Fires in underground mines pose significant risks to worker safety. In this study, a digital twin of an underground mine was created, and the heat, gas distribution, and airflow dynamics were investigated during and after the fire using computational fluid dynamics (CFDs) methods at three different locations. While traditional methods did not indicate any problems, the results from the CFDs analyses revealed some important findings. One of the key findings of the study was the change in airflow direction caused by the changing thermodynamic conditions caused by the fire. The digital twin allows us to demonstrate how a fire at any point within the mine can affect the entire mine under these changing thermodynamic conditions. The digital twin enables the real-time monitoring of underground events. Additionally, it facilitates strategic planning to anticipate potential incidents during a fire in an underground mine, allowing for necessary precautions to be implemented.

Fires in underground metal mines pose significant risks to worker safety and operational continuity. This study analyses the performance of the ventilation system after a fire in an underground metal mine using the Computa-tional Fluid Dynamics (CFD) method. Three different fire scenarios were modelled, examining temperature distri-bution, toxic gas dispersion, and airflow dynamics during the fire. Simulation results reveal how the fire spreads in other areas and assess the efficiency of the existing ventilation system. Findings indicate that the ventilation system is insufficient in certain areas for smoke extraction, and the post-fire gas clearance process varies across different locations. In particular, the positioning of auxiliary fans and the airflow direction are key factors in determining the spread of smoke after a fire. Based on these analyses, optimising post-fire ventilation strategies and enhancing emergency action plans are recommended. This study highlights the critical role of CFD analyses in the mining in-dustry in improving safety and efficiency and contributes to developing safer underground mine ventilation sys-tems. Furthermore, this study stands to make a substantial impact on the practical implementation of the "ventila-tion on demand" concept, advancing our understanding and application of this critical approach. On the other hand, the most important result of this study is that an underground mine with a very large volume is subject to cdf analysis as a whole. Because it is the first study to reveal that the direction of air flow changes as a fire in any part of the mine changes the thermodynamic conditions of the entire mine.

Blast-induced ground vibration is traditionally predicted using empirical scaled-distance equations or numerical simulations driven by simplified analytical loading functions. Although dynamic finite element modeling has significantly advanced the understanding of stress-wave propagation, existing approaches remain unable to reproduce the complete seismic response of actual production blasting because the true blast source is generally unknown and is therefore replaced by simplified pressure–time functions. Consequently, a field-calibrated physics-informed Digital Twin framework for production blasting remains insufficiently established. This study presents a PI-DDT framework for production blasting based on field-derived seismic source reconstruction. The proposed methodology consists of two complementary innovations. First, the three-component near-field pilot-blast record was analyzed through deconvolution-based inverse wave propagation, and the transverse, longitudinal, and vertical components were independently deconvolved to reconstruct three orthogonal equivalent single-hole seismic source histories at the pilot blast hole. Second, the three reconstructed source histories were incorporated into the PLAXIS 3D dynamic finite element model through component-specific dynamic multiplier functions together with the actual production-blast geometry, blast-hole coordinates, electronic initiation sequence, site-specific rock-mass properties, and attenuation characteristics to establish a field-calibrated PI-DDT framework for a full-scale production blast. The proposed framework was applied to a full-scale production blast comprising 83 blast holes in an operating open-pit mine. Model performance was evaluated through a multi-domain performance assessment including PPV, amplitude-envelope development, frequency-spectrum agreement, and cumulative-energy evolution. The simulated responses showed practically meaningful agreement with field measurements across multiple monitoring locations, with a median component PPV error of 11.8%, a mean three-dimensional resultant PPV error of 14.2%, a mean resultant spectral similarity of 84.0%, and a mean three-dimensional cumulative-energy MAE of 4.7%. Unlike conventional blasting simulations that rely on simplified analytical loading functions, the proposed methodology reconstructs a field-derived equivalent seismic source signature and integrates it directly into a physics-based numerical model. The principal scientific contribution of the study lies in the field-calibrated integration of equivalent seismic source reconstruction, actual production-blast geometry and initiation timing, three-dimensional dynamic FEM, and multi-domain model-performance evaluation within a unified physics-informed framework. The developed framework provides a physics-based computational foundation for blast-design evaluation, vibration-control planning, digital mining applications, and future AI-assisted blast-design optimization and adaptive vibration-control workflows.