基于神经网络算法的大型刚构拱桥有限元模型修正.doc

摘要 襄阳汉江五桥是典型的大跨度连续刚构拱桥，拱肋与箱梁结合部位构造复杂。大桥是襄阳内环线的控制性工程，利用成桥荷载试验进行有限元模型修正对长期健康监测具有重要价值。本襄阳汉江五桥为工程背景，首先研究分析其整体有限元模型建立中几个关键因素的影响，并对拱脚的构造复杂部位进行了局部有限元分析在此基础上利用成桥荷载试验结果和人工神经网络方法对初始有限元模型进行修正，对拱桥拱脚部位的刚域合理尺寸及结构的重要物理参数杨氏模量的进行了，最终获得了合理可靠的有限元模型为具体开展的工作）前半部分，主要针对襄阳汉江五桥整体有限元模型的成桥状态了讨论了拱肋采用梁单元或板单元、成桥吊杆力优化、桩土效应等的影响并对拱脚有限元模型的局部进行细的分析，MIDAS软件计算结果差异，对可修正因素探讨，为后期的修正奠定基础。）刚度的分析结果表明连续拱桥中，梁交汇处存在着明显的刚域效应如果未将其纳入试验的修正考虑范围，将使结构的荷载效验系数产生较大的误差的规范对于刚域的规定明确，构拱桥刚确定需要的分析。神经网络的学习尺寸的，得到静载试验实测。）考虑刚域效应多数测点的挠度效验系数提高至0.7~0.8内，与工程实际结构高度吻合的有限元模型结构的重要物理参数，杨氏模量值与规范设计值的偏差混凝土、拱肋预应力束杨氏模量修正基于灵敏度考虑，将混凝土、钢拱肋及预应力束的弹性模量纳入模型修正的考虑范围，与刚域尺寸同时作为可调结构参数将弹性模量作为模型修正的主考虑因素，将刚域长度作为副考虑因素采用均匀设计的方法进行参数组合，利用人工神经网络对数据进行训练，在其中挑选出一组最优组合，运营期健康监测。 关键词：连续刚构拱桥荷载试验刚域，局部分析 Abstract Xiangyang Hanjiang Bridge Five is a typical long-span continuous rigid frame bridge, the structure of the arch rib and box beam combining parts is complex. As the controlling project of Xiangyang inner ring, it is of great value to use the load test results to make an updating of the finite element model in the long-term health monitoring. This paper systematically introduces the influences of several key factors in establishing the whole finite element model, and makes a local finite element analysis on the complex parts of the arch foot. On this basis, using the load test results and the artificial neural network method a correction of the initial finite element model is made. Then we mainly analyze and discuss the reasonable rigid zone and structural physical parameters at the stewback of arch bridge. The influence of Young’s modulus on the deflection in static loading test is analyzed. Using the research results above in the fluctuation test combined with the boundary condition factors, the datum of static load test of the artificial neural network are reasonably corrected, finally a more reasonable and reliable finite element model has been got. The following is the specific work carried out in this article: (1) In the first half of the thesis, the reasonable