Term of Award

Spring 2011

Degree Name

Master of Science in Applied Engineering (M.S.A.E.)

Document Type and Release Option

Thesis (open access)

Copyright Statement / License for Reuse

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


Department of Mechanical Engineering

Committee Chair

Brian L. Vlcek

Committee Member 1

David Williams

Committee Member 2

Aniruddha Mitra


Since fatigue is probabilistic, trends observed in large populations of data are necessary to select materials, compare engineering designs, or establish preventative maintenance schedules. The generation of large experimental fatigue populations, however, is prohibitively time consuming and costly. As a solution a Weibull-based Monte Carlo simulation of fatigue life was developed based upon a failed "bin" model, and five billion fatigue lives were simulated. These fatigue lives were used to generate L10 lives. A model of confidence number was developed dependent upon statistically large samples of simulated L10 fatigue lives, and independent of a limited number of published curves. Using these simulated values, Confidence number figures were generated that deviated from 0.0% - 7.4% of previously published figures and were independent of confidence bands. Results differed as little as 1% from those determined graphically for experimental bearing data sets while graphical interpolation was eliminated.

Research Data and Supplementary Material