Numerical method applied to duplex stainless steel welding

Abstract

Microstructure plays an essential role in the attractive properties of the duplex stainless steels (DSSs) such as toughness and corrosion resistance. These properties are obtained by an adequate balance between the fractions of the ferrite and austenite phases, which can be modified when DSSs are welded. Besides the unbalanced fractions of ferrite and austenite, the precipitation of deleterious compounds at high temperatures such as sigma phase can also occur during DSS welding. In this work, a model based on transport equations was numerically implemented by the finite volume method in a computational code in order to simulate the 2205 DSS welding. It was able to evaluate qualitatively the sigma phase precipitation and the formation of the ferrite and austenite phases by calculating the cooling rates reached during 2205 DSS welding. The results are discussed in light of the previous work, and good agreement between numerical and experimental results was obtained.

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

“…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.…”

“…The material used in this study was selected due to its ability to undergo multiphase transformations during cooling, which allows the verifications of the kinetic model for phase transformations from the available data 16 . Furthermore, the computer code used in this study has been continuously developed by the authors and applied for different materials and welding conditions, which has validated the general features of the model and computer implementations [17][18][19] . In this paper, new features such as models for kinetics of phase transformations and hardness prediction for low-alloy hypoeutectoid steel are added and, thus, improving the model capability.…”

“…In order to model the process, the phenomena of heat transfer by radiation, convection and conduction are taken into account coupled with mass transfer, melting and solidification and the thermophysical properties were assumed as composition and temperature dependent [20][21][22][23][24][25] . The energy equation for a general coordinate system is represented in compact form by the Equation 1 [17][18][19] . In Equation 1, ρ is the density; C p is the specific heat; k is thermal conductivity; U → is velocity field, which accounts for buoyancy driven flow in the liquid pool or moving mesh to match the geometry changes due to the metal deposition; T is the temperature field and S is the source term, which accounts for all source or sink due to phase transformations, melting and solidification.…”

“…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.…”

“…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.…”