A Prediction Model of Effective Thermal Conductivity for Metal Powder Bed in Additive Manufacturing

In current research, many researchers propose analytical expressions for calculating the packing structure of spherical particles such as DN Model, Compact Model and NLS criterion et al. However, there is still a question that has not been well explained yet. That is: What is the core factors affecting the thermal conductivity of particles? In this paper, based on the coupled discrete element-finite difference (DE-FD) method and spherical aluminum powder, the relationship between the parameters and the thermal conductivity of the powder (ETC_p) is studied. It is found that the key factor that can described the change trend of ETC_p more accurately is not the materials of the powder but the average contact area between particles (a_ave) which also have a close nonlinear relationship with the average particle size d₅₀. Based on this results, the expression for calculating the ETC_p of the sphere metal powder is successfully reduced to only one main parameter d₅₀ and an efficient calculation model is proposed which can applicate both in room and high temperature and the corresponding error is less than 20.9% in room temperature. Therefore, in this study, based on the core factors analyzation, a fast calculation model of ETC_p is proposed, which has a certain guiding significance in the field of thermal field simulation.