I. Bunaziv, E. W. Hovig, O. E. Godinez Brizuela, Kai Zhang, Xiang Ma, X. Ren, M. Eriksson, P. Skjetne
{"title":"预测铝合金激光焊接和增材制造缺陷的 CFD 模型","authors":"I. Bunaziv, E. W. Hovig, O. E. Godinez Brizuela, Kai Zhang, Xiang Ma, X. Ren, M. Eriksson, P. Skjetne","doi":"10.2351/7.0001401","DOIUrl":null,"url":null,"abstract":"Aluminum and its alloys are widely used in various applications including e-mobility applications due to their lightweight nature, high corrosion resistance, good electrical conductivity, and excellent processability such as extrusion and forming. However, aluminum and its alloys are difficult to process with a laser beam due to their high thermal conductivity and reflectivity. In this article, the two most used laser processes, i.e., laser welding and laser powder bed fusion (LPBF) additive manufacturing, for processing of aluminum have been studied. There are many common laser-material interaction mechanisms and challenges between the two processes. Deep keyhole mode is a preferred method for welding due to improved productivity, while a heat conduction mode is preferred in LPBF aiming for zero-defect parts. In LPBF, the processing maps are highly desirable to be constructed, which shows the transition zone. Presented numerical modeling provides a more in-depth understanding of porosity formation, and different laser beam movement paths have been tested including circular oscillation paths. High accuracy processing maps can be constructed for LPBF that allows us to minimize tedious and time-consuming experiments. As a result, a modeling framework is a highly viable option for the cost-efficient optimization of process parameters.","PeriodicalId":508142,"journal":{"name":"Journal of Laser Applications","volume":"111 11","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"CFD modeling for predicting imperfections in laser welding and additive manufacturing of aluminum alloys\",\"authors\":\"I. Bunaziv, E. W. Hovig, O. E. Godinez Brizuela, Kai Zhang, Xiang Ma, X. Ren, M. Eriksson, P. Skjetne\",\"doi\":\"10.2351/7.0001401\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aluminum and its alloys are widely used in various applications including e-mobility applications due to their lightweight nature, high corrosion resistance, good electrical conductivity, and excellent processability such as extrusion and forming. However, aluminum and its alloys are difficult to process with a laser beam due to their high thermal conductivity and reflectivity. In this article, the two most used laser processes, i.e., laser welding and laser powder bed fusion (LPBF) additive manufacturing, for processing of aluminum have been studied. There are many common laser-material interaction mechanisms and challenges between the two processes. Deep keyhole mode is a preferred method for welding due to improved productivity, while a heat conduction mode is preferred in LPBF aiming for zero-defect parts. In LPBF, the processing maps are highly desirable to be constructed, which shows the transition zone. Presented numerical modeling provides a more in-depth understanding of porosity formation, and different laser beam movement paths have been tested including circular oscillation paths. High accuracy processing maps can be constructed for LPBF that allows us to minimize tedious and time-consuming experiments. As a result, a modeling framework is a highly viable option for the cost-efficient optimization of process parameters.\",\"PeriodicalId\":508142,\"journal\":{\"name\":\"Journal of Laser Applications\",\"volume\":\"111 11\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Laser Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2351/7.0001401\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Laser Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2351/7.0001401","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
CFD modeling for predicting imperfections in laser welding and additive manufacturing of aluminum alloys
Aluminum and its alloys are widely used in various applications including e-mobility applications due to their lightweight nature, high corrosion resistance, good electrical conductivity, and excellent processability such as extrusion and forming. However, aluminum and its alloys are difficult to process with a laser beam due to their high thermal conductivity and reflectivity. In this article, the two most used laser processes, i.e., laser welding and laser powder bed fusion (LPBF) additive manufacturing, for processing of aluminum have been studied. There are many common laser-material interaction mechanisms and challenges between the two processes. Deep keyhole mode is a preferred method for welding due to improved productivity, while a heat conduction mode is preferred in LPBF aiming for zero-defect parts. In LPBF, the processing maps are highly desirable to be constructed, which shows the transition zone. Presented numerical modeling provides a more in-depth understanding of porosity formation, and different laser beam movement paths have been tested including circular oscillation paths. High accuracy processing maps can be constructed for LPBF that allows us to minimize tedious and time-consuming experiments. As a result, a modeling framework is a highly viable option for the cost-efficient optimization of process parameters.