Computational Modeling of Microstructural-Evolution in AISI 1005 Steel During Gas Metal Arc Butt Welding

Grujičić, M.; Ramaswami, S.; Snipes, J. S.; Yavari, R.; Arakere, A.; Yen, Chian-Fong; Cheeseman, B. A.

doi:10.1007/s11665-012-0402-1

Cited by 19 publications

(12 citation statements)

References 29 publications

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“…These deficiencies of the public-domain GMAW process models have been addressed in our recently developed multiphysics GMAW process model (Ref [1][2][3][4][5]. A brief description of the basic structure of this model and the defining features of its six modules will be provided in section 2.…”

Section: Gmaw Process Modelingmentioning

confidence: 99%

“…Our recently proposed multi-physics computational model for the conventional gas metal arc welding (GMAW) joining process (Ref [1][2][3][4][5] has been extended in the present work with respect to its predictive capabilities regarding the process optimization for the attainment of maximum ballistic limit within the weld. The original GMAW process model was already capable of correlating the welding process parameters with the spatial distribution of the ballistic limit within the weld (consisting of the solidified weld pool, also referred to as the fusion zone, FZ, and the adjacent heat-affected zone, HAZ).…”

Section: Introductionmentioning

confidence: 99%

“…Based on the overview presented above, the concepts most relevant to the present work are (a) the basics of GMAW; (b) weld zones; (c) weld microstructure evolution in steels; (d) welding of MIL A46100 steel; (e) GMAW process modeling; and (f) GMAW process optimization. Since the concepts (a)-(c) were covered in great detail in (Ref [1][2][3][4][5], the same will not be reviewed here. On the other hand, in the remainder of this section, a brief description is provided for concepts (d)-(f).…”

Section: Introductionmentioning

confidence: 99%

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Optimization of Gas Metal Arc Welding (GMAW) Process for Maximum Ballistic Limit in MIL A46100 Steel Welded All-Metal Armor

Grujičić

Ramaswami

Snipes

et al. 2014

J. of Materi Eng and Perform

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Our recently developed multi-physics computational model for the conventional gas metal arc welding (GMAW) joining process has been upgraded with respect to its predictive capabilities regarding the process optimization for the attainment of maximum ballistic limit within the weld. The original model consists of six modules, each dedicated to handling a specific aspect of the GMAW process, i.e., (a) electro-dynamics of the welding gun; (b) radiation-/convection-controlled heat transfer from the electric arc to the workpiece and mass transfer from the filler metal consumable electrode to the weld; (c) prediction of the temporal evolution and the spatial distribution of thermal and mechanical fields within the weld region during the GMAW joining process; (d) the resulting temporal evolution and spatial distribution of the material microstructure throughout the weld region; (e) spatial distribution of the as-welded material mechanical properties; and (f) spatial distribution of the material ballistic limit. In the present work, the model is upgraded through the introduction of the seventh module in recognition of the fact that identification of the optimum GMAW process parameters relative to the attainment of the maximum ballistic limit within the weld region entails the use of advanced optimization and statistical sensitivity analysis methods and tools. The upgraded GMAW process model is next applied to the case of butt welding of MIL A46100 (a prototypical high-hardness armor-grade martensitic steel) workpieces using filler metal electrodes made of the same material. The predictions of the upgraded GMAW process model pertaining to the spatial distribution of the material microstructure and ballistic limit-controlling mechanical properties within the MIL A46100 butt weld are found to be consistent with general expectations and prior observations.

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Section: Gmaw Process Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimization of Gas Metal Arc Welding (GMAW) Process for Maximum Ballistic Limit in MIL A46100 Steel Welded All-Metal Armor

Grujičić

Ramaswami

Snipes

et al. 2014

J. of Materi Eng and Perform

Self Cite

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“…Rosenthal developed an equation for predicting cooling rates and peak temperatures in HAZ of weldment for thin plates. On the other hand, cooling rate and peak temperatures could be measured by thermocouple [17][18][19][20][21]. Because weld metals are subjected to continuous cooling upon solidification, the resultant microstructures should be predictable from continuous cooling transformation (CCT) diagrams [24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

The Relationship Between Continuous Cooling Rate and Microstructure in the Heat Affected Zone (Haz) of the Dissimilar Weld Between Carbon Steel and Austenitic Stainless Steel

Le¹,

Khanh²,

Le³

et al. 2017

Acta Metall Slovaca

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This paper investigates the changed in the microstructure in HAZ of the dissimilar weld between carbon steel and 304 austenitic stainless steel. Continuous cooling transformation diagrams (CCT), peak temperature profiles and cooling rates can be used to predict the change in the microstructure of the HAZ during the welding process. Optical microscopy, X -ray, SEM and TEM were used to determine the phases which formed in HAZ of carbon steel and austenitic stainless steel. The results of this study indicate that grain size in HAZ depended on the temperature at that point could be reached during the welding. Fully Martensitic layer observed at the interface in carbon side due to the combination of the rapid cooling subsequent to weld and local chemical composition. Cooling rate played the rule on forming Widmanstatten ferrite, Bainite and Pearlite. On the other hand, microstructures and grain size in HAZ of austenitic stainless steel were not affected by temperature and cooling rate. Carbides precipitation (M23C6, M7C3), however, were found in the boundary of grains.

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“…Smith et al (2012) took into account the material hardening model and high temperature annealing behavior in the FE model for accurate prediction of residual stress in stainless steel welds. In recently years, Grujicic et al (2013Grujicic et al ( , 2014Grujicic et al ( , 2015a developed a multi-physics finite-element procedure in which the contributions of microstructure evolution of the weld metal and heat affected zone to residual stress are considered.…”

Section: Introductionmentioning

confidence: 99%

Effects of material hardening model and lumped-pass method on welding residual stress simulation of J-groove weld in nuclear RPV

Liu

Luo

Yang

et al. 2016

Engineering Computations

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Purpose -The purpose of this paper is to clarify the effect of material hardening model and lump-pass method on the thermal-elastic-plastic (TEP) finite element (FE) simulation of residual stress induced by multi-pass welding of materials with cyclic plasticity. Design/methodology/approach -Nickel-base alloy and stainless steel, which are used in J-type weld for manufacturing the nuclear reactor pressure head, can easily harden during multi-pass welding. The J-weld welding experiment is carried out and the temperature cycle and residual stress are measured to validate the TEP simulation. Thermal-mechanical sequence coupling method is employed to get the welding residual stress. The lumped-pass model and pass-by-pass FE model are built and two materials hardening models, kinematic hardening model and mixed hardening model, are adopted during the simulations. The effects of material hardening models and lumped-pass method on the residual stress in J-weld are distinguished. Findings -Based on the kinematic hardening model, the stresses simulated with the lumped-pass FE model are almost consistent with those obtained by the pass-by-pass FE model; while with the mixed hardening material model, the lumped-pass method has great effect on the simulated stress. Practical implications -A computation with mixed isotropic-kinematic material seems not to be the appropriate solution when using the lumped-pass method to save the computation time. Originality/value -In the simulation of multi-pass welding residual stress involved in materials with cyclic plasticity, the material hardening model should be carefully considered. The kinematic hardening model with lump-pass FE model can be used to get better simulation results with less computation time. The results give a direction for welding residual stress simulation for the large structure such as the reactor pressure vessel.

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Computational Modeling of Microstructural-Evolution in AISI 1005 Steel During Gas Metal Arc Butt Welding

Cited by 19 publications

References 29 publications

Optimization of Gas Metal Arc Welding (GMAW) Process for Maximum Ballistic Limit in MIL A46100 Steel Welded All-Metal Armor

Optimization of Gas Metal Arc Welding (GMAW) Process for Maximum Ballistic Limit in MIL A46100 Steel Welded All-Metal Armor

The Relationship Between Continuous Cooling Rate and Microstructure in the Heat Affected Zone (Haz) of the Dissimilar Weld Between Carbon Steel and Austenitic Stainless Steel

Effects of material hardening model and lumped-pass method on welding residual stress simulation of J-groove weld in nuclear RPV

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