Confinement model for LRS FRP-confined concrete using conventional regression and artificial neural network techniques
Confinement model for LRS FRP-confined concrete using conventional regression and artificial neural network techniques
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DOI：
10.1016/j.compstruct.2021.114779
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发表时间：
2021-10
影响因子：
6.3
通讯作者：
Haytham F. Isleem;Feng Peng;Bassam A. Tayeh
中科院分区：
文献类型：
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作者：
Haytham F. Isleem;Feng Peng;Bassam A. Tayeh
使用纤维增强聚合物（FRP）复合材料约束的混凝土在强度和应变方面有显著的增强。对于现有钢筋混凝土（RC）结构的抗震加固，大断裂应变（LRS）FRP（即，聚对苯二甲酸乙二醇酯和萘二甲酸乙二醇酯，分别表示为PET和PEN）具有大于5%的较大断裂应变，是具有小于3%的断裂应变的常规FRP的有希望的替代物。FRP约束混凝土轴压应力-应变性能的分析模型主要集中在传统FRP约束混凝土上。然而，LRS FRP约束混凝土的分析研究是有限的。在理论分析和试验数据拟合的基础上，确定了现有的应力应变模型。本文采用人工神经网络（ANN）方法，直接从实验数据中建立一个约束模型，预测应力-应变响应的不同分量。使用了由226个LRS FRP约束混凝土试件轴压试验组成的试验数据库。试验结果，在全侧限应力-应变响应，强度，应变，FRP破裂应变，和膨胀响应进行了研究。预测表达式和实用的人工神经网络模型的强度，应变和形状的轴向应力-应变响应。现有的LRS FRP约束混凝土模型也进行了评估。现有的和拟议的模型的结果报告，所提出的方法取得了显着更好的结果。
Concrete confined using fiber-reinforced polymer (FRP) composites experience significant enhancements in strength and strain. For the seismic retrofitting of existing reinforced concrete (RC) structures, a large rupture strain (LRS) FRP (i.e., polyethylene terephthalate and naphthalate, denoted as PET and PEN respectively), with a larger rupture strain of more than 5%, is a promising alternative to conventional FRPs with a rupture strain of less than 3%. The majority of analytical models on the stress–strain behavior of FRP-confined concrete under axial compression have focused largely on concrete confined with the traditional FRP material. Analytical research on LRS FRP-confined concrete is, however, limited. Moreover, all existed stress–strain models were determined based on theoretical analysis and test data fitting. In this paper, the artificial neural networks (ANN) method is employed to build a confinement model directly from experimental data to predict the different components of the stress–strain response. A test database consisting of 226 axial compression tests on LRS FRP-confined concrete specimens is used. The test results, in terms of full confined stress–strain response, strength, strain, FRP rupture strain, and dilation response were investigated. Predictive expressions and practical ANN models for the strength, strain, and shape of an axial stress–strain response are provided. Existing models for LRS FRP-confined concrete were also evaluated. The results of the existing and proposed models report that the proposed methods achieve significantly better results.