TY - JOUR
T1 - A new method for reliability analysis and reliability-based design optimization
AU - Canelas, Alfredo
AU - Carrasco, Miguel
AU - López, Julio
N1 - Funding Information:
Acknowledgements Alfredo Canelas thanks the Uruguayan Councils ANII and CSIC for the financial support.
Funding Information:
Funding information This research was supported by CONICYT-Chile, via FONDECYT project 1160894.
Publisher Copyright:
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2019/5/15
Y1 - 2019/5/15
N2 - 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.
AB - 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.
KW - Reliability-based design
KW - Stochastic structural model
KW - Truss topology optimization
UR - http://www.scopus.com/inward/record.url?scp=85059679928&partnerID=8YFLogxK
U2 - 10.1007/s00158-018-2151-8
DO - 10.1007/s00158-018-2151-8
M3 - Article
AN - SCOPUS:85059679928
SN - 1615-147X
VL - 59
SP - 1655
EP - 1671
JO - Structural and Multidisciplinary Optimization
JF - Structural and Multidisciplinary Optimization
IS - 5
ER -