DRAFT: OPTIMIZATION UNDER UNCERTAINTY OF NONLINEAR ENERGY SINKS

International audienceNonlinear Energy Sinks (NES) are used to passively reduce the amplitude of vibrations. This reduction is made possible by introducing a nonlinearly stiffening behavior in the NES, which might lead to an irreversible transfer of energy between the main system (e.g., a building) and the NES. However, this irreversible transfer, and therefore the efficiency of the NES, is strongly dependent on the design parameters of the NES. In fact, the efficiency of the NES might be so sensitive to changes in design parameters and other factors (e.g., initial conditions) that it is dis-continuous, switching from efficiency to inefficiency for a small perturbation of parameters. For this reason, this work introduces a novel technique for the optimization under uncertainty of NES. The approach is based on a support vector machine clas-sifier, which is insensitive to discontinuities and allows one to efficiently propagate uncertainties. The paper will provide examples of robust design of NES either modeled analytically or using finite elements