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Accurate estimation of Weibull parameters is an important issue for the characterization of the strength variability of brittle ceramics with Weibull statistics. In this paper, a simple method was established for the determination of the Weibull parameters, Weibull modulus m and scale parameter σ0, based on Monte Carlo simulation. It was shown that an unbiased estimation for Weibull modulus can be yielded directly from the coefficient of variation of the considered strength sample. Furthermore, using the yielded Weibull estimator and the mean value of the strength in the considered sample, the scale parameter σ0 can also be estimated accurately.


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Determination of the Weibull parameters from the mean value and the coefficient of variation of the measured strength for brittle ceramics

Show Author's information Bin DENGaDanyu JIANGb( )
Department of the Prosthodontics, Chinese PLA General Hospital, Beijing 100853, China
Analysis and Testing Center for Inorganic Materials, State Key Laboratory of High Performance Ceramics and Superfine Microstructure, Shanghai Institute of Ceramics, Shanghai 200050, China

Abstract

Accurate estimation of Weibull parameters is an important issue for the characterization of the strength variability of brittle ceramics with Weibull statistics. In this paper, a simple method was established for the determination of the Weibull parameters, Weibull modulus m and scale parameter σ0, based on Monte Carlo simulation. It was shown that an unbiased estimation for Weibull modulus can be yielded directly from the coefficient of variation of the considered strength sample. Furthermore, using the yielded Weibull estimator and the mean value of the strength in the considered sample, the scale parameter σ0 can also be estimated accurately.

Keywords:

Weibull distribution, Weibull parameters, strength variability, unbiased estimation, coefficient of variation
Received: 11 January 2017 Accepted: 07 April 2017 Published: 16 June 2017 Issue date: June 2017
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Publication history

Received: 11 January 2017
Accepted: 07 April 2017
Published: 16 June 2017
Issue date: June 2017

Copyright

© The author(s) 2017

Acknowledgements

The authors acknowledge the support of Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDB06050301).

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