
Experimental and numerical evaluations of composite concrete-to-concrete interfacial shear strength under horizontal and normal stresses
Author(s) -
Mohammed Yahya Mohammed Al-Fasih,
Mazmira E. Mohamad,
Izni Syahrizal Ibrahim,
Yusof Ahmad,
Mohd Azreen Mohd Ariffin,
Noor Nabilah Sarbini,
Roslli Noor Mohamed,
Ahmad Beng Hong Kueh
Publication year - 2021
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0252050
Subject(s) - materials science , shear (geology) , failure mode and effects analysis , cohesive zone model , composite material , adhesive , direct shear test , finite element method , slip (aerodynamics) , structural engineering , shear stress , solver , geotechnical engineering , geology , fracture mechanics , engineering , mathematics , layer (electronics) , mathematical optimization , aerospace engineering
Effects of different surface textures on the interface shear strength, interface slip, and failure modes of the concrete-to-concrete bond are examined through finite element numerical model and experimental methods in the presence of the horizontal load with ‘push-off’ technique under different normal stresses. Three different surface textures are considered; smooth, indented, and transversely roughened to finish the top surfaces of the concrete bases. In the three-dimensional modeling via the ABAQUS solver, the Cohesive Zone Model (CZM) is used to simulate the interface shear failure. It is observed that the interface shear strength increases with the applied normal stress. The transversely roughened surface achieves the highest interface shear strength compared with those finished with the indented and smooth approaches. The smooth and indented surfaces are controlled by the adhesive failure mode while the transversely roughened surface is dominated by the cohesive failure mode. Also, it is observed that the CZM approach can accurately model the interface shear failure with 3–29% differences between the modeled and the experimental test findings.