Risks of failure of annealed glass panels subject to point contact actions

•Stochastic methodology has been developed for estimating impact damage to a glass panel.•Flaw size distribution function has been determined.•Simulation model is capable of predicting the origins of fracture.•Predicted CPDs of failure load for larger panels have been verified experimentally. The st...

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Bibliographic Details
Published inInternational journal of solids and structures Vol. 129; pp. 177 - 194
Main Authors Pathirana, Mahil, Lam, Nelson, Perera, Shihara, Zhang, Lihai, Ruan, Dong, Gad, Emad
Format Journal Article
LanguageEnglish
Published New York Elsevier Ltd 15.12.2017
Elsevier BV
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Summary:•Stochastic methodology has been developed for estimating impact damage to a glass panel.•Flaw size distribution function has been determined.•Simulation model is capable of predicting the origins of fracture.•Predicted CPDs of failure load for larger panels have been verified experimentally. The strength of glass panels is normally expressed in probabilistic terms by the use of either the Weibull distribution or Log–Normal distribution functions. Values of the modelling parameters can be obtained by calibration against experimental data. This conventional approach to probabilistic modelling has significant shortcomings as the extent of generalising the use of the calibrated parameter values is uncertain. The alternative approach of predicting the risk of failure is by stochastic simulations of Griffith flaws. The developing methodology involves the use of fracture mechanics theory and load duration theory. Limited amount of such simulation studies have been undertaken for predicting the failure of glass under wind pressure. In this paper, the stochastic methodology is further developed to simulate the risk of fracture of the glass panel when subject to the transient action of point contact that can be generated by the impact of hailstones or windborne solid debris particles. The flaw size distribution behaviour of annealed glass plate has been determined by calibrating against experimental results from the testing of glass panels of different dimensions and different rates of loading. Significantly, very good correlation between the simulated and experimental results has been observed across a range of loading scenarios when the set of modelling parameters characterising flaw size distribution was held constant. The introduced simulation methodology is aimed at bringing about significant savings by waiving away the need of conducting repetitive physical experimentation on glazing panels of different dimensions, and at different rates of loading.
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ISSN:0020-7683
1879-2146
DOI:10.1016/j.ijsolstr.2017.09.001