Linkage of Macro- and Microscale Modeling Tools for Additive Manufacturing of Steels
Additive manufacturing (AM) offers several benefits including the capability to produce unique microstructures, geometrical freedom allowing for material and energy savings, and easy production lines with fewer post-processing steps. However, AM processes are complex and phenomena occurring at diffe...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-05-01
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| Series: | Frontiers in Materials |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fmats.2022.797226/full |
| _version_ | 1817986222950187008 |
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| author | Julia Sjöström Julia Sjöström A. Durga Greta Lindwall |
| author_facet | Julia Sjöström Julia Sjöström A. Durga Greta Lindwall |
| author_sort | Julia Sjöström |
| collection | DOAJ |
| description | Additive manufacturing (AM) offers several benefits including the capability to produce unique microstructures, geometrical freedom allowing for material and energy savings, and easy production lines with fewer post-processing steps. However, AM processes are complex and phenomena occurring at different length and time scales need to be understood and controlled to avoid challenges with, for example, defects, residual stresses, distortions, and alloy restrictions. To overcome some of these challenges and to have more control over the final product, computational tools for different length scales need to be combined. In this work, an 18Ni300 maraging steel part is studied to understand the link between the process parameters and the as-built microstructure. The temperature evolution during laser powder bed fusion is simulated using the MSC simulation software Simufact Additive. This result is then linked to microscale models within the Thermo-Calc software package to predict the elemental micro-segregation, martensite start (Ms) temperature, and martensite fraction. The different values of the key process parameters such as laser speed, laser power, heating efficiency, and baseplate temperature are considered, leading to different thermal histories. The thermal histories affect the elemental segregation across the solidification structure, which in turn results in different Ms temperatures at different locations of the built part. It is found that higher laser energy generally causes higher temperatures and higher cooling rates, which results in a larger degree of elemental segregation and lower Ms temperatures in segregated regions. Furthermore, the segregated regions are predicted to have Ms temperatures below 200°C, which would result in retained austenite when using a baseplate temperature of 200°C. On the other hand, by using a baseplate temperature of 100°C, all regions would reach temperatures below the Ms temperature, and an almost fully martensitic structure would be possible. In summary, it is demonstrated how the linkage of macro- and microscale modeling tools for AM can be used to optimize the process and produce the desired microstructure, thereby achieving the desired mechanical properties. |
| first_indexed | 2024-04-14T00:07:38Z |
| format | Article |
| id | doaj.art-513860e27a604f5e8e0f8ae4dd1e365e |
| institution | Directory Open Access Journal |
| issn | 2296-8016 |
| language | English |
| last_indexed | 2024-04-14T00:07:38Z |
| publishDate | 2022-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Materials |
| spelling | doaj.art-513860e27a604f5e8e0f8ae4dd1e365e2022-12-22T02:23:29ZengFrontiers Media S.A.Frontiers in Materials2296-80162022-05-01910.3389/fmats.2022.797226797226Linkage of Macro- and Microscale Modeling Tools for Additive Manufacturing of SteelsJulia Sjöström0Julia Sjöström1A. Durga2Greta Lindwall3Department of Materials Science and Engineering, KTH Royal Institute of Technology, Stockholm, SwedenVBN Components AB, Uppsala, SwedenDepartment of Materials Science and Engineering, KTH Royal Institute of Technology, Stockholm, SwedenDepartment of Materials Science and Engineering, KTH Royal Institute of Technology, Stockholm, SwedenAdditive manufacturing (AM) offers several benefits including the capability to produce unique microstructures, geometrical freedom allowing for material and energy savings, and easy production lines with fewer post-processing steps. However, AM processes are complex and phenomena occurring at different length and time scales need to be understood and controlled to avoid challenges with, for example, defects, residual stresses, distortions, and alloy restrictions. To overcome some of these challenges and to have more control over the final product, computational tools for different length scales need to be combined. In this work, an 18Ni300 maraging steel part is studied to understand the link between the process parameters and the as-built microstructure. The temperature evolution during laser powder bed fusion is simulated using the MSC simulation software Simufact Additive. This result is then linked to microscale models within the Thermo-Calc software package to predict the elemental micro-segregation, martensite start (Ms) temperature, and martensite fraction. The different values of the key process parameters such as laser speed, laser power, heating efficiency, and baseplate temperature are considered, leading to different thermal histories. The thermal histories affect the elemental segregation across the solidification structure, which in turn results in different Ms temperatures at different locations of the built part. It is found that higher laser energy generally causes higher temperatures and higher cooling rates, which results in a larger degree of elemental segregation and lower Ms temperatures in segregated regions. Furthermore, the segregated regions are predicted to have Ms temperatures below 200°C, which would result in retained austenite when using a baseplate temperature of 200°C. On the other hand, by using a baseplate temperature of 100°C, all regions would reach temperatures below the Ms temperature, and an almost fully martensitic structure would be possible. In summary, it is demonstrated how the linkage of macro- and microscale modeling tools for AM can be used to optimize the process and produce the desired microstructure, thereby achieving the desired mechanical properties.https://www.frontiersin.org/articles/10.3389/fmats.2022.797226/fullmaraging steellaser powder bed fusiontemperature evolutionmacro-scale modelingmicro-segregationmulti-scale modeling |
| spellingShingle | Julia Sjöström Julia Sjöström A. Durga Greta Lindwall Linkage of Macro- and Microscale Modeling Tools for Additive Manufacturing of Steels Frontiers in Materials maraging steel laser powder bed fusion temperature evolution macro-scale modeling micro-segregation multi-scale modeling |
| title | Linkage of Macro- and Microscale Modeling Tools for Additive Manufacturing of Steels |
| title_full | Linkage of Macro- and Microscale Modeling Tools for Additive Manufacturing of Steels |
| title_fullStr | Linkage of Macro- and Microscale Modeling Tools for Additive Manufacturing of Steels |
| title_full_unstemmed | Linkage of Macro- and Microscale Modeling Tools for Additive Manufacturing of Steels |
| title_short | Linkage of Macro- and Microscale Modeling Tools for Additive Manufacturing of Steels |
| title_sort | linkage of macro and microscale modeling tools for additive manufacturing of steels |
| topic | maraging steel laser powder bed fusion temperature evolution macro-scale modeling micro-segregation multi-scale modeling |
| url | https://www.frontiersin.org/articles/10.3389/fmats.2022.797226/full |
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