Fatigue design: load, stress state, technological factors

Fatigue resistance evaluation of mechanical components is still a challenging topic for a lot of researches that aim to foresee the residual life or to establish the fatigue limit of a component. Fatigue resistance of a component is not only dependent on the mechanical characteristics of the material, but also is strongly influenced by the load history, the induced stress state, surface hardness and technological factors. Each component is subjected to different manufacturing processes before its utilisation; another important factor that has a big influence on the fatigue resistance is the presence of a tensile or compressive residual stress field, after machining or surface treatment, at the surface of the component. In the last few years, the finite element method helped in simulating conditions in which a mechanical component is subjected to special kind of loads. The residual stress field can be simulated too and fatigue crack propagation in residual stress field is no longer a matter of few high-level researches. Only an intensive use of numerical models, confirmed by means of experimental tests, can represent a powerful tool to enhance the fatigue behaviour of mechanical components. The aim of this Special Issue of International Journal of Materials and Product Technology regards the study and presentation of detailed analyses on the effect that loads, stress state and technological factors have on the fatigue resistance of mechanical components. The results of such analyses could be used directly by a machine designer who needs to asses whether a component can exhibit particular fatigue resistance capabilities. The contributors to this Special Issue try to propose numerical and analytical models that are able to predict the effects induced by mechanical and thermal processes or simulate the working conditions of complex mechanical components. The authors present different solution algorithms and search a confirmation to the trustworthiness of their models by executing several experimental tests. The result is a useful collection of papers that gives a survey of the state-of-the-art in the fatigue life prediction field. I would like to thank the authors for their valuable contributions to this Special Issue. Acknowledgements are also due to Dr. M.A. Dorgham for initiating this Special Issue and to the reviewers for their support of the initiative and careful re-examination of the manuscripts.