| Summary: | 碩士 === 國立臺北科技大學 === 土木與防災研究所 === 93 === Genetic algorithm (GA) and Neural Networks (NN) are two important approaches of artificial intelligence (AI) to deal with highly nonlinear problems effectively. With the strong ability in searching global minimum or maximum, GA is recognized as a powerful procedure for optimization. With the significant ability in learning, NN is able to reflect the nonlinear mapping relationships between input and output. As a result, GA and NN have been successfully applied to various engineering field. However, few of their applications to cable-stayed bridge were found. This thesis thus focuses on the applications of GA and NN on the structural optimal design and structural health diagnosis of cable-stayed bridge.
Based on the structural optimization approach, this thesis uses the theory of minimum strain energy of the bridge in deriving the objective function as the quadratic form of the post-tensioning cable forces. In addition, the equality constraints for the restriction on the displacements of the pylon and the un-equality constraints for the limitation on the envelopes of the cable forces are both implemented in the optimization model. GA is then conducted to find the post-tensioning cable forces of the bridge for the structural optimal design. Besides, GA and NN are used, respectively, to find the corresponding post-tensioning cable forces of the bridge subject to the measured rotations of pylon for the structural health diagnosis.
The Mau-Lo Hsi Cable-stayed Bridge is adopted as a case study. The results obtained revealed that the presented method indeed fulfill the structural optimal design and the structural health diagnosis and might be a useful reference for similar bridge engineering.
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