:::

詳目顯示

回上一頁
題名:以環境風場為導向之工業區建築配置研究
作者:游振偉
作者(外文):Cheng-Wei Yu
校院名稱:中國文化大學
系所名稱:建築及都市設計學系
指導教授:邱英浩
學位類別:博士
出版日期:2020
主題關鍵詞:計算流體力學CFD
原始連結:連回原系統網址new window
相關次數:
  • 被引用次數被引用次數:期刊(1) 博士論文(0) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:1
  • 共同引用共同引用:0
  • 點閱點閱:2
近年全球暖化、極端氣候導致環境氣候變遷劇烈,聯合國永續發展目標為規劃界關注焦點,減少能源消耗與適應環境之建築設計理念已成現今主流,國內亦藉綠建築政策鼓勵建築提高所使用資源效率,以及減低對環境與人體健康之影響。根據相關研究,良好之環境風場由於換氣效果較佳,能減緩區域性之空氣污染問題,並可改善環境熱舒適度。目前已有許多關於都市地區環境風場之相關研究,但對濱海工業區環境之研究則相對較少,而濱海工業區風力強勁,如何維持良好風環境品質更為重要,因此本研究將以濱海工業區之環境風場進行建築配置原則之研究。
本研究理論包含計算流體力學(Computational Fluid Dynamics,CFD)、熱舒適理論、通風效益,與無因次分析。CFD是運用數值方法解出流體力學的控制方程式,並可透過不同的邊界條件,進而預測流場的流動;熱舒適理論為說明人體對於四種物理環境因素(氣溫、輻射溫度、風速、濕度)與兩種人為因素(代謝率、衣服保溫)的熱平衡關係;通風效益探討街谷內與建築室內空氣交換之效益;無因次分析則用來探討物理量之間的關係,運用在探討大氣氣候與微氣候兩者之間的關係。本研究以歸納法分析關於研究主題之相關文獻,再透過實測蒐集基礎數據,以Fluent軟體以數值模擬法分析基地戶外物理環境與計算熱舒適度,並比對驗證實際量測之數據與CFD模擬之數據,驗證CFD模擬數據之可信賴度,進而調整CFD模型不同條件下的變因,並以無因次分析法呈現數據之間關係,再根據分析結果,擬定最佳化風場之建築配置原則。研究結果顯示街谷高寬比(H/W)以0.1為最佳,並不超過0.3為宜,建築配置以單開口配置為最佳,並建議避免採用錯列配置。
Global warming has caused severe world climate variability in recent years. In responding to this, to follow the UN Sustainable Development Goals (SDGs), and to design architectural project associated with concepts of the energy consumption reduction and environment adaptation, are becoming the focused streams in planning and architect fields. Concurrently in Taiwan, a Green Building promotion program is being used as a major policy to encourage efficient usage of building resource, and to reduce the harmful environmental effects, such as the effect of air pollutant to human health. This kind of regional air pollution problems, as well as some thermal comfort issues, according to several related studies, can be alleviated and improved by air flow exchange of well environmental ventilation. Although certain amount air field studies have been conducted to follow the Green Building policy, they were mainly conducted at urban areas. Studies for coastal industrial district where there usually bears strong monsoon wind are still limited. How to maintain a better quality of air environment in coastal industrial district is an important issue, and this motivates the present study to find principles for industrial district building layout.
Based mainly on the concepts of the “thermal comfort theory,” and “ventilation efficiency,” this study tries to reveal answers for climate and macro-climate interacting problem through two tools. Thermal comfort theory displays the satisfaction of human perception by the four physical factors: air temperature, radiant temperature, wind speed, humidity; and by the two human attached factors: metabolic rate and clothing insulation. Ventilation efficiency, the second concept, is to show the effectives of air flow exchange rate between street canyon and adjoined buildings. About the two tools, they are dimensional-analysis and computational fluid dynamics modelling (CFD). Dimensional analysis is to find dimensionless parameters, for example, the street canyon aspect ratio, such that physical quantities gathered from field measurement and from literature review can be corelated using them. The CFD tool, this study adopts the Fluent package to form a numerical model, with properly introduced flow and boundary conditions, such as building dimension and optimized air field, to represent a physical field. After being verified with measured physical data, this model can be used to simulate scenarios and to examine the thermal comfort indexes generated by these scenarios. From examination of non-dimensional outcomes of these scenarios, the advantage and demerit of industrial district building layout principle can then be evaluated.Through the evaluations, the research results show that 0.1 is the best height-to-width ratio (H/W), and it is not more than 0.3. The best building configuration is single-opening configuration, and it is recommended to avoid staggered configuration.
參考文獻
1.Chiu,Y.H.,D.W.Etheridge(2007).External flow effects on the discharge coefficients of two types of ventilation opening.Journal of Wind Engineering and Industrial Aerodynamics,95,225-252.
2.Chiu,Y.H.、Chiang;Y.C., Chen,Y.(2017).Insights into Adaptive Thermal Comfort on Learning Efficiency of Students – A Classroom-based Case Study. Ergonomics International Journal, 1/4
3.Fanger, P. O. (1970). Thermal Comfort. Analysis and Applications in Environmental Engineering.
4.Ghiaus, C., Allard, F., Santamouris, M., Georgakis, C., Nicol, F. (2006). Urban environment influence on natural ventilation potential. Building and Environment, 41, 395-406.
5.Harman IN, Barlow JF, Belcher SE (2004) Scalar fluxes from urban street canyons part II: model. Bound-Layer Meteorol 113(3):387–409
6.Honjo, T. (2009). Thermal Comfort in Outdoor Environment. Global Environmental Research (13), 43-47.
7.Hu, C.-H., Wang, F. (2005). Using a CFD approach for the study of street-level winds in a built-up area. Building and Environment, 40, 617-631.
8.Krüger EL, Minella FO, Rasia F (2011) Impact of urban geometry on outdoor thermal comfort and air quality from field measurements in Curitiba, Brazil. Build Environ 46:621–634
9.Lateb M, Meroney RN, Yataghene M, Fellouah H, Saleh F, Boufadel MC (2016) On the use of numerical modelling for near-field pollutant dispersion in urban environments − A review. Environ Pollut 208(A):271–283
10.Matzarakis, A., Amelung, B. (2008). Physiological Equivalent Temperature as Indicator for Impacts of Climate Change on Thermal Comfort of Humans. Seasonal Forecasts, Climatic Change and Human Health, 30, 161-172.
11.Matzarakis, A., Mayer, H., Iziomon, M. G. (1999). Applications of a Universal Thermal Index: Physiological Equivalent Temperature. International Journal of Biometeorology, 43(2), 76-84.
12.Mohammadreza Shirzadi, Mohammad Naghashzadegan, Parham A. Mirzaei (2018). Improving the CFD modelling of cross-ventilation in highly-packed urban areas. Sustainable Cities and Society,37, 451-465.
13.Nestoras Antoniou, Hamid Montazeri, Marina Neophytou, Bert Blocken (2019). CFD simulation of urban microclimate: Validation using high-resolution field measurements. Science of The Total Environment, 695, 133743.
14.Qin, Hongqiao, Hong, Bo, Jiang, Runsheng (2018). Are Green Walls Better Options than Green Roofs for Mitigating PM10 Pollution? CFD Simulations in Urban Street Canyons. Sustainability 10(8):2833.
15.Shouzhi, Chang, Jiang, Qigang, Zhao, Ying (2018). Integrating CFD and GIS into the Development of Urban Ventilation Corridors: A Case Study in Changchun City, China. Sustainability 10(6):1814.
16.Silvana Di Sabatino, Riccardo Buccolieri, Beatrice Pulvirenti, Rex Britter (2007). Simulations of pollutant dispersion within idealised urban-type geometries with CFD and integral models. Atmospheric Environment, 41(37), 8316-8329.
17.Siple P (1958) quoted in: Cold Injury. Steven Horvath editor, Josiah Macy Foundation, p 216
18.Sun CY (2011) A street thermal environment study in summer by the mobile transect technique. Theor Appl Climatol 106:433–442
19.Takahashi, K., Yoshida, H., Tanaka, Y., Aotake, N., Wang, F. (2004). Measurement of thermal environment in Kyoto city and its prediction by CFD simulation. Energy and Buildings, 36, 771-779.
20.Toparlar Y, Blockena B, Maiheub B, van Heijstd GJF (2017) A review on the CFD analysis of urban microclimate. Renew Sust Energ Rev 80:1613–1640
21.Tzu-Ping Lin, Shing-Ru Yang, Yung-Chang Chen, Andreas Matzarakis (2018). The potential of a modified physiologically equivalent temperature (mPET) based on local thermal comfort perception in hot and humid regions. Theoretical and Applied Climatology,135,873–876.
22.Tzu-Ping Lin, Yu-Cheng Chen, Andreas Matzarakis (2017). Urban thermal stress climatic mapping: Combination of long-term climate data and thermal stress risk evaluation. Sustainable Cities and Society, 34, 12-21.
23.Vranckx, S., Vos, P., Maiheu, B., Janssen, S. (2015). Impact of trees on pollutant dispersion in street canyons: A numerical study of the annual average effects in Antwerp, Belgium. Science of the Total Environment, 532, 474-483.
24.Xiaomin, X., Zhen, H., Jiasong, W. (2006). The impact of urban street layout on local atmospheric environment. Building and Environment, 41, 1352-1363.
25.Xiaoxue Wang, Yuguo Li (2016). Predicting urban heat island circulation using CFD. Building and Environment, 99, 82-97.
26.Yang W, Wong NH, Li QC (2016) Effect of street design on outdoor thermal comfort in an urban street in Singapore. J Urban Plann Dev 142(1):05015003
27.Yoshihide Tominaga, Ted Stathopoulos (2013). CFD simulation of near-field pollutant dispersion in the urban environment: A review of current modeling techniques. Atmospheric Environment, 79, 716-730.
28.Yu, C.W.; Chiu, Y.H.(2019). Environmental-comfort building layout principle for a coastal industrial park. Theoretical and Applied Climatology. 138(1), 1013-1023.
29.方富民、陳瑞鈴、黎益肇、陳建忠、郭建源(2018),建築學報(103),17-34。
30.朱佳仁(2006),風工程概論,台北:科技圖書股份有限公司。
31.朱佳仁、邱英浩、陳彥志、王宇文(2009),建築物開口對風壓通風影響之研究,建築學報(69),17-33。
32.朱佳仁,王宇文,陳瑞鈴,黎益肇,劉文欽(2011),多區間建築物風壓通風計算模式之研究,建築學報(78),107-121。
33.李偉誠、謝俊民(2011),連棟住宅之街谷比對街谷內風環境之影響-以台南市氣象資料爲例,建築學報(75),135-153。
34.周伯丞、江哲銘(2005),不同空調通風路徑對工作空間室內污染物移除效果之比較,建築學報,54,41-55。
35.林君娟、謝俊民、程琬鈺(2010),建立都市住宅風環境舒適度指標與改善策略評估-以台南市大林住宅都市更新地區為例,建築與規劃學報,11(3),221-241。
36.邱英浩(2011),建築配置形式對戶外空間環境風場之影響,都市與計劃,38(3),303-325。
37.邱英浩(2012),透水面積比例對環境微氣候之影響:以中興新村南核心區為例,都市與計劃,39(3),297-326。
38.邱英浩、陳慶融、陳佳聰(2014),封閉式中庭舖面類型及尺度對微氣候之影響,都市與計劃,41(4),395-427。
39.邱英浩、陳智仁、劉天祥 (2019),街道尺度與建築配置對室内自然通風效益之影響,建築學報(108),59-79。
40.邱英浩、吳孟芳(2010),不同街道尺度對環境風場之影響,都市與計劃,37(4),501-528。
41.邱英浩、吳孟芳、譚政泓(2008),不同街谷形式對都市風場之影響,建築與規劃學報,9(2),141-165。
42.邱英浩、黃政達(2008),以CFD探討住宅單元單開口通風之效能,建築與規劃學報,9(3),169-192。
43.林憲德、孫振義(2006),台南地區都市熱島強度全年變動之研究,都市與計劃,33(1),51-68。
44.林家伃 (2014),喬木條件配置對風環境之影響研究(碩士論文)。中國文化大學,台北市。
45.林家伃、邱英浩、游振偉(2016),植栽與建築物配置對風環境之影響,建築學報,95,87-102。
46.陳慶融、邱英浩(2015),植栽對戶外熱舒適之影響研究,建築學報,92,43-60。
47.張瑋如(2006)。兩層樓建築物橫流型自然通風模式的CFD研究。建築學報,56,133-149。
48.孫振義(2017),熱季街道環境與熱舒適性關係之研究,都市與計劃,44(4),375-397。
49.蔡繼堯(2017),以環境風場為導向之廠房配置研究-以濱海工業園區為例(碩士論文)。中國文化大學,台北市。
50.賴湘文、邱英浩、高立新、王价巨(2016),都市街廓特徵與人體熱舒適之關係研究,都市與計劃,43(1),89-114。
51.蘇瑛敏,張惠婷(2017),亞熱帶騎樓形式對於戶外行人舒適度影響之研究,建築學報,101,39-58。
52.蘇瑛敏、李仲翊(2019),透空式高層建築對都市街谷中污染物擴散之影響,物業管理學報,10(2),1-15。


 
 
 
 
第一頁 上一頁 下一頁 最後一頁 top
QR Code
QRCODE