Compressive behavior of hybrid steel-polyvinyl alcohol fiber-reinforced concrete containing fly ash and slag powder:experiments and an artificial neural network model

作     者：Fang-yu LIU Wen-qi DING Ya-fei QIAO Lin-bing WANG Qi-yang CHEN Fang-yu LIU;Wen-qi DING;Ya-fei QIAO;Lin-bing WANG;Qi-yang CHEN

作者机构：Department of Civil and Environmental EngineeringVirginia Polytechnic Institute and State UniversityVirginia 24061USA Department of Geotechnical EngineeringCollege of Civil EngineeringTongji UniversityShanghai 200092China Key Laboratory of Geotechnical and Underground EngineeringMinistry of EducationShanghai 200092China Department of Civil and Environmental EngineeringUniversity of Illinois at Urbana-ChampaignUrbana 61801USA 

出 版 物：《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》 (浙江大学学报（英文版）A辑（应用物理与工程）)

年 卷 期：2021年第22卷第9期

页      面：721-735页

核心收录：

学科分类：08[工学] 081304[工学-建筑技术科学] 0805[工学-材料科学与工程（可授工学、理学学位）] 080502[工学-材料学] 0813[工学-建筑学] 

基　　金：Project supported by the National Natural Science Foundation of China(Nos.51978515 and 52090083) the Shanghai Sailing Program(No.19YF1451400) the Shanghai Municipal Science and Technology Major Project(No.2017SHZDZX02),China 

主　　题：Experiments Artificial neural network(ANN) Hybrid fiber-reinforced concrete(HFRC) Compressive behavior Stress-strain curve 

摘      要：Understanding the mechanical behavior of hybrid fiber-reinforced concrete(HFRC),a composite material,is crucial for the design of HFRC and HFRC *** this study,a series of compression experiments were performed on hybrid steelpolyvinyl alcohol(PVA)fiber-reinforced concrete containing fly ash and slag powder,with a focus on the fiber content/ratio effect on its compressive behavior;a new approach was built to model the compression behavior of HFRC by using an artificial neural network(ANN)*** proposed ANN model incorporated two new developments:the prediction of the compressive stress-strain curve and consideration of 23 features of components of *** build a database for the ANN model,relevant published data were also *** indices were used to train and evaluate the ANN *** highlight the performance of the ANN model,it was compared with a traditional equation-based *** results revealed that the relative errors of the predicted compressive strength and strain corresponding to compressive strength of the ANN model were close to 0,while the corresponding values from the equation-based model were ***,the ANN model is better able to consider the effect of different components on the compressive behavior of HFRC in terms of compressive strength,the strain corresponding to compressive strength,and the compressive stress-strain *** an ANN model could also be a good tool to predict the mechanical behavior of other composite materials.