Journal of Inorganic Materials, Volume. 36, Issue 1, 61(2021)

Research on Machine Learning Based Model for Predicting the Impact Status of Laminated Glass

Yanran MENG1...2,3, Xinger WANG1,2,3,4, Jian YANG1,2,3,*, Han XU1,2,3, and Feng YUE12 |Show fewer author(s)
Author Affiliations
  • 1School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
  • 2State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
  • 3Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructure, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
  • 4Key Laboratory of Impact and Safety Engineering, Ministry of Education, Ningbo University, Ningbo 315211, China
  • show less

    Architectural laminated glass exhibits significant vulnerability under hard body impacts such as windborne debris impacts. In this work, a prediction model is proposed for assessing the impact status of laminated glass under hard body impact. Multiple design variables including the glass make-ups, interlayer types, support conditions and size are considered. The impact tests with consecutive impact attempts are first conducted. A comprehensive database encompassing the failure condition of each glass layer is then established. This database has 567 groups of PVB laminated glass data and 210 groups of SGP laminated glass data. A combined WOA-KELM machining learning based model is subsequently developed to predict the impact status of laminated glass. The modelling results are compared with that from SVM and LSSVM based models. The results show that the proposed model has a prediction accuracy of 88.45% in failure status of each glass layer. Such model can well predict the impact status of laminated glass and shows better performance in both accuracy and computation cost than other models.

    Tools

    Get Citation

    Copy Citation Text

    Yanran MENG, Xinger WANG, Jian YANG, Han XU, Feng YUE. Research on Machine Learning Based Model for Predicting the Impact Status of Laminated Glass[J]. Journal of Inorganic Materials, 2021, 36(1): 61

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: RESEARCH PAPER

    Received: Apr. 9, 2020

    Accepted: --

    Published Online: Jan. 21, 2021

    The Author Email: YANG Jian (j.yang.1@sjtu.edu.cn)

    DOI:10.15541/jim20200187

    Topics