Probabilistic Prediction Model of Fatigue Life of RC Structures Considering the Meso-scale Inhomogeneity of Concrete

被引:0
|
作者
Jin, Liu [1 ]
Yang, Jian [1 ]
Wu, Jieqiong [1 ]
Du, Xiuli [1 ]
机构
[1] The Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education, Beijing University of Technology, Beijing,100124, China
来源
Cailiao Daobao/Materials Reports | 2024年 / 38卷 / 20期
基金
中国国家自然科学基金;
关键词
Cements - Concrete aggregates - Concrete mixtures - Concrete testing - Digital elevation model - Failure rate - Fatigue damage - Stress concentration;
D O I
10.11896/cldb.23090009
中图分类号
学科分类号
摘要
A 3D microscopic numerical model for chloride diffusion in fatigue-damaged concrete was established, where the concrete was treated as a three-phase composite consisting of coarse aggregate, mortar matrix and ITZ to consider its inhomogeneity. Results showed that the chloride concentration in concrete increases significantly with the increase of fatigue stress level, water-cement ratio, temperature and exposure time, in which the chloride concentration at the same depth is different. According to the K-S test, the chloride concentration at a certain concrete depth follows the mixed normal distribution at a 5% significance level, based on which, a probabilistic fatigue life prediction model is proposed. It was found that the failure probability increases with the increase of fatigue life, but decreases with the decrease of fatigue stress level, water-cement ratio, temperature and exposure time. Hence it was suggested that RC structure should be maintained a fatigue stress level of below 0. 4 (failure probability of 10% and 2 million cycles of fatigue life)during its service . In addition, based on the proposed model, the fatigue life of RC structures in four coastal cities was predicted and the related durability recommendations were given. © 2024 Cailiao Daobaoshe/ Materials Review. All rights reserved.
引用
收藏
相关论文
共 50 条
  • [41] Numerical modeling of the carbonation depth of meso-scale concrete under sustained loads considering stress state and damage
    Shi, Xinyu
    Zhang, Cheng
    Liu, Zhiyuan
    Van den Heede, Philip
    Wang, Ling
    De Belie, Nele
    Yao, Yan
    Construction and Building Materials, 2022, 340
  • [42] Numerical modeling of the carbonation depth of meso-scale concrete under sustained loads considering stress state and damage
    Shi, Xinyu
    Zhang, Cheng
    Liu, Zhiyuan
    Van den Heede, Philip
    Wang, Ling
    De Belie, Nele
    Yao, Yan
    CONSTRUCTION AND BUILDING MATERIALS, 2022, 340
  • [43] Prediction model for fatigue life considering microstructures of steel
    Ueda, Koya
    Shibanuma, Kazuki
    Kinefuchi, Masao
    Nemoto, Yoshiki
    Suzuki, Katsuyuki
    Enoki, Manabu
    21ST EUROPEAN CONFERENCE ON FRACTURE, (ECF21), 2016, 2 : 2575 - 2582
  • [44] 3D meso-scale simulation of chloride ion transportation in cracked concrete considering aggregate morphology
    Zheng, Bin
    Li, Tongchun
    Qi, Huijun
    Gao, Lingang
    Liu, Xiaoqing
    Yuan, Li
    CONSTRUCTION AND BUILDING MATERIALS, 2022, 326
  • [45] A unified probabilistic fatigue life prediction model for natural rubber components considering strain ratio effect
    Liu, Xiangnan
    Zhao, Xuezhi
    Liu, Xiao-Ang
    FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES, 2023, 46 (04) : 1473 - 1487
  • [46] Finite Element Analysis of Concrete Beam under Flexural Stresses Using Meso-Scale Model
    Al-Zuhairi, Alaa H.
    Taj, Ali I.
    CIVIL ENGINEERING JOURNAL-TEHRAN, 2018, 4 (06): : 1288 - 1302
  • [47] Fatigue life prediction for the reinforced concrete (RC) beams under the actions of chloride attack and fatigue
    Wu, Jieqiong
    Xu, Jianchao
    Diao, Bo
    Jin, Liu
    Du, Xiuli
    ENGINEERING STRUCTURES, 2021, 242 (242)
  • [48] Reconstruction of the meso-scale concrete model using a deep convolutional generative adversarial network (DCGAN)
    Liu, Yifan
    Zhang, Jie
    Zhao, Tingting
    Wang, Zhiyong
    Wang, Zhihua
    CONSTRUCTION AND BUILDING MATERIALS, 2023, 370
  • [49] Bayesian prediction and probabilistic model of fatigue cracks in steel structures
    Chen, Meng-Cheng
    Fang, Wei
    Yang, Chao
    Xie, Li
    ENGINEERING FAILURE ANALYSIS, 2019, 103 : 335 - 346
  • [50] 3D meso-scale numerical model and dynamic mechanical behavior of reinforced concrete
    Deng, Y. J.
    Li, L.
    Lv, T. H.
    Chen, X. W.
    Ye, Z. J.
    STRUCTURAL CONCRETE, 2024, 25 (03) : 1819 - 1839