Cross-sectional Plane Research Articles

Liquid flows induced in a rotating drum with different fill ratios

In the present study, we experimentally investigate the liquid flow induced in a rotating drum (cylindrical tank with a short aspect ratio) aligned horizontally, focusing on the variation in the time-averaged and fluctuating flow structures with different fill ratios. For each fill ratio, controlled by varying the water height, we measure the velocity fields at different cross-sectional planes with particle image velocimetry while varying the rotational speed of the drum. Compared to the condition of a fill ratio of 1.0, in which the liquid inside the drum rotates forming a large-scale (solid-body rotation) organized flow structure, a substantial asymmetric flow structure shows up in partially-filled conditions driven by the imbalance between (i) the momentum diffusion along the radial direction and the centrifugal acceleration, and (ii) the downward (gravitational) flux of the induced flow. In addition to the mean flow structure, we examine the fluctuating velocity fields together with the dynamics of the free surface, and we also briefly discuss the difference between the liquid flow and granular (particle) flow in a partially-filled drum. We think that the present results provide valuable insights on the partially-filled liquid drum toward various engineering applications.

Volumetric imaging of trabecular meshwork dynamic motion using 600 kHz swept source optical coherence tomography.

The motion of the trabecular meshwork (TM) facilitates the aqueous drainage from the anterior chamber to the venous system, thereby maintaining normal intraocular pressure. As such, characterizing the TM motion is valuable for assessing the functionality of the aqueous outflow system, as demonstrated by previous phase-sensitive optical coherence tomography (OCT) studies. Current methods typically acquire motion from a single cross-sectional plane along the circumference of the anterior chamber. While effective, the lateral scan pattern only intersects one spatial location on the TM at a time, significantly limiting examination throughput. In this study, we introduce the first volumetric imaging approach for assessing TM motion. Rather than monitoring a single cross-sectional plane, our method employs repeated volumetric scans, allowing for simultaneous observation of a continuous TM band spanning two millimeters. We also show that the field of view could be further expanded by stitching multiple scans. To ensure robust data processing, we developed a customized volume registration algorithm to correct motion artifacts and an automated segmentation algorithm to identify the TM boundary based on the correlation of OCT phase dynamics with heartbeats. Imaging results from a healthy subject confirmed the feasibility of our approach, revealing considerable variation in TM motions at different spatial locations through the stitching process. This proposed methodology offers unprecedented capabilities and examination throughput in the biomechanical imaging of the TM, providing significant scientific insights and diagnostic value for identifying abnormalities in aqueous outflow.

On the river flow motion in the bend channel cross-section

At the river bed curves, secondary flow normal to the main flow direction are formed. Depending on the channel geometry, there may be several secondary flows in the cross-section, and they may have different scales. Even a small secondary cross-section flow affects the parameters of the hydrodynamic flow and this influence must be taken into account when modeling riverbed processes and researching coast deformations of the channel. Three-dimensional modeling of such multi-scale processes requires large computational costs and is currently possible only for small model channels. Therefore, a reduced-dimensional model is proposed in this paper to study coastal processes. The performed reduction of the problem from a three-dimensional model of river flow motion to a two-dimensional one in the plane of the channel cross-section assumes that the hydrodynamic flow is quasi-stationary and the hypotheses on the asymptotic behavior of the flow along the flow coordinate are fulfilled for it. Taking into account these limitations, a mathematical model of the problem of a stationary turbulent calm river flow in a channel cross-section is formulated in this work. The problem is formulated in a mixed velocity–vortex–stream function formulation. Specifying of the boundary conditions on the flow free surface for the velocity field determined in the normal and tangential directions to the cross-section axis is required as additional conditions for the problem reduction. It is assumed that the values of this velocity field should be determined from the solution of auxiliary problems or obtained from data of natural or experimental measurements. The finite element method in the Petrov–Galerkin formulation is used for the numerical solution of the formulated problem. A discrete analog of the problem is obtained and an algorithm for its solution is proposed. The performed numerical studies showed generally good agreement between the obtained solutions and the known experimental data. The authors associate the errors in the numerical results with the need for a more accurate determination of the radial component of the velocity field in the cross-section by selecting and calibrating a more suitable model for turbulent viscosity calculating and a more accurate determination of the boundary conditions on the cross-section free boundary.

Engaging grade school learners with an interactive medical imaging activity.

This case report describes a 45-min active learning lesson plan that engages 4th-5th and 6th-8th grade school students in spatial reasoning through a review of medical imaging. The lesson plan reviews different planar orientations and cross-sections of computed tomography (CT) images of familiar objects. The lesson is designed to introduce students to the idea that scientists are key contributors to healthcare, including in medical imaging technologies that facilitate the visualization of internal structures of patients without invasive procedures. The lesson demonstrates the three standard anatomical planes, axial, sagittal and coronal, by guiding students through CT image datasets of various objects. Students then are led in an interactive "dissection" of fruit to compare internal structures with medical images. The lesson plan aligns with key aspects of Next Generation Science Standards and aims to spark interest in the field of medical physics among a young student population through an introduction to imaging technologies. Worksheets and imaging datasets are included as supplementary materials to facilitate interested physicists adapting this work for educational purposes in their own communities, with minimal repeated effort.

ON THE STABILITY OF STRICT EQUILIBRIUM OF PLASMA IN TWO-DIMENSIONAL MATHEMATICAL MODELS OF MAGNETIC TRAPS

The article presents an analysis of instabilities known from previous works in a two-dimensional mathematical model of plasma configuration equilibrium using the example of a toroidal magnetic trap “Galatea–Belt” straightened into a cylinder and possessing plane symmetry. It is established that the previously observed large values of the two-dimensional velocity of disturbances in the plane of the cylinder cross-section arise on the periphery of the configuration near its conventional boundary, do not grow with time, and are due to arbitrarily small values of density, which is not determined by the idealized model of strict equilibrium. By varying the density, it is possible to influence stability. Three-dimensional (corrugated along the axis of the cylinder) disturbances grow with time in accordance with the traditional Lyapunov instability. Calculations allow us to determine the dependence of its quantitative characteristics on the problem parameters.

Experimental study on eccentric compressive performance of RC columns strengthened with textile-reinforced high-strength high ductile concrete

Textile-reinforced concrete (TRC) exhibits limited efficiency in strengthening RC columns, primarily due to low textile utilization and inadequate compressive strength. To improve the compressive performance of RC columns, high-strength high ductile concrete (HSHDC) is employed to replace the concrete in TRC, forming textile-reinforced HSHDC (TR-HSHDC). HSHDC possesses a compressive strength exceeding 100 MPa and a peak tensile strain of 2 %, with internal short fibers contributing to improved textile utilization. Eight RC columns, including two control columns, one HSHDC-strengthened column, and five TR-HSHDC-strengthened columns, were tested under eccentric loading. The experimental parameters included initial eccentricity, level of preloading, and number of textile layers. The results indicated that the strengthened columns exhibited good integrity at failure and generated fine cracks on the surface. Under non-preloading conditions, the load-bearing capacity and ductility gain caused by TR-HSHDC jackets were from 48.6 % to 181.7 % and 12.1–59.3 %, respectively. As the initial eccentricity increased, the load-bearing capacity gain improved. However, the strengthening effect decreased as the level of preloading increased, which was attributed to the strain lag of the strengthening material. Finally, based on the plane cross-section assumption, a calculation formula considering strain-lag behavior was established to predict the maximum load of the column strengthened with TR-HSHDC.

Three-dimensional simulation of film boiling on a horizontal surface with magnetic field

This study conducts a numerical investigation into the three-dimensional film boiling of liquid under the influence of external magnetic fields. The numerical method incorporates a sharp phase-change model based on the volume-of-fluid approach to track the liquid–vapour interface. Additionally, a consistent and conservative scheme is employed to calculate the induced current densities and electromagnetic forces. We investigate the magnetohydrodynamic effects on film boiling, particularly examining the pattern transition of the vapour bubble and the evolution of heat transfer characteristics, exposed to either a vertical or horizontal magnetic field. In single-mode scenarios, film boiling under a vertical magnetic field displays an isotropic flow structure, forming a columnar vapour jet at higher magnetic field intensities. In contrast, horizontal magnetic fields result in anisotropic flow, creating a two-dimensional vapour sheet as the magnetic strength increases. In multi-mode scenarios, the patterns observed in single-mode film boiling persist, with the interaction of vapour bubbles introducing additional complexity to the magnetohydrodynamic flow. More importantly, our comprehensive analysis reveals how and why distinct boiling effects are generated by various orientations of magnetic fields, which induce directional electromagnetic forces to suppress flow vortices within the cross-sectional plane.

Speeding up echocardiographic examination by automated generation of 2D imaging views from 3D volumetric data using machine learning

Abstract Background 3D echocardiographic data contain infinite 2D echocardiographic planes generated by multiplanar reconstruction, but the process is labor-intensive and time-consuming. Artificial intelligence (AI) utilizing cutting-edge machine learning techniques may improve the accuracy and efficiency of the process. In the study, we developed and validated an AI software that automatically reconstructs 7 2D views recommended by the American Society of Echocardiography from 3D echocardiographic data. Method Convolutional neural network (CNN) architecture utilizing Spatial Configuration Net was used as the machine learning model. We identify a minimum of 3 key feature landmarks on each 2D cross-sectional plane, with the 3D coordinates representing 2D cross-sectional planes accordingly. Subsequently, these landmarks are accurately labeled within a 3D space. 31 landmarks were identified across 7 2D cross-sectional planes and a total of 472 3D volume data were labelled. The performance of the model is evaluated by Root Mean Square Error (RMSE) of the predicted landmark coordinates. Results The mean RMSE over 31 predicted landmarks evaluated in testing is 2.70% for the input 3D volume dimensions. The average time used to generate the 7 2D imaging views was 19.91±3.19 seconds (figure). Conclusion The AI algorithm can efficiently convert 3D echocardiographic data into guideline-recommended 2D images, which shortens the length of echo examination but still preserves the accuracy.AI generation of 2D views from 3D echo

Computational Study of Pump Turbine Performance Operating at Off-Design Condition-Part I: Vortex Rope Dynamic Effects

As global power demand increases, hydropower plants often must operate beyond their optimal efficiency to meet grid requirements, leading to unstable, high-swirling flows under various load conditions that can significantly shorten the lifespan of turbine components. This paper presents an in-depth computational study on the performance and dynamics of a pump-turbine operating under 80% partial load, focusing on the formation and impact of vortex ropes. Large Eddy Simulation (LES) was utilized to model the turbulent flow, revealing complex patterns and significant pressure fluctuations. A pronounced straight vortex rope was identified in the draft tube, maintaining its trajectory and core size consistently, profoundly affecting flow characteristics. Pressure fluctuations were observed at various cross-sectional planes, with peaks and troughs primarily near the runner, indicating areas prone to instability. The standard deviation of pressure fluctuations ranged from 4.51 to 5.26 along the draft tube wall and 4.27 to 4.97 along the axial center, highlighting significant unsteady flow. Moreover, the frequency corresponding to the highest amplitude in pressure coefficient spectrographs remained consistent at approximately 9.93 to 9.95, emphasizing the persistent influence of vortex rope dynamics. These dynamics affected power generation, which was approximately 29.1 kW, with fluctuations accounting for about 3% of the total generated power, underscoring the critical impact of vortex rope formation on the performance and operational stability of pump-turbines under off-design conditions. This study provides essential insights vital for enhancing the design and operational strategies of these turbines, ensuring more efficient and reliable energy production in the face of increasing power demands.

Comparative analysis of inlet and outlet cavity designs on the thermal-hydraulic performance of compact heat exchangers for combustion engine exhaust heat recovery

ABSTRACT Improving the Internal Combustion Engines (ICEs) overall thermal efficiency is crucial to reduce fuel consumption and emissions. To achieve this goal, waste heat recovery from exhaust gases remains the most promising strategy, which involves the utilization of compact heat exchangers. This study evaluates the performance of novel Monolithic Integrated Thermal Exchange Matrixes (MITEMs) designs for recovering exhaust heat from a 70 hp diesel engine, focusing on the impact of inlet/outlet cavities. Computational Fluid Dynamics simulations were employed to analyze the heat transfer rate, pressure drop, and overall thermal-hydraulic performance of different MITEM designs. The Rectangular Channels with Large Cavities (RCLC) design exhibited superior performance, enhancing the heat transfer rate by 14.7% compared to the baseline design while limiting pressure drop increase to 9.2%. The RCLC design increased local Nusselt numbers and heat transfer coefficients by up to 60%, achieving peak velocities of 98 m/s within cross-sectional planes. These findings provide valuable insights for optimizing exhaust heat recovery systems in diesel engines.

Deep learning-based characterization of pathological subtypes in lung invasive adenocarcinoma utilizing 18F-deoxyglucose positron emission tomography imaging

SummaryObjectiveTo evaluate the diagnostic efficacy of a deep learning (DL) model based on PET/CT images for distinguishing and predicting various pathological subtypes of invasive lung adenocarcinoma.MethodsA total of 250 patients diagnosed with invasive lung cancer were included in this retrospective study. The pathological subtypes of the cancer were recorded. PET/CT images were analyzed, including measurements and recordings of the short and long diameters on the maximum cross-sectional plane of the CT image, the density of the lesion, and the associated imaging signs. The SUVmax, SUVmean, and the lesion's long and short diameters on the PET image were also measured. A manual diagnostic model was constructed to analyze its diagnostic performance across different pathological subtypes. The acquired images were first denoised, followed by data augmentation to expand the dataset. The U-Net network architecture was then employed for feature extraction and network segmentation. The classification network was based on the ResNet residual network to address the issue of gradient vanishing in deep networks. Batch normalization was applied to ensure the feature matrix followed a distribution with a mean of 0 and a variance of 1. The images were divided into training, validation, and test sets in a ratio of 6:2:2 to train the model. The deep learning model was then constructed to analyze its diagnostic performance across different pathological subtypes.ResultsStatistically significant differences (P < 0.05) were observed among the four different subtypes in PET/CT imaging performance. The AUC and diagnostic accuracy of the manual diagnostic model for different pathological subtypes were as follows: APA: 0.647, 0.664; SPA: 0.737, 0.772; PPA: 0.698, 0.780; LPA: 0.849, 0.904. Chi-square tests indicated significant statistical differences among these subtypes (P < 0.05). The AUC and diagnostic accuracy of the deep learning model for the different pathological subtypes were as follows: APA: 0.854, 0.864; SPA: 0.930, 0.936; PPA: 0.878, 0.888; LPA: 0.900, 0.920. Chi-square tests also indicated significant statistical differences among these subtypes (P < 0.05). The Delong test showed that the diagnostic performance of the deep learning model was superior to that of the manual diagnostic model (P < 0.05).ConclusionsThe deep learning model based on PET/CT images exhibits high diagnostic efficacy in distinguishing and diagnosing various pathological subtypes of invasive lung adenocarcinoma, demonstrating the significant potential of deep learning techniques in accurately identifying and predicting disease subgroups.

Multi-scale three-dimensional simulation of the solidification microstructure evolution in laser welding of aluminum alloys under dynamic spatial thermal cycling

Laser welding process involves three-dimensional (3D) highly dynamic spatial thermal cycling that results in intricate microstructure evolution in different zones. Understanding of the 3D topological evolution of microstructure under spatial thermal cycling is crucial for effective control in solidification processes. In this paper, a 3D multiphase-field model combined with accelerated methods and multi-scale coupling algorithms was developed for high-precision prediction of the dynamic microstructure evolution in laser welding. The heat flow distribution during laser welding varied significantly, with the cooling rates of 1.7–1.9 × 104 K/s at the middle region and 7.5–9.0 × 104 K/s at the bottom region. Considering the effects of 3D heat flow, a large angle may appear between the grains' primary growth direction and the cross-sectional plane, thereby the ultimate morphology through 2D analysis may lead to distortion from reality. The simulation of 3D microstructure evolution during distinct regions results showed that the grains at the bottom region exhibited larger characteristic dimensions (Length/Height >2.5, Length/Width >2.0) and columnar shape, while the middle region tended to form equiaxed structures. The grain size statistics revealed that the grains in the middle region exhibited larger scale due to their smaller GR (G: temperature gradient, R: growth rate) values. The simulation results were in good agreement with the electro-back-scattered diffraction testing results and the theoretical analysis.

Numerical Study of Surface Flow for Ahmed Body in Crosswind Conditions

This study investigates standard vehicles' flow behavior and drag during crosswind conditions by a numerical approach. The model is a half-scaled Ahmed body with a slant angle of 25°. Reynolds Average Navier-Stokes equations with turbulent model k-ω SST is applied to solve Navier Stokes equation by discrete method. Experimental data validated the numerical results at the same flow conditions. The results indicated that the model's drag increases with yaw angles, which is connected with the development of the longitudinal vortex on the windward side. However, the lift coefficient and pressure drag acting on the slant showed a maximum value at a yaw angle of around 35° before they dropped again. The drop of those coefficients results in the moving upward of the longitudinal vortex above the slant. The complex vortex structures around the base in both cross-sectional and symmetric planes are analyzed. The skin-friction pattern and pressure distribution on the slant are exposed to understand the effect of the yaw angle on aerodynamic forces.

Microstructure-Reconfigured Graphene Oxide Aerogel Metamaterials for Ultrarobust Directional Sensing at Human-Machine Interfaces.

Graphene aerogels hold huge promise for the development of high-performance pressure sensors for future human-machine interfaces due to their ordered microstructure and conductive network. However, their application is hindered by the limited strain sensing range caused by the intrinsic stiffness of the porous microstructure. Herein, an anisotropic cross-linked chitosan and reduced graphene oxide (CCS-rGO) aerogel metamaterial is realized by reconfiguring the microstructure from a honeycomb to a buckling structure at the dedicated cross-section plane. The reconfigured CCS-rGO aerogel shows directional hyperelasticity with extraordinary durability (no obvious structural damage after 20 000 cycles at a directional compressive strain of ≤0.7). The CCS-rGO aerogel pressure sensor exhibits an ultrahigh sensitivity of 121.45 kPa-1, an unprecedented sensing range, and robust mechanical and electrical performance. The aerogel sensors are demonstrated to monitor human motions, control robotic hands, and even integrate into a flexible keyboard to play music, which opens a wide application potential in future human-machine interfaces.

A method for the determination of local packing factor distribution of a packed pebble bed by the improved line-based averaging method

The packing factor is an important parameter for describing the internal structural features in pebble beds, which have a significant influence on the heat and mass transfer behavior and the thermo-mechanical properties of the pebble bed. A comprehensive understanding of the packing structure is essential for the design and optimization of the pebble bed and can promote the application of the pebble bed. In this work, an improved line-based averaging method was proposed to calculate the local packing factor or local porosity distribution and validated by comparing the results with those obtained from experimental and numerical studies of cylindrical packed pebble bed. Furthermore, the local packing factor distributions in the angular-radial plane of the cylindrical pebble bed were revealed for the first time. In addition, the line-based averaging method has been applied to reveal the local packing factor distributions in the annular pebble beds, U-shaped pebble beds and hexagonal pebble beds. The main feature of this method is the ability to calculate and plot contour maps of local packing factor or porosity distributions for columnar pebble beds of arbitrary shapes, especially the local packing factor distributions in the cross-sectional plane and the angular-radial plane.

Characterizing magnetohydrodynamic effects on developed nanofluid flow in an obstructed vertical duct under constant pressure gradient

Abstract This research endeavors to conduct an examination of the thermal characteristics within the duct filled with the copper nanoparticles and water as base fluid. In exhaust systems, like car exhausts, chimneys, and kitchen hoods, duct flows are crucial. These systems safely discharge odors, smoke, and contaminants into the atmosphere after removing them from enclosed places. The study focuses on a laminar flow regime that is both hydrodynamically and thermally developed, with a specified constraints at any cross-sectional plane. To address this, we employ the finite volume method as it stands as a judicious choice, offering a balance between computational efficiency and solution accuracy. Notably, we have observed that the deceleration of flow induced by elevated Rayleigh numbers can be effectively regulated by the application of an appropriately calibrated external magnetic field. The prime parameters of the problem with ranges are: pressure gradient ( 1 ≤ p 0 ≤ 100 ) (1\le {p}_{0}\le 100) , Hartmann number ( 0 ≤ Ha ≤ 50 ) (0\le \text{Ha}\le 50) , Rayleigh number ( 1 , 000 ≤ Ra ≤ 40 , 000 ) (1,000\le \text{Ra}\le 40,000) , and magnetic parameter ( 0 ≤ M ≤ 50 ) (0\le M\le 50) . Furthermore, our analysis reveals that the Nusselt number exhibits a nearly linear correlation with the nanoparticle volume fraction parameter, a trend observed across a range of Rayleigh numbers and magnetic parameter values. We have noted that a mere 20% nanoparticle volume fraction can result in up to 62% rise in the Nusselt number while causing an almost 50% decrease in the factor f Re. This research framework serves as a robust foundation for understanding the intricate interplay between magnetic influences and thermal-hydraulic behavior within the delineated system.

Twice-topology optimized heat sinks for enhanced heat transfer performance: Numerical and experimental investigation

Since the heat dissipation problem is always confusing and hindering the computing power improvement of electronic chip, an effective thermal management strategy is critical to relieve these problems. In this work, a new twice topology optimization design method combining topology optimization and image processing to design heat sinks is presented, which extends topology optimization from 2Dimention (2D) to 3Dimention(3D). Firstly, on the horizontal design domain, the conventional topology optimization is conducted for the minimization of average temperature/standard deviation. Then the optimal shape of liquid domain is converted into 1D flow routine by thinning algorithm. After that, another topology optimization is performed on the flow channel cross-section plane to get the best cross-section shape of channels. The liquid domain of the final heat sink is then obtained by scanning the optimized flow channel cross-section along the 1 Dimension (1D) flow routine and solving the interference by introducing cylinder joints. Finally, two kinds of twice topology optimized heat sinks including TTOHS-1 with minimized temperature variation as optimal goal and TTOHS-2 with minimized average temperature as optimal goal are generated by combining the liquid domain and a cuboid using Boolean Operation. The performance of heat sinks is numerically investigated, and the results indicate that the thermal performance of TTOHS-1 and TTOHS-2 are much better than that of the traditional heat sink with straight channels (TSCHS). When Re = 689, the average temperature and the maximum temperature of the heat source surface of TTOHS-1 are decreased by 4.99 % and 6.29 % respectively, compared to the TSCHS. The Nusselt number is increased by 46.16 % while the thermal resistance is reduced by 33.13 %. At last, the thermal and flow performance of the TTOHS-1 is studied by conducting experiments, showing that the numerical results agree well with that of the experiment.

Pulsed directed energy deposition-arc technology for depositing stainless steel 309L: Microstructural, elements distribution, and mechanical characteristics

In recent years, additive manufacturing has increased in prominence as a primary method of manufacturing around the globe. Modern metal additive manufacturing presents an innovative approach to manufacturing complex structures for the aerospace, energy, and construction sectors, due to technological advancements. In the present study, the austenitic stainless steel 309L (SS-309L) thick wall component was manufactured employing pulsed current gas tungsten arc welding (PC-GTAW) WAAM technology. The metallurgical characteristics of the as-deposited SS-309L thick wall part were evaluated. The investigation of material characteristics in the manufactured areas encompasses a study of cross-sectional (CS) and transverse-sectional (TS) regional portions, specifically the upper, middle, and lower regions. The microstructures of the CS and TS planes showed austenite, columnar, and delta ferrite dendrites in the upper, middle, and lower regions, respectively. The CS sample reveals the greatest grain size at 159.4 μm, following the EBSD investigation. The average size of the grains across the TS is 127.09 μm. The thermal cycles in multi-layer production result in changes in grain size. The microhardness in the transverse sectional regions is higher than in the CS regions, measuring average values of 257 HV, 253 HV, and 251 HV for the upper, middle, and lower sections, respectively. The ultimate tensile strengths (UTS) in the cross-sectional parts are 656 MPa, whereas in the transverse regions it was 661 MPa for the topmost regions. This study investigates the correlation among the mechanical and metallurgical properties of wire arc additively fabricated SS-309L austenite steel material.

Effect of secondary flow and wall collisions on particle-laden flows in 90° pipe bends

Fully developed, statistically stationary particle-laden turbulent flows in a 90° pipe bend at a moderate Reynolds number are studied using direct numerical simulation coupled to a Lagrangian particle tracking technique. Three populations of particles are studied which are two-way coupled with the carrier phase. The focus is the investigation of the effect of strong curvature on particle transport dynamics across a range of particle inertias. A validation of the carrier phase predictions is performed, with good agreement found with available experimental data. It is demonstrated that the presence of particles notably affects the turbulence statistics of the carrier phase, decreasing the mean fluid velocity in the outer bend while slightly increasing it in the inner bend. Two intriguing phenomena emerge: the presence of a particle void near the inner bend and reflection layers near the outer bend. Centrifugal forces are responsible for driving particles to the outer wall, with some rebounding back into the main body of the flow, and others, influenced by the secondary flow in the plane of the pipe cross-section, converging towards the inner wall before re-entering the central pipe region. These effects dictate the size and shape of the particle void region and the formation of reflection layers due to particle-wall collisions. These two phenomena have a significant influence on the particle distribution in the pipe bend, as well as on the first- and second-order moments of the velocity and acceleration of the particulate phase. Finally, a heat map of particle-wall collision statistics indicates that the effect of the secondary flow on particle distribution and particle-wall collisions is not negligible.

Large-Scale Side By Side Stereo-PIV Measurements In An Automotive Wind Tunnel: Aerodynamic Influence Of Ride Height Variations.

In this investigation, we conducted large-scale Stereo PIV experiments in the flow around a Volkswagen ID.4. within the Aerodynamic and Aeroacoustic Wind Tunnel (AAK) at Volkswagen AG, Wolfsburg. The primary objective of these experiments was to investigate the effects of ride height variation on the near wake of the passenger vehicle using Stereo PIV, while minimizing wind tunnel occupancy. The measurements aimed to create datasets for CFD validation to improve virtual aerodynamic development capabilities of passenger vehicles. The experiment was performed on a 1:1 scale vehicle and multiple cross-sectional planes were scanned along the longitudinal axis of the vehicle. The impact of ride height alterations on the wake flow topology were evaluated. Average velocity vector fields were computed per case, providing comprehensive insights into the aerodynamic effects of diverse vehicle setups. A small change in the ride height has shown to have a significant impact on the wake topology. The results show that the electric SUV ID.4 can yield a wake topology similar to the estate back and fast/notchback type of vehicle, depending on the ride height. The normal ride height of the ID.4 shows to have a broader but lower wake region, with a significant downwash. The PIV results of this configuration show significant similarities to the wake topology of a fast back vehicle. Lowering the ride height by 15 mm has shown already to be enough to cause a global effect on the wake topology and to exhibit a narrower wake and recirculation region, like an estate back vehicle. Additionally, the association between the drag/lift coefficients and the wake topology of both configurations was discussed. Results have shown that sole measurements in the wake are not sufficient to fully explain changes in the determined drag or front lift coefficients. The rear lift coefficients however, indicate a stronger relationship with the near wake topology of the vehicle.