Publicação
Review on laser shock peening Effect on fatigue of power bed fusion materials
| Resumo: | The ability to manufacture parts with complex geometry by sending a model from CAD directly to the manufacturing machine has attracted much attention in the industry, driving the development of additive manufacturing technology. However, studies have shown that components manufactured using additive manufacturing technology have several problems, namely high tensile residual stresses, cracks, and voids, which are known to have a major impact on material performance (in service). Therefore, various post-treatment methods have been developed to address these drawbacks. Among the post-treatment techniques, laser shock peening (LSP) is currently considered one of the most efficient post-treatment technologies for improving the mechanical properties of materials. In practice, LSP is responsible for eliminating unfavorable tensile residual stresses and generating compressive residual stresses (CRS), which result in higher resistance to crack initiation and propagation, thus increasing component life. However, since CRS depends on many parameters, the optimization of LSP parameters remains a challenge. In this paper, a general overview of AM and LSP technology is first provided. It then describes which parameters have a greater influence during powder bed melting and LSP processing and how they affect the microstructure and mechanical properties of the material. Experimental, numerical, and analytical optimization approaches are also presented, and their results are discussed. Finally, a performance evaluation of the LSP technique in powder bed melting of metallic materials is presented. It is expected that the analysis presented in this review will stimulate further studies on the optimization of parameters via experimental, numerical, and perhaps analytical approaches that have not been well studied so far. |
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| Autores principais: | Bumba, Francisco |
| Outros Autores: | Morais, Paulo; Batalha, Rodolfo; Anes, Vitor; Reis, Luís |
| Assunto: | Laser shock peening Powder bed fusion Fatigue Residual stress |
| Ano: | 2023 |
| País: | Portugal |
| Tipo de documento: | artigo original |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Instituto Politécnico de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Científico do Instituto Politécnico de Lisboa |
| Resumo: | The ability to manufacture parts with complex geometry by sending a model from CAD directly to the manufacturing machine has attracted much attention in the industry, driving the development of additive manufacturing technology. However, studies have shown that components manufactured using additive manufacturing technology have several problems, namely high tensile residual stresses, cracks, and voids, which are known to have a major impact on material performance (in service). Therefore, various post-treatment methods have been developed to address these drawbacks. Among the post-treatment techniques, laser shock peening (LSP) is currently considered one of the most efficient post-treatment technologies for improving the mechanical properties of materials. In practice, LSP is responsible for eliminating unfavorable tensile residual stresses and generating compressive residual stresses (CRS), which result in higher resistance to crack initiation and propagation, thus increasing component life. However, since CRS depends on many parameters, the optimization of LSP parameters remains a challenge. In this paper, a general overview of AM and LSP technology is first provided. It then describes which parameters have a greater influence during powder bed melting and LSP processing and how they affect the microstructure and mechanical properties of the material. Experimental, numerical, and analytical optimization approaches are also presented, and their results are discussed. Finally, a performance evaluation of the LSP technique in powder bed melting of metallic materials is presented. It is expected that the analysis presented in this review will stimulate further studies on the optimization of parameters via experimental, numerical, and perhaps analytical approaches that have not been well studied so far. |
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