Detail publikace

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

Originální název

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

Anglický název

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

Jazyk

en

Originální abstrakt

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 deection of the beam. These chance constraints are handled by a sampling method (Probabilistic Robust Design).

Anglický abstrakt

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 deection of the beam. These chance constraints are handled by a sampling method (Probabilistic Robust Design).

Dokumenty

BibTex


@article{BUT149130,
  author="Jakub {Kůdela} and Pavel {Popela}",
  title="Chance constrained optimal beam design: convex reformulation and probabilistic robust design",
  annote="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 deection of the beam. These chance constraints are handled by a sampling
method (Probabilistic Robust Design).",
  address="UTIA",
  chapter="149130",
  doi="10.14736/kyb-2018-6-1201",
  howpublished="online",
  institution="UTIA",
  number="6",
  volume="54",
  year="2018",
  month="december",
  pages="1201--1217",
  publisher="UTIA",
  type="journal article in Web of Science"
}