Stability analysis of surrounding rock in novel mining-induced self-forming roadway without advance tunnelling

The mining-induced self-forming roadway without advance tunnelling (MSRWAT) method is an innovative longwall mining technique developed in China. In this method, the roadway is formed automatically by the coal shearer during coal extraction, eliminating the need for chain pillars and all advance roadway excavation. This study investigates the stability of MSRWAT roadway, with a particular focus on its unique formation mechanism. The results show that the average convergence between the roof and floor in MSRWAT roadway is 11.34% lower than in gob-side entry retaining by roof cutting (GERBRC) roadway, primarily because the MSRWAT roadway avoids the abutment stress ahead of the mining face. Compared to conventional rectangular roadways, the cambered side of the MSRWAT roadways reduce failure depth by 5% to 40% across different conditions. This cambered geometry optimizes the stress distribution, minimizing the development of tensile stress in the surrounding rock. Based on these findings, corresponding engineering recommendations were proposed and successfully validated in the field. Field monitoring shows that the surrounding rock deformation in MSRWAT roadway is 73.67% less than that in GERBRC roadway. This work confirms the superior stability of MSRWAT roadways and offers practical guidance for implementing no pillar mining technology in underground coal mines.

Authors

Institutions

Publication Details

Journal
International Journal of Mining Science and Technology
Published
2026-04-01
DOI
https://doi.org/10.1016/j.ijmst.2026.03.016
Citations
1
Primary Topic
Rock Mechanics and Modeling
Type
article
Field-Weighted Citation Impact
9.71

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Stability analysis of surrounding rock in novel mining-induced self-forming roadway without advance tunnelling

Ming He, Xiaojie Yang, Jianping Zuo, Gang Yang
1 citations
International Journal of Mining Science and Technology
Rock Mechanics and Modeling
9.71
article

Stability analysis of surrounding rock in novel mining-induced self-forming roadway without advance tunnelling

Ming He, Xiaojie Yang, Jianping Zuo, Gang Yang
article en
1 citations

Abstract

The mining-induced self-forming roadway without advance tunnelling (MSRWAT) method is an innovative longwall mining technique developed in China. In this method, the roadway is formed automatically by the coal shearer during coal extraction, eliminating the need for chain pillars and all advance roadway excavation. This study investigates the stability of MSRWAT roadway, with a particular focus on its unique formation mechanism. The results show that the average convergence between the roof and floor in MSRWAT roadway is 11.34% lower than in gob-side entry retaining by roof cutting (GERBRC) roadway, primarily because the MSRWAT roadway avoids the abutment stress ahead of the mining face. Compared to conventional rectangular roadways, the cambered side of the MSRWAT roadways reduce failure depth by 5% to 40% across different conditions. This cambered geometry optimizes the stress distribution, minimizing the development of tensile stress in the surrounding rock. Based on these findings, corresponding engineering recommendations were proposed and successfully validated in the field. Field monitoring shows that the surrounding rock deformation in MSRWAT roadway is 73.67% less than that in GERBRC roadway. This work confirms the superior stability of MSRWAT roadways and offers practical guidance for implementing no pillar mining technology in underground coal mines.

International Journal of Mining Science and Technology
China University of Mining and Technology (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation
Openalex Percentile: Top 2%
Rock Mechanics and Modeling
9.71
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.