Prediction of Concrete Failure Time Based on Statistical Properties of Compressive Strength

被引:7
|
作者
Wang, Jiao [1 ]
Zheng, Weiji [1 ]
Zhao, Yangang [2 ]
Zhang, Xiaogang [3 ]
机构
[1] Guangzhou Univ, Sch Civil Engn, Guangzhou 510006, Peoples R China
[2] Kanagawa Univ, Dept Architecture & Bldg Engn, Yokohama, Kanagawa 2218686, Japan
[3] Shenzhen Univ, Coll Civil & Transportat Engn, Shenzhen 518060, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2020年 / 10卷 / 03期
关键词
concrete strength; failure probability; third-moment method; equivalent design concrete strength; OF-THE-ART; CARBONATION DEPTH; CEMENT; REINFORCEMENT; CORROSION;
D O I
10.3390/app10030815
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Since the heterogeneity of the cement-based material contributes to a random spatial distribution of compressive strength, a reliability analysis based on the compressive strength of concrete is fundamental to carry out structural safety assessment. By analyzing 10,317 datapoints on compressive strength of concrete, a time-varying reliability evaluation based on the third-moment (TM) method was proposed to predict the service life of concrete. Unlike the second-moment (SM) method, skewness is taken into account in the TM; thus, the calculated result of concrete failure time based on the TM is more accurate. In this paper, the errors of the calculated results using time-varying reliability evaluation are within 3%, as shown by Monte Carlo (MC) simulation. In addition, the proposed model (aiming to calculate the equivalent design compressive strength) verifies the concrete failure time calculated by time-varying reliability. According to the results, concrete failure times calculated by these two models are in good agreement. Overall, based on the simple and effective methodology adopted in this paper, it is feasible to develop time-varying reliability based on other factors that might also lead to concrete failure, such as carbonation-induced corrosion, cracking, or deflection of the concrete.
引用
收藏
页数:18
相关论文
共 50 条
  • [1] Prediction of compressive strength of concrete based on accelerated strength
    Shelke, N. L.
    Gadve, Sangeeta
    STRUCTURAL ENGINEERING AND MECHANICS, 2016, 58 (06) : 989 - 999
  • [2] PREDICTION OF CONCRETE MIX COMPRESSIVE STRENGTH USING STATISTICAL LEARNING MODELS
    Shaqadan, A. A.
    Al-Rawashdeh, M.
    JOURNAL OF ENGINEERING SCIENCE AND TECHNOLOGY, 2018, 13 (07): : 1916 - 1925
  • [3] Neural prediction of concrete compressive strength
    Dauji S.
    Dauji, Saha (acad.dauji@gmail.com), 2018, Inderscience Publishers, 29, route de Pre-Bois, Case Postale 856, CH-1215 Geneva 15, CH-1215, Switzerland (12) : 17 - 35
  • [4] COMPRESSIVE STRENGTH OF CEMENT AS A CRITERION FOR PREDICTION OF COMPRESSIVE STRENGTH OF CONCRETE.
    Reddy, B.S.N.
    Kamasundara Rao, A.
    1600, (59):
  • [5] Prediction of Compressive Strength of Alccofine-Based Geopolymer Concrete
    Diksha
    Dev, Nirendra
    Goyal, Pradeep Kumar
    IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF CIVIL ENGINEERING, 2023, 48 (4) : 2077 - 2093
  • [6] Prediction of compressive strength of GGBS based concrete using RVM
    Prasanna, P. K.
    Murthy, A. Ramachandra
    Srinivasu, K.
    STRUCTURAL ENGINEERING AND MECHANICS, 2018, 68 (06) : 691 - 700
  • [7] Compressive strength prediction of recycled concrete based on deep learning
    Deng, Fangming
    He, Yigang
    Zhou, Shuangxi
    Yu, Yun
    Cheng, Haigen
    Wu, Xiang
    CONSTRUCTION AND BUILDING MATERIALS, 2018, 175 : 562 - 569
  • [8] Real-time monitoring and prediction of compressive strength of mortar and concrete
    Kishore, S.
    Kumar, A. Arun
    MATERIALS RESEARCH EXPRESS, 2025, 12 (02)
  • [9] Statistical analysis of the compressive strength of concrete in structures
    Bartlett, FM
    MacGregor, JG
    ACI MATERIALS JOURNAL, 1996, 93 (02) : 158 - 168
  • [10] PREDICTION OF TRIAXIAL COMPRESSIVE STRENGTH OF GEOMATERIALS BASED ON A FAILURE CRITERION
    Bineshian, Hossein
    Bineshian, Zahra
    PROCEEDINGS OF THE ASME 31ST INTERNATIONAL CONFERENCE ON OCEAN, OFFSHORE AND ARCTIC ENGINEERING, 2012, VOL 4, 2012, : 21 - 26