The three-dimensional wind velocity and dynamic pressure for stationary tornado-like vortices that developed over ground of different roughness categories were investigated to clarify the effects of ground roughness. Measurements were performed for various roughness categories and two swirl ratios. Variations of the vertical and horizontal distributions of velocity and pressure with roughness are presented, with the results showing that the tangential, radial, and axial velocity components increase inside the vortex core near the ground under rough surface conditions. Meanwhile, clearly decreased tangential components are found outside the core radius at low elevations. The high axial velocity inside the vortex core over rough ground surface indicates that roughness produces an effect similar to a reduced swirl ratio. In addition, the pressure drop accompanying a tornado is more significant at elevations closer to the ground under rough compared with smooth surface conditions. We show that the variations of the flow characteristics with roughness are dependent on the vortex-generating mechanism, indicating the need for appropriate modelling of tornado-like vortices. 相似文献
Mining-induced tremors are indispensable events that gestate and trigger coal bursts. The radiated energy is usually considered a key index to assess coal burst risk of seismic events. This paper presents a model to assess coal burst risk of seismic events based on multiple seismic source parameters. By considering the distribution and relation laws of the seismic source parameters of coal bursts, the model aims to identify dangerous seismic events that more closely match the characteristics of multiple seismic source parameters of coal bursts. The new coal burst risk index T is proposed. It consists of the similarity index SI (representing the similarity degree of relations between seismic events and coal burst events based on seismic source parameters) and the strength index ST (representing the burst strength of seismic events). We studied 79 coal burst events that occurred during extraction in LW250105 of the Huating coal mine in Gansu Province, China. We obtained the distribution and relation laws of multiple seismic source parameters of coal burst events to establish SI and ST. Two groups of seismic events with different energy distributions were examined to compare the assessment results based on the new model and energy criteria. The results show that 80% and 89% of seismic events with strong coal burst risk in Groups A and B, respectively, were coincident, and the seismic events with medium coal burst risk were slightly less compared to those based on radiated energy. The results indicate that the assessment based on the T value is a modification and optimization of that based on radiated energy. This model is conducive to improving the efficiency of monitoring and early warning of coal burst risk.
The Qinghai-Tibet Plateau is the world’s highest and largest plateau. Due to increasing demands for environment exploration and tourism, a large transitional area is required for altitude adaptation. Hehuang valley, which locates in the transition zone between the Loess Plateau and the Qinghai-Tibet Plateau, has convenient transportation and relatively low elevation. Our question is whether the geographic conditions here are appropriate for adapted stay before going into the Qinghai-Tibet Plateau. Therefore, in this study, we examined the potential use of ecological niche modeling (ENM) for mapping current and potential distribution patterns of human settlements. We chose the Maximum Entropy Method (Maxent), an ENM which integrates climate, remote sensing and geographical data, to model distributions and assess land suitability for transition areas. After preprocessing and selection, the correlation between variables and spatial autocorrelation input data were removed and 106 occurrence points and 9 environmental layers were determined as the model inputs. The threshold-independent model performance was reasonable according to 10 times model running, with the area under the curve (AUC) values being 0.917 ± 0.01, and 0.923 ± 0.002 for test data. Cohen’s kappa coefficient of model performance was 0.848. Results showed that 82.22% of the study extent was not suitable for human settlement. Of the remaining areas, highly suitable areas accounted for 1.19%, moderately for 5.3% and marginally for 11.28%. These suitable areas totaled 418.79 km2, and 86.25% of the sample data was identified in the different gradient of suitable area. The decisive environmental factors were slope and two climate variables: mean diurnal temperature range and temperature seasonality. Our model showed a good performance in mapping and assessing human settlements. This study provides the first predicted potential habitat distribution map for human settlement in Ledu County, which could also help in land use management. 相似文献
