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Gurson-Tvergaard-Needleman 本构模型在带腐蚀坑钢筋拉伸性能中的应用。

Application of Gurson-Tvergaard-Needleman constitutive model to the tensile behavior of reinforcing bars with corrosion pits.

机构信息

School of Materials Science and Engineering, Southeast University, Nanjing, Jiangsu, P. R. China.

出版信息

PLoS One. 2013;8(1):e54368. doi: 10.1371/journal.pone.0054368. Epub 2013 Jan 14.

DOI:10.1371/journal.pone.0054368
PMID:23342140
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3544769/
Abstract

Based on meso-damage mechanics and finite element analysis, the aim of this paper is to describe the feasibility of the Gurson-Tvergaard-Needleman (GTN) constitutive model in describing the tensile behavior of corroded reinforcing bars. The orthogonal test results showed that different fracture pattern and the related damage evolution process can be simulated by choosing different material parameters of GTN constitutive model. Compared with failure parameters, the two constitutive parameters are significant factors affecting the tensile strength. Both the nominal yield and ultimate tensile strength decrease markedly with the increase of constitutive parameters. Combining with the latest data and trial-and-error method, the suitable material parameters of GTN constitutive model were adopted to simulate the tensile behavior of corroded reinforcing bars in concrete under carbonation environment attack. The numerical predictions can not only agree very well with experimental measurements, but also simplify the finite element modeling process.

摘要

基于细观损伤力学和有限元分析，本文旨在描述 Gurson-Tvergaard-Needleman（GTN）本构模型在描述腐蚀钢筋拉伸行为方面的可行性。正交试验结果表明，通过选择不同的 GTN 本构模型材料参数，可以模拟不同的断裂模式和相关的损伤演化过程。与失效参数相比，两个本构参数是影响拉伸强度的显著因素。名义屈服强度和极限拉伸强度均随本构参数的增加而显著降低。结合最新数据和试错法，采用合适的 GTN 本构模型材料参数模拟碳化环境侵蚀下混凝土中腐蚀钢筋的拉伸行为。数值预测不仅与实验测量非常吻合，而且简化了有限元建模过程。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1125/3544769/a82df2ffe0e1/pone.0054368.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1125/3544769/79dd7ca84c22/pone.0054368.g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1125/3544769/2609b72bf376/pone.0054368.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1125/3544769/d0eefbb40fc7/pone.0054368.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1125/3544769/4328c3c7f39a/pone.0054368.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1125/3544769/a82df2ffe0e1/pone.0054368.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1125/3544769/79dd7ca84c22/pone.0054368.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1125/3544769/ef5d66036d93/pone.0054368.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1125/3544769/72e9a92a1f8b/pone.0054368.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1125/3544769/2609b72bf376/pone.0054368.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1125/3544769/d0eefbb40fc7/pone.0054368.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1125/3544769/4328c3c7f39a/pone.0054368.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1125/3544769/a82df2ffe0e1/pone.0054368.g007.jpg

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