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Development of deep neural network model to predict the compressive strength of FRCM confined columns

Khuong LE-NGUYEN; Quyen Cao MINH; Afaq AHMAD; Lanh Si HO

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 10, Pages 1213-1232 doi: 10.1007/s11709-022-0880-7

Abstract: model for predicting concrete columns confinement influence with Fabric-Reinforced Cementitious Matrix (FRCMThe results revealed that the proposed ANN models well predicted the compressive strength of FRCM withwith double hidden layers (APDL-1) was shown to be the best to predict the compressive strength of FRCMthe results also reveal that the unconfined compressive strength of concrete, type of fiber mesh for FRCMsection, and the corner radius ratio, are the most significant input variables in the efficiency of FRCM

Keywords： FRCM deep neural networks confinement effect strength model confined concrete