Flow Field Properties Research Articles

Exact Solutions to the Oberbeck–Boussinesq Equations for Describing Three-Dimensional Flows of Micropolar Liquids

The article proposes several classes of exact solutions to the Oberbeck–Boussinesq equations to describe convective flows of micropolar fluids. The possibility of using families of exact solutions for convective flows of classical incompressible fluids to micropolar incompressible fluids is discussed. It is shown that the three-dimensional Oberbeck–Boussinesq equation for describing steady and unsteady flows of micropolar fluids satisfies the class of Lin–Sidorov–Aristov exact solutions. The Lin–Sidorov–Aristov ansatz is characterized by a velocity field with a linear dependence on two spatial coordinates. These coordinates are called horizontal or longitudinal. The coefficients of the linear forms of the velocity field depend on the third coordinate (vertical or transverse) and time. The pressure field and the temperature field are described using quadratic forms. Generalizations of the Ostroumov–Birikh class are considered a special case of the Lin–Sidorov–Aristov family for describing unidirectional flows and homogeneous shear flows. An overdetermined system of Oberbeck–Boussinesq equations is investigated for describing non-homogeneous shear flows of non-trivial complex topology in 3D metric space. A compatibility condition is obtained in the Lin–Sidorov–Aristov class. Finally, a class of exact solutions with a vector velocity field that is nonlinear in part of the coordinates is presented in our analysis; such partially invariant solutions correspond to theoretical findings regarding symmetric/asymmetric properties of flow fields in solutions topology in a part of the existence appropriate for symmetry for the obtained invariant solutions.

Relationship between Hydrophilicity of Cathode Porous Flow Field and Current Efficiency for Toluene Direct Electro-Hydrogenation Cells

Introduction Organic chemical hydrides have been attracted as an energy carrier for mass storage and transportation of renewable energy. In particular, a toluene (TOL) / methylcyclohexane (MCH) system has advantages in terms of using conventional petroleum infrastructure and relatively low toxic properties. A TOL direct electro-hydrogenation cell has a cathode catalyst layer and electrolyte which are similar to proton exchange membrane fuel cells. Anode reaction is oxygen evolution. An issue of the cell is the electro-osmosis of water through the electrolyte membrane to the cathode catalyst layer. It inhibits the diffusion of TOL into the catalyst layer and promotes H2 evolution as a side reaction.1 Therefore, it is important for a cathode porous flow field that not only the flow of TOL and MCH but also the enhancement of water and H2 discharge. In this study, we focused on the hydrophilicity of the cathode porous flow field and investigated the relationship between current efficiency and hydrophilicity of the porous flow field. Experiments Nafion115® (DuPont Inc.) was used as the electrolyte membrane. A DSE® for oxygen evolution (De Nora Permelec Ltd.) was used as an anode and 1 mol dm-3 H2SO4 was circulated as anolyte at 10 ml min-1. As a cathode, 1 mg-PtRu cm-2 of PtRu/C (TEC61E54, TKK) with 0.8 of ionomer/carbon weight ratio, was coated on the membrane. 10 vol. %TOL - MCH was circulated at 10 ml min-1. As the cathode porous flow field, carbon papers with various contact angles and thicknesses were used as shown in Table 1. The substrates were named "c"-contact angle-(thickness). Here, the C0(660), C0(320), and C145(280) had the same pore structure with various wettability and thickness. The C138MPL(280) is a commercially available carbon diffusion layer (39BB, SGL carbon Ltd.), which had a contact angle of 138° on both with and without a microporous layer (MPL). The internal resistance was measured by the high-frequency intercept of the Nyquist plot of impedance measurements after 3 minutes of constant current electrolysis. IR-free cell voltage was determined by subtraction of multiplied by the resistance and the current value from the measured cell voltage. Current efficiency was calculated with Faraday's law from the volume ratio of TOL/MCH solution to H2 gas after 3 minutes of constant current electrolysis. Results and discussion Figure 1 shows the dependence of cell voltages (open plots) and current efficiencies (close plots) on current density for TOL direct electro-hydrogenation cells with various cathode porous carbon flow fields. There were no significant differences in cell voltages for the cells. On the other hand, current efficiencies were significantly affected by the property of the porous carbon flow field. The C0(320), which was hydrophilic, had the highest current efficiency. Following the C0(320), the C69(220) and the C145(280) were high in this order. So, the more hydrophilic carbon papers showed the higher current efficiency. This implies that the use of a hydrophilic porous flow field promotes water removal in the cathode catalyst layer. As the effect of thickness in the same contact angle, the thinner cathode porous flow field of the C0(320) was higher than thicker that of the C0(660). This implies that a thin flow field would enhance TOL supply, and this means the flow velocity in line also affects current efficiency. C138MPL(280) was the lowest current efficiency. This may be due to the pore size of the MPL on the porous flow field in contact with the catalyst layer. The pores in the porous carbon flow field between the fibers and the MPL were fine nanocarbon particles with Teflon bonding; therefore, the pore size and the porosity of MPL are much smaller than those of the flow field. Then The lowest current efficiency of the C138MPL(280) would be affected by slow transport of TOL supply with slow discharge of MCH and water.In conclusion, it was suggested that the use of hydrophilic, thin, and large pore size cathode porous flow field facilitated the mass transportation of TOL into the catalyst layer and the emission of water and MCH from the catalyst layer and suppressed side reactions. References (1) Kensaku Nagasawa, Yuki Sawaguchi, Akihiro Kato, Yoshinori Nishiki and Shigenori Mitsushima, Electrocatalysis, 8, 164-169 (2017). Figure 1

Non-Pillar Coal Mining by Driving Roadway During Mining Period in High-Gas Top-Coal-Caving Working Face

To solve the problem of the inability to achieve Y-shaped ventilation in the boundary coal mining of high-gas mines and the problem of gas accumulation in the upper corner of a fully mechanized mining face, non-pillar coal mining technology is proposed by a driving roadway during the mining period. A high-gas working face requires Y-shaped ventilation to achieve upper corner gas control, but Y-shaped ventilation conditions are not available at the boundary coal body. In order to handle this challenge, studies have suggested non-pillar coal mining technology, which involves excavating roadways while mining in order to achieve non-pillar coal extraction and use recoverable wide coal pillars. During the simultaneous excavation of a working face and roadway, studies analyzed the distribution characteristics of the complicated stress environment. Following an evaluation of the impact of coal pillar width on the quality of an excavation roadway, this study’s development is in terms of an effective technique for retaining coal pillars as established. During the mining period of a working face, in the goaf of the working face, the research analyzed the distribution properties of the gas flow field, and findings from the study indicate that the width of the recovered coal pillar influences the distribution of gas. Finally, the width of the coal pillar was comprehensively determined, forming non-pillar coal mining technology by a driving roadway during the mining period. The on-site practice has shown that using a wide coal pillar with a width of 70 m to protect the roadway significantly reduces the deformation of the surrounding rock in the mining roadway, the gas concentration at the return airway is lower than the safety production standard, and by decreasing the mining succession time by 15 months, studies achieved improving the working face’s coal extraction rate by 12.6%.

Study on the flame structure and flow field of hydrogen-enriched combustion in array micro-tube

Addressing climate change and reducing greenhouse gas emissions are critical priorities. Utilizing hydrogen-rich methane or pure hydrogen as fuels within gas turbines, facilitated by array micro-tube premixed combustion technology, is anticipated to markedly accelerate the decarbonization process of the energy sector. In this study, the flame structure of the array micro-tube premixed burner under various fuel compositions was examined using OH-Planar Laser-Induced Fluorescence and Particle Image Velocimetry measurement techniques. The effects of the equivalence ratio (φ) and the hydrogen power ratio (HPR) on the characteristics of the flame front, including its curvature, density, volume, and the associated flow field properties, were discussed. As φ and HPR increase, the wrinkled structure of the flame front is significantly enhanced, with a more pronounced effect on smaller scales. This enhancement leads to the separation of the unburned pockets from the main flame. Concurrently, both the flame length and the flame area decrease with the augmentation of φ and HPR, indicating a more concentrated combustion process and increased combustion intensity under hydrogen-enriched and pure hydrogen conditions. The study also observed a slight increase in both the negative and positive curvatures of the flame front, with a more notable increase in the negative curvature. The increased negative curvature results in an elevated degree of wrinkling and a higher value of Σ (flame surface density), reaching a maximum of 0.876 mm−1 under the conditions where φ is 0.8 and ⟨c⟩ (mean progress variable) is 0.5, resulting in the smallest observed flame volume of 100.6 mm3. Upon coupling the flame with the flow field, it was discovered that the exit flow field of the array micro-tube exhibits symmetry and a characteristic conical flame shape. The burning velocity of the side flame brushes increases, and the velocity peak shifts upstream. The aforementioned findings confirm that the addition of hydrogen increases the laminar flame velocity, enabling the flame to stably anchor to the microtube outlet and thereby enhance the flame's robustness and stability.

Experimental and simulation study of flow field characteristics of a disturbing rotary centrifugal air classifier

In the present study, a new disturbing rotary centrifugal classifier was designed and a method was proposed to characterize its pressure signals. The models for evaluating the classification effects were established based on multi-zones. It was found that the flow field, processing parameters, and material properties significantly affected on the particle force and classification performance. The pressure with high amplitude and energy analyzed using Hilbert-Huang Transform (HHT) concentrated within 200–400 Hz, and the screening cage facilitated energy transfer to lower frequency bands. Correlation analysis demonstrated the correlation coefficients (A5 and A6) between adjacent measurement points increased with frequency, further enhanced by the screening cage. The flow field of simulation was characterized by a low-pressure, high-velocity gradient at the center and a high-pressure, low-velocity gradient at the sidewalls and the gas velocity and flow for experiment achieved the maximum at z = 0.50 m, while the magnitude of pressure change was significant at the inlet end and discharge end, where the velocity gradient and pressure drop had the same trend and small errors for experiments and simulation. The flow field affected the competing relationship between centrifugal and drag forces on the particles with different kinematic behavior during the classification process. The errors between the predicted values of the theoretical, simulated, and experimental cut particle size models and the true values were all within 10 %, based on which the multi-zone classification efficiency model applicable to the disturbing centrifugal classifier was established, and it was found that the models all had high prediction accuracy and suitability. The article delves into the correlation between pressure signals, flow field characteristics and particle behavior, aiming to provide an important reference for the internal flow field and classification performance of air classifiers.

Numerical investigation of heat transfer performance and flows characteristics in turbine blade internal cooling using Pin-Fin arrays coupled with discontinuous ribbed endwall

In the scientific domain of cooling techniques research utilizing pin-fins, a number of studies have concentrated on the configurations of pin-fins. However, recent investigations have shifted their focus towards the optimization of endwalls. The objective of this optimization is to better control and maintain vortices, which in turn leads to an increase in heat transfer near the endwall. Further research has taken this a step further by optimizing the lower and upper walls of the unadorned heated channel, resulting in a significant boost in heat transfer efficiency. These studies have also led to the discovery of new heat transfer properties and alterations in the flow structure. This research unveils the findings from an examination into the flow field and heat transfer properties of pin–fin arrays featuring a ribbed endwall, specifically referred to as a Discontinuous Ribbed Endwall (DRE). The investigations are executed using Reynolds-Averaged Navier-Stokes (RANS) equations with the k-ω turbulence model at the mesh parameter of the 20.4 million mesh model is used throughout the work. The study involves a numerical investigation of the heat transfer and pressure drop characteristics of the channel, comparing them with the case of flat endwall across a range of inlet Reynolds numbers, spanning from 7400 to 36000. The entire section of the heated channel is divided into 7 upper surfaces, 7 lower surfaces, and cylindrical surfaces to comprehensively investigate the heat transfer characteristics of both pin-fins and endwalls. The results reveal that the heat transfer regions at the pin-fins and endwalls are expanded and significantly enhanced, particularly causing notable alterations in the flow structure and velocity field. However, the coefficient of friction also increases. The Area-averaged Nusselt Number (Nu¯) and the Heat Transfer Efficiency Index (HTEI) improves from 42.99% to 88.65% and from 36.81% to 73.66% for the DRE compared to the case of flat endwall across the entire range of Reynolds numbers. With Reynolds number 21500, when varying the height parameter of the DRE, the maximum value of the HTEI improves by 84.13%. Other geometric parameters of the DRE, including forward width, behind width, left width, streamwise position, and left position, also undergo changes, with the maximum values of HTEI improving by 73.76%, 75.35%, 80.60%, 75.41% and 74.16%, respectively.

A thermochemical nonequilibrium model of CO2 plasma for studying flow-field properties of the spacecraft Mars Pathfinder

A thermochemical nonequilibrium model of CO2 plasma for studying flow-field properties of the spacecraft Mars Pathfinder

Novel design of multi-point injection system for laboratory simulation of Martian low-pressure dust devils

The Martian surface is frequently traversed by dust devils, presenting formidable challenges to exploration missions and posing significant safety risks. Establishing a ground-based simulation device for low-pressure Martian dust devils is essential for conducting reliability testing and research on extreme environments relevant to Mars rovers. This study introduces a Martian dust devil simulator comprising a simulation cabin and multi-point injectors. This apparatus facilitates the investigation of velocity and pressure distribution patterns within the flow field under varying operational conditions by adjusting injector positions, inlet pressure, and internal pressure. The simulator's design allows it to replicate Martian dust devil velocity fluctuations from 0 to 50 m/s and pressure variations spanning 100–1500 Pa, thereby meeting crucial criteria for simulating Martian atmospheric conditions. Through computational fluid dynamics (CFD) simulation, we analyzed the characteristics of dust devils generated by the simulation device and scrutinized the flow field properties following the coupling of sand-dust particles with airflow. The observed dust devil flow field closely resembles the Vastitas Borealis vortex. Additionally, experimental research was conducted. Comparing experimental, simulated, and theoretical models revealed a high degree of consistency in the internal flow field characteristics of the simulated dust devils. The apparatus's versatility extends to simulating various dust devil morphologies, offering significant potential for conducting model experiments pertinent to Martian probes and facilitating future crewed Mars exploration endeavors.

Investigation of dynamic characteristics of hydrofoil with leading-edge tubercles

The convex structure of a humpback whale flipper is included in the airfoil design to investigate the control principle of the dynamic stall process. The effect of two different types of tubercles on the dynamic stall process of airfoils was investigated. The distribution of dynamic hysteresis loops and pressure fields with streamlines was used to explain the properties of the dynamic flow field and the emergence of dynamic stall vortices. The results demonstrate that the airfoils with tubercles have stronger hysteretic characteristics in the pre-stall region, and the ζ CM of mod-1 is increased by 51.33%, indicating stronger torsional hydroelastic stability. In the post-stall region, mod-2 is always in a condition of significant flow separation, which impairs the torsional hydrodynamic stability of the airfoil and has the potential to cause flutter. These findings suggest that leading-edge tubercles offer a negligible advantage in reducing airfoil dynamic stall, and their significance warrants further investigation.

Calculations of flow field and heat exchange properties in high-power high-enthalpy inductively coupled plasma generator

Calculations of flow field and heat exchange properties in high-power high-enthalpy inductively coupled plasma generator

Particle-resolved hyperspectral pyrometry of metal particles

We present temperature histories of individual combusting metal particles using hyperspectral pyrometry. This method gives an increase in accuracy over traditionally used two- or three-color pyrometry, while maintaining temporal and spatial resolution. Temperatures can be determined between 1800 to >3000 K with a precision of typically <1%. It is shown that the maximum temperature of the burning iron particles increases from 2760 K to 2840 K with an increasing mean particle size from 32 to 54 μm in air with 21 % oxygen. The relatively high temperatures and its dependence on particle size are possibly related to flow field properties of the current experimental setup. Opportunities for this method, as well as future work, are discussed.Novelty and Significance Statement: In this article, a method to use a CCD camera and spectrograph as a hyperspectral detector, gaining a wavelength dimension while maintaining two spatial dimensions, is demonstrated and validated. This method is applied to measure the temperature of iron particles, a carbon free and circular energy carrier. This method is then used to prove that there is a particle size dependence on the maximum temperature, an open question which is often disputed in literature. This work will also add a dataset that can be used for the validation of numerical models. There are only two such datasets available for iron at this moment. Our analysis suggests that the heat release of iron is dependent on the slip velocity, possibly due to a circulating flow inside of the particle.

Identification of control equations using low-dimensional flow representations of pitching airfoil

This study investigates the application of data-driven modeling techniques for understanding the complex dynamics of pitching airfoils at low Reynolds numbers and high angles of attack. Linear and nonlinear dimensionality reduction methods, namely principal component analysis (PCA) and isometric mapping (ISOMAP), are employed to obtain low-dimensional representations of the flow field. Subsequently, sparse identification of nonlinear dynamics (SINDy) is utilized to model the governing equations. The key findings are as follows: PCA primarily captures linear information, with the first two to three dimensions maintaining relatively low reconstruction errors. In contrast, ISOMAP excels in capturing nonlinear features, exhibiting noticeably smaller reconstruction errors. The main information is concentrated in the two-dimensional plane constructed by PCA1 and PCA2 (or ISOMAP1 and ISOMAP2). Differences in trajectory planes formed by combinations of other axes reflect flow field disparities. ISOMAP provides a nonlinear low-dimensional representation, advantageous for capturing nonlinear relationships between flow field characteristics and governing equations. The combination of ISOMAP and SINDy yields virtually no errors in identifying governing equations. Conversely, PCA and SINDy result in significantly different linear trajectories, leading to higher reconstruction errors. The identified governing equations using ISOMAP and SINDy remain consistent across different datasets, demonstrating the method's stability and robustness in accurately characterizing flow field properties under similar conditions.

A hybrid Gaussian mixture/DSMC approach to study the Fourier thermal problem

In rarefied gas dynamics scattering kernels deserve special attention since they contain all the essential information about the effects of physical and chemical properties of the gas–solid surface interface on the gas scattering process. However, to study the impact of the gas–surface interactions on the large-scale behavior of fluid flows, these scattering kernels need to be integrated in larger-scale models like Direct Simulation Monte Carlo (DSMC). In this work, the Gaussian mixture (GM) model, an unsupervised machine learning approach, is utilized to establish a scattering kernel for monoatomic (Ar) and diatomic (H2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\hbox {H}_{2}$$\\end{document}) gases directly from Molecular Dynamics (MD) simulations data. The GM scattering kernel is coupled to a pure DSMC solver to study isothermal and non-isothermal rarefied gas flows in a system with two parallel walls. To fully examine the coupling mechanism between the GM scattering kernel and the DSMC approach, a one-to-one correspondence between MD and DSMC particles is considered here. Benchmarked by MD results, the performance of the GM-DSMC is assessed against the Cercignani–Lampis–Lord (CLL) kernel incorporated into DSMC simulation (CLL-DSMC). The comparison of various physical and stochastic parameters shows the better performance of the GM-DSMC approach. Especially for the diatomic system, the GM-DSMC outperforms the CLL-DSMC approach. The fundamental superiority of the GM-DSMC approach confirms its potential as a multi-scale simulation approach for accurately measuring flow field properties in systems with highly nonequilibrium conditions.

The comparative transient prediction on hydrodynamic characteristics and flow field properties of pump-jets with accelerating and decelerating ducts

Pump-jet holds a pivotal position in various marine applications, underscoring the need for comprehending their transient behavior for the purpose of design enhancement and performance refinement. This paper employs Reynolds-averaged Navier–Stokes equations method in conjunction with Detached Eddy Simulation model. The study delves into the ramifications of accelerating and decelerating ducts, distinguished by camber f and attack angles α, on transient hydrodynamic characteristics. The hydrodynamic characteristics are investigated numerically, after the validation of the numerical methodology by comparing simulation outcomes against experimental results. Subsequently, the study delves into propulsion characteristics, followed by an exploration of time-domain and frequency-domain data transformed through fast Fourier transform to analyze thrust fluctuations and pulsating pressures. Additionally, a detailed examination of pressure distribution and velocity field is provided, aiming to dissect the mechanisms through the variations in f and α influence the flow field. Findings suggest that the outlet velocity of accelerating ducts significantly surpasses the inlet velocity, a behavior contrasted by decelerating ducts. Notably, the patterns of accelerating and decelerating ducts resulting from alterations in f exhibit consistent characteristics with those brought about by changes in α. However, several opposite characteristics surface in transient flow field due to the distinct modifications in the duct profile. Furthermore, by considering vorticity magnitude distribution and vortices, a comparative analysis elucidates the effects of varying f and α on rotor and stator trailing vortices. This contributes to understanding the flow instability mechanism under differing duct configurations. It is evident that changes in f and α exert significant influence on both performance and flow field.

Liquid evaporation from nanochannel in the presence of non-condensable gas by direct simulation Monte Carlo

Liquid-vapor phase change in the form of evaporation and with the confinement of nanostructures is of vast importance in many engineering applications. The direct simulation Monte Carlo (DSMC) approach was employed to simulate the liquid evaporation from two-dimensional nanochannels in the presence of non-condensable (NC) gases. The thermodynamic properties of vapor and NC gas flow fields as well as the evaporation rate of liquid were calculated. Factors such as channel opening ratio, meniscus receding depth and the NC gas density were examined to reveal their impacts on the liquid evaporation rates. The results showed that the gas mixture flow field transforms to one-dimensional away from the channel exit. The overall vapor pressure drop can be divided into that across the liquid–vapor interface, that within the channel, outside the channel, as well as that caused by the binary diffusion. The effect of NC gas on the evaporation rate was found to be the most outstanding with pinned meniscus and with a wide channel opening, in which case the normalized evaporation rate drops to 0.43. Moreover, the Maxwell-Stefan equation could capture the evaporation data with modified diffusion lengths. For receded meniscus (250 nm deep) and small opening ratio (0.417), the effective diffusion length was as large as 1.6 times that in the one-dimensional case.

Aerodynamic design of a high-efficiency two-stage axial turbine, using streamline curvature method and performance optimisation by clocking of stator blades

Abstract Aerodynamic design of a high-efficiency two-stage axial turbine is carried out using a hybrid method through implantation of a two-step design procedure. In the first step, the well-known streamline curvature (SLC) and free vortex (FV) methods are properly combined to establish three-dimensional geometries of the blades at each row and to obtain the flow field properties. The second step is provided to obtain the highest aerodynamic efficiency by optimum clocking of the second stator blades relative to the first ones through executing steady and unsteady computational fluid dynamics (CFD) of three-dimensional viscous flow. Slight discrepancies were observed between gas dynamics results of the SLC and those of CFD. Total pressure and temperature at the turbine outlet, obtained from SLC method, differed from those obtained by 3D-CFD technique by 13.06% and 1.88% respectively. Aerodynamic efficiency of the turbine is obtained about 91.83%, based on 3D-CFD. Time-averaged results showed that under the optimum clocking of the second row stator blades, inlet total pressure and output power of the second rotor increase by 0.23%, and 0.93%, respectively, in comparison to the worst clocking case. These augmentations resulted in increased total to total efficiency of the second stage by 0.444%. Additionally, the total output power of the two stages increased by 0.71% through the optimum clocking. Modeling the unsteady wake flow trajectory within the blades passages confirmed that all of these beneficial effects happen if the upstream wake impinges on the leading edge region of the second stator blades.

Levenberg–Marquardt backpropagation neural networking (LMB-NN) analysis of hydrodynamic forces in fluid flow over multiple cylinders

The mathematical formulation of the flowing liquid stream around and through confined multiply connected domains brings a complex differential system. Due to this, one cannot provide a complete description of flow field properties. The current pagination provides a numerical remedy by the use of artificial intelligence in this direction. To be more precise, fluid is considered in the rectangular channel. The circular, square, and triangular-shaped cylinders are positioned as an obstacle to the continuous fluid. The channel’s left wall is viewed as an inlet and two different velocity profiles are introduced at an inlet that are constant and parabolic profile. To discretize the computational domain, hybrid meshing is used. The variance in basic variables, namely, the velocity of the liquid and the distribution of the liquid pressure, is recorded via graphs. The nine different meshed grades are tested for the drag and lift coefficients around the right-angle triangle, square, and circular barrier. The neural networking model is constructed by using 99 datasets of sample values for drag coefficient when characteristic length, the density of fluid, the dynamic viscosity of the fluid, and mean flow velocity are taken as inputs. The training of the neural network takes up 69 slots (about 70%), while the testing and validation of the neural network each take up 15 slots (15%). The Levenberg–Marquardt backpropagation algorithm is used for training. We have observed that for the parabolic profile, the drag coefficient is higher in intensity for each obstacle compared to the constant profile, while the lift coefficient shows opposite patterns.

Numerical study on hydrodynamic behaviors of and flow field around UHMWPE plane nets

The hydrodynamic behaviors of and flow field around the net made by ultra-high molecular weight polyethylene (UHMWPE) were seldom investigated previously. Therefore, a three-dimensional numerical model for the UHMWPE plane net is established herein based on the porous media model, and the unknown Darcy-Forchheimer coefficients are attained by fitting the experimental data of physical model with the minimum error function method. Then, the flow field characteristics around the UHMWPE plane net are investigated and it is noted that the flow velocity reduction along the horizontal centerline of net decreases with the increase in velocity, while larger attack angle and solidity both result in a larger flow velocity reduction. And, the effects of nets spacing and number on the velocity distribution and flow field properties in and around multi-layer nets are revealed. Finally, the empirical formulas for calculating the drag and lift coefficients of the UHMWPE plane net are proposed by considering as the function of solidity, Reynolds number and attack angle.

NUMERICAL SIMULATION OF THE RISE OF TWO PARALLEL UNEQUAL BUBBLES IN A VISCOELASTIC FLUID

The interaction of two parallel unequal bubbles in a viscoelastic fluid is investigated numerically using OpenFoam, the volume of fluid method (VOF) combined with a surface tension model to trace the gas-liquid interface, and the Giesekus model to characterise the rheological properties of the fluid. The numerical results are in good agreement with experimental results from the literature. The effects of bubble diameter, initial spacing between bubbles and rheological properties of the fluid on the rise, and separation and convergence of the two bubbles are investigated. The flow field properties and viscoelastic stress distribution around the bubbles are explored. As the bubble spacing increases, the maximum and terminal velocities of the two bubbles increase, and the relative positions of the bubbles change when they come into contact. As the relaxation time &amp;lambda; increases, the contact time of the bubbles decreases, and the small bubbles tend to have an inverted teardrop shape and the large bubbles have less deformation and no sharp tail. The relaxation time directly affects the accumulation of viscoelastic stress, leading to changes in the velocity of the bubbles at contact, and their maximum and terminal velocities increase. Bubbles in highly elastic fluids are more prone to negative wake phenomena.

A Data-Driven Machine Learning Approach for Turbulent Flow Field Prediction Based on Direct Computational Fluid Dynamics Database

A novel approach is presented for predicting compressible turbulent flow fields using a neural network-based data-driven method. Accurate prediction in turbulent regions heavily relies on the resolution of available data. Traditional methods, employing image-based techniques by mapping scattered computational fluid dynamics (CFD) data onto Cartesian grids, encounter data scarcity in critical areas such as the boundary layer and wake. Recently, convolutional neural networks (CNN) have gained prominence as the most widely referenced technique in fluid dynamics, utilizing flow field images as datasets for flow field prediction. However, CNN requires datasets with a high pixel density to enhance training accuracy in crucial regions, thereby increasing the input data volume and machine training time. To address this challenge, our proposed method deviates from using flow field images and instead generates datasets directly from the flow field properties of CFD grid points. By employing this approach, several advantages are realized. Firstly, the network benefits from the favorable characteristics of unstructured grids, such as varying point spacing near the object surface and in the far field, which effectively reduces the amount of input data and consequently the machine training cost. Secondly, the construction of the training dataset eliminates the need for interpolation or extrapolation, thereby preserving the accuracy of CFD data. In this case, a simple multilayer perceptron can be trained using the proposed dataset. Various flow field properties, including static pressure, turbulent kinetic energy, and velocity components, can be predicted with high accuracy within a few seconds.