Lagrangian Eulerian Research Articles

A novel approach to preventing SARS-CoV-2 transmission in classrooms: A numerical study

The education sector has suffered a catastrophic setback due to the ongoing COVID pandemic, with classrooms being closed indefinitely. The current study aims to solve the existing dilemma by examining COVID transmission inside a classroom and providing long-term sustainable solutions. In this work, a standard 5 × 3 × 5 m3 classroom is considered where 24 students are seated, accompanied by a teacher. A computational fluid dynamics simulation based on OpenFOAM is performed using a Eulerian–Lagrangian framework. Based on the stochastic dose–response framework, we have evaluated the infection risk in the classroom for two distinct cases: (i) certain students are infected and (ii) the teacher is infected. If the teacher is infected, the probability of infection could reach 100% for certain students. When certain students are infected, the maximum infection risk for a susceptible person reaches 30%. The commonly used cloth mask proves to be ineffective in providing protection against infection transmission, reducing the maximum infection probability by approximately 26% only. Another commonly used solution in the form of shields installed on desks has also failed to provide adequate protection against infection, reducing the infection risk only by 50%. Furthermore, the shields serve as a source of fomite mode of infection. Screens suspended from the ceiling, which entrap droplets, have been proposed as a novel solution that reduces the infection risk by 90% and 95% compared to the no screen scenario besides being completely devoid of fomite infection mode. The manifestation of infection risk in the domain was investigated, and it was found out that in the case of screens the maximum infection risk reached the value of only 0.2 (20% infection probability) in 1325 s.

A mesoscale bubble-induced turbulence model and simulation of gas–liquid flows

In gas–liquid two-phase flows, bubble motion significantly affects liquid phase turbulence, and adding bubble-induced turbulence (BIT) source term is widely used to improve the simulation accuracy. This paper presents a new BIT model based on the energy-minimization multi-scale (EMMS) methodology. The model was constructed by considering two mesoscale factors, i.e., the sub-grid structures through analyzing the slip velocity and the gas holdup gradient, and the equivalent diameter of turbulent eddies calculated by the EMMS-based turbulence model. In order to verify its performance, the model was incorporated to the Eulerian–Lagrangian simulating framework and applied to two typical experimental systems. Both mean flow characteristics and turbulence quantities were well predicted, and the new model showed advantages over traditional BIT models, especially at higher gas velocities. Moreover, a strategy for counting energy dissipation in the simulation was devised and performed whereby the dual effects of promotion and suppression on liquid phase turbulence by bubbles can be reflected. The simulations demonstrated that BIT dominated the energy dissipation and turbulence was enhanced by BIT at higher gas velocities, while shear-induced turbulence dominated the energy dissipation and turbulence is reduced due to the suppression by bubbles at lower gas velocities.

A comprehensive model to capture electrical discharge and spark channel evolution during spark-ignition processes

Emissions reduction through engine efficiency improvements is a priority for automakers who have turned to unconventional engine operation such as highly dilute, boosted, and stratified charge. Given its importance to flame initiation and sustained turbulent flame propagation, reliable and accurate spark ignition models are necessary to design ignition systems that reduce cyclic indicated mean effective pressure (IMEP) variability and increase engine efficiency in these operation modes. In this paper, secondary electric circuit, short-circuit, blowout, and re-strike sub-models are added to the Lagrangian–Eulerian spark ignition (LESI) model to simulate electrical discharge and spark channel elongation in an inert cross-flow combustion vessel. First, the physics of the underlying sub-models are described and the governing equations discussed with the spark channel voltage expression playing a critical role. Then, the experimental and simulations setups are presented. The results section begins with the derivation of spark channel voltage from experimental results. Then, electrical discharge and spark channel elongation simulations in inert flows are carried out using LESI and compared against experimental results. The results validate the model’s ability to accurately predict spark channel elongation, as well as the occurrence of short-circuits, blowouts, re-strikes, and end of discharge.

Material Defects in Friction Stir Welding through Thermo–Mechanical Simulation: Dissimilar Materials with Tool Wear Consideration

Despite the remarkable capabilities of friction stir welding (FSW) in joining dissimilar materials, the numerical simulation of FSW is predominantly limited to the joining of similar materials. The material mixing and defects' prediction in FSW of dissimilar materials through numerical simulation have not been thoroughly studied. The role of progressive tool wear is another aspect of practical importance that has not received due consideration in numerical simulation. As such, we contribute to the body of knowledge with a numerical study of FSW of dissimilar materials in the context of defect prediction and tool wear. We numerically simulated material mixing and defects (surface and subsurface tunnel, exit hole, and flash formation) using a coupled Eulerian-Lagrangian approach. The model predictions are validated with the experimental results on FSW of the candidate pair AA6061 and AZ31B. The influence of tool wear on tool dimensions is experimentally investigated for several sets of tool rotations and traverse speeds and incorporated in the numerical simulation to predict the weld defects. The developed model successfully predicted subsurface tunnel defects, surface tunnels, excessive flash formations, and exit holes with a maximum deviation of 1.2 mm. The simulation revealed the substantial impact of the plate position, on either the advancing or retreating side, on the defect formation; for instance, when AZ31B was placed on the AS, the surface tunnel reached about 50% of the workpiece thickness. The numerical model successfully captured defect formation due to the wear-induced changes in tool dimensions, e.g., the pin length decreased up to 30% after welding at higher tool rotations and traverse speeds, leading to surface tunnel defects.

Effect of Particle Diameter on Primary Breakup of High-Pressure Diesel Spray Atomization: A Study Based on Numerical Simulations Using the Eulerian–Lagrangian Model

The coupling of Eulerian and Lagrangian methods in the Eulerian–Lagrangian Spray Atomization (ELSA) approach is critical. This study proposes an equation for the primary breakup particle diameter D of a diesel fuel spray and adopts it as a key transition criterion for coupling. A three-dimensional diesel spray is modeled by the large-eddy simulation (LES) approach. This improved ELSA simulation was conducted using various transition criteria for particle diameter Dcr. The results show that fuel spray experiences two stages: stage I, when a liquid column appears without a dispersed phase, and stage II, when primary breakup occurs with many discrete particles. Although Dcr has little influence on the macro-spray characteristics, such as top penetration distance S and spray cone angle θ, it has significant effects on discrete particles, such as their number, average diameter, distribution and location, and spray cone area. Dcr should be determined on the basis of actual operating conditions.

Wear modelling and sealing performance prediction of C/C composite finger seal

Due to the high speed and high pressure operating conditions, wear between the finger seal and the rotor is inevitable, and this leads to an increase of leakage clearance and becomes an important factor affecting the seal life. The theory of anisotropic elasticity was employed to describe the mechanical characteristics of the seal material. An improved Archard wear model was proposed to calculate the nodal wear rate, and the local wear direction was also determined. The wear simulation model and procedure were established based on the Arbitrary Lagrangian Eulerian adaptive mesh strategy. The effects of material density, fabric orientation, pressure differential and rotor speed on the wear characteristics of finger seal and the change of leakage clearance caused by wear loss were studied. The results show that the wear first occurs at the heel area of the finger foot bottom and gradually extends to the toe area. C/C (carbon fibre reinforced carbon matrix) composite finger seal with higher material density has smaller leakage clearance and wear depth. With the increase of fabric orientation angle, the wear depth in the heel area of finger foot is smaller, and the circumferential wear area is narrower. The average wear depth of finger seal decreases with the orientation angle. When the orientation angle is 0, the seal leakage clearance is smaller. The increase of pressure differential not only aggravates the seal wear, but also expands the wear area, and also increases the average contact pressure and leakage clearance. Increasing the rotor speed make the wear depth of the heel area of finger foot gradually increase, but the wear area becomes narrower. The average contact pressure decreases and the average leakage clearance increases. This study provides a theoretical method and basis for the prediction and evaluation of the wear life and performance of C/C composite finger seal.

Conditional Generative Adversarial Networks for modelling fuel sprays

In this study, the probabilistic, data driven nature of the generative adversarial neural networks (GANs) was utilized to conduct virtual spray simulations for conditions relevant to aero engine combustors. The model consists of two sub-modules: (i) an autoencoder converting the variable length droplet trajectories into fixed length, lower dimensional representations and (ii) a Wasserstein GAN that learns to mimic the latent representations of the evaporating droplets along their lifetime. The GAN module was also conditioned with the injection location and the diameters of the droplets to increase the generalizability of the whole framework. The training data was provided from highly resolved 3D, transient Eulerian–Lagrangian, large eddy simulations conducted with OpenFOAM. Neural network models were created and trained within the open source machine learning framework of PyTorch. Predictive capabilities of the proposed method was discussed with respect to spray statistics and evaporation dynamics. Results show that conditioned GAN models offer a great potential as low order model approximations with high computational efficiency. Nonetheless, the capabilities of the autoencoder module to preserve local dependencies should be improved to realize this potential. For the current case study, the custom model architecture was capable of conducting the simulation in the order of seconds after a day of training, which had taken one week on HPC with the conventional CFD approach for the same number of droplets (200,000 trajectories).

Primary atomization of liquid jets: Identification and investigation of droplets at the instant of their formation using direct numerical simulation

A detailed investigation of droplet characteristics for the primary atomization of a round liquid jet injected into stagnant gas is performed using direct numerical simulation. The material properties correspond to a Diesel injection, and the numerical framework is based on the volume-of-fluid method. The study is carried out in the statistically steady state, which allows to collect time-averaged droplet formation statistics. A novel algorithm continuously detects droplets at the instant they detach from the liquid core jet, which are referred to as primary droplets. The main droplet characteristics, such as volume, velocity and sphericity, are captured for newly formed primary droplets as well as all other droplets in the domain. This allows a detailed comparison between droplet characteristics during and after their formation. In addition, the droplet Weber, Reynolds and Stokes numbers are computed. These dimensionless numbers govern important physical processes occurring subsequent to the droplet formation, such as potential secondary breakup and droplet motion. One central goal is to provide information relevant for large eddy simulation of sprays in the Eulerian–Lagrangian framework, where the formation of small droplets from the liquid core jet cannot be resolved, and therefore potentially needs to be modeled. Moreover, the relative importance of primary and secondary atomization is estimated for this specific setup. It is found that the distribution of the droplet sizes is very similar for primary droplets and the entire droplet collective. Furthermore, the droplet Weber numbers are significantly below the critical Weber number required for secondary droplet breakup. Together, these two observations indicate that, for the investigated configuration, primary atomization is the dominating process, while secondary atomization only plays a minor role. Moreover, the high droplet volume fraction observed shows that droplet–droplet collisions and coalescence can be expected to influence the spray behavior. To put the obtained results into perspective, empirical correlations for the Sauter Mean Diameter are used to discuss potential trends for higher Reynolds and Weber numbers.

A numerical investigation of the particle behaviors and entropy generation in mixed convection inside a vented enclosure

The present study is to focus on the numerical investigation of the transportation, deposition and removal of solid particles in the range of 5 μm to 0.01 μm for mixed convection flow in the vented square cavity by utilizing the Eulerian–Lagrangian method with one-way coupling. The change in the deposition and removal mechanisms affected by the forces acting on the particles is addressed for mixed convection of ventilation airflow. In the analysis of entropy generation, the irreversibilities due to the presence of solid particles are studied with a new approach for both dominant natural and forced convection. The governing equations for fluid phase and the Lagrangian particle tracking are scrutinized by employing the finite volume method with SIMPLE algorithm and explicitly integrating the set of ordinary differential equations, respectively. The examination of the thermal and flow fields is carried out in the cases of various Reynolds numbers and Richardson numbers. The minimum and maximum values of the average Nusselt number are determined with related operating parameters. By using the results of thermal behaviors and flow structures obtained at steady-state condition, the particle velocity, temperature and location are presented for the combined natural and forced convection. By investigating the particles deposited on the walls and ones removed from the exit section for different Reynolds numbers and Richardson numbers, it is demonstrated that the sum rate of deposition and removal is low at 1≤Ri≤10 and high Reynolds number for 1 μm and 0.1 μm particles. For given Reynolds number, increasing the buoyancy effect results in substantial changes in the thermal field and flow pattern, therefore the particles remaining suspended show different behaviors when the effect of natural convection alters from weak to dominant. It is observed that the Brownian and thermophoretic forces play an important role in the small particle deposition and removal. As a result of entropy generation analysis, the minimum total entropy generation is determined at Ri=5 for given Reynolds number except for Re=50. Moreover, it is proposed to investigate the irreversibilities due to the heat transfer between the particles and the fluid surrounding them and the frictional total force acting on the suspended particles.

Analysis on the Vulnerability of a Tunnel Entrance under Internal Explosion.

Tunnels play an essential role in the transportation network. Tunnel entrances are usually buried at a shallow depth. In the event of an internal explosion, the blast pressure will cause severe damage or even collapse of the tunnel entrance, paralyzing the traffic system. Therefore, an accurate assessment of the damage level of tunnel entrances under internal blast loading can provide effective assistance for the anti-blast design of tunnels, post-disaster emergency response, and economic damage assessment. In this paper, four tunnel entrance specimens were designed and fabricated with a scale ratio of 1/5.5, and a series of field blast tests were carried out to examine the damage pattern of the tunnel entrances under internal explosion. Subsequently, static loading tests were conducted to obtain the maximum bearing capacity of the intact specimen and residual bearing capacities of the post-blast specimens. After that, an explicit non-linear analysis was carried out and a numerical finite element (FE) model of the tunnel entrance under internal blast loading was established by adopting the arbitrary Lagrangian-Eulerian (ALE) method and validated based on the data obtained from the field blast and static loading tests. A probabilistic vulnerability analysis of a typical tunnel entrance subjected to stochastic internal explosions (assuming various charge weights and detonation points) was then carried out with the validated FE model. For the purpose of damage assessment, the residual bearing capacity of the tunnel entrance was taken as the damage criterion. The vulnerability curves corresponding to various damage levels were further developed based on the stochastic data from the probabilistic vulnerability analysis. When the charge weight was 200 kg, the tunnel entrance exhibited slight or moderate damage, while the tunnel entrance suffered severe or even complete damage as the charge weight increased to 1000 kg. However, the tunnel entrance's probability of complete damage was less than 10% when the TNT charge weight did not exceed 1000 kg.

Towards material flow prediction in friction stir welding accounting for mechanisms governing chip formation in orthogonal cutting

A new approach to integrate the damage in a 3D friction stir welding model within the coupled Eulerian–Lagrangian (CEL) framework is proposed. The novelty is represented by the employed damage criteria accounting for the mechanisms governing chip formation in orthogonal cutting. Material flow is correctly predicted with the new approach avoiding the problems encountered when neglecting damage or when including it through the traditional approach (Johnson–Cook failure criterion for initiation and energy criterion for evolution). The model can simulate in-plane forces and nugget zone width according to the experiments. The maximum equivalent plastic strain is estimated in the flow arm zone, due to the simultaneous action of pin and shoulder. Additionally, it is demonstrated the importance in mesh element size if material flow is investigated through CEL models. The elements in the interaction zone must be sufficiently small for describing the cyclical layer deposition at each tool rotation.

Numerical analysis of reinforced concrete buildings subjected to blast load

AbstractThis study deals with a three‐dimensional (3D) nonlinear finite element (FE) analysis of two reinforced concrete (RC) buildings. The first is a three‐floor flat slab building without shear walls. The second is a three‐floor flat slab building with four shear walls. The blast load has been simulated using the coupled Eulerian–Lagrangian (CEL) technique found in the FE software Abaqus/Explicit. Concrete behavior has been modeled using the Johnson–Holmquist damage model (JH‐2) with 3D eight‐node reduced Lagrangian integration elements (C3D8R). The reinforcement steel has been modeled using the Johnson–Cook (JC) plasticity model and the JC computational fracture model with beam elements (B31). Trinitrotoluene (TNT) explosive material has been modeled using the Jones–Wilkins–Lee (JWL) equation of state (EOS) with eight‐node reduced integration Eulerian elements (EC3D8R). Air has been modeled using the EOS for ideal gas with EC3D8R elements. TNT charges of 20, 100, and 1000 kg with standoff distances of 2, 5, and 10 m have been used in the analysis. An analysis has been performed to study the two RC buildings' deformation, stresses, and damage. The results showed that small TNT charges of less than 20 kg with a standoff distance of more than 10 m had almost no effect on the two buildings. Also, huge TNT charges of more than 1000 kg with a standoff distance of less than 10 m had a catastrophic impact on the two buildings.

Eulerian–Lagrangian modeling of deflagration to detonation transition in n-decane/oxygen/nitrogen mixtures

In this work, to promote deflagration to detonation transition (DDT), a designed hot jet in a pre-detonator is produced to initiate detonations in the main detonation tube. We perform two-dimensional simulations of the DDT process for low-volatile fuel (n-decane) mixed with nitrogen and oxygen based on the Eulerian–Lagrangian approach. The effects of fuel atomization, vaporization, and shock focusing on the flame acceleration and DDT are discussed under different nitrogen dilution ratio and droplet size conditions. The results show that the flame acceleration process can be divided into slow and fast deflagration stages. Additionally, initiation times are mainly determined by the fuel atomization and evaporation in the slow deflagration stage, which dominates the entire DDT time. Furthermore, there are different intensities of hot jets rather than stable detonation waves formed at the pre-detonator exit. Moreover, local decoupling and re-initiation events are detected near the internal wall of the U-bend, inducing the overdriven detonation decaying into stable detonation waves in the smooth tube. The results also demonstrate that the detonation pressure and velocity decrease by 13.56% and 12.55%, respectively, as the nitrogen dilution ratio increases from 0.5 to 2. In particular, as the nitrogen dilution ratio continued to increase to 2.25, the development in DDT is similar, but the jet intensity is significantly weakened. While as the droplet size increases from 10 to 40 μm, the detonation pressure and velocity decrease only by 2.69% and 1.49%, respectively.

Numerical simulations on the settling dynamics of an ellipsoidal particle in a viscoelastic fluid

The settling dynamics of a rigid ellipsoid in an unbounded viscoelastic fluid under inertialess conditions is studied through direct numerical simulations. The governing equations are solved by the finite element method with an Arbitrary Lagrangian–Eulerian formulation to handle the particle motion. The viscoelastic fluid is modeled through the Giesekus constitutive equation. Simulations are carried out up to a value of Deborah number of 5. The settling of prolate and oblate spheroidal particles is first addressed. The sedimentation, lift, and angular velocities are computed as a function of the orientation angle and for aspect ratios from 1/8 to 8. Regardless of the particle shape, initial orientation, and Deborah number, the particle rotates to align its longest axis along the force direction. A high extensional stress region behind the particle is observed at high aspect ratios due to the large curvature of the tip, leading to a fast decay of the axial fluid velocity downstream and to the appearance of a negative wake. Similarly, a triaxial ellipsoid reaches a final orientation with major axis parallel to the falling direction. The particle shape affects the orientational dynamics, both in terms of the orbits followed by the orientation vectors and the time needed to reach the equilibrium orientation, and the steady-state settling velocity. The fastest sedimentation rate is observed for a prolate spheroid with aspect ratio of about 2 whereas the slowest one for a high aspect ratio oblate spheroid. Triaxial ellipsoids settle with rates in between these two limiting behaviors.

Lagrangian Numerical Simulation of Proppant Transport in Channel Fracturing

This paper focuses on the numerical simulation of particle (“proppant”) transport in channel fracturing, in which fiber-proppant fluid is pumped intermittently into hydraulic fractures, alternated with clean fluid pulses. The pulsed pumping protocol leads to heterogeneous/channelized proppant distribution in fractures, generating open flow channels with high conductivity. To understand the evolution of the channelized proppant distribution, we develop an efficient pseudo-3D multiphase particle-in-cell (P3D MP-PIC) method to simulate the proppant transport during the pumping process. Compared with the Eulerian-Eulerian (EE) models, the MP-PIC approach has higher accuracy in modeling particle-fluid and particle-particle interactions by tracing the particles in a Lagrangian fashion. Compared with the computational fluid dynamics-discrete element method (CFD-DEM), the MP-PIC method is more computationally efficient due to a parcel feature and the fast calculation of particle forces. Reduced from the 3D MP-PIC method, the P3D MP-PIC method has better computational efficiency and flexibility to couple with other subsurface processes (e.g., fracture propagation and fluid leakoff) while also achieving sufficient accuracy for engineering purposes. Due to the Eulerian-Lagrangian (EL) nature, the P3D MP-PIC method can track the trajectories of the fiber-proppant clusters whose effective viscosity and the settling velocity are determined based on the laboratory results. With an accurate description of fluid and particle dynamics, this work reveals the critical physical mechanisms of the proppant transport in channel fracturing: stable displacement and Saffman-Taylor (ST) instability. The alternate occurrence of these two mechanisms gives rise to the channelized proppant distribution. To investigate the influential factors of the channel patterns, we conduct parametric studies on the operational parameters, including injection rate, fiber concentration, and pulsing mode. The effect of fracture propagation and gravitational settling is also discussed in detail.

A unified approach for the solution of fluid‐solid interaction problems with hyperelastic deformation in internal flows

AbstractIn the single domain method for solving fluid–solid interaction (FSI) problems, a unified formulation is used for the entire computational domain. In such monolithic FSI solvers, all of the governing equations are solved simultaneously. In the present study, the single domain method is further extended to an interface‐tracking FSI solver which accounts for mesh movement via an Arbitrary Lagrangian–Eulerian (ALE) description of the governing equations. The focus is on internal flow problems with large deformation. Pressure and velocity are selected as the dependent variables for both solid and fluid parts of the computational domain. A distinguishing feature of the proposed method is that the governing equations at the interface are discretized in a conservative manner. Interfacial boundary conditions are enforced via a pressure–velocity splitting method to convert the kinematic and dynamic conditions at the interface into pressure–velocity relations. A PISO‐like procedure is used to solve the discretized equations. In order to evaluate the proposed solver, strongly‐coupled FSI benchmark test cases are employed. The performance of the proposed method and computational results are also compared with those obtained by a conventional partitioned solver. The results show that the proposed solver provides more accurate results on a coarser mesh compared to the benchmark solutions. The proposed method is also capable of solving strongly coupled problems for which the partitioned solver fails to converge.

Development of Eulerian–Lagrangian simulation for snow transport in the presence of obstacles

The aim of this study is to develop a wind-induced snow transport model in a turbulent atmospheric boundary layer with the multiphase particle-in-cell (MP-PIC) approach. The airflow is treated as a continuum (Eulerian phase), and the snow is treated as discrete particles (Lagrangian phase). The momentum exchange between airflow and snow particles is considered, as well as the drag force of fluctuation velocity on particles, the turbulence damping near the snow-airflow interface, and the inter-particle collisions. The validation comprised wind-induced snow transport on flat terrain and around the roadbed, with the typical Eulerian–Eulerian approach serving as a control. The Eulerian–Lagrangian approach yields a better agreement with the experimental observations, especially in the presence of obstacles. On the contrary, considerable discrepancies with the experimental data are detected when utilizing the Eulerian–Eulerian approach. The Eulerian–Lagrangian approach is thought to have the advantages of independent snow momentum-governing equations and a precise snow-airflow momentum exchange model, which could be beneficial for snow transport prediction in urban environments.

Projection Based Semi-Implicit Partitioned Reduced Basis Method for Fluid-Structure Interaction Problems

In this manuscript a POD-Galerkin based Reduced Order Model for unsteady Fluid-Structure Interaction problems is presented. The model is based on a partitioned algorithm, with semi-implicit treatment of the coupling conditions. A Chorin–Temam projection scheme is applied to the incompressible Navier–Stokes problem, and a Robin coupling condition is used for the coupling between the fluid and the solid. The coupled problem is based on an Arbitrary Lagrangian Eulerian formulation, and the Proper Orthogonal Decomposition procedure is used for the generation of the reduced basis. We extend existing works on a segregated Reduced Order Model for Fluid-Structure Interaction to unsteady problems that couple an incompressible, Newtonian fluid with a linear elastic solid, in two spatial dimensions. We consider three test cases to assess the overall capabilities of the method: an unsteady, non-parametrized problem, a problem that presents a geometrical parametrization of the solid domain, and finally, a problem where a parametrization of the solid’s shear modulus is taken into account.

Drag Reduction in Polymer-Laden Turbulent Pipe Flow

The turbulence of a realistic dilute solution of DNA macromolecules is investigated through a hybrid Eulerian–Lagrangian approach that directly solves the incompressible Navier–Stokes equation alongside the evolution of 108 polymers, modelled as finitely extensible nonlinear elastic (FENE) dumbbells. At a friction Reynolds number of 320 and a Weissenberg number of 2×104, the drag reduction is equal to 26%, which is similar to the one obtained at the lower Reynolds number of 180. The polymers induce an increase in the flow rate and the turbulent kinetic energy, whose axial contribution is predominantly augmented. The stress balance is analysed to investigate the causes of the drag reduction and eventually the effect of the friction Reynolds number on the probability distribution of the polymer configuration. Near the wall, the majority of the polymers are fully stretched and aligned along the streamwise direction, inducing an increase in the turbulence anisotropy.

Numerical Analysis for Coal Gasification Performance in a Lab-Scale Gasifier: Effects of the Wall Temperature and Oxygen/Coal Ratio

The optimization of multiple factors for gasification performance using a 3D CFD model with advanced sub-models for single-stage drop tube coal gasification was compared with experimental results. A single-stage down-drop gasifier with multiple coal injectors and a single oxygen injector at the top of the gasifier was investigated at different temperatures and O2/coal ratios. A finite rate/eddy dissipation (FR/ED) model was employed to define the chemical reactions. Kinetic data for the various reactions were taken from previous work. The realizable k–ε turbulent model and Euler–Lagrangian framework were adopted to solve the turbulence equations and solid–gas interaction. First, various preliminary reactions were simulated to validate the reaction model with experimental data. Furthermore, various cases were simulated at various O/C ratios and wall temperatures to analyze the syngas species, temperature profile in the whole gasifier, exit temperature, carbon conversion, turbulent intensity, and velocity profile. The maximum CO was found to be 75.06% with an oxygen/coal ratio of 0.9 at 1800 °C. The minimum and maximum carbon conversions were found to be 97.5% and 99.8% at O/C 0.9 at 1200 °C and O/C 1.1 at 1800 °C, respectively.