ali madadi

This research aims to find suitable measurements to detect the occurrence of turbine erosion in Micro Gas Turbine engines. For this purpose, the off-design operation of this engine under the turbine's normal and eroded conditions has been modeled and the behavior of different parameters of the gas path has been analyzed. Turbine erosion is one of the most popular issues in gas turbine performance degradation. Accordingly, to have proportional health condition monitoring and diagnostics, it is necessary to know the effects of turbine erosion. Characteristic curves of an eroded turbine is utilized by the proposed off-design model to find the best parameters to detect turbine erosion. In the course of this research, two operation scenarios, one with maintaining the output power and the other with maintaining turbine inlet temperature, are examined. In both scenarios, the running line shifts to a new location with higher airflow and lower pressure ratio. When turbine inlet temperature is maintained, fuel flow, pressure ratio, and output power fall dramatically (9.8%, 11.1%, and 14.3% respectively) while in the other scenario temperature in the combustion chamber inlet and the turbine exhaust with 7% and 7.6% rise and pressure ratio with 4.4% reduction show most deviations from the healthy condition. So depending on the control scenario, the proper parameters can be selected from these sensitive parameters to detect turbine erosion in the Micro Gas Turbine.

The salient aim of this paper is the shape optimization of an airfoil equipped with Gurney-Flap for aerodynamic performance improvement. The optimization of the slotted Gurney-Flap for improving the aerodynamic efficiency and increasing the lift force of NACA 0012 is the novelty of this research. The Genetic Algorithm, Artificial Neural Network, and Computational Fluid Dynamics are employed for shape optimization. The optimization variables include the height and thickness of the GF; also, the thickness and position of the slot. All analyses have been conducted at Re=0.45×106 and AOA=8o to simulate the take-off phase. After validating numerical results, the optimization process was conducted with two different fitness functions of lift force and aerodynamic efficiency. According to the results, the geometry representing an optimized lift coefficient compared to the geometry with optimized aerodynamic efficiency has a considerably higher height. Furthermore, the thickness of the slot in the first geometry is lower than the second geometry. The first optimized geometry leads to a 21.64 percent lift coefficient increment; there is a 293 percent increment in aerodynamic efficiency due to the second optimized geometry. As a result, it can be indicated that the help of slotted optimized Gurney-Flap can provide the required lift force for Short Take-Off Landing distance.

In complicated systems such as satellites, each subsystem's design can affect the design of the overall system. In the design procedure, the effect of each technology on the other components should be determined. Because of the increase in space trash, the propulsion subsystems are introduced to avoid collision in space. One of the methods to attain high altitude orbits is flight maneuvers using propulsion systems. Several types of propulsion systems are utilized in satellites. Resistojets can be employed as low-cost propulsion systems for satellites because they do not use complicated technologies. In the present research, a resistojet propulsion system is designed for a CubeSat for the mission of orbital altitude reduction. The propellant is selected considering all properties. The design of the nozzle and the heater is also introduced. The overall layout of the system is presented. In the end, an algorithm is proposed for electrical propulsion systems for a specified mission.

A new iterative learning controller is proposed for a general unknown discretetime-varying nonlinear non-affine system represented by NARMAX (Nonlinear Autoregressive Moving Average with eXogenous inputs) model. The proposed controller is composed of an iterative learning neural identifier and an iterative learning controller. Iterative learning control and iterative learning identification are integrated in each iteration. A multi-layer neural network is used for identification. Since the system considered in this paper is time-varying, the proposed neural identifier also is time-varying. The weights of the neural identifier are updated at each iteration, so both tracking performance and identification are improved at each iteration simultaneously. The structure of the proposed neural network used for identification system is affine in control input. Then new iterative learning control law based on the neural identifier is proposed and applied to the system. It should be mentioned that the proposed integrated algorithm has a faster, better and more accurate performance when compared with other iterative learning control algorithms proposed for similar systems. Convergence of both the trajectory tracking error and identification error is guaranteed along the iteration domain with repeating the process within a time-limited range. Simulation and comparison results easily approve the effectiveness of the proposed method.

The intake is part of the aircraft, which provides air to the engine uniformly and with a minimum total pressure loss. Today, due to the abundant application of S-shaped inlet, optimization of these inlets has been considered by the researchers. The uniform distribution of the flow at the inlet of the compressor has a direct effect on engine performance. On the other hand, the separation of the flow through the duct reduces the pressure recovery and the engine thrust. In this article, an S-duct intake has been optimized to reduce the total pressure loss and flow distortion. The neural network, coupled with the genetic algorithm, is used to optimize the objectives in the shortest possible time. Two optimizations have been done. In the first case, new geometries have been generated by changing the center line coordinate and the cross-sectional area ratios. The first optimization results in an enhancement of 32.5% for pressure recovery coefficient and a reduction of 35.8% for flow distortion. In the second optimization, the length of the duct has also been decreased. By decreasing the length of the duct, the weight of the aerial vehicle is reduced, and on the other hand, the useful space inside the body is increased. This optimization gave an enhancement of 35.96% for pressure recovery coefficient and a reduction of 39.4% for flow distortion and a 25% reduction in the duct length.

Usually, ground testing of space engines is performed in high altitude test facility. The facility is equipped with a supersonic diffuser that expels automatically engine gases to the atmospheric pressure and maintains a vacuum pressure around its nozzle and motor. If the motor pressure is lower than a certain amount, the supersonic flow in the diffuser will not be established. In this situation, it is necessary to use auxiliary ejector at the end of the diffuser. In the present study, a new algorithm has been developed in the design of supersonic ejector. Unlike conventional methods, this algorithm can be used for different primary (input from the ejector nozzle) and secondary fluids (outlet from the diffuser end). In the design of the ejector, the main parameters are determined by the algorithm, while the secondary parameters are selected from the empirical test results of the proved references. In this algorithm, a safe margin is considered for the safe operation of the ejector and this margin is predicted by numerical simulation. Also, numerical simulation is used to validate the design method. Finally, using the proposed algorithm, an ejector is designed to reduce the start-up pressure of an engine-diffuser assembly. An integrated simulation of the diffuser-ejector was performed for both cases that rocket motor is off and on, and the appropriateness of the designed ejector was confirmed in both modes of operation