Quantifying Coal Rib Stability and Support Requirements using Bonded Block Modeling and Reliability Analysis based on the Random Set Theory

Abstract

An Apparent Flaw in Geomechanical Analysis of Rock Structures is the Application of Single Value Parameters as Input to Numerical Models. a Known But Often overlooked Characteristic of the Rock Mass is its Inherent Strong Property Variability. in Conventional Reliability Analysis of Rock Mechanics, Subjective Assumptions Are Often Made on the Probability Density Function of Parameters Because, in Many Cases, the Results of Geotechnical Investigations Are Set-Valued Rather Than Being Precise and Point-Valued. on the Other Hand, Imprecise Probability Theories Such as the Random Set Theory Could Be Considered a Possible Attractive Candidate to Employ in These Analyses. in This Study, the Random Set Theory in Combination with the Bonded Block Modeling (RS-BBM) Approach is Employed to Demonstrate its Practical Applicability in Determining Coal Rib Stability and Support Requirements. Sensitivity Analysis of the BBM Input Parameters is Conducted. the Uncertainties of the Geomechanical Parameters of the BBM Contacts, Which Control Model Behavior, Are Considered in the Reliability Analysis Model. the Analyses Were Performed in UDEC, and the Strength Reduction Method Was Used to Evaluate Rib Stability. It is Shown that RS-BBM is an Efficient Tool to Determine the Most Likely Bounds of Coal Rib Performance. a Method Combining the RS-BBM Approach with Empirical Methods is Also Described to Illustrate its Practical Application.

Department(s)

Mining Engineering

Comments

National Institute for Occupational Safety and Health, Grant None

Keywords and Phrases

Bonded block modeling; Coal rib stability; Numerical model input variability; Random set theory; Support requirement interval

International Standard Serial Number (ISSN)

1365-1609

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2023 Elsevier, All rights reserved.

Publication Date

01 Mar 2023

Link to Full Text

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