Research On Continuous Rigid Frame Bridge Girder Design Parameter Optimization Based On Genetic Algorithm

As a kind of bridge, the prestressed reinforced concrete continuous rigid frame bridge, which has the advantages of nice wholeness, bearing property, construction convenience, the larger span and the smooth driving, has been applied in plenty of practical engineering, besides, it has a further development prospects. The design parameters of continuous rigid frame bridge has been developed after the long-term practice, however, due to the complex and lengthy of the structural analysis and too many design factors, it is hard to do a systematic and scientific research on that bridge. Because of the lack of systematic theories, people design with experience and strong subjectivity, as a result, it costs of time and work, but still can not ensure the accuracy. Therefore, during the design of PC continuous rigid frame bridge, it is necessary to do further research on the data according to the existing results. This paper mainly studies on the design parameters of the main beam on the background of a continuous rigid frame bridge in Yunnan province with the method of numerical analysis, orthogonal experiment method and genetic algorithms. The main work is summarized as follows:(1)This paper introduces the development of the prestressed reinforced concrete continuous rigid frame bridge and the research status. And determine the parameters of the side-span ratio the high-span ratio at root of the beam, central beam high-cross ratio and the beam bottom curve line as the optimization variables, others as the optimization constants to analysis.(2) 26 bridges test model for the finite element analysis are built to calculate and find the best mid-span performance on an overall indicator on the basis of the internal force, stress, deflection and concrete volume, with the method of numerical analysis and orthogonal experiment, the parameter value combination are got.(3))This paper introduces the development and theory of heuristic algorithm. on the base of orthogonal experiment, do a further optimization research with genetic algorithm. Using MATLAB GA tool to do with the finite element analysis results of another 16 bridges test model, get a more accurate combination of parameter value. Besides, the results of genetic algorithm and orthogonal experiment method are proved each other.