A CFD analysis of natural and forced ventilation strategies for radon management in a uranium mine

Radon (²²²Rn) constitutes a primary source of public radiation exposure, posing significant health risks like lung cancer. This study investigates the dynamics of indoor radon accumulation and the effectiveness of mitigation strategies within the Laboratory of Natural Radiation (LNR), a unique facility situated in a former uranium mine in Saelices el Chico, Spain. We present a hybrid methodology that integrates experimental monitoring with high-fidelity Computational Fluid Dynamics (CFD) simulations, along with a high-precision reconstruction methodology.

Accurate risk assessment in complex terrains requires precise boundary conditions often missed by standard meteorological data. To overcome this, we utilized an automated CFD tool to reconstruct the surrounding topography and built environment, revealing discrepancies of up to 20% between raw regional meteorological records and the actual simulated wind fields affecting the site. These corrected parameters were used inside seasonal simulations of natural ventilation, which were compared against a forced ventilation scenario using an industrial fan.

The results demonstrate the critical limitations of passive strategies in poorly connected spaces. Under natural ventilation conditions across four seasons, air renewal rates remained critically low, ranging from 0.13 to 0.25 Air Changes per Hour (ACH). Consequently, simulated radon concentrations in the studied room consistently exceeded 10,000 Bq/m³. In contrast, the mechanical ventilation model, which showed strong agreement with experimental results, achieved up to 2.21 ACH. This active intervention successfully reduced radon levels to approximately 2,000 Bq/m³ within just one hour. These findings underscore the necessity of active decontamination strategies in high-hazard areas and demonstrate the value of detailed environmental reconstruction in predictive modeling for safer infrastructure designs.