The dynamic response of structures to operating or occasional loads is crucial for design considerations, as it directly impacts the cumulative fatigue life. In practice, accurately discerning the precise loads and structural conditions, which involve considerations such as boundary conditions, geometry, and mechanical properties, can be quite challenging. Significant efforts are invested in identifying these factors and developing suitable prediction models. Nonetheless, the estimated forces and boundary conditions remain approximations, leading to uncertainties which affects the overall predictions and the analysis of how stress and strain develop in the structure during subsequent evaluations.
Many researchers frequently employ a method where they estimate the forces acting on the system based on measurement data obtained at limited number of locations over the structure. This approach involves estimating the forces and applying them to determine the FE displacement and subsequent stress-strain histories. However, this methodology introduces complexities and multiple approximations, resulting in highly approximate solutions. Challenges arise due to the sensitivity of estimated forces to the number and distribution of measurement points, as well as the need for an accurately modelled finite element model to predict the actual displacement histories accurately.
This work is focused on obtaining accurate dynamic stress-strain for Exhaust system subjected to unknown and distributed loads. Instead of estimating the forces, the method focuses on obtaining precise modal participation factors from limited sets of acceleration measurements using System equivalent expansion and reduction (SEREP) process. These factors, combined with modal stresses obtained from finite element modal analysis, enable the accurate determination of dynamic stress-strain distributions and reliable predictions of cumulative fatigue life. By emphasizing the importance of capturing modal behavior, this alternative concept offers improved understanding of structural dynamics and enhanced predictions of stress and fatigue under uncertain loading conditions.