Study on the Impact of Different Parameters on Prediction of Crown Deformations in Underground Caverns

Kadiyala Sudhakar (), Rabindra Kumar Sinha and Sripad Ramachandra Naik
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Kadiyala Sudhakar: Department of Mining Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad 826004, India
Rabindra Kumar Sinha: Department of Mining Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad 826004, India
Sripad Ramachandra Naik: National Institute of Rock Mechanics, Bengaluru 560070, India

Sustainability, 2023, vol. 15, issue 17, 1-22

Abstract: Crown deformation is a major concern in the design and construction of underground caverns. It can lead to damage to the cavern structure and surrounding infrastructure and can also pose a safety hazard to workers. This paper studies the factors affecting crown deformation in underground caverns. A parametric study was conducted to investigate the effects of seven parameters on crown deformation: rock mass rating (RMR), uniaxial compressive strength (UCS), Young’s modulus of intact rock (Ei), Poisson’s ratio (υ), tensile strength (σt), angle of internal friction (φ), and cohesion (C). The results of the parametric study showed that the following parameters significantly affected crown deformation: RMR, UCS, Ei, and Φ. A multiple linear regression analysis was conducted to develop a regression equation to predict crown deformation. The coefficient of determination (R 2 ) for the regression equation is 92.92%, which indicates that the equation is a good predictor of crown deformation. The parametric study results and the regression analysis can be used to improve the design and construction of underground caverns. By considering the factors that affect crown deformation, engineers can design more stable caverns that are less likely to experience deformations. The results of the study can be used to improve the design and construction of caverns, making them safer and more sustainable.

Keywords: crown deformation; underground caverns; parametric study; multiple linear regression (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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