Journal of Materials Science

, Volume 51, Issue 14, pp 6639–6661 | Cite as

Comparison of maximum likelihood approaches for analysis of composite stress rupture data

  • Amy Engelbrecht-Wiggans
  • Stuart Leigh Phoenix
Original Paper


Stress rupture is a sudden, stochastic failure mode that occurs in continuous unidirectional fiber composites and in particular composite overwrapped pressure vessels subject to long-term, steady loads. A common approach for modeling stress rupture is the probabilistic classic power-law model for material breakdown within a Weibull framework (CPL-W). This model includes a number of parameters, which need to be estimated from real data. These parameters may be estimated in a variety of different ways. This paper investigates how best to estimate the parameters of the CPL-W model given a set of experimental data for both composite strength and composite lifetime obtained at multiple stress levels. Eight different maximum likelihood estimation approaches are investigated regarding their differing errors of estimation. The accuracy of each method is estimated by repeated Monte Carlo simulations of specific instances of the CPL-W model typical of various carbon/epoxy and aramid/epoxy fiber composite systems; no actual experimental data are analyzed. One particular approach stands out as having the least estimation error while a commonly used approach does very poorly.


Failure Probability Load Level Failure Time Lifetime Data Stress Rupture 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We would like to acknowledge Dr. Richard Engelbrecht-Wiggans for his guidance and advice. We would also like to thank Dr. Michael Kezirian for his helpful discussions regarding the context of this work in applications. Funding was provided under NIST Agreement ID 70NANB14H323.

Compliance with ethical standards

Conflict of Interest

The authors declare that they have no conflict of interest in presenting this work.


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Amy Engelbrecht-Wiggans
    • 1
  • Stuart Leigh Phoenix
    • 1
  1. 1.Sibley School of Mechanical and Aerospace EngineeringCornell UniversityIthacaUSA

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