Validation and sensitivity analysis of GPU-accelerated QES against wind tunnel experiments for air dispersion modeling under complex terrain and dense building at an AP1000 NPP site

Accurate air dispersion modeling can effectively support nuclear accident emergency decision-making and emergency planning zone (EPZ) optimization to improve the safety and economic efficiency of advanced nuclear power plants (NPPs). However, it faces the challenge of fast and detailed air dispersion modeling under heterogeneous terrain and dense building environments. This study presents the GPU-accelerated Quick Environmental Simulation (QES) system for high-resolution wind and concentration modeling within complex AP1000 NPP Scenarios and validates it against two wind tunnel experiments, evaluating wind direction, speed, and pollutant concentration in both horizontal and vertical profiles. The GPU-QES successfully simulated wind field with building effect over a 9 km2 domain with 35 million grids in just 4 seconds. Over 50% of wind and concentration simulations are within a factor of two of the measurements. At the site boundary, the GPU-QES is only 15% lower than the measurements and is 84.12% lower than the straight-line Gaussian plume model used in EPZ determination, proving GPU-QES’s potential in optimizing the EPZ for AP1000 NPPs. Sensitivity analyses suggest the optimal parameters: global memory solver, released particles per second of 200, non-local-mixing coefficient of 0.3 m2/s2, and grid size of 5 m both horizontally and vertically in similar scenarios.