Particle Image Velocimetry Measurements Research Articles

Laminar separation bubble formation and bursting on a finite wing

Laminar separation bubble formation and bursting on a finite wing

Effect of Tip Gap Size on the Tip Flow Structure and Turbulence Generation in a Low Reynolds Number Compressor Cascade

Abstract Efficient and compact axial compressors are currently undergoing rapid development for use in microcooling systems and small-scale vehicles. Limited experimental work concentrates on the inner flow field of the compressors working at such low Reynolds numbers (Re∼104). This study examines the vortical structures and the resulting turbulence production in the transitional flow over a C4 compressor blade at a Reynolds number Re of 24,000, with a specific focus on the impact of tip clearance. The particle image velocimetry measurements reveal the tip flow structures in detail, including the tip leakage vortex (TLV) and its induced complex vortical structures. The tip secondary flow at the low Reynolds number can be divided as the tip leakage flow (TLF)/vortex and transitional boundary layer both at the end walls and the blade surfaces. The TLV propagates at the highest spanwise positions and farthest pitchwise positions at the middle tip gap size (τ/C = 3%) for the three tip gap sizes investigated. The tip flow fluctuations decrease from τ/C = 5% to τ/C = 3% and then increase from τ/C = 3% to τ/C = 1%. The spatial distribution, streamwise evolution, and individual Reynolds normal stress components contributing to the turbulent kinetic energy (TKE) are discussed. The primary contributors to the turbulence generation are examined to elucidate the flow mechanism leading to the distinct anisotropic turbulence structure in the tip region with various tip gap sizes.

Analysis of the shear-driven flow in a scale model of a phase separator: Validation of a coupled CFD approach using experimental data from a physical model

The effects of shear stress at the interface between a flowing gaseous phase and a liquid-filled cavity, a scenario commonly found in flue gas/slag phase separators are investigated in this study. This effect is frequently disregarded in computational fluid dynamics (CFD) simulations within metallurgy, primarily due to its limited influence on the motion of liquids (e.g., slag, liquid metal) when compared to other factors such as stirring by natural convection or bubbling. This study was undertaken to investigate shear-driven flow in a 1:4 scale model of a phase separator in which a flue gas stream coming from a furnace is mobilizing the flow of a slag melt. To cover a wide range of operating conditions, silicone oil with varying viscosities (20, 50, and 70 cSt) was considered for mimicking viscous slag. Additionally, different volumetric airflow rates (18, 27, and 36 m3/h) were considered to simulate the flue gas flow. Particle image velocimetry (PIV) measurements were conducted on the model. The experimental results were utilized to validate computationally efficient, coupled steady-state simulations of the system. Notably, the steady-state simulations, requiring approximately one hour of CPU time, demonstrated a computation time decrease of two magnitudes compared to conventional Volume of Fluid (VOF) modeling. A stable, laminar flow pattern of the liquid phase with surface velocities of up to approximately 30 mm/s was observed for the case with the lowest oil viscosity and the highest airflow rate, while a steady, turbulent flow was observed in the gas phase. Conversely, the lowest surface velocities, measuring around 5 mm/s, were recorded and calculated for the scenario with the highest oil viscosity and the lowest airflow rate. It was noted that velocities increased proportionally with the airflow rate but exhibited a disproportionate relationship with oil viscosity. The prediction of velocity magnitudes by the steady-state CFD model was highly accurate, with only minor discrepancies observed between the measured and calculated flow patterns. In summary, valuable insights into the often-overlooked shear stress effects at the phase boundary in gaseous-liquid flow over a cavity are provided by our study.

High-resolution PIV measurement over wind-generated waves

The interaction between wind and waves plays a significant role in the exchange of heat, aerosols and gases, thereby influencing our understanding of climate dynamics and air–sea interaction. Particle image velocimetry (PIV) has emerged as a valuable tool for investigating the intricate effects of small-scale waves on airflow characteristics in laboratory settings. However, previous PIV experiments have exhibited notable variability in spatial resolution, potentially affecting the accuracy of turbulence statistics, particularly in relation to small-scale waves such as capillary ripples. To systematically explore the impact of PIV spatial resolution on airflow characteristics over multi-scale wind-generated waves, we conducted high-resolution planar PIV experiments near the wave surface. We adjusted the spatial resolution of the results by modifying the spatial filter. Additionally, recognising the limitations of the high-resolution PIV system in terms of wall-normal and streamwise extent, we conducted larger field-of-view experiments to capture consecutive waveforms and achieve spatial averaging across the boundary layer. Consistent with existing literature, our findings illustrate the formation of a horizontal shear layer leading to airflow separation on the lee side of the wave, accompanied by a pronounced vorticity field and circulation region. Notably, analysis of the high-magnification dataset reveals localised airflow separation caused by small-scale capillary waves, phenomena not resolved by the large field-of-view set-up, underscoring the importance of adequate spatial resolution. Further analysis indicates that a spatial resolution larger than the size of the capillary waves leads to significant attenuation of the spanwise vorticity imposed by the small-scale waves. In this study, we also introduce a novel method relying to identify wave surfaces solely on PIV images, demonstrating its effectiveness in detecting capillary-scale waves.

Large-scale flow field super-resolution via local-global fusion convolutional neural networks

Particle image velocimetry (PIV) techniques have a limited field of view of the flow field and can only capture high-resolution flow fields in localized areas. To obtain a larger measurement range, multiple cameras must be used to capture the flow field simultaneously and then stitch the parts together. However, this method can be expensive. We propose the local-global fusion convolutional neural network (LGF-CNN) for reconstructing large-field flow fields with high spatial resolution based only on two flow data types: local small-field high spatial resolution wake velocity fields and global large-field low spatial resolution velocity fields. The core of the model consists of convolutional neural network (CNN) architecture to learn the mapping relationship between the small field of view with high spatial resolution and the large field of view with low spatial resolution. Using the effectively trained LGF-CNN model, we demonstrate its ability to reconstruct high-resolution velocity fields around the circular cylinder. The LGF-CNN is rigorously validated on a number of representative datasets, including simulated data for Reynolds numbers of 200 and 500, as well as experimental data for a Reynolds number of 3.3 × 104 with the steady jet at the rear stagnation point of the cylinder. The results demonstrate the ability of LGF-CNN to generate accurate velocity fields with high spatial resolution, including reliable detection of high-frequency components. The proposed method could reduce the number of cameras required for large-field, high spatial resolution PIV measurements, thereby reducing experimental costs.

Vortex shedding behind porous flat plates normal to the flow

This work examines the influence of body porosity on the wake past nominally two-dimensional rectangular plates of fixed width $D$ in the moderate range of Reynolds numbers $Re = UD/\nu$ (with $U$ the incoming velocity and $\nu$ the kinematic viscosity) between 15 000 and 70 000. With porosity $\beta$ defined as the ratio of open to total area of the plate, it is well established that as porosity increases, the wake shifts from the periodic von Kármán shedding behaviour to a regime where this vortex shedding is absent. This change impacts the fluid forces acting on the plate, especially the drag, which is significantly lower for a wake without vortex shedding. We analyse experimentally the transition between these two regimes using hot-wire anemometry, particle-image velocimetry and force measurements. Coherence and phase measurements are used to determine the existence of regular, periodic vortex shedding based on the velocity fluctuations in the two main shear layers on either side of the wake. Results show that, independent of $Re$ , the wake exhibits the classical Kármán vortex shedding pattern for $\beta <0.2$ but this is absent for $\beta >0.3$ . In the intermediate range, $0.2<\beta <0.3$ , there is a transitional regime that has not previously been identified; it is characterised by intermittent shedding. The flow alternates randomly between a vortex shedding and a non-shedding pattern and the total proportion of time during which vortex shedding is observed (the intermittency) decreases with increasing porosity.

The effect of permeability on the flow structure of porous square cylinders

This study experimentally investigates the wake structure of a porous square cylinder in terms of permeability over two decades of $Da$ (i.e. $2.4 \times 10^{-5} < Da < 2.9 \times 10^{-3}$ ). The porous cylinder, featuring a simple cubic lattice structure, was fabricated using an additive manufacturing technique. This unique method, combined with a periodic and scalable lattice structure, effectively isolates permeability from porosity, making it suitable for an in-depth parametric study. The key parameter, permeability, was directly estimated by measuring the pressure drop and superficial velocity for each porous case in an open-loop pipe flow system. The downstream flow fields were obtained using standard planar particle image velocimetry measurements in an open-loop wind tunnel. Based on the experimental data, structural modifications in the near wake were examined in relation to permeability, leading to the identification of four distinct flow regimes depending on $Da$ . Additionally, the downstream flow adjustment length ( $L_i$ ) was assessed by introducing a permeability-based source term into the momentum equation, facilitating the development of an analytical model for $L_i$ . The present experimental data support this analytical model, and our results further confirmed that $L_i$ plays a crucial role as a characteristic length scale in the near wake.

Investigation of the asymmetric flow structure in a hydrocyclone

AbstractThe flow field of a hydrocyclone was investigated using both computational fluid dynamics (CFD) and particle image velocimetry (PIV). A refractive index matching method was employed to improve the precision of the PIV measurements. The CFD results are in good agreement with PIV measurements. Detailed analysis reveals significant axial asymmetry in the velocity components, with the radial velocity component exhibiting notable disparities. This observation is supported by quantitative data comparing different sections of the hydrocyclone. It is further found that the asymmetry might be mainly attributed to the secondary vortexes with the single inlet of the hydrocyclone. And the secondary vortexes, superimposed on the primary flow rather than existing on its own, spiral downwards from near the inlet towards the underflow orifice. It is hypothesized that specific boundary effects and pressure gradients play a pivotal role in the formation of secondary flows. This assumption is grounded on both theoretical considerations and empirical observations, suggesting that these factors significantly influence the flow dynamics within the hydrocyclone. The insights gained from our measurement methodology and enhanced understanding of secondary flows within hydrocyclones are not only poised to serve as valuable references for fellow researchers but also have the potential to inform the design and operational optimization of hydrocyclones for improved efficiency and performance.

Dual-Orthogonal-Plane Particle Image Velocimetry Measurement of the Turbulent Flow in the Channel Head of a Large-Scale Steam Generator Mockup

Abstract In this work, a large-scale mockup of a compact complex system integrating a steam generator (SG) and a reactor coolant pump (RCP) is considered. The three-dimensional turbulent flow in the steam generator channel head (SGCH) is measured in detail. Dual-orthogonal-plane particle image velocimetry (PIV) is employed to extract high-resolution flow information in two orthogonal planes. Two separate measurements are first made to see the three-dimensional time-mean flow dynamics and the statistical quantities in the two planes. These measurements highlight two distinct flow phenomena: jet arrays and massive turbulent separation bubbles (TSBs). These patterns are attributed to mass flow redistribution in the U-shaped tubes. Proper orthogonal decomposition (POD) identifies the first POD mode as corresponding to the TSB breathing-like motion, which significantly intensifies the side view streamwise velocity fluctuations, leading to them reaching 370% of the local mean velocity. To examine the unsteady behavior of massively separated regions, the dual-orthogonal-plane PIV system is then synchronized to simultaneously measure variations in the flow fields, and the missing data due to illumination interference are reconstructed using gappy POD. The synchronized analysis reveals a direct relationship between the low-frequency fluctuations in the side and front views. These fluctuations are in phase across both views, indicating a synchronized behavior that spans the entire field. This large-scale low-frequency breathing motion has critical implications for numerical simulations and sheds light on the unsteady behavior of the RCP system within the SGCH.

Experimental investigations on the effects of longitudinal groove fabric for drag reductions on a track cyclist

The previous study has shown that the longitudinal groove fabric can reduce drag forces on a circular cylinder by forcing a drag crisis (Zheng et al. 2021). In this study, the effects of the longitudinal groove fabric are investigated on a full-scale track cycling mannequin. The force measurement results show that the longitudinal groove fabric on the upper arms can achieve a maximum drag reduction of about 7% at a flow speed of 17 m/s, and its control effects depend on flow speeds. Large-scale particle image velocimetry measurements further show that the drag reductions on the upper arm are characterized by diminished streamwise velocity deficits. The control effects also vary on different spanwise locations of the arm, where the flow behaves distinctively. The measurements also reveal the distinct flow dynamics at different heights, i.e., wake interactions and swirling motions, showing the complexity of reducing drag forces from a track cyclist.

Spray formation and spray-wall-flow interaction in a gasoline direct-injection (GDI) engine under early-injection conditions: A flow bench study

The work presented in this study aims to understand the spray-wall-flow interaction within a gasoline direct-injection (GDI) engine flow bench under simulated early-injection conditions. The Engine Combustion Network (ECN) Spray G injector is installed in the Darmstadt optically accessible engine flow bench. Under simulated early-injection conditions, the formation of a multi-hole spray and the interaction with characteristic intake flows, such as the intake jet and central tumble flow, are extensively discussed. By reducing the complexity in the number of variables inherent in engine flow and whole-engine simulation, an engine flow bench operating under various mass flow rates is applied in this study. The numerical simulation is carried out using Large Eddy Simulation (LES) under the Eulerian-Lagrangian framework for spray simulation. Experimental data, acquired through particle image velocimetry (PIV) measurements, provides 2-D flow fields on both the central tumble and valve planes, facilitating the validation of in-cylinder flow fields. Furthermore, experimental data obtained through Mie scattering is utilized to investigate spray formation and evolution within the GDI engine, providing the liquid penetration length and liquid spray angle. Comparison between the numerical and experimental data demonstrates several agreements. Moreover, the variation of different spray plumes under different mass flow rates is observed in the case of both experimental and numerical data. Increasing the mass flow rate distorts the overall plume shape and shifts it away from the intake port. This phenomenon is examined by extracting the liquid volume fraction and vapor fields of each plume. Spray plumes encounter different convective disturbances and evaporation due to their local characteristic in-cylinder flow. Furthermore, spray-wall-flow interaction and wall film deposits are observed during the injection. Lastly, the influence of the spray-induced turbulence is analyzed under different mass flow rates.

Data Assimilation of Ideally Expanded Supersonic Jet Using RANS Simulation for High-Resolution PIV Data

Data assimilation using particle image velocimetry (PIV) and Reynolds-averaged Navier–Stokes (RANS) simulation was performed for an ideally expanded supersonic jet flying at a Mach number of 2.0. The present study aims to efficiently reconstruct all the physical quantities in the aeroacoustic fields that match well with a realistic, experimentally obtained flow field. The two-dimensional, two-component PIV measurement was applied to the jet axis plane, and the time-averaged velocity field was obtained using single-pixel ensemble correlation. Two-dimensional axisymmetric RANS simulation using the Menter shear stress transport (SST) model was also performed, and the parameters of the SST model were optimized via data assimilation using the ensemble Kalman filter. The standard deviation of the observation noise σ, which is a parameter of the ensemble Kalman filter, is estimated by the previously proposed method (Nakamura et al., Low-Grid-Resolution-RANS-Based Data Assimilation of Time-Averaged Separated Flow Obtained by LES. Int. J. Comp. Fluid. Dyn., 2022), and its effectiveness was investigated for the first time. This method effectively estimated the magnitude of σ at each generation without tuning the hyperparameters. The assimilated flow fields exhibited similar flow structures observed in PIV such as the potential core length or shear layer. Therefore, the present framework can be used to estimate time-averaged full flow fields that match well with experimentally observed flow fields, and has the potential to construct a database for the Navier-Stokes-based stability analysis that requires a full flow field.

Flow visualization experiments of argon injection in a molten salt natural circulation loop

Off-gas systems are implemented in molten salt reactor designs to control the release of gaseous fission products. Two-phase flow in molten salt must be studied to understand how the system will behave in comparison to traditional working fluids like water. Flow visualization experiments and particle image velocimetry measurements were performed for three argon bubble sizes injected into a co-current stream of molten salt in a natural circulation loop facility. Similar bubble sizes were injected in experiments with water to compare the bubble shape, trajectory, and wake flow behavior of the fluids. The bubble region of interest was used to calculate the equivalent diameter and terminal velocity. Results for water showed a wobbling bubble surface and less stable bubble trajectory due to lower surface tension and viscosity compared with molten salt. Particle image velocimetry results demonstrated the increased viscosity of salt dampens turbulent fluctuations for the smaller bubble size. For a cap bubble, turbulent fluctuations were larger and longer lasting than in results for the wake flow of an argon cap bubble in water.

Three-dimensional particle image velocimetry measurement through three-dimensional U-Net neural network

This paper proposes a light field (LF) three-dimensional (3D) particle image velocimetry (PIV) method based on a digital refocused algorithm and 3D U-Net neural network for 3D three-component (3D-3C) velocity measurement. A digital refocused algorithm is used to generate a stack of LF-refocused images of tracer particles for establishing the 3D U-Net. The 3D U-Net is then used for the 3D particle field reconstruction. Based on a pair of 3D particle fields, the 3D-3C velocity field is obtained through a 3D cross correlation algorithm. Numerical simulations and experiments are conducted to analyze the accuracy and efficiency of the proposed method. The simulation results show that the elongation along the depth direction and the efficiency of the 3D particle field reconstruction are improved by the 3D U-Net. The 3D U-Net also provides a better correlation coefficient. The experimental results show that the reconstruction time of the proposed method is ∼220 s which is 10 times faster than the LF tomographic PIV. This further demonstrates that the proposed method improves the reconstruction efficiency without affecting the accuracy of velocity measurement.

Flow field reconstruction from spray imaging: A hybrid physics-based and machine learning approach based on two-phase fluorescence particle image velocimetry measurements

The interaction between liquid spray and the surrounding air is crucial in fluid research, especially in the study of fuel spray and combustion. However, the fuel spray–air interaction is a complex process influenced by multiple factors, including fuel type, fuel injection pressure, and fuel temperature. These factors are coupled together, making it challenging and time-consuming to accurately capture the spray–air data using traditional experimental methods alone. The current study proposes a hybrid physics-based and machine learning model for utilizing spray images to reconstruct ambient flow fields. The novelty of this work lies in leveraging the spatial characteristics of spray and airflow data to optimize feature extraction and reduce unnecessary nonlinearity in the model. Consequently, the model offers complementary advantages, improving model interpretability and reducing its reliance on massive data. The training dataset is collected using a combined diagnostic approach, utilizing Mie-scattering imaging and fluorescence particle image velocimetry. The liquid spray and the ambient air velocity field are measured simultaneously under a wide range of experimental conditions, including different fuel types, fuel injection pressures, and fuel temperatures. The reconstruction results are validated against unseen experimental data. In general, the reconstruction results indicate that the model is accurate, fast, and robust for different fuel conditions and injector types. It provides an innovative way to reconstruct airflow fields based on spray images (spray density distribution). These findings highlight the potential of integrating physics-based and machine learning methods for multiphase flow diagnostics, paving the way for broader data-driven applications in fluid research.

Vortex shedding from a square cylinder interacting with an undular bore wave train

In this work, we studied the wave-induced vortex generation and shedding from a semi-submerged vertical square cylinder interacting with an upcoming undular bore wave train under a shallow water configuration. This unsteady and rapid process was investigated by means of numerical and experimental approaches. A numerical simulation, solving the full turbulent viscous Navier–Stokes equations, was carried out in order to study and characterize both the undular bore wave properties and the vortex dynamics triggered during this unsteady interaction. Starting with fluid at rest, the undular bore was generated by the impulsive translational motion of a piston wavemaker at laboratory scale in both a numerical and an experimental wave tank. When the undular bore impinges on the cylinder, filamentary vortex structures were formed at the four cylinder's edges synchronized with the propagating wave motion, leading to the vortex shedding phenomena at a frequency that matched the wave instantaneous frequency. These vortices extended along the entire cylinder span under the water column, from the free surface to the seabed. At the trailing edge of the cylinder, a pairing process of two shed vortices was observed, similar to a Lamb–Oseen vortex pair. These vortices were present during the whole undular bore wave train dynamic forcing. An overall agreement was found with the experimental version of the bore–cylinder interaction, carried out in a physical wave tank. Laser sheet bore profiling and particle image velocimetry measurements of the velocity field confirmed undular bore properties, the onset of vortex formation, subsequent shedding, and pairing in the experiments performed in similar conditions with the numerical approach.

On Improving the Noise Reduction Performance of Trailing Edge Serrations by Extension

Trailing edge serration is an effective method to reduce broadband noise generation by an airfoil. However, the noise reduction performance can be significantly reduced when there is flow misalignment at the serration. This experimental study investigates the impact of a shift in the serration position downstream of the airfoil trailing edge on the noise reduction performance, referred to in this paper as serration extension. Experiments were performed on a 100-mm-chord NACA 0012 wing model with sawtooth trailing edge serrations. The serration performance was studied at 0° and 7° flap-down configurations at various angles of attack. The serrations with three different extension lengths of 5, 10, and 15 mm were tested and compared with the baseline case without extension. The emitted noise was measured with a phased microphone array. The results show a significant reduction in broadband high-frequency noise by extension under loading conditions. Particle image velocimetry measurements of root flow along the wall-normal plane reveal diminished crossflow across the serration after extension. Furthermore, the extensions cause an up-to-25% increase in the maximum lift coefficient and improved or unaltered lift-to-drag ratios.

A simple analytical model for turbulent kinetic energy dissipation for self-similar round turbulent jets

This work presents a simple analytical model for the streamwise and radial variations of turbulent kinetic energy dissipation in an incompressible round turbulent jet. The key assumptions in the model are: similarity in the axial velocity profile with a Gaussian shape, axisymmetric flow and the dominance of radial derivatives of the mean velocity over axial direction derivatives (similar to boundary layer theory). Initially, a simplified eddy-viscosity relation for turbulent stresses is derived using the algebraic stress model by Gatski & Speziale (J. Fluid Mech., vol. 254, 1993, pp. 59–78). Subsequently, with this eddy-viscosity relation, the relation for variations of turbulent kinetic energy dissipation is formulated using the conservation of turbulent kinetic energy. To extract the necessary constants of the model, experimental velocity statistics for round jets are obtained through particle image velocimetry measurements. The experimental results of the mean entrainment coefficient for turbulent jets are also analysed. When comparing the radial variation of turbulent kinetic energy dissipation from the model with experimental results at Reynolds number $1.4\times 10^5$ and numerical results at Reynolds number $1200$ from the available literature, we observe a maximum error of $10\,\%$ and $15\,\%$ , respectively. Finally, using the validated model, we analyse the impact of mean velocity evolution parameters on the behaviour of turbulent kinetic energy dissipation and discuss its potential significance in future studies.

Experimental investigation on rheological behavior of dry granular mixtures based on direct measurement of basal friction

Geophysical flows, characterized by diverse particle-size mixtures, pose challenges for hazard risk assessment due to their anomalous fluidity and rheological behavior. This study investigates the rheological behavior of dry granular mixture flow in a flume setup using particle image velocimetry and triaxial force measurement. Key findings include a power-law relationship between the inertia value and the internal friction coefficient, affirming the applicability of the monodisperse friction model in mixed particle-size scenarios. A strong positive correlation is identified between the effective basal friction coefficient and internal friction coefficient, suggesting an influence of internal frictional properties on basal friction for granular flows on a flat surface. Additionally, positive correlations are observed between normalized stress fluctuation and both internal friction coefficient and inertia number, linking basal stress fluctuations to variations in internal frictional characteristics. These insights enhance our understanding of granular material dynamics, holding potential implications for geological disaster risk assessment.

A numerical framework to investigate isotropic turbulent inflow interacting with an airfoil’s leading edge

This paper presents a numerical framework to study the interaction of isotropic turbulence with airfoils. Specifically, the developed numerical framework is used to investigate the distortion of the turbulent structures interacting with an airfoil’s leading edge. For turbulence modeling, Large Eddy Simulation (LES) is used. The isotropic turbulent inflow for the Computational Fluid Dynamics (CFD) simulations is synthetically generated using the turbulent digital filter method. The case studied with the numerical framework is a NACA 0012 airfoil with a chord-based Reynolds number of Rec=2×105 and an angle of attack of α=5°. The numerical simulation results are compared to high-speed particle image velocimetry (PIV) measurements performed for a NACA 0012 airfoil at the equivalent chord-based Reynolds number and turbulent inflow conditions. The CFD results of the numerical framework compare well with the experiments in terms of velocity spectra and RMS values upstream of the airfoil’s leading edge. The spectra and correlations of the velocity field generated by the turbulent digital filter demonstrate its ability to generate isotropic turbulent inflow. Instantaneous velocity fields show that the airfoil suppresses large-scale turbulent structures of the incoming turbulent flow. The size of the incoming turbulent structures decreases as they approach the leading edge due to the presence of the airfoil. The pre-multiplied spectra of the different velocity components show that downstream of the airfoil’s leading edge, the turbulent structures are stretched in the streamwise direction. The streamwise turbulent integral length scales and the velocity RMS values upstream of the airfoil’s leading edge indicate that the velocity components most affected by distortion are the streamwise and wall-normal components.