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Granular flows of sintered bauxite proppants were examined along an inclined plane for solar thermal energy storage applications. Granular flow properties needed to drive numeric granular models were measured for improved numerical model predictions for Carbobead CP 50/140, 40/100, and 30/60 particles. Particle shape and size distributions were determined by coupling optical microscopy to an in-house image processing algorithm. The impulse excitation technique was used to measure elastic and shear moduli, and compute Poisson’s ratio. The coefficient of static sliding friction was measured using the slip-stick method, and the static rolling friction was determined from measured shear on particles positioned between two hot-pressed plates. The coefficient of restitution was measured by dropping particles on a surface and determining the kinetic energy before and after impact with the surface using high resolution particle tracking velocimetry. Particle size did not significantly impact the coefficients of restitution and static rolling friction, however, particle shape distribution resulted in a large variation in measurements. An inclined flow experiment was performed to characterize granular flows of Carbobead CP 30/60 particles using particle image velocimetry. Numerical models of the experiment using discrete element method were generated with the measured mechanical properties as inputs for comparison with experimental results. A constant directional torque rolling friction model best predicted bulk granular flow behavior. Good agreement between the model and experiment was achieved at ambient, steady state conditions, with average velocity differences

We detect the trajectory of particles using the feature matching method to improve the resolution of particle streak velocimetry (PSV), which is used to measure the velocity of particles from a visualized path line. PSV has a more reliable performance in particle matching as compared to particle tracking velocimetry and is therefore less likely to cause erroneous matching even in high-density images. The center of gravity of the first and last trajectories is obtained to calculate the displacement. The trajectory of the particle is illuminated using a diode laser and imaged using a digital single-lens reflex camera; the trajectory is then divided into three parts and recorded in a single frame using coded illumination. The first and second trajectories are short, and the third trajectory is long. The asymmetry of the trajectories is then used to determine the flow direction. We first evaluate the detection rate by increasing the trajectory density of synthetic images. The image size was fixed at 500 × 500 pixels, and the number of trajectories was increased from 28 to 280, and the detection rate was examined. Then, we evaluated the accuracy of detection of the center of gravity of the first and last trajectories using the root mean square error. Finally, we used the coded illumination method to visualize the swirling flow inside a device to examine its applicability to real flows.

Deep ultrasound localization microscopy (deep-ULM) allows sub-wavelength resolution imaging with deep learning. However, the injection of contrast agents (CAs) in deep-ULM is debatable because of their potential risk. In this study, we propose a deep learning-based super-resolution ultrasound (DL-SRU), which employs the concept of deep-ULM and a convolutional neural network. The network is trained with synthetic tracer images to localize positions of red blood cells (RBCs) and reconstruct vessel geometry at high resolution, even for CA-free ultrasound (US) images. The proposed algorithm is validated by comparing the full width at half-maximum values of the vascular profiles reconstructed by other techniques, such as the standard ULM and the US average intensity under in silico and in vitro conditions. RBC localization by DL-SRU is also compared with that by other localization approaches to validate its performance under in vivo condition, especially for veins in the human lower extremity. Furthermore, a two-frame particle tracking velocimetry (PTV) algorithm is applied to DL-SRU localization for accurate flow velocity measurement. The velocity profile obtained by applying the PTV is compared with a theoretical value under in vitro condition to verify its compatibility with the flow measurement modality. The velocity vectors of individual RBCs are obtained to determine the applicability to in vivo conditions. DL-SRU can achieve high-resolution vessel morphology and flow dynamics in vasculature, mapping 110 super-resolved images per second on a standard PC, regardless of various imaging conditions. As a result, the DL-SRU technique is much more robust in localization compared with previous deep-ULM. In addition, the performance of DL-SRU is nearly the same as that of deep-ULM in rapid computational processing and high measurement accuracy. Thus, DL-SRU might become an effective and useful instrument in clinical practice.

Purpose The purpose of this paper is to determine how the shape of the container affects the efficiency of a traveling magnetic field (TMF) stirring. Design/methodology/approach The modeling approach is based on finite element software Comsol which includes harmonic electromagnetic (EM), transient CFD and particle tracing modules. For evaluating efficiency of stirring the particle, homogenization parameter is used. Findings It has been determined that the use of an elliptical cylinder-shaped vessel allows better heat removal from the side surface and, at the same time, the stirring efficiency does not drop significantly. Practical implications The results of the work can be used in the design of EM stirring installations in which exothermic reactions occur. Originality/value The transient simulation of particle transport in a TMF-driven melt flow gives the opportunity to estimate the efficiency of stirring process in different vessel shapes.

Cold Spray(CS) is an emerging process, attracting much interest both as a coating and additive technique due to its solid-state nature and high deposition rates. The key element of any CS apparatus is the supersonic nozzle. The work presented here, for the first time, will explore in detail the relationship between particle flow, and its acceleration in the nozzle using Computational Fluid Dynamics and experimental measurements obtained with a Particle Tracking Velocimetry apparatus. We have developed modelling parameters capable to accurately predict the particle flow exit speed and space distribution, leading to considerably improved nozzle performances.

Introduction Patients suffering from low-flow, low-gradient aortic stenosis present a decreased stroke volume due to decreased contraction or relaxation function of the left ventricle. As a low stroke volume tends to cause a low transvalvular flow, transvalvular pressure gradient (TVPG) and effective orifice area, the clinician cannot rely on those parameters with confidence for the evaluation of aortic stenosis severity. Hence new diagnostic parameters have to be developed. Energy loss through turbulence associated with aortic stenosis represented the wasted left ventricle work. Currently, echocardiographic measurement of the turbulence intensity is not validated for clinical evaluations of aortic stenosis. Methods Two porcine aortic valves were harvested and inserted in a flow loop that replicates the pulsatile flow of the heart. A stiffening of the valves was achieved by treating them with formaldehyde. The stiffening was externally confirmed by a custom-made force-displacement device quantifying the rigidity of the leaflet yielding two stiffness grades per valve. Each valve was tested under three different mean flow rates (1, 2.5, and 4 l/min) at each of the two stiffness grades. Moreover the pressure in the left ventricle chamber and in the aortic chamber was recorded to calculate the TVPG. Particle tracking velocimetry measurements into the transparent silicone ascending aorta phantom allowed the computation of the turbulent kinetic energy (TKE), to evaluate the energy loss due to turbulence. Results We could confirm the enhanced rigidity of the valve leaflets with our custom device (data not shown) and measure a consistent increase in TVPG across all mean flow rates between the two stiffness grades. Moreover, an explicit increase of the TKE in the aortic phantom could be measured after the stiffening process (73.1% under 1 l/min, and 43% under both 2.5 and 4 l/min). In addition, a good correlation (R = 0.86) between the mean TVPG and the TKE was found. Conclusions This project demonstrated the possibility of quantifying the energy loss attributed to turbulence for porcine valves in vitro for native and added stiffness grade. This project lays the foundation for the development of a new diagnostic tool for the assessment of stenosis severity in patients with low-flow, low-gradient aortic stenosis in cardiac imaging tool such as echocardiography. Funding Acknowledgement Type of funding sources: None. TVPG and its correlation with TKEIntensity graphs of the TKE

A simple and low cost technique for visualization and quantitative analysis of water flow fields around aquatic animals is described based on particle tracking velocimetry (PTV). Stroboscopic or continuous 2D sheet illumination with a slide projector and a rotating shutter is used to visualize the flow of neutrally buoyant plastic particles suspended in the flow field. The flow pattern is recorded by photographing the streak lines of moving particles using long exposure times, or by filming them with a video camera. Digital photos stored on KODAK photo CD, or video frames digitized by a frame grabber, are analyzed on a MACINTOSH computer using “Colorlmage” software. Video frames are post-processed by the software by superimposing them onto one image. Velocity vectors are obtained by measuring the distances between traces of the same particle and the direction of the streak line. Applications of the technique include the analysis of the flow field of a swimming fish and the water currents generated by decapod crustaceans.

Hydrodynamics plays a major role in transport of heat and mass transfer in microchannels. This includes flow patterns and flow regimes in which the micro-channels are operated. The flow patterns have a major impact the transport properties. Another important aspect is the pressure drop in micro-channels. In the present review, the experimental and Computational Fluid Dynamics (CFD) studies covering all the above aspects have been covered. The effect of geometrical parameters like shape of channel, channel size, material of construction of channels; operating parameters like flow velocity, flow ratio and fluid properties have been presented and analyzed. Experimental and analytical work of different pressure drop models has also been presented. All the literature related to influence of flow patterns on transport properties like volumetric mass transfer coefficients (VMTC) and heat transfer coefficients (HTC) have been presented and analyzed. It is found that most works in Liquid-Liquid Extraction (LLE) systems have been carried out in slug flow and T-junctions. Models for coupled systems of flow and mass transfer have been presented and works carried out for different coupled systems have been listed. CFD simulations match experimental results within 20% deviations in quantitative and qualitative predictions of flow phenomena for most research articles referred in this review. There is a disparity in prediction of a generalized regime map and a generalized regime map for prediction of flow patterns for various systems would need the help of Artificial Intelligence.

A new approach to characterize airborne firebrands during Wildland-Urban Interface (WUI) fires is detailed. The approach merges the following two imaging techniques in a single field-deployable diagnostic tool: (1) 3D Particle Tracking Velocimetry (3D-PTV), for time-resolved mapping of firebrand 3D trajectories, and (2) 3D Particle Shape Reconstruction (3D-PSR), to reconstruct 3D models of individual particles following the Visual Hull principle. This tool offers for the first time the possibility to simultaneously study time-resolved firebrand fluxes and firebrand size distribution to the full extent of their three-dimensional nature within a control volume. Methodologies used in the present work are presented and their technical implementation is discussed. Validation tests to confirm proper tracking/sizing of particles are detailed. The diagnostic tool is applied to a firebrand shower artificially generated at the NIST National Fire Research Laboratory. A novel graphic representation, that incorporates both the Cumulative Particle Count (CPC, particles m−2) and Particle Number Flux (PNF, particles m−2 s−1) as relevant exposure metrics, is presented and the exposure level is compared to that of an actual outdoor fire. Size distributions obtained for airborne firebrands are compared to those achieved through ground collection and strategies to improve the particle shape reconstruction method are discussed.

Arctic oil spills are particularly detrimental as they could cause extensive ice melting in addition to the environmental pollution they create. Floating oil slicks amongst ice floes absorb ambient energy and transfer that energy to the ice to aggravate melting in the thaw season. However, few studies have been undertaken to reveal how oil-ice interactions impact ice melting. This research employs a measurement technique to investigate the heat transfer pathways from oil slicks to the ice. Dual-luminescence imaging and particle imaging velocimetry (PIV) in a side cooled cavity is performed for temperature and velocity measurements of Toluene, respectively. Dual-luminescence imaging captured the spatial temperature distribution of the fuel. Consecutive imaging of the seeding particles in PIV provided the spatial velocity field of the fuel in the cavity. The results show that the convective field is directly coupled with the temperature field, i.e., the temperature difference instigates a flow in the liquid. Successful implementation of the two measuring techniques together is a step toward analyzing heat transfer pathways in a liquid fuel adjacent to an ice body, indicating the extent of melting.

Acoustic Streaming is a flow phenomenon with many applications in the field of microfluidics, such as micro mixing[1, 2] and particle manipulation[3]. With the manufacturing techniques evolves, more complicated geometries can be designed for microfluidic device and 3-D acoustic streaming patterns may occurs. In this study, 3-D trajectories of particle induced by acoustic streaming around an inclined triangular obstruction in a microchannel were visualized by a volumetric tracking method using Digital Inline Holographic Microscopy (DIHM)[4-6]. The triangular obstruction has a tip angle of 20° and an inclined angle of 30°. The acoustic streaming is created under 12 kHz oscillation of a piezo plate driven by 20V voltage. Illuminated by a 450nm continuous laser, the magnified hologram of the motion of 1.79μm tracer particles was recorded by a low-cost 10X industrial microscope with a machine vision camera of 10 fps (frames per second). Using RayleighSommerfeld back-propagation method[7], particle locations was reconstructed frame by frame and 3-D tracking of individual particles was performed afterwards. The trajectories of each particle were reconstructed to reveal the vortical structure of the acoustic streaming flow. For the current system setup, the measurable range was estimated to be 550×685×840 μm3. The 3-D location reconstruction accuracy was verified with a calibration target and the location sensitivity was found to be linear throughout the measurable range. Reconstruction at different depth locations show that the dick-shaped calibration dots and the spherical polystyrene particles have different intensity profiles. The calibration dots show local minimum of intensity at the correct depth location, while polystyrene particles show local maximum of intensity instead. Resolved particle trajectories show that the acoustic streaming flows cause particles to move with 3-D spiral shaped motions near the side of the triangular obstruction, while particles away from the obstruction shows planar motions.

Time of Flight (ToF) cameras are a type of range-imaging camera that provides three-dimensional scene information from a single camera. This paper assesses the ability of ToF technology to be used for threedimensional particle tracking velocimetry (3D-PTV). Using a commercially available ToF camera various aspects of 3D-PTV are considered, including: minimum resolvable particle size, environmental factors (reflections and refractive index changes) and time resolution. Although it is found that an off-the-shelf ToF camera is not a viable alternative to traditional 3D-PTV measurement systems, basic 3D-PTV measurements are shown with large (6mm) particles in both air and water to demonstrate future potential use as this technology develops. A summary of necessary technological advances is also discussed.

The accurate measurement of a fluid flow inside a measurement volume (MV) with limited optical access poses a challenge since the view on the MV is often partially obstructed for all but one viewing angle. Defocusing particle tracking velocimetry (DPTV) can be used to determine the instantaneous threedimensional velocity field of the flow with a standard PIV setup, requiring only a single optical axis. Current detection algorithms reach an out-of-plane accuracy in an order of magnitude lower than the planar accuracy, on top of a low rate of detected particles in comparison to other PTV approaches. These drawbacks originate from the low image quality due to noise, fluctuations in illumination, reflections and overlapping particle images. It has been shown that Machine Learning (ML) based detection is more robust against these adverse effects, due to the ability to leverage a higher amount of optical features for detection than conventional algorithms (Lecun et al. (1998)). Therefore, the present work addresses the applicability of ML algorithms in the post-processing of DPTV experiments, which will be evaluated on the ground of the DPTV experiments conducted by Leister and Kriegseis (2019). The setup of these experiments can be seen in Figure 1(a) and a section of a raw image recorded during the experiments in Figure 1(b).

A new 2D velocimetry technique based on streaks formed by individual phosphor particles, which are moving during their luminescence decay following pulsed excitation is proposed in this study. Tin-doped phosphor particles (Sr,Mg)3(PO4)2:Sn2+ are dispersed into flows and excited by a pulsed UV light sheet. During the phosphor decay time (~27 µs), the emission streaks due to particle motion are recorded. A 2D fitting is then applied on each particle streak against the analytical expression of intensity distribution, to obtain the velocity information for each particle. Unlike Particle Tracking Velocimetry (PTV) this technique does not rely on any particle image searching procedure.

Noninvasive measurements of the regional microvascular perfusion might lead to sensitive biomarkers for the changes in intracranial hemodynamics that could guide timely surgical interventions for neonatal brain injuries. The current work utilizes a clinically available contrast enhanced ultrasound (CEUS) system and particle tracking velocimetry to perform ultrasound localization microscopy for measuring the microcirculation in piglets. A new deep learning method based on U-net is proposed for enhancing noisy raw CEUS images and detecting the microbubbles. Subsequently, the bubbles are tracked using a Kalman filter based method, which incorporates conditions of spatio-temporal consistency in flow direction and globally optimizes the assignment of bubbles to trajectories. Based on analysis of synthetic data, the U-net results demonstrate significant improvement in the processing speed and localization accuracy over a conventional blind deconvolution method. Visualization of the microvasculature is performed by superposing the bubble trajectories, enabling depiction of a complex micro-vessel network, where neighboring vessels separated by 40 µm can be distinguished. The corresponding perfusion map shows the velocity distribution in these vessels. Based on the current frame rate (44 fps), speeds in the 0.1 to 12 cm/s range can be well captured. These methods show promise as potential clinical tools for bedside measurement of cerebral microcirculation.

Defocus methods have become more and more popular for the estimation of the 3D position of particles in flows (Cierpka and Kahler, 2011; Rossi and K ¨ ahler, 2014). Typically the depth positions of particles are ¨ determined by the defocused particle images using image processing algorithms. As these methods allow the determination of all components of the velocity vector in a volume using only a single optical access and a single camera, they are often used in, but not limited to microfluidics. Since almost no additional equipment is necessary they are low-cost methods that are meanwhile widely applied in different fields. To overcome the ambiguity of perfect optical systems, often a cylindrical lens is introduced in the optical system which enhances the differences of the obtained particle images for different depth positions. However, various methods are emerging and it is difficult for non-experienced users to judge what method might be best suited for a given experimental setup. Therefore, the aim of the presentation is a thorough evaluation of the performance of general advanced methods, including also recently presented neural networks (Franchini and Krevor, 2020; Konig et al., 2020) based on typical images.

This paper focuses on the investigation of a multiphase flow of water, air, and abrasive particles inside and at the outlet of the abrasive head with the help of computational fluid dynamics calculations and measurements. A standard abrasive head with a water nozzle hole diameter of 0.33 mm (0.013”) and an abrasive nozzle cylindrical hole diameter of 1.02 mm (0.04”) were used for numerical modelling and practical testing. The computed tomography provided an exact 3D geometrical model of the cutting head that was used for the creation of the model. Velocity fields of abrasive particles at the outlet of the abrasive head were measured and analysed using particle tracking velocimetry and, consequently, compared with the calculated results. The calculation model took the distribution of the abrasive particle diameters with the help of the Rosin-Rammler function in intervals of diameters from 150 to 400 mm. In the present study, four levels of water pressure (105, 194, 302, 406 MPa) and four levels of abrasive mass flow rate (100, 200, 300, 400 kg/min) were combined. The values of water pressures and hydraulic powers measured at the abrasive head inlet were used as boundary conditions for numerical modelling. The hydraulic characteristics of the water jet were created from the measured and calculated data. The calculated pressure distribution in the cylindrical part of the abrasive nozzle was compared with studies by other authors. The details of the experiments and calculations are presented in this paper.

A novel simple and effective heating system for microfluidic direct methanol fuel cells was characterized experimentally. It consisted of a semi-conductive indium tin oxide heating layer of nanometer thickness that was applied to the anode and cathode cover plates and subjected to high electrical power. Within only 25 s, temperatures of up to 80 ∘ C were reached in the vicinity of the membrane, which was verified experimentally. With this system the time needed to generate more than 90 % of the maximum output power of the fuel cell can be reduced to 20 s, thus overcoming the well known problem of long start up times in the order of minutes of this type of fuel cells. Furthermore, deeper insight into the role of the convective heat transfer is given. For the first time simultaneous measurements of the three-dimensional velocity and temperature distributions within the anode channel of a microfluidic direct methanol fuel cell were performed by means of luminescence lifetime imaging and astigmatism particle tracking velocimetry. The experimental results prove a significant cooling effect of the anode flow, whereas the influence of the cathode flow is small. Finally, various possible future improvements to increase the efficiency of the heating system are identified.

Debris striking the internal structures of aircraft components is capable of causing on-board fires and leading to catastrophic damage to both the aircraft and flight crew. In the present work, two experiments were conducted to capture the characteristics of high-speed debris strikes and dry-bay fires. Particle tracking velocimetry technique was utilized to investigate the dynamics of debris striking structural components of the aircraft. In conjunction, a flame front detection measurement technique was developed to identify the size and duration of dry-bay fires. Results demonstrated the ability to utilize fundamental image correlation techniques to determine velocity, size, and duration of flash events in support of aircraft survivability and safety research.

In oil and gas industry, an increase in production is often achieved by injecting fracturing fluids with particles/proppants into rocks and reservoirs. There are various fracking fluids that oil and gas companies use, and some of these fracturing fluids demonstrate non-Newtonian flow behavior. In this paper, sand erosion behavior in shear-thinning carboxymethyl cellulose (CMC) solution is investigated with a jet impingement facility. Particularly, near wall flow speeds and particle impinging speeds are investigated in shear-thinning CMC fluids by Particle Image Velocimetery (PIV) and Particle Tracing Velocimetery (PTV) techniques. Computational Fluid Dynamics (CFD) are also used to predict the near wall particle impact information. The results indicate that different turbulence models resolve different near wall flow and particle impact characteristics. User Defined Functions (UDF) are developed and used to implement erosion ratio equations and simulate solid particle erosion behavior in the non-Newtonian fluid. The predictions are compared with experimental results. The results of this study can help improving erosion prediction in the hydraulic fracturing process utilizing CFD.

Particle tracking velocimetry (PTV) is a promising image-based approach for remote streamflow measurements in natural environments. However, most PTV approaches require highly-defined round-shaped tracers, which are often difficult to observe outdoors. PTV-Stream offers a versatile alternative to cross-correlation-based PTV by affording the identification and tracking of features of any shape transiting in the field of view. This nearest-neighbor algorithm is inherently thought for estimating surface flow velocity of streams in outdoor conditions. The procedure allows for reconstructing and filtering the trajectories of features that are more likely to pertain to actual objects transiting in the field of view rather than to water reflections. The procedure is computationally efficient and is demonstrated to yield accurate measurements even in case of downsampled image sequences.

We propose a seeding particle-based color-to-depth calibration methodology for three-dimensional color particle tracking velocimetry (3D color PTV) using a single camera and volumetric rainbow gradient illumination. The use of sheet-color illumination from a liquid crystal display projector enables in situ calibration, namely the color-to-depth relationships of particles seeded in a fluid are determined without inserting any calibration equipment or taking a different optical setup. That is, in this methodology, the calibration and application can be performed using the same optical configuration, and only the digital illumination patterns need to be changed. Adopting this calibration allows evaluating actual color-to-depth relationships of the particles in measurements. The calibration is conducted regarding the relationship between spatially distributed particle colors and their depth coordinates by support of an artificial neural network. By combining conventional PTV with the depth estimated by the color, particle trajectories in 3D real space can be reconstructed from the calibration. The performance of the proposed method was evaluated using a rotating flow in a cylindrical tank by comparing its results with the flow fields measured by conventional particle image velocimetry. Good accordance in the comparison at the highly 3D flow suggests the applicability of the present methodology for various flow configurations.

This Letter introduces a new, to the best of our knowledge, particle streak velocimetry technique based on decaying streaks formed by individual phosphor particles following pulsed excitation. Tin-doped phosphor particles are dispersed into flows and excited by a pulsed UV laser light sheet. Emission streaks are recorded as a result of particle motion during the persistence of luminescence (here ∼ 27 µ s ). The two components of the flow velocity are derived from the streaks without directional ambiguity by applying to each streak a two-dimensional fit describing a linearly moving point source with a mono-exponential decaying emission. This technique can achieve high spatial resolution compared to particle image velocimetry (PIV), while also requiring much fewer computational resources than particle tracking velocimetry (PTV) at high seeding densities. The wavelength-shifted luminescence also allows rejection of reflected laser light. The approach was validated in a free jet against simultaneous PTV and PIV and then successfully applied to measure a canonical boundary layer flow.

Background: Pressurized IntraPeritoneal Aerosol Chemotherapy (PIPAC) is a therapy option for patients with peritoneal metastases During PIPAC, a high-pressure injector delivers the drugs through a nebulizer into the peritoneal cavity However, gravity typically causes inhomogeneous droplet distribution in the peritoneal space and may be overcome by the addition of an electrostatic force, resulting in electrostatic precipitation PIPAC (ePIPAC) Our goal was to find the optimal electrical potential for ePIPAC by means of in vitro experiments and numerical modeling Materials and Methods: The ePIPAC in vitro experiments were performed in a Plexiglas box model, representing the peritoneal space Rat peritoneal tissue samples (185x135x152 mm3) were placed on 4 plates mounted at the inner boundaries of the box The box was first infused with CO2 gas to reach a pressure of 12 mmHg Black ink (20 mL) was subsequently injected with a high-pressure injector (Injektron™, Germany) at a flow rate of 0 5 mL/s Afterwards, the tissue specimens were digitally photographed and the distribution of ink was quantified using ImageJ In addition, a computational fluid dynamics (CFD) model of the box was generated using the CFD, AC/DC and Particle Tracing Modules in COMSOL Multiphysics (Burlington, VT) The initial (zero pressure) and boundary conditions (inlet flow at 12 mmHg) were assumed, consisting of the pressure, flow rate and the properties of the ink with considering drag, gravitational and electrical forces To study the impact of applied electrical potential, the electrostatic field was modeled using a brush electrode with a voltage of 4, 5, 6, 6 5, 7, 8 or 9 kV as a source and four metal plates as grounds Results: Imposing an electrostatic field to the PIPAC setup (ePIPAC) a more homogeneous aerosol droplet distribution in the box A significant increase for proportion of ink (a minimum of 60%) was observed at the stained tissue surface on the top wall of the box The results showed an overall good agreement for the experiments and simulation The electrical potential sensitivity analysis revealed that the aerosol droplets distribution became more homogeneous as the electrical potential increased, but no further improvements were obtained after 6 5 kV Consequently, the optimum electrical potential for ePIPAC was 6 5 kV Conclusions: In conclusion, electrostatic precipitation was shown to improve drug distribution during PIPAC and, hence, may lead to better anticancer efficacy Also, the simulation technique allows developing methods to predict droplet behavior and improve drug delivery Impact of COVID-19 on cancer surgical care

We present a joint optimization framework for four-dimensional (4D) optical imaging: volumes and movements are reconstructed jointly in a higher space-time dimen- sion, enabling faster convergence and better reconstruction quality of both the volumes and movements within a few minutes on modern GPUs. We verified the framework on digital holographic particle tracking velocimetry, a typical 4D optical imaging example. Experi- mental results are presented to show the efficiency of the proposed technique.

This study combines advanced optical diagnostics and high-fidelity Direct Numerical Simulations (DNS) to deepen the understanding of wall heat transfer processes in Otto engines under motored and fired conditions. To this end, a combination of optical diagnostics was applied simultaneously: High-resolution Particle Image Velocimetry (PIV) and Particle Tracking Velocimetry (PTV) to resolve the velocity boundary layer (BL) above the piston, Thermographic Phosphor Thermometry (TPT) to measure the wall temperature spatially resolved and Laser Induced Fluorescence (LIF) of SO2 to track the evolution of the flame. For the complementing simulations, an entire workflow was developed that employs process calculations (GT-Power), multi-cycle scale-resolving simulations (SRSs), and DNS. Well-calibrated GT-Power models provided boundary conditions for the experimentally validated SRSs, which in turn yielded initial conditions for the DNS. Using initial conditions from the SRSs at intake valve closure, the first ever DNS of a real engine geometry was successfully performed for one motored and one fired compression/expansion stroke. It was seen that momentum and thermal BLs evolve differently: the former are affected by changes in the bulk velocity (large scale tumble motion and its breakdown), while the temperature gradients monotonically follow the increase in pressure/Reynolds number. Both the scaled momentum and thermal BLs do not exhibit a logarithmic region and the law of the wall does not hold. Several sources for deviations thereto, both in momentum and thermal BLs, are extracted. For the reactive case, it was found that the early flame kernel development is significantly affected by the strong convective flow due to tumble and only when the flame is strong enough to counter-balance the strong convection it can propagate against it. A criterion has further been developed, which allows for distinction between head-on and side-wall quenching. The vast amount of high-fidelity experimental and fully resolved numerical data generated in this project provides a comprehensive database for validation of existing computational fluid dynamics (CFD) tools and can be used for the development of improved wall heat flux models. A first attempt has been made towards this direction by developing an algebraic wall heat transfer model for LES using a data-driven approach.

A novel method for three-dimensional particle tracking velocimetry (PTV) is proposed that enables flow measurements in large volumes [ $$V=\mathcal {O}(10$$ m $${^3}$$ )] using a single camera. Flow is seeded with centimeter-sized soap bubbles, when combined with suitable illumination, produce multiple glare points. The spacing between the two brightest glare points for each bubble is then utilized to reconstruct its depth. While the use of large soap bubbles comes at the expense of non-Stokesian behaviour, the excellent ray optics allow for large volume illumination when coupled with for instance pulsed LED banks. Possible error sources and the out-of-plane accuracy are discussed before the feasibility of the method is tested in an industrial-scale wind tunnel facility (test section of cross section 9.1 m $$\times$$ 9.1 m). In particular, the vortical structure in the wake of a 30%-scale tractor-trailer model at a $$9^{\circ }$$ yaw angle is captured in a 4.0 m $$\times$$ 1.5 m $$\times$$ 1.5 m measurement volume. Long tracks of up to 80 time steps are extracted in three-dimensional space via a single perspective. The successful proof-of-concept confirms the potential of the novel approach for three-dimensional measurements in volumes of industrial scale.

This paper proposes a data assimilation method based on artificial intelligence (AI) to obtain sound level spectrum as increasing the spatial and temporal resolution of time-resolved three-dimensional Particle Tracking Velocimetry (4D PTV) data. A 4D PTV has used to measure flow characteristics of three side mirror models adopting the Shake-The-Box (STB) algorithm with four high-speed cameras on a robotic arm for measuring industrial scale. Helium filled soap bubbles are used as tracers in the wind tunnel experiment to characterize flow structures around automobile side mirror models. Full volumetric velocity fields and evolution of vortex structures are obtained and analyzed. Instantaneous pressure fields are deduced by solving a Poisson equation based on the 4D PTV data. To increase spatial and temporal resolutions of velocity field, artificial intelligence (AI)-based data assimilation method has applied. Adaptive Neural Fuzzy Inference System (ANFIS) based machine learning algorithm works well to find hidden 3D vortical structures behind the automobile side mirror model. Using the high resolution ANFIS model, power spectrum of velocity fluctuations and sound level spectrum of pressure fluctuations are successfully obtained to assess flow and noise characteristics of three different side mirror models.

DEVELOPMENT OF CONFOCAL IMAGING TECHNIQUES FOR PROBING INTERFACIAL DYNAMICS IN MICROSCALE, GAS-LIQUID, TWO-PHASE FLOW Joseph E. Hernandez Michigan Technological University, 2014 Advisor: Dr. Jeffrey S. Allen Micro-scale, two-phase flow is found in a variety of devices such as Lab-on-a-chip, bio-chips, micro-heat exchangers, and fuel cells. Knowledge of the fluid behavior near the dynamic gas-liquid interface is required for developing accurate predictive models. Light is distorted near a curved gas-liquid interface preventing accurate measurement of interfacial shape and internal liquid velocities. This research focused on the development of experimental methods designed to isolate and probe dynamic liquid films and measure velocity fields near a moving gas-liquid interface. A highspeed, reflectance, swept-field confocal (RSFC) imaging system was developed for imaging near curved surfaces. Experimental studies of dynamic gas-liquid interface of micro-scale, two-phase flow were conducted in three phases. Dynamic liquid film thicknesses of segmented, two

Our paper provides an approach to create line-drawing stylizations of input images. The main idea is to use particle tracing with interaction between nearby particles: the particles coordinate their movements so as to produce varied but roughly parallel traces. The particle density varies according to the tone in the input images, thereby expressing bright and dark areas. Using procedural distributions of particles, we can also generate smooth abstract patterns.

Zinc-air flow batteries provide a scalable and cost-efficient energy storage solution. However, the achieved power density depends on the local flow conditions of the zinc particle suspension in the electrochemical cell. Numerical modeling is challenging due to the complex multiphase fluid and the interaction of flow and electrochemistry. Hence, performing experiments is crucial to investigate the influence of the flow conditions on the electrical performance, which requires flow instrumentation for the opaque suspension. To resolve the flow field across the 2.6-mm-wide flow channel of the investigated zinc-air flow battery (ZAB), a spatial resolution below 100 $\mu \text{m}$ has to be typically achieved. Using ultrasound techniques, the achieved spatial resolution is limited by the trade-off between ultrasound frequency and imaging depth. This trade-off is even more critical for suspensions due to the scattering of the ultrasound, which increases strongly with frequency. We propose super-resolution particle tracking velocimetry (SRPTV) to overcome this limitation by achieving the required spatial resolution at a low ultrasound frequency. SRPTV is based on the super-resolution technique ultrasound localization microscopy, which is adapted to strongly scattering suspensions by using a dual-frequency-phased array and applying a coherence weighting beamformer to suppress speckles, which result from the scattering at the zinc particles of the suspension. The spatial resolution and the velocity uncertainty are characterized through calibration measurement and numerical simulation. A spatial resolution of 66 $\mu \text{m}$ at an excitation wavelength of 330 $\mu \text{m}$ was achieved, which is sufficient for performing flow investigation in an operational ZAB. The measured flow profile reveals shear-thinning properties and wall slip and therefore differs significantly from a parabolic flow profile of a Newtonian fluid. The presented technique offers potential for performing flow investigations of suspensions in small geometries with a spatial resolution beyond the diffraction limit.

The encoded Particle Tracking Velocimetry (ePTV) is introduce in this paper as a specific approach of Particle Tracking Velocimetry (PTV). This method is applied to track particles obtained from flow images that contain significant background noise and relatively low particle density. Encoding is achieved by illuminating the flow with a series of light pulses within individual image exposures. Dependent upon the velocity, each particle will be illuminated multiple times in each image frame with spacing determined by both the pulse train timing and the particle velocity. A search algorithm is used that identifies each particle and seeks the encoded pattern with other particles in the image, repeating this until all encoded particles are found. Based on probability analysis and finite image size an analytic model is developed to determine the ratio of true particles, false particles and those that are ‘lost’ by exiting the image frame. This ePTV technique has been experimentally implemented to track spherical particles suspended in stationary vortices. By using a suspension of micro-particles, subsequent imaging with encoded pulse trains provided snap-shots of the complex flow patterns. Typically, even after filtering, the images show around 100 to 200 particles from which encoded trajectories have been extracted and typically account for about 30% of the objects identified in the image.

Separation of large-sized micro-particles or biological cells inside micro-fluidic environment has significant biomedical applications. In the present work, a spiral micro-channel of comparatively larger dimension has been used for separation of polymeric micro-particles based on their dimensions. A spiral micro-channel can also be effectively used for large-sized biological cell or circulating tumour cell (CTC) isolation. Conventional methods are generally used to fabricate small and precise micro-channels to achieve such separation. This requires sophisticated (mostly lithographic) fabrication facility which is time-consuming and costly. In the present study, a novel approach has been introduced to fabricate spiral micro-channel. A low-cost laser machining method has been used for fabricating the micro-channel that works on the concept of Dean’s flow fractionation for particle separation. In order to investigate the Dean’s flow-based separation process, we have modelled the overall process on a computational fluid dynamics (CFD) platform and have done the necessary simulations. For understanding the trajectories of particle flow inside the channel, we have done particle tracing study to reveal the physics of separation process based on Dean’s flow.

An algorithm for correcting color contamination is proposed for two-color, double-exposure particle tracking velocimetry (PTV). A two-color PTV system used in this study consists of blue and green laser diodes and a consumer digital camera, where a laser pulser with an avalanche transistor is developed for achieving optical pulses of 50 ns for application in airflows. In the PTV, the camera captures images of tracer particles illuminated by a sequence of green and blue light pulses with a certain time interval. Because of spectral characteristics of a Bayer filter, camera sensors in a blue channel respond to green light scattered by the particles. This color contamination results in pseudo-particles in the blue channel. Pixels occupied by the pseudo-particles have very high correlation of light intensity between green and blue channels. In the proposed method, the pseudo-particles caused by the color contamination are detected and removed based on the high correlation. The present color contamination correction hardly affects real particles illuminated by the blue laser diodes. Measurements of an airflow induced by DC fans confirm that the proposed system with the color contamination correction works well for PTV.

Computational fluid dynamics and particle tracing simulations are presented for a cloud droplet sensor. Airspeeds and streamlines around the sensor are calculated at several wind speeds and their effect on the droplet sampling are examined. Particle tracing is used to study the effect of different wind speeds and droplet sizes on the sampling of the cloud droplets. Simulated droplet concentrations are confirmed by comparing them with measured wind tunnel data. Results demonstrate clear sampling effects that are functions of both wind speed and droplet size. Optimal compromise between maximal measurement volume and sampling effects is found and a simple approximation for sensor’s sampling bias is presented. The results show that CFD simulations can give valuable information about the sampling of droplets in an ideal environment with known droplet concentrations. Even in a wind tunnel, the true test conditions are often impossible to accurately determine. Thus by simulating the sampling effects in different conditions, the sensor can be calibrated for a wide range of naturally occurring cloud conditions.

Dust devils are atmospheric air vortices with a vertical axis, which are formed by strong sun radiation and the resulting vertical temperature gradient. The structure of a typical dust devil is dominated by a radial inflow near the surface and a vertical upward flow within the vortex. Since experimental investigations are limited to local in-situ measurements of the atmosphere, many mechanisms related to their formation and their characteristic properties are insufficiently understood. We will present an idea how dust devils can be generated in a laboratory experiment and how processes, which contribute to their formation, can be investigated.We have chosen the so-called Rayleigh-Bénard set-up as an appropriate model experiment for our investigations. The "Barrel of Ilmenau" is a test facility, which consists mainly of an air-filled, cylindrical tank with a total diameter of 7 m and a total height of 8 m. At the bottom of the tank is a heating plate, whose temperature can be set precisely between 20°C and 80°C. A second plate, which can be positioned at any height between 0.2m and 6.3m above the heating plate, is used for cooling and can be set to temperatures as low as 10°C...30 °C. This results in a total temperature difference of up to 70K which is significantly beyond the temperature difference of the atmospheric boundary layer. The side wall of the tank is adiabatic. Due to the isothermal plates and a compensation heating system, a temperature that is constant over time is reached and controlled boundary conditions can be assumed.For the characterization of Dust Devil-like vortices, an optical measurement method is used to obtain the trajectories of single particles. Since there are no commercial systems that are suitable for such a large measurement volume, we created our own system. The measurements in the RB cell are carried out with an aspect ratio Γ=3 and a Ra number of Ra=2x1010 and Ra=8x1010. With the help of the measurements we want to show that Dust Devil-like vortices are created. The structure should be characterized and the results will be compared to DNS.

Particle recognition and particle matching are the core of particle tracking velocimetry (PTV). Particle recognition and matching directly determine the accuracy of flow field analysis, and particle recognition is a prerequisite for matching. In the engineering application of PTV technology, there are various reasons for the image noise generated by shooting, which seriously interferes with particle recognition. Accurately separating particles from noise is the most important and difficult process in particle recognition while ensuring that particle information is not damaged. According to the particle image captured by PTV experiment, the author has proposed a new processing method for denoising and recognition of noise-containing original image (ImageDenoising-ParticleRecognition). This method comprehensively uses SUSAN detection, expansion calculation, threshold segmentation, four-connected mark, non-particle culling, particle hole filling and other technologies to protect the image information of particles from loss to the maximum extent and ensure that the noise-containing particle images can complete particle recognition in one step. At the same time, the method proposed in this paper more accurately determines the edge of the particle image, and provides a more reliable particle image for the calculation of the flow field motion in the later stage. For the method proposed in this paper, based on the Visual C++ platform autonomous programming, the particle images generated by computer simulation and the SiO2 particle image with 500 nm diameter shot by the actual PTV experiment have been verified and analyzed respectively, and the recognition results with good accuracy have been obtained. The preprocessing of particle image is the prerequisite of PTV processing, and its level directly has a crucial impact on the final analysis accuracy of the flow field. According to the particle image captured by PTV experiment, the author has proposed a new preprocessing method to provide a more reliable particle image for the calculation of the flow field motion in the later stage.

X-ray particle tracking velocimetry (PTV) is performed, for the first time, to measure the velocity field inside a leading-edge of a turbine blade made by laser-additive-manufacturing (LAM) process. The traditional showerhead holes were replaced by a porous matrix in the leading-edge. The flow through such a leading-edge piece cannot be faithfully recreated by traditional prototype testing methods due to the surface roughness and imperfections caused by LAM process. Hence, direct measurement is the only option. However, it is difficult to measure flow inside such pieces with traditional velocimetry measurements due to the existence of metallic walls. Moreover, small internal size and high flow speeds call for a measurement technique with high spatial and temporal resolutions. To address these issues, we performed time-resolved X-ray PTV using the Advanced Photon Source (APS) synchrotron facility at the Argonne National Laboratory (ANL). A hydraulic system was constructed to run water, mixed with seeding particles, through the leading-edge piece. A high-speed camera captured the images of the seeding particles, which were later processed to create particle tracks. The time-averaged velocity field showed distinct pairs of vortices located in front of the porous outlet inside the leading-edge piece. The inlet channel showed reversed flow due to partial obstruction by the porous inlet of the test piece. Such knowledge of the flow field inside a leading-edge of a turbine blade will help us to design better cooling paths leading to higher cooling efficiency and increased life-span of a turbine blade.

In the present study, a simple method is developed to apply astigmatism particle tracking velocimetry (APTV) to transparent particles utilizing backlight illumination. Here, a particle acts as ball lens and bundles the light to a focal point, which is used to determine the particle’s out-of-plane position. Due to the distance between focal point and particle, additional features have to be considered in ball lens astigmatism particle tracking velocimetry (BLAPTV) compared to conventional APTV. We describe required calibration steps and perform parameter studies to show how the autocorrelation coefficient and the light exposure affect the accuracy of the method. It is found that the accuracy and robustness of the Euclidean calibration approach as also used in conventional APTV (Cierpka et al. in Meas Sci Technol 22(1):015401, 2010a) can be increased if an additional calibration curve for the light intensity of the particle’s focal point is considered. In addition, we study the influence of the particle diameter and the refractive index jump between liquid and particles on the calibration curves and the accuracy. In this way, particles of the same size, but different material, can be distinguished by their calibration curve. Furthermore, an approach is presented to account for shape changes of the calibration curve along the depth of the measurement volume. Overall, BLAPTV provides high out-of-plane particle reconstruction accuracies with respect to the particle diameter. In test cases, position uncertainties down to 1.8% of the particle diameter are achieved for particles of $$d_{\mathrm{p}}={124}\,{\upmu \hbox {m}}$$dp=124μm. The measurement technique is validated for a laminar flow in a straight rectangular channel with a cross-sectional area of $$2.3 \times 30$$2.3×30 $$\hbox {mm}^2$$mm2. Uncertainties of 0.75% for the in-plane and 2.29% for out-of-plane velocity with respect to the maximum streamwise velocity are achieved.Graphic abstract

Flow fields in rotary blood pumps (RBPs) have a significant influence on hemocompatibility. Because flow characteristics vary with flow rate, different operating conditions play a role. Furthermore, turbulence is crucial in the evaluation of blood damage potential, but the level of turbulence in implantable RBPs is still unknown. In this study, we addressed both research aspects and for the first time measured turbulent flow fields in the HeartMate 3 (HM3) at different operating flows. The averaged, three-dimensional velocity field including fluctuating velocity components in a HM3 with a transparent lower housing was measured using three-dimensional particle tracking velocimetry (3D-PTV). In vitro results were compared with computational fluid dynamic (CFD) simulations for two flow cases, representing the lower and upper physiologic flow range (2.7 and 5.7 L/min), using two different turbulence models that account for fluctuating velocity fields: the k-ω shear stress transport and the Reynolds stress model (RSM). The measurements revealed higher mean and turbulent kinetic energies (TKEs) for the low-flow condition especially within the gap beneath the impeller. Computed mean fields agree well with 3D-PTV for both models, but the RSM predicts the TKE levels better than the k-ω model. Computational fluid dynamic results further show wall shear stresses higher than 150 Pa, a commonly used damage threshold, in the bottom gap for the lower flow condition. In conclusion, the low-flow condition was found to be more prone to blood damage. Furthermore, CFD predictions for turbulence must be carefully experimentally validated.

Existing Particle Imaging Velocimetry techniques require the use of high-speed cameras to reconstruct time-resolved fluid flows. These cameras provide high-resolution images at high frame rates, which generates bandwidth and memory issues. By capturing only changes in the brightness with a very low latency and at low data rate, event-based cameras have the ability to tackle such issues. In this paper, we present a new framework that retrieves dense 3D measurements of the fluid velocity field using a pair of event-based cameras. First, we track particles inside the two event sequences in order to estimate their 2D velocity in the two sequences of images. A stereo-matching step is then performed to retrieve their 3D positions. These intermediate outputs are incorporated into an optimization framework that also includes physically plausible regularizers, in order to retrieve the 3D velocity field. Extensive experiments on both simulated and real data demonstrate the efficacy of our approach.

In this work, we introduce a novel approach to measure the flow velocity of liquid foam by tracking custom-tailored 3D-printed tracers in X-ray radiography. In contrast to optical observations of foam flow in flat cells, the measurement depth equals 100mm in X-ray beam direction. Light-weight tracers of millimetric size and tetrapod-inspired shape are additively manufactured from stainless steel powder by selective laser melting. Matching with the foam structure and bubble size, these tracers follow the foam flow minimally invasively. An X-ray beam passes through the radiotransparent foam channel and is detected by an X-ray image intensifier. The X-ray transmission images show the two-dimensional projections of the radiopaque tracers. Employing particle tracking velocimetry algorithms, the tracer trajectories are measured with both high spatial (0.2 mm) and temporal (25 fps) resolution. Fine-pored and coarse-pored liquid foam flow of different velocities are studied in a partly curved channel with rectangular cross section. The simultaneous time-resolved measurement of the tracers' translational motion and their intrinsic rotation reveal both the local velocity and vorticity of the foam flow. In the semi-circular curved channel section, the rigid-body-like flow pattern is investigated. Moreover, a relaxation of the foam structure in the transition zone between straight and curved section is observed.

The geometric parameters of labyrinth channels play an important role in the hydraulic and anti‐clogging performance of drip emitters. In this study, the flow fields, individual representative sands and sand groups in the labyrinth channel of emitters, with dentation angles of 90°, 60°, 45° and 30°, were firstly simulated using a computational fluid dynamics discrete element method (CFD–DEM) of coupling. Particle tracking velocimetry (PTV) was used to trace individual representative sands. The numerical results were verified with clear water hydraulic performance tests and muddy water anti‐clogging performance tests. The results suggest that the discharge coefficient and flow exponent declined when the dentation angle of the labyrinth channel was reduced. A large number of sand groups were observed to enter the vortex areas and move in a circular manner. The time it took for particles to pass through the labyrinth channel lengthened when the velocity decreased and as a result, the probability of emitter clogging increased. Therefore, by using a recommended angle range of 90° to 60° and a combined higher hydraulic performance level, emitters were less likely to clog. It was a novel approach to adopt a CFD–DEM coupling method to conduct numerical analysis of individual sand particles and sand groups in the investigation of emitter anti‐clogging issues. The findings will increase the design efficiency of flow channels and will save human and material resources. © 2018 John Wiley & Sons, Ltd.

Particle tracking velocimetry (PTV) is a quantitative field measuring technique originally developed to track and measure the velocity of individual particles in fluid flows. In this study, PTV was applied for the first time in three different experimental studies in the field of structural timber engineering: (1) dowel embedment testing in cross laminated timber (CLT), (2) large-scale dowelled CLT connection testing, (3) material testing of small clear wood and laminated veneer lumber (LVL). The suitability of PTV was first assessed by comparing the PTV displacements to those obtained by potentiometers. Furthermore, the behaviour of the timber substrate was analysed with PTV in both embedment and large-scale connection tests. It was found that PTV was able to not only accurately measure dowel displacements, but also capture crack growth in the timber and compute the resulting displacement and strain fields in the dowel embedment area. Lastly, PTV was applied to small clear specimen testing to capture brittle fracture in shear, tension perpendicular to the grain, and in cleavage. This study demonstrated that PTV is able to provide reliable contact-free high-resolution measurements of displacement and strain fields on exposed timber surfaces and capture failure mechanisms such as brittle fractures and crack growth.

Dual-angle particle tracking velocimetry (PTV) developed previously by the authors Pham et al. (2017) has been extended in this study to simultaneously measure volume and velocity of both irregular and sub-ranged spherical fragments generated in the near-field of atomizing sprays, enabling measurements of local Weber number. Dual-angle PTV is an imaging based technique where fragment morphologies are captured using two cameras oriented at 90 degrees to each other. Both cameras operate under PIV (particle imaging velocimetry) mode to enable tracking of fragment locations. In this contribution, fragments are sub-ranged, depending on their size, into 3 different groups: larger fragments (d10 > 150 μm), medium fragments (150 μm > d10 > 15 μm) and small droplets (d10

In order to understand the flow structure of a flickering flame, time-resolved observations are carried out of the velocity and density fields in a diffusion flame in co-flow using particle image velocimetry (PIV) and shadowgraph imaging, respectively. The PIV measurement combined with invalid velocity vector analysis using proper orthogonal decomposition (POD) allows for the high spatial resolution measurement of the velocity field in the flame, while the shadowgraph images show the high-temperature contour and soot formation of the flame. These experimental results indicate a periodic variation in the flow field and soot structure of the flickering flame. The observation of the velocity field shows that the periodic inflow and outflow are generated in the outer layer of the flame near the burner, which promotes the flow acceleration in the vertical direction leading to clip-off behavior. It is found that the vorticity contour evaluated from the velocity field matches well with the high-temperature contour observed in the shadowgraph images. Further examination of the flow structure is carried out using the first two POD modes, which demonstrate the presence of counter-rotating vortices in the outer flame contributing to stretching of the flame due to the clip-off motion in the flame.

Total internal reflection fluorescence microscopy (TIRFM) is a promising method for measuring fluid flow close to a wall with nanoscale resolution in a process that is termed “multilayer nanoparticle image velocimetry” (MnPIV). TIRFM uses evanescent light that is generated on a substrate (typically a glass slide) by total internal reflection of light. Many researchers have previously studied x–y–z (3D) flows of water close to flat glass slides using MnPIV. On the other hand, a fluid flow close to a structured surface is also important. To measure flows of water near micro-patterns, we previously developed an MnPIV technique that uses a refractive-index-matching method. In previous study, the micropattern is made of a thermoplastic material with a refractive index that closely matches that of water. In this study, ultraviolet nanoimprint lithography was used for fabricating the appropriate micro-patterns because this technique can fabricate a pattern with a high resolution. As a result, we succeeded in performing MnPIV in water with a circular hole array pattern made by ultraviolet nanoimprint using a refractive-index-matching method. We believe that this technique will be helpful in elucidating fluid flows around microstructures.