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Advisor(s)
Abstract(s)
A robust design optimization (RDO)
approach for minimum weight and safe shell composite
structures with minimal variability into design
constraints under uncertainties is proposed. A new
concept of feasibility robustness associated to the
variability of design constraints is considered. So, the
feasibility robustness is defined through the determinant
of variance–covariance matrix of constraint
functions introducing in this way the joint effects of
the uncertainty propagations on structural response. A
new framework considering aleatory uncertainty into
RDO of composite structures is proposed. So, three
classes of variables and parameters are identified:
deterministic design variables, random design variables
and random parameters. The bi-objective optimization
search is performed using on a new approach
based on two levels of dominance denoted by Co-
Dominance-based Genetic Algorithm (CoDGA). The
use of evolutionary concepts together sensitivity
analysis based on adjoint variable method is a new
proposal. The examples with different sources of
uncertainty show that the Pareto front definition
depends on random design variables and/or random parameters considered in RDO. Furthermore, the
importance to control the uncertainties on the feasibility
of constraints is demonstrated. CoDGA
approach is a powerfully tool to help designers to
make decision establishing the priorities between
performance and robustness.
Description
Keywords
Bi-objective optimization Composite structures Feasibility robustness Uncertainty sources Sensitivity Co-dominance
Citation
Publisher
Springer Verlag