東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Modeling Thermal Comfort in Outdoor ...

Lai, Dayi.

FindBook

Google Book

Amazon

博客來

Modeling Thermal Comfort in Outdoor Environments.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Modeling Thermal Comfort in Outdoor Environments./
作者:	Lai, Dayi.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:	181 p.
附註:	Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.
Contained By:	Dissertation Abstracts International78-12B(E).
標題:	Engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10272335
ISBN:	9780355089608

Modeling Thermal Comfort in Outdoor Environments.
Lai, Dayi.

Modeling Thermal Comfort in Outdoor Environments. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 181 p.

Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.

Thesis (Ph.D.)--Purdue University, 2017.

This investigation first conducted field surveys about outdoor thermal comfort in Tianjin, China by monitoring microclimates and interviewing subjects in a park. Although the outdoor thermal environment varied greatly with air temperature from -5.0 to 34.5°C, a total of 83.3% of respondents considered the overall comfort to be "acceptable". A "slightly warm" sensation was perceived to be the most comfortable during the cold season, "neutral" in the shoulder season, and "slightly cool" in the hot season. This study evaluated the three most widely used thermal comfort models in outdoor thermal comfort studies. The Predicted Mean Vote (PMV) overestimated the thermal sensation by 1.3 times. The neutral Physiological Equivalent Temperature (PET) range found in this study was 11--24°C, which was significantly different from the ranges found in Europe and Taiwan. The Universal Thermal Climate Index (UTCI) provided a satisfactory prediction of thermal comfort within the scope of our study, but the UTCI thermal sensation range derived in our study differs from the range found in Mediterranean climates. These results indicate that these models are not accurate when predicting outdoor thermal comfort.

ISBN: 9780355089608Subjects--Topical Terms:

586835
Engineering.

Modeling Thermal Comfort in Outdoor Environments.
LDR:06147nmm a2200361 4500 001 2156701
005 20180517121919.5
008 190424s2017 ||||||||||||||||| ||eng d
020 $a 9780355089608
035 $a (MiAaPQ)AAI10272335
035 $a (MiAaPQ)purdue:21328
035 $a AAI10272335
040 $a MiAaPQ $c MiAaPQ
100 1 $a Lai, Dayi. $3 3344464
245 1 0 $a Modeling Thermal Comfort in Outdoor Environments.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2017
300 $a 181 p.
500 $a Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.
500 $a Adviser: Qingyan Chen.
502 $a Thesis (Ph.D.)--Purdue University, 2017.
520 $a This investigation first conducted field surveys about outdoor thermal comfort in Tianjin, China by monitoring microclimates and interviewing subjects in a park. Although the outdoor thermal environment varied greatly with air temperature from -5.0 to 34.5°C, a total of 83.3% of respondents considered the overall comfort to be "acceptable". A "slightly warm" sensation was perceived to be the most comfortable during the cold season, "neutral" in the shoulder season, and "slightly cool" in the hot season. This study evaluated the three most widely used thermal comfort models in outdoor thermal comfort studies. The Predicted Mean Vote (PMV) overestimated the thermal sensation by 1.3 times. The neutral Physiological Equivalent Temperature (PET) range found in this study was 11--24°C, which was significantly different from the ranges found in Europe and Taiwan. The Universal Thermal Climate Index (UTCI) provided a satisfactory prediction of thermal comfort within the scope of our study, but the UTCI thermal sensation range derived in our study differs from the range found in Mediterranean climates. These results indicate that these models are not accurate when predicting outdoor thermal comfort.
520 $a Previous thermal comfort models can only give a single value prediction of the occupant's thermal comfort. However, due to great spatial and time variability of outdoor thermal environments, the thermal comfort for a group of people in an outdoor space has a wide distribution. To address this issue, this study applied the econometric and statistics method and developed an ordered probability model for outdoor thermal comfort by using the observations obtained from field surveys in Tianjin, China. This model can calculate the thermal sensation vote (TSV) distribution and can thus provide more information than traditional models. Air temperature (Ta), global solar radiation (G), wind speed (Va), the metabolic rate of occupants (MET), clothing (CLO), and the hot day indicator (HOT) were found to significantly affect the TSV distribution. The model performance test shows that the average difference between the predicted and sampled probability for different TSV categories was 2.61%. This model provides a new and more informative tool when studying outdoor thermal comfort.
520 $a The ordered probability model is developed based on statistical method and have no physical and physiological bearing. Thus, it is limited to the region where the data are obtained. To make the prediction of outdoor thermal comfort universally applicable, this study developed a multi-segment model based on heat transfer at various segments. This heat transfer included convection, radiation, and evaporation on bare skin and skin covered with clothing. The model accounts for non-uniform clothing insulation across different body segments with transient heat transfer in the clothing. The heat transfer between two body segments was estimated from blood circulation through counter-current heat exchange. The model allows calculation of complicated radiative heat transfer between the human body and the outdoor thermal environment. The developed model can be applied in a transient and non-uniform outdoor environment. The validity of the model was tested in various indoor and outdoor thermal environment. We conducted human subject tests in Tianjin, China and West Lafayette, United States to collect data for the outdoor validation. Using a total of 26 human subjects in 94 tests under these climatic conditions, this study measured outdoor thermal environmental parameters, monitored subjects' skin temperature, and recorded subjects' thermal sensation. Good agreement was observed between the measured and calculated mean skin temperature. However, the deviation between the predicted and measured local skin temperature under extreme cold condition can be as large as 6 K.
520 $a Finally, a dynamic outdoor thermal sensation model was developed by using the data collected from the human subject tests. Analysis of the test data showed that the thermal load, the mean skin temperature, and the change rate of the mean skin temperature of the subjects tested were the most important parameters affecting their thermal comfort in the outdoor spaces. These three parameters were integrated as predictor variables into a comfort model for predicting the outdoor thermal sensation. The model uses the thermal load to evaluate the thermal environment, and the mean skin temperature, and its change rate to consider dynamic changes in the thermal state of the human body. The validity of the model developed in one region was tested with the use of data obtained from the other region.
520 $a For the future work, to improve the performance of the human heat transfer model in predicting local skin temperatures, more accurate data on local segments' properties should be acquired. Furthermore, a systematic framework of designing comfortable outdoor spaces should be developed. Designers could follow the framework to obtain the required inputs and use the inputs to evaluate the thermal comfort of designed outdoor spaces. (Abstract shortened by ProQuest.).
590 $a School code: 0183.
650 4 $a Engineering. $3 586835
650 4 $a Architectural engineering. $3 3174102
650 4 $a Urban planning. $3 2122922
690 $a 0537
690 $a 0462
690 $a 0999
710 2 $a Purdue University. $b Mechanical Engineering. $3 1019124
773 0 $t Dissertation Abstracts International $g 78-12B(E).
790 $a 0183
791 $a Ph.D.
792 $a 2017
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10272335