- Email: [email protected]
Study of the effect of particles on the kinetic parameters of a turbulent two-phase flow
Energy Procedia 00 (2019) 000–000 Energy Procedia 00 (2019) 000–000
www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia
Availableonline onlineatatwww.sciencedirect.com www.sciencedirect.com Available
ScienceDirect ScienceDirect
Energy (2019) 000–000 201–210 EnergyProcedia Procedia162 00 (2017) www.elsevier.com/locate/procedia
Special Issue on Emerging and Renewable Energy: Generation and Automation Special Issue on Emerging and Renewable Energy: Generation and Automation
Study of the effect of particles on the kinetic parameters of a Study of the effectturbulent of particles on the kinetic twophase flow parameters of a a* a a turbulent twophase flow The 15thBayoudh International Symposium on ,District Heating and Cooling Mariem , Hazem Touati Hmaied Ben N’Ticha Mariem Bayoudha*, Hazem Touati a, Hmaied Ben N’Ticha a
Assessing the feasibility of using the heat demand-outdoor temperature function for a long-term district heat demand forecast
I. Andrića,b,c*, A. Pinaa, P. Ferrãoa, J. Fournierb., B. Lacarrièrec, O. Le Correc a Numerical simulations using aTechnology twofluid Eulerian were performed for twodimensional axisymmetric jets from a circular IN+ Center for Innovation, and Policymodel Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal20 b Numerical simulations using a twofluid Eulerian model were performed for particle twodimensional axisymmetric jets1.from circular 20 mm diameter nozzle. The particle size vary between 30 and 180 m and the ranges from 0.1 to The amodulations Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel,charge 78520 Limay, France c Département Systèmes Énergétiques et Environnement -m IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France mm diameter nozzle. The size vary between 30 of andthe 180 and the particle charge rangeswith from 0.1 to 1.sizes The modulations of the flow structures andparticle the turbulent characteristics gas flow due to the solid particles different and rates of of the flow structures and the turbulent characteristics of of thethe gasmean flowcenter due toline the velocity solid particles with different of particle loading are studied. The jet spread and the decay are calculated for all sizes sizes and rates particle particle loading are studied. Thestudy. jet spread and the of the mean line significantly velocity are calculated for turbulence all sizes and loading rates considered in this Additions of decay solid particles in thecenter gas flow modulate the of particle the gas loading rates as considered in flow this study. of solid particles in the gas flow significantly the turbulence of the gas in the nozzle well as the rates. Additions Fine particles suppress turbulence, while coarse particlesmodulate improve turbulence. inAbstract the nozzle as well as the flow rates. Fine particles suppress turbulence, while coarse particles improve turbulence. Copyright © 2019 Elsevier Ltd. All rights reserved. ©District 2019 The Authors. Published by Elsevier addressed Ltd heating networks are commonly in the literature as of one the most effective solutions decreasing the Copyright © 2019 Elsevierunder Ltd. All rights reserved. Selection and peerreview responsibility of the scientific committee theofSpecial Issue on Emerging and for Renewable Selection and peer-review under responsibility of theThese scientific committee of the investments 6th International Conference onthrough Emerging greenhouse emissions from responsibility the building sector. systems require which are returned theand heat Selection andgas peerreview under of the scientific committee of high the Special Issue on Emerging and Renewable Energy: Generation and Automation. Renewable Energy: Generation and Automation, ICEREGA 2018. sales. Due to the changed climate conditions and building renovation policies, heat demand in the future could decrease, Energy: Generation and Automation. prolonging the investment return period. The main scope of this paper is to assess the feasibility of using the heat demand – outdoor temperature function for heat demand forecast. The district of Alvalade, located in Lisbon (Portugal), was used as a case study. The district is consisted of 665 buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were compared with results from a dynamic heat demand model, previously developed and validated by the authors. The turbulent gassolid particle flows have many applications ranging from pneumatic conveying systems to coal The results showed that when only weather change is considered, the margin of error could be acceptable for some applications The turbulent gassolid particle flows haveinfluenced many applications ranging from pneumatic such conveying systems to coal gasifiers These flows are complex, by various physical phenomena, asintroducing particleturbulence (the error[1]. in annual demand wasvery lower than 20% for all weather scenarios considered). However, after renovation gasifiers [1]. These flows are very complex, influenced by various physical phenomena, such as particleturbulence interactions, drag forces, gravitational, viscous, and lift forces, etc. A fundamental understanding of the particle scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). interactions, drag forces, gravitational, viscous, and lift forces, etc. A fundamental understanding of the particle interaction with the fluid flow is necessary for process optimization and performance improvement. The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the interaction with the fluid flow is necessary for process optimization and performance improvement. There are two main approaches used to simulate twophase flow: the eulerianeulerian and eulerianlagrangian decrease in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and There arescenarios two main approaches to simulate twophase flow: increased the eulerianeulerian renovation considered). Onused the other hand, function intercept for 7.8-12.7%and per eulerianlagrangian decade (depending on the coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and * Corresponding author. of Tel.: +216 52 265estimations. 241; fax: +216 73 500 415. improve the accuracy heat demand * Corresponding author. Tel.: +216 52 265 241; fax: +216 73 500 415. [email protected]
[email protected] © 2017 The Authors. Published by Elsevier Ltd. Peer-review under©responsibility the Committee of The 15th International Symposium on District Heating and 18766102 Copyright 2019 Elsevier of Ltd. AllScientific rights reserved. Cooling.and Selection peerreview under responsibility the scientific 18766102 Copyright © 2019 Elsevier Ltd. All of rights reserved. committee of the Special Issue on Emerging and Renewable Energy: Generation and Automation. Selection and peerreview under responsibility of the scientific committee of the Special Issue on Emerging and Renewable Energy: Generation and Automation. Keywords: Heat demand; Forecast; Climate change
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. 1876-6102 © 2019 The Authors. Published by Elsevier Ltd. Selection and peer-review under responsibility of the scientific committee of the 6th International Conference on Emerging and Renewable Energy: Generation and Automation, ICEREGA 2018. 10.1016/j.egypro.2019.04.022
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Mariem Bayoudh et al. / Energy Procedia 162 (2019) 201–210
approach while particles are treated as discrete entities and tracked over the Eulerian model. In the Eulerian Lagrangian approach, gasphase is modeled as a continuum and solved following the computational domain using a Lagrangian formulation. Whereas the Eulerianeulerian or twofluid model handles the solid phase as a continuum, in which the motion of the individual particles is averaged so that mean equations for continuity and momentum are solved for both the gas and the solid phases, which are coupled through interfacial transfer terms. In the present study, drag force is the only term that acts as the particlefluid interaction. Previous works have focused on the effect of particle presence on fluid turbulence. Elfasakhany et al [2] conducted numerical and experimental investigations on the motion of pulverised wood particles in turbulent flows. A study the influence of the shape and the size of particle behaviour was performed. Kartushinsky et al. [3] studied experimentally and numerically the turbulent particleladen pipe flows. He applied the eulerianeulerian model to study the fluid dynamic behavior and he found that the difference of mean particle and fluid eulerian velocities decrease towards zero near the wall in both upflow and downflow. Patro et al. [4] studied a confined two phase flow and investigated the modulations on the flow structures and turbulent characteristics of gas flow due to the solid particles with different particle sizes and loadings and concluded that small particles attenuate turbulence, while larger ones increase turbulence in the jet. Recently, Ardekani et al. [5] performed simulations of turbulent channel flow with particles up to a volume fraction of φ = 15 %. It’s demonstrated that the presence of the suspension of spherical particles increases the turbulence activity for volume fractions below φ = 20 %. Zade et al. [6]. considered the turbulent flow of a particle suspension in a square duct and finished with the conclusion that the mean velocity profiles look fuller for large particles and fluctuations are more intense for smaller particles. Boivin et al. [7] investigated the modulation of isotropic turbulence by particles using direct numerical simulation (DNS) loading ratios φ ranging from 0 to 1 and it’s found that particles increasingly dissipate fluid kinetic energy and when the loading ratio increases, turbulence subsequently decreases. Lin et al. [8] studied the particle effects on turbulent flows in a square duct and reported that under a prescribed driving pressure gradient, the presence of particles attenuates the bulk velocity and the turbulent intensity and that all particleinduced effects are intensified with increasing particle volume fraction and decreasing particle size. Fornari et al.[9] studied the turbulent square duct flow of dense suspensions of spherical particles. By performing the turbulent kinetic energy budget, it’s concluded that the turbulence production is enhanced up to volume fraction of ϕ=0,1, while for ϕ=0,2 the production decreases below the values for ϕ=0,05. Ofei et al. [10] used the EulerianEulerian twofluid model to study the influence of particle size and in particle volume fraction on the radial distribution of particle concentration and velocity by adopting the kepsilon model to model the turbulence. It’s found that the particle concentration profiles for coarse particle were primarily dependent on the particle volume fraction and that fine particle size travelled faster than coarse particle size. Kabeel et al. [11] investigated the behavior of the gas turbulent flow laden with solid particles and reviewed the effect of significant parameters that influence the interactions between the both phases, such as particle size, loading ratio. It’s concluded that the turbulence degree is proportional to the particle size and that the particle shape, density and size significantly alter the turbulence characteristics. Welahettige et al. [12] studied vertically upward dilute phase pneumatic conveying flow using Euler Granular method. Simulations for different particle diameters were performed varying air velocities and ranging solid to air mass flow ratios. A study of air and particle velocity profiles and solid distribution profiles and comparaison of the results with experimental data from existing literature were done. Wang et al.[13] simulated numerically the gas–particle flow behavior using the Eulerian–Eulerian twofluid model and a drag model for gasparticles interaction and obtained the distribution of particle concentration, particle velocity and pressure. KIM H et al.[14] has conducted a study to investigate experimetally the particle size and velocity profile of gasoline port injector using Phase Doppler Particle Analyzer. It’s concluded that the length diameter the Sauter mean diameter ,and the mean droplet velocity are 4554 m, 99115 m and 1521 m/s, respectively. Hoffmann J.W. et al.[15] has studied the derate mitigation options for Pulverized Coal Power Plant Carbon Capture Retrofits.
Mariem Bayoudh et al. / Energy Procedia 162 (2019) 201–210
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At this work, it is proposed to study numerically the dynamic behavior of the twophase flow and to analyze the effect of the particleloading rate and size on the gas flow and turbulence. An EulerianEulerian approach has been adopted to model the solid phase and the kε model for turbulence. NaviersStokes equations were applied and discretized with finite volume method and computed with FORTRAN code. The modulations of the flow structures and the turbulent characteristics of the gas flow due to the solid particles with different sizes and rates of particle loading are studied. D dp g k mp np p r R Re Tau
diffusivity, m2 s−1 particle diameter, m acceleration due to gravity, m/s2 gas phase turbulent kinetic energy, m2 s−2 the particle mass, kg particle number per volume unity, m3 mean pressure, Pa distance along the radial direction, m radius Re particulate loading, m3
Greek symbol α volume fraction of solid ρ density, kg.m−3 ε dissipation rate of turbulence τp particle relaxation time, s τT the gas turbulence time scale,s µ dynamic viscosity, kg. m1.s1 ν kinematic viscosity, m2.s1 ϕ ratio of mass flow rate Subscript g,f s,p
gaz solid
The numerical model solves the standard equations for the conservation of mass, momentum, energy and species in the geometry of a coaxial burner. The κε model presented by Launder and Spalding [16] is used to model the turbulence. The governing equations for an Eulerian description of dilute and turbulent gassolid flows follow those given by Bolio [17]. • •
∂ (α ) = 0 ∂
Mass conservation equation Momentum conservation equation
(1)
Mariem Bayoudh et al. / Energy Procedia 162 (2019) 201–210
204 4
∂ (α ρ ∂
α ρ ( τ
=
) = −α −
∂ ∂ + ∂ ∂
α ∂ + ∂ ∂ ∂
+ ∂ (α ( ∂
)) + α
ρ +
)
(2)
Turbulent kinetic energy equation ∂κ ν ∂κ − ∂ = α ρ α ρ ν + ∂ ∂ σ ∂
•
(
α ρ 2 = − + κ − κ τ
With
− α ρ (
)
Turbulent kinetic energy dissipation rate equation ∂ε ν ∂ε ε − ∂ −α ρ = α ρ α ρ ν + ∂ ∂ σ ε ∂ κ ∂ ∂ 2 ε ( ) κ δ ν + = − ε = 3 ∂ 3 ∂ κ ,
) ∂∂
(3)
− α ρ ε +
•
•
Particle number conservation
•
Momentum conservation
∂ ∂ ( ) = + + ∂ ∂ = •
(
τ
−
∂ ε 1 1 ( ) + ε 2 2ε ∂ κ2 ,ν = ε
+ ε (4)
∂ ( ) = ∂ ν ∂ ∂ ∂ σ ∂
ν ∂ + ∂ ∂ ∂
∂ ν ∂ ∂ + + + ∂ σ ∂ ∂
(5)
(6)
)
Transport equation of turbulent kinetic energy
The turbulence quantities for the solid phase were obtained using the HinzeTchen algebraic model [18] of dispersion of particles by homogeneous turbulence.
κ = κ 1 +
with
τ =
τ
κ ε
,
τ τ
−1
(7)
and τ are respectively particle relaxation time and the gas turbulence time scale τ
=
ρ 2 18
The particulate loading Tau is defined as the ratio of the mass flow rate of the solid phase and the mass flow rate of the gas phase.
Mariem Bayoudh et al. / Energy Procedia 162 (2019) 201–210
=
205 5
α ρ
(1 − α )ρ
(8)
The mean jet composed of a airparticles mixture emerges from a primary nozzle (diameter of 20 mm), with an inlet velocity of 12.6 m/s surrounded by a secondary stream whose velocity is 0.05 m/s , low compared to the velocity of the mean jet. Beads velocity is close to that of the air according to the measurements of Modaress et al.[19]. The tube length is 90 times its diameter so that the turbulence is fully developed at the exit of the tube. Spherical glass beads of uniform size and density of 2990 kg/m3 were introduced into the jet (Fig. 1).
Fig. 1. Flow field around a jet
For the axial positions X/D=20 (Fig. 2.a) and X/D=30 (Fig. 2.b), the radial velocity curves as well as the turbulent intensity found are reported in Fig. 2 and 3 to confirm that the mean velocity and turbulence simulations are in good agreement with the experiments.
(a)
(b)
Fig. 2. velocity radial profile (a)for the section x/D=20 and (b) for the section x/D=30 for ϕ=0.32
6
Mariem Bayoudh et al. / Energy Procedia 162 (2019) 201–210
206
Fig. 3. Velocity axial Profile for ϕ=0.32
(a)
(b)
Fig. 4. Variation of the central line velocity for different particle sizes: (a) gaseous phase and (b) solid phase ρs = 1000 kg / m3, loading rate = 0.4
The centerline axial velocity profiles for both the phases are shown in Figs. 4 and 5 for different particle sizes and particulate loadings. The presence of the particles reduces the decay of the centerline velocity of the gas phase because of turbulence modulation by the particles. After coming out of the orifice, the air momentum is transmitted to the particles and the surrounding air, and so its velocity rapidly declines. Meanwhile, particles are accelerated by receiving momentum until they reach the end of a particle developing region, where particle velocity exceeds the gasphase velocity which lead to momentum transmission from the particles to the gas. So the decay of the axial mean velocity of the gas reduces along the centerline. • Effect of diameter variation of the particle The effect of the variation of the particle diameters on the two phases flow is illustrated in Fig. 4, which shows the velocity on the axis for different diameters of the particles. The increase in particle size increases the decay rate in gas
Mariem Bayoudh et al. / Energy Procedia 162 (2019) 201–210
207 7
phase velocity and reduces the decay rate of the solid phase velocity along the centerline. The heaviest particles disperse slowly along the radial direction, because of inertia, and therefore most of them are concentrated near the centerline of the jet. This obstructs the movement of the fluid near the central region and the velocity of the gas decreases. • Effect of the variation of the loading rate
(a)
(b)
Fig. 5. Variation of the velocity of the central line for different particle loading rates: (a) gaseous phase and (b) solid phase ρs = 1000 kg / m3, dp = 50 m
Fig. 5 shows the influence of the loading rate on the axial decay of the mean velocity. It can be seen that the decay rate of the axial velocity becomes slow as the loading rate increases. By increasing the particulate loading for the same particle size, larger eddies produced by the entrained air can be easily divided into smaller eddies [20]. Thus, the turbulent energy associated with these vortices is attenuated. Therefore, with a large particle charge, the momentum exchange between the phases becomes minimal. As a result, the decay rate of the velocity diminishes. •
Effect of loading rate
Fig. 6. Effect of loading rate on radial velocity profiles at X / D = 20, dp = 50 m and Um = 10 m /s ρp = 1020 Kg / m3
Mariem Bayoudh et al. / Energy Procedia 162 (2019) 201–210
208 8
On Fig. 6 velocity profiles of singlephase and twophase particulate jets are plotted radially at X/D =20 for 50 m particles for different axial positions 10, 20, and 30 from the orifice exit. With the increase in particulate loading, the radial velocity of both the phases increases, and the rate of increase is more for the gas phase. This results in a narrower jet than a singlephase jet. Solidphase velocity is upper than the gas phase velocity along the centerline, where the local solid concentration is high, which slows down the gas velocity. 4.4. The fluctuation of turbulence is supposed to be isotropic in the kε model. To quantify the change in turbulence due to the addition of particles, the percentage of turbulence modulation (TM) is calculated as: TM =
K , − K , x100 K ,
The indices TP and SP refer to the twophase flow and the singlephase flow, respectively. A positive value for TM indicates an enhancement of the turbulence, while a negative value indicates an attenuation of the turbulence.
(a)
(b)
Fig. 7. (a) turbulent kinetic energy and (b) turbulent modulations on the center line as a function of the axial distance, ρs = 3000 kg / m3
(a)
(b)
Fig. 8. (a) turbulent kinetic energy and (b) turbulent modulations along the centerline, ρs = 1000 kg / m3, Loading Rate = 0.4
Mariem Bayoudh et al. / Energy Procedia 162 (2019) 201–210
209 9
The axial distribution of the turbulent kinetic energy, normalized by its initial value, is presented in Figs. 7 (a) and 11 (a) for different particle sizes and loading rates. It is observed that, after an initial decrease due to the development of the jet, the turbulent kinetic energy increases strongly and then decreases. The singlephase results is also shown in Fig. 8 (a). Small particles dissipate turbulence more than large particles, and with the increase in particle diameter, turbulent energy increases. This is related to a significant increase in the integral turbulent length scale with the particle diameter [21–22]. As the smaller particles are smaller than the turbulent energetic eddies, they follow the eddies. Some part of the eddy’s energy is transferred to the particles, through the drag force, for moving them. Consequently, the turbulent energy of the eddies gets reduced and turbulence is attenuated. In Fig. 8 (a), it can be seen that with increasing loading rate, turbulent kinetic energy decreases in the region of flow development and then increases along the centerline. Fig.s 7 (b) and 8 (b) show the percentage of turbulence modulation (TM) in the twophase jet along the centerline. It is observed that the fine particles (30 m) reduce turbulence throughout the central line. The other coarse particles cause attenuation in the developing region (up to X/D =15) and augmentation in the region where the full length turbulence scale (L0) is higher. The larger particles more effectively break coherent eddies in the flow and reduce the turbulent stresses [6]. A similar tendency occurs for different loading rates. CFD simulation was performed for a turbulent gas flow containing dispersed solid particles diluted in a nozzle acting in the vertical direction downwards. The EulerEuler model was developed for solid gas streams for different sizes and rates of particle loading. The turbulence model kε with additional source terms representing the effect of solid particles with the function of the loglaw wall was used for the gas phase. This study showed that the particle size and the loading rate are the two parameters that significantly influence the twophase flow. The solid particles significantly affected the turbulence structure of the gaseous phase in the nozzle. Smaller particles enhanced turbulence, while larger ones increased turbulence in the jet. The first author acknowledge his training period in the Laboratory of Thermal and Energetic Systems Studies permitting the achievement of the present work. [1] Hoffmann J. W., Hackett G. A., Lewis E. G.and Chou V. H. “Derate Mitigation Options for Pulverized Coal Power Plant Carbon Capture Retrofits” Energy Procedia 114 (2017): 6465–6477. [2] El Fasakhany A., Taob L.X. and Baia X.S. “Transport of pulverized wood particles in turbulent flow: numerical and experimental studies” Energy Procedia 61 ( 2014 ): 1540 – 1543. [3] Kartushinsky A., Tisler S., Oliveira J.L.G., van der Geld C.W.M. ” EulerianEulerian modelling of particleladen twophase flow”. Powder Technology 301 (2016): 999–1007. [4] Patro P. and Dash S. “Computations of ParticleLaden Turbulent Jet Flows Based on Eulerian Model”. Journal of Fluids Engineering (2014) Vol. 136 / 0113011. [5] Ardekani M. N., Costa P., Breugem W. P., Picano F. & Brandt L.”Drag reduction in turbulent channel flow laden with finitesize oblate spheroids.” J. Fluid Mech. 816, (2017): 43–70. [6] Zade S, Costa P., Fornari W., Lundell F., and Brandt L. “Experimental investigation of turbulent suspensions of spherical particles in a square duct,” Journal of Fluid Mechanics. (2018). [7] Boivin M, Simonin O, and Squires K. “Direct numerical simulation of turbulence modulation by particles in isotropic turbulence”. J. Fluid Mech. vol. 375, (1998): 235–263. [8] Lin Z., Yu Z., Xueming S., Wang LP. “Effects of finitesize neutrally buoyant particles on the turbulent flows in a square duct, Physics of Fluids. (2017): 29(10):103304. [9] Fornari, W., Kazeroon, H.T. & Brandt, L. “Suspensions of nitesize neutrally buoyant spheres in turbulent duct Flow”. J. Fluid Mech. vol. 851, (2018): 148186.
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[10] Ofei TN. and Ismail AY. “EulerianEulerian Simulation of ParticleLiquid Slurry Flow in Horizontal Pipe” Journal of Petroleum Engineering Vol. 2016/ 5743471. (2016). [11] Kabeel A.E. and Elkelawy M. “Solid Particles Injection in Gas Turbulent Channel Flow”. J of Energy and Power Engineering, (2016): 8, 367388. [12]Welahettige P. HAriyaratne W.K. and Melaaen M. C. “EulerGranular Approach for Modelling of Dilute Phase Pneumatic Conveying in a Vertical Pipe”. Proceedings of the 58th SIMS, Reykjavik, Iceland. (2016). [13] Wang Q, Luo J, Xu C, Chen D, Sun B, and Feng J. “Numerical Simulation of the Gas–Particle Flow Behavior in Oil Shale SemiCoke Spouted Bed”. Energy Procedia 17 ( 2012 ): 892 – 900. [14] KIM H., TONGCHAI S. and LIM O. “A Study on the Particle Size and Velocity Profile on a Gasoline Port Injector Using a Phase Doppler Particle Analyzers (PDPA) “Energy Procedia 145 (2018): 374–380. [15] Hoffmann J. W., Hackett G. A., Lewis E. G.and Chou V. H. “Derate Mitigation Options for Pulverized Coal Power Plant Carbon Capture Retrofits” Energy Procedia 114 (2017): 6465–6477. [16] Launder B.E. and Spalding D. B. “The Numerical Computation of Turbulent Flows”, Computer Methods in Mechanics and Engineering, Volume 3, (1974): 269289. [17] Bolio, E. J., Yasuna, J. A., and Sinclair, J. L. “Dilute Turbulent Gas–Solid Flow in Risers With Particle–Particle Interactions” AIChE J., 141(6), (1995): 1375–1388. [18] HinzeTchen J. O. Turbulence, McGrawHill, New York, (1975). [19] Modarres, D., Tan, H., and Elghobashi, S. “Two Component LDA Measurements in a Two Phase Turbulent Jet”. AIAA J., 22(5), (1984): 624–630. [20] Gillandt, I., Fritsching, U., and Bauckhage, K. “Measurement of Phase Interaction in Dispersed GasParticle TwoPhase Flow,” Int. J. Multiphase Flow, 27, (2001):1313–1332. [21]Crowe, C. T. “On Models for Turbulence Modulation in Fluid–Particle Flows”. Int. J. Multiphase Flow, 26(5), (2000): 719–727. [22] Michaelides, E. E. “Particles, Bubbles and DropsTheir Motion, Heat and Mass Transfer”, World Scientific, New Jersey (2006).
www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia
Availableonline onlineatatwww.sciencedirect.com www.sciencedirect.com Available
ScienceDirect ScienceDirect
Energy (2019) 000–000 201–210 EnergyProcedia Procedia162 00 (2017) www.elsevier.com/locate/procedia
Special Issue on Emerging and Renewable Energy: Generation and Automation Special Issue on Emerging and Renewable Energy: Generation and Automation
Study of the effect of particles on the kinetic parameters of a Study of the effectturbulent of particles on the kinetic twophase flow parameters of a a* a a turbulent twophase flow The 15thBayoudh International Symposium on ,District Heating and Cooling Mariem , Hazem Touati Hmaied Ben N’Ticha Mariem Bayoudha*, Hazem Touati a, Hmaied Ben N’Ticha a
Assessing the feasibility of using the heat demand-outdoor temperature function for a long-term district heat demand forecast
I. Andrića,b,c*, A. Pinaa, P. Ferrãoa, J. Fournierb., B. Lacarrièrec, O. Le Correc a Numerical simulations using aTechnology twofluid Eulerian were performed for twodimensional axisymmetric jets from a circular IN+ Center for Innovation, and Policymodel Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal20 b Numerical simulations using a twofluid Eulerian model were performed for particle twodimensional axisymmetric jets1.from circular 20 mm diameter nozzle. The particle size vary between 30 and 180 m and the ranges from 0.1 to The amodulations Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel,charge 78520 Limay, France c Département Systèmes Énergétiques et Environnement -m IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France mm diameter nozzle. The size vary between 30 of andthe 180 and the particle charge rangeswith from 0.1 to 1.sizes The modulations of the flow structures andparticle the turbulent characteristics gas flow due to the solid particles different and rates of of the flow structures and the turbulent characteristics of of thethe gasmean flowcenter due toline the velocity solid particles with different of particle loading are studied. The jet spread and the decay are calculated for all sizes sizes and rates particle particle loading are studied. Thestudy. jet spread and the of the mean line significantly velocity are calculated for turbulence all sizes and loading rates considered in this Additions of decay solid particles in thecenter gas flow modulate the of particle the gas loading rates as considered in flow this study. of solid particles in the gas flow significantly the turbulence of the gas in the nozzle well as the rates. Additions Fine particles suppress turbulence, while coarse particlesmodulate improve turbulence. inAbstract the nozzle as well as the flow rates. Fine particles suppress turbulence, while coarse particles improve turbulence. Copyright © 2019 Elsevier Ltd. All rights reserved. ©District 2019 The Authors. Published by Elsevier addressed Ltd heating networks are commonly in the literature as of one the most effective solutions decreasing the Copyright © 2019 Elsevierunder Ltd. All rights reserved. Selection and peerreview responsibility of the scientific committee theofSpecial Issue on Emerging and for Renewable Selection and peer-review under responsibility of theThese scientific committee of the investments 6th International Conference onthrough Emerging greenhouse emissions from responsibility the building sector. systems require which are returned theand heat Selection andgas peerreview under of the scientific committee of high the Special Issue on Emerging and Renewable Energy: Generation and Automation. Renewable Energy: Generation and Automation, ICEREGA 2018. sales. Due to the changed climate conditions and building renovation policies, heat demand in the future could decrease, Energy: Generation and Automation. prolonging the investment return period. The main scope of this paper is to assess the feasibility of using the heat demand – outdoor temperature function for heat demand forecast. The district of Alvalade, located in Lisbon (Portugal), was used as a case study. The district is consisted of 665 buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were compared with results from a dynamic heat demand model, previously developed and validated by the authors. The turbulent gassolid particle flows have many applications ranging from pneumatic conveying systems to coal The results showed that when only weather change is considered, the margin of error could be acceptable for some applications The turbulent gassolid particle flows haveinfluenced many applications ranging from pneumatic such conveying systems to coal gasifiers These flows are complex, by various physical phenomena, asintroducing particleturbulence (the error[1]. in annual demand wasvery lower than 20% for all weather scenarios considered). However, after renovation gasifiers [1]. These flows are very complex, influenced by various physical phenomena, such as particleturbulence interactions, drag forces, gravitational, viscous, and lift forces, etc. A fundamental understanding of the particle scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). interactions, drag forces, gravitational, viscous, and lift forces, etc. A fundamental understanding of the particle interaction with the fluid flow is necessary for process optimization and performance improvement. The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the interaction with the fluid flow is necessary for process optimization and performance improvement. There are two main approaches used to simulate twophase flow: the eulerianeulerian and eulerianlagrangian decrease in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and There arescenarios two main approaches to simulate twophase flow: increased the eulerianeulerian renovation considered). Onused the other hand, function intercept for 7.8-12.7%and per eulerianlagrangian decade (depending on the coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and * Corresponding author. of Tel.: +216 52 265estimations. 241; fax: +216 73 500 415. improve the accuracy heat demand * Corresponding author. Tel.: +216 52 265 241; fax: +216 73 500 415. [email protected]
[email protected] © 2017 The Authors. Published by Elsevier Ltd. Peer-review under©responsibility the Committee of The 15th International Symposium on District Heating and 18766102 Copyright 2019 Elsevier of Ltd. AllScientific rights reserved. Cooling.and Selection peerreview under responsibility the scientific 18766102 Copyright © 2019 Elsevier Ltd. All of rights reserved. committee of the Special Issue on Emerging and Renewable Energy: Generation and Automation. Selection and peerreview under responsibility of the scientific committee of the Special Issue on Emerging and Renewable Energy: Generation and Automation. Keywords: Heat demand; Forecast; Climate change
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. 1876-6102 © 2019 The Authors. Published by Elsevier Ltd. Selection and peer-review under responsibility of the scientific committee of the 6th International Conference on Emerging and Renewable Energy: Generation and Automation, ICEREGA 2018. 10.1016/j.egypro.2019.04.022
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approach while particles are treated as discrete entities and tracked over the Eulerian model. In the Eulerian Lagrangian approach, gasphase is modeled as a continuum and solved following the computational domain using a Lagrangian formulation. Whereas the Eulerianeulerian or twofluid model handles the solid phase as a continuum, in which the motion of the individual particles is averaged so that mean equations for continuity and momentum are solved for both the gas and the solid phases, which are coupled through interfacial transfer terms. In the present study, drag force is the only term that acts as the particlefluid interaction. Previous works have focused on the effect of particle presence on fluid turbulence. Elfasakhany et al [2] conducted numerical and experimental investigations on the motion of pulverised wood particles in turbulent flows. A study the influence of the shape and the size of particle behaviour was performed. Kartushinsky et al. [3] studied experimentally and numerically the turbulent particleladen pipe flows. He applied the eulerianeulerian model to study the fluid dynamic behavior and he found that the difference of mean particle and fluid eulerian velocities decrease towards zero near the wall in both upflow and downflow. Patro et al. [4] studied a confined two phase flow and investigated the modulations on the flow structures and turbulent characteristics of gas flow due to the solid particles with different particle sizes and loadings and concluded that small particles attenuate turbulence, while larger ones increase turbulence in the jet. Recently, Ardekani et al. [5] performed simulations of turbulent channel flow with particles up to a volume fraction of φ = 15 %. It’s demonstrated that the presence of the suspension of spherical particles increases the turbulence activity for volume fractions below φ = 20 %. Zade et al. [6]. considered the turbulent flow of a particle suspension in a square duct and finished with the conclusion that the mean velocity profiles look fuller for large particles and fluctuations are more intense for smaller particles. Boivin et al. [7] investigated the modulation of isotropic turbulence by particles using direct numerical simulation (DNS) loading ratios φ ranging from 0 to 1 and it’s found that particles increasingly dissipate fluid kinetic energy and when the loading ratio increases, turbulence subsequently decreases. Lin et al. [8] studied the particle effects on turbulent flows in a square duct and reported that under a prescribed driving pressure gradient, the presence of particles attenuates the bulk velocity and the turbulent intensity and that all particleinduced effects are intensified with increasing particle volume fraction and decreasing particle size. Fornari et al.[9] studied the turbulent square duct flow of dense suspensions of spherical particles. By performing the turbulent kinetic energy budget, it’s concluded that the turbulence production is enhanced up to volume fraction of ϕ=0,1, while for ϕ=0,2 the production decreases below the values for ϕ=0,05. Ofei et al. [10] used the EulerianEulerian twofluid model to study the influence of particle size and in particle volume fraction on the radial distribution of particle concentration and velocity by adopting the kepsilon model to model the turbulence. It’s found that the particle concentration profiles for coarse particle were primarily dependent on the particle volume fraction and that fine particle size travelled faster than coarse particle size. Kabeel et al. [11] investigated the behavior of the gas turbulent flow laden with solid particles and reviewed the effect of significant parameters that influence the interactions between the both phases, such as particle size, loading ratio. It’s concluded that the turbulence degree is proportional to the particle size and that the particle shape, density and size significantly alter the turbulence characteristics. Welahettige et al. [12] studied vertically upward dilute phase pneumatic conveying flow using Euler Granular method. Simulations for different particle diameters were performed varying air velocities and ranging solid to air mass flow ratios. A study of air and particle velocity profiles and solid distribution profiles and comparaison of the results with experimental data from existing literature were done. Wang et al.[13] simulated numerically the gas–particle flow behavior using the Eulerian–Eulerian twofluid model and a drag model for gasparticles interaction and obtained the distribution of particle concentration, particle velocity and pressure. KIM H et al.[14] has conducted a study to investigate experimetally the particle size and velocity profile of gasoline port injector using Phase Doppler Particle Analyzer. It’s concluded that the length diameter the Sauter mean diameter ,and the mean droplet velocity are 4554 m, 99115 m and 1521 m/s, respectively. Hoffmann J.W. et al.[15] has studied the derate mitigation options for Pulverized Coal Power Plant Carbon Capture Retrofits.
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At this work, it is proposed to study numerically the dynamic behavior of the twophase flow and to analyze the effect of the particleloading rate and size on the gas flow and turbulence. An EulerianEulerian approach has been adopted to model the solid phase and the kε model for turbulence. NaviersStokes equations were applied and discretized with finite volume method and computed with FORTRAN code. The modulations of the flow structures and the turbulent characteristics of the gas flow due to the solid particles with different sizes and rates of particle loading are studied. D dp g k mp np p r R Re Tau
diffusivity, m2 s−1 particle diameter, m acceleration due to gravity, m/s2 gas phase turbulent kinetic energy, m2 s−2 the particle mass, kg particle number per volume unity, m3 mean pressure, Pa distance along the radial direction, m radius Re particulate loading, m3
Greek symbol α volume fraction of solid ρ density, kg.m−3 ε dissipation rate of turbulence τp particle relaxation time, s τT the gas turbulence time scale,s µ dynamic viscosity, kg. m1.s1 ν kinematic viscosity, m2.s1 ϕ ratio of mass flow rate Subscript g,f s,p
gaz solid
The numerical model solves the standard equations for the conservation of mass, momentum, energy and species in the geometry of a coaxial burner. The κε model presented by Launder and Spalding [16] is used to model the turbulence. The governing equations for an Eulerian description of dilute and turbulent gassolid flows follow those given by Bolio [17]. • •
∂ (α ) = 0 ∂
Mass conservation equation Momentum conservation equation
(1)
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∂ (α ρ ∂
α ρ ( τ
=
) = −α −
∂ ∂ + ∂ ∂
α ∂ + ∂ ∂ ∂
+ ∂ (α ( ∂
)) + α
ρ +
)
(2)
Turbulent kinetic energy equation ∂κ ν ∂κ − ∂ = α ρ α ρ ν + ∂ ∂ σ ∂
•
(
α ρ 2 = − + κ − κ τ
With
− α ρ (
)
Turbulent kinetic energy dissipation rate equation ∂ε ν ∂ε ε − ∂ −α ρ = α ρ α ρ ν + ∂ ∂ σ ε ∂ κ ∂ ∂ 2 ε ( ) κ δ ν + = − ε = 3 ∂ 3 ∂ κ ,
) ∂∂
(3)
− α ρ ε +
•
•
Particle number conservation
•
Momentum conservation
∂ ∂ ( ) = + + ∂ ∂ = •
(
τ
−
∂ ε 1 1 ( ) + ε 2 2ε ∂ κ2 ,ν = ε
+ ε (4)
∂ ( ) = ∂ ν ∂ ∂ ∂ σ ∂
ν ∂ + ∂ ∂ ∂
∂ ν ∂ ∂ + + + ∂ σ ∂ ∂
(5)
(6)
)
Transport equation of turbulent kinetic energy
The turbulence quantities for the solid phase were obtained using the HinzeTchen algebraic model [18] of dispersion of particles by homogeneous turbulence.
κ = κ 1 +
with
τ =
τ
κ ε
,
τ τ
−1
(7)
and τ are respectively particle relaxation time and the gas turbulence time scale τ
=
ρ 2 18
The particulate loading Tau is defined as the ratio of the mass flow rate of the solid phase and the mass flow rate of the gas phase.
Mariem Bayoudh et al. / Energy Procedia 162 (2019) 201–210
=
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α ρ
(1 − α )ρ
(8)
The mean jet composed of a airparticles mixture emerges from a primary nozzle (diameter of 20 mm), with an inlet velocity of 12.6 m/s surrounded by a secondary stream whose velocity is 0.05 m/s , low compared to the velocity of the mean jet. Beads velocity is close to that of the air according to the measurements of Modaress et al.[19]. The tube length is 90 times its diameter so that the turbulence is fully developed at the exit of the tube. Spherical glass beads of uniform size and density of 2990 kg/m3 were introduced into the jet (Fig. 1).
Fig. 1. Flow field around a jet
For the axial positions X/D=20 (Fig. 2.a) and X/D=30 (Fig. 2.b), the radial velocity curves as well as the turbulent intensity found are reported in Fig. 2 and 3 to confirm that the mean velocity and turbulence simulations are in good agreement with the experiments.
(a)
(b)
Fig. 2. velocity radial profile (a)for the section x/D=20 and (b) for the section x/D=30 for ϕ=0.32
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Fig. 3. Velocity axial Profile for ϕ=0.32
(a)
(b)
Fig. 4. Variation of the central line velocity for different particle sizes: (a) gaseous phase and (b) solid phase ρs = 1000 kg / m3, loading rate = 0.4
The centerline axial velocity profiles for both the phases are shown in Figs. 4 and 5 for different particle sizes and particulate loadings. The presence of the particles reduces the decay of the centerline velocity of the gas phase because of turbulence modulation by the particles. After coming out of the orifice, the air momentum is transmitted to the particles and the surrounding air, and so its velocity rapidly declines. Meanwhile, particles are accelerated by receiving momentum until they reach the end of a particle developing region, where particle velocity exceeds the gasphase velocity which lead to momentum transmission from the particles to the gas. So the decay of the axial mean velocity of the gas reduces along the centerline. • Effect of diameter variation of the particle The effect of the variation of the particle diameters on the two phases flow is illustrated in Fig. 4, which shows the velocity on the axis for different diameters of the particles. The increase in particle size increases the decay rate in gas
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phase velocity and reduces the decay rate of the solid phase velocity along the centerline. The heaviest particles disperse slowly along the radial direction, because of inertia, and therefore most of them are concentrated near the centerline of the jet. This obstructs the movement of the fluid near the central region and the velocity of the gas decreases. • Effect of the variation of the loading rate
(a)
(b)
Fig. 5. Variation of the velocity of the central line for different particle loading rates: (a) gaseous phase and (b) solid phase ρs = 1000 kg / m3, dp = 50 m
Fig. 5 shows the influence of the loading rate on the axial decay of the mean velocity. It can be seen that the decay rate of the axial velocity becomes slow as the loading rate increases. By increasing the particulate loading for the same particle size, larger eddies produced by the entrained air can be easily divided into smaller eddies [20]. Thus, the turbulent energy associated with these vortices is attenuated. Therefore, with a large particle charge, the momentum exchange between the phases becomes minimal. As a result, the decay rate of the velocity diminishes. •
Effect of loading rate
Fig. 6. Effect of loading rate on radial velocity profiles at X / D = 20, dp = 50 m and Um = 10 m /s ρp = 1020 Kg / m3
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On Fig. 6 velocity profiles of singlephase and twophase particulate jets are plotted radially at X/D =20 for 50 m particles for different axial positions 10, 20, and 30 from the orifice exit. With the increase in particulate loading, the radial velocity of both the phases increases, and the rate of increase is more for the gas phase. This results in a narrower jet than a singlephase jet. Solidphase velocity is upper than the gas phase velocity along the centerline, where the local solid concentration is high, which slows down the gas velocity. 4.4. The fluctuation of turbulence is supposed to be isotropic in the kε model. To quantify the change in turbulence due to the addition of particles, the percentage of turbulence modulation (TM) is calculated as: TM =
K , − K , x100 K ,
The indices TP and SP refer to the twophase flow and the singlephase flow, respectively. A positive value for TM indicates an enhancement of the turbulence, while a negative value indicates an attenuation of the turbulence.
(a)
(b)
Fig. 7. (a) turbulent kinetic energy and (b) turbulent modulations on the center line as a function of the axial distance, ρs = 3000 kg / m3
(a)
(b)
Fig. 8. (a) turbulent kinetic energy and (b) turbulent modulations along the centerline, ρs = 1000 kg / m3, Loading Rate = 0.4
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The axial distribution of the turbulent kinetic energy, normalized by its initial value, is presented in Figs. 7 (a) and 11 (a) for different particle sizes and loading rates. It is observed that, after an initial decrease due to the development of the jet, the turbulent kinetic energy increases strongly and then decreases. The singlephase results is also shown in Fig. 8 (a). Small particles dissipate turbulence more than large particles, and with the increase in particle diameter, turbulent energy increases. This is related to a significant increase in the integral turbulent length scale with the particle diameter [21–22]. As the smaller particles are smaller than the turbulent energetic eddies, they follow the eddies. Some part of the eddy’s energy is transferred to the particles, through the drag force, for moving them. Consequently, the turbulent energy of the eddies gets reduced and turbulence is attenuated. In Fig. 8 (a), it can be seen that with increasing loading rate, turbulent kinetic energy decreases in the region of flow development and then increases along the centerline. Fig.s 7 (b) and 8 (b) show the percentage of turbulence modulation (TM) in the twophase jet along the centerline. It is observed that the fine particles (30 m) reduce turbulence throughout the central line. The other coarse particles cause attenuation in the developing region (up to X/D =15) and augmentation in the region where the full length turbulence scale (L0) is higher. The larger particles more effectively break coherent eddies in the flow and reduce the turbulent stresses [6]. A similar tendency occurs for different loading rates. CFD simulation was performed for a turbulent gas flow containing dispersed solid particles diluted in a nozzle acting in the vertical direction downwards. The EulerEuler model was developed for solid gas streams for different sizes and rates of particle loading. The turbulence model kε with additional source terms representing the effect of solid particles with the function of the loglaw wall was used for the gas phase. This study showed that the particle size and the loading rate are the two parameters that significantly influence the twophase flow. The solid particles significantly affected the turbulence structure of the gaseous phase in the nozzle. Smaller particles enhanced turbulence, while larger ones increased turbulence in the jet. The first author acknowledge his training period in the Laboratory of Thermal and Energetic Systems Studies permitting the achievement of the present work. [1] Hoffmann J. W., Hackett G. A., Lewis E. G.and Chou V. H. “Derate Mitigation Options for Pulverized Coal Power Plant Carbon Capture Retrofits” Energy Procedia 114 (2017): 6465–6477. [2] El Fasakhany A., Taob L.X. and Baia X.S. “Transport of pulverized wood particles in turbulent flow: numerical and experimental studies” Energy Procedia 61 ( 2014 ): 1540 – 1543. [3] Kartushinsky A., Tisler S., Oliveira J.L.G., van der Geld C.W.M. ” EulerianEulerian modelling of particleladen twophase flow”. Powder Technology 301 (2016): 999–1007. [4] Patro P. and Dash S. “Computations of ParticleLaden Turbulent Jet Flows Based on Eulerian Model”. Journal of Fluids Engineering (2014) Vol. 136 / 0113011. [5] Ardekani M. N., Costa P., Breugem W. P., Picano F. & Brandt L.”Drag reduction in turbulent channel flow laden with finitesize oblate spheroids.” J. Fluid Mech. 816, (2017): 43–70. [6] Zade S, Costa P., Fornari W., Lundell F., and Brandt L. “Experimental investigation of turbulent suspensions of spherical particles in a square duct,” Journal of Fluid Mechanics. (2018). [7] Boivin M, Simonin O, and Squires K. “Direct numerical simulation of turbulence modulation by particles in isotropic turbulence”. J. Fluid Mech. vol. 375, (1998): 235–263. [8] Lin Z., Yu Z., Xueming S., Wang LP. “Effects of finitesize neutrally buoyant particles on the turbulent flows in a square duct, Physics of Fluids. (2017): 29(10):103304. [9] Fornari, W., Kazeroon, H.T. & Brandt, L. “Suspensions of nitesize neutrally buoyant spheres in turbulent duct Flow”. J. Fluid Mech. vol. 851, (2018): 148186.
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