<p>The strength of architectural glass (soda-lime silica) is highly dependent on surface flaws generated during production, handling and service life. Fracture mechanical investigation of glass, however, is challenging due to e.g. the randomness of flaw size, flaw orientation and quality. Generation of radial and median cracks is inevitable while using a mechanical indenter with direct contact. These undesirable effects, along with uncertainty about the groove’s depth and geometry, degrade the accuracy of results and underline the need for a more reliable tool. Consequently, this contribution focuses instead on the application of ultra-short laser as a non-contact tool, which recently has proved to be a promising solution because of its precision, high speed, and repeatability. Here, artificial grooves with a well-controlled depth are realized on the surface of soda-lime silica glass to investigate the effects of loading rate, flaw size and flaw orientation on the glass strength. Four- point bending tests are performed to assess the failure loads. The method manages to capture the results with a very low standard deviation of the failure stress (approximately 1 MPa), eliminating the need for using large series of specimens.</p>
Glass as a construction material has become indispensable and is still on the rise in the building industry. However, there is still a need for numerical models that can predict the strength of structural glass in different configurations. The complexity lies in the failure of glass elements largely driven by pre-existing microscopic surface flaws. These flaws are present over the entire glass surface, and the properties of each flaw vary. Therefore, the fracture strength of glass is described by a probability function and will depend on the size of the panels, the loading conditions and the flaw size distribution. This paper extends the strength prediction model of Osnes et al. with the model selection by the Akaike information criterion. This allows us to determine the most appropriate probability density function describing the glass panel strength. The analyses indicate that the most appropriate model is mainly affected by the number of flaws subjected to the maximum tensile stresses. When many flaws are loaded, the strength is better described by a normal or Weibull distribution. When few flaws are loaded, the distribution tends more towards a Gumbel distribution. A parameter study is performed to examine the most important and influencing parameters in the strength prediction model.
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