Probabilistic pore healing model for prediction of relative density in heat treatment

Abstract

Porous defect is a common defect that can reduce the mechanical properties of the material. There are few published studies to predict the relative density considering the stochastic characteristics of the pore sizes. In the current study, a probabilistic pore healing model for the prediction of relative density in heat treatment is presented based on the pore size distribution of porous defect. The probabilistic distribution of pore sizes was introduced into a deterministic model of sintering by taking the parameter of pore radius as a random variable. Numerical integration was used to calculate the relative density of the porous material. A pore healing diagram for the 316L stainless steel is constructed with axes of relative density and temperature. The critical healing time and temperature can be determined using the pore healing diagram. Comparison was made between the calculated and experimental results. The results indicate that the probabilistic model is more precise than the deterministic model in predicting the relative density of the material.