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Fine optimization of rigid frame bridge parameters based on the genetic algorithm

Lu Yao, Li Dejian, Yao Che, Li Zhen

Archives of Civil Engineering

2021

Vol. 67, nr 4

261--272

The primary aim of this paper is to study the optimization of rigid frame bridge parameters. With a three-span continuous rigid frame bridge as the engineering background, finite element models were established. Then an index about bridge force condition was proposed to calculate the optimal side-to-mid span ratio with different side-to-mid span ratio parameters. Based on the ratio, the values of the girder depth at the pier and the bottom curve degree of the box-girder were taken as parameters in their common ranges for further optimization. A comprehensive multi-objective evaluation index correlated with the mid-span section stress, the mid-span deflection, and the concrete consumption was proposed to do fine optimization through the genetic algorithm method. The result of this study shows that the genetic algorithm is an effective method for bridge optimization and could provide better girder design parameter combinations for the comprehensive performance, and the optimal result could be obtained in the continuous parameter definition domains. It also shows that a larger girder depth at the pier to span ratio and a smaller curve degree in their common ranges should be taken for the bridge’s comprehensive performance.