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dc.contributor.authorPagáč, Marek
dc.contributor.authorHajnyš, Jiří
dc.contributor.authorHalama, Radim
dc.contributor.authorAldabash, Tariq
dc.contributor.authorMěsíček, Jakub
dc.contributor.authorJančar, Lukáš
dc.contributor.authorJansa, Jan
dc.date.accessioned2021-05-19T09:51:39Z
dc.date.available2021-05-19T09:51:39Z
dc.date.issued2021
dc.identifier.citationApplied Sciences. 2021, vol. 11, issue 4, art. no. 1656.cs
dc.identifier.issn2076-3417
dc.identifier.urihttp://hdl.handle.net/10084/143072
dc.description.abstractThis paper deals with an experimental analysis of stress prediction and simulation prior to 3D printing via the selective laser melting (SLM) method and the subsequent separation of a printed sample from a base plate in two software programs, ANSYS Addictive Suite and MSC Simufact Additive. Practical verification of the simulation was performed on a 3Dprinted topologically optimized part made of AISI 316L stainless steel. This paper presents a typical workflow for working with metallic 3D printing technology and the state-of-the-art knowledge in the field of stress analysis and simulation of printed components. The paper emphasizes the role of simulation software for additive production and reflects on their weaknesses and strengths as well, with regard to their use not only in science and research but also in practice.cs
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofseriesApplied Sciencescs
dc.relation.urihttps://doi.org/10.3390/app11041656cs
dc.rights© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectSLMcs
dc.subjectAISI 316Lcs
dc.subjectadditive manufacturing (AM)cs
dc.subjectFEMcs
dc.subject3D scancs
dc.subjectdistortioncs
dc.titlePrediction of model distortion by FEM in 3D printing via the selective laser melting of stainless steel AISI 316Lcs
dc.typearticlecs
dc.identifier.doi10.3390/app11041656
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume11cs
dc.description.issue4cs
dc.description.firstpageart. no. 1656cs
dc.identifier.wos000632126900001


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© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
Except where otherwise noted, this item's license is described as © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.