Subtopic Deep Dive
Ground Pressure Monitoring in Deep Mines
Research Guide
What is Ground Pressure Monitoring in Deep Mines?
Ground Pressure Monitoring in Deep Mines uses instrumentation to measure strata pressure, convergence, and microseismic activity for predicting outbursts in underground coal mining.
This subtopic focuses on real-time sensors and data analysis for monitoring rock stress in deep coal seams. Key methods include microseismic monitoring and convergence gauges (Dou et al., 2014; 168 citations). Over 10 papers from 1985-2019 address monitoring technologies, with foundational work cited 398 times (Borquez et al., 1985).
Why It Matters
Monitoring systems provide early warnings for rockbursts, reducing fatalities in deep coal mines (Dou et al., 2014). Hongpu Kang (2014) reviews support technologies that integrate pressure data to stabilize roadways, enabling safer operations in complex conditions (211 citations). Zuo et al. (2019) analyze macro/meso failure behaviors, informing control strategies that prevent collapses and support high-production mining (98 citations).
Key Research Challenges
Rockburst Prediction Accuracy
Predicting dynamic rockbursts from pressure data remains unreliable due to complex stress interactions (Dou et al., 2014). Laboratory and field tests identify combined loading as a trigger, but real-time forecasting lags (168 citations). Wen et al. (2016) highlight differences between coal and metal mine bursts, complicating hazard evaluation (69 citations).
Surrounding Rock Deformation
Deep roadways experience severe deformation and damage under high ground pressure (Kang, 2014). Five roadway types show varying rock behaviors requiring tailored monitoring (211 citations). Zuo et al. (2019) detail macro/meso failure modes needing advanced instrumentation (98 citations).
Weak Floor Reinforcement
Weak floors in deep mines fail under pressure, demanding combined support systems (Kang et al., 2014). Monitoring convergence and stress is essential for reinforcement design (122 citations). Integration with real-time data analysis faces instrumentation durability issues.
Essential Papers
Rock mechanics for underground mining
G Borquez, J Folinsbee, M De Freitas et al. · 1985 · International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts · 398 citations
Support technologies for deep and complex roadways in underground coal mines: a review
Hongpu Kang · 2014 · International Journal of Coal Science & Technology · 211 citations
Based on geological and mining characteristics, coal mine roadways under complex conditions were divided into five types, for each type the deformation and damage characteristics of rocks surroundi...
Research progress of monitoring, forecasting, and prevention of rockburst in underground coal mining in China
Linming Dou, Zonglong Mu, Zhenlei Li et al. · 2014 · International Journal of Coal Science & Technology · 168 citations
As one of the dynamic disasters of coal mines, rockburst seriously affects underground safe coal mining. Based on the laboratory test, field test, and theoretical analysis, this study proposed the ...
Application of a combined support system to the weak floor reinforcement in deep underground coal mine
Yongshui Kang, Quansheng Liu, Guangqing Gong et al. · 2014 · International Journal of Rock Mechanics and Mining Sciences · 122 citations
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
A review on investigation of water-preserved coal mining in western China
Fan Li-min, MA Xiong-de · 2018 · International Journal of Coal Science & Technology · 72 citations
Abstract Yushenfu mining area is located in an ecological fragile area in western China, the coal seam of which is the Jurassic Yan’an Formation. The Jurassic Yan’an Formation contains five minable...
Reading Guide
Foundational Papers
Start with Borquez et al. (1985; 398 citations) for core rock mechanics, then Kang (2014; 211 citations) for deep roadway monitoring, and Dou et al. (2014; 168 citations) for rockburst principles.
Recent Advances
Study Zuo et al. (2019; 98 citations) for failure behaviors and Wen et al. (2016; 69 citations) for hazard evaluation in deep coal mines.
Core Methods
Core techniques are microseismic monitoring, convergence measurement, and stress analysis from field tests (Dou et al., 2014; Kang, 2014).
How PapersFlow Helps You Research Ground Pressure Monitoring in Deep Mines
Discover & Search
PapersFlow's Research Agent uses searchPapers and citationGraph to map monitoring literature from Borquez et al. (1985; 398 citations), revealing clusters around rockburst forecasting (Dou et al., 2014). exaSearch uncovers field-specific sensors in deep coal mines, while findSimilarPapers expands from Kang (2014) roadway supports.
Analyze & Verify
Analysis Agent applies readPaperContent to extract microseismic methods from Dou et al. (2014), then verifyResponse with CoVe checks prediction claims against field data. runPythonAnalysis processes pressure time-series with pandas for outlier detection, and GRADE scores evidence strength for rockburst models (Wen et al., 2016).
Synthesize & Write
Synthesis Agent detects gaps in real-time monitoring from Zuo et al. (2019) failure analyses, flagging contradictions in deformation models. Writing Agent uses latexEditText and latexSyncCitations to draft reports citing Kang (2014), with latexCompile generating figures and exportMermaid visualizing stress diagrams.
Use Cases
"Analyze microseismic data trends from recent rockburst papers for outlier detection."
Research Agent → searchPapers('rockburst monitoring coal') → Analysis Agent → runPythonAnalysis(pandas on time-series data) → matplotlib plot of pressure anomalies.
"Draft LaTeX report on roadway support technologies with citations."
Research Agent → citationGraph(Kang 2014) → Synthesis Agent → gap detection → Writing Agent → latexEditText + latexSyncCitations + latexCompile → PDF report.
"Find GitHub repos with ground pressure simulation code from mining papers."
Research Agent → paperExtractUrls(Zuo 2019) → Code Discovery → paperFindGithubRepo → githubRepoInspect → verified simulation scripts.
Automated Workflows
Deep Research workflow scans 50+ papers on pressure monitoring, chaining searchPapers → citationGraph → structured report on rockburst trends (Dou et al., 2014). DeepScan's 7-step analysis verifies deformation data from Kang (2014) with CoVe checkpoints. Theorizer generates hypotheses on integrated monitoring from Borquez et al. (1985) fundamentals.
Frequently Asked Questions
What is ground pressure monitoring in deep mines?
It involves sensors measuring strata pressure, convergence, and microseismics to predict outbursts (Dou et al., 2014).
What are key methods for rockburst monitoring?
Methods include laboratory tests, field monitoring, and combined stress analysis (Dou et al., 2014; Wen et al., 2016).
Which papers define the field?
Borquez et al. (1985; 398 citations) provides rock mechanics basics; Kang (2014; 211 citations) reviews deep roadway supports.
What are open problems in this area?
Challenges include accurate real-time rockburst prediction and durable sensors for weak floors (Zuo et al., 2019; Kang et al., 2014).
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