变形分离法与数据驱动下的拱坝工作性态评价

基于有限测点位移监测数据推求大坝空间位移场变化规律是评价大坝工作性态的有效手段之一。拱坝受水荷载、温度等作用下产生的变形，不仅与坝体自身弹性模量有关，更取决于地基的变形特性。由于地基存在不均匀性等复杂问题，致使通过数值模拟的方法精准预测大坝的变形存在一定困难。本文将拱坝坝体的监测位移分解为坝体受荷载产生的位移及坝基约束变形产生的位移两部分，以其监测值与预测值系统误差最小为目标函数，基于坝体有限元模型建立了包含基础约束变形及坝体弹性模量为未知量的求解方程，通过大量位移监测资料结合人工智能粒子群算法寻优实现数据驱动，可同时求解坝基约束变形及坝体分区弹性模量。根据算例研究成果，针对复杂地基，采用本文方法推求得到的大坝空间位移场，除靠近坝体与坝基交界面附近节点位移预测值与有限元计算值相对误差稍大（约为3%）外，其余节点相对误差均在1.5%范围内，证明了本文方法的合理性；从本文方法在白鹤滩拱坝工程中的应用研究成果可知，其空间位移场相对误差分布合理且变形分离结果与实际情况相符，从而证明了方法的可行性。

Deformation separation method and data-driven evaluation of arch dam performance

The monitored displacements of an arch dam body are decomposed into two parts: one caused by dam body loading and the other by the constrained effect of dam foundation. Then, a set of equations that take the minimum systematic error of the monitored and predicted values as the objective function, can be established for the two unknowns－constrained foundation displacement and dam body elastic modulus. And they are solved simultaneously from a large body of monitored displacement data combined with PSO to achieve data-driven effect. A case study of a dam body on a complicated dam foundation shows that relative to FEM calculations, the dam body displacements calculated using this new method have relative errors in the range of 1.5%, with the exception of the nodes (with 3% errors) near its interface with the foundation, proving our method is effective and accurate. Application to the Baihetan arch dam reveals that the displacement calculations feature a reasonable spatial pattern of relative errors, and the deformation separation results are close to the real case, which validates our new displacement model.