| 基于广义回归神经网络的纤维增强聚合物复合材料约束损伤混凝土强度预测 |
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| 引用本文： | 曹玉贵,赵国旭,尹亚运. 基于广义回归神经网络的纤维增强聚合物复合材料约束损伤混凝土强度预测[J]. 复合材料学报, 2021, 38(5): 1623-1628. DOI: 10.13801/j.cnki.fhclxb.20200804.001 |
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| 作者姓名： | 曹玉贵 赵国旭 尹亚运 |
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| 作者单位： | 武汉理工大学 道路桥梁与结构工程湖北省重点实验室,武汉430070;武汉理工大学 土木工程与建筑学院,武汉430070 |
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| 基金项目： | 国家自然科学基金(51808419)；湖北省自然科学基金(2019CFB217)；湖北省重大专项研发计划(2018AAA001)；武汉理工大学自主创新基金(2019IVA089) |
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| 摘 要： | 纤维增强聚合物复合材料(FRP)约束损伤混凝土抗压强度模型对于混凝土柱类构件的修复和加固具有重要指导意义.现有FRP修复混凝土的强度模型适用条件有限,同一模型不能同时应用于不同强弱约束、不同强度混凝土、不同倒角混凝土的强度预测.本文根据广义回归神经网络(GRNN)的特点,基于46个FRP强约束损伤混凝土方柱、210个F...
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| 关 键 词： | 广义回归神经网络(GRNN) FRP约束损伤混凝土 抗压强度 强弱约束 不同截面形状 |
| 收稿时间： | 2020-05-21 |
Strength prediction of fiber reinforced polymer composite confined damaged concrete using general regression neural network |
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| Affiliation: | 1.Hubei Key Laboratory of Roadway Bridge and Structure Engineering, Wuhan University of Technology, Wuhan 430070, China2.School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan 430070, China |
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| Abstract: | The compressive strength of damaged concrete reinforced with fiber reinforced polymer composite (FRP) has an important guiding significance in repairing of concrete columns. However, the existing model cannot capture the compressive strength of FRP hardening and softening confined damaged concrete with circular and square cross section. In order to fill this gap, an experimental database of 46 FRP hardening confined square damaged concrete, 210 FRP hardening confined circular damaged concrete and 35 FRP softening confined circular damaged concrete was established. Based on the characteristics of generalized regression neural network (GRNN) and database, the GRNN compressive strength model of FRP confined damaged concrete was developed. The GRNN model was compared with the existing model. The results show that the GRNN model can accurately predict the strength of FRP confined damaged concrete columns. |
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