Subtopic Deep Dive
Rock Mass Strength Criteria
Research Guide
What is Rock Mass Strength Criteria?
Rock mass strength criteria are empirical, semi-empirical, and probabilistic models used to predict the strength and failure behavior of jointed rock masses in geomechanics and mining engineering.
These criteria, such as the Hoek-Brown failure criterion and Geological Strength Index (GSI), account for rock mass discontinuities and intact rock properties. Foundational works include Santos and Bieniawski (1989) on floor design and Lorig and Varona (2013) on numerical modeling guidelines. Recent papers exceed 1,000 citations collectively, focusing on applications in deep coal mining stability.
Why It Matters
Rock mass strength criteria enable safe design of underground excavations by predicting stability in deep mining, reducing risks like coal bursts and roof failures. Wang et al. (2015) applied these in fully mechanized top-coal caving for ultra-thick seams, achieving high production rates. Zuo et al. (2019) used macro-meso models for roadway control, while Zhu et al. (2022) integrated them into fuzzy evaluation for coal burst prediction, preventing disasters in high-stress environments.
Key Research Challenges
Heterogeneity Quantification
Jointed rock masses exhibit variable discontinuity patterns, complicating uniform strength prediction. Singh and Tamrakar (2013) applied RMR and GSI to Himalayan rock slopes, highlighting rating inconsistencies. Probabilistic models are needed to capture spatial variability.
Deep Mining Instability
Increasing mining depths amplify stresses, leading to rockbursts and sloughing. Wen et al. (2016) differentiated coal mine rockbursts from metal mines, stressing hazard evaluation needs. Zuo et al. (2019) analyzed macro-meso failures in deep roadways.
Uncertainty in Parameters
Input parameters like GSI and intact strength carry high uncertainty from site variability. Zhu et al. (2022) used analytic hierarchy process for coal burst risk amid influencing factors. Microseismic integration, as in Li et al. (2023), addresses dynamic risks.
Essential Papers
Key technologies and equipment for a fully mechanized top-coal caving operation with a large mining height at ultra-thick coal seams
Jinhua Wang, Bin Yu, Hongpu Kang et al. · 2015 · International Journal of Coal Science & Technology · 115 citations
Thick and ultra-thick coal seams are main coal seams for high production rate and high efficiency in Chinese coal mines, which accounts for 44 % of the total minable coal reserve. A fully mechanize...
Macro/meso failure behavior of surrounding rock in deep roadway and its control technology
Jianping Zuo, Jintao Wang, Yunqian Jiang · 2019 · International Journal of Coal Science & Technology · 98 citations
Modeling study on the influence of the strip filling mining sequence on mining‐induced failure
Ning Jiang, Changxiang Wang, Haiyang Pan et al. · 2020 · Energy Science & Engineering · 94 citations
Abstract The strip filling mining method can solve the problems related to mining under structures, under aquifers, and under infrastructure (3U coal seams), while the reasonable selection of the m...
A Prediction Method of Coal Burst Based on Analytic Hierarchy Process and Fuzzy Comprehensive Evaluation
Zhijie Zhu, Yunlong Wu, Jun Han · 2022 · Frontiers in Earth Science · 73 citations
Coal burst has become a worldwide problem that needs to be solved urgently for the sake of coal mine safety production due to its complicated triggering mechanisms and numerous influencing factors....
A Study of Rockburst Hazard Evaluation Method in Coal Mine
Zhijie Wen, Wang Xiao, Yunliang Tan et al. · 2016 · Shock and Vibration · 69 citations
With the increasing of coal mining depth, the mining conditions are deteriorating, and dynamic hazard is becoming more likely to happen. This paper analyzes the relations and differences between ro...
Mining induced strata movement and roof behavior in underground coal mine
Tao Xu, Tianhong Yang, Chongfeng Chen et al. · 2015 · Geomechanics and Geophysics for Geo-Energy and Geo-Resources · 61 citations
Research on the Mechanism and Control Technology of Coal Wall Sloughing in the Ultra-Large Mining Height Working Face
Xuelong Li, Xinyuan Zhang, Wenlong Shen et al. · 2023 · International Journal of Environmental Research and Public Health · 59 citations
One of the primary factors affecting safe and effective mining in fully mechanized mining faces with large mining heights is coal wall sloughing. This paper establishes the mechanical model of the ...
Reading Guide
Foundational Papers
Start with Santos and Bieniawski (1989) for floor design principles and Lorig and Varona (2013) for numerical modeling guidelines, as they establish core strength criteria applications in mining support.
Recent Advances
Study Zuo et al. (2019) for deep roadway macro-meso behavior and Zhu et al. (2022) for fuzzy coal burst evaluation, representing high-citation advances.
Core Methods
Core techniques: Hoek-Brown criterion via GSI (Singh & Tamrakar, 2013), analytic hierarchy process (Zhu et al., 2022), and microseismic fuzzy models (Li et al., 2023).
How PapersFlow Helps You Research Rock Mass Strength Criteria
Discover & Search
Research Agent uses searchPapers and citationGraph to map foundational criteria like Hoek-Brown from Santos and Bieniawski (1989), then exaSearch for recent applications in coal bursts (Zhu et al., 2022), and findSimilarPapers to uncover 50+ related works on GSI in mining.
Analyze & Verify
Analysis Agent applies readPaperContent to extract GSI parameters from Singh and Tamrakar (2013), verifies Hoek-Brown fits via runPythonAnalysis with NumPy for stress-strain curves, and uses verifyResponse (CoVe) with GRADE grading to confirm probabilistic models against Zuo et al. (2019) data.
Synthesize & Write
Synthesis Agent detects gaps in rockburst prediction between Wen et al. (2016) and Li et al. (2023), flags contradictions in pillar design from Jawed (2013); Writing Agent uses latexEditText, latexSyncCitations for Hoek-Brown reports, and latexCompile for stability diagrams.
Use Cases
"Compare Hoek-Brown GSI ratings across deep coal mine papers for rockburst risk."
Research Agent → searchPapers + citationGraph → Analysis Agent → runPythonAnalysis (pandas statistical comparison of GSI data from Singh & Tamrakar 2013 and Zhu et al. 2022) → GRADE-verified summary table.
"Generate LaTeX report on coal pillar strength criteria for extra-thick seams."
Synthesis Agent → gap detection → Writing Agent → latexEditText + latexSyncCitations (He et al. 2019, Jawed 2013) + latexCompile → formatted PDF with failure mode diagrams.
"Find Python codes for Hoek-Brown criterion simulation in mining stability."
Research Agent → paperExtractUrls (Lorig & Varona 2013) → Code Discovery → paperFindGithubRepo + githubRepoInspect → executable NumPy scripts for strength envelope plotting.
Automated Workflows
Deep Research workflow conducts systematic review of 50+ papers on rock mass criteria, chaining searchPapers → citationGraph → structured report on Hoek-Brown evolutions from Santos & Bieniawski (1989). DeepScan applies 7-step analysis with CoVe checkpoints to verify GSI applications in Zuo et al. (2019). Theorizer generates probabilistic extensions from microseismic data in Li et al. (2023).
Frequently Asked Questions
What defines rock mass strength criteria?
Empirical models like Hoek-Brown and GSI predict jointed rock failure using intact strength and discontinuity ratings (Singh & Tamrakar, 2013).
What are common methods in this subtopic?
Methods include RMR/GSI classification, fuzzy comprehensive evaluation (Zhu et al., 2022), and microseismic-based modeling (Li et al., 2023).
What are key papers on rock mass strength?
Foundational: Santos & Bieniawski (1989) on floor design; Jawed (2013) on pillar design. Recent: Zuo et al. (2019) on deep roadway failure; He et al. (2019) on pillar width.
What open problems exist?
Challenges include uncertainty quantification in deep mining and integrating microseismic data for real-time rockburst prediction (Wen et al., 2016; Li et al., 2023).
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