复杂运行条件下水工建筑物结构物理力学参数往往会随着服役时间的增长发生变异,及时了解更新这些参数对于掌握水工建筑物工作性态,指导水工建筑物安全监控具有十分重要的意义。基于量子遗传算法QGA建立坝体有限元力学参数反演模型,通过MATLAB编程建立有限元软件命令调用接口,利用工程实测值与有限元计算结果建立目标适应度函数,并通过量子遗传算法智能寻优,实现水工建筑物结构参数反演。为验证本算法的有效性,特以混凝土重力坝为例对坝体及基岩综合弹性模量进行反演分析,并与传统遗传算法反演结果进行对比,结果表明本算法反演精度及运行速度均较高于传统遗传算法,具有一定的科学和实践应用价值。

Physical and mechanical parameters of hydraulic structure under complex operation conditions tend to vary with the growth of time, and it is important to obtain these parameters in time for mastering working state, and guiding safety monitoring of hydraulic structures. In this paper, on the basis of quantum genetic algorithm (QGA) and finite element model, we establish an inverse model for mechanical parameters of dam. Through coding by using MATLAB, we build the interface of command calling for finite element software, and establish objective fitness function in association with calculated data of finite element model and measured data. Structural parameter inversion of hydraulic building is completed by intelligent optimization of QGA. In order to verify the algorithm in this paper, we take a concrete gravity dam as an example to carry out inverse analysis of comprehensive elastic modulus for dam concrete and rock in the foundation. Results show that the inversion accuracy and computing speed of the method above are better than those of traditional genetic algorithm. Finally, the research can be referenced for similar projects.