TY - JOUR
T1 - Structural design optimization based on hybrid time-variant reliability measure under non-probabilistic convex uncertainties
AU - Wang, Lei
AU - Ma, Yujia
AU - Yang, Yaowen
AU - Wang, Xiaojun
N1 - Publisher Copyright:
© 2018 Elsevier Inc.
PY - 2019/5
Y1 - 2019/5
N2 - Structural safety assessment issue, considering the influence of uncertain factors, is widely concerned currently. However, uncertain parameters present time-variant characteristics during the entire structural design procedure. Considering materials aging, loads varying and damage accumulation, the current reliability-based design optimization (RBDO) strategy that combines the static/time-invariant assumption with the random theory will be inapplicable when tackling with the optimal design issues for lifecycle mechanical problems. In light of this, a new study on non-probabilistic time-dependent reliability assessment and design under time-variant and time-invariant convex mixed variables is investigated in this paper. The hybrid reliability measure is first given by the first-passage methodology, and the solution aspects should depend on the regulation treatment and the convex theorem. To guarantee the rationality and efficiency of the optimization task, the improved GA algorithm is involved. Two numerical examples are discussed to demonstrate the validity and usage of the presented methodology.
AB - Structural safety assessment issue, considering the influence of uncertain factors, is widely concerned currently. However, uncertain parameters present time-variant characteristics during the entire structural design procedure. Considering materials aging, loads varying and damage accumulation, the current reliability-based design optimization (RBDO) strategy that combines the static/time-invariant assumption with the random theory will be inapplicable when tackling with the optimal design issues for lifecycle mechanical problems. In light of this, a new study on non-probabilistic time-dependent reliability assessment and design under time-variant and time-invariant convex mixed variables is investigated in this paper. The hybrid reliability measure is first given by the first-passage methodology, and the solution aspects should depend on the regulation treatment and the convex theorem. To guarantee the rationality and efficiency of the optimization task, the improved GA algorithm is involved. Two numerical examples are discussed to demonstrate the validity and usage of the presented methodology.
KW - Convex mixed variables
KW - Non-probabilistic time-variant hybrid reliability optimization
KW - The first-passage method
KW - The improved GA algorithm
UR - https://www.scopus.com/pages/publications/85059301195
U2 - 10.1016/j.apm.2018.12.019
DO - 10.1016/j.apm.2018.12.019
M3 - 文章
AN - SCOPUS:85059301195
SN - 0307-904X
VL - 69
SP - 330
EP - 354
JO - Applied Mathematical Modelling
JF - Applied Mathematical Modelling
ER -