Thermo-mechanical-microstructural simulation of double-pass welding process in a TWIP steel by FE formulation and probab
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ORIGINAL ARTICLE
Thermo-mechanical-microstructural simulation of double-pass welding process in a TWIP steel by FE formulation and probabilistic model V. García-García 1,2 & I. Mejía 1 & F. Reyes-Calderón 2 & H. Hernández-Belmontes 1 Received: 25 March 2020 / Accepted: 20 September 2020 / Published online: 7 October 2020 # Springer-Verlag London Ltd., part of Springer Nature 2020
Abstract This research work developed a decoupled thermo-mechanical-microstructural (TMM) numerical framework to simulate a multipass welding process. The numerical framework was applied to evaluate the effect of operating parameters on the weldability of a twinning induced plasticity (TWIP) steel considering metallurgical defects and the weld joint’s mechanical properties. The thermo-mechanical model was solved numerically using a finite element model (FEM). After that, the simulation of the thermo-microstructural field was performed through a combined probabilistic approach Monte Carlo (MC)-Voronoi tessellation. The staggered solution approach and the optimized FE macro-scale mesh further improved the convergence and reduced computing time. The correlation of TMM model estimations with thermal history measurements and mechanical and metallographic characterizations helped explain the variation of post-welding mechanical properties. The nature of residual stresses in the TWIP steel joint was correlated with the heat flux in the critical weld regions. The thermal gradients were also correlated with the weld regions that underwent grain growth and grain size reduction. The grain growth simulation performed by the MCVoronoi model was in good agreement with the hardness reduction in the heat-affected zone (HAZ). The grain size distribution in the HAZ produced an unexpected tensile elongation. Keywords TWIP steel . Multi-pass welding . TMM framework . Process optimization
Nomenclature Symbols CP Specific heat (J/kg °C) T Temperature (°C) t Time (s) k Thermal conductivity (W/m °C) qf, r Heat source (W/m3) a, b, cf, Geometric parameters of double cr ellipsoidal heat source (m) Q Heat input (J/m) * I. Mejía [email protected] 1
Instituto de Investigación en Metalurgia y Materiales, Universidad Michoacana de San Nicolás de Hidalgo, Edificio “U-5”, Ciudad Universitaria, 58066 Morelia, Michoacán, Mexico
2
Departamento de Metal Mecánica, Posgrado en Metalurgía/ Doctorado en Ciencias en Ingeniería, Tecnológico Nacional de México / Instituto Tecnológico de Morelia, Av. Tecnológico 1500, 58120 Morelia, Michoacán, Mexico
V I v ff, fr x, y, z C T˙ rp rq Rpext Rpint Ni B V A h Δt Qinf bc {s}
Voltage (V) Current intensity (A) Welding speed (m/s) Weight factors (-) Global Cartesian coordinates (inertial) (m) Specific heat matrix (J/kg °C) Transient temperature (°C) Thermal load vector (W/m2) Volumetric heat vector (W/m3) External forces vector (N) Internal forces vector (N) Vector of shape functions (-) Vector of derivates of shape functions (-) Volume (m3) Area (m2) Convection coefficient (W/m2 °C) Time increment (s) Material parameter (MPa) Material par
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