Abstract
Knowledge of the deformation properties of the rock mass is essential for the stress–strain analysis of structures such as dams, tunnels, slopes, and other underground structures and the most important parameter of the deformability of the rock mass is the deformation modulus. This paper describes statistical models based on multiple linear regression and artificial neural networks. The models are developed using the test results of the deformation modulus obtained during the construction of the Iron Gate 1 dam on the Danube River and correlate these with measurements of the velocities of longitudinal waves and pressures in the rock mass. The parameters used for defining the models were obtained by in situ testing during dam construction, meaning that scale effects were also taken into account. For the analysis, 47 experimental results from in situ testing of the rock mass were obtained; 38 of these were used for modelling and nine were used for testing of the models. The model based on the artificial neural networks showed better performance in comparison to the model based on multiple linear regression.
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Acknowledgements
The part of this research is supported by Ministry of Education and Science of Serbia, Project TR37013 (Development of a system for safety management of high dams in the Republic of Serbia).
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Radovanović, S., Ranković, V., Anđelković, V. et al. Development of new models for the estimation of deformation moduli in rock masses based on in situ measurements. Bull Eng Geol Environ 77, 1191–1202 (2018). https://doi.org/10.1007/s10064-017-1027-2
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DOI: https://doi.org/10.1007/s10064-017-1027-2