Computers and Concrete

Volume 20, Number 3, 2017, pages 275-282

DOI: 10.12989/cac.2017.20.3.275

Evaluating analytical and statistical models in order to estimate effective grouting pressure

Hassan Bakhshandeh Amnieh, Majid Masoudi and Mohammdamin Karbala

Abstract

Grouting is an operation often carried out to consolidate and seal the rock mass in dam sites and tunnels. One of the important parameters in this operation is grouting pressure. In this paper, analytical models used to estimate pressure are investigated. To validate these models, grouting data obtained from Seymareh and Aghbolagh dams were used. Calculations showed that P-3 model from Groundy and P-25 model obtained from the results of grouting in Iran yield the most accurate predictions of the pressure and measurement errors compared to the real values in P-25 model in this dams are 12 and 14.33 Percent and in p-3 model are 12.25 and 16.66 respectively. Also, SPSS software was applied to define the optimum relation for pressure estimation. The results showed a high correlation between the pressure with the depth of the section, the amount of water take, rock quality degree and grout volume, so that the square of the multiple correlation coefficient among the parameters in this dams were 0.932 and 0.864, respectively. This indicates that regression results can be used to predict the amount of pressure. Eventually, the relationship between the parameters was obtained with the correlation coefficient equal to 0.916 based on the data from both dams generally and shows that there is a desirable correlation between the parameters. The outputs of the program led to the multiple linear regression equation of P=0.403 Depth+0.013 RQD+0.011 LU–0.109 V+0.31 that can be used in estimating the pressure.

Key Words

grouting; analytical and statistical modeling; pressure

Address

Hassan Bakhshandeh Amnieh: School of Mining, College of Engineering, University of Tehran, Iran Majid Masoudi: Department of Mining Engineering, Faculty of Engineering, University of Kashan, Iran Mohammdamin Karbala: Mining Eng., Amirkabir Univ. of Tech (Tehran Polytechnic), Rahsazi & Omran Iran Cons. Co., Iran