A combinatorial optimization design method applied to S-shaped compressor transition duct design

Abstract

This paper presents a combinatorial optimization method based on uniform design in combination with response surface methodology and genetic algorithm. Uniform design is used to obtain experimental points and response surface methodology to establish a mathematical regression model. Subsequently, genetic algorithm is employed to acquire optimal solution of the objective function. The optimization method has been applied to a two-dimensional S-shaped transition duct design. The process is performed with two design variables. One defines the drop height ratio which describes wall profile, and the other depicts the length ratio between the axial length of the S-shaped transition duct and the duct inlet height. Total pressure loss coefficient as an aerodynamic performance parameter is selected as the objective function for optimization. The objective function is numerically assessed at design points sampled by uniform design in the experimental domain. The initial transition duct was designed with a radius-change to length ratio 11.6% larger than current engine design limits, and the optimization yields a decrease of 36.9% in total pressure loss and more uniform distributions of parameters at the outlet. The paper shows that the described optimization method can be applied to turbofan engines to increase the radial offset and decrease the axial design space between the fans and cores without jeopardizing performance.

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

“…To obtain the objective function and specified constraints, almost 117 numerical simulations have been carried out by altering all three variables by keeping area ratio unity for all cases. To obtain the 117 sets of numerical simulations, the ranges of independent variables are to select and are chosen as per available literature [18,20,39] and shown into Eqs. (9), (10), and (11), respectively.…”

“…The computational fluid dynamics (CFD) can be implemented as a design tool for performance evaluation with a combination of various optimization techniques [16]. Many researchers have reported that applying the response surface methodology (RSM) altogether with the design of experiments (DOE) may be a decisive and sturdy method for CFD-based optimization techniques [17][18][19][20]. Wallin and Eriksson [17] applied RSM together with DOE to the baseline S-shaped duct containing eight struts for minimizing the total pressure loss and achieved a 24% reduction of the total pressure loss.…”

“…Reduction of the total pressure loss by suppressing the peak deceleration in the strut-hub corner region could be achieved through an optimized non-axisymmetric end wall profile that is developed using the RSM approach [18,19]. Lu et al [20] exercised the combination of RSM and genetic algorithm (GA) to optimize the S-shaped duct and found a reduction of 36.9% in total pressure loss with higher uniformity at the outlet.…”

Study and Numerical Analysis of Compressor Transition Duct

“…Over the passage of time, researchers are trying to design the duct which is having less length and weight [4,[6][7][8][9][10]. The total pressure loss occurs at the bottom wall more than the casing wall due to instability [8].…”

“…The total pressure loss occurs at the bottom wall more than the casing wall due to instability [8]. Performance of the duct depends on operating conditions of the outlet guide vanes of a compressor [9].…”