The KSFM Journal of Fluid Machinery (한국유체기계학회 논문집)

Korean Society for Fluid machinery (한국유체기계학회)
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Optimization of a Cooling Channel with Staggered Elliptical Dimples Using Neural Network Techniques

신경회로망기법을 사용한 타원형 딤플유로의 냉각성능 최적화

  • 김현민 (인하대학교 대학원 기계공학과) ;
  • 문미애 (인하대학교 대학원 기계공학과) ;
  • 김광용 (인하대학교 기계공학부)
  • Received : 2010.08.12
  • Accepted : 2010.11.16
  • Published : 2010.12.01
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Abstract

The present analysis deals with a numerical procedure for optimizing the shape of elliptical dimples in a cooling channel. The three-dimensional Reynolds-averaged Navier-Stokes (RANS) analysis is employed in conjunction with the SST model for predictions of the turbulent flow and the heat transfer. Three non-dimensional geometric design variables, such as the ellipse dimple diameter ratio, ratio of the dimple depth to the average diameter, and ratio of the distance between dimples to the pitch are considered in the optimization. Twenty-one experimental points within design space are selected by Latin Hypercube Sampling. Each objective function values at these points are evaluated by RANS analysis and producing optimal point using surrogate model. The linear combination of heat transfer coefficient and friction loss related terms with a weighting factor is defined as the objective function. The results show that the optimized elliptical dimple shape improves considerably the heat transfer performance than the circular dimple shape.

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References

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