Zhang Lu, Wei Tingyu, Li Hongyu, Zeng Jian, Deng Xiaofang
College of Civil Engineering and Architecture, Guilin University of Technology, Guilin 541004, China.
Department of Management Engineering, Guangxi Polytechnic of Construction, Nanning 530000, China.
Materials (Basel). 2021 May 19;14(10):2662. doi: 10.3390/ma14102662.
Many negative factors can influence the progressive collapse resistance of reinforced concrete (RC) frame structures. One of the most important factors is the corrosion of rebar within the structure. With increasing severity of corrosion, the duration, robustness, and mechanical performance can be greatly impaired. One specific side effect of rebar corrosion is the significant loss of protection against progressive collapse. In order to quantify the effects of rebar corrosion on load-resisting mechanisms (compressive arch action (CAA) and tensile catenary action (TCA)) of RC frames, a series of numerical investigations were carried out in this paper. The previous experimental results reported in the literature provide a benchmark for progressive collapse behavior as a sound condition and validate the proposed numerical model. Furthermore, based on the verified numerical model, the CAA and TCA with increasing corrosion and an elapsed time from 0 to 70 years are investigated. Comparing with the conventional empirical model, the proposed numerical model has shown the ability and feasibility in predicting the collapse resistance capacity in structures with corroded rebar. Therefore, this numerical modeling strategy provides comprehensive insights into the change of load-resisting mechanisms in these structures, which can be beneficial for optimizing the design.
许多负面因素会影响钢筋混凝土(RC)框架结构的抗连续性倒塌能力。其中最重要的因素之一是结构内钢筋的腐蚀。随着腐蚀程度的加剧,结构的耐久性、坚固性和力学性能会受到极大损害。钢筋腐蚀的一个特定副作用是对连续性倒塌的防护能力显著丧失。为了量化钢筋腐蚀对RC框架抗荷载机制(抗压拱作用(CAA)和抗拉悬链线作用(TCA))的影响,本文进行了一系列数值研究。文献中报道的先前实验结果为处于良好状态的连续性倒塌行为提供了基准,并验证了所提出的数值模型。此外,基于经过验证的数值模型,研究了腐蚀程度增加以及经过时间从0到70年时的CAA和TCA。与传统经验模型相比,所提出的数值模型在预测钢筋锈蚀结构的抗倒塌能力方面显示出了能力和可行性。因此,这种数值建模策略为深入了解这些结构中抗荷载机制的变化提供了全面的认识,这有助于优化设计。