computational fluid dynamics (cfd)

The aerodynamic performance of wind turbines is significantly influenced by the design of their blades, which are engineered with advanced aerodynamic airfoils. However, the effectiveness of these designs is compromised by environmental factors such as dust, corrosion, sand, and insects, leading to alterations in blade shape and surface integrity over the turbine's operational period. These changes reduce the aerodynamic efficiency of the turbines. To assess these detrimental effects, this study utilizes a 3D Computational Fluid Dynamics (CFD) model based on the exact blade geometry. A modified version of the universal logarithmic wall function was implemented to quantify the influence of surface roughness. Comparative analyses between clean and rough blade surfaces under varying wind conditions showed that surface degradation significantly impacts the efficiency of wind turbines. Specifically, the findings indicate that surface roughness can lead to a substantial decrease in power output, with losses potentially reaching up to 35% under tested conditions. Notably, this roughness effect exhibits a critical value of  , beyond which the impact of roughness becomes negligible. Based on these results, an exponential correlation has been proposed. This study suggests that maintaining smooth blade surfaces or minimizing roughness is crucial for optimal turbine performance, especially under high wind conditions.

Turbulent impinging jet array is one of the most efficient and popular techniques for cooling gas turbine blades. In the present paper, we numerically investigated how the geometrical design parameters affect the cooling performance for jet array impinged to a curved target. The influence parameters, including jet spacing (2.5≤Pj≤10), jet angle (-45°≤θ≤+45°), and off-center distance (0≤Ej≤6) on average Nusselt number (Nu), air pressure drop (Δp), and heat transfer uniformity index (UI) were identified through a parametric study at a constant total mass flow rate. Results show, increasing jet spacing improved heat transfer but lowered uniformity and required more compression power. Tilting the jets generally decreases the average Nusselt number but boosts the uniformity. Also, increasing the inclination angle reduces the pressure drop. Moving the jets off-center consistently lowered pressure drop until Ej=4 and average Nusselt number till Ej=2 without affecting uniformity much up to until Ej=3, and beyond those values, increased them. best performance based on average Nusselt number is achieved for the case of Pj=10, θ=0°, and Ej=0. Also, the uniformity index is maximized and pressure drop is minimized at Pj=5, θ=+45°, and Ej=0.

The heat transfer improvement and the increase of heat exchangers’ efficiency represent a very important issue in the energy field. Many research projects have focused on the use of fluids with high thermal conductivity such as nanofluids. In this case, hybrid nanofluids, are a new class of nanofluids with good heat transfer characteristics. The present work falls within this framework and involves a numerical study to examine the influence of two oil-based hybrid nanofluids, Al2O3-MWCNT and MgO-MWCNT, with different volume concentrations and inlet flow rates. More to the point, the impact of different nanoparticle ratio and the location of hybrid nanofluid in a laminar flow of two-pipe counter-current heat exchanger have been investigated. In virtue of which, the results illustrate that increasing the volume concentration of nanoparticles and the flow rate of the hybrid nanofluid has a positive impact on improving the heat transfer rate. Therefore, the improvement in heat transfer rate reached 77.8% for Al2O3-MWCNT/oil hybrid nanofluid and 59.5% for MgO-MWCNT/oil hybrid nanofluid. Similarly, the study has also revealed that the preferred nanoparticles ratio for Al2O3-MWCNT/oil hybrid nanofluid is in the order of (25:75) and its circulation in the inner tube as a hot fluid makes it possible to improve the thermal performance of the considered two-tube heat exchanger to a greater advantage.

Imitating Dolphin fish-like movement is productive method for enhancing their hydrodynamic capabilities. This work aims to analyze and understand the oscillations of tail fluke of Dolphin, which can be used as a propulsive mechanism for underwater fish robots and vehicles. The objective of the work is to achieve the desired oscillating amplitude by simulating the NACA 0012 profile using computational models and Set up the swimming movement of the dolphin, imitating a fish like model. Computational techniques were employed to examine the propulsive capabilities of the oscillating hydrofoil, inspired by the dolphin's biological propulsion. The evolutionary of fluid pattern in the field surrounding both Dolphin fish model and the NACA0012 hydrofoil, from initial motion to cruising, was established, and the hydrodynamic impact was subsequently studied. An user-defined function (UDF) was developed to create a dynamic mesh interface with CFD code ANSYS FLUENT for establishing the oscillations of Dolphin tail across the flow field. Influencing hydrodynamic coefficients such as lift and drag coefficients at different frequencies were also obtained. The findings shown that when the acceleration of the Dolphin fish model increases, the time averaged drag force coefficient drops because The wake field's vortex disperses to have some beneficial effects and pressure of water surrounding the fish head intensifies to produce a large resistance force. Simulation results show a 98% agreement at lower frequency and speed levels but a 5% deviation at higher frequency and speed due to turbulence effects in both models. It was established that the vortex superposition enhances the Dolphin fish like model rather than lowering its positive impacts.  The Strouhal number, which is obtained by the fluid field's evolution rule, can be linked to the Kármán vortex street span with reverse.

The present research used a numerical simulation technique known as the Discrete Fracture Model (DFM) to examine the propagation of shale gas in fractured porous media. It employed a novel mathematical model for seepage flow, incorporating the application of the 'cubic law' for flow in fractures and Darcy's law for the seepage flow in the matrix. The impact of fracture aperture on flow behavior was simulated by solving a set of nonlinear, partial, differential equations using the finite element method (FEM). Through this work, a sensitivity analysis of the significant parameters, including hydraulic fracture numbers and permeability, hydraulic fracture aperture, and wellbore length, on the productivity of a shale gas reservoir was conducted. Hydraulic fracture permeability with increasing oil production (more than twice) had the greatest effect on the wellbore productivity. Furthermore, the simulation results showed that augmenting the number of hydraulic fractures from 4 to 15 resulted in a production increase of over twofold. Also, it was observed that the production rate increased due to the existence of a positive correlation between the fracture aperture size and the drainage area. The outcome of this research showed the significance of hydraulic fracture characteristics and its ensuing effects on the productivity and feasibility. In order to validate the accuracy of the numerical model, the pressure distribution in a single fractured reservoir was compared with the pressure contour of a phase field discrete fracture model (PFDFM). The results indicated that the proposed method (FPM) was precise, convergent, and extremely promising.

In this article, an extracorporeal membrane oxygenator (ECMO) is simulated in 2D geometry using computational fluid dynamics (CFD). Momentum and mass transport equations were solved for the laminar flow regime (30 < Re < 130 for the blood channel) using the finite element method. In this study, the software COMSOL was used as the solver. To this end, the main problem of ECMO devices is the pressure drop and the risk of thrombus formation due to blood stagnation, so to solve this problem, the oxygen transfer rate to the blood should be increased. Therefore, in the present study, to optimize the oxygen transfer rate of the blood, three basic parameters were examined: blood flow velocity, oxygen velocity, and membrane thickness. Blood flow was considered at five different velocities (0.2, 0.4, 0.5, 0.6, and 0.8 mm/s). Results showed that increased blood flow velocity adversely affected oxygen permeability, increasing oxygen permeability from about 60% at 0.2 mm/s to about 24% at 0.9 mm/s. In addition, five different membrane thicknesses (0.04, 0.06, 0.08, 0.2, and 0.3 mm) were investigated, and, as expected, better oxygen exchange occurred as the membrane thickness decreased. We also found that the diffusion rate is about 40% for the 0.4 mm/s thin films and about 25% for the same inlet velocity and larger film thickness. Furthermore, the oxygen diffusivity increases from 28% to 38% as the oxygen gas velocity increases. However, oxygen velocities above 0.8 mm/s should not be used, as the range of oxygen diffusivity variation decreases with higher oxygen gas velocities.

Numerous studies have been conducted to investigate effect of blade geometry of vertical axis wind turbine performance. Most of the evaluations have focused on the airfoil series and airfoil geometry parameters such as thickness and camber of the airfoil. Few studies have examined the effect of other blade geometry parameters on the vertical axis wind turbine performance. In the present study, the effect of geometric change in leading-edge radius (LER) of a vertical axis wind turbine performance has been numerically studied. Hence, modified NACA 0021 airfoil profiles were created using the geometric method (CST). Then, the flow behavior around a Darrieus vertical axis wind turbine was simulated under the influence of the reduction and set-up coefficients of the leading-edge radius at a constant wind speed of 9 m/s and a tip speed ratio of 1.5 to 3.5 using the computational fluid dynamics. Additionally, the effects of the examined parameter (leading-edge radius) on fluid flow and aerodynamic performance coefficients, including the coefficients of power and torque, were investigated. The results indicated that the leading-edge radius affected the near wake flow of the turbine, and the optimization of leading-edge radius parameter controls the dynamic stall and reduces the formation of a vortex. Finally, the optimization of LER revealed that at 20% reduction in the LER the performance of the turbine at tip speed ratio of 1.5 was increased by more than 50%. This reinforces the self-starting capability of a Darrieus wind turbine.

Due to the vital role of motor-driven pumps in various industries such as oil and gas, manufacturing, chemical, etc., their continuous monitoring and implementing effective maintenance methods is of crucial importance. Periodic inspections and intermittent vibration data collection using accelerometers is among the most common methods. Electrical signature analysis is an alternative approach that only uses electrical measurements for the purpose of fault detection. Despite the unique advantages of this method, such as its non-intrusiveness and possibility of continuous monitoring of the equipment, there have been limited studies on its underlying theory with majority of the proposed ESA-based methods taking data-driven approach towards condition monitoring problem. Data-driven methods rely on the experimental data collected from the equipment to train the statistical models. This imposes a serious limitation on the application of electrical signature analysis and makes the generalization harder. In this paper the electromechanical coupling in a motor-driven centrifugal pump is studied in order to demonstrate the effects of different operating conditions of pump on motor electrical signals. Lumped parameter approach is employed to derive governing equations of the induction motor and computational fluid dynamics is utilized to analyze the interaction of the centrifugal pump blades and fluid. Such a modeling platform presents a physics-based approach towards electrical signature analysis based condition monitoring. A closed-loop hydraulic test rig is built to compare and verify the simulation results.

In this study, complex processes in a typical Electric Arc Furnace (EAF) such as combustion, radiation, heat, and mass transfer were solved and the optimum injector location was found using computational fluid dynamics (CFD). The main aim of the injection optimization was to improve the thermal performance and the metallurgical process by changing the injection angle, the central angle of the injector (CAI), and injector length. Fifteen parametric cases were predicted and analyzed for optimization study. To decrease each simulation solution time of each cases, a polyhedral mesh structure was used instead of tetrahedral mesh for the EAF geometry. Thus, the total element number of the model was decreased by 1/5 while providing faster and unchanging results compared to the case with a tetrahedral mesh structure. The response surface optimization method was used for the optimization study. As a result, the optimum injector positioning was obtained as injection angle: -45°, injector length 614 mm, and CAI: 60°.

In the present work, the effects of modifying the tongue geometry of a centrifugal pump on pressure pulsations under the design and off-design conditions are carried out numerically by the unsteady analysis of fluid flow. Numerical modeling based on the Re-Normalization Group (RNG) k-ε turbulence model using a Mosaic mesh structure, a technology which can easily, quickly and formally connects any type of mesh for complex geometries and flow regimes, is applied to simulate the flow within the modeled pump, which is validated with the available experimental results. The flow is simulated through a commercial Computational Fluid Dynamics (CFD) software that solved Reynolds-Averaged Navier-Stokes (RANS) equations for a three-dimensional unsteady flow. In addition to choosing Qd (the design flow rate), 0.4 Qd and 1.2Qd  are also taken into account as the inlet flow rates. Besides, pressures of 101KPa and 13KPa are considered as additional inlet conditions for this investigation. This unsteady simulation employing different inlet conditions is used to investigate the impacts of various volute tongue angles on the pressure coefficient (cp ). Results indicate that, overall, by changing the angle from 40° to 85°, the value of the pressure coefficient at the pump outlet grows by about 10% where it also causes a rise in the amplitude of pressure fluctuations. By the same token, a decrement to the inlet flow rate up to 40% of the nominal value brings about the amplitude of pressure fluctuations at the pump outlet to be increased significantly.

Methane has been known as a safety risk for the coal mining activities. Accordingly, one can mitigate this risk, and hence, the level of hazard to which the mining workers are exposed, by predicting the possible exceedance of allowable methane dosage should be provided with a reliable information on the distribution of methane across the working face considering the uncertainties associated with the gas content of such deposits. In this work, the gas content uncertainty in a coal seam is first investigated using the geo-statistical simulation. Then a method is proposed in order to predict methane gas emission based on the Monte Carlo random simulation method. Next, the results obtained are introduced into a 3D Computational Fluid Dynamics (CFD) model to estimate the methane distribution considering the uncertainty associated with the gas content. Defined as zones where the methane concentration is so high that an explosion is much likely to occur, the elevated methane zones (EMZs) are delineated across the working faces. The results obtained show that UGC has an impact on the ventilation parameters and EMZs. The proposed method could be carried out in order to guide the ventilation design in improving safety.

This paper investigates the flow structures on the near- and far-wake of a 1/8th scaled simplified heavy vehicle model called Ground Transportation System (GTS) model using a steady-state Reynolds-averaged Navier-Stokes (RANS) with k-ω Shear Stress Transport (SST) turbulence model at Reynolds number (Re) of 1.6 × 106 and yaw angles (Ψ) = 0o-14o. The current CFD results have been validated using experimental data from the literature. Two crosswind conditions based on the crosswind incidence angle (β) are adopted; β < 90o is called crosswind, and β = 90o (perpendicular to the GTS side surface) is called pure crosswind. Vortex detection scheme based on Ω method and total pressure coefficient (Cpt) contours is used to visualize the wake structure. With Ψ, vortices on the GTS roof take birth as a result of pressure differences between the windward and leeward sides. These vortices grow in size as they travel downstream. The growth in size is related to the Helmholtz theorem of vorticity and Kelvin’s Circulation Theorem. The vortices merged at Z/W > -4 (Z/W = 0 is the GTS rear surface) downstream of the GTS for Ψ = 7.5o and 14o. The merged vortex dissipates at Z/W > -6 and Z/W > -8 for Ψ = 7.5o and 14o, respectively. In the pure crosswind condition, the merged vortex attaches to the ground due to the velocity difference between the freestream and the moving computational ground used in the present simulation. At Ψ = 14o, surface streamlines on the GTS surface show the creation of two co-rotating vortices on the windward roof. For the present Ψ, similar flow structures between the two crosswind conditions are shown. Initial results show that the aerodynamic crosswind stability of a truck is related to the spanwise pressure difference between the windward and leeward surfaces of the truck.

In this paper, the capability of the Computational Fluid Dynamics (CFD) approach is evaluated to reliably predict the fluid dynamic and the separation performance of Pd membranes modules for gas mixture separation. In this approach, the flow fields of the pressure and velocity for the gas mixture and the species concentration distribution in the selected three-dimensional domains are obtained by simultaneous and numerical solution of continuity, momentum, and species transport (especially, gas-through-gas diffusion term that derived from the Stefan–Maxwell formulation) equations. Therefore, the calculation of the hydrogen permeation depends on the local determination of the mass transfer resistance caused by the gas phase and membrane, which is modeled as a permeable surface of known characteristics. The applicability of the model to properly predict the separation process under a wide range of pressure, feed flow rate, temperature, and gas mixtures composition is assessed through a strict comparison with experimental data. Moreover, in this work, the influence of inhibitor species on the module performance is discussed, which is obtained by implementing the CFD model. The results of the simulation showed that increasing the pressure on the feed side increases the molar fraction of hydrogen gas, the feed inlet flow on the shell side, and the hydrogen permeation through the membrane in the tube side. Comparison of simulation results with laboratory data showed good agreement. The model was obtained with an error of less than 3% at 450K and below 6% for 475K and 500K.

The effect of geometric parameters of the zigzag, rectangular, and serpentine channels on convective heat transfer coefficient and pressure drop was investigated using computational fluid dynamics (CFD). In all channels, the same boundary conditions were considered, and the number of steps was equal to 10. The simulations were performed for turbulent flows (liquid water as the operating fluid), and Reynolds number (Re) range between 20000 and 60000 was selected. The zigzag channel showed a best thermal performance and the serpentine channel showed the best hydraulic performance. The thermal-hydraulic performance (THP) factor was employed for comparing the channels. As the complexity of the channels surfaces increased, the two parameters of convective heat transfer coefficient (positive factor) and pressure drop (negative factor) increased simultaneously. Therefore, predictive correlations for friction factor and Nusselt number were presented using genetic algorithm (GA), and the multi-objective optimization was performed to obtain the most appropriate Nusselt number and minimum friction factor as the two basic objective functions. The resulting Pareto set, which includes the optimum geometric dimensions of the heat exchangers, allows a designer to choice the geometries based on higher heat transfer or lower pumping power.

Nowadays, biomechanical methods are useful to identify the cause and treating of diseases. One of these diseases is the cerebral aneurysm. This disease starts by the inflation of artery wall and then by rupturing, it leads to intracranial hemorrhage. Therefore, it leads to morbidity or even it is the cause of the mortality for many patients. For this reasons, it is important to anticipate the emersion, growth and the rupture of a cerebral aneurysm. Computational fluid dynamics (CFD) and 2-way fluid-structure interaction (FSI) are common methods for interrogation the rupture of aneurysms and evaluating the effective hemodynamic parameters. In this study, they were employed to obtain appropriate information of a cerebral aneurysm. A patient-specific giant aneurysm was chosen in the internal carotid artery (ICA). Mooney-Rivlin parameters were used for the solid part and a non-Newtonian Carreu model was employed in the fluid part. Important hemodynamic parameters such as wall shear stress (WSS), time average wall shear stress (TAWSS), spatial average wall shear stress (SAWSS), oscillatory shear index (OSI), and relative residence time (RRT) were discussed. In addition, these methods were then compared and the number of cycles assessed to determine the accuracy of the solutions. Both methods illustrate a similar location for the risk of a rupture related to these hemodynamic parameters but with different quantities. The novelty of this works lies at the feasibility of using the FSI and CFD methods to show the cost function in the future clinical decision-making.