著者
足永 靖信 河野 孝昭
出版者
一般社団法人 日本風工学会
雑誌
日本風工学会年次研究発表会・梗概集 平成18年度日本風工学会年次研究発表会
巻号頁・発行日
pp.115-120, 2006 (Released:2006-09-23)

本研究では、地球シミュレータを都市環境問題に初めて活用することにより、個々の建物を解像したヒートアイランド解析に取り組んだ。今回は新たに解析モデルを開発し、都市部の熱環境解析の一例として、水平5mメッシュの解像度で汐留の再開発エリアを含む5km四方領域の熱環境解析を実施した。そして、超高層ビル群による熱環境の影響について考察を行った。超高層ビル群がある場合は、超高層ビル群の前方から後方の広範な領域で風速5m/s以下であり、特に下流側では風速2m/s以下に風速が低下した。これに対応して、広い範囲にわたって気温が上昇した。本解析では、超高層ビル群による影響がビル高さの数倍に相当する風下1kmの広範な領域に及んでいることが示された。
著者
森山 正和 宮崎 ひろ志 吉田 篤正 竹林 英樹 足永 靖信 成田 健一 依田 浩敏 土井 正一
出版者
一般社団法人日本建築学会
雑誌
日本建築学会技術報告集 (ISSN:13419463)
巻号頁・発行日
no.15, pp.199-202, 2002-06-20
被引用文献数
2

The thermal environments of the three types of urban blocks were observed on the street in Osaka in the summer season. Air temperature and surface temperature of each urban block were high in comparison with Osaka Castle Park. Temperature differences of urban blocks in the daytime were bigger than those in the early morning. MRT was influenced by the sky and green cover ratio strongly, and in the street whose sky cover ratio was small that it was surrounded by a high-rise building MRT became small. And in the street whose green cover ratio was big by the street trees MRT was small compared with other streets. SET each urban block takes the influence of MRT strongly, SET of small, and it was improved as a thermal environment because the comparatively big amount of ventilation was secured in the street whose width was big like OBP (Osaka Business Park) in the daytime.
著者
足永 靖信 阿部 敏雄
出版者
日本建築学会
雑誌
日本建築学会環境系論文集 (ISSN:13480685)
巻号頁・発行日
vol.72, no.614, pp.65-70, 2007
参考文献数
14
被引用文献数
2 1

The climatic response of cities to the heat island effect is thought to vary by city size and location. In this paper, we analyzed weather data for representative Japanese cities from 1961 onwards and examined characteristics of time series meteorological data statistics such as annual number of tropical nights. The number of winter days decreased, and the number of summer nights, tropical nights and extremely hot days increased in all cities. As a result of principal component analysis, the rise of temperature was identified as the first principal component, and the decline of the daily range of temperatures was identified as the second principal component. A cluster analysis using the first four principal components categorized the 16 Japanese cities into four sets. Factors related to the results of the principal component are discussed with the aid of multiple regression analysis. Numerical results show that the magnitude of the first principal component is described by latitude and distance from the sea, the magnitude of the second principal component is described by the logarithm of the DID (Densely Inhabited District) population and distance from the sea.