Statistical regression analysis of seepage and seepage-pressure of gravity dam foundation of Shiban Hydropower Station

ZHANG Qiang-yong; LIN Chun-jin; XIANG Wen

doi:10.16285/j.rsm.2006.10.039

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Statistical regression analysis of seepage and seepage-pressure of gravity dam foundation of Shiban Hydropower Station

更新时间：2026-06-25

- Statistical regression analysis of seepage and seepage-pressure of gravity dam foundation of Shiban Hydropower Station
- Issue 10, Pages: 1831-1834(2006)
- 作者机构：
  
  1. 山东大学岩土与结构工程研究中心
  2. 山东大学岩土与结构工程研究中心,济南,250061
- 作者简介：
- 基金信息：
- DOI：10.16285/j.rsm.2006.10.039
  CLC： TV223.4
- Published：2006
- 稿件说明：
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[1]张强勇,林春金,向文.石板水电站重力坝坝基渗流渗压观测资料的统计回归分析[J].岩土力学,2006(10):1831-1834.

ZHANG Qiang-yong, LIN Chun-jin, XIANG Wen. Statistical regression analysis of seepage and seepage-pressure of gravity dam foundation of Shiban Hydropower Station[J]. 2006, (10): 1831-1834.
[1]张强勇,林春金,向文.石板水电站重力坝坝基渗流渗压观测资料的统计回归分析[J].岩土力学,2006(10):1831-1834. DOI： 10.16285/j.rsm.2006.10.039.

ZHANG Qiang-yong, LIN Chun-jin, XIANG Wen. Statistical regression analysis of seepage and seepage-pressure of gravity dam foundation of Shiban Hydropower Station[J]. 2006, (10): 1831-1834. DOI： 10.16285/j.rsm.2006.10.039.

摘要

渗流、渗压是影响坝基稳定的重要因素。通过对石板水电站重力坝坝基渗流、渗压多年观测数据的统计分析

考虑水位、温度和时效的影响

采用逐步回归分析法建立了坝基渗流、渗压的统计回归分析模型。回归计算结果表明

渗流、渗压统计值与观测值吻合较好

统计复相关系数较大

估计标准误差较小。统计回归分析模型有效地反映了坝基渗流、渗压的变化规律和发展趋势

为评价大坝运行安全性态提供了有效地分析手段和途径。

Abstract

Seepage and seepage-pressure are important factors which influence the stability of dam foundation. Based on some measured data of gravity dam of Shiban Hydropower Station

taking into account the influence of water

temperature and time on the seepage and seepage-pressure of dam foundation

a statistical regression analysis model for seepage and seepage-pressure has been established by the stepwise regression analysis method. Computing results indicate that the statistical regression data for seepage and seepage-pressure are accordant with measured data; the statistical double correlation coefficients between them are larger; and the estimation standard errors between them are smaller. The statistical regression analysis model efficiently reflects the changing rule and developing trend of seepage and seepage-pressure of dam foundation. This model has provided efficient analysis means for evaluating safety properties of the gravity dam.

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Related Author

ZHANG Qiang-yong

LIN Chun-jin

XIANG Wen

HUANG Rui

XIA Tang-dai

FANG Kai

LIU Zhi-jun

XU Wei-sheng

Related Institution

MOE Key Laboratory of Soft Soils and Geoenvironmental Engineering, Zhejiang University

Research Center of Coastal and Urban Geotechnical Engineering, Zhejiang University

College of Resources and Environmental Engineering, Shandong University of Science and Technology

State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University

School of Water Resources and Hydropower, Wuhan University

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