A Smart Bi-Directional Model of Heat Transfer and Free Surface Flow in Gas-Metal-Arc Fillet Welding for Practising Engineers

In recent years, numerical heat transfer and fluid flow models have provided significant insight about fusion welding processes and welded materials. A major problem in their practical use is that several input parameters cannot be easily prescribed from fundamental principles. Available inverse models of fusion welding for the determination of these unknown parameters have ignored important physical processes such as convection in the weld pool to make computational tasks tractable. As a result, these models are not very different from the neural network type models that are not required to obey any physical law. A smart, bi-directional, numerical model has been developed to determine three-dimensional temperature and velocity profiles, weld geometry and the shape of the solidified weld reinforcement surface during gas metal arc (GMA) welding of fillet joints. Apart from the transport of heat from the welding arc, additional heat from the metal droplets was also considered in the model. The model is capable of estimating unknown parameters such as the arc efficiency, effective thermal conductivity and effective viscosity from a limited number of data on weld geometry based on multivariable optimisation. Alternative strategies for the optimisation are examined. The calculated shape and size of the fusion zone, finger penetration characteristic of the GMA welds and the solidified free surface profile were in fair agreement with the experimental results for various welding conditions. In particular, the computed values of the leg length, the penetration depth and the actual throat agreed well with those measured experimentally for various heat inputs. The weld thermal cycles and the cooling rates were also in good agreement with the independent experimental data. The research presented here shows that advances in computational hardware and software have now made construction of smart, bi-directional, large transport phenomena based phenomenological models a useful undertaking.

[1]  James V. Beck,et al.  Parameter Estimation in Engineering and Science , 1977 .

[2]  A. N. Tikhonov,et al.  REGULARIZATION OF INCORRECTLY POSED PROBLEMS , 1963 .

[3]  T. DebRoy,et al.  Macroporosity free aluminum alloy weldments through numerical simulation of keyhole mode laser welding , 2003 .

[4]  M. N. Özişik,et al.  Inverse Heat Transfer: Fundamentals and Applications , 2000 .

[5]  T. Brubaker,et al.  Nonlinear Parameter Estimation , 1979 .

[6]  John E. Dennis,et al.  Numerical methods for unconstrained optimization and nonlinear equations , 1983, Prentice Hall series in computational mathematics.

[7]  T. DebRoy,et al.  Kinetic modeling of phase transformations occurring in the HAZ of C-Mn steel welds based on direct observations , 2003 .

[8]  P. W. Fuerschbach,et al.  Heat transfer and fluid flow during laser spot welding of 304 stainless steel , 2003 .

[9]  Michel Rappaz,et al.  Modeling of casting, welding and advanced solidification processes-V : proceedings of the fifth International Conference on Modeling of Casting and Welding Processes, held in Davos Switzerland, September 16-21, 1990 , 1991 .

[10]  B. Blackwell,et al.  Inverse Heat Conduction: Ill-Posed Problems , 1985 .

[11]  K. Masubuchi.  Analysis of Welded Structures , 1980 .

[12]  T. DebRoy,et al.  Effects of time, temperature, and steel composition on growth and dissolution of inclusions in liquid steels , 2001 .

[13]  Wei Zhang,et al.  Modeling of temperature field and solidified surface profile during gas–metal arc fillet welding , 2003 .

[14]  Wei Zhang,et al.  Modeling of heat transfer and fluid flow during gas tungsten arc spot welding of low carbon steel , 2003 .

[15]  A. B. Strong,et al.  Modelling turbulent thermofluid flow in stationary gas tungsten arc weld pools , 2002 .

[16]  J. Wong,et al.  Evolution of titanium arc weldment macro and microstructures -- Modeling and real time mapping of phases , 2000 .

[17]  Sindo Kou,et al.  Computer simulation of convection in moving arc weld pools , 1986 .

[18]  V. Voller,et al.  A fixed grid numerical modelling methodology for convection-diffusion mushy region phase-change problems , 1987 .

[19]  Thomas W. Eagar,et al.  Pressures produced by gas tungsten arcs , 1986 .

[20]  S. Patankar.  Numerical Heat Transfer and Fluid Flow , 2018, Lecture Notes in Mechanical Engineering.

[21]  J. Szekely,et al.  Mathematical models of transport phenomena associated with arc-welding processes: A survey , 1994 .

[22]  O. Alifanov.  Inverse heat transfer problems , 1994 .

[23]  Amitava De,et al.  Probing unknown welding parameters from convective heat transfer calculation and multivariable optimization , 2004 .

[24]  T. DebRoy,et al.  Three dimensional Monte Carlo simulation of grain growth during GTA welding of titanium , 2000 .

[25]  Ashwani Kumar,et al.  Calculation of three-dimensional electromagnetic force field during arc welding , 2003 .

[26]  Joe F. Thompson,et al.  Numerical grid generation: Foundations and applications , 1985 .

[27]  James V. Beck,et al.  Inverse Heat Conduction , 2023 .

[28]  T. DebRoy,et al.  Modeling and real time mapping of phases during GTA welding of 1005 steel , 2002 .

[29]  J. Szekely,et al.  The Possible Role of Turbulence in GTA Weld Pool Behavior , 1994 .

[30]  A Tikhonov,et al.  Solution of Incorrectly Formulated Problems and the Regularization Method , 1963 .

[31]  C. M. Reeves,et al.  Function minimization by conjugate gradients , 1964, Comput. J..