A numerical kinematic model of welding process for low carbon steels

Ni, Junyan; Wahab, Magd Abdel

doi:10.1016/j.compstruc.2017.03.009

Cited by 29 publications

(10 citation statements)

References 46 publications

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“…That is to say, as the chemical composition changes, the parameters in their model need to be determined again by metallurgical diagrams or experiments. The model by Kirkaldy [15] provides sufficient flexibility but rather coarse results [17]. The series of work done by Bhadeshia et al [6][7][8][9] are able to predict the microstructural evolution without the necessity of calibrating parameters.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, the metallurgical algorithm of Bhadeshia et al [6][7][8][9] is implemented into the coupled FE model to evaluate the influence of pAGS on phase transformation and residual stress. It should be also mentioned that the grain growth algorithm has never been incorporated to Bhadeshia's model before [10,17]. It is the first time that the two models are joined together to provide a complete metallurgical simulation in FE analysis.…”

Section: Introductionmentioning

confidence: 99%

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Dependency of phase transformation on the prior austenite grain size and its influence on welding residual stress of S700 steel

Voorde²,

Antonissen³

et al. 2018

Weld World

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The austenite grain size (AGS) before decomposition is a crucial factor for the development of microstructure. However, this dependency is seldom discussed due to the difficulty of observing the grain growth of austenite during welding. In the current work, a grain growth algorithm is combined in a thermodynamics-based metallurgical model for the first time to analyse the influence of prior austenite grain size (pAGS). The phase volume fractions predicted at different cooling rates and pAGSs are compared with the experimental results of the continuous cooling transformation (CCT) diagram. To further investigate the influences of pAGS and microstructure on residual stress, experiments of bead-on-plate welding are conducted at three heat inputs, in which plates of S700 steel are operated by the arc welding process. The geometries after welding, chemical composition in the fusion zone (FZ) and the parameters of the double ellipsoidal heat source are calibrated using the software SimWeld. These geometries are imported to ABAQUS to create a finite element (FE) model. The validated metallurgical model together with the grain growth algorithm are implemented in the subroutine ABAMAIN to provide a thorough prediction of microstructure. With the knowledge of temperature and phase distributions, a coupled thermo-metallomechanical FE model is established to predict the residual stress distributions. The material properties are assigned by interpolating the individual phase property with its volume fraction. By comparing the results predicted by the model assuming constant pAGS, the influence of the pAGS on the residual stress is manifested. Moreover, simulations using overall material properties are also conducted. The stress distributions in the middle of plate surface are plotted along with the volume fractions of product phases to analyse the sensitivity of the residual stress to microstructure.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dependency of phase transformation on the prior austenite grain size and its influence on welding residual stress of S700 steel

Voorde²,

Antonissen³

et al. 2018

Weld World

View full text Add to dashboard Cite

show abstract

“…In this context, many researchers have been studying this problem until nowadays, and have been proposing physical models to predict the kinetics of phase transformation under continuous cooling. However, most part of this physical models are very complex, assume many physical simplifications and require powerful computational resources, making them difficult to apply in the industrial environment 3,5,[11][12][13][14][15][16][17][18][19] .…”

Section: ( )mentioning

confidence: 99%

Proposition of an Empirical Functional Equation to Predict the Kinetics of Austenite to Ferrite Transformation in a Continuous Cooled IF-Ti-Stabilized Steel

Cezário

Faria

2021

Mat. Res.

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The kinetics of phase transformations in isothermal processes is well described by the classic JMAK model. However, it is known that most industrial facilities employ continuous cooling processes and, for this condition, the JMAK model is adapted but, sometimes, without success. Considering the importance to predict critical temperatures, the present work proposes an alternative empirical functional equation to describe the kinetics of steel phase transformation under continuous cooling, being useful when the JMAK use is not successful. In this study, the continuous cooling austenite to ferrite transformation was experimentally characterized by dilatometry for an IF-Ti-stabilized steel. The proposed equation was compared with the classic adapted JMAK model regarding to evaluate its efficacy to fit the dilatometric experimental data. Using the constants obtained by the both model fittings as input parameters, a computational simulation was performed to determine the CCT diagram of the IF-Ti steel. The proposed functional equation was efficient to predict the critical temperatures, the kinetics of austenite decomposition and the CCT diagram of the studied steel. The results predicted by the proposed model greatly met the experimental data measured by dilatometry.

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“…In continuum mechanics, one of the well-known theories is the nonlocal continuum theory of Eringen [1]. Finite Element method (FEM) is a very well know numerical techniques and has been used for a wide range of applications [2][3][4][5][6][7][8][9][10][11][12][13][14][15]. Using FEM, Free vibration analysis of FG size-dependent nanobeams was studied by Alshorbagy et al [16].…”

Section: Introductionmentioning

confidence: 99%