A database of clothing overall and local insulation and prediction models for estimating ensembles' insulation

被引:27
|
作者
Tang, Yin [1 ]
Su, Zixiong [1 ]
Yu, Hang [1 ]
Zhang, Kege [1 ]
Li, Chaoen [3 ]
Ye, Hai [2 ]
机构
[1] Tongji Univ, Sch Mech Engn, Shanghai 201804, Peoples R China
[2] Tongji Univ, Coll Architecture & Urban Planning, Shanghai 200092, Peoples R China
[3] Ningbo Univ Technol, Sch Civil & Transportat Engn, Ningbo 315211, Peoples R China
基金
中国国家自然科学基金;
关键词
Clothing insulation; Thermal manikin; Thermal comfort; THERMAL COMFORT; ENERGY EFFICIENCY; HEATING SEASON; ENVIRONMENT; MANNEQUINS; SENSATION; AIR;
D O I
10.1016/j.buildenv.2021.108418
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Clothing has a significant impact on the heat transfer between the human body and the environment, and clothing insulation is an important input parameter for many thermal comfort models. With the development of studies on non-uniform environment and human's local thermal comfort, the clothing local insulation is required in the multi-node human thermoregulation models and significantly affects the accuracy of simulation results. However, there lacks data on clothing local insulation values in standards. In this study, the local insulation of 57 typical garments and 62 ensembles with different layers (1-6 layers) were measured using a thermal manikin. The results show that the ranges of overall insulation for tested garments and ensembles were 0.01-0.56 clo and 0.27-2.17 clo, respectively. The local insulation values differed greatly from the overall insulation values, and varied greatly between different body parts. Further, the linear regression was performed between the ensembles' local insulation at different body parts and the sum of the garments' local insulation. Based on the prediction equations of local insulation, a new method for estimating the overall insulation of ensembles was proposed. Compared with the tradition method using the linear regression equations of overall insulation, the new method reduced the mean relative error from 12.6%-9.1% to 3.4%. This study provided basic data and prediction equations of local insulation for future researches of clothing insulation and local thermal comfort.
引用
收藏
页数:21
相关论文
共 50 条
  • [1] A database of clothing overall and local insulation and prediction models for estimating ensembles’ insulation
    Tang, Yin
    Su, Zixiong
    Yu, Hang
    Zhang, Kege
    Li, Chaoen
    Ye, Hai
    Building and Environment, 2022, 207
  • [2] THE ACCURACY OF ESTIMATING THE THERMAL INSULATION OF CLOTHING ENSEMBLES - THE EFFECT OF APPRAISERS
    KAHKONEN, E
    NYKYRI, E
    TAMMELA, E
    ILMARINEN, R
    SEPPALA, T
    APPLIED ERGONOMICS, 1990, 21 (04) : 325 - 330
  • [3] ESTIMATING CLOTHING INSULATION
    MCCULLOUGH, EA
    ASHRAE JOURNAL-AMERICAN SOCIETY OF HEATING REFRIGERATING AND AIR-CONDITIONING ENGINEERS, 1987, 29 (04): : 45 - 45
  • [4] Estimating local thermal insulation of clothing garments: Modelling and application
    Tang, Yin
    Yu, Hang
    Ye, Hai
    Zhang, Kege
    Wang, Faming
    Mao, Huice
    Wang, Zi
    BUILDING AND ENVIRONMENT, 2023, 243
  • [5] Thermal insulation provided by chairs with various clothing ensembles
    Wang, Yudong
    Wang, Feixiang
    Ma, Hongjin
    Sun, Zhen
    Zhang, Wenhao
    Zhai, Yongchao
    BUILDING AND ENVIRONMENT, 2024, 266
  • [6] A Database of Static Thermal Insulation and Evaporative Resistance Values of Dutch Firefighter Clothing Items and Ensembles
    Kuklane, Kalev
    Eggeling, Jakob
    Kemmeren, Maurice
    Heus, Ronald
    BIOLOGY-BASEL, 2022, 11 (12):
  • [7] The thermal insulation difference of clothing ensembles on the dry and perspiration manikins
    Zhou Xiaohong
    Zheng Chunqin
    Qiang Yingming
    Holmer, Ingvar
    Gao, Chuansi
    Kuklane, Kalev
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2010, 21 (08)
  • [8] Estimating Clothing Thermal Insulation Using an Infrared Camera
    Lee, Jeong-Hoon
    Kim, Young-Keun
    Kim, Kyung-Soo
    Kim, Soohyun
    SENSORS, 2016, 16 (03)
  • [9] Overall and local intrinsic clothing insulation using thermal manikin: Impact of methods employed and postures
    Gao, Shan
    Ooka, Ryozo
    Oh, Wonseok
    BUILDING AND ENVIRONMENT, 2023, 243
  • [10] Artificial neural networks for prediction of local thermal insulation of clothing protecting against cold
    Dabrowska, Anna Katarzyna
    INTERNATIONAL JOURNAL OF CLOTHING SCIENCE AND TECHNOLOGY, 2018, 30 (01) : 82 - 100