National Taiwan Ocean University, Keelung 202, Taiwan, R.O.C. 2 Master, Department of Harbor and River Engineering,

Transcription

1 Measurement on the Flow and Dispersion of Two Identical Sources in Side-by-Side Discharging over Journal of Coastal and Ocean Engineering, Vol. 16, No. 2, Aligned pp Array (2016) Configuration of Cube in a Turbulent Boundary Layer DOI: /JCOE Measurement on the Flow and Dispersion of Two Identical Sources in Side-by-Side Discharging over Aligned Array Configuration of Cube in a Turbulent Boundary Layer Bao-Shi Shiau 1* Yen-Shih Tseng 2 1 Professor, Department of Harbor and River Engineering, National Taiwan Ocean University, Keelung 202, Taiwan, R.O.C. 2 Master, Department of Harbor and River Engineering, National Taiwan Ocean University, Keelung 202, Taiwan, R.O.C. ABSTRACT This study employed the environmental wind tunnel to investigate the flow and dispersion characteristics of two identical sources in side-by-side discharging over arrays of cube with sparse and dense density. Two identical sources in side-by-side were set apart with different gaps. Mean velocity profiles and turbulence intensity profiles of canopy flows above the array of cube are measured, and it is presented to show the variations for arrays of cube with sparse and dense densities. The measured vertical dispersion parameter is shown to increase with further downstream from the sources. When the deployment of arrays of cube in the downstream of sources changed from sparse density to dense density, the vertical dispersion parameter is found to be larger. After two plumes merged together, averaged height of merged plume increases along with the downstream distance of sources. Analysis of measured concentration profiles reveals that averaged height of the merged plume becomes higher when deployment of arrays of cube downstream of the sources varies from sparse density to dense density. Key words: dispersion, turbulent boundary layer, aligned array of cube, canopy flow, two sources in side-byside. * Corresponding author, bsshiau@gate.sinica.edu.tw Journal of Coastal and Ocean Engineering, Vol. 16, No. 2 (2016) 55

2 Bao-Shi 海洋工程學刊 Shiau 第十六卷 Yen-Shih 第二期 Tseng (2016), 第 頁 DOI: /JCOE 左右兩相鄰排放源排放於規則方塊排列之延散量測研究 1 2 蕭葆羲 1* 曾彥士 國立臺灣海洋大學河海工程學系教授國立臺灣海洋大學河海工程學系碩士 2 摘 要 本文應用風洞模擬都市型中性大氣邊界層流, 量測分析探討在左右相鄰兩排放源排放於下游規則方塊排列之擴散特性 實驗之濃度擴散特性結果, 其與高斯擴散理論公式比較, 二者吻合 當兩排放源形成之雙羽昇流延著下游距離逐漸混合為一, 此羽昇流平均高度將隨下游距離之增加而變高 又規則方塊排列之密度變大時, 羽昇流之平均高度也隨之增高 關鍵詞 : 延散 紊流邊界層 規則方塊排列 頂蓬流 左右相鄰兩排放源 * 通訊作者 bsshiau@gate.sinica.edu.tw 56 Journal of Coastal and Ocean Engineering, Vol. 16, No. 2 (2016)

3 Measurement on the Flow and Dispersion of Two Identical Sources in Side-by-Side Discharging over Aligned Array Configuration of Cube in a Turbulent Boundary Layer 1. INTRODUCTION Many industrial parks are located at the coastal region in Taiwan. Chimneys allocated apart with different gaps had existed in the industrial parks. Two stacks in side-by-side forming pollution plume dispersing through obstacles often encountered in the industrial complex, or near-by urban or country region. This is one of key topics of environmental wind engineering in the atmospheric turbulent boundary layer. It is interesting for basic research of pollution dispersion, and it is also worth for environmental wind engineering application study. Relevant literature on such problems, such as: Mfula et al. (2005) used wind tunnel to model the urban building exposure to outdoor pollution. They investigated the effects of area density of array on the magnitude and spatial distribution in concentrations on the test building. Davidson et al. (1995) had made field investigation the plume dispersion through large groups of obstacles. The plume was released below the height of the obstacle array, and a second control plume was released alongside the array. Hanna et al. (2002) studied the comparison of 3-D numerical model simulations with observations of mean flow and turbulence within simple obstacle arrays of sparse and dense density. Frank and Ruck (2005) studied experimentally for the influence of porosity on wind reduction between doublearranged mound-mounted shelterbelts. Contini and Robins (2004) studied the rise and mixing of plume from two identical sources in neutral cross flow in flat terrain. They investigated the details of interaction between two rising buoyant plumes with separation 12D and 22D, where D is the diameter of plume discharge. Gailis and Hill (2006) conducted wind tunnel experiments on the single source plume dispersion within a large array of obstacles. Their emphasis is mainly placed on the description and mathematical modeling of concentration fluctuations within the plume. Shiau and Lin (2007) employed wind tunnel to study the pollution dispersion in urban environment for different wind directions. They set one source upstream the array of cube. Wang et al. (2009) studied numerically the dispersing of a passive scalar released from an instantaneous point source in a buit-up (urban) environment. Schatzmann and Leitl (2011) reported issues and validation of urban flow and dispersion computational fluid models. In summary of the above relevant literature, study on two side-by-side stacks plumes dispersing through the sparse and dense density of aligned array configuration of cube seems insufficiently. In order to understand more on the dispersion of plume under such conditions, the main purpose of present study is to measure in the wind tunnel on the flow and dispersion characteristics of concentration plume discharging from two identical sources over sparse and dense arrays of cube in the turbulent boundary layer flow. 2. EXPERIMENTAL SET-UP The experimental measurements were carried out in the National Taiwan Ocean University s Environmental Wind Tunnel Laboratory. The wind tunnel test section has a cross section of 2 m wide by 1.4 m height, and 12.5 m long. The tunnel is an open suction type and it contracts to the test section with an area ratio of 4:1. The turbulence intensity of empty tunnel in test section is less than 0.5 % at the mean velocity of 5 m/s. An X-type hot-wire incorporating with the TSI IFA- 300 constant temperature anemometer was employed to measure the turbulent flow signals. Output of the analog signals for turbulent flow was digitized through the 12 bit Analog-to-Digital converter. Since none of the analog signals containing significant energy or noise above 1 khz, with the Nyquist criteria, a digitizing rate of 2 khz was sufficient. The low pass frequency for the analog signals is set as 1 khz in all runs of the experiments. Four spires of 100 cm height are equally spaced and properly arranged at the entrance of test section, and roughness elements succeeded to be arranged 9 m long to ensure generation of a fully developed turbulent boundary layer which was used as the approaching flow. A model scale 1:400 was used to simulate the neutral atmospheric turbulent boundary layer flow. The boundary layer thickness generated in the wind tunnel is about 100 cm. The free stream velocity is about 5.33 m/s. The Reynolds number of the approaching flow is therefore ~105, which is greater than the critical Reynolds number ~104. The threshold Reynolds number assured the flow similarity between wind tunnel model and atmospheric prototype according to the Reynolds Journal of Coastal and Ocean Engineering, Vol. 16, No. 2 (2016) 57

4 Bao-Shi Shiau Yen-Shih Tseng number independence or Reynolds number similarity (Towsend, 1956). The cubic element model was with the size of length L = 5 cm, width W = 5 cm, and height H = 5 cm. Cubic element models arranged in line with different gaps S = 1.5 H, and S = 0.5 H (which corresponded to arrays of cube with dense density d = 44% and sparse density d = 16%. Refer to Fig. 1) were adopted in the present experiment. This is to ensure two different flow regimes. Here the density, d is calculated in accordance with Hanna et al. (2002): d = HW (S + W) (1) The flow regime of sparse density of cube arrays (d = 16%) is wake interference flow, and dense density of cube arrays (d = 44%) is skimming flow (Hunter et al., ). Two identical sources with height of two times of cubic element height were set at a distance of three times of cubic element height before the first array of elements. Fig. 1 showed the schematic diagram of the cubic model arrangement. To avoid the downwash of the plume, the stack height was set 2H. And to ensure the plumes through the array of cube, sources were placed at upstream 3H of first array of cube. The intervals between the two side by side sources are 9D and 18D. Here D is the source diameter. Selection of two stacks spacing of 9D and 18 D is to avoid the nearby vortices in the merging plume oppose on another (Macdonald et al., 2002). Tracer gas was applied to use as the concentration indicator. The tracer gas was a mixture of volume ratio of 1:9 for methane and standard gas. The mixed gas emitted from the two stacks as the sources in the experiments. So tracer gas was slightly lighter than the ambient environment of air. The momentum buoyant plume of discharge is controlled by the densimetric Froude number, Fr, and it is defined as: Fig. 1. Schematic diagram of cubic elements arrangement. (2) where U s is the discharged velocity of tracer gas; g is the gravity; g is the gravitational acceleration; D is the diameter of stack; ρ s is the density of tracer gas; ρ a is the density of ambient air. In present study, the discharging condition for tracer gas emitted from the stack in all runs 58 Journal of Coastal and Ocean Engineering, Vol. 16, No. 2 (2016)

5 Measurement on the Flow and Dispersion of Two Identical Sources in Side-by-Side Discharging over Aligned Array Configuration of Cube in a Turbulent Boundary Layer of experiment was Fr = 50; where U s = 2.22 m/s, g = 9.81 m/s 2, D = m, ρ s = kg/m 3, ρ a = kg/m 3. The designed rake of sampling tubes was employed to take tracer gas samples. The rake was composed of many tubes. A cam system was applied to accomplish the work of pumping tracer gas. The system was performed to suck simultaneously the tracer gas through many tubes mounted on the rake, and the sampled tracer gas for each tube was connected to a corresponding airbag with size of three liters. The sucking time was three minutes in each run. The collected tracer gas in airbag was analyzed with FID (Flame Ionization Detector). The methane contained in the sampled tracer gas was quickly burned and detected by the FID, and the concentration of the sample was yielded. 3. RESULTS AND DISCUSSION 3.1 Simulation of approaching flow A thick turbulent boundary layer flow was generated as the approaching flow. The simulated mean velocity and turbulence intensity profiles of approaching flow are show in Fig. 2(a) and Fig. 2(b). The boundary layer thickness Z ref is about 100 cm, and free stream velocity U ref = 5.33 m/s. Fig. 2(a) shows the mean velocity profile of the turbulent boundary layer flow which is fitted as the power law form shown as Eq. (3) with an exponent n = U(Z) U zef = ( Z Z ref ) n (3) where U(Z) is the mean velocity at the height of Z. The value of power exponent of mean velocity profile falls in the range of 0.23 n 0.4 which is the field measurement result of urban terrain of neutral atmospheric turbulent boundary layer proposed by Counihan (1975). The longitudinal turbulence intensity used in the present study is defined as: TI u (%) = u 2 /U 100% (4) Where u 2 is the root mean square of turbulent velocity; U is the local mean velocity. Fig. 2(b) shows the simulated longitudinal turbulence intensity profile of approaching flow in wind tunnel. The longitudinal turbulence intensity of approaching flow close to the ground shown in Fig. 2(b) is about 22 %. This value falls in the range 0.2 u 2 /U 0.35 which is for urban terrain of neutral atmospheric turbulent boundary layer as proposed by Counihan (1975) Mean Velocity Profile = experimental data n = Turbulence intensity = experimental data Z/Zref Z/Zref U/Uref (a) Tlu (%) (b) 24 Fig. 2. Approaching flow; (a) mean velocity profile; (b) longitudinal turbulence intensity profile. Journal of Coastal and Ocean Engineering, Vol. 16, No. 2 (2016) 59

6 Bao-Shi Shiau Yen-Shih Tseng 3.2 Canopy flow of arrays of cube The flows above the canopy of the arrays of cube for flat terrain and sparse or dense arrangements of arrays of cube were measured and compared. For the case of flat terrain, i.e., without arrays of cube deployed on the surface, we define the density as 0%. The mean velocity profiles for flat terrain (density d = 0%) and arrays of cube with sparse density d = 16% along the downstream of source are show in Fig. 3. In the figure, U H is the mean velocity at the height of H in the upstream of flow, and it is used as velocity scale. As comparing the mean velocities above the canopy of cubic element along the downstream distance, it is found that the mean velocities of canopy decrease when the terrain is with sparse arrays of cube of density d = 16%. The mean velocity profiles along the downstream distance of source above the canopy of arrays of cube with sparse density (d = 16%) and dense density (d = 44%) are shown in Fig. 4. The results reveal that at farther downstream distances, the mean velocity profiles above the canopy of cube for sparse density (d = 16%) and dense density (d = 44%) are of no significant difference. But at nearer downstream distances (like St1, St2, St3), the mean velocity profiles above the canopy of cube for sparse density (d = 16%) are slightly smaller than that of for dense density (d = 44%). Fig. 5 is the turbulence intensity profiles along the downstream distance of source above the canopy of arrays of cube with sparse density (d = 16%) and dense density (d = 44%). At farther downstream distance, the turbulence intensity profiles of the canopy for sparse density (d = 16%) and dense density (d = 44%) seems of no significance. But at nearer downstream distances (like St1, St2, St3), the turbulence intensity profiles above the canopy of cube for sparse density (d = 16%) are larger than that of for dense density (d = 44%). The flow regime of sparse density of cube arrays (d = 16%) is wake interference flow, and dense density of cube arrays (d = 44%) is skimming flow (Hunter et al., ). The wake interference flow disturbs flow more than skimming flow does. Numerical flow simulation by Yang and Shao (2008) obtained similar results. Sparse density induces larger turbulence intensity than dense density. The large eddy simulation (LES) numerical technique calculation results of turbulence intensity above canopy of array of cube for sparse density (d = 16%) and dense density (d = 44%) by Hannna et al. (2002) also obtained the result of tendency of sparse density case has larger turbulence intensity than the dense case. Fig. 3. The mean velocity profiles for flat terrain (density d = 0%) and arrays of cube arranged with sparse density (d = 16%) along the downstream of source. 60 Journal of Coastal and Ocean Engineering, Vol. 16, No. 2 (2016)

7 Measurement on the Flow and Dispersion of Two Identical Sources in Side-by-Side Discharging over Aligned Array Configuration of Cube in a Turbulent Boundary Layer Fig. 4. Comparison of mean velocity profiles of canopy flow for arrays of cube with sparse density (d = 16%) and dense density (d = 44%). Fig. 5. Comparison of turbulence intensity profiles of canopy flow for arrays of cube arranged with sparse density (d = 16%) and dense density (d = 44%). 3.3 Concentration distribution and dispersion parameters For analysis of the concentration distributions and dispersion parameter, the dimensionless concentration, K is used, which is obtained from scaling the measured concentration C by the cubic structure height H, source emission discharge rate Q, and mean wind speed at the height H upstream of the sources U H. So the dimensionless concentration, K is shown as follows: Journal of Coastal and Ocean Engineering, Vol. 16, No. 2 (2016) 61

8 Bao-Shi Shiau Yen-Shih Tseng CH 2 U K = H (5) Q To validate the concentration measurements, we compared the measured plume concentration profiles with the calculated results of Gaussian dispersion equation in the flat terrain. The equation is shown as follows: (6) where C maxz is the plume centerline concentration, σ z is the vertical dispersion parameter, and Z c is the plume averaged height. σ z and Z c are defined as follows: (7) (8) Fig. 6(a) and Fig. 6(b) show the comparison of the measured vertical concentration profiles along the plume center in the downstream distances with that of the calculated results of Gaussian reflected formula in the flat terrain for gaps between two sources of 9D, and 18D, respectively. Here D is the diameter of source discharge. Results exhibit that the measured results are found in good agreement with calculations of theoretical formula. Two side-by-side sources plume horizontal concentration profiles for the source separated gaps 9D and 18D for arrays of cube with sparse density 16% are shown as Fig. 7(a) and Fig. 7(b), respectively. The concentration profiles are found close to the Gaussian profile. Fig. 8(a) and Fig. 8(b) show the two side-by-side sources plume horizontal concentration profiles with arrays of cube with dense density 44% for the sources gaps 9D and 18D, respectively. Results of concentration profiles shown in the figures are found close to the Gaussian profile. The vertical dispersion parameter σ z (sigma Z) was obtained by calculating the standard deviation of the concentration distributions in vertical directions. This parameter can be used as the indicator for the extent of (a) (b) Fig. 6. Comparisons of measured concentration profiles in the downwind distance of sources for flat terrain with that of calculations of theoretical Gaussian plume model in the flat terrain; (a) gap between two sources: 9D; (b) gap between two sources: 18D. 62 Journal of Coastal and Ocean Engineering, Vol. 16, No. 2 (2016)

9 Measurement on the Flow and Dispersion of Two Identical Sources in Side-by-Side Discharging over Aligned Array Configuration of Cube in a Turbulent Boundary Layer (a) (a) (b) Fig. 7. The two side-by-side sources plume horizontal concentration profiles at different downstream distances for array of cube with density 16%; (a) gap between two sources: 9D; (b) gap between two sources: 18D. (b) Fig. 8. The two side-by-side sources plume horizontal concentration profiles at different downstream distance for array of cube with density 44%; (a) gap between two sources: 9D; (b) gap between two sources: 18D. concentration plume spread in the vertical direction. The plume averaged height was defined as the centroid of the concentration profile. Fig. 9 shows the vertical dispersion parameter as the function of downstream distance for arrays of cube with sparse density (d = 16%) and dense density (d = 44%) for the two sources gap of 9D. Results reveal that the dispersion parameter in vertical direction σ z increases along with the downstream distance of sources X. The relation between σ z /H and X/H can be fitted as the power law equation as follows: σ z H = ( X H )α (9) where power exponent α depends on the density of arrays of cube. Journal of Coastal and Ocean Engineering, Vol. 16, No. 2 (2016) 63

10 Bao-Shi Shiau Yen-Shih Tseng It also shows that along with the downstream distance of sources, the vertical dispersion parameter σ z becomes larger when terrain condition downstream of the sources change form flat terrain (d = 0%) to arrays of cube with dense density (d = 44%). This implies that array of cube in the downstream of sources is favor of dispersion. Similar results of the relation between the vertical dispersion parameter and density of arrays of cube are also obtained for the case of two sources gap of 18D. Fig. 10. Plume averaged height as the functions of downstream distance for different densities of arrays of cube; two sources gap of 9D. 4. CONCLUDING REMARKS Fig. 9. Dispersion parameter as the functions of downstream distance for different densities of cubic structures arrangement; source separated gap 9D. The plume averaged height as the function of downstream distance for different densities of arrays of cube for two sources gap of 9D are presented in Fig. 10. In the figure, it is shown that after two plumes merged together, the merged plume averaged height increased along with the downstream distance of sources. As increasing the density of arrays of cube from flat terrain (d = 0%) to dense density (d = 44%), the plume averaged height increases. This indicates that existence of array of cube would be helpful for the dispersion of pollution plume. For the case of two sources gap of 18D, similar results of the averaged height as the function of downstream distance for different densities of arrays of cube are also obtained. The effect of density of arrays of cube on the variation of plume averaged height is also the same as the case of two sources gap of 9D. This study employed the environmental wind tunnel to measure the flow and dispersion characteristics for two identical sources side-by-side with different separated gaps which were discharged into arrays of cube deployed with sparse density (d = 16%) and dense density (d = 44%). In summary of the measured results of flow and plume concentration, concluding remarks are made as follows: (1) At nearer downstream distances of sources (like St1, St2, St3), the turbulence intensity profiles above the canopy of array of cube for sparse density (d = 16%) are larger than that of for dense density (d = 44%). Sparse density induces larger turbulence intensity than dense density. (2) The vertical dispersion parameter is found to increase when terrain condition of downstream the sources changed from flat terrain density (d = 0%) to that of sparse density (d = 44%). (3) When two identical concentration plumes merge together, averaged height of the merged plume increases along with the downstream distance of source. Averaged height of merged plume is higher as the density of arrays of cube changes from sparse density (16 %) to dense density (44%). 64 Journal of Coastal and Ocean Engineering, Vol. 16, No. 2 (2016)

11 Measurement on the Flow and Dispersion of Two Identical Sources in Side-by-Side Discharging over Aligned Array Configuration of Cube in a Turbulent Boundary Layer REFERENCES Counihan, J. (1975) Adiabatic atmospheric boundary layer: a review and analysis of data from the period , Atmospheric Environment, Vol. 9, pp Contini, D. and Robins, A. (2004) Experiments on the rise and mixing in neutral crossflow of plume from two identical sources for different wind directions, Atmospheric Environment, Vol. 38, pp Davidson, M. J., Mylne, K. R., Jones, C. D., Philips, J. C., Perkins, R. J., Fung, J. C. H. and Hunt, J. C. R. (1995) Plume dispersion through large group of obstacles -- a field investigation, Atmospheric Environment, Vol. 29, pp Frank, C. and Ruck, B. (2005) Double-arranged mound-mounted shelterbelts: inf luence of porosity on wind reduction between shelterbelts, Environmental Fluid Mechanics, Vol. 5, pp Gallis, R. M. and Hill, A. (2006) A wind tunnel simulation of plume dispersion within a large array of obstacles, Boundary Layer Meteorology, Vol. 119, pp Hanna, S. R., Tehranian, S., Carissimo, B., Macdonald, R. W. and Lohner, R. (2002) Comparison of model simulations with observations of mean flow and turbulence within simple obstacle rrays, Atmospheric Environment, Vol. 36, pp Hunter, L. J., Watson, I. D. and Johnson, G. T. ( ) Modeling air f low regimes in urban canyons, Energy Buildings, Vol. 15, pp Macdonald R. W., Strom, R. K. and Slawson, P. R. (2002) Water flume study of the enhancement of buoyant rise in pairs of merging plumes, Atmospheric Environment, Vol. 36, pp Mfula, A. M., Kukadia, V., Griffiths, R. F. and Hall, D. J. (2005) Wind tunnel modeling of urban building exposure to outdoor pollution, Atmospheric Environment, Vol. 39, pp Schatzmann, M. and Leitl, B. (2011) Issues with validation of urban flow and dispersion CFD models, Journal of Wind Engineering and Industrial Aerodynamics, Vol. 99, pp Shiau, B. S. and Lin, Y. S. (2007) Measurement on the dispersion of pollution in urban environment of cubic building arrays with different wind directions, Proceedings of the International Workshop on Physical Modeling of Flow and Dispersion Phenomenon, Orleans, France, pp Towsend, A. A. (1956) The Structure of Turbulent Shear Flow, Cambridge University Press, UK. Wang, B.-C., Yee, E. and Lien, F.-S. (2009) Numerical study of dispersing pollutant clouds in a buit-up environment, International Journal of Heat and Fluid Flow, Vol. 30, pp Yang, Y. and Shao, Y. (2008) Numerical simulation of f low and pollution dispersion in urban atmospheric boundary layer, Environmental Modelling and Software, Vol. 23, pp Manuscript Received: Mar. 3, 2016 Revision Received: Jun. 7, 2016 and Accepted: J u l. 18, 2016 Journal of Coastal and Ocean Engineering, Vol. 16, No. 2 (2016) 65

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