanotechnology is an important area of scientific and technical activities. Functionalization involves different expertise insofar as its complexity impacts physics, chemistry, electronics, measurement and instrumentation, and materials science. The research presented in this paper proposes criteria for verifying silica nanoparticles in terms of shape and dimensions based on processing transmission electron microscopy (TEM) images related to the nanoparticles using two techniques: monadic vision, mostly employed in robotics, and particle image velocimetry (PIV) used in fluid motion characterization through imaging. The first technique is connected to the characterization of the dimensions of objects by a robot having vision. The second, used in fluid velocimetry, is related to motion. Here, we do not deal with motion in the traditional meaning but during functionalization droplets of materials are generally seen. So droplets can be considered as quasi-motion from the main body to the outside due to centrifugal forces. In any case, both algorithms yield to shape and dimension determination for assessing the quality of functionalization.

High solid anaerobic digestion (HSAD) is a promising technology for the treatment of organic waste. Mixing process in HSAD is quite difficult with long mixing time, poor homogenization, significant short-circuiting and stagnant zones. However, the mass transfer in mixing process in HSAD has not been visualized due to the lack of a proper method. In this study, a novel approach for experimentally quantifying the mass transfer in HSAD’s mixing process was proposed in a mixing tank equipped with multistage impellers by means of the Laser Induced Fluorescence (LIF) technique. Flow field was investigated for better illustrating the mass transfer, thus Particle Image Velocimetry (PIV) and Computational Fluid Dynamics (CFD) technique were conducted for flow field measurement. The obtained results revealed that the feedstock tended to accumulate around the impeller in the HSAD system, especially near the 1st stage. The tracer diffused rapidly around the 1st impeller in t = 10 s, but the diffusion around the 2nd impeller was quite tough even after 4 h 08 min 23 s. And prolonging mixing time could not significantly improve the flow pattern along with the mixing. In this study, new insight was thrown into the visualization of the mass transfer in mixing process within a HSAD reactor. The visualization of mass transfer in the mixing process in HSAD could offer reference information to the study of the mixing process of HSAD even in full-scale.

A study about the influence of geometry simplification on the swirling flow of a cyclone was performed by comparing CFD results with experimental data. The numerical results were obtained by solving the mass and momentum equations with the Reynolds Stress Model (RSM) for the turbulence closure. On other hand, the experimental data were obtained in the literature, the authors used the Particle Image Velocimetry (PIV) technique to measure the velocity fields and a differential manometer to measure the pressure drop. In this work, different test facility geometries configurations were simulated: the complete test facility; and others with some simplifications downstream and upstream of the cyclone. The boundary condition for both numerical and experimental analysis was performed with inlet velocity in 10.5 and 12.25 m/s. Results showed a decrease in the gas vortex velocity in the cyclone center when simplifications in the test facility geometry are made. These bring significant consequences in the performance parameters, like almost 20% in the pressure drop values.

BACKGROUND: The haemodynamics determined by different approaches for studying fluid dynamics – i.e. computational fluid dynamics (CFD), particle image velocimetry (PIV), and phase-contrast magnetic resonance imaging (PC-MRI) – have rarely been thoroughly compared; nor have the factors that affect accuracy and precision in each method. As each method has its own advantages and limitations, this knowledge is important for future studies to be able to achieve valid analyses of fluid flows. OBJECTIVE: To gauge the capacity of these methods for analysing aneurysmal flows, we compared the haemodynamic behaviours determined by each method within a patient-specific aneurysm model. METHODS: An in vitro silicone aneurysm model was fabricated for PIV and PC-MRI, and an in silico aneurysm model with the same geometry was reconstructed for CFD. With the same fluid model prepared numerically and physically, CFD, PIV and PC-MRI were performed to study aneurysmal haemodynamics. RESULTS: 2D velocity vectors and magnitudes show good agreement between PIV and CFD, and 3D flow patterns show good similarity between PC-MRI and CFD. CONCLUSIONS: These findings give confidence to future haemodynamic studies using CFD technology. For the first time, the morphological inconsistency between the PCMRI model and others is found to affect the measurement of local flow patterns.

A survey conducted by Abiomed, Inc. revealed that 10 of 60 patients who received ventricular assistance via the AB5000 ventricular assist device (VAD) experienced hemolysis. The present study was conducted to investigate which factors influence hemolysis under pulsatile-flow VADs such as the AB5000. We compared the specificity of the AB5000 and its driving console with those of the NIPRO-VAD and VCT50χ under severe heart failure conditions using a mock circulatory system with a glycerol water solution. We used the mock circuit with bovine blood to confirm which pump conditions were most likely to cause hemolysis. In addition, we measured the shear velocity using particle image velocimetry by analyzing the seeding particle motion for both the AB5000 and NIPRO-VAD under the same conditions as those indicated in the initial experiment. Finally, we analyzed the correlation between negative pressure, exposure time, and hemolysis by continuously exposing fixed vacuum pressures for fixed times in a sealed device injected with bovine blood. Applying higher vacuum pressure to the AB5000 pump yielded a larger minimum inlet pressure and a longer exposure time when the negative pressure was under - 10 mmHg. The plasma-free hemoglobin increased as more negative pressure was driven into the AB5000 pump. Moreover, the negative pressure interacted with the exposure time, inducing hemolysis. This study revealed that negative pressure and exposure time were both associated with hemolysis.

In the present work, approaches of the Computational Fluid Dynamics (CFD) simulation, the Particle Image Velocimetry (PIV) measurement, and the spinning experiment were applied to investigate the phenomenon of air recirculation in blunt-die melt-blown airflow. Firstly, the characteristics of air recirculation were explored by CFD simulation. The simulation results predicted that the air recirculation generated a lateral air velocity along the nose-piece direction. Then, the air circulation was experimental verified by using PIV technique. The PIV results confirmed the predicted conclusions of CFD simulation. Finally, the effect of air recirculation on the microfiber spinning during the melt-blown process was experimentally investigated by a spinning experiment using a blunt die with nose-piece width of 2.56 mm. The spinning results indicated that the air circulation had a tendency of splitting the normal polymeric stream, which played negative effect on the continuity of microfiber spinning. This work is expected to provide some clues to melt-blown die design and the quality control of nonwoven products.

Swirl-Loop Scavenging (SLS) improves the performance of 2-stroke aircraft diesel engine because the involved swirl may not only benefit the scavenging process, but also facilitate the fuel atomization and combustion. The arrangement of scavenge port angles greatly influences in-cylinder flow distribution and swirl intensity, as well as the performance of the SLS engine. However, the mechanism of the effect and visualization experiment are rarely mentioned in the literature. To further investigate the SLS, Particle Image Velocimetry (PIV) experiment and Computational Fluid Dynamics (CFD) simulation are adopted to obtain its swirl distribution characteristics, and the effect of port angles on scavenging performance is discussed based on engine fired cycle simulation. The results illustrate that Reynolds Stress Turbulence model is accurate enough for in-cylinder flow simulation. Tangential and axial velocity distribution of the flow, as well as the scavenging performance, are mainly determined by geometric scavenge port angles αgeom and βgeom. For reinforcement of scavenging on cross-sections and meridian planes, αgeom value of 27° and βgeom value of 60° are preferred, under which the scavenging efficiency reaches as high as 73.7%. Excessive swirl intensity has a negative effect on SLS performance, which should be controlled to a proper extent.

Purpose: Computational Fluid Dynamics (CFD) simulations are performed to investigate the impact of adding a grid to a two-inlet dry powder inhaler (DPI). The purpose of the paper is to show the importance of the correct choice of closure model and modeling approach, as well as to perform validation against particle dispersion data obtained from in-vitro studies and flow velocity data obtained from particle image velocimetry (PIV) experiments. Methods: CFD simulations are performed using the Ansys Fluent 2020R1 software package. Two RANS turbulence models (realisable $k - \epsilon$ and $k - \omega$ SST) and the Stress Blended Eddy Simulation (SBES) models are considered. Lagrangian particle tracking for both carrier and fine particles is also performed. Results: Excellent comparison with the PIV data is found for the SBES approach and the particle tracking data are consistent with the dispersion results, given the simplicity of the assumptions made. Conclusions: This work shows the importance of selecting the correct turbulence modelling approach and boundary conditions to obtain good agreement with PIV data for the flow-field exiting the device. With this validated, the model can be used with much higher confidence to explore the fluid and particle dynamics within the device., Comment: Accepted in Pharmaceutical Research (2021)

Experimental works for analysing flow behaviour inside human trachea has become continuous problem as the model used to study cannot imitate the real geometry of human trachea structure. As the technology develop, Rapid Prototyping (RP) become more useful in constructing the 3D model that has complexity in their geometries. RP not only offer several technologies in developing the 3D model, but also varies type of materials that can be used to manufacture the 3D model. In this study, RP technique was chosen to develop the 3D model of human trachea to do the Particle Image Velocimetry (PIV) experimental works. Material used was Vero Clear due to PIV need a model that transparent so that visualization on flow inside the model can be seen and the velocity magnitude can be capture. The geometry was adapted from 60 years old trachea patient where the images of trachea was taken by using CT-scan. MIMICS software was used to extracted the images before reconstruct the trachea into 3D model. Velocity distribution was visualized and the magnitude were taken at both left and right bronchi. From the analysis, it concluded that the distribution of airflow to the second generation of trachea was 60:40 to right and left bronchi. It follows the rules as the right bronchi need to supply more air to the right lung compared to left as the volume of right lung bigger that left lung.

The most common type of cardiac arrhythmia is atrial fibrillation (AF), which is characterised by irregular and ineffective atrial contraction. This behaviour results into the formation of thrombi, mainly in the left atrial appendage (LAA), responsible for thromboembolic events. Very different approaches are considered as therapy for AF patients. Therefore, it is necessary to yield insight into the flow physics of thrombi formation to determine which is the most appropriate strategy in each case. Computational Fluid Dynamics (CFD) has proven successful in getting a better understanding of the thrombosis phenomenon, but it still requires validation by means of accurate flow field in vivo atrial measurements. As an alternative, in this paper it is proposed an in vitro flow validation, consisting in an idealised model that captures the main flow features observed in the human LA which, once combined with Particle Image Velocimetry (PIV) measurements, provides readily accessible, easy to emulate, detailed velocity fields. These results have been used to validate our laminar and Large Eddy Simulation (LES) simulations. Besides, we have run a parametric study of different boundary conditions sets previously employed in the literature. These data can be used as a benchmark for further development of LA CFD models.

Particle image velocimetry (PIV) plays a significant role in experimental fluid mechanics, which aims to extract the velocity fields from successive particle image pairs. Deep learning (DL) techniques have been proposed to solve such a fluid motion estimation problem. However, the existing DL methods put emphasis on accuracy while ignoring the problem of model redundancy and low computational efficiency. In this article, we propose a novel lightweight convolutional neural network called LightPIVNet for PIV estimation, which is targeted to improve the advanced optical flow model Recurrent All-Pairs Field Transforms (RAFT). Furthermore, considering the real fluid scene, we generated a new dataset PIV-Dataset-II to train our network, which increases the amount and variety of flow fields. Our approach has been verified and analyzed on synthetic and experimental particle images. The experimental results indicate that our method achieves state-of-the-art performance among all the DL methods and is much superior to those classical traditional methods, such as WIDIM and HS optical flow. Meanwhile, our model LightPIVNet reduces parameters by 40.2% and improves inference time by 14.3% compared to the current best DL model PIV-LiteFlowNet-en.

In a previous study we demonstrated a novel two-phase PIV technique based on the laser-induced incandescence (LII) signal from black submicron tungsten carbide particles (WC), which achieved velocity measurements for both dispersed-form (large water droplet) and continuous-form (gas). Submicron WC particles are intentionally seeded into a two-phase flow, and heated by a light sheet generated by a double-pulsed PIV laser running at high energy. The 200 nm diameter, light absorbing WC particles are heated to several thousand degrees to emit strong incandescence signals, whilst the temperature rise in liquid droplets or large particles remains negligible. The small particles follow the gas phase flow, unlike the droplets which may have a different velocity. Droplets are detected via the Mie scatter signal at the same incident wavelength, whereas the LII signal from small WC particles is detected at a suitably different wavelength within the LII emission spectrum, thus allowing discrimination of velocities between phases. The LII-PIV technique had been implemented with a low-speed CCD PIV camera in non-reacting flows. In flames, the strong flame luminosity saturated the second frame due to the long exposure time as the characteristics of the device. To solve this problem, in the present study, we synchronized two high-speed CMOS cameras to a low speed laser. One records the LII signal and the other records the Mie scatter signal from 36.6 µm water droplets. The scattering from WC particles appears only as a weak background signal in the Mie image, which can be easily removed by applying a high-pass filter. Simultaneous velocity measurements for both gas and liquid phase are demonstrated in an air jet, a cold impinging flow, and finally in a Bunsen flame. The last two cases are repeated using the traditional two-phase PIV technique based on image segmentation so as to conduct a fair comparison of both techniques. We show that LII-PIV can achieve the same level of accuracy as the segmentation method in non-reacting flows, and can be applied to measure in flames with two-phase flows with less stringent requirements regarding seeding quality.

A digital image processing-based technique has been developed for residence time distribution (RTD) analysis in a steelmaking tundish. This work presents an alternative approach to current RTD analysis techniques like tracer dispersion analysis, particle image velocimetry, numerical analysis, etc. The video analysis method has been developed, and different process conditions have been evaluated. The physical model of a steelmaking tundish having water as a working fluid similar to the one which is used for RTD analysis through other methods has been used. New incoming fluid (water) has been identified using colored water so that all properties apart from color remain the same. The proposed method breaks the video into static frames, and through application of Lucas–Kanade method, the moving colored pixels in the region of interest are identified. Further intensity analysis of the moving colored pixels is done. In the present novel method, RTD curve is obtained by plotting the intensity of blue component at the outlet vs time. The obtained RTD from VT-LK method has been validated against conventional and established RTD technique widely used for RTD analysis.

High-speed, three-dimensional (3D) scalar-velocity field measurements are demonstrated in a lifted partially-premixed dimethyl-ether/air jet flame using simultaneous laser-induced fluorescence (LIF) of formaldehyde (CH2O) and tomographic particle image velocimetry (TPIV). The 3D LIF measurements are performed by raster scanning the laser beam from a 100 kHz pulse-burst laser across the probe volume using an acousto-optic deflector. The volumetric reconstruction of the LIF signal from ten parallel planes provides quasi-instantaneous 3D LIF measurements that are synchronized with 10 kHz TPIV measurements. The temporally resolved CH2O-LIF and velocity field data are used to analyze Lagrangian particle trajectories and displacement speeds at the base of the lifted flame. The particle trajectories reveal flow structures that are difficult to observe in an Eulerian reference frame. Positive and negative displacement speeds are observed at the CH2O-LIF surfaces at the inner and outer regions of the jet flame with a maximum displacement speed of approximately eight times the laminar flame speed of a stoichiometric dimethyl-ether/air mixture. The observations in present study support formation of lean premixed flames near the flame base whose role in flame stabilization should be investigated in more detail.

The mortality and morbidity rate due to the severe effect of intracranial aneurysm (IA) is increasing, which has driven research trend on aneurysm rupture risk. By understanding the nature and causes of the aneurysm rupture, preventive measures could be taken in avoiding rupture besides recommending proper treatments such as endovascular coiling. However, the presence of flow recirculation causes the aneurysm wall to degenerate and weakened. The weakened wall is due to the haemodynamic factors such as velocity, wall shear stress (WSS), time average WSS (TAWSS), OSI and RRT, which were analysed in this study. In the present study, the flow model simulated a human patient-specific aneurysm at the apex of the bifurcation in the middle cerebral artery (MCA) in the transient state. Experimental results of full-scale models were collected on a median, side plane to study the flow behaviour and validation to the numerical simulation settings, which resulted in good agreement with only 8% difference. The simulation results obtained showed several interesting findings. The jet flow into the aneurysm led to complex vortex formation due to impinging flow behaviour within the aneurysm dome. Additionally, the area that recorded low velocity was at 30% of low TAWSS with only 1% of OSI that was more than 0.3, while the OSI critical value and 0.27% area exceeded RRT threshold, which caused the large oscillating blood flow direction and activated the atherosclerosis progression. These results suggest that the jet flow into the dome may cause further damage to the wall of the MCA aneurysm, which will help in providing an insight towards completing a guidance system assessment of rupture risk for medical practitioners in future work.

Machine learning (ML) models based on a large data set of in-cylinder flow fields of an IC engine obtained by high-speed particle image velocimetry allow the identification of relevant flow structures underlying cycle-to-cycle variations of engine performance. To this end, deep feature learning is employed to train ML models that predict cycles of high and low in-cylinder maximum pressure. Deep convolutional autoencoders are self-supervised-trained to encode flow field features in low dimensional latent space. Without the limitations ascribable to manual feature engineering, ML models based on these learned features are able to classify high energy cycles already from the flow field during late intake and the compression stroke as early as 290 crank angle degrees before top dead center ([Formula: see text]) with a mean accuracy above chance level. The prediction accuracy from [Formula: see text] to [Formula: see text] is comparable to baseline ML approaches utilizing an extensive set of engineered features. Relevant flow structures in the compression stroke are revealed by feature analysis of ML models and are interpreted using conditional averaged flow quantities. This analysis unveils the importance of the horizontal velocity component of in-cylinder flows in predicting engine performance. Combining deep learning and conventional flow analysis techniques promises to be a powerful tool for ultimately revealing high-level flow features relevant to the prediction of cycle-to-cycle variations and further engine optimization.

Stroke has become the main cause of mortality and morbidity in patients treated with Left Ventricular Assist Devices (LVADs). The hemodynamics of the left ventricle are altered by the implantation of an LVAD, with the increase of thrombogenic flow patterns, such as stagnation regions. Time-resolved stereo particle image velocimetry (Stereo-PIV) measurements of the flow inside a patient-specific model of the left ventricle (LV) implanted with an LVAD were performed. The effects of LVAD speed, peripheral resistance and afterload were investigated. The impact of activating the LVAD pulsatility mode (periodic speed modulation) was also evaluated. Analysis of the velocity measurements in two orthogonal planes revealed stagnation zones which may be favorable to thrombus formation. Increasing LVAD speed, despite increasing the flow rate through the inflow cannula, does not automatically result in smaller stagnation regions. These results demonstrated the strong interdependence of peripheral resistance, afterload and flow through the LVAD. As a consequence, the pulsatility mode showed very limited effect on overall flow rate. However, it did reduce the size of high stagnation areas. This study showed how LVAD speed, peripheral resistance and afterload impact the complex intraventricular flow patterns in a ventricle implanted with an LVAD and quantify their thrombogenic risk.

Thermocapillarity is a physical phenomenon used in many industrial processes, mainly in the field of miniaturization. Thermocapillary forces are the base of thermocapillary pumping (TCP), in which a drop of liquid moves through a microchannel or flat surface after temperature gradient occurs. The objective of this work was to study the thermocapillary convection during pumping without inserting external particles, monitored by the Particle Image Velocimetry (PIV) technique. The experiment consisted of a Pasteur tube containing a yellow fluorescein solution (0.02, 0.04, 0.06, 0.08, and 0.1 Molar), illuminated by a laser beam of 545 nm, 40 mW. After 2 minutes of illumination, the thermocapillary movement occurred at a distance of 0.05 mm below the meniscus when using a laser beam of 545 nm, 3 mW. The images were captured by a charge-coupled device (CCD) camera and processed using the PIV technique. The results showed an internal conversion capacity between the intersystem crossing, vibrational, and relaxation phenomena, also demonstrating the potential for applying the proposed approach. The images presented velocity distribution caused by thermocapillarity. The PIV was a useful tool for convective flow analysis if connected to appropriate image processing and enhancement techniques. In conclusion, the research showed the images with velocity distribution caused by thermocapillarity.

Aneurysms are common vascular diseases which affect normal haemodynamics in the aorta. Endovascular aortic repair (EVAR) using stent-grafts is a common treatment that excludes the aneurysm from the...

In high gas-bearing conditions, the oil phase—in the form of droplets— often enters the reciprocating multiphase pump via the valves. Understanding the droplet-carrying characteristics of the gas flow is important for determining the transport capacity and stability of multiphase pump valves. In this paper, the turbulent gas flow and droplet movement behaviors in three typical valves of the reciprocating multiphase pumps were studied mainly by the theoretical analysis, the numerical simulation of computational fluid dynamics (CFD) and the verification test of particle image velocimetry (PIV). The steady and transient droplet trajectories, concentration distributions, and passing capacities were comprehensively studied with different valve openings, Reynolds numbers, and two-phase slip conditions. The results show that the ball valve performs steadily during the transport of the small to large droplets, while the cone valve and the disk valve perform well when transporting the small droplets with d≤250μm and the medium-sized droplets with 300μm≤d≤600μm under the initial conditions, respectively. Finally, the correlations of the volume mean diameter (dvm) of the droplets successfully passing through the cavities were proposed for the three valves. The results of this study are beneficial to help optimize and design new high-efficiency multiphase transport systems.

Despite numerous applications of helical anchors in slope stabilisation and retaining wall construction, a limited number of studies have been conducted on their performance. In the present study, ...