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The development and application of a strategy are presented, for estimating the full tensor of hydraulic permeability of porous media, without any a priori assumption on the principal directions. A comprehensive description of the X-ray tomographic and image analysis techniques is drawn for the quantitative morphological characterization of the pore space. Pore-scale Direct Numerical Simulation is used to compute the velocity and pressure fields in the digital pore space, reconstructed from high-resolution X-ray tomography. A commercial Finite Volume fluid dynamic solver is used, which operates on voxel-based computational meshes. The proposed methodology is validated by reproducing literature results on monodisperse periodic arrays of spheres. The hydraulic permeability of real-life porous media, characterized by highly complex morphology, is compared with laboratory experimental measurements.

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A probabilistic model for quantifying the number of load cycles for nucleation of forging flaws into a crack has been developed. The model correlates low cycle fatigue (LCF) data, ultrasonic testing (UT) indication data, flaw morphology and type with the nucleation process. The nucleation model is based on a probabilistic LCF model applied to finite element analyses (FEA) of flaw geometries. The model includes statistical size and notch effects. In order to calibrate the model, we conducted experiments involving specimens that include forging flaws. The specimens were machined out from heavy duty steel rotor disks for the energy sector. The large disks, including ultrasonic indications on the millimeter scale, were cut into smaller segments in order to efficiently machine specimens including manufacturing related forging flaws. We conducted cyclic loading experiments at a variety of temperatures and high stresses in order to capture realistic engine operating conditions for flaws as they occur in service. This newly developed model can be incorporated into an existing probabilistic fracture mechanics framework and enables a reliable risk quantification allowing to support customer needs for more flexible operational profiles due to the emergence of renewable energy sources.