Computational modeling of laser welding of Cu-Ni dissimilar couple
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3/4/04
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Computational Modeling of Laser Welding of Cu-Ni Dissimilar Couple GANDHAM PHANIKUMAR, PRADIP DUTTA, and KAMANIO CHATTOPADHYAY A three-dimensional transient model to solve heat transfer, fluid flow, and species conservation during laser welding of dissimilar metals is presented. The model is based on a control volume formulation with an enthalpy-porosity technique to handle phase change and a mixture model to simulate mixing of molten metals. Weld pool development, solidified weld pool shape, and composition profiles are presented for both stationary as well as continuous laser welding in conduction mode. Salient features of a dissimilar Cu-Ni weld are summarized and thermal transport arguments are employed to successfully explain the observations. It is found that the weld pool shape becomes asymmetric even when the heat source is symmetrically applied on the two metals forming the couple. It is also observed that convection plays an important role in the development of weld pool shape and composition profiles. As the weld pool develops, the side melting first (nickel) is found to experience more convection and better mixing. Results from the case studies of computation are compared with corresponding experimental observations, showing good qualitative agreement between the two.
I. INTRODUCTION
FUSION welding is an important manufacturing technique that has attained a state of maturity in the past few decades. The physical processes that take place during fusion welding, namely, heat transfer, melting, Marangoni convection, electromagnetic and buoyancy forces, and solidification, are well documented.[1,2,3] Microstructure of the weldment, which determines the mechanical properties of the product, is understood in terms of grain structure and phase formation as a function of processing parameters.[4] Several computational studies have also successfully shown insights into the physical processes that occur during welding.[5–11] Convection in the weld pool is now recognized as one of the important processes that determine weld pool characteristics such as size and shape.[12–16] Experimental verification of computational models and prediction of weld pool characteristics as a function of processing conditions have also been relatively successful.[17,18] However, much of the work on numerical simulation of welding is in the context of joining of similar metals and alloys. Recent advances in manufacturing industry require dissimilar metals and alloys to be joined. Studies on the extension of current understanding of welding of similar metals/alloys to that of dissimilar metals/alloys are limited.[19,20] It is found that a majority of the existing literature on the joining of dissimilar metals and alloys is mainly concentrated on steels and the problem should be analyzed in a case-by-case manner. The quality of weld assessed for several metals is used to decide if a combination is weldable.[21] It may be noted, however, that microstructural features that emerge due to differences in the phys
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