Multi-objective optimization of viscoelastically damped systems combining robust condensation and metamodels

Abstract

The use of viscoelastic materials has been regarded as an interesting means of achieving effective vibration mitigation in various types of mechanical systems at a relatively low cost. To enable efficient analysis and design of viscoelastic dampers as applied to complex structures such as vehicles, machines and structures to reduce the vibration levels, the optimization procedures based on multi-objective evolutionary algorithms (MOEAs) is an important step to be investigated. In such applications, including optimal and/or robust design and model updating, the MOEAs combining meta-models and robust condensation is a very useful tool. In this paper, the interest is the use of the so called non sorting dominated genetic algorithms (NSGA), combining robust condensation and meta-models for the viscoelastic damped systems. This approach enables us to avoid the updating of the exact analysis during the optimization leading to a significant time-reduction cost in the design process. © 2006 Civil-Comp Press.

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