Fuzzy genetic optimization on performance-based seismic design of reinforced concrete bridge piers with single-column type
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This paper presents a fuzzy genetic optimization for performance-based seismic design (PBSD) of reinforced concrete (RC) bridge piers with single-column type. The design is modeled as a constrained optimization problem with the objective of minimizing construction cost subject to the constraints of qualified structural capacity and suitable reinforcement arrangements for the designed RC pier. A violation of the constraints is combined with construction cost to serve as the objective function. The fuzzy logic control (FLC), which adapts the penalty coefficients in the genetic algorithm (GA) optimization solver, was employed to avoid a penalty that is too strong or too weak through the entire calculation so that a feasible solution can be obtained efficiently.
The reported results of cyclic loading tests for three piers with square section, rectangular section and circular section, respectively, were employed as the data-base of investigation. Furthermore, a case study on the PBSD of a square RC bridge pier with four required performance objectives (fully operational, operational, life safety and near collapse) corresponding to different peak ground accelerations (PGAs) of earthquakes was analyzed. Six feasible designs of the pier were determined successfully and the optimal one with minimum construction cost was obtained accordingly. The result obtained shows that the proposed algorithm gives an acceptable design for the PBSD of the RC bridge piers.
The superiorities of GA and FLC were incorporated and the availability of the proposed procedure was investigated. Moreover, through the proposed systematic design procedure, the discrepancy in the PBSD from different design engineers will be lessened effectively and the design efficiency as well as the design precision will also be enhanced significantly.
KeywordsMinimum construction cost Penalty coefficient Pushover analysis Structural performance
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