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Statistical Analysis of Slow Crack Growth Experiments




A common approach for the determination of Slow Crack Growth (SCG) parameters are the static and dynamic loading method. Since materials with small Weibull module show a large variability in strength, a correct statistical analysis of the data is indispensable. In this work we propose the use of the Maximum Likelihood method and a Baysian analysis, which, in contrast to the standard procedures, take into account that failure strengths are Weibull distributed. The analysis provides estimates for the SCG parameters, the Weibull module, and the corresponding confidence intervals and overcomes the necessity of manual differentiation between inert and fatigue strength data. We compare the methods to a Least Squares approach, which can be considered the standard procedure. The results for dynamic loading data from the glass sealing of MEMS devices show that the assumptions inherent to the standard approach lead to significantly different estimates.

Author(s): Pfingsten, T. and Glien, K.
Journal: Journal of the European Ceramic Society
Volume: 26
Number (issue): 15
Pages: 3061-3065
Year: 2006
Month: November
Day: 0

Department(s): Empirical Inference
Bibtex Type: Article (article)

Digital: 0
DOI: doi:10.1016/j.jeurceramsoc.2005.08.004
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

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  title = {Statistical Analysis of Slow Crack Growth
  author = {Pfingsten, T. and Glien, K.},
  journal = {Journal of the European Ceramic Society},
  volume = {26},
  number = {15},
  pages = {3061-3065},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  month = nov,
  year = {2006},
  month_numeric = {11}