Design optimization of S-shaped compressor transition duct using particle swarm optimization algorithm

Abstract

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.

Portable non-battery pressure monitoring gloves for basketball sport analysis

“…But here, the movement of the hand will make the system design more complex and difficult. The S-shape structure is used in the line connection of the system to make the electric line have more extensibility [28]. With the help of the structure, the pressure sensing system is built on gloves.…”

Hybrid Nearest-Neighbor Ant Colony Optimization Algorithm for Enhancing Load Balancing Task Management

“…The MOO algorithm is used in connection with optimization problems that include more than one conflicting objective function to be optimized simultaneously [32]. Multiobjective problems, such as routing in communication networks [33,34], compressor design [35,36], engineering [37,38], and logistics [39], require a number of objective functions for simultaneous optimization [40].…”