• Home
  • Journals
  • Focus
  • Conferences
  • Researchers
  • Sign in

Outline

  • Abstract
  • Keywords

Figures(5)

标签(1)

Table 1

其他(2)

PDF
Document

Frontiers of Structural and Civil Engineering

    • PDF
    • collect

    An artificial neural network model on tensile behavior of hybrid steel-PVA fiber reinforced concrete containing fly ash and slag power

    . Department of Civil and Environmental Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA.. Department of Geotechnical Engineering, College of Civil Engineering, Tongji University, Shanghai 200092, China.. Key Laboratory of Geotechnical and Underground Engineering (Tongji University), Ministry of Education, Shanghai 200092, China

    Received：2020-11-27 Accepted： 2020-12-28 Available online：2020-12-28
    Show More
    10.1007/s11709-020-0712-6
    Cite this article
    Fangyu LIU, Wenqi DING, Yafei QIAO, Linbing WANG.An artificial neural network model on tensile behavior of hybrid steel-PVA fiber reinforced concrete containing fly ash and slag power[J].Frontiers of Structural and Civil Engineering:1299-1315.

    Abstract

    The tensile behavior of hybrid fiber reinforced concrete (HFRC) is important to the design of HFRC and HFRC structure. This study used an artificial neural network (ANN) model to describe the tensile behavior of HFRC. This ANN model can describe well the tensile stress-strain curve of HFRC with the consideration of 23 features of HFRC. In the model, three methods to process output features (no-processed, mid-processed, and processed) are discussed and the mid-processed method is recommended to achieve a better reproduction of the experimental data. This means the strain should be normalized while the stress doesn’t need normalization. To prepare the database of the model, both many direct tensile test results and the relevant literature data are collected. Moreover, a traditional equation-based model is also established and compared with the ANN model. The results show that the ANN model has a better prediction than the equation-based model in terms of the tensile stress-strain curve, tensile strength, and strain corresponding to tensile strength of HFRC. Finally, the sensitivity analysis of the ANN model is also performed to analyze the contribution of each input feature to the tensile strength and strain corresponding to tensile strength. The mechanical properties of plain concrete make the main contribution to the tensile strength and strain corresponding to tensile strength, while steel fibers tend to make more contributions to these two items than PVA fibers.

    Keywords

    artificial neural network ; hybrid fiber reinforced concrete ; tensile behavior ; sensitivity analysis ; stress-strain curve
    Previous article in issue
    article in issue Next
    登录后，您可以进行评论。请先登录

    评论

    评论

    • 所有评论
     咋就跳到顶部了
    2019-04-23 11:24:14
    回复 (0)
    inspur  手机账号
    2019-05-10 11:30:17
    回复 (0)

    Read

    22

    Download

    0

    Related Research

    Current Issue
      Current Issue
        Follow us
        Copyright © 2015 China Engineering Science Press.
        京ICP备11030251号
        Follow us
        Copyright © 2015 China Engineering Science Press.
        京ICP备11030251号