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Publicación seriada
Referencias AnalíticasReferencias Analíticas
Autor: d`Ippolito, R. ; Donders, S. ; Hack, M. ; Hermans, L. ; Tzannetakis, N. ; Vandepitte, D.
Título: Improving the fatigue life of a vehicle knuckle with a reliability-based desing optimization approach
Páginas/Colación: pp. 1619 - 1632
Fecha: Mayo
Journal of Statistical Planning and Inference Vol. 139, no. 5 May 2009
Información de existenciaInformación de existencia

Resumen
A major issue in vehicle industry is the presence of variability in the physical properties and manufacturing processes. Deterministic approaches are unable to take into account these variabilities without leading to oversized structures. The necessity of assessing the robustness of a particular design requires a new methodology based on reliability analysis and design optimization through probabilistic models of design variables. The vehicle lifetime is highly determined by the fatigue life of its components. Variability in the material parameters (such as Young's modulus and tensile strength) may have a strong effect on the fatigue life. This is demonstrated in this paper for a vehicle knuckle structure. As a first step, a probabilistic approach to fatigue life prediction is worked out to assess the reliability of vehicle fatigue predictions in the presence of material variability. In a second step, a reliability based design optimization methodology is applied to improve the design reliability for the given material variability. These two steps not only provide better insight in the effect of variability on the fatigue life prediction, but also guidelines to improve the material definition and manufacturing tolerances. One thus obtains a powerful tool to reduce design conservatism while maintaining and even improving the structural safety. This paper intends to demonstrate the effectiveness of this innovative approach by integrating probabilistic design methods into the traditional design process, stressing the advantages that such methodologies bring to the improvement of product fatigue life prediction and structural reliability.

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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