Exploiting invalid test results for assessing the distribution of glazing fracture strength

Glazing is increasingly used as a structural element in modern buildings. Current standards require characterizing this material's fracture strength (f_c) distribution with a minimum of 30 “valid” tests (i.e., samples with fracture initiation in the inner ring area of a co-axial double ring test), excluding “invalid” test results. However, the “invalid” tests do not mean the tests are incorrect or faulty. But rather they represent censored data and still contain information that can be exploited for enhanced accuracy. Thus, this study applies Bayesian updating to extract and incorporate such information in glazing fracture strength characterization. This approach is demonstrated using data from a recent experimental study which adopted coaxial double-ring standardized tests for fracture strength characterization at 25°C and 275 °C. For this case study, the paper also examines how the coefficient of variation of the 5% quantile of f_c changes in function of the number of tests executed. The proposed methodology reduces the uncertainty in estimating the characteristic value of glazing fracture strength and improves testing efficiency. Indeed, it enables achieving the same confidence level as that implied by performing the test number required by the standard with fewer tests, particularly at elevated temperatures.