Mining Contract: Mitigation of Groundfall Hazards Through Integration of Novel Field and Numerical Techniques

Contract # 200-2016-90154
Start Date 9/15/2016
Research Concept

This capacity-building contract will develop improvements in ground characterization, monitoring, analysis, and design approaches that will reduce injuries and fatalities associated with ground failures. Specific research goals associated with mitigation of these hazards are to improve prediction of skin failures through advancement of ground characterization, mapping and monitoring techniques; propose improvements in the design of ribs and their support through numerical back analyses of in-situ monitoring data;   identify opportunities for minimizing bursting risk through improved understanding of the mechanisms leading to instability in overstressed conditions; and reduce risk associated with pillar recovery by improving techniques for analyzing the potential for unexpected and sudden development of instability. The outcome of the proposed work will be a significant reduction in the number of injuries and fatalities associated with ground failures. Achieving these goals requires examination of the fundamental geological, geotechnical, and mine design factors which lead to ground instability in underground mines. This examination will be carried out using a combination of conventional and advanced ground characterization and monitoring technologies, empirical data and models, and numerical models.

Contract Status & Impact

This contract is ongoing. For more information on this contract, send a request to mining@cdc.gov.

In-situ data collection will focus on geological mapping and displacement monitoring; the latter will incorporate both conventional approaches (e.g., extensometers) and a 3-D point cloud-based approach. Research by Kromer et al. (2015) and Walton et al. (2016b) suggests that LiDAR data can be used to accurately record sub-mm displacement over large mine areas. The LiDAR data collected will be used to perform a detailed comparison of measured deformations to geological and geotechnical features identified through mapping and characterization activities. The high-resolution nature of the data will allow movements in both small and large segments of skin of the excavation to be analyzed. The ground characterization and deformation data will be distilled into a series a guidelines which will recommend what methods of ground characterization are most effective in assessing and prediction skin failure hazards, what monitoring procedures are best suited for practical implementation, and how best to analyze displacement data to predict skin failures.

Sensitivity analyses will be conducted to evaluate the relationships between material parameter inputs used to model yield (continuum models) or rock fracture development (SRM and FDEM) and rock and rock mass stress-strain behavior at various scales. By rigorously examining the connections between model parameters and observed phenomena, the efficiency of back analyses of laboratory and mine monitoring data can be greatly improved. With respect to the emerging FDEM modelling approach, the Hybrid Optimized Software Suite (HOSS) FDEM code developed at the Los Alamos National Laboratory (LANL) will be used (Rougier et al., 2014). Using well-studied cases from the literature (e.g., hard rock rib pillar monitoring by Walton et al., 2015 or coal rib pillar monitoring by Mohamed et al., 2016), different modeling approaches will be compared in their ability to replicate observed strength and deformational behavior of mine structures. This will allow for the evaluation of the ability of each approach to be calibrated to field data and will permit the determination of the relative strengths and weaknesses of each approach. Field data will be used both to investigate the mechanisms of rib instability directly as well as to calibrate numerical models. Calibration will be based on all available quantitative data and qualitative in-situ observations. Once calibrated, numerical models will be investigated to evaluate how variables which are not directly observable (e.g., strength evolution, dilatancy, stress path) may have changed over the monitoring period.

Research on bursting risk will begin with an extensive review of cases where bursting has occurred to identify common factors (e.g. geological, geotechnical, and mine design factors) which potentially contributed to the observed instability. Modeling of bursting phenomena will focus on replicating observed mechanisms from case studies and will build on the existing work of the research team (Gu & Ozbay, 2014; Walton et al., 2016a). The material models used will also be in part constrained by the results of numerical modeling activities previously performed. Numerical tests will be employed to evaluate the potential efficacy of design strategies for bursting risk mitigation (e.g., Iannacchione & Tadolini, 2008).

Data previously collected will be used both to investigate changes in pillar stresses and damage during pillar extraction. Numerical models will be constructed to test the responses of mine pillars to various loading conditions. These models will then be validated against various empirical systems to identify potential conditions under which each of the modeling approaches tested may not be applicable. The focus of this validation task will be on the modeling approaches which have a less developed history of validation in the literature (i.e., SRM and especially FDEM). Validated models will subsequently be calibrated to data collected. Emphasis will be placed on comparing different modeling approaches and the different potential instability mechanisms which they show in the context of the in-situ monitoring data. Based on the comparison of validated and calibrated results obtained using different modeling approaches, best practices for analysis will be established. The results of the analysis will also be used to suggest potential design solutions for pillar support and extraction procedures.


Page last reviewed: 9/18/2020 Page last updated: 9/18/2020