A Numerical Study of Topography and Roughness of Sloped Surfaces Using Process Simulation Data for Laser Powder Bed Fusion

MakaleAçık ErişimScopus SJRQ2

Özet

The simulation of additive manufacturing has become a prominent research area in the past decade. Process physics simulations are employed to replicate laser powder bed fusion (L-PBF) manufacturing processes, aiming to predict potential issues through simulated data. This study focuses on calculating surface roughness by utilizing 3D surface topology extracted from simulated data, as surface roughness significantly influences part quality. Accurately predicting surface roughness using a simulation remains a persistent challenge. To address this challenge, the L-PBF technique with two different cases (pre- and post-contouring) was simulated using two-step process physics simulations. The discrete element method was utilized to simulate powder spreading, followed by the Flow-3D melting simulation. Ten layers were simulated at three different linear energy density (LED) combinations for both cases, with samples positioned at a 30-degree angle to accommodate upskin and downskin effects. Furthermore, a three-dimensional representation of the melted region for each layer was generated using the thermal gradient output from the simulated data. All generated 3D layers were stacked and merged to consolidate a 3D representation of the overall sample. The surfaces (upskin, downskin, and side skins) were extracted from this merged sample. Subsequently, these surfaces were analyzed, and surface roughness (Sa values) was calculated using MATLAB. The obtained values were then compared with experimental results. The downskin surface roughness results from the simulation were found to be within the range of the experimental results. This alignment is attributed to the fact that the physics simulation primarily focuses on melt pool depth and width. These promising findings indicate the potential for accurately predicting surface roughness through simulation.

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RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/bayburt/12997Resmi atıflarda kullanılan kalıcı adres
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https://doi.org/10.3390/ma17235955Yayıncı resmi DOI adresi
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Tam Kayıt
AlanDeğerDil
dc.contributor.authorAydogan, Beytullah
dc.contributor.authorChou, Kevin
dc.date.accessioned2026-10-29T19:10:19.952586113Z
dc.date.available2026-10-29T19:10:19.952586113Z
dc.date.issued2024
dc.description.abstractThe simulation of additive manufacturing has become a prominent research area in the past decade. Process physics simulations are employed to replicate laser powder bed fusion (L-PBF) manufacturing processes, aiming to predict potential issues through simulated data. This study focuses on calculating surface roughness by utilizing 3D surface topology extracted from simulated data, as surface roughness significantly influences part quality. Accurately predicting surface roughness using a simulation remains a persistent challenge. To address this challenge, the L-PBF technique with two different cases (pre- and post-contouring) was simulated using two-step process physics simulations. The discrete element method was utilized to simulate powder spreading, followed by the Flow-3D melting simulation. Ten layers were simulated at three different linear energy density (LED) combinations for both cases, with samples positioned at a 30-degree angle to accommodate upskin and downskin effects. Furthermore, a three-dimensional representation of the melted region for each layer was generated using the thermal gradient output from the simulated data. All generated 3D layers were stacked and merged to consolidate a 3D representation of the overall sample. The surfaces (upskin, downskin, and side skins) were extracted from this merged sample. Subsequently, these surfaces were analyzed, and surface roughness (Sa values) was calculated using MATLAB. The obtained values were then compared with experimental results. The downskin surface roughness results from the simulation were found to be within the range of the experimental results. This alignment is attributed to the fact that the physics simulation primarily focuses on melt pool depth and width. These promising findings indicate the potential for accurately predicting surface roughness through simulation.
dc.description.sponsorshipUniversity of Louisville Research Foundation
dc.identifier.articlenumber5955
dc.identifier.doi10.3390/ma17235955
dc.identifier.eissn1996-1944
dc.identifier.issn1996-1944
dc.identifier.issue23
dc.identifier.pmcidPMC11643527
dc.identifier.pmid39685391
dc.identifier.scopus2-s2.0-85211918004
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/bayburt/12997
dc.identifier.volume17
dc.identifier.wosWOS:001376375900001
dc.language.isoen
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)
dc.relation.ispartofMaterials
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectadditive manufacturing
dc.subjectlaser powder bed fusion
dc.subjectprocess simulation
dc.subjectsurface roughness
dc.subjecttopography
dc.subject.classificationChemistry, Physical
dc.subject.classificationMaterials Science, Multidisciplinary
dc.subject.classificationMetallurgy & Metallurgical Engineering
dc.subject.classificationPhysics, Applied
dc.subject.classificationPhysics, Condensed Matter
dc.subject.classificationChemistry
dc.subject.classificationMaterials Science
dc.subject.classificationPhysics
dc.subject.otherLaser materials processing
dc.subject.otherLayered manufacturing
dc.subject.otherSupersaturation
dc.subject.otherSurface topography
dc.subject.otherContouring
dc.subject.otherLaser powder bed fusion
dc.subject.otherLaser powders
dc.subject.otherManufacturing process
dc.subject.otherPhysics simulation
dc.subject.otherPowder bed
dc.subject.otherProcess simulations
dc.subject.otherResearch areas
dc.subject.otherSimulation data
dc.subject.otherSloped surfaces
dc.subject.otherMATLAB
dc.titleA Numerical Study of Topography and Roughness of Sloped Surfaces Using Process Simulation Data for Laser Powder Bed Fusion
dc.typeArticle
rdl.citation.openalex1
rdl.citation.scopus0
rdl.citation.wos0
rdl.departmentDepartment of Industrial Engineering, J.B. Speed School of Engineering, University of Louisville, Louisville, KY 40292, USA
rdl.departmentBayburt University, Bayburt 69000, Turkey
rdl.oa.statusgold
rdl.oa.statusgreen
rdl.oa.urlhttps://doi.org/10.3390/ma17235955
rdl.scopus.quartileQ2
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.source.indexPUBMED
rdl.wos.indexScience Citation Index Expanded (SCI-EXPANDED)