Probability Distributions in the Glass Failure Prediction Model
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 act...
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| Format: | Article |
| Language: | English |
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Challenging Glass Conference
2018-05-01
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| Series: | Challenging Glass Conference Proceedings |
| Subjects: | |
| Online Access: | https://proceedings.challengingglass.com/index.php/cgc/article/view/79 |
| _version_ | 1818904705739259904 |
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| author | Samir Blanchet H. Scott Norville Stephen M. Morse |
| author_facet | Samir Blanchet H. Scott Norville Stephen M. Morse |
| author_sort | Samir Blanchet |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-19T21:11:41Z |
| format | Article |
| id | doaj.art-8431695102a74d5c98f8a34153336ba8 |
| institution | Directory Open Access Journal |
| issn | 2589-8019 |
| language | English |
| last_indexed | 2024-12-19T21:11:41Z |
| publishDate | 2018-05-01 |
| publisher | Challenging Glass Conference |
| record_format | Article |
| series | Challenging Glass Conference Proceedings |
| spelling | doaj.art-8431695102a74d5c98f8a34153336ba82022-12-21T20:05:28ZengChallenging Glass ConferenceChallenging Glass Conference Proceedings2589-80192018-05-016110.7480/cgc.6.218866Probability Distributions in the Glass Failure Prediction ModelSamir Blanchet0H. Scott Norville1Stephen M. Morse2Texas Tech UniversityTexas Tech UniversityMichigan Tech UniversityGlass, 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.https://proceedings.challengingglass.com/index.php/cgc/article/view/79Glass Failure Prediction ModelSurface Flaw ParametersWeibull DistributionEquivalent Failure Load |
| spellingShingle | Samir Blanchet H. Scott Norville Stephen M. Morse Probability Distributions in the Glass Failure Prediction Model Challenging Glass Conference Proceedings Glass Failure Prediction Model Surface Flaw Parameters Weibull Distribution Equivalent Failure Load |
| title | Probability Distributions in the Glass Failure Prediction Model |
| title_full | Probability Distributions in the Glass Failure Prediction Model |
| title_fullStr | Probability Distributions in the Glass Failure Prediction Model |
| title_full_unstemmed | Probability Distributions in the Glass Failure Prediction Model |
| title_short | Probability Distributions in the Glass Failure Prediction Model |
| title_sort | probability distributions in the glass failure prediction model |
| topic | Glass Failure Prediction Model Surface Flaw Parameters Weibull Distribution Equivalent Failure Load |
| url | https://proceedings.challengingglass.com/index.php/cgc/article/view/79 |
| work_keys_str_mv | AT samirblanchet probabilitydistributionsintheglassfailurepredictionmodel AT hscottnorville probabilitydistributionsintheglassfailurepredictionmodel AT stephenmmorse probabilitydistributionsintheglassfailurepredictionmodel |