computational fluid dynamic

Present work is a simulation of shock absorbers of aircraft landing gear. Equations are solved by finite element method and grid type is unorganized. Comparison with experimental data shows an error of about 5%. The results show that the displacement starts when the landing gear is pushed, which is observed in 0.05 seconds. In this case, the greatest stress comes to the base of the landing gear. By comparing this state with the previous state, it can be seen that it has increased at least tenfold. With the introduction of the shock absorber system, this tension is reduced. The reduction of the maximum stress from 3*108 to 1.6*108 pascal indicates the same thing. As the landing gear moves, the tension continues to decrease. It can also be seen that the range of relative displacement is very large at the beginning and even reaches 35 cm, but due to energy loss in the shock absorber and tires, it quickly disappears. So that after 0.45 seconds it is almost below 5 cm and after 0.7 seconds it is damped. 

With the advent of morphing airfoils, the aerodynamics of wind turbines and wings underwent many changes. In this study, the aerodynamic coefficients of morphing airfoil based on NACA 0015 are optimized in the range of Reynolds number 105 to 106 and the angle of attack 0 to 12 degrees using Artificial Neural Network (ANN) and Genetic Algorithm(GA). First, the airfoils were created in MATLAB software by random control points and mesh generated in Gambit software, then in two-dimensional Ansys software were simulated. The simulation results, including lift and drag coefficients, separation point and pressure center, with control points were used to train the Artificial Neural Network (ANN). The trained function is given as an input function to the Genetic Algorithm(GA) to optimize the desired coefficients.Lift coefficient, the center of pressure, separation point and lift to drag ratio were optimized as a single objective, In single-objective optimization, the lift coefficient was increased by 18% using the morphing airfoil. Also, the lift coefficient and the center of pressure, the lift coefficient and the drag coefficient were optimized as the dual-objectives optimization. In the optimization of the dual objectives, lift and drag coefficients were controlled by 0.8 and 0.03, respectively, by the morphing airfoils.

With the advent of smart materials in recent years, the aviation industry and airfoils have undergone many changes. Research into the use of smart materials in aircraft wings to increase their performance and then the use of smart materials in wind turbine airfoils has begun. In this study, computational fluid dynamics and URANS equations for a three-bladed Darrieus wind turbine equipped with a morphing airfoil was used to determine the optimum blade cross-section. 250 airfoils were generated by random control points, in Gambit software, they were unstructured and generated as a sliding mesh then they were simulated in 2D Ansys using the k-ω SST turbulence model and PISO algorithm. Control points and power coefficient were used for Artificial Neural Network (ANN)training and the Genetic Algorithm(GA) was used to optimize the power coefficient. In this study, the base airfoil is NACA0015. The results of that have been very effective. For the first case (Determine the optimal cross-section of the turbine at a full round) the power coefficient of Darrieus wind turbine with the optimal cross-section increased by 42%, and the blade section(airfoil) was also drawn. For the second case(Determine the optimal cross-section in each of the four zones of the rotor), the most efficient sections(airfoils) in four-zone were obtained, increasing the turbine power coefficient by 60% was the result of this optimization.

The change of the vapor to liquid phase, which is widely used in industry, is called condensation. Dropwise condensation(DWC) occurs on the hydrophobic and the super hydrophobic surfaces. Research has shown that the creation of micro-nanostructured structures on surfaces is one of the ways . The difference in temperature between the vapor and the liquid can lead to temperature gradient, which causes the convection Marangoni convection. This paper simulates a single drop on surfaces with Cassie and Wenzel structures in four different modes and a smooth surface, and the heat transfer rate for a single drop condensed on these surfaces is calculated in two modes with and without marangoni.The results show that the rate of heat transfer passing through the static drop in the case of the presence of marangoni is higher than the non-Maragoni mode. The rate of heat transfer from the droplet in the without-Marangoni state on the surface with the roughness of the cassie from the smooth surface is 350% ,And the smooth surface is 128% higher than the surface with the roughness of the the Wenzel. In the case of Marangoni, the mode of change of heat transfer rate from these surfaces is affected by the contact angle of the drop on the surface.

The dual fuel diesel engine (DDF) is a one of the various IC engine that can used alternative fuel for power generation. Emission and fuel consumption reduction are some of the properties that use a combination of fuel mixture in dual fuel diesel engine (gas-diesel). We focused in this research to study the effect of start of injection (SOI) and blend of fuel variation in OM355 EU2 dual fuel diesel engine at two various speeds with the help of the computational fluids dynamic. The modeling of the artificial neural network (ANN) has been used to study the interaction effects of SOI and blend of fuel on the operational parameters. The non-sorted genetic algorithm (NSGA II) has been used for determining the optimized levels of the variables. The results of this study show that the RBFNN has acceptable predictions about the outputs’ variables (R^2=0.99 ,RMSE=0.01), and the optimized range of the engine function in the specific speeds has been attained with the help of the responding surface of the neural network. Besides, the optimizing capabilities of the NSGA II have provided the optimized levels of the input and output variables in the various speeds.

Today, due to the various usage of compression ignition engines in urban transportation, as well as the need to reduce exhaust emissions and control fuel consumption, the use of alternative fuels has become common in diesel engines. Gaseous fuel is one of the most common alternative fuels that can be used in diesel engines. The utilization of alternative fuels in compression ignition engines requires the study of the combustion quality and the type of flammable mixture formation in the combustion chamber. Fuel injection parameter play a significant role in the combustion quality of dual-fuel diesel/gas engines. The injection timing and gaseous fuel mixing percentage together are among the parameters associated with fuel injection. In order to investigate the effect of fuel injection timing on the combustion quality of dual-fuel diesel / gas engines, a study was conducted. In this research, dual-fuel diesel engine is evaluated at two different speeds using the CFD method. To this research, three modes were selected for the fuel IT: BTDC 22°, BTDC 18° and BTDC 14° and three modes for gaseous fuel mixing percentage: 90%-10%, 85%-15% and 75%-25%. The results of numerical studies showed that with increasing fuel injection timing in a diesel / gas dual-fuel engine, the combustion chamber temperature and cylinder pressure peak (PCP) was increased. Increasing the IT also increased the ignition delay, diesel Knocking and distanced the PCP curve from TDC. The IMEP and output torque increased by 16% as the PCP increased. As the mass flow rate of pilot fuel increased, the ignition delay decreased, causing the PCP to fall. The output torque and indicator power decreased by 17% and 70% respectively. Reducing the fuel IT at high speed, the indicator power improved and the emission results showed that the IT advancing increased the NOx and CO2 by 31% and 16% respectively, indicating improved combustion quality in the dual-fuel diesel engine.

A Rod Baffle shell-tube heat exchanger was simulated using HTRI software and Computational Fluid Dynamics (CFD). The results from both models were compared with available experimental data. In addition, the effects of distance of baffles and cold fluid’s velocity on the heat exchanger’s performance were analyzed. The obtained results showed that decreasing the distance between baffles can improve the heat transfer. However, diminution of this distance more than a threshold can lead to a significant reduction in the heat transfer. By comparing the two employed methods for simulation of shell-tube heat exchangers with bar baffles, one can say that the use of HTRI software is easier and faster than the CFD method and achieves acceptable responses, on the other hand, the CFD results are more accurate. Furthermore, the details of the temperature and velocity profiles of the fluid inside the heat exchanger can be calculated and analyzed. The results of this research can be an effective step in developing the application of this type of heat exchanger and redesigning of it.

Heat exchangers that use the Maisotsenko Cycle have high efficiency despite using evaporative cooling. Therefore, in this study, based on computational fluid dynamics, the simulation of the Maisotsenko Cycle has been investigated. In this paper, the effects of all operational parameters such as temperature, inlet air huidity, air velocity in wet and dry channels, as well as geometric parameters such as the length of the heat exchanger and the height of the channels on the efficiency of heat exchanger have been studied. The simulation results showed that the heat exchanger has a favorable efficiency in different climatic conditions, so that wet efficiency for this heat exchanger varies from 103 to 115, but the increase in humidity will reduce the efficiency and the effectiveness of the heat exchanger.Also, the results showed that an increase in the velocity inside the dry and wet channels, respectively, decreases and increases the efficiency. Finally, the optimum ratio of the mass flow rate of wet channel to dry one is determined to be 1.3.