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Validation study demonstrates accurate underground deformation modeling using intelligent rock bolt data and statistical filtering, highlighting a reproducible framework for mine safety.
Numerical modelling is a powerful tool used in geomechanics; however, its reliability depends on proper validation. This study demonstrates the use of intelligent rock bolt measurements to validate the numerical model of underground deformation, providing a practical and applicable approach even with all numerical modelling simplifications. A numerical model of a selected Case Study Location was developed using geomechanical data from laboratory tests (uniaxial compressive strength, triaxial test, and Brazilian test). The numerical model was validated using deformation data collected by intelligent rock bolts installed in the underground mine. Applying statistical data correction methods, the model data accuracy was further improved. Applying Kalman filtering improved the correlation between measured and modelled deformations from 0.90 to 0.98, demonstrating the effectiveness of statistical methods. The novelty of this work lies in the combined use of intelligent rock bolts, FEM simulations, and statistical data correction to achieve a practical and reproducible validation framework, even when simplified geological assumptions are used.
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Varelija et al. (2026) studied this question.
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