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1、Numerical study on particle removal performance of pickup head for a street vacuum sweeperSim-Lin Lau, Michael K. Stenstrom*Department of Civil and Environmental Engineering, 5714 Boelter Hall, University of California a

2、t Los Angeles, Los Angeles, CA 90095, USAa b s t r a c t a r t i c l e i n f oArticle history:Received 24 August 2009Received in revised form 27 January 2010Accepted 1 February 2010Available online 10 February 2010Keywor

3、ds:Pickup headParticle removal performanceCFDSweeper-traveling speedPressure dropThe purpose of this paper is to investigate the particle removal performance of pickup head for a streetvacuum sweeper numerically. An inte

4、grated 3D numerical model was constructed based on particle suctionprocess in computational fluid dynamics (CFD) software. The airflow through the pickup head was treated asa continuum, while particles were modeled as di

5、spersed phase. The Reynolds stress model (RSM) anddiscrete particle model (DPM) were chosen in order to predict the air and particles flow accurately. Thenumerical simulation results show that the sweeper-traveling speed

6、 and the pressure drop across the pickuphead have great effects on the particle removal performance. The removal efficiency of particles increaseswith the lower sweeper-traveling speed or the higher pressure drop, and sm

7、all size particles have highergrade efficiency than that of large size particles under the same operating conditions. Moreover, the removalmass flow rate of particles increases with the higher sweeper-traveling speed. Th

8、erefore, a trade-off shouldbe considered among high removal efficiency, low energy consumption, and high removal mass flow rate.Through the numerical simulation, the effectiveness of street vacuum sweeper for removing pa

9、rticles fromroad surface is evaluated, and an optimal operating condition is obtained. Besides, more information isgenerated to better understand the particle suction process of the pickup head.© 2010 Elsevier B.V.

10、All rights reserved.1. IntroductionCurrently, there is a widespread concern over the pollution ofparticle matter. Dust and silt are the major sources of particle matterpollution, the removal of which therefore attracts c

11、onsiderable at-tention [1]. Street sweeping is typically practiced to remove the ac-cumulation of dust and silt from road surface to improve aesthetics,public healthy, and storm water quality, so it is considered as anef

12、fective pollutant control practice for many local authorities [2,3].Pickup head is the key component of street vacuum sweeper, which isdesigned to pick up particles efficiently from road surface and sendthem to dust coll

13、ection hopper smoothly. The particle removal per-formance of the pickup head is the most important index for a streetvacuum sweeper.Many researches have been performed on estimating the particleremoval performance of str

14、eet sweeping. For example, a study byChang et al. [4] evaluated the effectiveness of street sweeping andwashing for controlling ambient total suspended particles by experi-ments, which indicated that the street sweeping

15、and washing processwas effective at removing dust and silt from urban roads. However,some researchers such as Vaze and Chiew [5] considered that thecontribution of street sweeping to environmental quality was not verycle

16、ar, and may have an adverse impact because street sweepers didnot pick up smaller size particles effectively. Kang and Stenstorm [6]studied the street sweeping effectiveness as a stormwater manage-ment practice by using

17、statistical power analysis. They pointed outthat the effect of street sweeping should not be underestimatedbecause some previous researches were based on insufficient data.Therefore, new methods were needed to evaluate t

18、he street sweepingeffectiveness.As the particle removal performance for street vacuum sweepervaries based on sweeping technology, operating conditions, sweepingfrequency, street dirt loading and particle size distributio

19、n [7], it isnecessary to develop a repeatable and reliable method to calculatethe particle removal performance of pickup head for a street vacuumsweeper. In order to evaluate the particle removal performance ofpickup hea

20、d, engineers generally concentrate on two parameters,the sweeper-traveling speed and the pressure drop across the pickuphead. Their influences on the particle removal efficiency and theparticle removal mass flow rate dir

21、ectly relate to the performance ofthe street vacuum sweeper. Chen et al. [8] investigated the influenceof sweeper structure and sweeper-traveling speed on the particleremoval performance by experiments. They found that t

22、he wing plateof pickup head and the sweeper-traveling speed had great influenceon the critical pickup velocity of particles. Meanwhile, they analyzedthe relationship of the particle pickup velocities and the airflow rate

23、s.With the rapid development of the computer technology, thecomputational fluid dynamics (CFD) has been successfully adopted toPowder Technology 200 (2010) 16–24? Corresponding author. Tel.: +86 21 34206821; fax: +86 21

24、34204542.E-mail address: stenstro@seas.ucla.edu (M.K. Stenstrom).0032-5910/$ – see front matter © 2010 Elsevier B.V. All rights reserved.doi:10.1016/j.powtec.2010.02.001Contents lists available at ScienceDirectPowde

25、r Technologyjournal homepage: www.elsevier.com/locate/powtecTherefore, in order to get high quality meshes, it is necessary todecompose the model geometry into several portions. The neck por-tion was meshed with tetrahed

26、ral grids because of complex geometry.For other portions, hexahedral schemes with map or cooper typeswere employed. The computational grids in this study were ap-proximately 274,157 cells. Fig. 5 shows the surface meshes

27、 of thephysical model.4. Mathematical model4.1. Governing equationsThe airflow through the pickup head was calculated numericallyby solving a set of governing equations. Considering the steadyand incompressible airflow t

28、hrough the pickup head, the Reynolds-Averaged Navier–Stokes equations can be written asContinuity : ?ui ?xi = 0 ð2ÞMomentum : ??xj ρuiuj? ? = ? ?P?xi + ??xj μ ?ui ?xj + τij!+ ρgi ð3Þwhere ui and gi ar

29、e the airflow velocity and the gravity accelerationalong the coordinate xi, respectively, ρ is the air density, P is thepressure, μ is the viscosity, and τij = ?ρP u′ iu′ j is Reynolds stress, whichrepresents the effects

30、 of turbulent fluctuation.4.2. Reynolds stress model (RSM)The airflow through the pickup head is turbulent flow due to itshigh velocity, and the key to success of modeling the particle suctionprocess lies in the accurate

31、 description of the turbulent behavior. Theselection of turbulence model depends on the physical model. Com-paring with the k?ε model that is widely used in industrial flowcalculations, the RSM is more accurate as the RS

32、M accounts for theeffects of streamline curvature, swirl, rotation, and rapid changes instrain rate in a more rigorous manner, and consequently it has greaterpotential to give accurate predictions for complex flows [15].

33、 Manystudies indicated that the RSM could provide better accuracy than thek?ε model for the calculations of complex flows [16,17].In the RSM, the eddy viscosity approach is discarded, and theReynolds stress transport equ

34、ation is utilized to describe the effectsof the Reynolds stress. The Reynolds stresses are then used to obtainthe closure of the Reynolds-Averaged momentum equation [18]. Forsteady, irrotational and incompressible airflo

35、w, the Reynolds stresstransport equation takes the following formCij = DT;ij + DL;ij + Pij + ?ij + εij ð4Þwhere Cij, DT,ij, DL,ij, Pij, ?ij and εij are convection term, diffusion term,molecular duffusion term,

36、stress production term, pressure strainterm, and viscous dissipation rate term, respectively.In terms of Eq. (4), the turbulent kinetic energy k and thedissipation rate ε can be obtained by solving the transport equation

37、s??xi ρkui ð Þ = ??xj μ + μt σk? ? ?k?xj“ #+ 12 Pii?ρε ð5Þ??xi ρεui ð Þ = ??xj μ + μt σε? ? ?ε?xj“ #+ C1ε12 Pii?C2ε ρ ε2k ð6Þwhere μt is the turbulent viscosity, and the constants

38、used in thismodel are σk=0.82, Cμ=0.09, σε=1.0, C1ε=1.44, C2ε=1.92 [19].4.3. Particle movementThe Euler–Lagrange approach was employed to predict the gas–solid flow field in the pickup head. The gas phase was treated as

39、acontinuum by solving the Reynolds-Averaged Navier–Stokes equa-tions described above, while the solid phase was calculated bytracking particles through the continuum fluid field. In the particlesuction process, the solid

40、 phase is presented at a low volume fraction,so the gas–solid flow is a dilute phase flow. This discrete phase modelTable 1The main dimensions of the pickup head.Length(mm)Width(mm)Height(mm)Narrow slots height (mm) Outl

41、etdiameter(mm) Front Left Right Rear1800 400 430 15 10 10 10 200Fig. 3. The cumulative size distribution of sand particles.Fig. 4. Physical model of the pickup head.Fig. 5. CFD surface meshes of the physical model.18 S.-

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