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

Abstract : 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.
Complete list of metadatas

Cited literature [21 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-02105068
Contributor : Americo Cunha Jr <>
Submitted on : Saturday, April 20, 2019 - 12:08:49 AM
Last modification on : Friday, June 28, 2019 - 5:01:03 AM

File

MECC-D-18-00701_v6.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-02105068, version 1

Collections

Citation

Piotr Wolszczak, Pawel Lonkwic, Americo Cunha Jr, Grzegorz Litak, Szymon Molski. Robust optimization and uncertainty quantification in the nonlinear mechanics of an elevator brake system. Meccanica, Springer Verlag, 2019, 54, pp.1057-1069. ⟨hal-02105068⟩

Share

Metrics

Record views

40

Files downloads

21