# Investigation of surface subsidence behaviour in multi-slice longwall mining using numerical simulations in Barapukuria coal mine, Bangladesh

## TL;DR

This study uses simulations to analyze how multi-slice longwall mining causes surface subsidence in Bangladesh, showing increasing vertical and horizontal displacements.

## Contribution

The study introduces a numerical simulation approach to quantify nonlinear subsidence progression in multi-slice longwall mining.

## Key findings

- Vertical subsidence reached 5.14 m after the third mining slice, with a subsidence ratio increasing from 0.08 to 0.86.
- Horizontal displacement peaked at 1.91 m, while stress redistribution in overburden reached 35.50 MPa, causing strata compaction and fracturing.
- The research emphasizes the need for improved subsidence prediction models to protect infrastructure and ensure sustainable mining.

## Abstract

This study investigates surface subsidence induced by multi-slice longwall mining in the Barapukuria coal basin using FLAC3D numerical simulations. The research quantifies the progressive vertical and horizontal deformations caused by mining over multiple phases, analysing the redistribution of stress in the surrounding strata and the corresponding surface displacements. The results demonstrate a clear nonlinear escalation of vertical subsidence, with maximum displacements reaching 5.14 m after the third mining slice. Horizontal displacement similarly increased, with peak values reaching 1.91 m. The study reveals that the subsidence ratio, defined as vertical displacement relative to mining thickness, increased from 0.08 to 0.86 as mining depth progressed, while the horizontal deformation coefficient decreased. Stress redistribution analysis shows that the peak vertical stress in the overburden reached 35.50 MPa in the third phase, leading to significant compaction and fracturing of the strata, which contributed to the observed subsidence. These findings underscore the cumulative and nonlinear nature of surface deformation, emphasizing the critical need for advanced subsidence prediction models and effective mitigation strategies. In particular, the research offers practical insights into managing surface displacement in areas with dense infrastructure, such as residential, industrial, and transportation networks, as well as in environmentally sensitive regions. The study further highlights the importance of incorporating stress redistribution mechanisms to enhance subsidence management, thereby minimizing the risk of damage to local infrastructure and ensuring sustainable mining practices.