PROBABILISTIC FATIGUE FOR RELIABILITY SIMULATIONS. CASE STUDY OF AUTOMOTIVE COMPONENTS
Structural simulation is increasingly used in the automotive industry to validate component designs without extensive physical prototyping. Finite Element Analysis (FEA) identifies stress concentrations and predicts fatigue damage, enabling durability estimation.
To address the limits of deterministic models, stochastic fatigue simulations incorporate variability in fatigue behavior. This study applies these methods to automotive components under mechanical reliability tests, using Monte Carlo simulations with Latin hypercube sampling and correlating results with physical failure tests through Weibull analysis.
Two case studies, a supporting bracket and a heat exchanger, demonstrate how probabilistic FEA results can be linked to real reliability tests, supporting faster validation and reducing reliance on physical testing.
