This paper presents a successful approach in designing a Fuzzy Logic Controller (FLC) for a specific Jet Engine. At first, a suitable mathematical model for the jet engine is presented by the aid of SIMULINK. Then by applying different reasonable fuel flow functions via the engine model, some important engine-transient operation parameters (such as thrust, compressor surge margin, turbine inlet temperature, etc.) are obtained. These parameters provide a precious database, which train a neural network. At the second step, by designing and training a feedforward multilayer perceptron neural network according to this available database; a number of different reasonable fuel flow functions for various engine acceleration operations are determined. These functions are used to define the desired fuzzy fuel functions. Indeed, the neural networks are used as an effective method to define the optimum fuzzy fuel functions. At the next step, we propose a FLC by using the engine simulation model and the neural network results. The proposed control scheme is proved by computer simulation using the designed engine model. The simulation results of engine model with FLC illustrate that the proposed controller achieves the desired performance and stability.
In this paper, the effects of streamwise Nanosecond Dielectric Barrier Discharge (NS-DBD) actuators on Shock Wave/Boundary Layer Interaction (SWBLI) are investigated in a Mach 2.5 supersonic flow. In this regard, the numerical investigation of NS-DBD plasma actuator effects on unsteady supersonic flow passing a 14° shock wave generator is performed using simulation of Navier-Stokes equations for 3D-flow, unsteady, compressible, and
k
‐
ω
SST turbulent model. In order to evaluate plasma discharge capabilities, the effects of plasma discharge length on the flow behavior are studied by investigating the flow friction factor, the region of separation bubble formation, velocity, and temperature distribution fields in the SWBLI region. The numerical results showed that plasma discharge increased the temperature of the discharge region and boundary layer temperature in the vicinity of flow separation and consequently reduced the Mach number in the plasma discharge region. Plasma excitation to the separation bubbles shifted the separation region to the upstream around 6 mm, increased SWBLI height, and increased the angle of the separation shock wave. Besides, the investigations on the variations of pressure recovery coefficient illustrated that plasma discharge to the separation bubbles had no impressive effect and decreased pressure recovery coefficient. The numerical results showed that although the NS-DBD plasma actuator was not effective in reducing the separation area in SWBLI, they were capable of shifting the separation shock position upstream. This feature can be used to modify the structure of the shock wave in supersonic intakes in off-design conditions.
The present research investigates the effect of the location and the width of single shallow circumferential groove casing treatment on the flow field and the stability improvement of NASA Rotor 37 utilizing the help of computational fluid dynamics. At first, steady state simulation of Rotor37 was presented for smooth casing (without groove). Then, forty five various grooved casing were simulated and compared with the smooth casing. The results indicated that narrow grooves had slight effect on the adiabatic efficiency but as the width of the groove was increased, a decline in efficiency was observed. The investigation on the stall margin revealed that narrow grooves next to the leading edge could improve the stall margin by a reduction in the size of vortex breakdown zone. Medium-width grooves displayed an effective role in delaying the separation-produced by shock wave and boundary layer interaction-on the blade suction side near the casing. This type of grooves could improve the stall margin more than narrow grooves when located on the top of separation zone near the blade suction side. Wide grooves had negative effect on the stall margin and caused a significant drop in the efficiency and the total pressure ratio of the compressor.
This study deals with the application of optimization in Finocyl grain design with ballistic objective functions using a genetic algorithm. The classical sampling method is used for space filling; a level-set method is used for simulating the evaluation of a burning surface of the propellant grain. An algorithm is developed beside the level-set code that prepares the initial grain configuration using a computer-aided design (CAD) to export generated models to the level-set code. The lumped method is used to perform internal ballistic analysis. A meta-model is used to surrogate the level-set method in an optimization design loop. Finally, a case study is done to verify the proposed algorithm. Observed results show that the grain design method reduced the design time significantly, and this algorithm can be used in designing any grain type.
Modern techniques are required for many complex systems where increasingly strict performance and regulatory requirements must be achieved. In this paper, a genetic-fuzzy control is employed in order to meet the engine performance requirement and constraints. (Knowledge and understanding of the system behavior is an essential factor in control system development. Particularly, this factor is more serious for defining fuzzy membership functions and developing fuzzy rules which both are based on knowledge and experience of the controller designer. First, a successful approach based on Artificial Neural Networks (ANNs) is used for simulating the engine performance in a reversed manner, and achieving a set of suitable fuel flow functions. The fuzzified forms of these functions are used to produce first generation of chromosomes (fuzzy fuel functions). Indeed, the method of neural networks is used as an effective idea to define first generation of fuzzy fuel functions. Subsequently, tuning of the FLC parameters is obtained based on an optimization problem solved by a multiobjective genetic algorithm (GA). Finally, a fuzzy logic controller is developed using the engine simulation model, and the GA results. Simulation results of the optimized fuzzy controller, simple fuzzy controller and a conventional controller are presented to demonstrate the capability of proposed optimized fuzzy controller in achieving a fast engine response with consideration of all safety constraints.
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