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Novel airside heat transfer surface designs using an integrated multi-scale analysis with topology and shape optimization.

Number: pap. 2117

Author(s) : BACELLAR D., AUTE V., HUANG Z. W., et al.

Summary

The major limitation of air-to-refrigerant Heat eXchangers (HX) is the airside thermal resistance which can account for more than 90% of the overall thermal resistance. The current research on heat transfer augmentation extensively focuses on the secondary heat transfer surfaces (fins). The main reason is that the heat transfer coefficient on the primary surfaces (tubes) is usually not sufficiently high to provide a minimum thermal resistance without significantly increasing the HX size. One contributing factor is the tube size; the reduction of the hydraulic diameter significantly improves performance and compactness. Another contributing factor is the shape of the tube itself, which is generally limited to circular, oval, or flat. In this paper, we investigate three novel surface concepts, using NURBS and ellipse arcs, focusing on the airside tube shape with small flow channels aiming at the minimization or total elimination of fins. The study constitutes designing a 1.0kW air-to-water HX, using an integrated multi-scale analysis with topology and shape optimization methodology. We leverage automated CFD simulations and Approximation Assisted Optimization (AAO), thus, significantly reducing the computational time and resources required for the overall analysis. The resulting optimum designs exhibit capacity similar to a baseline microchannel HX (MCHX), with same flow rates and 10% reduced approach temperature, more than 20% reduction in pumping power, more than 20% reduction in size. Experimental validation for a proof-of-concept design is conducted and the predicted heat capacity agrees within 5% of the measured values, whereas the airside pressure drop agrees within 10%.

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Pages: 9 p.

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Details

  • Original title: Novel airside heat transfer surface designs using an integrated multi-scale analysis with topology and shape optimization.
  • Record ID : 30018657
  • Languages: English
  • Source: 2016 Purdue Conferences. 16th International Refrigeration and Air-Conditioning Conference at Purdue.
  • Publication date: 2016/07/11

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