TY - JOUR
T1 - Compromise design of stochastic dynamical systems
T2 - A reliability-based approach
AU - Jensen, Hector A.
AU - Kusanovic, Danilo S.
AU - Valdebenito, Marcos A.
N1 - Funding Information:
This research was partially supported by CONICYT (National Commission for Scientific and Technological Research) under grant numbers 1070903 and 1110061 . This support is gratefully acknowledged by the authors.
PY - 2012/7
Y1 - 2012/7
N2 - This paper presents a procedure for obtaining compromise designs of structural systems under stochastic excitation. In particular, an effective strategy for determining specific Pareto optimal solutions is implemented. The design goals are defined in terms of deterministic performance functions and/or performance functions involving reliability measures. The associated reliability problems are characterized by means of a large number of uncertain parameters (hundreds or thousands). The designs are obtained by formulating a compromise programming problem which is solved by a first-order interior point algorithm. The sensitivity information required by the proposed solution strategy is estimated by an approach that combines an advanced simulation technique with local approximations of some of the quantities associated with structural performance. An efficient Pareto sensitivity analysis with respect to the design variables becomes possible with the proposed formulation. Such information is used for decision making and tradeoff analysis. Numerical validations show that only a moderate number of stochastic analyses (reliability estimations) has to be performed in order to find compromise designs. Two example problems are presented to illustrate the effectiveness of the proposed approach.
AB - This paper presents a procedure for obtaining compromise designs of structural systems under stochastic excitation. In particular, an effective strategy for determining specific Pareto optimal solutions is implemented. The design goals are defined in terms of deterministic performance functions and/or performance functions involving reliability measures. The associated reliability problems are characterized by means of a large number of uncertain parameters (hundreds or thousands). The designs are obtained by formulating a compromise programming problem which is solved by a first-order interior point algorithm. The sensitivity information required by the proposed solution strategy is estimated by an approach that combines an advanced simulation technique with local approximations of some of the quantities associated with structural performance. An efficient Pareto sensitivity analysis with respect to the design variables becomes possible with the proposed formulation. Such information is used for decision making and tradeoff analysis. Numerical validations show that only a moderate number of stochastic analyses (reliability estimations) has to be performed in order to find compromise designs. Two example problems are presented to illustrate the effectiveness of the proposed approach.
KW - Compromise design
KW - Optimization
KW - Reliability analysis
KW - Sensitivity analysis
KW - Uncertainty
UR - http://www.scopus.com/inward/record.url?scp=84857662358&partnerID=8YFLogxK
U2 - 10.1016/j.probengmech.2012.02.001
DO - 10.1016/j.probengmech.2012.02.001
M3 - Article
AN - SCOPUS:84857662358
SN - 0266-8920
VL - 29
SP - 40
EP - 52
JO - Probabilistic Engineering Mechanics
JF - Probabilistic Engineering Mechanics
ER -