• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.11
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• pp.903-910
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• 2014

Electric fans, which consist of axial blades, are operated by the induction motor. In this paper, the objective of this study is the performance improvement of the base model fan using the design optimization. In order to aerodynamic analysis, computational simulations are performed using commercial tool ANSYS-CFX ver. 14.5. And k-${\omega}$ SST turbulence model is used for the CFD analysis. The design variables are set up as sweep and lean angles. Volumetric flow rate and torque of the fan blades are fixed to objective function. The optimized model is shown the increment of the volumetric flow rate and the reduction of the torque compared with the base model. The experimental procedure is followed KS C 9301. CFD results and experimental results are fairly well matched.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.30 no.7 s.250
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• pp.603-611
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• 2006

This paper presents the response surface optimization method using three-dimensional Wavier-Stokes analysis to optimize the blade shape of an axial flow fan. Reynolds-averaged Wavier-Stokes equations with $k-{\epsilon}$ turbulence model are discretized with finite volume approximations using the unstructured grid. Regression analysis is used for generating response surface, and it is validated by ANOVA and t-statistics. Four geometric variables, i.e., sweep and lean angles at mean and tip respectively were employed to improve the efficiency. The computational results are compared with experimental data and the comparisons show generally good agreements. As a main result of the optimization, the total efficiency was successfully improved. Also, detailed effects of sweep and lean on the axial flow fan are discussed.

• 유체기계공업학회:학술대회논문집
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• 2003.12a
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• pp.639-645
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• 2003

Design optimization of a transonic compressor rotor (NASA rotor 37) using response surface method and three-dimensional Navier-Stokes analysis has been carried out in this work. Baldwin-Lomax turbulence model was used in the flow analysis. Two design variables were selected to optimize the stacking line of the blade, and mass flow was used as a design variable, as well, to obtain new design point at peak efficiency. Data points for response evaluations were selected by D-optimal design, and linear programming method was used for the optimization on the response surface. As a main result of the optimization, adiabatic efficiency was successfully improved, and new design mass flow that is appropriate to an improved blade was obtained. Also, it is found that the design process provides reliable design of a turbomachinery blade with reasonable computing time.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.2690-2695
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• 2007

This work presents numerical optimization for design of a blade stacking line of a low speed axial flow fan with a fast and elitist Non-Dominated Sorting of Genetic Algorithm (NSGA-II) of multi-objective optimization using three-dimensional Navier-Stokes analysis. Reynolds-averaged Navier-Stokes (RANS) equations with ${\kappa}-{\varepsilon}$ turbulence model are discretized with finite volume approximations and solved on unstructured grids. Regression analysis is performed to get second order polynomial response which is used to generate Pareto optimal front with help of NSGA-II and local search strategy with weighted sum approach to refine the result obtained by NSGA-II to get better Pareto optimal front. Four geometric variables related to spanwise distributions of sweep and lean of blade stacking line are chosen as design variables to find higher performed fan blade. The performance is measured in terms of the objectives; total efficiency, total pressure and torque. Hence the motive of the optimization is to enhance total efficiency and total pressure and to reduce torque.