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Determination of Size Distribution and Probable Maximum Size of Inclusions in AISI304 Stainless Steel
KTH, School of Industrial Engineering and Management (ITM), Materials Science and Engineering, Applied Process Metallurgy.
KTH, School of Industrial Engineering and Management (ITM), Materials Science and Engineering, Applied Process Metallurgy.
2013 (English)In: ISIJ International, ISSN 0915-1559, E-ISSN 1347-5460, Vol. 53, no 11, 1968-1973 p.Article in journal (Refereed) Published
Abstract [en]

The probable maximum sizes (PMS) of inclusions in AISI304 stainless steels were predicted by two methods of the statistics of extreme values (SEV) and the particle size distributions (PSD). Firstly, the PMS of inclusions in the molten steel taken from a tundish agreed well with those in the slab sample. The particle size distributions (PSD) of inclusions almost obeyed exponential functions. The results of comparison between the two methods showed that the PMS by the SEV analysis agreed with that by the PSD approximation in the case of the steel with the higher oxygen content. However, in the case of the steel with the lower oxygen content, the PMS by the PSD approximation overestimated the predicted size with the reference to the SEV analysis. In this case, the approximations with elimination of some largest inclusions which were deviated from an exponential distribution were found to be effective to predict the probable largest size in a reference area. This above result suggests that it is necessary to decide if some largest inclusions are employed for adequate predictions. It is considered that necessity of this operation increases with decreasing oxygen content.

Place, publisher, year, edition, pages
2013. Vol. 53, no 11, 1968-1973 p.
Keyword [en]
stainless steel, inclusion, particle size distribution, statistics of extreme values, maximum size
National Category
Metallurgy and Metallic Materials
Identifiers
URN: urn:nbn:se:kth:diva-139187DOI: 10.2355/isijinternational.53.1968ISI: 000327809300011Scopus ID: 2-s2.0-84889031214OAI: oai:DiVA.org:kth-139187DiVA: diva2:685458
Note

QC 20140109

Available from: 2014-01-09 Created: 2014-01-08 Last updated: 2017-12-06Bibliographically approved

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