Robust optimization and uncertainty quantification in the nonlinear mechanics of an elevator brake system

This paper deals with nonlinear mechanics of an elevator brake system subjected to uncertainties. A deterministic model that relates the braking force with uncertain parameters is deduced from mechanical equilibrium conditions. In order to take into account parameters variabilities, a parametric probabilis-tic approach is employed. In this stochastic formalism, the uncertain parameters are modeled as random variables , with distributions specified by the maximum en-tropy principle. The uncertainties are propagated by the Monte Carlo method, which provides a detailed statistical characterization of the response. This work still considers the optimum design of the brake system, formulating and solving nonlinear optimization problems, with and without the uncertainties effects.