Control Volume Finite Element Research Articles

MODELING AND SIMULATION OF FLUID FLOWDYNAMICS FOR CO₂ MIGRATION IN TWO-DIMENSIONAL SALINE AQUIFERS

Geological carbon sequestration is increasingly recognized as a promising solution for mitigating CO2 emissions by storing CO2 in geological formations such as saline aquifers. Although recent research has primarily focused on optimizing CO2 trapping mechanisms to enhance storage efficiency, the flow dynamics of CO2 plume migration—particularly the propagation and growth of fingers—remain insufficiently understood. In response to these challenges, we develop a model to simulate CO2 plume migration in both homogeneous and heterogeneous porous media within two-dimensional (2D) saline aquifers. This study utilizes high-order reservoir simulations within the ICFERST framework, employing the control volume finite element method (CVFEM) to specifically capture the viscous instabilities associated with CO2 plume migration. The simulation process integrates various mesh resolutions and incorporates adaptive mesh optimization (AMO). Our results indicate that increasing mesh resolution significantly enhances the ability to accurately capture the formation and growth of CO2 fingers. In homogeneous porous media, AMO effectively balances accuracy and computational efficiency by dynamically refining or coarsening the mesh in critical regions. In heterogeneous porous media, simulations reveal the emergence of wider and larger fingers compared to those observed in homogeneous settings, with bifurcations occurring at locations where relative permeability undergoes significant changes.

The neural networking strategy results in the tri‐hybrid nanofluid flowing over a slippery flat plate to act as an antimicrobial agent through solar radiation

AbstractHybrid nanofluids are employed to enhance the antibacterial effect produced by solar radiation. Antimicrobial properties are present in metal nanoparticles (such as silver, copper, or zinc) or metal oxides (such as titanium dioxide or zinc oxide) when exposed to solar radiation. Nanomaterials that have antimicrobial properties are selected from the available literature. A solar sheet with an inclined plane has been chosen and filled with tri‐hybrid nanofluids (THNFs). Hybrid nanofluids including (CuO), Copper oxide, TiO2 (Titanium oxide), and SiO2 (Silicon dioxide), are selected from metal and metal oxide classes including water as a base fluid. The antimicrobial action caused by solar radiation is enhanced by the slip boundaries and variable porous space. The influence of flow and thermal fields on isotherms, velocities, flow lines, and Nusselt numbers are considered. The transformed system of differential equations is solved by the Control Volume Finite Element Method (CVFEM) and RK‐4 technique. The nanoparticulate volume fraction of CuO, TiO2, and SiO2 is largely responsible for the enhancement in the heat transfer rate (HT), as observed. Improved thermal performance is achieved through the flow of THNFs, which in turn acts as an antimicrobial agent. Increasing values of parameters lead to an improvement in the heat transfer rate, which in turn decreases microbial activity.

A single mesh approximation for modeling multiphase flow in heterogeneous porous media

A single mesh approximation for modeling multiphase flow in heterogeneous porous media

Quantitative analysis of the electromagnetic hybrid nanofluid flow within the gap of two tubes using deep learning neural networks

Purpose(1) A mathematical model for the Hybrid nanofluids flow is used as carriers for delivering drugs. (2) The flow conditions are controlled to enable drug-loaded nanofluids to flow through the smaller gap between the two tubes. (3) Hybrid nanofluids (HNFs) made from silver (Ag) and titanium dioxide (TiO2) nanoparticles are analyzed for applications of drug delivery. (Ag) and (TiO2) (NPs) are suitable candidates for cancer treatment due to their excellent biocompatibility, high photoactivity, and low toxicity. (4) The new strategy of artificial neural networks (ANN) is used which is machine-based and more prominent in validation, and comparison with other techniques.Design/methodology/approachThe two Tubes are settled in such a manner that the gap between them is uniform. The Control Volume Finite Element Method; Rk-4 and Artificial Neural Network (ANN).Findings(1) From the obtained results it is observed that the dispersion and distribution of drug-loaded nanoparticles within the body will be improved by the convective motion caused by hybrid nanofluids. The effectiveness and uniformity of drug delivery to target tissues or organs is improved based on the uniform flow and uniform gap. (2) The targeting efficiency of nanofluids is further improved with the addition of the magnetic field. (3) The size of the cylinders, and flow rate, are considered uniform to optimize the drug delivery.Research limitations/implications(1)The flow phenomena is considered laminar, one can use the same idea through a turbulent flow case. (2) The gap is considered uniform and will be interesting if someone extends the idea as non-uniform.Practical implications(1) To deliver drugs to the targeted area, a suitable mathematical model is required. (2) The analysis of hybrid nanofluids (HNFs) derived from silver (Ag) and titanium dioxide (TiO2) nanoparticles is conducted for the purpose of drug delivery. The biocompatibility, high photoactivity, and low toxicity of (Ag) and (TiO2) (NPs) make them ideal candidates for cancer treatment. (3) Machine-based artificial neural networks (ANN) have a new strategy that is more prominent in validation compared to other techniques.Social implicationsThe drug delivery model is a useful strategy for new researchers. (1) They can extend this idea using a non-uniform gap. (2) The flow is considered uniform, the new researchers can extend the idea using a turbulent case. (3) Other hybrid nanofluids flow, in the same model for other industrial usages are possible.Originality/valueAll the obtained results are new. The experimental thermophysical results are used from the existing literature and references are provided.

Investigation of natural convection heat transfer in various structures of a partitioned triple porous enclosure under permanent magnetic field

Investigation of natural convection heat transfer in various structures of a partitioned triple porous enclosure under permanent magnetic field

The evaluation of error estimation for the Casson hybrid nanofluid flow in the uniform gap between two tubes for drug delivery applications

ABSTRACT Hybrid nanofluids are capable of being used as a carrier for delivering drugs to targeted areas in the body. For this purpose, the Casson hybrid nanofluids (HNFs) flow is suggested between the gap of two tubes. The study involves analyzing blood-based hybrid nanofluids (HNFs) that consist of silver (Ag) and titanium dioxide (TiO2) nanoparticles for applications of drug delivery. Titanium oxide nanoparticles, or TiO2 NPs, have strong photoactivity, low toxicity, and excellent biocompatibility, making them promising candidates for cancer treatment. The attractiveness of silver nanoparticles (AgNPs) for cancer therapy is due to their unique properties. Graphic representations are provided based on the simulations of non-dimensional velocity, temperature, and skin friction under physical parameter variations, for the applications of drug delivery are investigated and discussed. The control volume finite element method (CVFEM), is used to solve the problem. The new strategy of artificial neural networks (ANN) is also used to solve the transform equations. Nanoparticles increase drug stability and extend shelf life by protecting them from degradation or inactivation.

Artificial neural network analysis of the flow of nanofluids in a variable porous gap between two inclined cylinders for solar applications

Copper (Cu) nanoparticles (NPs) and polyvinyl alcohol (PVA) are utilized to enhance heat transfer (HT) which is used in the efficiency of solar energy systems. Copper nanoparticles have excellent thermal conductivity (TC) properties that enable them to conduct heat efficiently. In this arrangement, the gap between the two cylindrical channels is settled for the hybrid nanofluids (HNFs) flow in an inclined position that is favourable to sunlight. The nanomaterials consist of a mixture of PVA and Cu nanoparticles (NPs), to execute HNFs. Solar radiation is present on the hot side of the system. The porous gap between the two channels is considered variable which plays a crucial role in enhancing heat transfer and energy conversion. The varying permeability of the gap is adjusted to control the flow resistance and improve the stability of the system. It is observed that higher porosity allows for better convective heat transfer and reduced pressure drop. The transformed equations are solved through an artificial neural network (ANN) while the control volume finite element method (CVFEM) is also used to handle the governing equations. The Cu and PVA (HNF) improves solar radiation absorption and protects components, ultimately increasing the performance and efficiency of the systems.

Stable and locally mass- and momentum-conservative control-volume finite-element schemes for the Stokes problem

Stable and locally mass- and momentum-conservative control-volume finite-element schemes for the Stokes problem

Numerical study of mass and heat transport within a ceramic porous tank

<p>In porous media, the thermal transfer phenomenon is widely applied in diverse energy-intensive industrial processes. This research paper aims to elucidate the simultaneous transfer of mass and heat within a ceramic porous tank. To simulate these transport phenomena, a numerical method is developed: Control Volume Finite Element Method (CVFEM), in conjunction with the utilization of a free mesh generator called Gmsh. The study showcases numerous simulation results that depict the transport phenomenon, such as the three-dimensional evolution of three parameters (temperature, saturation and pressure) during the heating of the ceramic tank. By employing this numerical model, a more comprehensive comprehension of these transport phenomena can be achieved.</p>

Production simulation and prediction of fractured horizontal well with complex fracture network in shale gas reservoir based on unstructured grid

In order to accurately simulate the productivity variation characteristics of fractured wells with complex fracture network in shale gas reservoir, based on the multiple migration mechanism of shale gas, the micro-seismic data and discrete fracture model were used to characterize the fracture geometry and complex boundary characteristics, and the comprehensive seepage mathematical model of fractured wells with complex fracture network was established based on the dual porosity-discrete fracture model, and the numerical solution was carried out by combining the unstructured grid and the control volume finite element method. The sensitivity analysis of the influence of key parameters such as fracture conductivity, physical property difference in composite area and Langmuir volume on the production performance of fractured horizontal wells is carried out. This study provides theoretical methods and calculation tools for accurate prediction of productivity change and optimization of production system of fractured horizontal wells with complex fracture network in shale gas reservoirs.

Irreversibility analysis through neural networking of the hybrid nanofluid for the solar collector optimization

Advanced techniques are used to enhance the efficiency of the energy assets and maximize the appliance efficiency of the main resources. In this view, in this study, the focus is paid to the solar collector to cover thermal radiation through optimization and enhance the performance of the solar panel. Hybrid nanofluids (HNFs) consist of a base liquid glycol (C3H8O2) in which nanoparticles of copper (Cu) and aluminum oxide (Al2O3) are doped as fillers. The flow of the stagnation point is considered in the presence of the Riga plate. The state of the solar thermal system is termed viva stagnation to control the additional heating through the flow variation in the collector loop. The inclusion of entropy generation and Bejan number formation are primarily conceived under the influence of physical parameters for energy optimization. The computational analysis is carried out utilizing the control volume finite element method (CVFEM), and Runge–Kutta 4 (RK-4) methods. (FEATool Multiphysics) software has been used to find the solution through (CVFEM). The results are further validated through a machine learning neural networking procedure, wherein the heat transfer rate is greatly upgraded with a variation of the nanoparticle's volume fraction. We expect this improvement to progress the stability of heat transfer in the solar power system.

3D Thermal Study of Double Partition Brick Drying

In porous media, heat and mass transfer is a classical model of transport and it is one of the most energy-intensive industrial processes with a wide variety of applications. This present paper is developed in order to explain the coupled heat and mass transfer that arise during drying process. A free mesh generator Gmsh is used and a 3-D unstructured Control Volume Finite Element Method (CVFEM) is employed to simulate the transport phenomena with a convective drying. Several simulation results, that depict the transport phenomenon inside a porous brick are presented and analyzed. Indeed, thanks to this numerical model, we can observe the three-dimensional distribution of temperature, liquid saturation and pressure during double partition brick drying.

Electro-enhanced natural convection analysis for an Al2O3-water-filled enclosure by considering the effect of thermal radiation

One of the most crucial topics in the thermal sciences is the analysis of how an external electric field affects the natural convection flow. In this study, the heat transfer of electro-hydrodynamic natural convection in an enclosure with a wavy hot wall is numerically studied. Al2O3-water nanofluid is considered as the working fluid, and furthermore, the effect of thermal radiation on the characteristics of fluid flow is simulated. Non-dimensional forms of governing equations are numerically solved using control volume finite element method. The effects of operational parameters such as Rayleigh number, nanoparticles volume-fraction, Lorentz force number, Eckert number, charge diffusivity number, and electric field number on the maximum absolute value of stream function and the average Nusselt number are investigated. Two new parameters are defined to evaluate the contribution of the electrical field and radiation effects on the fluid flow. The results show that ascends 7.95% when increases from 0 to 0.05 at Also, the values of and increase 27.6% and 37.2%, respectively, when goes up from 0 to 0.5 at The values of and decrease 48.7% and 27.1%, respectively, with decreasing the amplitude parameter from 0.1 to 0.3 at

Comparative analysis of the flow of the hybrid nanofluid stagnation point on the slippery surface by the CVFEM approach

Comparative analysis of the flow of the hybrid nanofluid stagnation point on the slippery surface by the CVFEM approach

Numerical Investigation of Heat Transfer Inside Participating Media: Built Thermal Environment Application

This paper is devoted to studying the effect of volumetric radiation on coupled convection and radiation heat transfer in a participating two-dimensional enclosure with emitting absorbing and scattering medium which is a crucial criterion in design of built thermal environment. Radiative information is gotten by resolving RTE (the radiative transfer equation) by means of CVFEM (the Control Volume Finite Element Method). Temperature, density and velocity fields are calculated using the mesoscopic two double population lattice Boltzmann approach. Results are validation of results with existing works in literature and the proposed approach was found to be numerically stable, efficient and accurate.

Ferrofluid treatment with insertion of electric field inside a porous cavity considering forced convection

The electro-hydrodynamic (EHD) ferrofluid flow through a porous square shaped enclosure is simulated with different shapes of nanomaterial in the presence of constant heat flux. The flow is governed by coupled partial differential equations and is simulated with the well-established computational technique of control volume finite element method (CVFEM). The effects of the enhancing medium permeability and electric field strength on the flow are displayed through contour plots of streamlines and isotherms. The calculations are performed for different governing parameters namely, porosity, applied electric field , radiation effect , and nanomaterial shape factor over the Nusselt number . It is found that the medium augmenting permeability depreciates the ferrofluid streaming in the absence as well as in the presence of the applied electric field. The temperature of the ferrofluid augments with the medium increasing porosity in the absence of an external electric field, while an opposite effect is observed on the temperature in the presence of the electric field. The enhancement in the medium porosity makes the ferrofluid flow more regular in the absence as well as in the presence of an external electric field.

Production performance simulation of a horizontal well in a shale gas reservoir considering the propagation of hydraulic fractures

Production performance simulation of a horizontal well in a shale gas reservoir considering the propagation of hydraulic fractures

A hybrid pressure approximation in the control volume finite element method for multiphase flow and transport in heterogeneous porous media

A hybrid pressure approximation in the control volume finite element method for multiphase flow and transport in heterogeneous porous media

Research of the thermoelastic performance of the functionally graded sandwich slabs with convective-radiative boundary conditions based on FVM

<p indent="0mm">In this study, a two-dimensional control volume finite element method (CV-FVM) has been developed for the thermoelastic coupling problem of sandwich structures with functionally graded material core under a convection-radiation heat transfer environment. Based on a four-node quadrilateral element, the discrete process of the governing equation and the nonlinear heat transfer boundary are given in detail. Based on the staggered grid technology, the variables are stored at the node of the element, and the material parameters are defined at the center of the element. To ensure the convergence of the temperature solution, the radiation heat transfer boundary condition is handled by the linearization technique. The numerical method developed in this study is validated for the heat conduction problem of sandwich structures with an exponential core. The results showed that CV-FVM results are consistent with the analytical solution. The influences of the geometric and physical parameters, such as the Biot number, radiation conduction coefficient, environmental temperature ratio, panel thickness, and gradient index of the functionally graded core, on the thermoelastic performance of the structure are investigated. The results showed that the Biot number of the heating surface has only a slight effect on the thermoelastic response of the structure, whereas the Biot number of the cooling surface has a significant effect on the thermoelastic response. The cooling surface is more sensitive to the change in the environmental temperature than the heating surface. For sandwich structures with an exponential core, increasing the thickness of the upper panel can reduce the large gradient change of the stress at the junction between the upper panel and the core. The stress with a linear variation of the properties (<italic>p</italic> = 1) is smoother than that with a nonlinear variation of the properties (<italic>p</italic> = 0.1 and 10), and the large gradient change of the stress of the structure can be reduced significantly (<italic>p</italic> = 1).

Production Performance Simulation of the Fractured Horizontal Well Considering Reservoir and Wellbore Coupled Flow in Shale Gas Reservoirs

Unmodified original shale gas reservoirs have been demonstrated to have extremely low permeability, and the long horizontal drilling and hydraulic fracturing techniques are widely used to obtain economic gas production. However, these techniques can result in a nonlinear flow of fluids during transport through the multi-scale pore system and the complex fracture network around the horizontal well, as well as a two-phase gas-water flow during shale production. To solve these issues, in this paper, first, the complex fracture network around the horizontal well is characterized using the discrete main hydraulic fractures combined with composite regions with different properties. Then, the dual porosity media and discrete-fracture model are implemented to describe the nonlinear flow behavior in the multi-scale pore system, and a wellbore pressure drop model is established to characterize the transient two-phase gas–liquid flow in the different sections of the fractured horizontal well. Finally, the coupled reservoir wellbore flow model is fully implicitly solved using the control volume finite element method and unstructured tetrahedral grids. The results of the simulation model of a multi-stage fractured horizontal well in the shale of the Longmaxi Formation will help field engineers deeply understand gas and water production performance and the dynamics of wellbore and reservoir pressure, as well as optimize development schemes.