Image Velocity Field Research Articles

CME Velocity Field Calculation Model Based on an Unsupervised Transformer Optical Flow Network

The optical flow algorithm (OF) is one the main methods for calculating image velocity field and has many applications in space weather. Most OF calculations are applied to the motion of labeled rigid objects and are not suitable for velocity detection of high-energy particles, such as in a coronal mass ejection (CME). Fluctuations in exposure time and the influence of space weather will lead to inconsistent brightness of the same feature point at different times. To address this problem, we propose an unsupervised multiscale optical flow network based on Vision Transformer, named UTFlowNet. The network comprises a multiscale feature extraction module and a coarse-to-fine global optical flow calculation module. The movement of high-energy particles emitted during a CME eruption follows certain physical rules. Therefore, we apply fluid motion–based loss functions to analyze the motion of high-energy particles more effectively, addressing the problem of CME motion field extraction. Our method can be applied to the real-time automatic extraction of a CME’s velocity field and performs well with inconsistent brightness, large-scale motion, and strong CME noise. Additionally, we can estimate subpixel level fine-grained velocity. Our model may be affected by overfitting during cross–data set inference, so we encourage performing a small amount of transfer learning on new data sets to mitigate this issue. In order to verify the accuracy of our method, we conducted experiments and verification on the Solar and Heliospheric Observatory LASCO C2 data and the High Altitude Observatory MLSO data. We constructed a large-scale displacement simulation data set based on LASCO C2 data and tested on it, achieving the best results.

An Improved Method for Calculating Wave Velocity Fields in Fractured Rock Based on Wave Propagation Probability

Ultrasonic velocity field imaging offers a robust tool for characterizing and analyzing damage and its evolution within fractured rock masses. The combined application of ultrasonic first arrival waves and coda waves can significantly enhance the accuracy and range of velocity field imaging. This manuscript introduces an improved imaging method that integrates the propagation probability distribution of the first arrival and coda waves to calculate the velocity field. The proposed method was applied to the velocity field imaging of a medium with multiple scatterers and varying degrees of fracturing. The overall error and calculation unit error of the proposed method were analyzed, and its improvement in calculation accuracy and applicable scope was verified. Additionally, this method was employed to image the velocity field during the damage process of fractured rock masses. The imaging results were compared against digital speckle patterns to confirm the method’s suitability. Finally, we discussed the impact of measurement errors and sensor missing on the accuracy of the computational outcomes presented in this method. These two situations will affect the calculation results, and the influence of reducing the number of sensors is smaller than that of measuring time shifts with error.

Mechanism analysis and optimal design of sound-absorbing metastructure constructed by slit-embedded Helmholtz resonators

<sec>Low-frequency noise has always been a thorny problem in the field of noise control. In recent years, the development of sound-absorbing metastructures has provided new ideas for controlling low-frequency noise. In this work, we propose a low-frequency sound-absorbing metastructure constructed by Helmholtz resonators with embedded slit. Analytical and numerical models are established to analyze the sound absorption performance and mechanism of the proposed sound-absorbing metastructure, and optimization design is conducted to achieve low-frequency wideband absorption performance. The analytical modeling method and the performance of the proposed sound-absorbing metastructure are also experimentally verified. The main conclusions are summarized as follows.</sec><sec>1) By using transfer matrix method and finite element method, analytical and numerical models for calculating sound absorption coefficient are established. It is shown that analytical predictions are in good agreement with numerical calculations. It is demonstrated that a typical design of a 30-mm-thick single-cell metastructure can achieve a sound absorption coefficient of 0.88 at 404 Hz. Typical designs of two-cell parallel structure and the four-cell parallel structure (both with a thickness of 50 mm) can achieve two and four nearly perfect low-frequency sound absorption peaks in a frequency band of 200–400 Hz, respectively.</sec><sec>2) The low-frequency sound absorption mechanisms of the proposed metastructures are explained from four aspects: simplified equivalent model parameters, normalized acoustic impedance, complex-plane zero/pole distribution, and sound pressure cloud image and particle velocity field distribution. It is demonstrated that the main sound absorption mechanism is related to the thermal viscous loss of sound waves, caused by the inner wall of embedded slit.</sec><sec>3) The design for broadband low-frequency absorption performance is optimized by using differential evolution optimization algorithm. An optimized parallel-multi-cell coupled metastructure with multiple perfect sound absorption peaks below 500 Hz is realized. For a thickness of 90 mm, the sound absorption coefficient curve of an optimized metastructure exhibits 8 almost perfect sound absorption peaks and an average sound absorption coefficient of 0.86 in a frequency range of 170－380 Hz.</sec><sec>4) Experimental samples are fabricated to test sound absorption. Experimental results are basically consistent with the analytical predictions. The results from analytical model, numerical calculations and experimental measurements are mutually verified.</sec><sec>In summary, the sound-absorbing metastructures with a thickness of sub-wavelength, proposed in this work, exhibit outstanding sound absorption performance at low frequencies. We demonstrate that they are suitable for low frequency broadband sound absorption below 500 Hz. Owing to their thin thickness and relatively simple construction, they have broad application prospects in practical noise control engineering.</sec>

Improved deep learning method for accurate flow field reconstruction from sparse data

The analysis of flow field is essential for the fluid dynamics and the internal mechanism of hydraulic machinery. The use of deep learning technology has revolutionized the field of fluid dynamics by not only reducing computational power and time, but also improving the quality of experimental measurements and numerical simulations. However, certain numerical computing errors can lead to inaccurate simulation results with inadequate data. Fortunately, deep learning technology can accurately reconstruct distorted results, making flow mechanism research more convenient. In this study, a novel super-resolution convolutional neural network with a u-shaped architecture (SRUnet) model was developed by combining the benefits of super-resolution convolutional neural network (SRCNN) and convolutional neural network with the u-shaped architecture (U-net) to address the challenge of reconstructing turbulence flow field images with low resolution. The SRUnet model was validated with small datasets and was shown to deliver high-precision results when applied to reconstruct the velocity flow field of the two-dimensional (2D) cylinder wake flow. Furthermore, the SRUnet model's training and testing performance surpasses that of SRCNN and U-net models, producing more under-resolved details. When compared to the quality of the velocity flow field reconstruction of SRCNN and U-net models with the same hyper-parameter values, the SRUnet model produced 5.35% and 14.22% higher average values of the peak signal-to-noise ratio (PSNR) when low-resolution velocity field images were used as model inputs for the testing dataset reconstruction. Additionally, the average values of the structural similarity index metric (SSIM) were 1.09% and 3.33% higher than those of SRCNN and U-net models. When super-low resolution flow field images were used as model inputs for the testing dataset reconstruction, the average values of the PSNR metric were 8.31% and 2.76% higher than those of SRCNN and U-net models, respectively. The average values of the SSIM metric were also 5.81% and 2.25% higher than those of SRCNN and U-net models, respectively.

Machine Learning for Aiding Blood Flow Velocity Estimation Based on Angiography.

Computational fluid dynamics (CFD) is widely employed to predict hemodynamic characteristics in arterial models, while not friendly to clinical applications due to the complexity of numerical simulations. Alternatively, this work proposed a framework to estimate hemodynamics in vessels based on angiography images using machine learning (ML) algorithms. First, the iodine contrast perfusion in blood was mimicked by a flow of dye diffusing into water in the experimentally validated CFD modeling. The generated projective images from simulations imitated the counterpart of light passing through the flow field as an analogy of X-ray imaging. Thus, the CFD simulation provides both the ground truth velocity field and projective images of dye flow patterns. The rough velocity field was estimated using the optical flow method (OFM) based on 53 projective images. ML training with least absolute shrinkage, selection operator and convolutional neural network was conducted with CFD velocity data as the ground truth and OFM velocity estimation as the input. The performance of each model was evaluated based on mean absolute error and mean squared error, where all models achieved or surpassed the criteria of 3 × 10-3 and 5 × 10-7 m/s, respectively, with a standard deviation less than 1 × 10-6 m/s. Finally, the interpretable regression and ML models were validated with over 613 image sets. The validation results showed that the employed ML model significantly reduced the error rate from 53.5% to 2.5% on average for the v-velocity estimation in comparison with CFD. The ML framework provided an alternative pathway to support clinical diagnosis by predicting hemodynamic information with high efficiency and accuracy.

Experimental Study of Collateral Patency following Overlapped Multilayer Flow Modulators Deployment

Decades after its introduction, endovascular aneurysm repair remains a challenging procedure with risks of collateral patency failure. Here, we investigate the ability of a porous stent, the Multilayer Flow Modulator (MFM), to maintain renal perfusion after a single or overlapping case. Silicone models representing an ideal infrarenal AAA geometry were used to analyze and compare three cases (control, single MFM and two overlapped MFMs). Micro-computed tomography was used to image the deployed MFM devices geometry and evaluate pore size and density along with porosity in both two (planimetric) and three dimensions (gravimetric). Laser particle image velocimetry (PIV) experiments were performed to image velocity and vorticity fields at the aorta-renal bifurcation. Flow experiments revealed renal arteries perfusion preservation in both single and overlapped cases. Microstructure analysis revealed an uneven distribution of wires in the MFM devices leading to local change in planimetric porosity and pore size. Overlap of a second MFM device led to a significant decrease in those 2D metrics but did not affect the gravimetric porosity and the branch perfusion. This first microstructure evaluation of MFM device combined with flow experiments revealed the ability of the device to preserve collateral flow thanks to a highly porous microstructure.

PIV-system for flow measurements on the benchmark of promising fast neutron nuclear reactor

Carrying out spatio-temporal flow fields parameters is one of the most important and complicated problem within the modeling of heat and hydrophysical processes in operating regimes of the power plants (including nuclear (NPP)). Particle Image Velocimetry (PIV) method (based on the flow visualization, using laser illumination) fits best to satisfy the demands of such measurements. For the experiments on large-scale models of NPP, there is a number of problems in the application of this method, for example, large scales of the flows of the investigated model objects; a noticeable variability of the flow parameters processes with strong temperature fluctuations, leading to optical distortions; necessity of combining imaging and contact gauges probing etc. In this paper we describe PIV- system specifically designed for the study of heat and hydrophysical processes in large-scale model setup of promising fast neutron reactor. The system allows the PIV-measurements for the conditions of complicated configuration of the reactor model, reflections and distortions section of the laser sheet, blackout, in a closed volume. The illumination system using of two lasers and two video cameras with synchronization, allows to obtain an image of the flow in the whole volume of investigation. The use of filtering techniques and method of masks images enabled us to reduce the number of incorrect measurement of flow velocity vectors by an order. The method of conversion of image coordinates and velocity field in the reference model of the reactor using a virtual 3D simulation targets, without loss of accuracy in comparison with a method of using physical objects in filming area was released. The results of measurements of velocity fields in various modes, both stationary (operational), as well as in non-stationary (emergency). These results are compared with measurements of temperature distribution, which were carried out simultaneously. The obtained data set can be used for verifying CFD codes.

Particle Image Velocimetry in a High-Pressure Turbine Stage at Aerodynamically Engine Representative Conditions

Abstract Particle image velocimetry (PIV) is a well-established technique for determining the flow direction and velocity magnitude of complex flows. This paper presents a methodology for executing this nonintrusive measurement technique to study a scaled-up turbine vane geometry within an annular cascade at engine-relevant conditions. Custom optical tools such as laser delivery probes and imaging inserts were manufactured to mitigate the difficult optical access of the test section and perform planar PIV. With the use of a burst-mode Nd: YAG laser and Photron FASTCAM camera, the frame straddling technique is implemented to enable short time intervals for the collection of image pairs and velocity fields at 10 kHz. Furthermore, custom image processing tools were developed to optimize the contrast and intensity balance of each image pair to maximize particle number and uniformity while removing scattering and background noise. The preprocessing strategies significantly improve the vector yield under challenging alignment, seeding, and illumination conditions. With the optical and software tools developed, planar PIV was conducted in the passage of a high-pressure stator row, at midspan, in an annular cascade. Different Mach and Reynolds number operating conditions were achieved by modifying the temperature and mass flow. With careful spatial calibration, the resultant velocity vector fields are compared with Reynolds-averaged-Navier–Stokes (RANS) simulations of the vane passage with the same geometry and flow conditions. Uncertainty analysis of the experimental results is also presented and discussed, along with prospects for further improvements.

An accurate optical flow estimation of PIV using fluid velocity decomposition

In this study, we propose a novel optical flow formulation for estimating high-accuracy velocity fields from tracer particle image sequences. According to the Helmholtz velocity decomposition theorem, the proposed optical flow method decomposes the two-dimensional velocity field into four components: translation motion, linear distortion motion, shear distortion motion and rotation motion. In this context, regularization terms for different motion components are designed, which have a reasonable physical interpretation for the flow characteristics of the fluid. Subsequently, we design specific regularization parameters for the corresponding regularization terms according to the flow characteristics of the motion components. These regularization parameters can be adaptively adjusted with changes in the image space and velocity field. In addition, the data term of the optical flow formulation is based on the projected-motion equation derived from the continuity equation, which maintains the compressibility of the fluid in the two-dimensional plane. Velocity fields are estimated from synthetic tracer particle images and hypersonic experimental image sequences, and the velocity results are compared to those of an advanced cross-correlation-based PIV method and previous advanced optical flow methods. The results and comparisons indicate that the proposed method shows good performance and high measurement accuracy when acquiring compressible flow structures from fluid measurements.

Puzzling Bubble Rise Speed Increase in Dense Granular Suspensions.

We present an anomalous experimental observation on the rising speed of air bubbles in a Hele-Shaw cell containing a suspension of spherical, neutrally buoyant, non-Brownian particles. Strikingly, bubbles rise faster in suspensions as compared to particle-less liquids of the same effective viscosity. By carefully measuring this bubble speed increase at various particle volume fraction and via velocity field imaging, we demonstrate that this strange bubble dynamics is linked to a reduction in the bulk dissipation rate. A good match between our experimental data and computations based on a Suspension Balance Model (SBM) illustrates that the underlying mechanism for this dissipation-rate deficit is related to a nonuniform particle distribution in the direction perpendicular to the channel walls due to shear-induced particle migration.

Improvements in the accuracy of wavelet-based optical flow velocimetry (wOFV) using an efficient and physically based implementation of velocity regularization

This manuscript details recent improvements in a wavelet-based optical flow velocimetry (wOFV) method that represents a more physically sound implementation and results in increased accuracy of the velocity estimation. A novel regularization scheme is presented that is based on penalization of directional derivatives of the estimated velocity field or more specifically, second-order penalization of the gradients of divergence and curl, which enforces realistic flow structure. The regularization is performed in the wavelet domain with symmetric boundary conditions for the first time using an alternative wavelet transform approach of matrix multiplications. The method for the computation of full two-dimensional wavelet transforms by a single pair of matrix multiplications is described and shown to be significantly more efficient than a lifting implementation or convolution in MATLAB. Velocity fields are estimated from synthetic tracer particle images generated from 2D DNS of isotropic turbulence and from experimental results from a turbulent flow. Results are compared to an advanced correlation-based PIV algorithm and previous advanced optical flow methods. The velocity results estimated with the new regularization scheme are shown to be more accurate and exhibit a significant reduction in non-physical small-scale artifacts compared to previous results. A significant result from the current method is the ability to generate 2D velocity field images that resolve the dissipative scales in high-Reynolds number, turbulent flows.

Imaging Velocity Fields Analysis of Space Camera for Dynamic Circular Scanning

Compared with traditional push-broom imaging, the space camera that performs the new circular scanning imaging can effectively enlarge the imaging area and obtain high-resolution images. However, the imaging velocity fields of space camera will seriously deteriorate the image quality in the circular scanning imaging process. And the velocity fields are anisotropically distributed due to various factors, including attitude maneuvering, satellite precession, earth curvature, and earth rotation. Therefore, this paper proposes a mathematical model of the velocity field to analyze the effect of circular scanning imaging. Based on the principle of ray tracing, the expression of the instantaneous velocity field on the ground is first derived, and then the corresponding image velocity field is obtained by mapping the velocity vector to the focal plane. In addition, numerical simulations and image simulations are performed to analyze the anisotropy distribution of the velocity vectors. Moreover, the dynamic characteristics of the space camera are analyzed to evaluate the performance of this new imaging. The simulation results show that the higher velocity leads to worse imaging quality. The study of this paper provides guidance for attitude planning and imaging assessment for new remote sensing imaging of space cameras.

Microfluidic-Based Biosensor for Sequential Measurement of Blood Pressure and RBC Aggregation Over Continuously Varying Blood Flows.

Aggregation of red blood cells (RBCs) varies substantially depending on changes of several factors such as hematocrit, membrane deformability, and plasma proteins. Among these factors, hematocrit has a strong influence on the aggregation of RBCs. Thus, while measuring RBCs aggregation, it is necessary to monitor hematocrit or, additionally, the effect of hematocrit (i.e., blood viscosity or pressure). In this study, the sequential measurement method of pressure and RBC aggregation is proposed by quantifying blood flow (i.e., velocity and image intensity) through a microfluidic device, in which an air-compressed syringe (ACS) is used to control the sample injection. The microfluidic device used is composed of two channels (pressure channel (PC), and blood channel (BC)), an inlet, and an outlet. A single ACS (i.e., air suction = 0.4 mL, blood suction = 0.4 mL, and air compression = 0.3 mL) is employed to supply blood into the microfluidic channel. At an initial time (t < 10 s), the pressure index (PI) is evaluated by analyzing the intensity of microscopy images of blood samples collected inside PC. During blood delivery with ACS, shear rates of blood flows vary continuously over time. After a certain amount of time has elapsed (t > 30 s), two RBC aggregation indices (i.e., SEAI: without information on shear rate, and erythrocyte aggregation index (EAI): with information on shear rate) are quantified by analyzing the image intensity and velocity field of blood flow in BC. According to experimental results, PI depends significantly on the characteristics of the blood samples (i.e., hematocrit or base solutions) and can be used effectively as an alternative to blood viscosity. In addition, SEAI and EAI also depend significantly on the degree of RBC aggregation. In conclusion, on the basis of three indices (two RBC aggregation indices and pressure index), the proposed method is capable of measuring RBCs aggregation consistently using a microfluidic device.

Application of GPR and seismic methods for noninvasive examination of glacial and postglacial sediments in the Psia Trawka glade: the Tatra Mts., Poland

Presented study gives an insight into general proportions of the actual geomorphology, subglacial morphology and thickness of the drift (quaternary sediments) particularly well-pronounced glacial morphology in the Tatras and, on the other hand, the general scarcity of the data in this field. Objectives of the geophysical survey in this study were imaging of the morphology of bedrock surface under the drift (glacial and postglacial) sediments and determination of thickness of the drift and its composition. Two methods were applied: Ground Penetrating Radar (GPR) and seismic refraction profiling. GPR was used to examine drift sediments due to its high resolution and low depth of penetration. Seismic method with lower resolution but higher penetration depth gave an image of boundary between bedrock and drift. In addition, the results of seismic tomography allowed the velocity field imaging which shows changes inside the postglacial deposits. The results of the two methods used in this research suggest that points of depression exist in the subglacial morphology with a depth of about c.a. 40 below the present-day terrain surface and c.a. 25 m below surrounding subglacial surface. This trough has also been estimated to be about 150 m wide. Its considerable depth and steep slopes show that its origin can be related to erosion of subglacial water during the decay of the last (Würm) glaciation of the Sucha Woda and Panszczyca valleys.

CO Multi-line Imaging of Nearby Galaxies (COMING). VII. Fourier decomposition of molecular gas velocity fields and bar pattern speed

Abstract The 12CO (J = 1→0) velocity fields of a sample of 20 nearby spiral galaxies, selected from the CO Multi-line Imaging of Nearby Galaxies (COMING) legacy project of Nobeyama Radio Observatory, have been analyzed by Fourier decomposition to determine their basic kinematic properties, such as circular and noncircular velocities. On average, the investigated barred (SAB and SB) galaxies exhibit a ratio of noncircular to circular velocities of molecular gas larger by a factor of 1.5–2 than non-barred (SA) spiral galaxies at radii within the bar semimajor axis ab at 1 kpc resolution, with a maximum at a radius of R/ab ≈ 0.3. Residual velocity field images, created by subtracting model velocity fields from the data, reveal that this trend is caused by kpc-scale streaming motions of molecular gas in the bar region. Applying a new method based on radial velocity reversal, we estimated the corotation radius RCR and bar pattern speed Ωb in seven SAB and SB systems. The ratio of the corotation to bar radius is found to be in a range of $\mathcal {R}\equiv R_\mathrm{CR}/a_\mathrm{b} \approx 0.8$–1.6, suggesting that intermediate (SBb–SBc), luminous barred spiral galaxies host fast and slow rotator bars. Tentative negative correlations are found for Ωb vs. ab and Ωb vs. total stellar mass M*, indicating that bars in massive disks are larger and rotate slower, possibly a consequence of angular momentum transfer. The kinematic properties of SAB and SB galaxies, derived from Fourier decomposition, are compared with recent numerical simulations that incorporate various rotation curve models and galaxy interactions.

Wall shear stress estimation in the aorta: Impact of wall motion, spatiotemporal resolution, and phase noise.

Wall shear stress (WSS) presents an important parameter for assessing blood flow characteristics and evaluating flow-mediated lesions in the aorta. To investigate the robustness of WSS and oscillatory shear index (OSI) estimation based on 4D flow MRI against vessel wall motion, spatiotemporal resolution, and velocity encoding (VENC). Simulated and prospective. Synthetic 4D flow MRI data of the aorta, simulated using the Lattice-Boltzmann method; in vivo 4D flow MRI data of the aorta from healthy volunteers (n = 11) and patients with congenital heart defects (n = 17). 1.5T; 4D flow MRI with PEAK-GRAPPA acceleration and prospective electrocardiogram triggering. Predicated upon 3D cubic B-splines interpolation of the image velocity field, WSS was estimated in mid-systole, early-diastole, and late-diastole and OSI was derived. We assessed the impact of spatiotemporal resolution and phase noise, and compared results based on tracked-using deformable registration-and static vessel wall location. Bland-Altman analysis to assess WSS/OSI differences; Hausdorff distance (HD) to assess wall motion; and Pearson's correlation coefficient (PCC) to assess correlation of HD with WSS. Synthetic data results show systematic over-/underestimation of WSS when different spatial resolution (mean ± 1.96 SD up to -0.24 ± 0.40 N/m2 and 0.5 ± 1.38 N/m2 for 8-fold and 27-fold voxel size, respectively) and VENC-depending phase noise (mean ± 1.96 SD up to 0.31 ± 0.12 N/m2 and 0.94 ± 0.28 N/m2 for 2-fold and 4-fold VENC increase, respectively) are given. Neglecting wall motion when defining the vessel wall perturbs WSS estimates to a considerable extent (1.96 SD up to 1.21 N/m2 ) without systematic over-/underestimation (Bland-Altman mean range -0.06 to 0.05). In addition to sufficient spatial resolution and velocity to noise ratio, accurate tracking of the vessel wall is essential for reliable image-based WSS estimation and should not be neglected if wall motion is present. 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Velocity mapping of steady water flow through methane hydrate bearing samples

The productivity of methane from natural gas hydrate reservoirs is predominantly controlled by the fluid migration mechanisms in hydrate-bearing sediments. Thus, the characterization of the effects of hydrate distribution on fluid migration is significant in the exploitation of natural gas hydrates. In this work, a phase contrast method was used to visualize water flow velocity fields at three cross-sections under different injecting flow rates by using magnetic resonance imaging (MRI). Four experimental cases were performed to directly measure the cross-sectional velocity fields in a sand packed hydrate-bearing sample with hydrate saturations varying from 22.5% to 32.7%. The effect of hydrate distribution on the water velocity fields was discussed. It was found that hydrate formed nonuniformly in the sand packed sample in all four cases, and the hydrate distribution predominantly affected the water effective permeability and cross-sectional velocity fields when steady water flow was injected. When hydrate saturation was higher than 22.5%, a two-region flow pattern was observed with a clear boundary between the fast-flowing region and the slow-flowing region. The cross-sectional flow rates calculated according to the velocity field images fitted well with the injecting flow rates.

Experimental investigation on the flow transition in different pin-fin arranged microchannels

The flow characteristics of water through the in-line and staggered pin-fin microchannels with length of 25 mm, width of 2.4 mm and height of 0.11 mm were studied experimentally. The flow transition was identified as a sudden increasing slope in both pressure drop versus mass flow rate curve and friction factor versus Reynolds number curve for in-line pin-fin microchannels, but it did not occur for staggered pin-fin microchannels. The effect of pin-fin arrangements on the flow transition was not reported in the previous literature. With the aid of microparticle image velocimetry (Micro-PIV) technology, the streamlines, velocity fields and velocity fluctuation fields of flow through the pin-fin microchannels were captured to explain the flow transition, and the effect of pin-fin arrangements on the flow transition was analyzed for the first time. It was found that at the critical Reynolds number where the flow transition occurred for the in-line pin-fin microchannels, the steady double-vortex wake flow changed to the unsteady vortex-shedding wake flow. The occurrence of vortex shedding caused an obvious change in main stream from straight flow to wavy flow and further induced significant increases of transversal velocity and velocity fluctuations, which induced strong flow disturbance in transversal directions and large additional pressure drop, and finally caused the flow transition in the in-line pin-fin microchannels. For the staggered pin-fin microchannels, the main stream through the pin-fin arrays was found to be already the wavy flow before the vortex shedding. Thus, the transversal velocity and velocity fluctuations induced by the vortex shedding were relatively small, and therefore, the flow transition with an abrupt pressure drop increase was not observed in the staggered pin-fin microchannels.

The particular use of PIV methods for the modelling of heat and hydrophysical processes in the nuclear power plants

In this paper we describe PIV-system specially designed for the study of the hydrophysical processes in large-scale benchmark setup of promising fast reactor. The system allows the PIV-measurements for the conditions of complicated configuration of the reactor benchmark, reflections and distortions section of the laser sheet, blackout, in the closed volume. The use of filtering techniques and method of masks images enabled us to reduce the number of incorrect measurement of flow velocity vectors by an order. The method of conversion of image coordinates and velocity field in the reference model of the reactor using a virtual 3D simulation targets, without loss of accuracy in comparison with a method of using physical objects in filming area was released. The results of measurements of velocity fields in various modes, both stationary (workers), as well as in non-stationary (emergency).

A particle-image velocimetry system for measurement of velocity flow fields for investigations of thermohydraulic processes on the large-scale benchmark of a promising fast-neutron reactor

The use of visualization techniques in the research on thermohydraulic processes using large-scale models of nuclear power plants is discussed. In particular, the original particle-image velocimetry (PIV) measurement system at the TISEI test bench was presented, which is a model of a proposed fast-neutron reactor. Illumination and video-filming systems with the simultaneous use of several lasers and camcorders, as well as image-processing algorithms that make it possible to carry out field measurements with high precision in a complex configuration of the reactor model, reflections and distortions of the laser knife section, and shadowing by obstacles are described. The developed methodology of conversion of the image coordinates and velocity field into the reference system of the reactor model using a virtual 3D simulation made it possible to significantly simplify the experiments.