Design Technology of Centrifugal Fan Impeller Based on Response Surface Methodology

Zhu, Changyun; Qin, Guoliang

doi:10.1115/fedsm-icnmm2010-30002

Cited by 3 publications

(3 citation statements)

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“…[20][21][22][23] Some researchers have also used RSM in combination with experimental design methods for aerodynamic design. 24,25 A mathematical regression model approximating the objective function is constructed from the responses by using RSM. Since a traditional secondorder response surface does not provide the satisfactory approximation expected, an improvement is made in traditional RSM to acquire a more accurate mathematical model.…”

Section: Response Surface Methodologymentioning

confidence: 99%

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

Zheng

2014

Proceedings of the Institution of Mechanical Engineers, Part G:

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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.

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Section: Response Surface Methodologymentioning

confidence: 99%

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

Zheng

2014

Proceedings of the Institution of Mechanical Engineers, Part G:

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“…A second-degree polynomial regression model based on response surface methodology (RSM) is used to establish the correlation between the response and independent variables. This regression model is widely applied to the aerodynamic configuration design by many researchers [20,[43][44][45]. The output of a second-order polynomial RSM is expressed by Eq.…”

Section: Formulation Of the Regression Modelmentioning

confidence: 99%

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

Sharma

Baloni

2020

SN Appl. Sci.

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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.

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“…In the present case, a second-degree polynomial regression model based on response surface methodology (RSM) is used to establish the correlation between the response and independent variables. This regression model is widely applied to the aerodynamic configuration design by many researchers [23,[29][30][31]. The outcome of a second-order polynomial RSM is expressed by Eq.…”

Section: Formulation Of the Regression Modelmentioning

confidence: 99%

Design optimization of a compressor transition S-shaped duct using a teaching–learning-based optimization algorithm

Sharma

Baloni

2019

J Braz. Soc. Mech. Sci. Eng.

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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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Design Technology of Centrifugal Fan Impeller Based on Response Surface Methodology

Cited by 3 publications

References 0 publications

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

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

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

Design optimization of a compressor transition S-shaped duct using a teaching–learning-based optimization algorithm

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