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This study evaluated the small-scale atmospheric dispersion performance of the Micro-SWIFT SPRAY (MSS) model and the GPU-accelerated QES model (GPU-QES) in the complex environment of a nuclear power plant site. Based on wind tunnel experimental data from the Sanmen Nuclear Power Plant, two typical wind direction dispersion scenarios were simulated by both models, and the results were compared in terms of wind field and concentration field predictions, including horizontal ground-level wind and concentration fields, as well as vertical wind speed and concentration profiles. The results indicated that GPU-QES outperformed MSS in wind speed prediction, especially in the areas between buildings, where the underestimation of wind speed is reduced by about 53%. Furthermore, GPU-QES simulated the three-dimensional wind field 450times faster than MSS, generating wind data over a 9km2 area with 35million grid points in just 4s. In plume dispersion prediction, high-concentration areas were effectively reproduced by both models, but GPU-QES showed higher consistency with actual values in low-concentration regions. Statistical analysis revealed that both models meet internationally accepted model criteria. However, higher simulation accuracy was demonstrated by GPU-QES in most metrics, especially in the building ground area, where the fraction of predictions within a factor of two of the observations (FAC2) was 4.5% higher than that of MSS. Additionally, due to differences in the dispersion behavior behind buildings between MSS and GPU-QES, simulation accuracy was improved by averaging the results of both models (FAC2reached 71.8%). On the other hand, due to differences in concentration calculation methods, GPU-QES generated the plume approximately 48times faster than MSS. Therefore, a clear advantage was shown by GPU-QES over MSS in nuclear emergency response scenarios that required rapid and accurate predictions.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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