-A Bell type nozzle is most commonly used shape for rocket nozzles. This type of nozzle not only offers significant advantages in terms of size and performance over the conical nozzle but also reduces complexity compared to annular nozzles. The nozzle uses the stagnation temperature (To) and stagnation pressure (Po) generated in the combustion chamber to create thrust by accelerating the combustion gases to a high supersonic velocity. The nozzle expansion ratio was governed by the exit velocity. During flight, the jet flow is ideally expanded and adapted to the surrounding flow only during a short period. The rest of the time, the rocket engine operates in off-design conditions. The present work incorporates 2D axisymmetric flow analysis within the bell type nozzle, at design and off-design conditions, by using computational fluid dynamic software GAMBIT 2.4.6 and FLUENT 6.3.26. A computer code, with the use of the method of characteristics and stream function, is developed to define the higher efficiency nozzle contours for analysis. Simulation has been carried out separately for two different flow conditions i.e. cold and hot. Shear Stress Transport k-ω turbulence model has been chosen for flow analysis. The converged solutions captured asymmetric lambda shock in the nozzles at higher nozzle pressure ratios (NPR) for viscous flows. It also predicted aftershock and flow separation depending upon NPR. The strength of the normal shock, at Mach stem in viscous prediction, generally increases with an increase in NPR. Good agreement is observed between predicted simulation and analytical results in terms of shock structure, shock location, the size of normal shock, aftershock, and asymmetric lambda shocks.
A high-bypass turbofan engine transfers air from low-to the high-pressure compressor through an S-shaped transition duct. Minimization of the total pressure loss and maximization of uniform flow are key factors to ensure the maximum performance of the S-shaped transition duct. The conventional design approach is time-consuming and does not guarantee an optimal solution. Hence, the present article is based on the application of optimization for the S-shaped compressor transition duct. The optimization is carried out on the basis of shape parameters to minimize objectives namely pressure loss coefficient and non-uniformity with the reduction of length of the S-shaped transition duct. The 2-D axisymmetric approach of computational fluid dynamics is used as a design tool for performance evaluation with optimization techniques. The simulation model is validated with the available experimental results of the literature. The correlation between the response and independent variables is established with the help of the second-order polynomial response surface methodology. Further, individual optimization is carried out for single-objective consideration using particle swarm optimization and gray wolf optimization algorithms. As the results of single-objective optimization depict the conflicts between both objectives, later optimization using multi-objective particle swarm optimization and multi-objective gray wolf optimization algorithms is carried out. The performance metrics are obtained and compared. The 'TOPSIS' method is applied to get best solution out of multiple solutions. The optimized duct reduced pressure loss coefficient and non-uniformity index by 28.14% and 43.33% with a reduction of 6.37% of length compared to baseline S-shaped duct.
A high bypass turbofan aero-engine delivers compressed air from the low-pressure to the high-pressure compressor through a compressor transition duct. Weight and design space limitations impel to its S-shaped design. Despite that, the compressor transition duct has to guide the flow very carefully to the high-pressure compressor without disturbances and flow separations. Hence, the present paper is devoted to elaborate on the application of the proposed heuristic optimization technique known as multi-objective teaching-learning-based optimization (MO-TLBO) algorithm in the area of S-shaped transition compressor duct. The present algorithm is applied for obtaining the optimum design of the S-shaped duct while minimizing the total pressure loss coefficient and non-uniformity index at the S-shaped duct outlet. These objectives are also optimized independently and as a multi-objective consideration as well. Because of the conflicting nature of the objective functions, a Pareto-optimal curve is also presented for a successful trade-off between the objectives. Pareto-optimal curve gives flexibility to the designer for selecting the best set of the parameters based on the objectives. Successful execution of the proposed MO-TLBO algorithm is examined by comparing the optimum results acquired by the multi-objective genetic algorithm and comparisons divulge that the TLBO algorithm can be successfully practiced to obtain the optimized design of compressor transition S-shaped duct. Optimized duct shows the reduction in total pressure loss and non-uniformity by 28.80% and 36.67%, respectively, despite the reduction of 14.74% in overall length.
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