Structural and Multidisciplinary Optimization

, Volume 59, Issue 5, pp 1655–1671 | Cite as

A new method for reliability analysis and reliability-based design optimization

  • Alfredo CanelasEmail author
  • Miguel Carrasco
  • Julio López
Research Paper


We present a novel method for reliability-based design optimization, which is based on the approximation of the safe region in the random space by a polytope-like region. This polytope is in its turn transformed into quite a simple region by using generalized spherical coordinates. The failure probability can then be easily estimated by considering simple quadrature rules. One of the advantages of the proposed approach is that by increasing the number of vertices, we can improve arbitrarily the accuracy of the failure probability estimation. The sensitivity analysis of the failure probability is also provided. We show that the proposed approach leads to an optimization problem, where the set of optimization variables includes all the original design variables and all the parameters that control the shape of the polytope. In addition, this problem can be solved by a single iteration scheme of optimization. We illustrate the performance of the new approach by solving several examples of truss topology optimization.


Reliability-based design Truss topology optimization Stochastic structural model 



Alfredo Canelas thanks the Uruguayan Councils ANII and CSIC for the financial support.

Funding information

This research was supported by CONICYT-Chile, via FONDECYT project 1160894.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Alfredo Canelas
    • 1
    Email author
  • Miguel Carrasco
    • 2
  • Julio López
    • 3
  1. 1.Facultad de Ingeniería, Instituto de Estructuras y TransporteUniversidad de la RepúblicaMontevideoUruguay
  2. 2.Facultad de Ingeniería y Ciencias AplicadasUniversidad de los AndesSantiagoChile
  3. 3.Facultad de Ingeniería y CienciasUniversidad Diego PortalesSantiagoChile

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