Development of Closed-Form Equations for Estimating Mechanical Properties of Weld Metals according to Chemical Composition
In this study, data analysis was performed using an artificial neural network (ANN) approach to investigate the effect of the chemical composition of welds on their mechanical properties (yield strength, tensile strength, and impact toughness). Based on the data collected from previously performed e...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | Metals |
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| Online Access: | https://www.mdpi.com/2075-4701/12/3/528 |
| _version_ | 1797444921885458432 |
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| author | Jeong-Hwan Kim Chang-Ju Jung Young IL Park Yong-Taek Shin |
| author_facet | Jeong-Hwan Kim Chang-Ju Jung Young IL Park Yong-Taek Shin |
| author_sort | Jeong-Hwan Kim |
| collection | DOAJ |
| description | In this study, data analysis was performed using an artificial neural network (ANN) approach to investigate the effect of the chemical composition of welds on their mechanical properties (yield strength, tensile strength, and impact toughness). Based on the data collected from previously performed experiments, correlations between related variables and results were analyzed and predictive models were developed. Sufficient datasets were prepared using data augmentation techniques to solve problems caused by insufficient data and to make better predictions. Finally, closed-form equations were developed based on the predictive models to evaluate the mechanical properties according to the chemical composition. |
| first_indexed | 2024-03-09T13:18:27Z |
| format | Article |
| id | doaj.art-69c463c8445a41ee9d335ed28f9120e8 |
| institution | Directory Open Access Journal |
| issn | 2075-4701 |
| language | English |
| last_indexed | 2024-03-09T13:18:27Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Metals |
| spelling | doaj.art-69c463c8445a41ee9d335ed28f9120e82023-11-30T21:32:38ZengMDPI AGMetals2075-47012022-03-0112352810.3390/met12030528Development of Closed-Form Equations for Estimating Mechanical Properties of Weld Metals according to Chemical CompositionJeong-Hwan Kim0Chang-Ju Jung1Young IL Park2Yong-Taek Shin3Department of Naval Architecture and Offshore Engineering, Dong-A University, Busan 49315, KoreaDepartment of Naval Architecture and Offshore Engineering, Dong-A University, Busan 49315, KoreaDepartment of Naval Architecture and Offshore Engineering, Dong-A University, Busan 49315, KoreaDepartment of Naval Architecture and Offshore Engineering, Dong-A University, Busan 49315, KoreaIn this study, data analysis was performed using an artificial neural network (ANN) approach to investigate the effect of the chemical composition of welds on their mechanical properties (yield strength, tensile strength, and impact toughness). Based on the data collected from previously performed experiments, correlations between related variables and results were analyzed and predictive models were developed. Sufficient datasets were prepared using data augmentation techniques to solve problems caused by insufficient data and to make better predictions. Finally, closed-form equations were developed based on the predictive models to evaluate the mechanical properties according to the chemical composition.https://www.mdpi.com/2075-4701/12/3/528data analysisartificial neural network (ANN)chemical composition of weldsdata augmentation technique |
| spellingShingle | Jeong-Hwan Kim Chang-Ju Jung Young IL Park Yong-Taek Shin Development of Closed-Form Equations for Estimating Mechanical Properties of Weld Metals according to Chemical Composition Metals data analysis artificial neural network (ANN) chemical composition of welds data augmentation technique |
| title | Development of Closed-Form Equations for Estimating Mechanical Properties of Weld Metals according to Chemical Composition |
| title_full | Development of Closed-Form Equations for Estimating Mechanical Properties of Weld Metals according to Chemical Composition |
| title_fullStr | Development of Closed-Form Equations for Estimating Mechanical Properties of Weld Metals according to Chemical Composition |
| title_full_unstemmed | Development of Closed-Form Equations for Estimating Mechanical Properties of Weld Metals according to Chemical Composition |
| title_short | Development of Closed-Form Equations for Estimating Mechanical Properties of Weld Metals according to Chemical Composition |
| title_sort | development of closed form equations for estimating mechanical properties of weld metals according to chemical composition |
| topic | data analysis artificial neural network (ANN) chemical composition of welds data augmentation technique |
| url | https://www.mdpi.com/2075-4701/12/3/528 |
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