中文摘要：

结构的材料常数的动态贝叶斯的错误功能为薄墙的曲线盒子 girders 被开发。为一个维的 Fibonacci 系列与最佳的步长度与自动搜索计划结合了， Powells 优化理论被用来执行薄墙的曲线盒子的材料常数的随机的鉴定。然后，在参数鉴定的步被介绍。为薄墙的曲线盒子的材料常数的 Powells 鉴定过程被编，在哪个薄墙的曲线盒子的机械分析基于有限曲线长带元素(FCSE ) 被完成方法。一些古典例子证明 Powells 鉴定数字地稳定、会聚，显示现在的方法和编的过程正确、可靠。在参数期间反复的进程， Powells 理论随 FCSE 部分区别的计算是无关的，它证明高计算是学习方法的效率。系统参数和回答的随机的表演同时在动态贝叶斯的错误函数被考虑。最佳的步长度的一个维的优化问题被没有决定这个区域，优化的步长度躺在的需要，采用 Fibonacci 系列搜索方法解决。

英文摘要：

A dynamic Bayesian error function of material constants of the structure is developed for thin-walled curve box girders. Combined with the automatic search scheme with an optimal step length for the one-dimensional Fibonacci series, Powell＇s optimization theory is used to perform the stochastic identification of material constants of the thin-walled curve box. Then, the steps in the parameter identification are presented. Powell＇s identification procedure for material constants of the thin-walled curve box is compiled, in which the mechanical analysis of the thin-walled curve box is completed based on the finite curve strip element （FCSE） method. Some classical examples show that Powell＇s identification is numerically stable and convergent, indicating that the present method and the compiled procedure are correct and reliable. During the parameter iterative processes, Powell＇s theory is irrelevant with the calculation of the FCSE partial differentiation, which proves the high computation efficiency of the studied methods. The stochastic performances of the system parameters and responses axe simultaneously considered in the dynamic Bayesian error function. The one-dimensional optimization problem of the optimal step length is solved by adopting the Fibonacci series search method without the need of determining the region, in which the optimized step length lies.