Stochastic fatigue damage in viscoelastic materials using probabilistic pseudo J-integral Paris' law

Using Pseudo-stochastic Rational Languages in Probabilistic Grammatical Inference

In probabilistic grammatical inference, a usual goal is to infer a good approximation of an unknown distribution P called a stochastic language. The estimate of P stands in some class of probabilistic models such as probabilistic automata (PA). In this paper, we focus on probabilistic models based on multiplicity automata (MA). The stochastic languages generated by MA are called rational stocha...

Monitoring fatigue damage in materials using magnetic measurement techniques

A generalized Paris’ law for fatigue crack growth

An extension of the celebrated Paris law for crack propagation is given to take into account some of the deviations from the power-law regime in a simple manner using the Wöhler SN curve of the material, suggesting a more general ‘‘unified law’’. In particular, using recent proposals by the first author, the stress intensity factor K(a) is replaced with a suitable mean over a material/structura...

Probabilistic fatigue damage prognosis using maximum entropy approach

A general framework for probabilistic fatigue damage prognosis using maximum entropy concept is proposed in this paper. The fatigue damage is calculated using a physics-based crack growth model. Due to the stochastic nature of crack growth process, uncertainties arising from the underlying physical model, parameters of the model, and the measurement noise are considered and integrated into this...

Impact Fatigue of Viscoelastic Materials Subjected to Pounding

The pounding tuned mass damper (PTMD) is a novel vibration control device that can be used for many different structures. The PTMD utilizes a viscoelastic delimiter to enhance its vibration control effectiveness and robustness though pounding between the tuned mass and the viscoelastic material. However, the viscoelastic material is subjected to repeated poundings during its service life, which...