Modeling of Tensile Test Results for Low Alloy Steels by Linear Regression and Genetic Programming Taking into Account the Non-Metallic Inclusions
Štore Steel Ltd. is one of the biggest flat spring steel producers in Europe. The main motive for this study was to study the influences of non-metallic inclusions on mechanical properties obtained by tensile testing. From January 2016 to December 2021, all available tensile strength data (472 cases...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-08-01
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| Series: | Metals |
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| Online Access: | https://www.mdpi.com/2075-4701/12/8/1343 |
| _version_ | 1797408826207502336 |
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| author | Miha Kovačič Uroš Župerl |
| author_facet | Miha Kovačič Uroš Župerl |
| author_sort | Miha Kovačič |
| collection | DOAJ |
| description | Štore Steel Ltd. is one of the biggest flat spring steel producers in Europe. The main motive for this study was to study the influences of non-metallic inclusions on mechanical properties obtained by tensile testing. From January 2016 to December 2021, all available tensile strength data (472 cases–472 test pieces) of 17 low alloy steel grades, which were ordered and used by the final user in rolled condition, were gathered. Based on the geometry of rolled bars, selected chemical composition, and average size of worst fields non-metallic inclusions (sulfur, silicate, aluminium and globular oxides), determined based on ASTM E45, several models for tensile strength, yield strength, percentage elongation, and percentage reduction area were obtained using linear regression and genetic programming. Based on modeling results in the period from January 2022 to April 2022, five successively cast batches of 30MnVS6 were produced with a statistically significant reduction of content of silicon (<i>t</i>-test, <i>p</i> < 0.05). The content of silicate type of inclusions, yield, and tensile strength also changed statistically significantly (<i>t</i>-test, <i>p</i> < 0.05). The average yield and tensile strength increased from 458.5 MPa to 525.4 MPa and from 672.7 MPa to 754.0 MPa, respectively. It is necessary to emphasize that there were no statistically significant changes in other monitored parameters. |
| first_indexed | 2024-03-09T04:05:11Z |
| format | Article |
| id | doaj.art-1164ef06285b466ab380ec02038b28ce |
| institution | Directory Open Access Journal |
| issn | 2075-4701 |
| language | English |
| last_indexed | 2024-03-09T04:05:11Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
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| series | Metals |
| spelling | doaj.art-1164ef06285b466ab380ec02038b28ce2023-12-03T14:07:08ZengMDPI AGMetals2075-47012022-08-01128134310.3390/met12081343Modeling of Tensile Test Results for Low Alloy Steels by Linear Regression and Genetic Programming Taking into Account the Non-Metallic InclusionsMiha Kovačič0Uroš Župerl1ŠTORE STEEL, d.o.o., Research and Development, 3220 Štore, SloveniaFaculty of Mechanical Engineering, University of Maribor, 2000 Maribor, SloveniaŠtore Steel Ltd. is one of the biggest flat spring steel producers in Europe. The main motive for this study was to study the influences of non-metallic inclusions on mechanical properties obtained by tensile testing. From January 2016 to December 2021, all available tensile strength data (472 cases–472 test pieces) of 17 low alloy steel grades, which were ordered and used by the final user in rolled condition, were gathered. Based on the geometry of rolled bars, selected chemical composition, and average size of worst fields non-metallic inclusions (sulfur, silicate, aluminium and globular oxides), determined based on ASTM E45, several models for tensile strength, yield strength, percentage elongation, and percentage reduction area were obtained using linear regression and genetic programming. Based on modeling results in the period from January 2022 to April 2022, five successively cast batches of 30MnVS6 were produced with a statistically significant reduction of content of silicon (<i>t</i>-test, <i>p</i> < 0.05). The content of silicate type of inclusions, yield, and tensile strength also changed statistically significantly (<i>t</i>-test, <i>p</i> < 0.05). The average yield and tensile strength increased from 458.5 MPa to 525.4 MPa and from 672.7 MPa to 754.0 MPa, respectively. It is necessary to emphasize that there were no statistically significant changes in other monitored parameters.https://www.mdpi.com/2075-4701/12/8/1343mechanical propertiestensile testtensile strengthyield strengthpercentage elongationpercentage reduction area |
| spellingShingle | Miha Kovačič Uroš Župerl Modeling of Tensile Test Results for Low Alloy Steels by Linear Regression and Genetic Programming Taking into Account the Non-Metallic Inclusions Metals mechanical properties tensile test tensile strength yield strength percentage elongation percentage reduction area |
| title | Modeling of Tensile Test Results for Low Alloy Steels by Linear Regression and Genetic Programming Taking into Account the Non-Metallic Inclusions |
| title_full | Modeling of Tensile Test Results for Low Alloy Steels by Linear Regression and Genetic Programming Taking into Account the Non-Metallic Inclusions |
| title_fullStr | Modeling of Tensile Test Results for Low Alloy Steels by Linear Regression and Genetic Programming Taking into Account the Non-Metallic Inclusions |
| title_full_unstemmed | Modeling of Tensile Test Results for Low Alloy Steels by Linear Regression and Genetic Programming Taking into Account the Non-Metallic Inclusions |
| title_short | Modeling of Tensile Test Results for Low Alloy Steels by Linear Regression and Genetic Programming Taking into Account the Non-Metallic Inclusions |
| title_sort | modeling of tensile test results for low alloy steels by linear regression and genetic programming taking into account the non metallic inclusions |
| topic | mechanical properties tensile test tensile strength yield strength percentage elongation percentage reduction area |
| url | https://www.mdpi.com/2075-4701/12/8/1343 |
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