Although numerical heat transfer and fluid flow models have provided significant insight about fusion welding processes and welded materials in recent years, several model input parameters cannot be easily prescribed from fundamental principles. As a result, the model predictions do not always agree with the experimental results. In order to address this problem, the approach adopted here is to develop and test a model that embodies a heat transfer and fluid flow sub-model and an algorithm for optimizing and learning the values of uncertain process variables from a limited volume of experimental data. The heat transfer and fluid flow sub-model numerically calculates three-dimensional temperature and velocity fields, the 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 is also considered in the model. Alternative algorithms for optimization of uncertain welding variables are examined. The overall model is capable of estimating uncertain parameters such as the arc efficiency, effective thermal conductivity and effective viscosity from a limited number of data on weld geometry. Part I of this paper is focused on the details of the numerical model, optimization technique used and an examination of the important features of the model. In an accompanying article (part II), the application of the model to GMA fillet welding of mild steel is described.
All Science Journal Classification (ASJC) codes
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Acoustics and Ultrasonics
- Surfaces, Coatings and Films