Abstract of: Mechanical Behaviour of Transparent Structural Silicone Adhesive (TSSA) Steel-to-Glass Laminated Connections Under Monotonic and Cyclic Loading
Steel-to-glass laminated connections, which have recently been developed, limit stress intensifications on the glass and combine strength and transparency. Transparent Structural Silicone Adhesive (TSSA) connections have been used in several projects worldwide; however, the hyperelastic and viscoelastic nature of the material has to date not been fully investigated. In this work, the first objective is to investigate the mechanical response of TSSA connections under static and cyclic loading by means of experimental tests. Firstly, the shear behaviour of TSSA circular connections is characterized by means of monotonic and cyclic loading tests. The adhesive exhibits significant stress-softening under repeated cycles that becomes more severe as the maximum load increases. Secondly, TSSA circular connections are subjected to monotonic and cyclic tensile loading of increasing maximum load. The way whitening propagates on the adhesive surface shows some consistency comparing the cases of static and cyclic loading. The second objective is to analytically describe the deformation behaviour of the adhesive based on hyperelastic prediction models. Uniaxial and biaxial tension tests are combined with the simple shear tests, for the material characterization of TSSA. The hyperelastic material parameters are calibrated by a simultaneous multi-experiment-data-fit based on the nonlinear least squares optimization method. The softening behaviour observed in shear tests is modeled based on a simplified pseudo-elastic damage model proposed by Ogden–Roxburgh. A first attempt is also made to model the actual softening response of the adhesive. A less conservative approach proposed by Guo, also based on the theory of pseudo-elasticity, proved to give a good approximation of the actual cyclic response of the adhesive.
Joints, Fixings & Adhesives
Keywords:Glass, TSSA, Silicone, Mullins effect
Copyright (c) 2018 Anna Ioannidou-Kati, Manuel Santarsiero, Peter de Vries, Sofia Teixeira de Freitas, Rob Nijsse, Christian Louter
This work is licensed under a Creative Commons Attribution 4.0 International License.