About this Abstract |
Meeting |
2020 TMS Annual Meeting & Exhibition
|
Symposium
|
Fatigue in Materials: Fundamentals, Multiscale Characterizations and Computational Modeling
|
Presentation Title |
Statistical Modeling of Censored Life Data |
Author(s) |
D. Gary Harlow |
On-Site Speaker (Planned) |
D. Gary Harlow |
Abstract Scope |
Frequently fatigue life tests are censored prior to failure, particularly for high cycles. Censoring is utilized because the number of cycles required to reach failure exceed the allotted physical time or costs. The major issue is that censoring occurs for extrema where high reliability is required. New materials often have limited life data, especially for typical operating conditions. Accurate statistical modeling of censored life data are critical, albeit more challenging than modeling complete data. A methodology where variability can be managed for censored life data is illustrated. The variability is assumed to be cumulative from all sources. The procedure focuses on the fusion of experimental data over different applied loading conditions. The approach is contrasted with classical statistical characterization techniques for life analysis. The major conclusion is that using all available data, including censored data, improves estimation of life distribution functions, leading to more accurate prediction of reliability. |
Proceedings Inclusion? |
Planned: Supplemental Proceedings volume |