TY - GEN
T1 - Probability distributions in the glass failure prediction model
AU - Blanchet, Samir
AU - Scott Norville, H.
AU - Morse, Stephen M.
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Glass, a brittle material, fractures under tensile stress acting over a time duration. Lateral loads, such as wind, acting on a simply supported rectangular glass lite, put one surface of the lite primarily into tension. ASTM E 1300 defines load resistance of glass as the uniform lateral loading acting over a duration of 3 seconds that is associated with a probability of breakage of 8 lites per 1000 at the first occurrence of the loading. To determine load resistance, the underlying window glass failure prediction model facilitates determination of a probability distribution of 3 second equivalent failure loads, P3. The glass failure prediction model is based on a Weibull distribution, and most people believe the distribution of P3 is, in fact, a Weibull distribution. However, the authors contend that this is not the case. This paper provides an explanation of the glass failure prediction model, its basis, and a discussion of the method for determining surface flaw parameters with an example. The authors demonstrate the distribution of the equivalent failure loads does not follow a Weibull distribution, and they will elucidate the relationship between the distribution of P3 and the Weibull distribution.
AB - Glass, a brittle material, fractures under tensile stress acting over a time duration. Lateral loads, such as wind, acting on a simply supported rectangular glass lite, put one surface of the lite primarily into tension. ASTM E 1300 defines load resistance of glass as the uniform lateral loading acting over a duration of 3 seconds that is associated with a probability of breakage of 8 lites per 1000 at the first occurrence of the loading. To determine load resistance, the underlying window glass failure prediction model facilitates determination of a probability distribution of 3 second equivalent failure loads, P3. The glass failure prediction model is based on a Weibull distribution, and most people believe the distribution of P3 is, in fact, a Weibull distribution. However, the authors contend that this is not the case. This paper provides an explanation of the glass failure prediction model, its basis, and a discussion of the method for determining surface flaw parameters with an example. The authors demonstrate the distribution of the equivalent failure loads does not follow a Weibull distribution, and they will elucidate the relationship between the distribution of P3 and the Weibull distribution.
KW - Equivalent failure load
KW - Glass failure prediction model
KW - Surface flaw parameters
KW - Weibull distribution
UR - http://www.scopus.com/inward/record.url?scp=85072843060&partnerID=8YFLogxK
U2 - 10.7480/cgc.6.2188
DO - 10.7480/cgc.6.2188
M3 - Conference contribution
T3 - Challenging Glass 6: Conference on Architectural and Structural Applications of Glass, CGC 2018 - Proceedings
BT - Challenging Glass 6
A2 - Louter, Christian
A2 - Bos, Freek
A2 - Belis, Jan
A2 - Veer, Fred
A2 - Nijsse, Rob
PB - TU Delft Open
T2 - 6th Challenging Glass Conference on Architectural and Structural Applications of Glass, CGC 2018
Y2 - 17 May 2018 through 18 May 2018
ER -