Velocity Field Information Research Articles

Slip velocity and field information of two-phase cavitating flows

In this work, laser-induced florescent particle image velocimetry was performed to measure simultaneously the liquid and vapor velocity fields at the mid-span of a small-scale Venturi type section to determine the presence of a slip velocity between the phases. Various dynamic behavior and Kelvin–Helmholtz (K-H) instability involved in the cloud cavity shedding regime are discussed at four different cavitation numbers. The velocity, vorticity, and turbulence field information of the two phases are analyzed. The liquid–vapor mixture in a cavitating flow is usually considered a homogeneous medium in currently used computational models, but it is shown in this study that the two phases have very different dynamics. The measurements of the time-averaged velocities highlight the existence of a noteworthy slippage between the liquid and the vapor phases, especially in the upstream part of the cavitation region, where the slippage between the two phases can reach about 50% of the liquid velocity. Using phase-locked average, it is shown that the slip velocity in the upstream region is mainly located at the upper liquid–vapor interface, while the slip velocity in the closure area is near the bottom wall, due to the reentrant jet. These results contradict a primary assumption of the current models, where the medium is usually considered as a homogeneous mixture with a unique velocity field, thus providing a reference for future computational model improvement.

Enhancing Accuracy In 3D Defocusing Particle Tracking Using 3D-Printed Ramp

Three-dimensional defocusing particle tracking velocimetry (3D DPTV) is an emerging tool for investigating fluid motion within microfluidic devices, where observation is typically limited to a single direction. This technique enables the reconstruction of 3D flow fields by analyzing the defocused particle images. The accuracy of 3D DPTV significantly relies on the collection of a proper calibration image stack containing particle images with precisely known defocus distances. One major challenge is to insert a microscale calibration target inside the microfluidic devices due to the small length scales of microfluidic devices. While the alternative approaches such as using tilted glass slides or conducting z-scans of particles fixed at the bottom wall, face several limitations. Here, we present the application of a two-photon polymerization (2PP) based method to manufacture a microscale reference ramp as the calibration target. We demonstrate the fabrication of a precise reference ramp structure that spans the desired calibration range to enhance accuracy in 3D defocusing particle tracking. We experimentally and computationally compare the result with the commonly employed methods to obtain the calibration image stack. The performance of the 2PP-based calibration ramps is compared with the z-scanning method using the General Particle tracking (GPTV). The results demonstrate that the z-scanning method underestimates the defocused distances compared to the ground truth provided by the ramp approach, with the error increasing as the defocused distance grows. The integration of microscale calibration targets using 2PP fabrication method offers a significant advancement in the reliability and accuracy of 3D DPTV measurements in microfluidic systems. By enabling precise, device-specific calibration, this approach can enhance the fidelity of flow field reconstructions, benefiting a wide range of microfluidic applications that rely on detailed velocity field information.

Artificial intelligence-based speckle featurization and localization for ultrasound speckle tracking velocimetry

Deep learning-based super-resolution ultrasound (DL-SRU) framework has been successful in improving spatial resolution and measuring the velocity field information of a blood flows by localizing and tracking speckle signals of red blood cells (RBCs) without using any contrast agents. However, DL-SRU can localize only a small part of the speckle signals of blood flow owing to ambiguity problems encountered in the classification of blood flow signals from ultrasound B-mode images and the building up of suitable datasets required for training artificial neural networks, as well as the structural limitations of the neural network itself. An artificial intelligence-based speckle featurization and localization (AI-SFL) framework is proposed in this study. It includes a machine learning-based algorithm for classifying blood flow signals from ultrasound B-mode images, dimensionality reduction for featurizing speckle patterns of the classified blood flow signals by approximating them with quantitative values. A novel and robust neural network (ResSU-net) is trained using the online data generation (ODG) method and the extracted speckle features. The super-resolution performance of the proposed AI-SFL and ODG method is evaluated and compared with the results of previous U-net and conventional data augmentation methods under in silico conditions. The predicted locations of RBCs by the AI-SFL and DL-SRU for speckle patterns of blood flow are applied to a PTV algorithm to measure quantitative velocity fields of the flow. Finally, the feasibility of the proposed AI-SFL framework for measuring real blood flows is verified under in vivo conditions.

Massive laser pulling of graphene nanosheets in water.

Light manipulation of graphene-based materials attracts much attentions. As a new light manipulation concept, optical pulling develops rapidly in the past decade. However, optical pulling of graphene in liquid is rarely reported. In this work, laser pulling of graphene nanosheets (GN) in pure water by using common gauss beams is presented. This phenomenon holds for multiple incident laser wavelengths including 405 nm, 488 nm, 532 nm and 650 nm. A particle image velocimetry software PIVlab is adopted to analyze the velocity field information of GN. The laser pulling velocity of the GN is approximately ∼ 0.5 mm/s corresponding to ∼ 103 body length/s, which increases with an increase of the incident laser energy. This work presents a contactless mothed to massively pull microscale graphene materials in simple liquid, which supplies a potential manipulation technique for micro-nanofluidic devices and also provides a platform to investigate laser-graphene interaction in a simple liquid phase medium.

Experimental Study on the Flow Pattern of Double-hemisphere Rough Elements with Different Streamwise Spacing

Particle image velocimetry is used to study the variation around single- and double-hemisphere rough elements with different streamwise spacings immersed in the boundary layer. Instantaneous velocity field information in the streamwise–normal and streamwise–spanwise directions is collected at a Reynolds number of 1800. 3R, 5R, and 7R are determined as the rough element spacing used in the double-hemisphere rough element experiment, representing the smaller, medium transition, and larger rough element spacing, respectively. The average velocity, Reynolds shear stress, shedding frequency, and proper orthogonal decomposition results of the flow field around the rough elements under various working conditions were compared. The downstream hemisphere will encroach on the streamline following the upstream hemisphere, and changing the spacing means changing the position of the encroached area. When the spacing is smaller, the streamline reattachment is destroyed, and the momentum and mass exchange between the two-hemisphere rough elements decreases. The double-hemisphere rough element is a slender, blunt, rough element. At the medium transition spacing, the shear layer and vortex structure shed from the upstream hemisphere are over the downstream hemisphere, and the double-hemisphere rough elements will cause disturbance in a larger wall-normal range. The streamline has been reattached at the larger streamwise spacing, and the interaction between the two hemispheres is the weakest. Here, the double-hemisphere rough element will form the recirculation zone, recirculation arch vortex, and periodic hairpin vortex.

LEGO calibration targets for large-FOV particle image velocimetry

Particle image or particle–tracking velocimetry nonintrusively provides velocity field information, and the proposition large field-of-view (FOV) measurements are highly attractive from an experimental standpoint. Stitching multiple smaller FOVs to achieve the large FOV of interest is an approach that faces challenges rooted in the calibration process. For stereoscopic PIV (SPIV), the use of a multi-level target simplifies calibration. However, this is problematic for large-FOV measurements, as standardised multi-level targets are relatively small and expensive. LEGO® bricks are well-suited to the construction of large, customised multi-level targets due to their high-dimensional tolerance and their stackability with high precision. To evaluate the feasibility of LEGO®-based targets, a two-sided multi-level target covering 380 times 1150 mm was created and used for SPIV measurements of the inflow conditions of the Atmospheric Wind Tunnel Munich. Calibrations were also performed using the Type 31 target for comparison. Analysis of the datasets with both calibration targets shows good agreement in the measurement of the streamwise, out-of-plane component u. A parametric study of different LEGO® target configurations was used to verify the calibration performance of the targets as well as identify optimal configurations for experimental use. Due to the high level of agreement in calibration parameters and quantitative and qualitative flowfield parameters in PIV tests, as well as the consistency observed in the subsequent parametric study, LEGO-based calibration targets show potential for further development and usage in large-FOV measurements.Graphic abstract

Experimental Study of the Particles Influence on the Pyramid Wake within the Turbulent Boundary Layer

Particle imaging velocimetry (PIV) was used to study the near-field variation of a pyramid rough element in clear water and a liquid–solid boundary layer (thickness: 60 mm). Particles with an average diameter of 355 µm and Stokes number of 4.3 were injected into a 1:1000 mass ratio (solid particles: water) liquid–solid two-phase solution. Experiments were conducted to collect instantaneous velocity field information in the streamwise–normal direction and streamwise–spanwise direction at a Reynolds number of 8350. Then, the average velocity field and turbulence intensity of the rough element wake under single-phase and two-phase conditions were compared, and the morphology and periodicity of the shedding structure were analyzed by using proper orthogonal decomposition (POD) combined with the power spectral density function (PSD). Particles were shown to have no significant impact on the recirculation area in the streamwise–spanwise plane but did result in a reduction of the recirculation zone in the streamwise–normal plane and a 0.2h closer location of the streamline's origin to the obstacle. Along with the weakening of the upwash structure, the particle phase diminishes the velocity gradient along the span direction and turbulence intensity. Structural shedding at the top of the pyramid and near the wall occurred simultaneously, and the same shedding period was maintained. Particularly, in the first two POD modes, the energy of the shedding structure near the wall was higher than that at the obstacle tip, with a maximum energy differential of approximately 6%. The Strouhal number of the shedding structure decreased by particles from 0.217 to 0.209. The concentration distribution and degree of dispersion in the particle-laden flow illustrate different results, with lower statistics in the wake flow field.

Place cells dynamically refine grid cell activities to reduce error accumulation during path integration in a continuous attractor model

Navigation is one of the most fundamental skills of animals. During spatial navigation, grid cells in the medial entorhinal cortex process speed and direction of the animal to map the environment. Hippocampal place cells, in turn, encode place using sensory signals and reduce the accumulated error of grid cells for path integration. Although both cell types are part of the path integration system, the dynamic relationship between place and grid cells and the error reduction mechanism is yet to be understood. We implemented a realistic model of grid cells based on a continuous attractor model. The grid cell model was coupled to a place cell model to address their dynamic relationship during a simulated animal’s exploration of a square arena. The grid cell model processed the animal’s velocity and place field information from place cells. Place cells incorporated salient visual features and proximity information with input from grid cells to define their place fields. Grid cells had similar spatial phases but a diversity of spacings and orientations. To determine the role of place cells in error reduction for path integration, the animal’s position estimates were decoded from grid cell activities with and without the place field input. We found that the accumulated error was reduced as place fields emerged during the exploration. Place fields closer to the animal’s current location contributed more to the error reduction than remote place fields. Place cells’ fields encoding space could function as spatial anchoring signals for precise path integration by grid cells.

LEGO Calibration Targets For Large-FOV Particle Image Velocimetry

Particle-image or particle-tracking velocimetry (PIV/PTV) nonintrusively provides velocity field information, and consequently, the proposition of measurements in a large plane is highly attractive from an experimental standpoint, particularly for experiments conducted in large atmospheric and flight-scale wind tunnels. Physical limits to the size of the useful field-of-view (FOV) that can be achieved with a single camera depend on striking a balance between the physical capabilities of the cameras and the physics of interest in the flow. A typical solution is to stitch together multiple smaller FOVs to achieve the large FOV of interest, presenting a number of challenges, some of which are rooted in the calibration process. For SPIV calibrations, the use of a multi-level target simplifies the calibration process. However, this is problematic for large-FOV measurements, as standardised multi-level targets are typically relatively small and expensive due to the precision-engineering required. As an alternative, LEGO bricks are extremely well-suited to the construction of large, customised multi-level targets due to their high dimensional tolerance and their stackability with high precision. In order to create a prototype two-sided multi-level SPIV target and evaluate whether the LEGO bricks can be used successfully to calibrate a large FOV, the LaVision Type 31 target was chosen as a model. In order to further augment the flexibility offered by the LEGO-based targets, the backing used to mount the baseplates was designed to be modularly reconfigurable. The resultant two-sided multi-level target has an area of approximately 380 x 1150 mm. To evaluate the target, SPIV measurements of the inflow conditions of the Atmospheric Wind Tunnel Munich (AWM) were performed; calibrations were also performed using the Type 31 target for comparison. Analysis of the datasets with both calibration targets shows good agreement in the measurement of the streamwise, out-of-plane component u. However, there is some uncertainty regarding the accuracy of the computation of in-plane components. Due to the high level of agreement in calibration parameters, out-of-plane component, and the qualitative location of flow features, this disagreement is believed to be a fixable issue. These early results indicate that with some refinement, the LEGO-based calibration target can be developed further and used for large-FOV measurements in the future.

Low-cost surface particle image velocimetry for hydraulic model studies

An application of a large-scale PIV technique on a scaled hydraulic model of a hydroelectric powerplant was performed. A detailed study regarding the relationship between the tracer size (paper confetti) and the spatial resolution settings of the statistical correlation program was carried out. The validated parameters and operational procedures were used for the flow characterization in two areas: the spillway approaching area and the tailrace channel. The larger tracer (10 mm diameter) performed better. The manual particle seeding showed to produce negative bias effects in velocity measurements, due to particle agglomeration. The low-cost measurements resulted in velocity field information of a resurgence flow in the tailrace channel measured with only 10 pairs of images. The study showed, as a proof of concept, that hydraulic model studies could easily be complemented with LS-PIV techniques providing spatial and temporal variations of velocity fields for flow analysis with advantages against intrusive point-based measurement techniques.

Progress in numerical simulation of casting process

The numerical simulation of casting process can calculate casting filling process, solidification process, and obtain change and coupling information of temperature field, velocity field, pressure field, stress field and microstructure. At present, numerical simulation of casting process has been quite mature at the macro level, and is developing towards the direction of micro level. The coupling and integration of different fields between temperature, flow, stress, and microstructure, is the shape of things for numerical simulation research of casting process. This paper reviews and summarizes the research history and current situation of numerical simulation of casting process. The progress in numerical simulation from five aspects of casting solidification, casting filling, stress field, microstructure, commercial software, is presented.

Ultrasound deep learning for monitoring of flow–vessel dynamics in murine carotid artery

Several arterial diseases are closely related with mechanical properties of the blood vessel and interactions of flow–vessel dynamics such as mean flow velocity, wall shear stress (WSS) and vascular strain. However, there is an opportunity to improve the measurement accuracy of vascular properties and hemodynamics by adopting deep learning-based ultrasound imaging for flow–vessel dynamics (DL-UFV). In this study, the DL-UFV is proposed by devising an integrated neural network for super-resolved localization and vessel wall segmentation, and it is also combined with tissue motion estimation and flow measurement techniques such as speckle image velocimetry and speckle tracking velocimetry for measuring velocity field information of blood flow. Performance of the DL-UFV is verified by comparing with other conventional techniques in tissue-mimicking phantoms. After the performance verification, in vivo feasibility is demonstrated in the murine carotid artery with different pathologies: aging and diabetes mellitus (DM). The mutual comparison of flow–vessel dynamics and histological analyses shows correlations between the immunoreactive region and abnormal flow–vessel dynamics interactions. The DL-UFV improves biases in measurements of velocity, WSS, and strain with up to 4.6-fold, 15.1-fold, and 22.2-fold in the tissue-mimicking phantom, respectively. Mean flow velocities and WSS values of the DM group decrease by 30% and 20% of those of the control group, respectively. Mean flow velocities and WSS values of the aging group (34.11 cm/s and 13.17 dyne/cm2) are slightly smaller than those of the control group (36.22 cm/s and 14.25 dyne/cm2). However, the strain values of the aging and DM groups are much smaller than those of the control group (p < 0.05). This study shows that the DL-UFV performs better than the conventional ultrasound-based flow and strain measurement techniques for measuring vascular stiffness and complicated flow–vessel dynamics. Furthermore, the DL-UFV demonstrates its excellent performance in the analysis of the hemodynamic and hemorheological effects of DM and aging on the flow and vascular characteristics. This work provides useful hemodynamic information, including mean flow velocity, WSS and strain with high-resolution for diagnosing the pathogenesis of arterial diseases. This information can be used for monitoring progression and regression of atherosclerotic diseases in clinical practice.

Extracting turbulence parameters of smoke via video analysis

Turbulence can be observed in almost all the smoke videos, so turbulence parameters can be extracted as features of smoke in the video smoke detection system. A video-based turbulence parameter measuring method is proposed in this paper. Turbulence can be regarded as a series of irregular flow states with instantaneous velocity fluctuations. First, the instantaneous turbulent velocity field is obtained from the real-time video using an optical flow method, and based on the velocity field information, the turbulence kinetic energy (TKE) and dissipation rate are calculated using large eddy simulation and sub-grid scale (SGS) models. Three different methods, Smagorinsky model, gradient model, and dimensional analysis, are used to obtain the dissipation rate. The results obtained using different methods are compared. The dissipation rate estimated using the SGS models shows high consistency and that estimated by the dimensional analysis has a similar distribution, which shows that the choice of the SGS model is not important for the dissipation rate estimation. Then the TKE is calculated, and the processed images show that each plume structure has its own life cycle and the rising velocity of each plume structure is steady. This method is efficient for the plume turbulence measurement, and it provides benefits to the experimental study of fire plumes. Furthermore, the measured parameters can be analyzed for video-based fire detection. It is a useful method in both scientific research and industrial development.

STEREO-PHOTOGRAMMETRIC MEASUREMENT OF SPATIO-TEMPORAL VELOCITY FIELDS AT LANGE GLACIER, KING GEORGE ISLAND

Abstract. A network consisting of six cameras was set up on both sides of Lange Glacier on King George Island, Antarctica, for a period of two years to monitor changes in the glacier’s motion behaviour. The cameras were observing spatio-temporal glacier surface velocity vector fields as well as the position of the glacier front. Velocity field information was obtained from image sequences by applying subpixel accuracy photogrammetric image sequence analysis techniques. Georeferencing in a superordinate coordinate system was performed via integrated photogrammetric-geodetic network adjustment. As a result, velocity fields were determined with maximum glacier surface velocities in the order of 1.5 meter per day. The results of terrestrial camera image sequence processing can be used as validation and calibration reference for satellite image based glacier velocity dynamics calculations. Moreover, the very high temporal resolution of the image sequences taken at 20 minute time intervals can also be used to analyse highly dynamic processes.

Estimation of velocity potential of water waves using a Luenberger-like observer

We propose a Luenberger-like observer for a water wave system. The water wave dynamics are assumed to be governed by the linearized water wave equation (LWWE). Our proposed observer estimates the velocity potential of water waves by measuring only the surface wave elevation. The information of the water-wave velocity field is then extracted from the gradient of the velocity potential. It is shown that the estimation error of the observer converges exponentially to zero as time tends to infinity. Furthermore, we numerically solve the LWWE and observer equation by the finite difference method. The efficiency of our proposed numerical scheme and the performance of the observer are validated by numerical simulation results.

Equivalent boundary model of lunar soil drilling simulation by DEM

Aiming to solve the computational cost problem in the discrete element simulation for lunar soil drilling sampling, an equivalent boundary method was proposed. A high-accuracy DEM model of lunar soil was established firstly. As the novel alterable constitutive law, the accuracy of the model was verified to meet the performance of real lunar soil very much both in shear strength indices and elastic–plastic behavior. A common drill bit in the geological exploration field for sampling soil was chosen as the simulation object. In preanalysis, it was known that with the increase of drilling depth, the stress concentration area was always near the drill bit, while the affected area of the lunar soil was a cylindrical area around the drill pipe, which extended towards the drilling direction instead of extending around it. Then a big boundary drilling simulation scene was established to investigate the flow direction of lunar soil particles. The motion law of particles and the velocity field information were obtained, and a U-shape chain was described around the drill bit. Finally an equivalent boundary was set near the U-shaped chain, and the size was determined by comparing the soil stress in the fierce collision zone and around the reference boundary. This method could be a reference for other lunar soil drilling researches with other drills of different sizes.

On the amount of peculiar velocity field information in supernovae from LSST and beyond

Peculiar velocities introduce correlations between supernova magnitudes, which implies that the supernova Hubble diagram residual carries information on both the matter power spectrum at the present time and its growth rate. By a combination of brute-force exact computations of likelihoods and Fisher matrix analysis, we investigate how this information, which comes from supernova data only, depends on different survey parameters such as covered area, depth, and duration. We show that, for a survey like The Rubin Observatory Legacy Survey of Space and Time (LSST) and a fixed redshift depth, the same observing time provides the same cosmological information whether one observes a larger area, or a smaller area during more years. We also show that although the peculiar velocity information is peaked in the range $z \in [0, 0.2]$, there is yet plenty of information in $z \in [0.2, 0.5]$, and for very high supernova number densities there is even more information in the latter range. We conclude that, after 5 years, LSST could measure $\sigma_8$ with an uncertainty of 0.17 with the current strategy, and that this could be improved to 0.09 if the supernova completeness is improved to 20%. Moreover, we forecast results considering the extra parameter $\gamma$, and show that this creates a non-linear degeneracy with $\sigma_8$ that makes the Fisher matrix analysis inadequate. Finally, we discuss the possibility of achieving competitive results with the current Zwicky Transient Facility.

Heat transfer and flow characteristics of forced convection in PDMS microchannel heat sink

Recently, microfluidic devices are being widely used in various heat transfer applications and, thermal management in microchannels is a challenging issue. As a solution, different types of microchannel heat sinks have been employed to enhance the heat transfer. The flow characteristics in the microchannel heat sink have influence on the heat transfer rate and thermal management performance. Therefore, the simultaneous measurement of temperature and velocity fields is highly required to understand the single-phase heat transfer phenomena in the PDMS microchannel heat sink. In this study, μPIV-μLIF technique which can provide the velocity and temperature field information of micro-scale thermofluid flow was newly developed to analyze the heat transfer of forced convection in PDMS microchannel heat sink. Especially, flow characteristics in the microchannel heat sink were systematically investigated. At a high Re flow (Re = 10) with heating, a high-speed crossflow occurs in the microchannel heat sink. Spanwise vorticity and Reynolds shear stress, which contribute to heat transfer in the microchannel, exhibit higher values at Re = 10 with heating compared to the non-heating case. Variations in velocity and local Nu number were also compared to explain heat transfer enhancement in the microchannel heat sink. Temporal variations in the temperature field were evaluated to demonstrate the effect of flow on heat transfer. The results presented herein would be helpful for understanding heat transfer in microscale thermofluid flows and for designing microscale heat transfer devices.

Assessment of Measurement Accuracy of a Micro-PIV Technique for Quantitative Visualization of Al2O3 and MWCNT Nanofluid Flows

Nanofluids, which are liquids containing nanoparticles, are used to modify heat transfer performance in various systems. To explain the mechanism of heat transfer modification with nanofluids, many theories have been suggested based on numerical simulations without experimental validation because there is no suitable experimental method for measuring the velocity fields of nanofluid flows. In this study, the measurement accuracy of micro-particle image velocimetry (μ-PIV) is systemically quantified with Al2O3 and multi-walled carbon nanotube (MWCNT) nanofluids. Image quality, cross-correlation signal-to-noise ratio, displacement difference, and spurious vector ratio are investigated with static images obtained at various focal plane positions along the beam pathway. Applicable depth is enough to investigate micro-scale flows when the concentrations of Al2O3 and MWCNT nanofluids are lower than 0.01% and 0.005%, respectively. The velocity fields of Hagen–Poiseuille flow are measured and compared with theoretical velocity profiles. The measured velocity profiles present good agreement with the theoretical profiles throughout. This study provides the criteria for μ-PIV application and demonstrates that μ-PIV is a promising technique for measuring the velocity field information of nanofluids.

T cell migration in microchannels densely packed with T cells

T cells migrate diverse microenvironments of the body to mount antigen-specific immune responses. T cell activation, a key initial process for antigen-specific immune responses, occur in secondary lymphoid organs such as spleens and lymph nodes where high density of T cells migrates rapidly through the reticular networks formed by stromal cells. In vitro model system recapitulating key characteristics of secondary lymphoid organs, confined spaces densely packed with rapidly migrating cells, would be useful to investigate mechanisms of T cell migration. In this study, we devised a method to fabricate microchannels densely packed with T cells. Microchannel arrays with fixed height (4 μm) and length (1.5 mm) and various widths (15~80 μm) were fabricated in between trapezoid-shaped reservoirs that facilitated T cell sedimentation near microchannel entries. Microchannel surface chemistry and filling time were optimized to achieve high packing density (0.89) of T cell filling within microchannels. Particle image velocimetry (PIV) analysis method was employed to extract velocity field of microchannels densely packed with T cells. Using velocity field information, various motility parameters were further evaluated to quantitatively assess the effects of microchannel width and media tonicity on T cell motility within cell dense microenvironments.