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Extreme value distributions of inclusions in six steels

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Abstract

There is a prevailing assumption that the largest inclusions in steel volumes follows mode I of the Generalized Extreme Values (GEV) distribution. In this work, the GEV distributions of non-metallic inclusions in six different high performance steels, of different grades and processing routes, were investigated by means of fractography of inclusions causing failure in ultrasonic fatigue testing to one billion cycles and all three modes of the GEV were found for the different steel grades. Values of the shape parameter ξ of the GEV distribution as high as 0.51 (standard deviation 0.11) were found in one steel grade. Thus, the present results show that the assumption of GEV-I (Gumbel, LEVD) distribution has to be substantiated before being used to estimate the size of the largest inclusions.

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References

  • Anderson, C.W., de Maré, J., Rootzen, H.: Methods for estimating the sizes of large inclusions in clean steels. Acta Mater. 53, 2295–2304 (2005)

    Article  Google Scholar 

  • Anderson, C.W., Shi, G., Atkinson, H.V., Sellars, C.M.: The precision of methods using the statistics of extremes for the estimation of the maximum size of inclusions in clean steels. Acta Mater. 48, 4235–4246 (2000)

    Article  Google Scholar 

  • Beretta, S., Murakami, Y.: Largest-extreme-value distribution analysis of multiple inclusion types in determining steel cleanliness. Metall. Mater. Trans., B 32, 517–523 (2001)

    Article  Google Scholar 

  • Coles, S.: Introduction to Statistical Modeling of Extreme Values. Springer, New York (2001)

    MATH  Google Scholar 

  • Ekengren, J., Kazymyrovych, V., Burman, C., Bergström, J.: Relating gigacycle fatigue to other methods in evaluating the inclusion distribution of a H13 tool steel. In: Proceedings of the Fourth International Conference on Very High Cycle Fatigue (2007)

  • Joossens, E.: Extreme value statistics: second-order models and applications in metal fatigue. Ph.D. thesis, K.U. Leuven (2006)

  • Murakami, Y.: Inclusion rating by statistics of extreme values and its application to fatigue strength prediction and quality control of materials. J. Res. Natl. Inst. Stand. Technol. 99, 345–351 (1994)

    Google Scholar 

  • Murakami, Y., Beretta, S.: Small defects and inhomogeneities in fatigue strength: experiments, models and statistical implications. Extremes 2(2), 123–147 (1999)

    Article  MATH  Google Scholar 

  • Nordberg, H.: Initiation of fatigue failures by non-metallic inclusions. In: Ohlson, N.-G., Nordberg, H. (eds.) Classical Fatigue (1985)

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Correspondence to Jens Ekengren.

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Ekengren, J., Bergström, J. Extreme value distributions of inclusions in six steels. Extremes 15, 257–265 (2012). https://doi.org/10.1007/s10687-011-0139-5

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  • DOI: https://doi.org/10.1007/s10687-011-0139-5

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