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Author ORCID Identifier

https://orcid.org/0009-0002-6884-929X

Date Available

4-22-2026

Year of Publication

2026

Document Type

Master's Thesis

Degree Name

Master of Science in Mining Engineering (MSMIE)

College

Engineering

Department/School/Program

Mining Engineering

Faculty

Zach Agioutantis

Abstract

This study evaluates the Surface Deformation Prediction System (SDPS Version 7) for predicting final and dynamic subsidence in longwall mining. Using the influence function method, SDPS 7 was calibrated using data from the Quarto 7 Mine (Ohio, USA) and two panels in Anhui Province, China, to test the reliability of the method under varying geological and operational conditions, particularly low advance rates.

For the Quarto 7 Mine, monument line C provided the optimal set of subsidence parameters: SSF of 78%, tanβ of 2.97, edge‑effect offset of 160 ft, with an RMSE of 0.108 ft. These values aligned with estimates obtained using values suggested in the literature for that region. Results for monument lines E and W showed reasonable parameters but slightly higher RMSE, suggesting localized variability. The analysis for the dynamic site specific parameters for monument line C yielded a time factor of 0.04 day⁻¹, matching measured subsidence curves closely.

Chinese case studies involving deeper panels and thicker unconsolidated overburden exhibited supercritical behavior (SSF ≈ 95%, tanβ ≈ 2.4–3). Dynamic time factors (0.03–0.04 day⁻¹) were consistent with the U.S. data. While SDPS 7 accurately reproduced subsidence troughs and temporal development, numerical instability occurred when low advance rates were combined with high time factors and small influence angles.

Overall, SDPS 7 offers reliable subsidence predictions across varied conditions when parameters are carefully calibrated and numerical limits respected. The system is validated for engineering decision‑making and risk management, though caution is advised under specific dynamic constraints. Future work should address additional mining geometries, horizontal deformation, and validation against subsequent mining panels.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2026.27b

Archival?

Archival

Funding Information

The Office of Surface Mining Reclamation & Enforcement is acknowledged for partially funding this research through grant number S24AC00036 under the Applied Science Grants.

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