Search results

Sand production is a challenging issue during hydrocarbon production in the oil and gas industry. This paper aims to investigate one sand production process, i.e. transient sand production, using a novel bonded particle lattice Boltzmann method. This mesoscopic technique provides a unique insight into complicated sand erosion process during oil exploitation.

The mesoscopic fluid-particle coupling is directly approached by the immersed moving boundary method in the framework of lattice Boltzmann method. Bonded particle method is used for resolving the deformation of solid. The onset of grain erosion of rocks, which are modelled by a bonded particle model, is realised by breaking the bonds simulating cementation when the tension or tangential force exceeds critical values.

It is proved that the complex fluid–solid interaction occurring at the pore/grain level can be well captured by the immersed moving boundary scheme in the framework of the lattice Boltzmann method. It is found that when the drawdown happens at the wellbore cavity, the tensile failure area appears at the edge of the cavity. Then, the tensile failure area gradually propagates inward, and the solid particles at the tensile failure area become fluidised because of large drag forces. Subsequently, some eroded particles are washed out. This numerical investigation is demonstrated through comparison with the experimental results. In addition, through breaking the cementation, which is simulated by bond models, between bonded particles, the transient particle erosion process is successfully captured.

A novel bonded particle lattice Boltzmann method is used to investigate the sand production problem at the grain level. It is proved that the complex fluid–solid interaction occurring at the pore/grain level can be well captured by the immersed moving boundary scheme in the framework of the lattice Boltzmann method. Through breaking the cementation, which is simulated by bond models, between bonded particles, the transient particle erosion process is successfully captured.

The MRT lattice Boltzmann simulation of natural convection in a confined environment is carried out. The flow and heat transfer during natural convection in a symmetrical annulus are studied.

The cavity is filled with TiO₂-water nanofluid, and the thermal conductivity and dynamic viscosity of nanofluid are measured experimentally. The experimental data are utilized in the numerical simulations. The nanofluids are prepared at four different nanoparticle concentrations φ = 0, 0.1, 0.3 and 0.5. It is notable that the radial coordinate is used into the temperature distribution function. As a result, only one source term is required for the present lattice Boltzmann model. On the other hand, the macro cylindrical energy equation is exactly recovered using Chapman–Enskog analysis.

Influence of some main parameters including Rayleigh number in range of 103 to 106, solid volume fraction of nanofluid in range of 0 to 0.5 and four different aspect ratios on the the nanofluid flow (i.e. streamlines), heat transfer (i.e. temperature distribution and average Nusselt number) and entropy generation (i.e. total entropy generation and Bejan number) are presented, quantitatively and graphically. It is found that adding TiO2 nanoparticles to the base fluid has considerable positive effect on the heat transfer performance and entropy generation. In addition, the configuration of the annulus can be good controlling parameter on the heat transfer rate during natural convection.

The originality of this work is using of a modern numerical method to simulate the free convection and conducting experimental observations to calculate the thermo-physical properties of nanofluid. In addition, the numerical and experimental works are combined to provide accurate results.

This study aims to modify the standard probabilistic lattice Boltzmann methodology (LBM) cellular automata (CA) algorithm to enable a more realistic and accurate computation of the ensemble rather than individual particle trajectories that need to be updated from one time step to the next (allowing, as such, a fraction of the collection of particles in any lattice grid cell to be updated in a time step, rather than the entire collection of particles as in the standard LBM-CA algorithm leading to a better representation of the dynamic interaction between the particles and the background flow). Exploitation of the inherent parallelism of the modified LBM-CA algorithm to provide a computationally efficient scheme for computation of particle-laden flows on readily available commodity general-purpose graphics processing units (GPGPUs).

This paper presents a framework for the implementation of a LBM for the simulation of particle transport and deposition in complex flows on a GPGPU. Towards this objective, the authors have shown how to map the data structure of the LBM with a multiple-relaxation-time (MRT) collision operator and the Smagorinsky subgrid-scale turbulence model (for turbulent fluid flow simulations) coupled with a CA probabilistic method (for particle transport and deposition simulations) to a GPGPU to give a high-performance computing tool for the calculation of particle-laden flows.

A fluid-particle simulation using our LBM-MRT-CA algorithm run on a single GPGPU was 160 times as computationally efficient as the same algorithm run on a single CPU.

The method is limited by the available computational resources (e.g. GPU memory size).

A new 3D LBM-MRT-CA model was developed to simulate the particle transport and deposition in complex laminar and turbulent flows with different hydrodynamic characteristics (e.g. vortex shedding, impingement, free shear layer, turbulent boundary layer). The solid particle information is encapsulated locally at the lattice grid nodes, allowing for straightforward mapping of the datastructure onto a GPGPU enabling a massive parallel execution of the LBM-MRT-CA algorithm. The new particle transport algorithm was based on the local (bulk) particle density and velocity and provides more realistic results for the particle transport and deposition than the standard LBM-CA algorithm.

The purpose of this paper is to investigate the laminar flow and heat transfer characteristics in a two‐dimensional horizontal channel with two square blocks placed side‐by‐side using a numerical scheme based on a coupling between the lattice Boltzmann method and the finite difference method.

The multiple‐relaxation‐time (MRT) lattice Boltzmann equation model coupled with the finite difference method are used to predict numerically the velocity and the temperature fields.

A complex structure of the fluid flow was observed for various dimensionless block separation distance (G). An unsteady flow was found when the two blocks are placed side by side (G = 0). For G < 1.5, the presence of each block develops the street of Van Karman which generates complex binary vortex street. In the opposite case (G > 1.5), the effect of this parameter (G) on the fluid is reduced, whereas, the distance between the blocks and the nearest walls have a great influence on the fluid flow and the heat transfer. When the obstacles are posed on the walls (G = 3), an important heat exchange between the blocks and the nearest walls is noted.

This study offers more knowledge on natural convection in an obstructed channel. Furthermore, this work shows the effectiveness of the MRT lattice Boltzmann equation model for this kind of geometry.

The main purpose of this paper was to investigate Lattice Boltzmann (LB) models for the bulk incompressible flow past immersed bodies and to find the set of boundary conditions (BCs) that can be considered suitable for modeling the borders of the numerical simulation domain in such a way as to avoid any effect of these BC on the flow trail that is formed behind the body.

Three different models of the Lattice Boltzmann equation (LBE) and six different sets of BCs are tested. In addition to the classical LBE based on the Bhatnagar–Gross–Krook (BGK) single relaxation time collision model, a moments-based model and a model with two relaxation times were investigated.

The flow pattern and its macroscopic effects on the aerodynamic coefficients appear to be very dependent on the set of BC models used for the borders of the numerical domain. The imposition of pressure at the exit results in pressure perturbations, giving rise to sound waves that propagate back into the simulation domain, producing perturbations on the upwind flow. In the same way, the free-slip BC for the lateral bords appears to affect the trail of vortices behind the body in this range of Reynolds number (Re = 1,000).

The paper investigates incompressible flow past immersed bodies and presents the set of BCs that can be considered suitable for modeling the borders of the numerical simulation domain in such a way as to avoid any effect of these BCs on the flow trail that is formed behind the body.

This paper aims to study the natural convection of a nanofluid inside a cavity which contains obstacles using lattice Boltzmann method (LBM). The results have focused mainly on various parameters such as number and aspect ratio of roughness elements and different nanoparticle volume fraction. The isotherms and streamlines are presented to describe the hydrodynamics and thermal behaviors of the nanofluid flow throughout the enclosure.

The methodology of this paper consists of mathematical model, statement of the problem, nanofluid thermophysical properties, lattice Boltzmann method, LBM for fluid flow, LBM for heat transfer, numerical strategy, boundary conditions, Nusselt (Nu) number calculation, code validation and grid independence.

Natural convection heat transfers of a nanofluid inside cavities with and without rough elements have been studied. Lattice Boltzmann technique has been used as numerical approach. The results showed that at higher Rayleigh number (Ra = 10⁶), there are denser streamlines near the left (source) and right wall (sink) which results in better cooling and enhances convective heat rejection to the heat sink. After a distinctive aspect ratio of rough elements (A = 0.1), change in streamline pattern which arises from increasing of aspect ratio does not have an important effect on isotherms. Results indicate that for lower Rayleigh number (Ra = 10³), no variation in average Nu is observed with increasing in number of roughness, while for higher one (Ra = 10⁶) average Nu decreases from N = 0 (smooth cavity) up to N = 4 and then remains constant (N = 6).

Currently, no argumentative and comprehensive extraction can be concluded without fully understanding the role of different arrangement of roughness. Some geometrical parameters such as aspect ratio, number and position of rough elements have been considered. Also, the effect of nanoparticle concentration was studied at different Ra number. Briefly, using LBM, this paper aims to investigate the natural convection of a nanofluid flow on the thermal and hydrodynamics parameters in the presence of rough element with various arrangements.

Lattice Boltzmann method (LBM) has made great success in computational fluid dynamics, and this paper aims to establish an efficient simulation model for the polymer injection molding process using the LBM. The study aims to validate the capacity of the model for accurately predicting the injection molding process, to demonstrate the superior numerical efficiency in comparison with the current model based on the finite volume method (FVM).

The study adopts the stable multi-relaxation-time scheme of LBM to model the non-Newtonian polymer flow during the filling process. The volume of fluid method is naturally integrated to track the movement of the melt front. Additionally, a novel fractional-step thermal LBM is used to solve the convection-diffusion equation of the temperature field evolution, which is of high Peclet number. Through various simulation cases, the accuracy and stability of the present model are validated, and the higher numerical efficiency verified in comparison with the current FVM-based model.

The paper provides an efficient alternative to the current models in the simulation of polymer injection molding. Through the test cases, the model presented in this paper accurately predicts the filling process and successfully reproduces several characteristic phenomena of injection molding. Moreover, compared with the popular FVM-based models, the present model shows superior numerical efficiency, more fit for the future trend of parallel computing.

Limited by the authors’ hardware resources, the programs of the present model and the FVM-based model are run on parallel up to 12 threads, which is adequate for most simulations of polymer injection molding. Through the tests, the present model has demonstrated the better numerical efficiency, and it is recommended for the researcher to investigate the parallel performance on even larger-scale parallel computing, with more threads.

To the authors’ knowledge, it is for the first time that the lattice Boltzmann method is applied in the simulation of injection molding, and the proposed model does obviously better in numerical efficiency than the current popular FVM-based models.

This paper aims to use the Lattice Boltzmann method (LBM) to numerically simulate the natural convection heat transfer of Cu-water nanofluid in an L-shaped enclosure with curved boundaries.

LBM on three different models of curved L-shape cavity using staircase approach is applied to perform a comparative investigation for the effects of curved boundary on fluid flow and heat transfer. The staircase approximation is a straightforward and efficient approach to simulating curved boundaries in LBM.

The effect of curved boundary on natural convection in different parameter ranges of Rayleigh number and nanoparticle volume fraction is investigated. The curved L-shape results are also compared to the rectangular L-shape results that were also achieved in this study. The curved boundary LBM simulation is also validated with existing studies, which shows great accuracy in this study. The results show that the top curved boundary in curved L-shape models causes a notable increase in the Nusselt number values.

Based on existing literature, there is a lack of comparative studies which would specifically examine the effects of curved boundaries on natural convection in closed cavities. Particularly, the application of curved boundaries to an L-shape cavity has not been examined. In this study, curved boundaries are applied to the sharp corners of the bending section in the L-shape and the results of the curved L-shape models are compared to the simple rectangular L-shape model. Hence, a comparative evaluation is performed for the effect of curved boundaries on fluid flow in the L-shape enclosure.

The purpose of this paper is to model the convective flows in a room equipped by a glass door and a heated floor of length l = 0.8 × H and submitted to a sinusoidal temperature profile and mono alternative temperature profile.

The paper opts for a numerical study of convective flows in a large scale cavity using the Lattice Boltzmann Method (LBM) by considering a two dimensions (2D) square cavity of side H and filled by air (Pr = 0.71). All the vertical walls, the ceiling and the rest of the floor are thermally insulated, the hot portion of length l = 0.8×H is heated with two imposed temperature profiles of amplitude values 0.2 ≤  a  ≤ 0.6 and for two different periods ζ = ζ0 and ζ = 0.4×ζ0. One of the vertical walls has a cold portion θ_c = 0 that represents the glass door.

A systematic study of the flow structure and heat transfer is carried out considering principal control parameters: amplitude “a” and period ζ for Rayleigh number Ra = 10⁸. Effects of these parameters on results are presented in terms of isotherms, streamlines, profiles of velocities, temperature in the cavity, global and local Nusselt number. It has been found that an increase in amplitude or period increases the amplitude of the temperature in the core of cavity. The Nusselt number increases when the amplitude “a” of the imposed temperature increases, but this later is not affected by variation of the period.

The authors used LBM to simulate the convective flows in a cavity at high Ra, heated from below by tow imposed temperature profiles. Indeed, they simulate a local equipped by a solar water heater (SWH). The floor is subjected to a periodic heating: Sinusoidal heating (Case 1) for which the temperature varies sinusoidally (SWH without a supplement), and mono alternation heating (Case 2), the temperature evolves like a redressed signal (SWH with a supplement). The considered method has been successfully validated and compared with the previous work. The study has been conducted using several control parameters such as the signal amplitude and period in the case of turbulent convection. This allowed us to obtain a considerable set of results that can be used for engineering.

The purpose of this study is investigating the effect of using multi-phase nanofluids, Rayleigh number and baffle arrangement simultaneously on the heat transfer rate and Predict the optimal arrangement type of baffles in the differentiation of Rayleigh number in a 3D enclosure.

Simulations were performed on the base of the L25 Taguchi orthogonal array, and each test was conducted under different height and baffle arrangement. The multi-phase thermal lattice Boltzmann based on the D3Q19 method was used for modeling fluid flow and temperature fields.

Streamlines, isotherms, nanofluid volume fraction distribution and Nusselt number along the wall surface for 104 < Ra < 108 have been demonstrated. Signal-to-noise ratios have been analyzed to predict optimal conditions of maximize and minimize the heat transfer rate. The results show that by choosing the appropriate height and arrangement of the baffles, the average Nusselt number can be changed by more than 57 per cent.

The value of this paper is surveying three-dimensional and two-phase simulation for nanofluid. Also using the Taguchi method for Predicting the optimal arrangement type of baffles in a multi-part enclosure. Finally statistical analysis of the results by using of two maximum and minimum target Function heat transfer rates.