混凝土拱坝作为一种高次超静定结构,具有较强的自适应性和整体性,但传统混凝土拱坝变形统计模型主要考察单个测点的变形序列,不能体现不同测点之间的相互作用。基于传统混凝土拱坝变形统计模型,用空间计量方法挖掘了拱坝不同测点同一时刻误差项空间面板数据的空间关联特性;进一步采用空间面板自回归模型拟合变形序列误差项面板数据,建立了混凝土拱坝变形预测空间误差模型。小湾拱坝坝体34个监测点水平向变形监测序列分析结果表明:误差面板数据之间存在很强的正空间关联性质,空间误差模型的预测效果优于传统统计模型,具有一定应用前景。
Abstract
Concrete arch dam, as a highly statically indeterminate structure, has strong adaptability and integrity. Traditional statistical models for concrete arch dam mainly focus on the deformation of a single point rather than the interaction among different points. In this article, the spatial autocorrelation of errors of different points at the same instance was mined by using spatial econometric method. Furthermore, the errors were modified by using the spatial regression model, and hence a spatial error model for concrete arch dam was established. As an example, the deformation sequences of 34 monitoring points in Xiaowan arch dam were studied and the results show that the error panel data are of strong positive correlation, and the spatial error model is superior to traditional statistical models.
关键词
混凝土拱坝 /
空间面板数据 /
空间误差模型 /
空间自相关 /
变形预测
Key words
concrete arch dam /
spatial panel data /
spatial error model /
spatial autocorrelation /
deformation forecast
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基金
国家自然科学基金重点项目(41323001,51139001);高等学校博士学科点专项基金项目(20120094110005,20120094130003,20130094110010);江苏省杰出青年基金项目(BK20140039);水利部土石坝破坏机理与防控技术重点实验室基金项目(ky914002)
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