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Numerical and experimental analysis for solidification and residual stress in the GMAW process for AISI 304 stainless steel

dc.contributor.authorChoi, J.en_US
dc.contributor.authorMazumder, Jyotien_US
dc.date.accessioned2006-09-11T15:14:58Z
dc.date.available2006-09-11T15:14:58Z
dc.date.issued2002-05en_US
dc.identifier.citationChoi, J.; Mazumder, J.; (2002). "Numerical and experimental analysis for solidification and residual stress in the GMAW process for AISI 304 stainless steel." Journal of Materials Science 37(10): 2143-2158. <http://hdl.handle.net/2027.42/44769>en_US
dc.identifier.issn1573-4803en_US
dc.identifier.issn0022-2461en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/44769
dc.description.abstractGas Metal Arc Welding (GMAW) process was analyzed by combining a finite element thermomechanical model for temperature and stress with solidification model. Model prediction was compared with experimental data in order to validate the model. The effects of welding process parameters on these welding fields were analyzed and reported. The effort to correlate the residual stress and solidification was initiated, yielding some valuable results. The solidification process was simulated using the formulation based on the Hunt-Trivedi model. Based on the temperature history, solidification speed and primary dendrite arm spacing were predicted at given nodes of interest. Results show that the variation during solidification is usually within an order of magnitude. The temperature gradient was generally in the range of 10 4 –10 5 K/m for the given welding conditions (welding power = 6 kW and welding speed = 3.39 to 7.62 mm/sec), while solidification speed appeared to slow down from an order of 10 −2 to 10 −3 m/sec during solidification. SEM images revealed that the Primary Dendrite Arm Spacing (PDAS) fell in the range of 10 1 −10 2 μm. The range of predicted sizes was in agreement with the experimental values. It was observed that the average size of the PDAS was dependent upon the welding speed. The PDAS fell between 7.5 to 20 μm for columnar and 10 to 30 μm for equiaxed dendrites, for welding speeds between 3.39 to 7.62 mm/sec. When the welding speed increased, it was observed that the average size of the PDAS decreased, as the model had predicted. For grain growth at the Heat Affected Zone (HAZ), Ashby's model was employed, and the prediction was in agreement with experimental results. For the residual stress calculation, the same mesh generation used in the heat transfer analysis was applied to make the simulation consistent. The analysis consisted of a transient heat analysis followed by a thermal stress analysis. An experimentally measured strain history was compared with the simulated result. The relationship between microstructure and the stress/strain field of welding was also obtained.en_US
dc.format.extent398692 bytes
dc.format.extent3115 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherKluwer Academic Publishers; Springer Science+Business Mediaen_US
dc.subject.otherCharacterization and Evaluation Materialsen_US
dc.subject.otherChemistryen_US
dc.subject.otherPolymer Sciencesen_US
dc.subject.otherIndustrial Chemistry/Chemical Engineeringen_US
dc.subject.otherMechanicsen_US
dc.titleNumerical and experimental analysis for solidification and residual stress in the GMAW process for AISI 304 stainless steelen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelMaterials Science and Engineeringen_US
dc.subject.hlbsecondlevelEngineering (General)en_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumCenter for Laser-Aided Intelligent Manufacturing, Department of Mechanical Engineering, University of Michigan at Ann Arbor, Ann Arbor, MI, 48109, USAen_US
dc.contributor.affiliationumCenter for Laser-Aided Intelligent Manufacturing, Department of Mechanical Engineering, University of Michigan at Ann Arbor, Ann Arbor, MI, 48109, USAen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/44769/1/10853_2004_Article_5089117.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1023/A:1015258322780en_US
dc.identifier.sourceJournal of Materials Scienceen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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