Rapid multiaxial high cycle fatigue limit predictions using self-heating-based probabilistic multiscale models

Thermal measurements under multiaxial cyclic loadings are used herein to predict multiaxial fatigue properties. Two models describing random microplasticity activation via a Poisson Point Process. The thermal response is interpreted as the “mean” behaviour of the microplastic activity, whereas the fatigue limit relies on the weakest link assumption. The first model is based upon a yield surface approach to account for stress multiaxiality at a microscopic scale. The second one relies on a probabilistic modelling of microplasticity at the scale of slip-planes. Both models are identified on thermal results and a uniaxial mean fatigue limit, and then validated using fatigue limits as well as thermal responses in the case of tension-torsion loadings on tubular specimens made of medium carbon steel. They predict well hydrostatic stress, volume and proportional multiaxial effects. The model with microplasticity described at the scale of slip-planes also offers a good prediction of nonproportional mean fatigue limits (~ 5% error) whereas the other model is less predictive (~ 17% error).