Additive manufacturing (AM) has enabled the fabrication of complex geometries directly from the design data and gained a lot of interest. However, AM products can contain pores, which can significantly reduce fatigue life. The main focus of this work is to evaluate the effect of the pores in Ti6Al4V dog-bone samples, produced by AM, and propose a methodology to estimate the fatigue life reduction due to the internal pores. The bond-based Peridynamics (PD) fatigue model was utilised to analyse the fatigue life of the defect-free sample with the calibrated PD parameters. Moreover, a numerical model is developed to investigate two types of porosities in a system. The application of the PD model showed a capability of crack nucleation prediction for the titanium alloy samples under cycling loading. The predicted results are compared with experimental data using the stress-life (S-N) curve. Furthermore, this paper presents a numerical approach to assess the influence of the pore location and size on the fatigue life of Ti6Al4V. The PD predictions indicated the critical pore characteristics and the applicability of the developed PD model on samples with low porosity for high cycle fatigue-loaded applications.
|Number of pages||32|
|Journal||Theoretical and Applied Fracture Mechanics|
|Publication status||Accepted/In press - 30 Jan 2021|
- additive manufacturing
- porosity defects
- fatigue life prediction