The paper concerns the metallic material lifetime calculation under arbitrary multiaxial thermo-mechanical fatigue loading. An energy-based damage operator approach ([Formula: see text]) is introduced. In such an approach, fatigue lifetime is continuously computed by the Prandtl type damage operator. The dissipated energy of plastic deformation is applied as a damage parameter that is obtained at any moment by the recently developed multiaxial energy operator approach. Strain-life curves are transformed into energy-cycle damage curves in order to associate the damage parameter with the fatigue lifetime. The present approach is validated on turbocharger housing. A satisfactory evaluation of the fatigue lifetime is obtained even though visco-plasticity and mean stress correction are not addressed yet.
This paper details an advanced method of continuous fatigue damage prediction of rubber fibre composite structures. A novel multiaxial energy‐based approach incorporating a mean stress correction is presented and also used to predict the fatigue life of a commercial vehicle air spring. The variations of elastic strain and complementary energies are joined to form the energy damage parameter. Material parameter α is introduced to adapt for any observed mean stress effect as well as being able to reproduce the well‐known Smith‐Watson‐Topper criterion. Since integration to calculate the energies is simplified, the approach can be employed regardless of the complexity of the thermo‐mechanical load history. Several numerical simulations and experimental tests were performed in order to obtain the required stress‐strain tensors and the corresponding fatigue lives, respectively. In simulations, the rubber material of the air spring was simulated as nonlinear elastic. The mean stress parameter α, which controls the influence of the mean stress on fatigue life, was adjusted with respect to those energy life curves obtained experimentally. The predicted fatigue life and the location of failure are in very good agreement with experimental observations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.