![10%
40%
30%
60%
70%
90%
日射透過優先
断熱優先
日射透過優先
断熱優先
モデル名 構成 熱貫流率[W/m??K] 日射取得率[-]
modelA E2-Ar12-FL2 1.44 0.66
modelB E2-Ar12-FL2 1.38 0.42
modelC E3-Ar16-FL3-Ar16-E3 0.73 0.56
modelD E3-Ar16-FL3-Ar16-E3 0.69 0.35
トリプルガラス
ペアガラス
窓の構成、および性能
[mm]10800
20%
50%
80%
7100
南立面図(窓面積率を示す)
60030003000500
2F
1F
床下
断面図
小屋裏
[mm]6300
热环境のシミュレーション](https://image.slidesharecdn.com/mori-170703053415/85/-20-320.jpg)
![24
いま考えていること１：この画像のデータベース
正射影画像
X(西)
Z(天空)
Y(南)
Q2
h
A
O
Q1
Q
250px
L
0
100
200
300
400
500
600
700
800
900
0
100
200
300
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時刻別水平面全天日射量 (energy-plus)[Wh/m?]
時刻別水平面全天日射量 (本手法)[Wh/m?]](https://image.slidesharecdn.com/mori-170703053415/85/-25-320.jpg)
![画像の特性を生かした補正
区分 距離範囲[m] スクリーン位置[m]
区分1 0～20 10
区分2 20～40 30
区分3 40～60 50
区分4 60～80 70
区分5 80～100 90
区分6 100～120 110
区分7 120～140 130
区分8 140～200 170
周辺建物 200～2000 200](https://image.slidesharecdn.com/mori-170703053415/85/-29-320.jpg)
北海道大学建筑环境学研究室での地図情报利用
- 3. Introduction about our lab. Lab. Of Building Environment, Graduate School of Eng., Hokkaido Univ. 2 Research topics are Energy conservation -> Residential and non- Residential building -> Data Center Planning and Evaluation of high performance housings Renewable energy PCM Fuel Poverty in Japan GIS Etc. 3 prof. and 20 students Prof. Hirofumi Hayama Assoc. prof. Taro Mori Assistant prof. Koki Kikuta
- 5. Research topics in this fiscal year, professors 1. Facility management 2. Investigation and evaluation on air-conditioning system for datacenter 3. Investigation and evaluation on healthy thermal environment for elderly facility 4. Evaluation on high efficiency air-conditioning system on office building and factory 5. Pre-heating system for ventilation by solar collector with PCM 6. Evaluation on urban thermal environment by using PV output 7. Fuel poverty in Hokkaido, counter plan for vacant houses in shrinking area 8. Numerical simulations of indoor climate and energy consumption with GIS data 9. R-housing project, R=Renovation 10. Development of ZEH in cold climate area 11. Improvement of working environment and energy consumption in office building 4
- 6. Research topics in this fiscal year, phD students 1. Tatematsu, NBRI, Improvement of energy consumption on high thermal performance houses in Hokkaido (finish) 2. Hirakawa, Dau co. ltd, LCA of RC apartment housings renovated with external insulation (finish) 3. Kohata, NTT-F, Evaluation of high-efficiency radiant ceiling cooling system coupled with 4. Uozumi, HSU, Evaluation of free cooling system in cold climate area 5. Futawatari, NTT-F, Evaluation on energy conservation in Data center with outdoor air cooling 6. Takada, excel-shanon window, Development of new plastic flame for high performance window system 7. Abe, NBRI, Research on possibility of district heating in rural area, Hokkaido 8. Koichi Shinagawa, Nihon sekkei co. ltd., Development of design method for ZEB in Japan 5
- 7. Chise (house for indigenous people) Thermal environment of CLT Evacuation facility Wood biomass PCM 6 GIS Low-energy houses Thank you for your attention
- 12. y = 0.44x + 0.04 R? = 0.15 0% 5% 10% 15% 20% 25% 30% 0% 10% 20% 30% 40% 空家率 高齢化率 S市地区別の高齢化率と空家率の相関図 高齢化率＝ その地区に75歳以 上の人がいる割合 N=143 国勢調査とのリンク
- 15. 14 20km 2km DSM
- 19. 18 都市形状
- 20. 10% 40% 30% 60% 70% 90% 日射透過優先 断熱優先 日射透過優先 断熱優先 モデル名 構成 熱貫流率[W/m??K] 日射取得率[-] modelA E2-Ar12-FL2 1.44 0.66 modelB E2-Ar12-FL2 1.38 0.42 modelC E3-Ar16-FL3-Ar16-E3 0.73 0.56 modelD E3-Ar16-FL3-Ar16-E3 0.69 0.35 トリプルガラス ペアガラス 窓の構成、および性能 [mm]10800 20% 50% 80% 7100 南立面図(窓面積率を示す) 60030003000500 2F 1F 床下 断面図 小屋裏 [mm]6300 热环境のシミュレーション
- 21. 热环境のシミュレーション
- 29. 画像の特性を生かした補正 区分 距離範囲[m] スクリーン位置[m] 区分1 0～20 10 区分2 20～40 30 区分3 40～60 50 区分4 60～80 70 区分5 80～100 90 区分6 100～120 110 区分7 120～140 130 区分8 140～200 170 周辺建物 200～2000 200
Editor's Notes
- I’m taro mori Hokkaido univ. thank you to give me the opportunity. Today id like to introduce the activity we are planning next summer with finish prof.s
- The artificial satellite makes this image everyday. The image show you the altitude of the land with buildings, trees , etc. We have high mountains in the southwest zone. The resolution of the image is very high, then we can magnify the image like this. This image shows you the city center area. As you see, we have some high rise building in city center.
- Then we can make urban geometry data by using GIS data. we need three data to make the models.
- We made two method to calculate thermal env and thermal load We make this image by using GIS data. We combine the image with solar position.
- We make building urban geometry by GIS data. We call it detail analysis. Method 1 can’t calculate the distribution of solar radiation. Also, ut has some errors
- We made two method to calculate thermal env and thermal load We make this image by using GIS data. We combine the image with solar position.