2017/09/01 by Lucas Mäde, Mäde, Lucas, Sebastian Schmitz +5
Decision Sciences · Engineering · #62N86 #65L60 #FOS: Physical sciences #Fatigue and fracture mechanics #High Temperature Alloys and Creep #Materials Science (cond-mat.mtrl-sci) #Probabilistic and Robust Engineering Design
paper · pdf · doi:10.48550/arxiv.1709.00320
openalex publication_date 2017/09/01 · openalex created_date 2022/10/03 · openalex updated_date 2026/07/28
In recent years a local probabilistic model for low cycle fatigue (LCF) based\non the statistical size effect has been developed and applied on engineering\ncomponents. Here, the notch support extension based on the stress gradient\neffect is described in detail, as well as an FEA-based parameter calibration.\nAn FEA is necessary to simulate non-homogeneous stress fields in non-smooth\nspecimens which exhibit gradients and determine size effects. The hazard\ndensity approach and the surface integration over the FEA stress lead to\ngeometry-independent model parameters. Three different materials (superalloys\nIN-939, Rene80, steel 26NiCrMoV14-5) and three different geometry types\n(smooth, notch, cooling hole specimens) are considered for a more comprehensive\nvalidation of the probabilistic LCF model and to demonstrate its wide\napplication range. At the same time, a reduced testing effort is needed\ncompared to deterministic model predictions with notch support.\n