Estimation of the grout take using empirical relationships (case study: Bakhtiari dam site)

Sohrabi-Bidar, Abdollah; Rastegarnia, Ahmad; Zolfaghari, Abbas

doi:10.1007/s10064-015-0754-5

Cited by 31 publications

(21 citation statements)

References 18 publications

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“…Aperture may also affect the rock mass permeability. In this study, joint apertures were calculated according to Equation (2) suggested by Sohrabi-Bidar et al [14]:…”

Section: Gsi Is a Chart That Was Developed For Hoek And Brown Criterimentioning

confidence: 99%

“…The results of Kayabasi et al [13] show that the models developed are reliable enough and, if there is no direct test result, these models can be used in engineering projects. Sohrabi et al [14] correlated the grout volume with the Q-value, Lugeon number, SPI value, and joint apertures in Bakhtiri dam site in Iran. They defined a general correlation with mentioned parameters and grout take (Gt).…”

Section: Introductionmentioning

confidence: 99%

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An Assessment on Permeability and Grout Take of Limestone: A Case Study at Mut Dam, Karaman, Turkey

Kayabaşı

Gökçeoğlu

2019

Water

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The main purposes of the present study are to evaluate pilot grouting and to develop regression equations for prediction of grout intake. There are no permeability problems with the sandstone-siltstone-claystone alternations and basement clayey limestone at the dam site. Karstic limestone block is permeable due to karstification and heavy discontinuities. For the purpose of the study, Q system, geological strength index (GSI), secondary permeability index (SPI), joint spacing (JSP), joint apertures (Ap), Lugeon (Lu), and the permeability coefficient (k) were determined. Karstic limestone block rock mass properties correlated with grouting material amount. A series of simple and multiple nonlinear regression analyses was performed between grout take material amount (Gt) and average values of these rock mass properties. Significant determination coefficients were determined. Prediction capacity of the empirical equations were also examined with root mean square error (RMSE), values account for (VAF), mean absolute percentage error (MAPE), and prediction error evaluations. Considering simple regression analyses, the equation derived with Gt-SPI gives the best performance. The best prediction is determined with the equation derived with rock quality designation values (RQD), SPI, and joint aperture as input parameters with the multiple nonlinear regression analysis, in addition to this, other empirical equations also provide acceptable results.

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“…Aperture may also affect the rock mass permeability. In this study, joint apertures were calculated according to Equation (2) suggested by Sohrabi-Bidar et al [14]:…”

Section: Gsi Is a Chart That Was Developed For Hoek And Brown Criterimentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Assessment on Permeability and Grout Take of Limestone: A Case Study at Mut Dam, Karaman, Turkey

Kayabaşı

Gökçeoğlu

2019

Water

View full text Add to dashboard Cite

show abstract

“…One is the artificial empirical prediction method, which is basically based on the engineering experience of technicians and depends on the artificial experience to predict the grouting volume. Sohrabi-Bidar et al [39] established an empirical estimation method of grouting volume by taking the Bakhtiari dam site as a case study. Gustafson and Stille [40] established a prediction method of grouting volume in grouting construction based on empirical knowledge according to grouting characteristics and hydrogeological data.…”

Section: Introductionmentioning

confidence: 99%

An Intelligent Prediction Method of the Karst Curtain Grouting Volume Based on Support Vector Machine

Niu

Wang

et al. 2020

Geofluids

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The prediction of the grouting volume is a very important task in the grouting quality control. Because of the concealment and complexity of the karst curtain grouting engineering, there is little research on the prediction of the karst curtain grouting volume (KCGV), and the prediction is hindered by the practical problems of small samples, high dimensions, and nonlinearity. In the study, based on the basic idea of support vector machine (SVM), a multiparameter comprehensive intelligent prediction method of the KCGV is proposed, which overcomes the limitation of few sample data in practical engineering. This method takes the grouting construction conditions and the slurry conditions which control the slurry diffusion as the input parameters, which are the basic data which can be easily obtained in the field grouting process. This feature greatly improves the prediction accuracy and generalization performance of the method. The intelligent prediction method of the KCGV based on SVM is applied to a typical karst curtain grouting project. The mean absolute error of the prediction results is 3.47 L/m, and the mean absolute percentage error of the prediction results is 5.97%. The results show that the proposed prediction method has an excellent prediction effect on the KCGV and can provide practical and beneficial help for the field karst curtain grouting project.

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“…The first is the artificial experience prediction method, which is basically based on the engineering experience of technicians and relies on manual experience to predict the unit grouting quantity. Sohrabi-Bidar et al [18] used the Bakhtiari dam site as a research case to establish an empirical estimation method of the unit grouting quantity. Gustafson et al [19] established a prediction method of the unit grouting quantity in grouting construction based on empirical knowledge according to grouting characteristics and hydrogeological data.…”

Section: Introductionmentioning

confidence: 99%

Predicting of the Unit Grouting Quantity in Karst Curtain Grouting by the Water Permeability of Rock Strata

Niu

Bin

Chen³

et al. 2019

Applied Sciences

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The prediction of the unit grouting quantity is one of the key points in the design and construction of karst curtain grouting. Because of the concealment and complexity of the karst curtain grouting project, there is no reliable solution to this problem. In this paper, based on the calculation method of water permeability in water-pressure test in grouting engineering, Poiseuille flow equation in fluid mechanics, and cubic law, the relationship between the unit grouting quantity and the water permeability of rock strata in karst curtain grouting is studied. It is found that there is a nonlinear positive correlation between the unit grouting quantity and the water permeability of rock strata in karst curtain grouting, which is in the form of power function. At the same time, the comprehensive coefficient of karst curtain grouting ( K ) is introduced to describe the quantitative relationship between the unit grouting quantity and the water permeability of rock strata. K is comprehensively characterized by three controlling factors, namely, the characteristics of slurry fluid, the characteristics of grouted rock strata, and the technical factors of grouting in karst curtain grouting. Based on this theoretical relationship, a method for predicting the unit grouting quantity in karst curtain grouting by the water permeability of rock strata is proposed in this paper. Finally, based on the typical example of karst curtain grouting project, through the field grouting test and nonlinear function fitting, the comprehensive coefficient of karst curtain grouting ( K ) is 24.37 in the area of strong karst development, and it is 16.51 in the area of weak karst development. The proposed method is applied to the prediction of the unit grouting quantity in the main project of karst curtain grouting, and the results verify the rationality and applicability of the method. This study has a certain reference value and guiding role in the design, construction, and theoretical research of karst curtain grouting.

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Estimation of the grout take using empirical relationships (case study: Bakhtiari dam site)

Cited by 31 publications

References 18 publications

An Assessment on Permeability and Grout Take of Limestone: A Case Study at Mut Dam, Karaman, Turkey

An Assessment on Permeability and Grout Take of Limestone: A Case Study at Mut Dam, Karaman, Turkey

An Intelligent Prediction Method of the Karst Curtain Grouting Volume Based on Support Vector Machine

Predicting of the Unit Grouting Quantity in Karst Curtain Grouting by the Water Permeability of Rock Strata

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