| Project/Area Number |
17K14769
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Architectural environment/Equipment
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| Research Institution | Tokyo Institute of Technology |
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Principal Investigator |
Kawai Hidenori 東京工業大学, 環境・社会理工学院, 助教 (00735376)
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2019: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2018: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2017: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Keywords | 微気象 / 植栽 / 換気 / LES / 建物熱負荷計算 / 乱流構造 / CFD / パッシブクーリング / 自然換気・通風 / 熱環境 |
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| Outline of Final Research Achievements |
This study reveals characteristics of local micrometeorology around residential building by multi-point measurement system and analyzes thermal balance of garden planting located around ventilation window. For numerical simulation, coupling method of thermal radiation analysis and LES is presented and models of drag effect and sensible heat flux for garden planting are introduced to the presented model. Then, improvement effect on micrometeorology in residential areas by garden plantings is predicted by the coupling method. Finally, based on the measurement result of thermal balance for garden planting, prediction model of indoor climate considering the local distribution of air temperature caused by garden planting is presented. The presented model is applied to long-period prediction of indoor climate in summer and the improvement effect of indoor climate by garden planting located around ventilation window.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究で構築する解析手法において，数値流体解析結果を用いて建物近傍の外気温・湿度分布を推定することで室内熱環境改善効果が得られる植栽の種類の選定・配置や外構部材の設計方法が確立可能となる。さらに今後，数値流体解析によってとらえた風速場・温度場を建築内外の熱・水・空気のマクロな収支モデルに組み込むことで，住宅周囲の植栽による微気象の空間分布を考慮しながら数日～数か月単位にわたる室温・湿度変化を予測することが可能となり，屋内外を包括した熱環境改善手法の設計・評価が実現可能となる。
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