Fluid Flow Field Research Articles

A mathematical model for wind-generated particle–fluid flow fields with an application to the helicopter cloud problem

We develop a model for the interaction of a fluid flowing above an otherwise static particle bed, with generally the particles being entrained or detrained into the fluid from the upper surface of the particle bed, and thereby forming a fully two phase fluidized cloud above the particle bed. The flow in this large-scale fluidized region is treated as a two-phase flow, whilst the key processes of entrainment and detrainment from the particle bed are treated by examining the local dynamical force balances on the particles in a thin transition layer at the interface between the fully fluidized region and the static particle bed. This detailed consideration leads to the formation of an additional macroscopic boundary condition at this interface, which closes the two-phase flow problem in the bulk fluidized region above. We then introduce an elementary model of the well-known helicopter brownout problem, and use the theory developed in the first part of the paper to fully analyse this model, both analytically and numerically.

Rotational flow field of a particle-laden fluid on a co-rotating disk

The particle-modified velocity field of a rotating particulate fluid on a co-rotating disk is studied. Unlike a clear fluid, which admits pure rigid-body rotation with a zero radial velocity component, it is shown here that an unbounded particle-laden fluid does not admit pure rigid-body rotation. An exact solution is given for an unbounded rotating particle-laden fluid, which contains a non-zero radial velocity component and cannot meet the no-slip boundary conditions on a disk co-rotating at the same angular velocity. Explicit leading-order solutions are derived for the particle-modified velocity field of a rotating particulate fluid on a co-rotating disk. It is shown that the disturbed radial and azimuthal velocities due to the co-rotating disk are oscillatory and decay exponentially with the distance from the disk, while the disturbed axial velocity approaches a constant at infinity. The derived formula is used to discuss the radial, azimuthal, and axial velocities of dispersed particles and their effects on the rotational flow of the rotating particle-laden fluid.

A general Physics-Informed neural network approach for deriving fluid flow fields from temperature distribution

A general Physics-Informed neural network approach for deriving fluid flow fields from temperature distribution

Experimental Study of Airfoil Aerodynamic Behavior under Oscillating Motion in Ground Effect

When a flying vehicle approaches a water or land surface, it induces changes in the fluid flow field pattern known as the "ground effect." This research analyzes the ground effect phenomenon, exploring its impact on aerodynamic coefficients and flow patterns around the NACA0012 airfoil in an incompressible subsonic regime under static and dynamic conditions with pitch movements. Numerical simulations and experimental testing in an incompressible subsonic wind tunnel were deployed. The flow field solution is derived from the Navier-Stokes equations, incorporating the Transition SST turbulence model. Initially, the impact of the ground effect phenomenon was investigated at varying distances from the surface in the static state. Subsequently, the airfoil underwent a sinusoidal pitching oscillation at each distance with a specified frequency and amplitude. This allowed for examining its aerodynamic characteristics over time. The static analysis results reveal alterations in the curve's behavior and pressure distribution on the airfoil surface at close distances to the surface. This is attributed to the ground effect phenomenon, which reduces lift force to a certain height and then increases. Dynamic analysis further demonstrates changes in lift coefficient oscillation amplitude. It also exhibits a minimum and maximum lift point phase difference as the airfoil approaches the surface.

Chemical Bath Deposition of NiFe Alloy Anode for Efficient Alkaline Water Electrolyzer Integration.

Green hydrogen production from water splitting is a feasible way for intermittent renewable energy storage and utilization, where the exploration and scale-up preparation of high-performance anodic oxygen evolution electrocatalysts are critical prerequisites for its industrial-level applications. Herein, a chemical bath deposition of FeNi3 intermetallic alloys onto Ni mesh support is performed, which delivers a current density of 0.62 Acm-2 at 1.72 V versus reversible hydrogen electrode for alkaline water oxidation in 1 m KOH and an excellent electrolysis stability at 0.2 A cm-2 for over 300 h. Moreover, via 3D computational fluid dynamics simulation and flow field optimization, a homogeneous deposition of ≈5400 cm2 NiFe anode is demonstrated within 4 min using the developed flow bath reactor. Once integrating the as-prepared NiFe anodes into alkaline electrolyzer stack, the voltage variation between each unit cell is below 40 mV at a total operation current of 71 A, or ca. current density of 0.2 A cm-2, confirming the uniformity of this batch synthesis protocol and its great potential for industrial alkaline water electrolysis.

Induced magnetic field and thermal regulation of synovial fluid flow through irregular surfaces with first-order slip and gold nanoparticles

ABSTRACT The current computational exploration develops a poroelastic model of the knee cartilage to elevate its temperature under cyclic sinusoidal loading. A contributing factor to the rise in temperature is this tissue’s viscous dissipation, which converts some of the mechanical energy supplied into heat. The manipulation of cartilage temperature is mostly reliant on the movement of synovial fluid inside the space between joints and within the permeable cartilage. We developed the region flow model in the presence of induced magnetic fields and gold nanoparticles, which enhanced the efficiency of joint lubrication by boosting the load-carrying capacity. We dealt with the problem for two different models. Model 1 assumes that viscosity is exponentially dependent on concentration. The shear thinning index in Model 2 is regarded as a concentration-dependent variable. We introduce these models for a complex wavy surface, where the first-order slip effect occurs. We modified the governing problem by assuming a long wavelength and a low Reynolds number. We followed up with a computational analysis utilizing the Rung–Kutta–Merson approach with Newton iteration in a shooting and matching strategy. We have conducted detailed comparisons between Model 1 and Model 2. The graphical findings have been shown for the distributions of velocity, temperature, and nanoparticle concentration. Additionally, the pressure gradients, streamlines, and axially generated magnetic fields have also been included. These results are presented for numerous physical parameters. The mechanics of trapping are thoroughly examined through the use of streamlines.

Flowing Liquid Crystal Torons Around Obstacles

Liquid crystal torons, localized topological structures, are known for their stability and dynamic behaviour in response to external stimuli, making them attractive for advanced material applications. In this study, we investigate the flow of torons in chiral nematic liquid crystals around obstacles. We simulate the fluid flow and director field interactions using a hybrid numerical method combining lattice Boltzmann and finite difference techniques. Our results reveal that the toron dynamical behaviour depends strongly on the impact parameter from the obstacle. At impact parameters smaller than half cholesteric pitch, the flowing toron is destabilized by the interaction with the obstacle; otherwise, the flowing toron follows a trajectory with a deflection which decays exponentially with the impact parameter. Additionally, we explore the scattering of torons by multiple obstacles, providing insights into how the dynamics of these structures respond to complex environments.

An Optimization Design of Piezoelectric Hair Sensor for Oscillatory Flow Detection

Abstract Biological hair is widely found in nature, and they are responsible for sensing and responding to environmental stimuli in living organisms. By simulating biological hair characteristics, they develop hair flow sensor to achieve high sensitivity detection of environmental factors such as small motion and fluid flow field. Output signal is the key indicator of hair flow sensor, and the improvement of output signal is important to the design of hair flow sensor. The existing hair flow sensor sensing structure is generally straight hair, and the output signal is limited by the structure, and the response is small. Using the direct piezoelectric fiber as the initial configuration, we form a new piezoelectric curved fiber by modeling the secondary spline curve and control point. We propose an optimization model for piezoelectric functional hair design using axial strain as a target function. At 100Hz and 500Hz, the output voltage of the optimized model is much higher than that of straight, 10 times and 7 times that of straight, respectively; An optimized curved hair configuration is obtained in a specific frequency band from 1 Hz to 500 Hz, whose average voltage magnitude of 3.1×10−3 V is 4 times greater than that of the straight hair of 7.8×10−4 V with the same size. The curved hair flow sensor breaks the output limitation of traditional straight hair configuration.

Flow field analysis of newtonian fluid flow induced by planetary and radial motion of drill string

Abstract At present, in the process of oil drilling, the drill string is an essential downhole drilling tool. It is immersed in the hole filled with drilling fluid for a long time, and it is driven by the rotation of the rotary table to drill down. In this process, the drill string will not only rotate around its axis but also may rotate around the axis of the hole and produce radial motion. It is important to study the flow law of Newtonian fluid flow induced by drill string movement, which can effectively reduce drilling accidents caused by drill string vortex and buckling, thus reducing economic losses. After research and analysis, the finite volume method, which has good applicability and obvious advantages, is used to discretize the established mathematical model, and the mathematical equation after discretization is obtained. By using MATLAB software, the flow field of Newtonian fluid induced by drill string rotation motion is analyzed, the axial velocity distribution diagram and tangential velocity distribution diagram are obtained, and the velocity flow diagram under different eccentricity conditions is drawn. It is found that secondary flow occurs only when the eccentricity reaches a certain distance requirement.

Analysis and comparison of high-performance computing solvers for minimisation problems in signal processing

Several physics and engineering applications involve the solution of a minimisation problem to compute an approximation of the input signal. Modern hardware and software use high-performance computing to solve problems and considerably reduce execution time. In this paper, different optimisation methods are compared and analysed for the solution of two classes of non-linear minimisation problems for signal approximation and denoising with different constraints and involving computationally expensive operations, i.e., (i) the global optimisers divide rectangle-local and the improved stochastic ranking evolution strategy, and (ii) the local optimisers principal axis, the Limited-memory Broyden, Fletcher, Goldfarb, Shanno, and the constrained optimisation by linear approximations. The proposed approximation and denoising minimisation problems are attractive due to their numerical and analytical properties, and their analysis is general enough to be extended to most signal-processing problems. As the main contribution and novelty, our analysis combines an efficient implementation of signal approximation and denoising on arbitrary domains, a comparison of the main optimisation methods and their high-performance computing implementations, and a scalability analysis of the main algebraic operations involved in the solution of the problem, such as the solution of linear systems and singular value decomposition. Our analysis is also general regarding the signal processing problem, variables, constraints (e.g., bounded, non-linear), domains (e.g., structured and unstructured grids, dimensionality), high-performance computing hardware (e.g., cloud computing, homogeneous vs. heterogeneous). Experimental tests are performed on the CINECA Marconi100 cluster at the 26th position in the “top500” list and consider several parameters, such as functional computation, convergence, execution time, and scalability. Our experimental tests are discussed on real-case applications, such as the reconstruction of the solution of the fluid flow field equation on an unstructured grid and the denoising of a satellite image affected by speckle noise. The experimental results show that principal axis is the best optimiser in terms of minima computation: the efficiency of the approximation is 38% with 256 processes, while the denoising has 46% with 32 processes.

Super-Resolving and Denoising 4D flow MRI of Neurofluids Using Physics-Guided Neural Networks.

To obtain high-resolution velocity fields of cerebrospinal fluid (CSF) and cerebral blood flow by applying a physics-guided neural network (div-mDCSRN-Flow) to 4D flow MRI. The div-mDCSRN-Flow network was developed to improve spatial resolution and denoise 4D flow MRI. The network was trained with patches of paired high-resolution and low-resolution synthetic 4D flow MRI data derived from computational fluid dynamic simulations of CSF flow within the cerebral ventricles of five healthy cases and five Alzheimer's disease cases. The loss function combined mean squared error with a binary cross-entropy term for segmentation and a divergence-based regularization term for the conservation of mass. Performance was assessed using synthetic 4D flow MRI in one healthy and one Alzheimer' disease cases, an in vitro study of healthy cerebral ventricles, and in vivo 4D flow imaging of CSF as well as flow in arterial and venous blood vessels. Comparison was performed to trilinear interpolation, divergence-free radial basis functions, divergence-free wavelets, 4DFlowNet, and our network without divergence constraints. The proposed network div-mDCSRN-Flow outperformed other methods in reconstructing high-resolution velocity fields from synthetic 4D flow MRI in healthy and AD cases. The div-mDCSRN-Flow network reduced error by 22.5% relative to linear interpolation for in vitro core voxels and by 49.5% in edge voxels. The results demonstrate generalizability of our 4D flow MRI super-resolution and denoising approach due to network training using flow patches and physics-based constraints. The mDCSRN-Flow network can facilitate MRI studies involving CSF flow measurements in cerebral ventricles and association of MRI-based flow metrics with cerebrovascular health.

Role of periodic oscillating flow modulators on mixed convection in a long horizontal channel

Present study explores mixed convection characteristics in a long horizontal channel subjected to multiple periodically distributed flow modulators. The flow modulators are represented by oscillating blades placed along a centerline of the channel whose lower and upper walls are kept at constant high and low temperatures respectively. In replicating the blade oscillation, moving mesh approach has been adopted within Arbitrary Lagrangian–Eulerian (ALE) framework for a representative periodical unit. The corresponding non-dimensional governing mass, momentum and energy conservation equations have been solved through Galerkin finite element solver for a wide variations of modulator's dynamic condition (oscillating frequency and maximum angular displacement) for different fluids represented by Prandtl number. Heat transfer performance of the system has been demonstrated in terms of spatially-averaged transient as well as time-averaged Nusselt number while qualitative analysis of fluid flow and thermal field has been presented as streamline and isotherm plots. Present study indicates that the time averaged Nusselt number undergoes significant variation with blade oscillating frequency and maximum angular displacement depending on both the Prandtl number and Reynolds Number. Power spectrum analysis obtained through Fast Fourier Transformation (FFT) of the imposed blade frequency and induced thermal frequency reveals different correlation depending on the blade frequency. Blade friction power requirement has been found to increase at higher blade frequency as well as maximum angular displacement. However, contrary to power consumption, increase in frequency does not result in a significant rise in heat transfer. Consequently, specific heat transfer decreases at higher blade oscillating frequency and maximum angular displacement.

Optimizing the design of parallel busbars to suppress the Taylor Instability in large-scale liquid metal batteries

Abstract In this study, we utilize the open-source software OpenFOAM to numerically simulate the Tayler instability in liquid metal batteries. The simulation depicts the dynamic evolution of the electrolyte layer, fluid flow, and magnetic field distribution in the battery at different operating times. Special attention is paid to the influence of optimizing the parallel busbar configuration on Tayler instability and battery capacity. It is found that the additional magnetic field generated by the busbars can effectively alter the magnetic field distribution inside the battery, thereby significantly reducing the Lorentz force and suppressing the Tayler instability within the battery. Therefore, by optimizing the parallel busbar configuration, the stable operating time of the battery is prolonged, and the battery capacity is enhanced. This study provides theoretical support and practical guidance for the application of liquid metal batteries in large-scale grid-level energy storage systems and offers new insights into the development of energy storage technology.

Reconstruction of particle distribution for tomographic particle image velocimetry based on unsupervised learning method

The development of deep learning has inspired some new methods to solve the 3D reconstruction problem for Tomographic Particle Image Velocimetry (Tomo-PIV). However, the supervised learning method requires a large number of data with ground truth as training information, which is very difficult to gather from experiments. Although synthetic datasets can be used as alternatives, they are still not exactly the same with the real-world experimental data. In this paper, an Unsupervised Reconstruction Technique based on U-net (UnRTU) is proposed to reconstruct volume particle distribution explicitly. Instead of using ground truth data, a projection function is used as an unsupervised loss function for network training to reconstruct particle distribution. The UnRTU was compared with some traditional algebraic reconstruction algorithms and supervised learning method using synthetic data under different particle density and noise level. The results indicate that UnRTU outperforms these traditional approaches in both reconstruction quality and noise robustness, and is comparable to the supervised learning methods AI-PR. For experimental tests, particles dispersed in cured epoxy resin are moved by an electric rail with a certain speed to obtain the ground truth data of particle velocity. Compared with other algorithms, the reconstructed particle distribution by UnRTU has the best reconstruction fidelity. And the accuracy of the 3D velocity field estimated by UnRTU is 12.9% higher than that from the traditional MLOS-MART algorithm. It demonstrates significant potential and advantages for UnRTU in 3D reconstruction of particle distribution. Finally, UnRTU was successfully applied to the high-speed planar cascade airflow field, demonstrating its applicability for measuring complex fluid flow fields at higher particle density.

Physical and Numerical Study on Right Side and Front Side Gas Blowing at Walls in a Single‐Strand Tundish

The compromise between inclusions removal by small bubbles and proper agitation of fluid flow in tundish by gas blown is challenging. The single‐strand tundish without flow control devices (bare tundish) is used to study the effects of side‐wall gas blowing on the flow field. The water model, particle image velocity measurement and computational fluid dynamics simulation are used to study bubble behavior, fluid flow field, and tracer transport. A large horse shoe vortex and a short circuit flow at the bottom are formed in the bare tundish. Gas blowing at the outlet‐side wall of the tundish creates multiple vortices in the right‐side region, with blowing rate and position greatly influencing the surface flow within the tundish. Gas blowing at the front‐side wall creates a large spiral vortex, agitating the fluid in the tundish and improving the flow field. Increasing the blowing rate strengthens the vortex in the right region, but raising the blowing position affects surface flow and creates a counterclockwise flow toward the shroud. In all schemes, gas blowing at a low position on the front‐side wall with a small gas flowrate is the optimized scheme which shows the smallest dead volume and enhances surface flow.

Minor Loss Coefficient for Abrupt Section Changes in a Cylindrical Pipe Using a Numerical Approach

Abrupt section changes are a classic problem in the study of flow in cylindrical ducts or pipes. For its analysis, there are a wide set of exiting data from previous studies, among which some authors stand out and will be mentioned. Those previous works have been used to obtain reliable results for the resolution of section changes along a pipe, either due to cross area increases or reductions on a 1D basis. It is also known that a numerical 2D axisymmetric simulation (CFD) could find a consistent result compared to experimental data in almost all fluid flow fields. The main novelty of the present study is the development of a simple numerical approach used to solve the minor loss calculation. Firstly, a theoretical analysis is developed, and then the results of the numerical simulations carried out on the behavior that affects the water and air flow rate in an abrupt section change, for both contraction and expansion problems, are presented. In both cases, the results are analyzed with different meshes (discretizations) and turbulence models. Finally, the obtained numerical results are compared with those in the technical literature. Also, a theoretical approach is shown in order to show a whole frame of the discussion. The core results are the loss coefficient evolution as a function of the section change both for the sudden contraction and the expansion of a pipe flow. As the results follow the existing experimental values, it is concluded that the developed model provides a feasible and quick design tool to analyze possible geometrical changes without the need for further experiments.

Numerical simulation of aluminum-steel clad strip production using horizontal single belt casting process

A 3-D steady-state turbulent flow and solidification model was developed to simulate melt flow in a Horizontal Single Belt Caster for the production of an Al-Steel composite strip. The steel substrate is attached to the moving belt and moves at the same speed as the belt while the aluminum melt is introduced onto the substrate via an extended nozzle melt delivery system. A finite volume method was used to numerically solve the governing equations. In order to model the turbulent flow, a low Reynolds k − ε turbulent model was adopted. The developed numerical model was further employed to investigate the effect of such parameters as clad thickness, casting speed, molten aluminum superheat, and heat extraction rate from the belt surface on fluid flow and temperature fields in the system. It was found that for a certain clad thickness, casting speed and cooling rate should be adjusted properly and outlet strip temperature is independent of Inlet melt superheat.

Mapping electro-vortex flow patterns from tornado to inverted tornado in a hemispherical container

This study aims to investigate the intricate interaction between fluid flow and magnetic fields, known as magnetohydrodynamic (MHD) phenomena, within a hemispherical container filled with conducting gallium–indium–tin (Ga-In-Sn) liquid. The primary objective is to explain the influence of the external magnetic field and electric current intensities on the flow structure. Novel insights into the emergence of Lorentz forces that drive the flow dynamics are pursued by varying these parameters. The motivation for this investigation is rooted in the desire to deepen our understanding and uncover new insights into magnetohydrodynamic (MHD) phenomena within a specific experimental setup. Specifically, we aim to understand how swirl velocity is generated and altered by fluctuations in magnetic field strength and electric current intensity within the system. Our investigation reveals a transformation in the flow pattern in a hemispherical pool as the magnetic field strength increases while maintaining a constant electric current intensity. Sequential transformations from a rope tornado to a tornado, cyclone, and finally an inverted tornado are observed, shedding light on the complex behavior of the system. On the other hand, under fixed external magnetic field conditions, it is observed that, as the electric current intensifies, the flow pattern evolves from a tornado to a rope tornado or from a cyclone to a tornado. Furthermore, once the electric current intensity exceeds a specific threshold, the flow pattern remains unchanged, providing valuable insights for process optimization and control. This study contributes to a deeper understanding of MHD phenomena and offers practical implications for optimizing processes such as electroslag remelting (ESR) and vacuum arc remelting (VAR) that involve a similar hemispherical pool of conductive liquid. The simulation results are validated against experimental measurements, ensuring the reliability and accuracy of our findings.

Numerical simulation of free-surface evolution in laser polishing of 100 Cr6 bearing steel

Abstract This research focuses on the laser surface polishing process of 100 Cr6, employing a moving Gaussian heat source. It establishes a two-dimensional transient model for laser polishing, taking into account the integrated effects of fluid flow and temperature fields, as well as the combined influence of capillary and thermocapillary forces. The model was used to perform numerical simulations to study the evolution of surface morphology during the laser polishing process. The investigation specifically examines how laser power and scanning speed influence the quality of the polishing outcome. The results demonstrate that an optimal surface roughness of approximately 0.571 μm is attained at a laser power setting of 200 W and a scanning speed of 300 mm/s.

Numerical Simulation of the Transport of Gas Species in the PVT Growth of Single‐Crystal SiC

AbstractSingle‐crystal silicon carbide (SiC) is an important semiconductor material for the fabrication of power and radio frequency (RF) devices. The major technique for growing single‐crystal SiC is the so‐called physical vapor transport (PVT) method, in which not only the thermal field but also the fluid‐flow field and the distribution of gas species can be hardly measured directly. In this study, a multi‐component flow model is proposed that includes the inside and outside of a growth chamber and a joint between the seed crystal holder and crucible which allows exchanges of the gas species. The joint is simulated as a thin porous graphite sheet. The Hertz‐Knudsen equation is used to describe the sublimation and deposition. The convection and diffusion are described by the Navier–Stokes equations and mixture‐averaged diffusion model, in which the Stefan flow is taken into account. The numerical simulations are conducted by the finite element method (FEM) with a multi‐physics coupled model, which is able to predict the fluid flow field, species distribution field, crystal growth rate, and evolution of the molar concentration of dopant gas. Using this model, the effects of several experimental conditions on the transport of gas species and the growth rate of single‐crystal SiC are analyzed.