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Deformation forecasting model and its modeling method of super high arch dams during initial operation periods
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摘要: 针对特高拱坝运行初期温度场的非稳定性和时效的非单调增长性，发展变形监测和预报模型，并提出构建方法。通过主成分上的分层聚类法选取代表性温度测点，将其实测值作为温度变量，引入包含徐变及其恢复项的时效变量表达式，论证其表达谷幅变形的能力。进而考虑库水位、实测温度、组合时效等变量，应用增强回归树方法提出特高拱坝运行初期变形监测和预报模型，并通过后向消减变量建立优化模型。分析各变量对变形的边际效应，得出相对影响，借助部分依赖图，辨识变量间相关关系及其对坝体变形的影响规律，揭示变形机制。将该模型应用于某特高拱坝，验证该模型的可行性和有效性；并将结果与支持向量机、多元回归模型进行对比分析，得出该模型具有显著的优越性。Abstract: The dam temperature field has not been stabilized, and the time dependent effect does not increase non-monotonously for super high arch dams during initial operation period. Therefore a special deformation monitoring and forecasting model was developed, and its modeling method was proposed in the study. The key temperature measurement points were chosen by the hierarchical clustering on principal component method, and the corresponding time series were inputted as thermal predictors. The combined time dependent effect, including creep and its restoration, was introduced as time dependent deformation. This time dependent effect was employed to validate its characterization for the valley contraction deformation. Considering the predictor variables such as reservoir water level, adopted measured temperatures, estimated time dependent effect, the simple boosted regression tree (BRT) based dam deformation prediction model was constructed. Through the backward elimination method, a simplified BRT (SBRT) model only including major predictors was obtained. The marginal effects of variables on deformation were analyzed, and the relative influences can be quantitatively analyzed. With the help of partial dependence plot, the correlations among variables and the influences of variables on deformation can be explored, and the deformation mechanism can be revealed. The model was applied to a super high arch dam, and the case study verified the feasibility of the model. The results were compared with those by the support vector machine model and the traditional multiple regression models, which shows the superiority of the developed model.
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图 1 坝体垂线和16#坝段温度测点布置
Figure 1. Layout of embedded pendulums and temperature sensors in Monolith 16
图 2 蓄水、坝顶径向位移和谷幅变形过程线
Figure 2. Time histories of reservoir water level, dam crest displacment and valley contraction deformation
图 3 蓄水过程16#坝段典型高程温度时空变化过程
Figure 3. Evolutions of air, water and concrete temperatures of typical points in Monolith 16
图 4 PL15-5库水温和典型段坝体温度测点HCPC结果
Figure 4. HCPC results of reservoir water temperatures and dam concrete temperatures of typical observation points
图 5 采用时效变量拟合得到的谷幅变形过程线
Figure 5. Comparison of observed and fitted values of contraction deformation of VDL04
表 1 模型构建考虑的实测温度变量
Table 1. Measured temperature variables considered in model construction
垂线段 PL15-5 PL15-4 PL15-3 PL15-2 PL15-1 选取的温度计 T6，S3-1，S6-4，S6-9 T14，T15 S5-4，T18 S5-5，T28 T29 
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表 2 各模型的训练集和预测集的平均绝对误差
Table 2. Comparisons of mean absolute errors among training and prediction sets of constructed models
单位：mm 模型 SBRT SVM HTT HST 训练 预测 训练 预测 训练 预测 训练 预测 平均绝对误差 0.42 0.84 0.95 1.49 1.83 3.07 5.96 6.62
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