The Seventh International Colloquium on Bluff Body Aerodynamics and Applications (BBAA7) Shanghai, China; September 2-6, 2012 Study on characteristics

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1 Study on characteristics of ore storage-pile fugitive-dust based on wind tunnel experiments Yonghua Xue a a Tianjin Research Institute for Water Transport Engineering of Ministry of Transport, 2618#, Xingang Road No.2, Tanggu, Binhai New Area, Tianjin, China ABSTRACT: Dust is the main pollution issue of the bulk port. This paper investigated characteristics of ore storage-pile fugitive-dust by means of wind tunnel experiments. Three typical ore, including Australia, Indian and Brazil ore, were selected, since these ore are common in ports. The proportion of model and corresponding boundary conditions was determined under wind tunnel parameters. Relationship between amount of dust and ore particle size distribution, startup wind velocity and mean wind velocity were investigated by regression analysis. Furthermore, difference on amount of dust between single-pile and multi-piles was also examined. The paper presents a mathematical model of ore dust and a new practical method for calculation of ore fugitive dust. KEYWORDS: Ore dust, Wind tunnel, Windblown particles, Regression analysis 1 INTRODUCTION Wind erosion is a major cause of particulate pollution in the yard of ports [1]. Recently, atmospheric dispersion of wind-blown dust particles from coal piles in the open storage yards has brought about severe air pollution and environmental problems due to fugitive dust emission. Therefore, it is of great importance to analyze the motion of wind-blown particles in order to develop effective means for controlling the particulate pollution. Studies have been carried out to investigate the mechanisms of wind-blown particles. Bagnold (1941) investigated the wind-induced sand movement in a Libyan desert [2]. Finney (1934) used wind tunnel simulations to investigate snowdrift phenomena [3]. Zingg (1952) investigated the movement of sedimentary materials and particle saltation by means of a wind tunnel test [4]. Coal pile has been the research focus of windblown particles regularity, while few model established for ore pile. There is considerable throughout of ore in most ports, which continued to grow rapidly. Since coal and ore are very different in particle size distribution, density and moisture content, the research on ore windblown particle regularity and the associated coefficient is very urgent. Wind-induced movement of small particles has been classified into three transport processes: saltation, suspension and surface creep [1]. Saltation is the primary wind erosion mechanism, referring to a bouncing motion of particles. In general, particles with diameters ranging from about 100 to 1000 μm are involved in the saltation process. These particles lift off the surface and travel in curved trajectories under the influence of wind and gravity. The particles engaged in saltation are sufficiently massive that air turbulence has little influence on their motion. The ballistice trajectory of particles undergoing this kind of motion is 5-10 times longer than the maximum height. Most mass transportation occurring near the ground surface is due to saltation [5]. 1692

2 The study carried out s series of wind tunnel experiments and the data collected were analyzed by mathematical methods. Particle size distribution, startup wind velocity, mean velocity and stacked pattern were discussed separately. 2 EXPERIMENTAL APPARATUS AND METHODS Experiments were performed in a opened blow-out boundary wind tunnel with a test section size of 4.4m (W) 2.5m (H) 15.0m (L). Wind tunnel fan speed is controlled in direct mode and the maximum wind speed is 30 m/s. Wind tunnel turbulence intensity is less than 1% and axial static pressure gradient (dp/dx) is less than 0.01m. Spires and roughness elements were installed along the span wise direction to creat a neutrally buoyant atmospheric boundary layer. 2.1 Similarity criteria Geometry similarity Geometry similarity is the basic condition of flow similarity. For the wind tunnel test, model scale is the ratio of corresponding length of several similar objects. According to the yard of the actual situation and the wind tunnel size, the model scale of experiment is 1:100. A schematic diagram of the wind tunnel test section is shown in figure 1(a) and size description of standard ore pile tested in experiments is shown in figure 1(b). U(z) W top =13 cm 45º h=6 cm W bottom =25 cm Figure 1(a). Schematic diagram of ore pile settings in the test section of wind tunnel W top =13 cm L top =38 cm h=6 cm W bottom =25 cm L bottom =50 cm Figure 1(b). Schematic diagram of standard single ore pile size. Long side of ore pile was set facing the wind stream in the wind tunnel test section in the single pile experiment. On the other hand, settings of ore piles in multi-pile experiments were similar to single pile, but in the 2 2 pattern. One or four Ore-pile were placed in the middle of test section of the wind tunnel. Atmospheric boundary layer similarity 1693

3 Artificial boundary layer was simulated by spires and roughness elements. Expression of the power functions of wind velocity profile deduced by near the ground and neutral stratification and underlying surface conditions as follows: u/u 1 =(z/z 1 ) m where u is the mean wind velocity (m/s), u 1 is the wind velocity (m/s) of height z 1 and m is a function of surface roughness and temperature stratification, which values depending on different regions and atmosphere stability. Renault similarity In addition to similarity of geometry and atmospheric boundary layer, Renault similarity is also an important prerequisite for the wind tunnel experiments. This study experimental wind velocity range of 4.5~12 m/s meets the Renault similarity requirements. 2.2 Experimental apparatus Ore size distributions were measured by sonic vibration of semi-automatic screening particle size analyzer. ESJ200-4A and YP 200K-1 electronic balance were employed to weight measurement. 2.3 Materials Three typical ore, including Australia ore, Indian ore and Brazil ore, were collected in port of Xiamen. All of ore samples were flattened and natural dried for 20 days in laboratory. Australia ore nature moisture content was 3.8%, while Brazil and Indian ores were 3.5% and 2.9%. Data of size distribution were acquired by particle size analyzer referred above. The size distribution of three ore type is illustrated in Figure 2. Figure 2. Size distributions of three typical ore Smaller size was observed in Australia and Brazil ore, while Indian ore dust particle size is larger. This may lead to different dust characteristic, including startup wind velocity and amount of windblown dust. Furthermore, finer particles were observed in Brazil ore samples than Australia ore. 1694

4 2.4 Particle startup wind velocity experiments Method for the determination of the startup wind velocity as follows: Ore powder with natural moisture was spread evenly on a sheet as much as possible to avoid surface wrinkles. Digital camera was mounted above the tested ore pile to monitor particle status. Start the wind tunnel, gradually increasing wind velocity and observe the movement of particles at the same time. The wind velocity was recorded when obvious particles movement was observed. Repeat this test process 5 times to acquire the mean startup velocity for each type of ore. The results of startup velocity are list in table 1. Table 1. Startup wind velocity for tested ore. Ore type Startup wind velocity (m/s) Australia 4.0 Brazil 4.6 Indian Windblown experiments Each of ore pile put in the wind tunnel for experiment was placed on a thin enough sheet, which weighted together with the ore pile both before and after test. Each test lasted 15 minutes. The test wind velocity (U) includes 4.5, 6, 8, 10 and 12 m/s. weight of ore blown off could be calculated by weight difference. 3 RESULTS AND DISCUSSION Figure2 shows the relationship between quantity of windblown dust and mean wind velocity, which obtained by regression analysis. With wind velocity increases, the quantity of windblown dust increases rapidly and then slowly. According to data collected in the wind tunnel experiments of three ores, quantity of windblown dust was deduced as follows: Q=A (U-U 0 ) 3 Where Q is the quantity of windblown dust, A is species coefficient, U is mean wind velocity during an experiment and U 0 is the startup wind velocity of corresponding species. The detailed values are shown in table 2 and the regression curves are illustrated in the figure 3. Table 2. Coefficient of quantity of windblown dust on mean velocity Coefficient Australia Ore Brazil Ore Indian Ore A U

5 Figure 3 (a). Quantity of windblown dust at various wind velocities for Australia ore. Figure 3 (b). Quantity of windblown dust at various wind velocities for Brazil ore. 1696

6 Figure 3 (c). Quantity of windblown dust at various wind velocities for Indian ore. In the case of ore natural moisture content, similar regularity of windblown dust was observed between Australia and Brazil ore. However, less dust blown off was observed in Indian ore experiment at lower velocity (< 8 m/s). This phenomenon may relate to greater particles than the other two ores. Figure 4. Quantity of windblown dust at various wind velocities for Australia ore. Figure 4 shows the curve regressed of multi-pile experiment. In this case, the coefficient A value is Contrast to single pile result, only 30% dust was blown off under the same conditions. The result indicated that less dust be blown off in the multi-pile pattern, which may be due to mutual shelter effect of the piles and then reduced wind velocity. 4 CONCLUSION In this paper, a preliminary study on windblown dust law of different ore was carried out by wind tunnel simulation. Quantity of windblown ore increases with increasing wind velocity, especially when the wind speed is greater than 8 m/s. Expressions were regressed by mathematical 1697

7 method, which could be used to estimate windblown dust. Because of shelter effect of piles between each other, the quantity of windblown dust of multi-pile is far less than single pile. REFERENCES 1 S.J. Lee, K.C. Park and C.W. Park, Wind tunnel observations about the shelter effect of porous fences on the sand particle movements, Atmospheric Environment, 36(2002), p R.A. Bagnold, The physics of blown sand and desert dunes. Mathuen, London, E.A. Finney, Snow control on the highway, Michigan Engineering Experiment Station (East Lansing), Bulletin No. 57, pp A.W. Zingg, Wind tunnel studies of the movement of sedimentary material. Proceedings of the Fifth Hydraulics Conferences, Vol.34, University of Iowa, pp R.J. Kind, Mechanics of Aeolian transport of snow and sand. Journal of Wind Engineering and Industrial Aerodynamics 36,