A fatigue life prediction method distinguishing fracture modes for Ni-based single crystal superalloys considering porosity defect. (April 2021) - Jiang, Wen; Yao, Weixing; Li, Piao; Luo, Peng
Highlights: The CPFEM was constructed as a life evaluation tool and calibrated by LCF hysteresis loop. Porosity-related fatigue damage parameters were evaluated and the GCF parameter is the best in this study. A new porosity-related fatigue damage parameter distinguishing fracture modes was proposed. The proposed method has improved the life prediction ability compared with the GCF parameter. Abstract: Microporosity is one of the most common defects in nickel base single crystal (N-SC) superalloys, which is a great threat to fatigue performance. In this paper, nine porosity-related fatigue damage parameters for N-SC superalloys were selected by referring to those parameters originally proposed for casting and 3D printing metal materials as well as the critical plane damage parameters commonly used in N-SC superalloys. According to the plastic constitutive model of single crystals, a crystal plastic finite element (CPFE) model was established to evaluate these different fatigue damage parameters, and the parameters of CPFE were calibrated by the low cycle fatigue (LCF) hysteresis loop obtained from the fatigue test. The evaluation results showed that the geometric mean of stress–strain concentration factor (GCF) k g was a satisfactory parameter to quantify the effect of porosity defects on fatigue. Inspired by the discovery and considering the slip systems characteristics of N-SC superalloys, the geometric mean of resolved stress–strain concentration factor (GRCF) k rg on slip systems was proposed, and it was found that the max ( k rg, k g ) could be used to predict the fracture modes of N-SC superalloys. Based on the max ( k rg, k g ), a porosity-related fatigue life prediction method which can distinguish the fracture modes was put forward. The prediction results showed that the fracture mode prediction results were consistent with the test results, and the life prediction results were also improved compared with the GCF parameter.