Source Journal of Chinese Scientific and Technical Papers
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YANG Yuan, CUI Qiandao, LIAN Jijian, LIU Hongbo, ZHOU Guangen, CHEN Zhihua. LSTM-BASED DAMAGE PREDICTION AND ASSESSMENT OF SPATIAL FRAME STRUCTURE[J]. INDUSTRIAL CONSTRUCTION, 2021, 51(7): 203-208. doi: 10.13204/j.gyjzG20092308
Citation: GONG Chao, HOU Zhaoxin, LIANG Zihao, WU Zhaoqi, LIANG Weiqiao, FANG Wujun. Experimental Research on Mechanical and Thermal Properties of Four Insulating Materials for Heat Bridge Effect[J]. INDUSTRIAL CONSTRUCTION, 2022, 52(12): 66-71,165. doi: 10.13204/j.gyjzG21030909

Experimental Research on Mechanical and Thermal Properties of Four Insulating Materials for Heat Bridge Effect

doi: 10.13204/j.gyjzG21030909
  • Received Date: 2021-03-09
    Available Online: 2023-03-22
  • Thermal break connection can effectively deal with the problem of thermal bridge effect within the overhanging steel components. The selection of thermal insulation materials is a key to thermal break connection technology while there are few research focused on it. Materials of PA6, PVC, FR4 and PEEK were selected for the potential insulating materials through extensive investigations. A total of 40 compressive tests and 12 thermal conductivity tests of PA6, PVC, FR4 and PEEK were conducted, and their compressive strength, compressive modulus of elasticity, and thermal conductivity coefficients were recorded. The yielding points were studied by using the Farthest Point Method, and the compressive constitute models were obtained by curve-fitting according to Sherwood-Frost model. Combined with the performances of these four materials including mechanical properties, thermal properties and economy, the adaptability of these four materials used in thermal break connections was analyzed. The results indicated that PA6, PVC and PEEK specimens showed a ductile failure mode, while FR4 showed a laminated brittle failure mode. The tested yield strength were 60.1, 50.4 and 125.8 MPa respectively for PA6, PVC and PEEK, while their thermal conductivity coefficients were 0.1755, 0.1424 and 0.2318 W/(m·K), respectively. It was found that FR4 showed the best comprehensive performance while PA6 took the second place, and PVC took the last place. Due to its high cost, PEEK is not appropriate for thermal break material in practical engineering.
  • [1]
    李彦伯. 剪力墙结构温度效应与热桥效应研究[D]. 西安:西安建筑科技大学, 2009.
    [2]
    徐峰, 周爱东, 刘兰, 等. 建筑围护结构保温隔热技术应用[M]. 北京:中国建筑工业出版社, 2011.
    [3]
    中华人民共和国住房和城乡建设部. 严寒和寒冷地区居住建筑节能设计标准:JGJ 26-2010[S]. 北京:中国建筑工业出版社, 2010.
    [4]
    李佳. 绿色建筑节能设计中的围护结构保温技术[J]. 建材与装饰, 2020(15):83-84.
    [5]
    CLEARY D B, RIDDELL W T, CAMISHION N, et al. Steel connections with fiber-reinforced resin thermal barrier filler plates under service loading[J]. Journal of Structural Engineering, 2016, 142(11). DOI: 10.1061/(ASCE)ST.1943-541X.0001576.
    [6]
    LARBI A B, COUCHAUX M, BOUCHAIR A. Thermal and mechanical analysis of thermal break with end-plate for attached steel structures[J]. Engineering Structures, 2017, 131:362-379.
    [7]
    ALHAWARI A, MUKHOPADHYAYA P. Thermal bridges in building envelopes-an overview of impacts and solutions[J]. International Review of Applied Sciences and Engineering, 2018, 9(1):31-40.
    [8]
    GHAZI W K, SIMMLER H, FRANK T. Experimental and numerical thermal analysis of a balcony board with integrated glass fibre reinforced polymer GFRP elements[J]. Energy and Buildings, 2007, 39(1):76-81.
    [9]
    GOULOUTI K, CASTRO J D, KELLER T. Aramid/glass fiber-reinforced thermal break-thermal and structural performance[J]. Composite Structures, 2016, 136:113-123.
    [10]
    GOULOUTI K, DE CASTRO J, VASSILOPOULOS A P, et al. Thermal performance evaluation of fiber-reinforced polymer thermal breaks for balcony connections[J]. Energy and Buildings, 2014, 70:365-371.
    [11]
    章炜. 典型有机建筑保温材料热解动力学行为特性研究[D]. 武汉:武汉理工大学, 2015.
    [12]
    马鑫. 典型有机保温材料的热过程演化及火蔓延特性研究[D]. 合肥:中国科学技术大学, 2015.
    [13]
    谭海平, 张虎, 田耿东. 外墙常用无机保温材料的应用及展望[J]. 四川建材, 2020, 46(3):16-17.
    [14]
    李爽, 周玉琼. 民用建筑节能检测之常用外墙保温隔热材料检测分析[J]. 智能城市, 2020, 6(16):106-107.
    [15]
    黄欢. 无机保温材料在建筑节能工程中的应用[J]. 江西建材, 2020(8):25-27.
    [16]
    刘欢, 刘涛, 龙志凡. 常见的保温材料燃烧热值分析[J]. 建材与装饰, 2020(10):39-40.
    [17]
    全国纤维增强塑料标准化技术委员会. 纤维增强塑料性能试验方法总则:GB/T 1446-2005[S]. 北京:中国标准出版社, 2005.
    [18]
    全国纤维增强塑料标准化技术委员会. 纤维增强塑料压缩性能试验方法:GB/T 1448-2005[S]. 北京:中国标准出版社, 2005.
    [19]
    全国绝热材料标准化技术委员会. 绝热材料稳态热阻及有关特性的测定防护热板法:GB/T 10294-2008[S]. 北京:中国标准出版社, 2005.
    [20]
    冯鹏, 强翰霖, 叶列平. 材料、构件、结构的"屈服点"定义与讨论[J]. 工程力学, 2017, 34(3):36-46.
    [21]
    郑休宁, 张德伟, 扈廷勇. PVC-U管材拉伸屈服点的确定[J]. 聚氯乙烯, 2012, 40(8):21-23.
    [22]
    朱艳峰, 蔡丹阳, 黄窈婷. 城市地下PVC-U塑料排水管材本构试验研究[J]. 广东建材, 2019, 35(10):25-29.
    [23]
    雷鹏. 聚乙烯拉伸应变速率的本构方程改进及运用[J].包装工程, 2019, 40(13):110-115.
    [24]
    SHERWOOD J A, FROST C C. Constitutive modeling and simulation of energy absorbing polyurethane foam under impact loading[J]. Polymer Engineering and Science, 1992, 32(16):1138-1146.
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