Mathematical and Computational Methods in Deep Rock Mechanics
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E: Applied Mathematics".
Deadline for manuscript submissions: 31 May 2027 | Viewed by 52
Editors
Interests: rock engineering; rock mechanics; computational methods
Special Issues, Collections and Topics in MDPI journals
Interests: mining engineering; intelligent rock mechanics; rock dynamic; numerical simulation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Rock masses are inherently heterogeneous and discontinuous, exhibiting complex mechanical responses across multiple scales. Under deep excavation and high in situ stress, sudden failure phenomena such as rockbursts frequently occur, endangering both safety and sustainability. Traditional empirical and deterministic approaches struggle to capture the spatiotemporal evolution of stress redistribution, energy accumulation and release. This is where advanced mathematical and computational frameworks become essential, not merely for forward simulation, but for formulating new constitutive laws, solving inverse problems and quantifying uncertainties.
This Special Issue invites original contributions that develop rigorous mathematical theories, including nonlinear PDEs, stochastic processes and optimization, alongside high‑performance numerical algorithms (FEM, DEM, phase‑field, etc.) to address core challenges. Special emphasis is placed on rockburst prediction and early warning: microseismic signal processing, energy‑based instability criteria, machine learning from multi‑sensor monitoring and real‑time Bayesian hazard updating. We also welcome studies on fracture network evolution, coupled thermo‑hydro‑mechanical processes, tunnel stability and long‑term convergence of underground openings. By bridging mathematical rigor with practical engineering demands, especially in deep mining and tunnel construction, this Issue aims to cultivate robust, interpretable and field‑adaptable methodologies for safer and more efficient rock engineering.
Dr. Song Luo
Prof. Dr. Kang Peng
Guest Editors
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Keywords
- rock mechanics
- mathematical modeling
- computational simulation
- rockburst prediction and early warning
- numerical methods
- uncertainty quantification
- machine learning in geomechanics
- fracture and damage evolution
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