Application of optimization techniques and the enthalpy method to solve a 3D-inverse problem during a TIG welding process

A GTA Welding Cooling Rate Analysis on Stainless Steel and Aluminum Using Inverse Problems

“…The same pattern is seen in Aissani et al [8]. In their work, the authors model a TIG welding process for the same stainless steel of Gonçalves et al [7]. They used a linearization of the radiation equation of the Stefan-Boltzmann law and a constant heat transfer coefficient for the convection analysis.…”

“…These models satisfactorily predict the temperature at the peak point [7,8]. However, they fail to analyze the cooling rate because they use simple approaches for the radiation and heat transfer coefficient by convection.…”

“…However, they fail to analyze the cooling rate because they use simple approaches for the radiation and heat transfer coefficient by convection. For instance, Gonçalves et al [7] used a three-dimensional model based on the diffusion equation and the enthalpy method to model a TIG welding process. The authors' model used an empirical correction to estimate the heat transfer coefficient in the sample.…”

Influences of deposited metal material parameters on weld pool geometry during shield metal arc welding

“…Heat and mass transfer perform important functions on weld pool geometry and determine weld quality [5][6][7][8]. Kim and Na [9] investigated weld pool convection and claimed that heat transfer and fluid flow in the weld pool significantly affect weld pool geometry and influence the temperature gradients of the weld pool, its local cooling rates, and its solidification structure.…”

Estimation of operating parameters of a reheat regenerative power cycle using simplex search and differential evolution based inverse methods

“…Inverse analysis is however computationally expensive and mathematically more complicated compared to its forward counterpart due to ill posed and iterative nature of the problem [14][15][16] and many a times multiple combinations of parameters are obtained that satisfy the same given reference output. This is one of the unique features of inverse analysis due to which it has become very popular and successfully applied in many engineering problems in the last decade [17][18][19][20][21][22][23][24][25][26][27][28]. Various methods such as conjugate gradient method, steepest descent method, linear least-squares error method, golden section technique, genetic algorithm and DE are used in the inverse analysis.…”