Chance constrained optimal beam design: convex reformulation and probabilistic robust design

Title:

Chance constrained optimal beam design: convex reformulation and probabilistic robust design

Creator:

Kůdela, Jakub and Popela, Pavel

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:e403cc8e-e3bf-462a-a49c-8f6b45fd2e6d
uuid:e403cc8e-e3bf-462a-a49c-8f6b45fd2e6d
doi:10.14736/kyb-2018-6-1201

Subject:

optimal design, stochastic programming, chance constrained optimization, probabilistic robust design, and geometric programming

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

In this paper, we are concerned with a civil engineering application of optimization, namely the optimal design of a loaded beam. The developed optimization model includes ODE-type constraints and chance constraints. We use the finite element method (FEM) for the approximation of the ODE constraints. We derive a convex reformulation that transforms the problem into a linear one and find its analytic solution. Afterwards, we impose chance constraints on the stress and the deflection of the beam. These chance constraints are handled by a sampling method (Probabilistic Robust Design).

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Kybernetika | 2018 Volume:54 | Number:6

Harvested from:

CDK

Metadata only:

false