Rapid and accurate fatigue assessment by an efficient critical plane algorithm: application to a FSAE car rear upright

The topic of material fatigue is widely discussed and researched in both scientific and industrial communities. Fatigue damage remains a significant issue for both metallic and non-metallic components, leading to unforeseen failures of in-service parts. Critical plane methods are particularly recommended in case of multiaxial fatigue assessment and have gained relevance as they allow for the identification of the component's critical location and early crack propagation. However, the standard method for calculating critical plane factors is time-consuming, utilizing nested for/end loops and, for that, is mainly applied in a research context, or when critical regions are already known. In many cases, the critical area of a component cannot be identified due to complex geometries and loads or time constraints. This becomes particularly relevant after topological optimization of components and, more generally, in lightweight design. An efficient algorithm for critical plane factors evaluation have been recently proposed by the authors. The algorithm applies to all critical plane factors that require the maximization of a specific parameter based on stress and strain components or a combination of them. The methodology is based on tensor invariants and coordinates transformation law. This paper presents and validate the proposed methodology through an automotive case study: the new algorithm was tested on a rear upright of a FSAE car, having complex geometry, subjected to non-proportional loading conditions. The efficient algorithm showed a significant reduction in computation time compared to the (blind search-for) standard plane scanning method, without any loss in solution accuracy.