A statistical approach to multi-input equivalent fatigue loads for the durability of automotive structures
Doctoral thesis, 2006
In the automotive industry, due to temporal and financial
constraints, we need to strongly reduce the duration of the design phase, but still ensure reliability and robustness. Structures in service are often exposed to complex variable amplitude loads. In order to characterize the severity of customers, to define specification for designing metallic structures by computation or for the validation on test rigs, simple forces are more useful. The equivalent fatigue approach, developed at PSA PEUGEOT CITROËN, is a method for transforming variable amplitude measured forces into simpler loads, equivalent in terms of damage. The transformation should be performed without information about the geometry of the structure undergoing the loads. The aim of this work is to extend the one-input equivalent fatigue method, to the multi-input forces.
A great part of the work is devoted to the condition of equivalence of damage between the measured forces and the equivalent ones, when information about the structures is limited. The structures are considered to be elastic and quasi-static. Models of life prediction like Basquin's criterion, for structures submitted to uniaxial fatigue at their critical points, and Morel's model for structures exposed to multiaxial fatigue, are used. Three types of multi-input equivalent fatigue loads are developed. The sinusoidal and the Gaussian multi-input equivalent fatigue loads are studied, as well as the Markov chain multi-input loads. For the Markov loads, a new theory needs to be developed in order to evaluate the rainflow content of linear combinations of multi-input Markov chain. Several applications of those three models are presented, and a set-up of experiments is proposed.
uniaxial and multiaxial high cycle fatigue
multi-input variable amplitude loads
10.15 Sal Pascal, Matematiska vetenskaper, Chalmers Tvärgata 3, Chalmers
Opponent: Professor LINDGREN, Lunds universitet, Sweden