Fatigue behaviour of plain and reinforced concrete: A systematic review

可用性(结构) 断裂力学 结构工程 巴黎法 钢筋混凝土 断裂(地质) 材料科学 计算机科学 工程类 裂缝闭合 复合材料
作者
Ram Lal Riyar,Mansi,Sonali Bhowmik
出处
期刊:Theoretical and Applied Fracture Mechanics [Elsevier BV]
卷期号:125: 103867-103867 被引量:36
标识
DOI:10.1016/j.tafmec.2023.103867
摘要

Damage tolerance design approach such as the fatigue crack propagation approach provides a more realistic solution for fatigue problems in concrete to overcome the limitations associated with the conventional design approach. The fatigue response of concrete is characterised by different fracture parameters, which have substantial impact on structural integrity and serviceability. Till now, many researchers have studied the fracture behaviour of concrete under static as well as fatigue loading. A critical review considering aspects which affects the fatigue fracture behaviour of concrete is necessary to represent the available information in a more systematic format. The goal of comprehensive assessment of the fracture behaviour of concrete is to understand the mechanics behind the different mechanisms of failure under fatigue loading. Real-time damage of structures must be quantified in order to create robust damage quantification models using various concepts. This will be helpful to recommend improved design and rehabilitation schemes to reduce structural failure. In this review, firstly a brief introduction is given describing the necessity of fatigue and fracture analysis in concrete. The studies on existence of Fracture Process Zone and estimation of its shape and size have been highlighted. A detailed study of size effect is then presented which mentions the different types of size effect laws that evolved with time. The evolution of crack growth rate laws in concrete is discussed in a detailed manner. Furthermore, a rigorous study has been done on various fatigue crack growth characterising factors such as loading rate, reinforcement ratio, coupled corrosion fatigue, bond slip, and temperature. Finally, the review is concluded with the studies on artificial neural networks, machine learning, and deep learning in the domain of fatigue and fracture analysis of concrete. Based on this review, various research gaps and open problems are identified for future reference.

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