| China's western region is located in the hinterland of Eurasia, where the environment was generally affected by Mongolian cold high pressure and Siberia anticyclone. It is cold, dry, windy and long in winter, and the snow cover period there is also long. Wind and snow disasters often appear on the roads in China's western region. Snow walls were commonly used as a kind of control technique to prevent snow airflow disaster of the road. Systematic researches were insufficient on the action principle and offects of each type of snow wall. In order to research the variation of airflow fields of snow walls, snowing process and response relationship between airflow and snowing process effected by multi-factors, in this study,24snow wall experimental combination types were designed and were smulated by particle image velocimetry (PIV) system and wind tunnel, including2height types ((?)=30mm,40mm),4kinds of porosity (η=0.00,0.30,0.40,0.50) and3groups of wind angle (8=90°,60°,30°) and were simulated by particle image velocimetry (PIV) system and wind tunnel.(1) When airflow affected the snow wall with different wind directions(δ), The move path of airflow around the snow walls with different experimental combination types of airflow showed different differentiation regularities. Airflow movement paths of different models were divided into3Parts, one part moved along the surface layer, the other became lifting or boosting airflow, and the third part was the upper turbulent airflow. This kind of differentiation regularities vanished with the decline of angle of wind direction. With the same snow height(H) and porosity(r)), reverse flow vortex area appeared both on the windward and leeward side. With the increase of the angle of wind direction and snow walls, and the decline of distance between reverse vortex position and snow wall, the airflow rate, airflow frequency and vortex scale of the center of leeward increased. In the horizontal direction of snow walls windward side, airflow speed up rate (S) and horizontal distance (H) accorded with polynomial function relation. In the vertical direction, airflow speed up rate and vertical distance accorded with positive index function correlation. But as the wind angle decreased, it no longer followed the two kinds of the rule above. At the leeward side of the snow wall, the phenomenon of reattachment appeared in different position after airflow separated. When airflow angle was90°, reattachment distances of different modeling combination were0.7h,1.3h,2.3h and4.3h respectively. They were0.3h,1h,2.6h and3.3h when airflow angle was60°,When airflow angle was30°, airflow reduced on the leeward side, and the surface was not attached by airflow.(2) It indicates that porosity of different modeling combinations had effect on airflow around snow wall. In the same conditions (H,δ), with the porosity (η) increases, horizontal airflow acceleration effect on the windward side and secondary airflow frequency decreases gradually in the horizontal direction. However, the opposite phenomenon appeared on the leeward side. Meanwhile, in the vertical direction, the upper (2h) and below airflow have a significant effect on snow wall model, Snow wall (η=0.00) model of the horizontal airflow around the model change is most complex. A multiple secondary airflow was formed both on the windward and leeward side. With the porosity increased, the airflow curve changed relatively flatting. In the same conditions (H,δ), with the decrease of wind angle, horizontal airflow speed decreased on the windward side and secondary airflow frequency increased gradually. The porosity played an important role in airflow acceleration, and deceleration on the windward side, and airflow separation and reattachment on the leeward side.(3) It shows that the different heights of snow wall (30mm/40mm) influenced the airflow. In the same conditions (ηδ,), airflow movement process was similar between different modeling combinations. Due to the wall height, with the increase of the snow wall height, the reverse airflow frequency rising on the windward side increased, but more significant deceleration on the leeward side was performed. The reattachment distance decreased while reattachment process followed with snow wall rule of30mm.(4) Different modeling combinations of snow wall influenced accumulation process of snow. In the same conditions (H, η), with the wind angle decreases, the length (L) of snow and snow thickness (D) constantly decreased on the windward side, the snow width (W) will increase. While on leeward side was contrary. Snow accumulation section line analysis demonstrates that the snow accumulation thickness (D) and horizontal distance (H) accorded with polynomial function in the windward side, while with linear negative correlation in leeward side. These two kinds of relations were not obvious and the curve becomes gentle with the increase of porosity and the decrease of angle. Comprehensive analysis shows that the various combinations of snow wall model of snow volume (Q) is maximum changes to the η=0.30.(5) The influencing factors of snow were simplified using SPSS software. Snow wall windward and leeward side snow volume (Q) was as the dependent variable. Snow wall space structure factors (porosity, angle), synthesis air flow velocity (VU) and L, W, D were as the variable. The trend surface response model that snow wall accumulated snow on the windward and leeward side was followed: Q迎=A1+B1η1+C1δ1+D1VU1-E1η12-F1δ1η1+G1δ12+H1VU1η1-I1VU1δ+J1VU12Q背=A2-B2η2+C2δ2-D2VU2-E2η22+F2δ2η2+G2δ22+H2VU2η2-12VU2δ+J2VU22(6) Combined with PIV experimental results and wind tunnel test data, the FUZZY snow ability evaluation model was set up. The results shows that, different models of snow wall snow capacity index was H30=(0.662,0.742,0.670,0.482,0.484,0.583,0.447,0.378,0.398,0.391,0.380,0.232), and H40=(0.598,0.769,0.696,0.522,0.439,0.506,0.508,0.423,0.308,0.385,0.328,0.295). Both combined model appeared optimal ability at porosity of the η=0.30,8=90°of snow angle, and the snow wall snow capacity index of40mm was greater than that of30mm. |
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