Annual Performance Prediction of Cool and Heat Trench in the Medical Facility

Bibliographic Information

Other Title
  • 実在医療施設に導入されたクール/ヒートトレンチの年間性能予測に関する研究
  • 第1報−長期実測と計算負荷を低減した非定常CFD解析による検証
  • Part 1-Performance Verification Based on Long-Term Actual Survey and Unsteady CFD Analysis That Reduced Calculation Load

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Description

<p>In recent years, passive cooling systems have been added to existing office buildings, thus bringing them to the public′s attention. Passive cooling systems, which control or utilize natural energy sources, can contribute to the cooling/heating of a building without the need for mechanical equipment. Cool and heat trenches, which are a type of earth-to-air heat exchanger, have often been adopted as a method of passive cooling and heating in relatively large office buildings. The pre-cooling and pre-heating effects of outdoor air on a cool and heat trench must be simulated over long periods of time by three-dimensional unsteady computational fluid dynamics (CFD) analysis. However, because of the limitations of the calculation load of flow fields, annual calculation of unsteady CFD analysis is difficult with conventional computers. In this study, an annual prediction method of pre-cooling and pre-heating performance for a cool and heat trench with an unsteady a CFD analysis, which did not analyze flow fields to reduce the calculation load, was proposed, and its validity was verified in comparison with a long-term actual survey. First, we evaluated the annual thermal performance of a cool and heat trench in a medical facility with a long-term actual survey. Secondly, the estimation of the thermal performance of this trench was also conducted based on with an unsteady CFD analysis that did not analyze flow fields. The following results were obtained: (1) The sensible heat load of an outdoor air-conditioning unit was reduced by 48.4% and 44.5% in summer and winter, and that the annual reduction ratio of cool and heat trench was 45.3%. (2) The prediction accuracy of the proposed method was verified by comparing the results with the long-term actual survey. It was confirmed that the proposed method had high prediction accuracy. (3) The calculation time was greatly reduced with the proposed method.</p>

Journal

Details 詳細情報について

  • CRID
    1390001206546551424
  • NII Article ID
    130006302010
  • DOI
    10.18948/shase.42.238_1
  • ISSN
    24240486
    0385275X
  • Text Lang
    ja
  • Data Source
    • JaLC
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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