This paper proposes an approach for optimal design of multilevel systems under uncertainty. The approach utilizes the stochastic extension of the analytical target cascading formulation. The reliability of satisfying the probabilistic constraints is computed by means of the most probable point method using the hybrid mean value algorithm. A linearization technique is employed for estimating the propagation of uncertainties throughout the problem hierarchy. The proposed methodology is applied to a piston-ring/cylinder-liner engine subassembly design problem. Specifically, we assess the impact of variations in manufacturing-related properties such as surface roughness on engine attributes such as brake-specific fuel consumption. Results are compared to the ones obtained using Monte Carlo simulation.


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    Title :

    Propagation of Uncertainty in Optimal Design of Multilevel Systems: Piston-Ring/Cylinder-Liner Case Study


    Additional title:

    Sae Technical Papers



    Conference:

    SAE 2004 World Congress & Exhibition ; 2004



    Publication date :

    2004-03-08




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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