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作 者:易晓园 张爱玲 YI Xiaoyuan;ZHANG Ailing(School of Architecture,Chengdu Jincheng College,Chengdu 611731,China;School of Civil and Environment Engineering,Chengdu Jincheng College,Chengdu 611731,China)
机构地区:[1]成都锦城学院建筑学院,成都611731 [2]成都锦城学院土木与环境工程学院,成都611731
出 处:《复合材料科学与工程》2023年第11期102-107,共6页Composites Science and Engineering
摘 要:近年来,纤维增强复合材料(FRP)已被广泛应用于既有混凝土结构加固。而现有FRP与混凝土界面黏结强度模型的预测精度偏低,无法为FRP的实际应用提供有效的参考。为此,本文建立了一个由855组试验数据组成的大型数据库,并在此基础上利用数据分组处理算法(GMDH)提出了一个高精度预测模型。为验证GMDH模型是否能为FRP-混凝土界面的黏结强度计算提供更有价值的参考,本文将GMDH模型与现有七个文献模型进行对比,并采用决定系数(R^(2))、变异系数(COV)和相对平方根误差(RRSE)等三个统计指标对模型的预测结果进行评价。结果表明,与现有文献模型相比,本文所提GMDH模型的R^(2),COV和RRSE值至少改进了11.9%、30.9%和35.3%。因此,GMDH模型能够为FRP的实际应用提供更加有效的参考。In recent years,fiber-reinforced polymer(FRP)has been widely used in concrete reinforcement.However,the prediction accuracy of the existing FRP-concrete interface bond strength prediction models is low,which cannot provide an effective reference for the practical applications of FRP composites.Therefore,a large database consisting of 855 sets of test data was established in this study,and a bond strength model with high prediction accuracy was proposed by using group method of data handling(GMDH).In order to verify whether the GMDH model can provide a more valuable reference for the calculation of the bond strength of the FRP-concrete interface,the GMDH model was compared with seven existing literature models,and coefficient of determination(R^(2)),coefficient of variation(COV)and relative square root error(RRSE)were used to evaluate the prediction results of these models.The results showed that,compared with the existing literature models,the R^(2),COV and RRSE values of the proposed GMDH model were improved by at least 11.9%,30.9%and 35.3%,respectively.Therefore,the GMDH model can provide a more effective reference for the practical applications of FRP composites.
关 键 词:黏结强度 FRP板 混凝土 GMDH 机器学习 复合材料
分 类 号:TB332[一般工业技术—材料科学与工程]
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