FEM prediction of welding residual stress and distortion in carbon steel considering phase transformation effects

Deng, Dean

doi:10.1016/j.matdes.2008.04.052

Cited by 484 publications

(276 citation statements)

References 12 publications

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“…3 kg m − . The thermal conductivity and specific heat for individual phases reported in the literature depend of the authors, although follows similar trends [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][24][25][26][27][28][29][30][31][32][33] . The reason for such lack is due to the possibility of different features of the phases formed depending on the thermal history.…”

Section: Thermophysical Propertiesmentioning

confidence: 72%

“…The available data 22 can be fitted as shown in Equation 6. However, a common approach is to assume constant emissivity during welding simulations when Equations 2 and 3 are used to dynamically impose the volumetric heat source due to the welding arc, where the heat source parameters includes the net heat transferred to the workpiece at high temperatures [5][6][7][8][9][10][11][12][13][17][18][19] . In this model, the Equation 6, obtained by regression of the data presented by Paloposki and Liedgust 22 , is used for imposing the radiative cooling boundary conditions additionally to the double ellipsoid heat flux.…”

Section: Initial and Boundary Thermal Conditionsmentioning

confidence: 99%

“…Equation 6 predicts constant emissivity for temperature below 300 o C and above 750 o C. This behavior is due to the range of measured data for low-alloyed steels, which is assumed to have similar behavior to the steel considered in this study. A clear shortcoming of this approach is that effects related to the surface parameters and environment temperature and composition are not considered and assumed negligible during the cooling by radiation and natural convection [5][6][7][8][9][10][11][12][13][17][18][19] . These shortcomings are usually overcame by adjusting the heat source parameters, shown in Table 2, which is dominant for the high temperature region (above 750 o C), meanwhile, the radiation cooling effects for low temperature (below 200 o C ) are negligible compared with the convection contribution.…”

Section: Initial and Boundary Thermal Conditionsmentioning

confidence: 99%

“…Several works have been carried out and highlighted the importance of taking into account the phase transformations effects and properties evaluation developed during welding [2][3][4][5][6][7][8][9][10][11][12][13] . Simultaneously, the numerical methods have been a fundamental tool for supporting qualitative and quantitative analysis of these stresses, as well as on the prediction of the resultant microstructure and mechanical properties of the weldment.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, this FVM based computational code differs from previous works due to its ability to handle simultaneous phase transformations, heat input effects and nonlinearities into an efficient flamework 5,6,[8][9][10][11][12] . Therefore, the approach used in this study represents a step forward on the challenging task of numerically predicts the complex phenomena and changes taking place during the steels welding and could be used to evaluate new welding procedures for the industrial practice.…”

Section: Introductionmentioning

confidence: 99%

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Numerical Predictions for the Thermal History, Microstructure and Hardness Distributions at the HAZ during Welding of Low Alloy Steels

et al. 2016

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A phenomenological model to predict the multiphase diffusional decomposition of the austenite in low-alloy hypoeutectoid steels was adapted for welding conditions. The kinetics of phase transformations coupled with the heat transfer phenomena was numerically implemented using the Finite Volume Method (FVM) in a computational code. The model was applied to simulate the welding of a commercial type of low-alloy hypoeutectoid steel, making it possible to track the phase formations and to predict the volume fractions of ferrite, pearlite and bainite at the heat-affected zone (HAZ). The volume fraction of martensite was calculated using a novel kinetic model based on the optimization of the well-known Koistinen-Marburger model. Results were confronted with the predictions provided by the continuous cooling transformation (CCT) diagram for the investigated steel, allowing the use of the proposed methodology for the microstructure and hardness predictions at the HAZ of low-alloy hypoeutectoid steels.

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Section: Thermophysical Propertiesmentioning

confidence: 72%

Section: Initial and Boundary Thermal Conditionsmentioning

confidence: 99%

Section: Initial and Boundary Thermal Conditionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Numerical Predictions for the Thermal History, Microstructure and Hardness Distributions at the HAZ during Welding of Low Alloy Steels

et al. 2016

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Numerical prediction and experimental validation of temperature and residual stress distributions in buried‐arc welded thick plates

et al. 2019

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Summary The paper deals with the numerical simulation and experimental investigations of a buried‐arc welding process on a butt‐welded plate sample. In the numerical investigations, the finite element analysis is carried out by applying the element birth and death technique in the thermal analysis, while the mechanical analysis is performed simultaneously in one step to reduce simulation time. The temperature history at two locations is recorded with thermocouples, while residual stresses are measured by using the hole‐drilling stress relaxation method at four points. The heat input efficiency for the buried‐arc welding process is determined by using a parametric analysis. The numerically obtained temperatures and residual stresses correspond very well with the experimental measurements. Furthermore, by using buried‐arc welding, 73% of the weld filler material is saved and 59% of energy, whereas the CO2 emission to the atmosphere is reduced by 83% in comparison with conventional metal active gas welding for a model of the same dimensions.

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Deformation‐Inhibited Cementite Precipitation Effect and Its Influence on Residual Stress

Yan

Ding

Liang³

et al. 2023

steel research int.

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High‐strength steels with low carbon content have low stress relaxation during tempering and are prone to distortion during processing. To improve tempering stress relaxation, 10% compression predeformation is introduced. Carbide precipitation is characterized by dislocation density and dilatometry curves, and the evolution of residual stress during tempering is investigated. The results show that predeformation can inhibit cementite precipitation, increase the effective carbon concentration in the ferrite matrix, and induce the diffuse precipitation of alloy carbides. The dispersed alloy carbides provide more interfaces for Mn partitioning, strengthen the transformation plasticity, and enhance the stress relaxation. After tempering at 700 °C for 30 min, the average residual stress and the elastic strain energy of undeformed/predeformed specimens are 39.18/13.25 MPa and 25.40%/90.92%, respectively.

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FEM prediction of welding residual stress and distortion in carbon steel considering phase transformation effects

Cited by 484 publications

References 12 publications

Numerical Predictions for the Thermal History, Microstructure and Hardness Distributions at the HAZ during Welding of Low Alloy Steels

Numerical Predictions for the Thermal History, Microstructure and Hardness Distributions at the HAZ during Welding of Low Alloy Steels

Numerical prediction and experimental validation of temperature and residual stress distributions in buried‐arc welded thick plates

Deformation‐Inhibited Cementite Precipitation Effect and Its Influence on Residual Stress

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