China Nonferrous Metallurgy

Laser cladding technology has demonstrated remarkable advantages in enhancing materials’ hightemperature resistance， corrosion resistance， wear resistance， and enabling material recycling. However， experimental observation of transient evolution processes within the molten pool remains challenging， which hinders in-depth understanding of microstructure formation mechanisms. Numerical simulation techniques have emerged as powerful tools to address this limitation. Thermophysical parameters， such as temperature gradients and cooling rates， play a critical regulatory role in determining grain geometric characteristics including size and morphology. Concurrently， hydrodynamic behaviors within the molten pool influence solute redistribution and preferred dendrite growth orientations， further shaping the microstructure. The non-equilibrium solidification process during laser cladding triggers competitive evolution of grain structures， with morphological evolution， size distribution， and crystallographic orientations being closely correlated with the anisotropic mechanical properties and functional characteristics of the coatings. Notably， topological morphology evolution at the dendrite growth front not only determines microscopic structural features like dislocation density and phase boundary characteristics but also exerts cross-scale effects on macroscopic service performance. This review systematically examines multiscale computational models in numerical simulations， elucidating the solidification dynamics during laser cladding processes. It particularly focuses on analyzing core issues such as coupled thermal-mass transport， grain topological structure evolution， non-equilibrium solute distribution， and dendrite morphology development， Future research in this field should place greater emphasis on refined multiphysics coupling， the integration of microstructural evolution with macroscopic performance， and the modeling of multicomponent alloy systems. Numerical simulation is expected to advance toward higher resolution， multidimensional characterization， and datadriven approaches， thereby providing stronger support for the development of high-performance coating materials and the optimization of processing parameters.