Estimation of the probable maximum size of inclusions using statistics of extreme values and particle size distribution methods
Prediction of the maximum size of inclusion in a large weight of steel using data from a small volume steel sample is an important topic for steelmakers. Therefore, the probable maximum sizes (PMS) of inclusions in three steel grades were evaluated by the statistics of extreme values (SEV) and the p...
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Elsevier
2022-09-01
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| Series: | Journal of Materials Research and Technology |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2238785422011826 |
| _version_ | 1797991953692884992 |
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| author | Yong Wang Hong Bai Chengsong Liu Hua Zhang Hongwei Ni Pär Jönsson |
| author_facet | Yong Wang Hong Bai Chengsong Liu Hua Zhang Hongwei Ni Pär Jönsson |
| author_sort | Yong Wang |
| collection | DOAJ |
| description | Prediction of the maximum size of inclusion in a large weight of steel using data from a small volume steel sample is an important topic for steelmakers. Therefore, the probable maximum sizes (PMS) of inclusions in three steel grades were evaluated by the statistics of extreme values (SEV) and the particle size distributions (PSD) methods based on three-dimensional (3D) investigations of inclusions using the electrolytic extraction (EE) method. The effect of number of measurements and size of unit area on the PMS of inclusions were investigated. The results showed that at least 80 measurements of NMIs should be done in the SEV method, while in the PSD method the number of measurements has little influence when the number of inclusions in the observed areas was large enough. The effect of unit area size on the PMS of inclusions in the SEV method can be ignored for small-sized inclusions (less than 10 μm). The PMS of inclusions determined from the SEV method agreed with that from the PSD method by considering the 95% confidence interval. The SEV method was preferred when predicting the PMS of inclusions because of its simplicity by reducing the cost and labour involved compared to the PSD method. |
| first_indexed | 2024-04-11T09:00:21Z |
| format | Article |
| id | doaj.art-366cc4db455f49c9947d97bbd4a385db |
| institution | Directory Open Access Journal |
| issn | 2238-7854 |
| language | English |
| last_indexed | 2024-04-11T09:00:21Z |
| publishDate | 2022-09-01 |
| publisher | Elsevier |
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| series | Journal of Materials Research and Technology |
| spelling | doaj.art-366cc4db455f49c9947d97bbd4a385db2022-12-22T04:32:47ZengElsevierJournal of Materials Research and Technology2238-78542022-09-012024542465Estimation of the probable maximum size of inclusions using statistics of extreme values and particle size distribution methodsYong Wang0Hong Bai1Chengsong Liu2Hua Zhang3Hongwei Ni4Pär Jönsson5The State Key Laboratory of Refractories and Metallurgy, Wuhan University of Science and Technology, Wuhan, 430081, China; Department of Materials Science and Engineering, KTH Royal Institute of Technology, Stockholm, SE-100 44, SwedenKey Laboratory for Anisotropy and Texture of Materials, School of Materials Science and Engineering, Northeastern University, Shenyang, 110819, ChinaThe State Key Laboratory of Refractories and Metallurgy, Wuhan University of Science and Technology, Wuhan, 430081, China; Corresponding author.The State Key Laboratory of Refractories and Metallurgy, Wuhan University of Science and Technology, Wuhan, 430081, ChinaThe State Key Laboratory of Refractories and Metallurgy, Wuhan University of Science and Technology, Wuhan, 430081, China; Corresponding author.Department of Materials Science and Engineering, KTH Royal Institute of Technology, Stockholm, SE-100 44, SwedenPrediction of the maximum size of inclusion in a large weight of steel using data from a small volume steel sample is an important topic for steelmakers. Therefore, the probable maximum sizes (PMS) of inclusions in three steel grades were evaluated by the statistics of extreme values (SEV) and the particle size distributions (PSD) methods based on three-dimensional (3D) investigations of inclusions using the electrolytic extraction (EE) method. The effect of number of measurements and size of unit area on the PMS of inclusions were investigated. The results showed that at least 80 measurements of NMIs should be done in the SEV method, while in the PSD method the number of measurements has little influence when the number of inclusions in the observed areas was large enough. The effect of unit area size on the PMS of inclusions in the SEV method can be ignored for small-sized inclusions (less than 10 μm). The PMS of inclusions determined from the SEV method agreed with that from the PSD method by considering the 95% confidence interval. The SEV method was preferred when predicting the PMS of inclusions because of its simplicity by reducing the cost and labour involved compared to the PSD method.http://www.sciencedirect.com/science/article/pii/S2238785422011826Electrolytic extractionStatistics of extreme valuesParticle size distributionMaximum size |
| spellingShingle | Yong Wang Hong Bai Chengsong Liu Hua Zhang Hongwei Ni Pär Jönsson Estimation of the probable maximum size of inclusions using statistics of extreme values and particle size distribution methods Journal of Materials Research and Technology Electrolytic extraction Statistics of extreme values Particle size distribution Maximum size |
| title | Estimation of the probable maximum size of inclusions using statistics of extreme values and particle size distribution methods |
| title_full | Estimation of the probable maximum size of inclusions using statistics of extreme values and particle size distribution methods |
| title_fullStr | Estimation of the probable maximum size of inclusions using statistics of extreme values and particle size distribution methods |
| title_full_unstemmed | Estimation of the probable maximum size of inclusions using statistics of extreme values and particle size distribution methods |
| title_short | Estimation of the probable maximum size of inclusions using statistics of extreme values and particle size distribution methods |
| title_sort | estimation of the probable maximum size of inclusions using statistics of extreme values and particle size distribution methods |
| topic | Electrolytic extraction Statistics of extreme values Particle size distribution Maximum size |
| url | http://www.sciencedirect.com/science/article/pii/S2238785422011826 |
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