Fire resistance of reinforced concrete columns: State of the art, analysis and prediction

被引:2
作者
Wang, Yuzhuo [1 ,2 ]
Liu, Zejian [1 ]
Zhang, Xiao [3 ]
Qu, Shuang [1 ,2 ]
Xu, Tiangui [4 ]
机构
[1] Shandong Jianzhu Univ, Sch Civil Engn, Jinan 250101, Shandong, Peoples R China
[2] Shandong Jianzhu Univ, Key Lab Bldg Struct Retrofitting & Underground Spa, Minist Educ, Jinan 250101, Shandong, Peoples R China
[3] Shandong Xiehe Univ, Coll Engn, Jinan 250109, Shandong, Peoples R China
[4] Southeast Univ, Sch Civil Engn, Key Lab Concrete & Prestressed Concrete Struct, Minist Educ, Jiulonghu Campus, Nanjing 211189, Peoples R China
来源
JOURNAL OF BUILDING ENGINEERING | 2024年 / 96卷
基金
中国国家自然科学基金;
关键词
Reinforced concrete column; Fire resistance; Parameter analysis; Prediction formula; Machine learning; M INTERACTION CURVE; PERFORMANCE; BEHAVIOR; MODEL;
D O I
10.1016/j.jobe.2024.110690
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Reinforced concrete (RC) columns are commonly used as the main load-bearing component of building structures owing to their excellent mechanical properties, and the fire resistance of RC columns has become a pivotal focus with the growing occurrence of building fires. In this paper, the fire resistance of 148 specimens in 89 references was first summarized, and 15 influencing parameters of fire resistance are obtained such as concrete cover thickness, load ratio and load eccentricity. The influence rules of the parameters, theoretical analysis, finite element (FE) analysis and fire resistance prediction formula of RC columns were summarized and analyzed. Secondly, the correlation analysis between 15 parameters and fire resistance was performed, and it was found that 7 parameters with a correlation coefficient higher than 0.15 can be considered as crucial parameters and used for the subsequent analysis. Furthermore, the prediction models of eight Machine Learning (ML) algorithms were established separately, and the Random Forest (RF) with high prediction accuracy (R-2 is 0.95) was carefully chosen to build the database. Finally, the prediction formula of RC columns was proposed through non-linear regression analysis on the database, and it was observed that the formula with R-2 of 0.895 has high accuracy in evaluating fire resistance. The formula can be regarded as a reference for the fire resistance design of RC columns.
引用
收藏
页数:20
相关论文
共 83 条
  • [21] Assessing the flexural and axial behaviour of reinforced concrete members at elevated temperatures using sectional analysis
    El-Fitiany, S. F.
    Youssef, M. A.
    [J]. FIRE SAFETY JOURNAL, 2009, 44 (05) : 691 - 703
  • [22] Fire tests and calculation methods for circular concrete columns
    Franssen, JM
    Dotreppe, JC
    [J]. FIRE TECHNOLOGY, 2003, 39 (01) : 89 - 97
  • [23] Freund Y., 1996, Machine Learning. Proceedings of the Thirteenth International Conference (ICML '96), P148
  • [24] Simple consideration of second-order effects in the calculation of RC column fire resistance
    Glowacki, Michal
    Kowalski, Robert
    [J]. FIRE SAFETY JOURNAL, 2022, 133
  • [25] Hass R., 1986, Practical Rules for the Design of Reinforced Concrete and Composite Columns Submitted to Fire
  • [26] Hastie T, 2009, The Elements of Statistical Learning, V2nd
  • [27] Fire-resistant capacity of RC structures considering time-dependent creep strain at elevated temperature
    Hwang, Ju-young
    Kwak, Hyo-Gyoung
    Hwang, Jinwook
    Lee, Yonghoon
    Kim, Wha-Jung
    [J]. MAGAZINE OF CONCRETE RESEARCH, 2016, 68 (15) : 782 - 797
  • [28] P-M interaction curve for reinforced concrete columns exposed to elevated temperature
    Kang, Hyun
    Cheon, Na-Rae
    Lee, Deuck Hang
    Lee, Jungmin
    Kim, Kang Su
    Kim, Heung-Youl
    [J]. COMPUTERS AND CONCRETE, 2017, 19 (05) : 537 - 544
  • [29] Effectiveness of Polypropylene and Steel Fibers in Enhancing Fire Resistance of High-Strength Concrete Columns
    Khaliq, Wasim
    Kodur, Venkatesh
    [J]. JOURNAL OF STRUCTURAL ENGINEERING, 2018, 144 (03)
  • [30] Obtaining interaction diagram of concrete section exposed to fire by mathematical optimization
    Kim, Han-Soo
    [J]. JOURNAL OF BUILDING ENGINEERING, 2021, 44