Fluid Flow Characteristics Research Articles

Fluid-solid coupling numerical simulation of the effects of different doses of verapamil on cancellous bone in type 2 diabetic rats

BackgroundThe purpose of this study was to investigate the effects of four different doses of verapamil on the mechanical behaviors of solid and the characteristics of fluid flow in cancellous bone of distal femur of type 2 diabetes rats under dynamic external load.MethodsBased on the micro-CT images, the finite element models of cancellous bones and fluids at distal femurs of rats in control group, diabetes group, treatment groups VER 4, VER 12, VER 24, and VER 48 (verapamil doses of 4, 12, 24, and 48 mg/kg/day, respectively) were constructed. A sinusoidal time-varying displacement load with an amplitude of 0.8 μm and a period of 1s was applied to the upper surface of the solid region. Then, fluid-solid coupling numerical simulation method was used to analyze the magnitudes and distributions of von Mises stress, flow velocity, and fluid shear stress of cancellous bone models in each group.ResultsThe results for mean values of von Mises stress, flow velocity and FSS (t = 0.25s) were as follows: their values in control group were lower than those in diabetes group; the three parameters varied with the dose of verapamil; in the four treatment groups, the values of VER 48 group were the lowest, they were the closest to control group, and they were smaller than diabetes group. Among the four treatment groups, VER 48 group had the highest proportion of the nodes with FSS = 1-3 Pa on the surface of cancellous bone, and more areas in VER 48 group were subjected to fluid shear stress of 1-3 Pa for more than half of the time.ConclusionIt could be seen that among the four treatment groups, osteoblasts on the cancellous bone surface in the highest dose group (VER 48 group) were more easily activated by mechanical loading, and the treatment effect was the best. This study might help in understanding the mechanism of verapamil’s effect on the bone of type 2 diabetes mellitus, and provide theoretical guidance for the selection of verapamil dose in the clinical treatment of type 2 diabetes mellitus.

A computational study of the impact of fluid flow characteristics on convective heat transfer with Hall current using the MHD non-Newtonian fluid model

The study focuses on the flow characteristics with geometrical considerations utilizing electrical-conduct Non-Newtonian Fluid. The tubular concentric annulus is the geometry selected for the investigation. The electric-conductive Non-Newtonian Fluid is a character-wise two-constant Bingham model used in this study. The study also utilized geometry, the magnetohydrodynamic (MHD) effect, and the hall current. The employed system had the inner tube spinning and the outer tube stationary. Prandtl's assumptions of boundary layer principles are applied to solve the governing equations using the finite difference method for various fluid flow parameters, the Gauss-Elimination method to compute the results, and the MHD field and geometrical factors with hall current. This paper discusses fluid flow properties such as axial, radial, tangential velocities, and pressure distribution. Further, the mentioned above flow properties impact the heat transfer effect. This research details how flow parameters in the concentric tube flow process affect the development of heat transfer effects in the MHD field and hall current.

Heat transfer and fluid flow characteristics over a backward-facing step (BFS) containing square-rectangular ribs integrated as forward-facing steps (FFS)

Heat transfer and fluid flow characteristics over a backward-facing step (BFS) containing square-rectangular ribs integrated as forward-facing steps (FFS)

Numerical study of gas invasion law in fractured reservoirs

Gas invasion during the drilling process in fractured reservoirs poses challenges, affecting drilling efficiency and increasing costs. Therefore, it is crucial to effectively and accurately describe the flow characteristics of subsurface fluids. Addressing the issue of gas invasion in fractured reservoirs, this study considers the influence of matrix deformation and fracture aperture variation on fluid flow and establishes a mathematical model for coupled flow and solid deformation in fractured reservoirs. The numerical formulation of the mathematical model is derived using the finite element method. To better represent real reservoir conditions, discrete fractures are created using MATLAB, and numerical solutions are obtained using the commercial software COMSOL Multiphysics. The accuracy of the model is verified through a comparison between numerical and analytical solutions. This paper first explores the characteristics of fluid flow within a single fracture and rock deformation when encountering a fracture during drilling. It then compares the predictive capability of the coupled model with that of the uncoupled model in estimating gas invasion. Finally, the primary factors influencing gas invasion in fractured reservoirs are analyzed from the perspectives of rock matrix, fractures, and drilling operations.

Phase-field-based finite element model for two-phase ferrofluid flows

In this study, we propose a phase-field-based finite element model to simulate two-phase ferrofluid flows in two and three dimensions. The proposed model combines the Cahn–Hilliard equation to handle the phase field, the Poisson equation to account for magnetics, and the Navier–Stokes equation to characterize fluid flow. To efficiently handle this coupling, we present a linear, totally decoupled numerical scheme, which involves solving four separate equations independently, namely, a linear elliptic system for the phase function, a Poisson equation for the magnetic potential, a linear elliptic equation for the velocity, and a Poisson equation for the pressure. To assess the accuracy, applicability, and numerical stability of the model, we conduct simulations for several typical problems. These include investigating the deformation of a ferrofluid droplet under a two-dimensional uniform magnetic field model, the bubble coalescence in ferrofluids under a three-dimensional uniform magnetic field model, the collision of two ferrofluid droplets under two-dimensional shear flow, and the two-dimensional interfacial instability of a ferrofluid. The numerical results confirm the model's capability to robustly simulate multiphase flow problems involving high-density and high-viscosity ratios, both in two- and three-dimensional problems. Moreover, the model effectively captures fundamental phenomenological features of two-phase ferrofluid flows under large topological changes such as the Rosensweig instability.

Numerical study of electrically conducting MHD fluids in a vertical channel with Jeffrey fluid flow and first order chemical reaction

This research paper explores the influence of first order chemical reaction on sustainable properties of electrically conducting magnetohydrodynamic (MHD) fluids in a vertical channel with the unique characteristics of Jeffrey fluid flow. The mathematical model of MHD flow with Jeffrey fluid and chemical reaction incorporates the impacts of viscous dissipation, Joule heating and a non-Newtonian fluid model with viscoelastic properties in the flow regions. The governing equations of the flow field were solved using finite difference method and impacts of flow parameters on the flow characteristics are discussed numerically using graphical representation. It’s revealed that increasing Jeffrey parameter results to decline in the velocity field profiles. Also, species concentration field profiles decline with higher values of destruction chemical reaction parameter. The findings of this study have significant implications in various engineering applications, including energy generation, aerospace engineering, and materials processing. Additionally, the inclusion of Jeffrey fluid flow introduces a viscoelastic component, enhancing the complexity of the fluid dynamics.

Machine learning for rapid discovery of laminar flow channel wall modifications that enhance heat transfer

Numerical simulation of fluid flow plays an essential role in modeling many physical phenomena, which enables technological advancements, contributes to sustainable practices, and expands our understanding of various natural and engineered systems. The calculation of heat transfer in fluid flow in simple flat channels is a relatively easy task for various simulation methods. However, once the channel geometry becomes more complex, numerical simulations become a bottleneck in optimizing wall geometries. We present a combination of accurate numerical simulations of arbitrary, flat, and non-flat channels as well as machine learning models trained on simulated data to predict the drag coefficient and Stanton number. We show that convolutional neural networks (CNNs) can accurately predict target properties at a fraction of the computational cost of numerical simulations. We use CNN models in a virtual high-throughput screening approach to explore a large number of possible, randomly generated wall architectures. Data augmentation techniques are incorporated to enforce physical invariances toward shifting and flipping, contributing to precise prediction for fluid flow and heat transfer characteristics. Moreover, we approach the interpretation of the trained model to better understand relevant channel structures and their influence on heat transfer. The general approach is not only applicable to simple flow setups as presented here but can be extended to more complex tasks, such as multiphase or even reactive unit operations in chemical engineering.

Artificial neural networks based computational and experimental evaluation of thermal and drying performance of partially covered PVT solar dryer

This study proposes a mixed-mode dryer with a semi-transparent photovoltaic thermal (PVT) collector for the assessment of drying and thermal performance using computational and experimental findings. The thermal behavior and fluid flow characteristics have been analyzed to optimize the air flow rate in the PVT solar dryer by considering three different inlet velocities of 0.048 m/s (Case 1), 0.096 m/s (Case 2), and 0.144 m/s (Case 3). The temperature distribution is obtained more uniformly for the PVT collector and dryer cabin in Case 2. The results of the investigation show that Case 3 has a positive impact on the PVT solar dryer performance. In numerical and experimental methods, the enhanced thermal efficiency is attained as 30.78% and 29.78% for Case 2, and 33.20% and 31.14% for Case 3, respectively, in comparison to Case 1. Case 3 has improved Reynolds and Nussselt numbers by 3.06 and 2.45 times, respectively compared to Case 1. Experimental results varied by 2.24 to 4.90% from simulated outcomes obtained from CFD. The machine learning approach of ANN has been implemented with different hidden layers network models to choose the best drying conditions by predicting the drying performance parameters.

3D seismic analysis of Cenozoic slope deposits and fluid-flow phenomena along the Nigerian Transform Margin

Abstract 3D seismic data provide new insights on c. 2 km thick Cenozoic post-transform slope sediments and fluid-flow phenomena along the Nigerian Transform Margin. The study documents large-scale mass-transport deposits (MTDs), deep-water channels, sediment waves, and a range of fluid-flow phenomena such as pockmarks, pipes, seabed mound and gas hydrates. They are observed from Pliocene-aged sediments and distributed above structural highs, regional faults, and active and relict deep-water channels in the eastern part of the area, closest to the Niger Delta cone. The fluid-flow features are interpreted to be indicative of an active petroleum system in the deeper subsurface and from fluid migration along planes of deep-seated faults. MTDs are mapped at multiple levels and the volume of failed sediments increased through time within the western part of the study area. The repeated and increased volume of MTDs in the area is attributed to an increased rate of sedimentation through time and slope gradient during the late Cenozoic. The presence of repeated MTDs and fluid-flow phenomena on the Nigerian Transform Margin has implications for installations of offshore facilities as they constitute potential geohazards. The study also documents, for the first time, polygonal fault systems offshore Nigeria.

Numerical simulation on thermohydraulic performance of different types of nanofluids in a corrugated-triangular channel

Nanofluids have garnered significant interest as a potential solution to address overheating challenges across diverse industries. Researchers are actively exploring different types of nanofluids to mitigate these issues. In this study, a numerical analysis was conducted using ANSYS software to examine the fluid flow and heat transfer characteristics of nanofluids (ranging from 0 to 4 volume fractions) in a corrugated wavy channel within the turbulent range. Various nanoparticles, including Al2O3, CuO, SiO2, and ZnO, were employed and dispersed in different base fluids such as ethylene glycol, glycerin, and water. The particle size of the nanoparticles ranged from 20 to 70 nm. The results revealed that SiO2/water-based nanofluids provide better heat transfer than all the water-based nanofluids. The maximum average Nusselt number and pressure drop of 200 and 115 Pa, respectively, were observed for SiO2 nanofluid (volume fraction of 0.04) with a particle size of 20 nm. Highlights Al2O3, CuO, SiO2 and ZnO considered in this work. Corrugated plates with three different corrugated angles of 20° to 60° are tested. Eexperiments are performed for different heat flux in turbulent range. Maximum heat transfer obtained for SiO2/water nanofluid.

Numerical Analysis of Fluid Flow and Heat Transfer Characteristics of Novel Microchannel Heat Sink

Microchannel heat sinks have gained prominence in the field of thermal management, offering compact and efficient solutions for dissipating heat flux from high performance electronic devices. Escalating heat flux in modern electronic devices, such as those found in telecommunication equipment, industrial automation equipment, solar devices, and data centre servers has driven the continuous development of microchannel heat sink to achieve efficient thermal management. The critical challenge in thermal management for these devices is to develop a microchannel that enhances heat transfer performance and minimises pressure drop. Heat transfer and pressure drop are two competing factors that determine the practicability of the design for real world application. Improvement in heat transfer performance usually results in an increase in pressure drop and pumping power. This study addresses the challenges of designing microchannel through comprehensive numerical analysis of fluid flow and heat transfer characteristics of a novel design that combines ribs, secondary channels, and tertiary channels. The numerical results showed that the novel microchannel design achieves a favourable balance between heat transfer and pressure drop, demonstrating its potential to be used in application where high heat transfer and efficiency are paramount. To assess the performance of the microchannels, thermal resistance, a measure of system’s resistance to heat transfer is used. At the same pumping power, thermal resistance in the new design is consistently lower compared to other designs.

Numerical modeling of natural convection heat transfer from radial branching heat sinks for LED cooling applications

Light Emitting Diodes (LEDs) have revolutionized the lighting industry due to their high energy efficiency. However, LEDs require effective thermal management to preserve their lifespan and luminous efficiency. In the current study, the design of a branching radial heat sink is numerically investigated and optimized for cooling LED panels of downlights under natural convection. Branching fins arranged radially on a horizontal circular plate were considered in the current study. The buoyant fluid flow over the heat sinks is observed and characterized using parameters such as fin length, height, inclination angle, and number. The dependency of Nusselt number, heat transfer coefficient and thermal resistance on the design parameters are explained by studying the buoyant fluid flow characteristics over the heat sink. Both heat transfer coefficient and thermal resistance decrease with geometric parameters such as fin length, height, and number. Due to branching, the Nusselt number decreases by 17% at lower fin lengths and by 20% at higher fin lengths, respectively. However, the thermal resistance of the heat sink arrays decreases by around 13% at lower fin lengths and remains constant at higher fin lengths due to branching. A comparative study is performed by plotting a contour map between the cooling performance of a radial branching heat sink and a radial flat plate heat sink using a heat transfer enhancement factor. Branching fins with angles above 25°and fin heights over 19 mm outperform plate-fin heat sinks of the same height and length for fin number n = 20. Finally, a correlation is proposed to predict the average Nusselt number of the fin arrays as a function of the design parameters.

Analysis of mixed convective stagnation point flow of hybrid nanofluid over sheet with variable thermal conductivity and slip Conditions: A Model-Based study

This research looks at the stagnation point flow of MHD Al2O3-Cu/H2O hybrid nanofluid against a permeable, vertically extending surface that uses thermal radiation and how different models of thermal conductivity affect it. This study is unique because it looks at how changes in thermal conductivity, mixed convection, and the slip velocity of hybrid nanofluids affect the stretching surface. It also looks at how changes in temperature, skin-friction coefficient, Nusselt number, and velocity affect convective thermal boundary conditions. With the use of boundary layer approximations, the complicated system of PDEs is simplified. The dimensionality of these PDEs and the boundary conditions they include are eliminated by applying certain modifications. Combining a local non-similarity approach up to the second truncation level with MATLAB's built-in finite difference code (bvp4c), one can obtain the results of the updated model. The research demonstrates and analyzes the impact of different factors on fluid flow and heat transfer characteristics in the studied flow situations. This is done by comparing the computed data with available literature and presenting the findings in graphical form. Tables are generated to present the numerical fluctuations of the drag coefficient and Nusselt number. This study shows how important thermal conductivity is in the mixed convection of hybrid nanofluids and looks into what happens when the thermal conductivity parameter is changed. Significantly, an augmentation in this parameter results in an elevation in the temperature distribution of the hybrid nanofluid while simultaneously reducing the rate of heat transfer across various models. Furthermore, increasing the nanoparticle volume fraction parameter leads to higher temperature and Nusselt number profiles while reducing skin friction. The mixed convection parameter has a notable impact on increasing the friction coefficient on the stretched vertical surface. However, because these elements function as regulating variables, it decreases when the magnetic, mass suction, and velocity slip parameters are present. The results also demonstrate notable discrepancies in the mean Nusselt values generated by various thermal conductivity models. According to the analysis, the Hamilton-Crosser model has the lowest average Nusselt numbers, followed by the Yamada-Ota model and the Xue model, in that order.

Dufour and thermal diffusion effects on time-dependent natural MHD convective transport over an inclined porous plate

In this research article, we examined the influences of thermal diffusion and Dufour on time-dependent free MHD convective transport flow through an inclined permeable plate numerically. The dimensionless ordinary differential equations are found from the dimensional governing non-linear partial differential equations through the use of similarity transformation. The transformed dimensionless ordinary differential equations are resolved by employing the finite difference method in the Shooting technique through MATLAB software. The numerical outcomes have been presented for the impact of several non-dimensional numbers or parameters to explore the fluid flow, and heat and mass transfer features. The fluid velocity diminishes for mounting amounts of the inclined angle. The values of f′(0) go up by about 75 % due to rising values of the inclined angle from 150 to 600. With other previously released research studies, a comparison has been performed. The present research reveals good agreement with the published study.

Numerical investigation on heat transfer characteristics of the viscoelastic fluid flow during wire coating process

Due to the high-quality data required in some major industrial fields, transferring those data seem to be an inevitable task. Wires and fibers used for data transmission are needed coating process to be safe from possible damage. This paper first conducted the mathematical Non-linear differential equations for a pressure-type die on wire coating process. Then it was found that the Least Square Method used to predict the thermal behavior of the operating fluid is reasonably accurate. At the end, some critical values such as permeability, magnetic, and third-grade parameters were changed to evaluate their effects on the fluid behavior. It found the temperature pattern rises around 21% by enhancing magnetic parameters. Moreover, the velocity pattern decreases by enlarging the magnetic field, and the temperature profile increases by rising Brinkman number.

Estimation of pore structure and permeability in tight carbonate reservoir based on machine learning (ML) algorithm using SEM images of Jaisalmer sub-basin, India

Analyzing the pore structure in carbonate reservoirs plays a crucial role in predicting fluid flow characteristics within these formations. The goal of the study was to use machine learning techniques for pore structure analysis and estimation of permeability in carbonate reservoirs. We implemented these algorithms by examining 2D scanning electron microscope (SEM) images of carbonate samples from the Jaisalmer sub-basin captured at various magnifications. In the initial stage of the analysis, various binarization algorithms were applied to determine carbonate sample porosity. Among these algorithms, the MaxEntropy algorithm gave a porosity value closely aligned with those obtained through petrography analysis. We employed the watershed algorithm to find the pore network parameters of carbonate samples at various magnifications. We observed that changes in magnification affected pore network parameters, resulting in a reduction in pore size distribution, throat radius, and grain size. Subsequently, we employed the numerical lattice Boltzmann method (LBM) to estimate the permeability of carbonate samples and compared to values derived from well logs. We employed machine learning (ML) algorithms, specifically Artificial Neural Network (ANN) and Support Vector Machine (SVM), to predict the permeability of carbonate samples. The input features for these models were the pore network parameters, while the LBM permeability values served as the output. We examine the prediction performance of these methods against the measured LBM permeability by conducting the error analysis and the coefficient of determination (R2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${R}^{2}$$\\end{document}) calculation. Our findings revealed that the ANN models outperformed the SVM models. Specifically, the ANN model displayed an impressive R2 value of 0.892, along with root mean square error (RMSE), mean squared error (MSE) and, mean absolute error (MAE) values of 1.927, 3.716 and 1.580, respectively. In contrast, the SVM model yielded an R2 value of 0.849, with RMSE, MSE and, MAE values of 2.324, 5.401 and, 2.166 respectively, when assessed on testing data of measured permeability. This study found that ANN is more dependable, robust, and precise than SVM in forecasting carbonate sample permeability.

Investigation on the flow behavior and mechanisms of water flooding and CO2 immiscible / miscible flooding in shale oil reservoirs

Shale reservoirs represent a significant untapped source of recoverable oil, and even a slight increase in recovery can yield substantial benefits. In recent years, there has been a growing interest in the development of shale reservoirs due to their vast potential. Shale reservoirs are characterized by their intricate pore structures, ultra-low porosity, and extremely low permeability. Consequently, fluid flow within shale formations is highly complex, and the distribution of shale oil is diverse. There is an urgent need to conduct research into the flow behavior of shale reservoirs and the modes of crude oil occurrence within them, in order to support effective shale oil extraction in the field. In this work, we established a MCMP-MRT-LBM model considering nano-scale confinement effects such as slip and adsorption. The model is employed to simulate single pore channels and blind-end pores to investigate the distinct mechanisms involved in water flooding, CO2 immiscible flooding, and CO2 miscible flooding. Subsequently, the research explores the fluid flow characteristics associated with these three development methods within porous media, as well as the distribution of remaining oil. Then we compared the oil displacement efficiency, swept volume, actual liquid injection volume and displacement front position of the three fluids in porous media. The results reveal that water flooding exhibits superior displacement performance in single pore channels, while CO2 miscible flooding proves to be the most effective method for exploiting oil in blind-end pores. In porous media, CO2 miscible flooding successfully mitigates fingering phenomena and efficiently recovers crude oil located at blind-end and corner regions of the pores. The recovery efficiency achieved through CO2 miscible flooding is approximately 30% higher than that of water flooding and about 10% greater than CO2 immiscible flooding.

Flow and Thermal Characteristics of Couple Stress Fluid over a Stretching Surface with Hybrid Nanoparticles

In the current research, a mathematical analysis of couple stress fluid flow and heat characteristics through a stretchable permeable surface with hybrid nanoparticles is conducted. The solid nanoparticles of the aluminium alloys (AA7072 and AA7075) are suspended in methanol to create the hybrid nanofluid. The similarity approach is used to reduce the governing equations into the similarity equations. Then, MATLAB's bvp4c function is employed to solve the resulting equations. The solutions for the flow and temperature fields, as well as the skin friction coefficient and Nusselt number are presented in table and graphical forms. The results demonstrate that hybrid nanofluids excel as thermal conductors, significantly augmenting the heat transfer rate. The heat transfer rate is increased by 0.38% for the nanofluid, while 0.89% increment for the hybrid nanofluid compared to the base fluid. Furthermore, a larger couple stress parameter is found to be associated with a decrease in the fluid temperature and an enhancement in fluid velocity.

The influence of tube diameter parameters on the flow resistance and heat transfer characteristics of supercritical CO2 in horizontal tubes

The diameter parameters of tubes are crucial for the flow and heat transfer characteristics of supercritical fluids. however, the diameter effect has not been fully understood. The existing literatures only investigate the effect of different tube diameters on the flow and heat transfer characteristics within a narrow parameter range, lacking specific theoretical analyses and verification in a wide range of parameters. Therefore, experimental research was conducted to investigate the influence of tube diameter parameters on the flow resistance and heat transfer of supercritical carbon dioxide(sCO2) in horizontal tubes and an explanation of the tube diameter effect mechanism is provided based on pseudo-boiling theory. Stainless steel smooth circular tubes with diameters of 8 mm, 10 mm, and 12 mm were used as the test section, and various experiments were carried out under the range of mass flux (G): 509.23–1267.34 kg/m2s, heat flux (qw): 97.91–410.43 kW/m2, and operating pressure (P): 5.54–20.32 MPa. From the pseudo-boiling theory analysis, the influence of tube diameter parameters has a greater influence on the heat transfer in the two-phase-like (TPL) regime and is almost negligible when the P exceeded 1.5Pc, indicating the interaction between liquid-like (LL) and vapor-like (VL) phases is found to be the dominant reason for the tube diameter effect on heat transfer and the correlations for predicting the maximum wall temperature difference between the top and bottom generatrix (ΔTmax) are established. The present work can significantly enhance the understanding on sCO2 flow boiling mechanism and provide a new research direction for supercritical fluid.

Analysis of MHD and Heat Transfer Characteristics of Thermally Radiative Upper-Convected Maxwell Fluid Flow between Moving Plates: Semi-Analytical and Numerical Solution

The current paper studies the MHD and heat transfer characteristics of radiative upper-convected Maxwell fluid flow between two plates approaching or receding from each other with injection at the fixed lower porous plate. The governing momentum and energy equations are reduced into non-linear ordinary differential equations employing similarity transformations. With the help of the Homotopy Perturbation Method (HPM), an approximate analytic solution is obtained. This work aims to determine the effects of Reynolds number (R), Deborah number (De), Radiation parameter (Rd), Magnetic parameter (M), and Prandtl number (Pr) on the velocity and temperature profiles. It is observed that the Deborah number has a direct impact on the velocity profile when there is a squeezed flow. It is also observed that the magnetic parameter shows an indirect impact on the temporal distribution for both the upper plate moving away and towards the lower. The variations in the significant physical parameters on the coefficient of skin friction and heat transfer rates are also calculated. The results are then compared with the classical finite difference method and are in excellent agreement. It is found that larger the magnetic parameter, the dominance of viscous forces retards the velocity in the core region, and the increase in radiation parameter suppresses the heat transfer rates. This study is helpful in industrial applications, specifically in polymer processing.