Document Type : Original Article
Authors
1
Department of Mining and Environmental Engineering, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran; ali_aalianvari@kashanu.ac.ir
2
3. Department of Civil Engineering, Technical and Vocational University (TVU), Tehran, Iran.
3
Department of Mining Engineering, Faculty of Engineering, University of Kashan, Kashan, Iran.
10.22077/jgm.2026.10549.1064
Abstract
Accurate estimation of cement take is crucial for the economical and efficient design of grout curtains in dam foundations. This research aimed to compare the accuracy of common analytical models and to develop new models based on real-world data from grouting operations at the Azad Kurdistan and Siah Bishe dams. Initially, seven well-known analytical models (Johnson, Stille, Hassler, Lombardi, Håkansson, Bitobi, and Rastegarnia) were evaluated. The results indicated that the Hassler model, with relative errors of 6.8% and 12.9% for the Azad and Siah Bishe dams, respectively, performed best among the analytical models. Subsequently, to enhance accuracy, regression analysis was employed using SPSS software. For the Azad dam, where a linear relationship was prevalent, a multiple linear regression model was developed, achieving an adjusted coefficient of determination (R²) of 0.985 and a Root Mean Square Error (RMSE) of 0.008. For the Siah Bishe dam, which exhibited nonlinear behavior, a third-degree multiple nonlinear regression model was developed, showing a coefficient of determination of 0.917 and an RMSE of 0.24. Finally, a comparison of evaluation metrics confirmed the significant superiority of the developed statistical models over the best analytical model (Hassler). This study underscores the strong capability of data-driven statistical approaches for predicting cement take based on field data.
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