Online porosity prediction in laser welding of aluminum alloys based on a multi-fidelity deep learning framework

An Inhomogeneous Model for Laser Welding of Industrial Interest

“…The physical parameters of the alloy Al-Si 5%, kindly provided by IRIS s.r.l., are listed in Table 4, and the laser physical parameters related to a typical welding process for alloy Al-Si 5% are listed in Table 5 (the laser intensity is computed by I 0 = P/πr 2 U ). Furthermore, we set σ B = 1.35 × 10 −23 J/K, T 0 = T air = T bench = 298 K (typical environmental temperature in welding forge [32][33][34]), h air = 15 × 10 −6 W/(mm 2 K), and h bench = 20h air (as experimentally suggested from metallurgical experiments [35][36][37][38][39][40] to guarantee the correct penetration without favoring the thermal degradation of the alloy structure, and it is such that it produces significant effects even at depth). Galerkin-FEM procedure applied to (28), described above and implemented in MatLab R2022 PDE Tool, optimizes a mesh with tetrahedral elements.…”

“…We finally observe that, also in this case, both transversal and longitudinal thermal cycles are qualitatively superimposable with those obtained using the other formulations of heat laser sources. Therefore, the proposed model, assisted by this formulation of the heat source laser and with appropriate power output, appears suitable for industrial and iron and steel applications, which require superficial and sub-surface fusions of the material [18,32,35,38,41].…”