Analysis of Temperature and Humidity Field in a New Bulk Tobacco Curing Barn Based on CFD

sensors

Article Analysis of Temperature and Humidity Field in a New Bulk Tobacco Curing Barn Based on CFD

Zhipeng Bai, Duoduo Guo, Shoucang Li and Yaohua Hu * College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling 712100, China; [email protected] (Z.B.); [email protected] (D.G.); [email protected] (S.L.) * Correspondence: [email protected]; Tel.: +86-29-8709-2391

Academic Editor: Gonzalo Pajares Martinsanz Received: 12 November 2016; Accepted: 24 January 2017; Published: 31 January 2017

Abstract: A new structure bulk tobacco curing barn was presented. To study the temperature and humidity ﬁeld in the new structure tobacco curing barn, a 3D transient computational ﬂuid dynamics (CFD) model was developed using porous medium, species transport, κ-ε turbulence and discrete phase models. The CFD results demonstrated that (1) the temperature and relative humidity predictions were validated by the experimental results, and comparison of simulation results with experimental data showed a fairly close agreement; (2) the temperature of the bottom and inlet area was higher than the top and outlet area, and water vapor concentrated on the top and outlet area in the barn; (3) tobacco loading density and thickness of tobacco leaves had an explicit effect on the temperature distributions in the barn.

Keywords: bulk tobacco curing barn; computational ﬂuid dynamics; temperature and humidity ﬁeld; sensors

1. Introduction In China, the bulk tobacco curing barn has been popularized during the last two decades due to high capacity and curing quality. In 1960, the first farm-scale operation in bulk curing was initiated in North Carolina [1]. Traditional natural ventilation used in the traditional tobacco curing barn was displaced by forced ventilation used in the bulk tobacco curing barn. Different from the traditional tobacco curing barn, the bulk tobacco curing barn added the hot air circulation system and the auto control system, which can save costs of energy and liberate manpower. Due to the application of forced ventilation technology, the diversity of structure of the bulk tobacco curing barn with different air flow directions is gaining a lot of interest in recent tobacco curing studies, specifically, the bulk tobacco curing barns with air rising [2,3], and air descending [4], which are the most common. In general, tobacco flue curing can be divided into yellowing, leaf drying, and stem drying stages [5]. Changes in tobacco flue curing processes are mainly the result of water evaporation and enzymatic reaction [6]. In addition, the quality of curing tobacco is influenced by the air flows, temperature and relative humidity distribution in bulk tobacco curing barn. Computational fluid dynamics (CFD) is increasingly being used to simulate flow field, mass and heat transfer. The capability of CFD modeling to predict air flows and temperature and relative humidity distributions for many applications in thermosyphon [7] and cool store [8] has been demonstrated. Temperature and relative humidity distributions in the tobacco drying process have been studied using artificial neural networks [9]. However, numerical studies focusing on tobacco curing barn were rarely considered. Zhang et al. [10] simulated the temperature field in tobacco oven during the drying process of cut tobacco based on the finite volume method. Wei et al. [11] studied the temperature distribution of tobacco curing barn with experiments and numerical simulation. Bao et al. [12] performed numerical studies for obtaining the temperature, humidity and velocity field

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Sensorssimulation.2017, 17 Bao, 279 et al. [12] performed numerical studies for obtaining the temperature, humidity2 ofand 16 velocity field in the tobacco curing barn. They applied a mixture model and porous medium to simulate the water evaporation process and tobacco leaves. Water-phase was introduced into the in the tobacco curing barn. They applied a mixture model and porous medium to simulate the water curing barn from inlet boundary. Tobacco leaves contained almost all the water in bulk tobacco evaporation process and tobacco leaves. Water-phase was introduced into the curing barn from inlet curing barn. As the water came from tobacco leaves and evaporated in them, it is therefore boundary. Tobacco leaves contained almost all the water in bulk tobacco curing barn. As the water necessary to develop a numerical model that would make possible to introduce water into the came from tobacco leaves and evaporated in them, it is therefore necessary to develop a numerical curing barn from tobacco leaves and predict temperature and relative humidity distributions model that would make possible to introduce water into the curing barn from tobacco leaves and accurately. predict temperature and relative humidity distributions accurately. A new structure bulk tobacco curing barn heated by heat pump was presented and a 3D A new structure bulk tobacco curing barn heated by heat pump was presented and a 3D transient transient CFD model using the species transport and the discrete phase models to predict the CFD model using the species transport and the discrete phase models to predict the temperature and temperature and humidity distributions in the bulk tobacco curing barn was developed in this humidity distributions in the bulk tobacco curing barn was developed in this study. The objectives of study. The objectives of this study were (1) to validate the CFD model with experimental this study were (1) to validate the CFD model with experimental temperature and relative humidity temperature and relative humidity data during the curing process; (2) to study the description of the data during the curing process; (2) to study the description of the temperature and water vapor mass temperature and water vapor mass fraction profiles in the tobacco curing barn; (3) to study the fraction proﬁles in the tobacco curing barn; (3) to study the temperature distributions with different temperature distributions with different porosities and particle average diameters. This can be the porosities and particle average diameters. This can be the basis for tobacco curing process and barn basis for tobacco curing process and barn design optimization. design optimization.

2. Materials and Methods

2.1. Description of the New Bulk Tobacco CuringCuring BarnBarn The new structure bulk tobacco curing barn was 8.2 m long, 2.9 m wide and 3.6 m high, and its total volumevolume waswas 8585 mm33. The barn contained two main parts: a tobacco curing chamber and an air return chamber. The ahead vertical wall was hidden to show internal structure in the curing barn as shown inin FigureFigure1 .1. The The tobacco tobacco curing curing chamber chamber and a thend airthe returnair return chamber chamber were were separated separated by a 0.1 by m a thick0.1 m layerthick oflayer polyurethane of polyurethane foam sandwich foam sandwich panel, andpanel two, and heat two pumps heat onpumps the roof on the provided roof provided heat for theheat radiators for the radiatorson the both on left the and both right left sides and of right the polyurethane sides of the polyurethane foam sandwich foam panel. sandwich There were panel. air holesThere andwere emergency air holes and gates emergency on the polyurethane gates on the foam polyurethane sandwichpanel. foam sandwich A steel frame panel. which A steel was frame 7.3 m long,which 2.7 was m wide7.3 m and long, 2.6 2.7 m highm wide was and placed 2.6 inm curinghigh was chamber. placed Tobacco in curing leaves chamber. were tiedTobacco along leaves sticks ofwere bamboo tied along before sticks being of placedbamboo on before the steel being frame. placed And on bamboo the steel curtains frame. And were bamboo hung on curtains both sides were of steelhung frame on both to protectsides of tobaccosteel frame leaves to protect as shown tobacco in Figure leaves2. as shown in Figure 2.

Figure 1. StructureStructure of of bulk bulk tobacco tobacco curing curing barn barn.. 1. 1.Left Left wall wall;; 2. L 2.eft Leftfan unit fan; unit; 3. Left 3. radiator Left radiator;; 4. Heat 4. Heatpump pump;; 5. Air 5. holes Air holes;; 6. Emergency 6. Emergency gate; gate;7. Steel 7. Steelframe frame;; 8. M 8.oisture Moisture discharged discharged holes holes;; 9. Inlet 9. Inlet;; 10. 10.Polyurethane Polyurethane foam foam sandwich sandwich panel panel;; 11. 11. Tobacco Tobacco curing curing chamber chamber;; 12. 12. A Airir return return chamber chamber;; 13. RightRight radiator;radiator; 14. RightRight fan unit;unit; 15. R Rightight wall wall..

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Figure 2. Tobacco curing chamber. 1. Bamboo curtain; 2. Steel frame; 3. Stick of bamboo; 4. Tobacco leaves. Figure 2. Tobacco curing chamber. 1. Bamboo curtain; 2. Steel frame; 3. Stick of bamboo; 4. Tobacco leaves. The air entered the air return chamber from the inlet of the roof as shown in Figure 1. The main stream, which was heated by the right radiator, went through the right fan unit. After being blown into theThe tobacco air entered curing the air chamber, return chamber the stream from went the through inlet of the tobacco roof as leaves, shown going in Figure up 1 through. The main the moisturestream, which discharged was heated holes, by the the air right holes radiator, and mostly went the through left fan the unit. right The fan a unit.ir that After went being up through blown into air holesthe tobacco and left curing fan unit chamber, returned the the stream tobacco went curing through chamber tobacco through leaves, the going left upfan throughunit, and the the moisture air that wentdischarged up through holes, moisture the air holes discharged and mostly holes the exited left fan the unit. barn The with air moisture. that went up through air holes and left fan unit returned the tobacco curing chamber through the left fan unit, and the air that went up 2.2.through Experimental moisture Setup discharged holes exited the barn with moisture. 2.2. ExperimentalThe tobacco Setup curing process was directed by a general purpose microcontroller, which controlled radiators and moisture discharged holes to satisfy the prescribed temperature and The tobacco curing process was directed by a general purpose microcontroller, which controlled humidity. Four MIAOXIN TH10R-EX integrated temperature and humidity sensors (MIAOXIN, radiators and moisture discharged holes to satisfy the prescribed temperature and humidity. Zhejiang, China; temperature accuracy: 0.5 K; temperature range: 233 to 358 K; humidity accuracy: Four MIAOXIN TH10R-EX integrated temperature and humidity sensors (MIAOXIN, Zhejiang, China; 5% RH; humidity range: 0 to 100% RH) consisting of sensor probes and data loggers were used to temperature accuracy: 0.5 K; temperature range: 233 to 358 K; humidity accuracy: 5% RH; humidity measure and record the temperature and relative humidity inside the tobacco curing chamber range: 0 to 100% RH) consisting of sensor probes and data loggers were used to measure and record during tobacco curing process. Air temperature and relative humidity were logged at four positions the temperature and relative humidity inside the tobacco curing chamber during tobacco curing for every 120 s as shown in Figure 3. One sensor probe (position-1) was mounted near to the right process. Air temperature and relative humidity were logged at four positions for every 120 s as fan. Three sensor probes (position-2, position-3, and position-4) were fixed inside tobacco curing shown in Figure3. One sensor probe (position-1) was mounted near to the right fan. Three sensor chamber at various locations. All the four positions were placed in the same vertical plane which probes (position-2, position-3, and position-4) were ﬁxed inside tobacco curing chamber at various was 0.75 m from the ahead vertical wall, and the data loggers connected with the four sensor probes locations. All the four positions were placed in the same vertical plane which was 0.75 m from the were placed outside the barn. A gravity-measuring device consisting of MEACON MIK-LCS1 ahead vertical wall, and the data loggers connected with the four sensor probes were placed outside gravity sensors (MEACON, Zhejiang, China; accuracy: 0.03% FS; range: 0 to 10 kg), MEACON the barn. A gravity-measuring device consisting of MEACON MIK-LCS1 gravity sensors (MEACON, MIK-BSQW transmitters (MEACON, Zhejiang, China) and MEACON MIK-R200D paperless Zhejiang, China; accuracy: 0.03% FS; range: 0 to 10 kg), MEACON MIK-BSQW transmitters (MEACON, recorder (MEACON, Zhejiang, China) was applied to measure and record the tobacco gravity Zhejiang, China) and MEACON MIK-R200D paperless recorder (MEACON, Zhejiang, China) was changes during tobacco curing process, which is shown in Figure 4. To capture the gravity changes applied to measure and record the tobacco gravity changes during tobacco curing process, which is inside the tobacco curing chamber, three gravity sensors were placed inside and weighed three shown in Figure4. To capture the gravity changes inside the tobacco curing chamber, three gravity sticks of tobacco leaves. Gravity signals transmitted on signal lines to transmitters, and were sensors were placed inside and weighed three sticks of tobacco leaves. Gravity signals transmitted displayed and recorded by paperless recorder every 120 s. The air flow velocity was measured on signal lines to transmitters, and were displayed and recorded by paperless recorder every 120 s. beside the right fan unit, using a TES-1340 hot-wire anemometer (TES, Taipei, Taiwan; accuracy: The air ﬂow velocity was measured beside the right fan unit, using a TES-1340 hot-wire anemometer 0.01 m/s; range: 0 to 30 m/s). (TES, Taipei, Taiwan; accuracy: 0.01 m/s; range: 0 to 30 m/s).

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Figure 3. Distribution of temperature and humidity sensors. FigureFigure 3.3. DistributionDistribution ofof temperaturetemperature andand humidityhumidity sensors.sensors.

Figure 4. Schematic diagram of a gravity-measuring device. 1. Gravity sensors; 2. Tobacco leaves; FigureFigure 4.4. SchematicSchematic diagramdiagram ofof aa gravity-measuringgravity-measuring device.device. 1.1. GravityGravity sensors;sensors; 2.2. TobaccoTobacco leaves;leaves; 3. Signal lines; 4. Transmitters; 5. Paperless recorder. 3.3. SignalSignal lines;lines; 4.4. Transmitters;Transmitters;5. 5. PaperlessPaperless recorder.recorder. 2.3. Mathematical Modeling 2.3.2.3. MathematicalMathematical ModelingModeling The model of the tobacco curing process was based on the following assumptions: The process TheThe modelmodel ofof thethe tobaccotobacco curingcuring processprocess waswas basedbased onon thethe followingfollowing assumptions:assumptions: TheThe processprocess was modeled in 3D; The tobacco leaves zones were assumed to be porous medium; The evaporation waswas modeledmodeled in in 3D; 3D; The The tobacco tobacco leaves leaves zones zones were were assumed assumed to to be be porous porous medium; medium The; The evaporation evaporation of of water in tobacco leaves was modeled, and the respiration of tobacco leaves during the curing waterof water in tobacco in tobacco leaves leaves was modeled,was modeled, and the and respiration the respiration of tobacco of tobacco leaves during leaves the during curing the process curing process was neglected; The air flow in the tobacco leaves zones was regarded as incompressible and wasprocess neglected; was neglected The air; flow The inair the flow tobacco in the leavestobacco zones leaves was zones regarded was regarded as incompressible as incompressible and laminar and laminar due to the low velocity; The effect of the air return chamber and steel frame in the tobacco duelaminar to the due low to velocity; the lowThe velocity effect; The of the effect air return of the chamberair return and chamber steel frame and insteel the frame tobacco in curingthe tobacco barn curing barn was neglected; And heat exchange with the surroundings was negligible. wascuring neglected; barn wa Ands neglected heat exchange; And heat with exchange the surroundings with the surroundings was negligible. was negligible. The following governing equations depend on the assumptions mentioned above. TheThe followingfollowing governinggoverning equationsequations dependdepend onon thethe assumptionsassumptions mentionedmentioned above.above. The continuity equation which can be also called the mass conservation equation for the fluid TheThe continuitycontinuity equation equation which which can can be be also also called called the the mass mass conservation conservation equation equation for thefor fluidthe fluid (air (air and water vapor) as follows [13]: and(air waterand water vapor) vapor) as follows as follows [13]: [13]:  ((uu)) ((vv)) ((ww)) ∂ρ  ∂(ρu)  ∂(ρv) ∂(ρw)  SM (1) t + x + y + z =SSM ((1)1) ∂tt ∂xx ∂yy ∂zz M where ρ (kg·m−3) is the fluid density, t (s) is the time, x, y, and z (m) are the three space directions, μ, where ρ (kg·m−−3) is the fluid density, t (s) is the time, x, y, and z (m) are the three space directions, μ, where ρ (kg·m−1 ) is the fluid density, t (s) is the time, x, y, and z (m) are the three space directions,−3µ,−ν1 , ν, and ω (m·s −1) are the velocity components according the direction of x, y, and z, and SM (kg·m −3·s −1) ν, and ω (m· −·1s ) are the velocity components according the direction xof yx, y, andz z, andS SM (·kg·−m3· ·−s1 ) andis theω water(m s vapor) are themass velocity source. components according the direction of , , and , and M (kg m s ) isis thethe waterwater vaporvapor massmass source.source. TheThe momentummomentum equationequation asas followsfollows [13][13]::

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The momentum equation as follows [13]:

∂(ρu) ∂p + div(ρuu) = div(µgrad u) − + S (2) ∂t ∂x u

∂(ρv) ∂p + div(ρvu) = div(µgrad v) − + S (3) ∂t ∂y v ∂(ρw) ∂p + div(ρwu) = div(µgrad w) − + S (4) ∂t ∂z w where p is the pressure (Pa), u is the velocity vector (m·s−1), µ is the dynamic viscosity of the ﬂuid −1 −1 −3 (kg·m ·s ), and Su, Sv, and Sw are the momentum source term components (N·m ) according the direction of x, y, and z. The momentum source term contains viscosity loss and inertial loss for porous medium as follows [13]: 3 3 1 Si = ∑ Dijµvj + ∑ Cij ρ vj vj (5) j=1 j=1 2 where i = u, v, w, D and C are given matrix. The energy equations as follows [13]:

[ + ( − ) ] " ! # ∂ γρ f Ef 1 γ ρsEs h i h + ∇ · v ρ f Ef + v = ∇ · Ke f f ∇T − ∑ hi Ji + (τ · v) + S f (6) ∂t i

ke f f = γk f + (1 − γ)ks (7) −1 where Ef is the ﬂuid energy (J·kg ), and Es is the tobacco energy, ρf is the tobacco density, γ is the −1 porosity of the porous medium, T is the temperature (K), hi is the enthalpy of species i (J·kg ), τ h −3 is the shear stress tensor (Pa), and Sf is the heat source (W·m ), Keff is the thermal conductivity −1 −1 (W·m ·k ) of the porous medium, kf is the thermal conductivity of the ﬂuid, and ks is the thermal conductivity of the tobacco. The transport equations for species s as follows [13]:

∂(ρc ) s + div(ρuc ) = div[D grad(ρc )] + S (8) ∂t s s s s where cs is the volume fraction of species s (%), and Ss is the production rate of water vapor (kg·m−3·t−1). The Reynolds number in the tobacco curing chamber was calculated by using the following equation [14]: −1 Re = ρvdη (9) where η is the viscosity of the ﬂuid (kg/ms). The κ-ε models remain popular because of their availability in user-friendly codes, which allow a straightforward implementation of the models, and because they are cheap in terms of computation time [15]. The standard κ-ε model has obtained applications in cheese-ripening room [16] and large food chillers room [17]. And the standard κ-ε model, proposed by Launder and Spalding in 1972, was used in this model [18].

2.4. CFD Grid The study focused on the tobacco curing chamber of the barn. Three-dimensional geometry of tobacco curing chamber was created, and the mesh was generated using ICEM CFD and exported to the ANSYS FLUENT for further processing. Figure5 shows a schematic diagram of CFD mesh of the tobacco curing barn. Structured grid calculations usually take less time than an unstructured grid calculation [19]. A structured mesh made of hexahedral cells was used in this study. Blocking method is used for generating structured mesh, and mesh was equally spaced with 50 mm mesh spacing. Total Sensors 2017, 17, 279 6 of 16 Sensors 2017, 17, 279 6 of 15 numbersspacing. Total of faces numbers are 1,944,245 of faces with are 635,1021,944,245 cells. with Minimum 635,102 orthogonalcells. Minimum quality orthogonal was 1 and quality maximum was aspect1 and m ratioaximum was 3.67aspect which ratio showed was 3.67 a goodwhich quality showed of a the good mesh. quality of the mesh.

Figure 5. ComputationalComputational fluid ﬂuid dynamics dynamics ( (CFD)CFD) mesh mesh of of the the tobacco tobacco curing curing barn barn.. 1. 1.Velocity Velocity inlet inlet;; 2. 2.Moisture Moisture discharged discharged hole hole;; 3. 3.Outlet Outlet;; 4. 4.Air Air holes holes;; 5. 5.Bamboo Bamboo curtain curtain;; 6. P 6.orous Porous zones zones..

2.5. B Boundaryoundary Conditions

2.5.1. V Velocityelocity Inlet There was one velocity inlet, and the air velocity velocity,, which was measured by anemometer,anemometer, had a uniform value of 33 m/s.m/s. The The inlet inlet air temperature and the mass fraction of water vapor were time dependent, and a u userser d deﬁnedefined f functionunction (UDF)(UDF) was used to describe the inlet air temperature and mass fraction fraction of of water water vapor vapor proﬁles profiles with with the time, the timeon the, on basis the of basis the measurement of the measurement data of position-1 data of measuredposition-1 bymeasured temperature by temperature and humidity and sensor. humidity And turbulentsensor. And intensity turbulent and intensity hydraulic and diameter hydraulic was calculateddiameter was by applyingcalculated the by following applying equationsthe following [20]: equations [20]: 1 −1 I = 00.16Re.16 Re 88 (10(10))

−11 DDHH=44APAPww (11(11)) 2 where A isis thethe inletinlet areaarea (m(m2), and Pw is the wetted perimeter (m).

2.5.2. Pressure Outlet 2.5.2. Pressure Outlet There were thirty-three pressure outlets, thirty for the air holes, two for the moisture discharged There were thirty-three pressure outlets, thirty for the air holes, two for the moisture discharged hole, and one for the outlet (left fan unit). A pressure of 1 atm was assumed at all the pressure outlet. hole, and one for the outlet (left fan unit). A pressure of 1 atm was assumed at all the pressure outlet. Turbulent intensity and hydraulic diameter was calculated by using Equations (10) and (11). Turbulent intensity and hydraulic diameter was calculated by using Equations (10) and (11).

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Sensors 17 2.5.3. W2017alls, , 279 7 of 16 All the boundaries except the velocity inlet and pressure outlets boundaries were the walls, and 2.5.3.all the Walls walls were assumed to be insulated. The standard wall functions were applied on the walls. All the boundaries except the velocity inlet and pressure outlets boundaries were the walls, and all2.5.4. the Porous walls were Medium assumed to be insulated. The standard wall functions were applied on the walls. The tobacco leaves were placed closely enough and simplified to six porous zones, with three 2.5.4. Porous Medium columns and two rows. Each of the six porous zones (the green area) was 7.3 m long, 1.3 m wide and 0.7 mThe high tobacco as shown leaves in were Figure placed 6. The closely porosity enough of and porous simpliﬁed zone was to six calculated porous zones, by applying with three the columnsfollowing and equations two rows. [20] Each: of the six porous zones (the green area) was 7.3 m long, 1.3 m wide and 0.7 m high as shown in Figure6. The porosity of porous zone was calculated by applying the following 1 equations [20]: r  1 (12) ρ1 r = 1 − d (12) ρd where ρ1 = 45.5 kg/m3 is the bulk density, and ρd = 515 kg/m3 is the apparent density [21]. Viscous 3 3 whereresistanceρ1 = factor 45.5 kg/m and inertialis the bulkresistance density, factor and wereρd = 515 used kg/m to calculateis the apparent the momentum density [source21]. Viscous term, resistanceand they were factor calculated and inertial by resistanceapplying the factor following were used equations to calculate [20]: the momentum source term, and they were calculated by applying the following equations [20]: 1 150（1- r）2 2 1 150(1 2− r) (13) = d r 3 (13) p2 3 α dp r 3.（5 1- r） C 3.5(1 − r) 2= 3 (14) C2 d r3 (14) dppr wherewhere ddpp = 0.01 m is the particle average diameter, and r isis thethe porosityporosity ofof porousporous zone.zone. The particle average diameter waswas regardedregarded asas thicknessthickness ofof tobaccotobacco leavesleaves inin thisthis model.model.

Figure 6.6. Schematic diagram of eighteen surfaces.surfaces. 1. Porous zones; 2. Surfaces.

2.5.5. Discrete Phase Model InIn order order to to introduce introduce water water droplets droplets into into the curingthe curing barn frombarn tobacco from tobacco leaves during leaves theduring tobacco the curingtobacco process, curing process,the discrete the phase discrete model phase (DPM) model and (DPM) species and transport species transport model in modelANSYS in FLUENT ANSYS wereFLUENT implemented. were implemented. The water The droplets waterwere droplets injected were into injected the tobacco into the curing tobacco chamber curing fromchamber eighteen from surfaceseighteen (the surfaces black planes),(the black which planes) distributed, which throughout distributed the throughout porous zones the (the porous green zones areas) (the as shown green inareas) Figure as 6shown. The surfacesin Figure injected 6. The 148,176surfaces particleinjected parcels 148,176 per particle DPM parc iteration.els per The DPM total iteration. mass ﬂow The oftotal water mass droplets flow of was water calculated droplets from was the calculated gravity changes from the of tobacco gravity leaveschanges measured of tobacco by gravity leaves sensors.measured According by gravity to the sensors measurement. According data to of the gravity measurement changes, the data whole of gravity tobacco changes, curing process the whole can betobacco divided curing into process four phases, can be and divided the total into mass four ﬂow phases, of water and the droplets total mass were 0.00465flow of kg/swater from droplets 0 to

Sensors 2017, 17, 279 8 of 15 wereSensors 0.004652017, 17, 279kg/s from 0 to 57,600 s, 0.00295 kg/s from 57,600 to 141,000 s, 0.0036 kg/s from 1418, of000 16 to 344,400 s and 0 kg/s from 344,400 to 397,200 s, respectively. This model can realize the water droplets evaporating inside the porous zones just like the actual situation in which water evaporate 57,600 s, 0.00295 kg/s from 57,600 to 141,000 s, 0.0036 kg/s from 141,000 to 344,400 s and 0 kg/s from inside tobacco. 344,400 to 397,200 s, respectively. This model can realize the water droplets evaporating inside the porous zones just like the actual situation in which water evaporate inside tobacco. 2.5.6. Initial Conditions 2.5.6.Prior Initial to Conditionsthe experiment, sticks of tobacco leaves were placed on the steel frame in the tobacco curingPrior barn. to The the experiment,initial temperature sticks ofand tobacco relative leaves humidity were placedof the barn on the was steel assumed frame to in thebe uniform tobacco atcuring 303 K barn. and 100 The% initial RH, which temperature was measured and relative by temperature humidity of and the humidity barn was sensor assumeds. The to besimulation uniform usedat 303 a Ktransient, and 100% pressure RH, which-based was solver measured and SIMPLE by temperature pressure– andvelocity humidity coupling sensors. algorithm The simulation. And the timeused step a transient, size was pressure-based chosen to be 120 solver s, which and SIMPLEhad the same pressure–velocity interval as the coupling data acquisition algorithm. sensors And the in thetime experiment. step size was chosen to be 120 s, which had the same interval as the data acquisition sensors in the experiment. 3. Results and Discussion 3. Results and Discussion 3.1. Grid Sensitivity and Computational Validation 3.1. Grid Sensitivity and Computational Validation Grid sensitivity tests were performed employing the three different meshes summarized in TableGrid 1. A sensitivity vertical line tests was were in performed the middle employing of a vertical the three plane, different which meshes was 0.75 summarized m from the in Table ahead1. verticalA vertical wall line. The was temperature in the middle profiles of a vertical along the plane, vertical which line was for 0.75the three m from meshes the ahead were compared vertical wall. in FigureThe temperature 7. Mesh1 profiles(the coarsest) along thedid verticalnot show line the for same the three temperature meshes were profile compared as observed in Figure with7. Mesh1mesh2 and(the coarsest)mesh3. Mesh3 did not (the show finest) the same can result temperature in very profile high resolution as observed of with com mesh2putational and mesh3. results, Mesh3 but it needed(the finest) more can time result for in calculation. very high resolution It was concluded of computational that the results, optimal but computational it needed more mesh time was for mesh2.calculation. It was concluded that the optimal computational mesh was mesh2.

TableTable 1 1.. InformationInformation on on the the meshes in the sensitivity tests tests..

Mesh1Mesh1 Mesh2Mesh2 Mesh3 Mesh3 Cells Cells65,355 65,355 635,102635,102 1,973,366 1,973,366 Faces Faces204,666 204,666 1,944,2451,944,245 6,003,052 6,003,052 Nodes Nodes741,88 741,88 674,531674,531 3,057,028 3,057,028

305 Mesh3 Mesh2 Mesh1

304

303

Temperature (K) Temperature

302 0 1 2 3 4 Height (m) FigureFigure 7. 7. TemperatureTemperature profiles proﬁles along the vertical line for mesh1, mesh2 and mesh3 mesh3..

ThreeThree-dimensional-dimensional transienttransient state state computations computations have been have performed. been performed. The time wise The temperature time wise temperatureand humidity and proﬁles humidity in the profile tobaccos in curing the tobacco barn werecuring measured barn were by measured the four integrated by the four temperature integrated temperatureand humidity and sensors. humidity The experimentalsensors. The temperatureexperimental and temperature humidity measurementsand humidity atmeasurements position-1 were at pousedsition for-1 the were inlet used boundary for the condition. inlet boundary In order condition. to validate In the order CFD simulationto validate model the CFD for the simulation tobacco modelcuring for barn, the the tobacco temperature curing andbarn, relative the temperature humidity predictions and relative at position-2,humidity predictions position-3 andat position position-4-2, positionwere compared-3 and position with the-4 experimentalwere compared temperature with the experimental and relative humiditytemperature measurements and relative in humidity Figure8. measurementThe temperatures inand Figure relative 8. The humidity temperature predictions and showed relative good humidity agreement predictions with the showed experimental good

Sensors 2017, 17, 279 9 of 16 Sensors 2017, 17, 279 9 of 15 temperatureagreement with and the humidity experimental measurements. temperature In Figure and 8 humiditya,b, the difference measurements. between In predictionsFigure 8a,b, and the experimentaldifference between measurements predictions at the and beginning experimen of thetal curing measurements process at at position-2 the beginning can be of explained the curing by theprocess fact thatat position in the experiment,-2 can be explained the humidity by the at fact position-2 that in the was experiment, higher than the we humidity measured. at Theposition errors-2 existedwas higher in the than measurements, we measured. which The were errors measured existed in by the integrated measurements, temperature which and were humidity measured sensors by andintegrated gravity tem sensors.perature The and gravity humidity measurements sensors and were gravity used to sensors. estimate The the gravity gravity measurements of tobacco leaves were in theused tobacco to estimate curing the barn. gravity There of were tobacco also some leaves discrepancies in the tobacco between curing predictions barn. There and were experimental also some measurementsdiscrepancies between at position-2 predictions and position-3 and experimental in Figure8a–d, measurements and they were at position mainly caused-2 and byposition the water-3 in estimationFigure 8a–d, error and in they tobacco were leaves. mainly caused by the water estimation error in tobacco leaves.

FigureFigure 8.8. Comparison between CFD simulation and experiment of the temperature temperature and and relative relative humidityhumidity atat position-2,position-2, position-3position-3 andand position-4.position-4.

As presented in Table 2, comparing the simulated temperature and relative humidity profile to the measured data at position-2, position-3 and position-4, leads to an average RMS error of 2.61%

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As presented in Table2, comparing the simulated temperature and relative humidity profile to the measured data at position-2, position-3 and position-4, leads to an average RMS error of 2.61% for temperature and 5.66% for relative humidity, while the average coefficient of correlation between the simulated values and the measured values were 0.98 and 0.98 for temperature and relative humidity, respectively. Because of the high coefficient of correlation and low RMS error, the predicted temperature and humidity profiles can be used to estimate and analyze the temperature and humidity distributions in the tobacco curing barn.

Table 2. Root mean square (RMS) error and coefﬁcient of correlation compared to the measured temperature and relative humidity.

P-2 (T/K) P-2 (RH/%) P-3 (T/K) P-3 (RH/%) P-4 (T/K) P-4 (RH/%) Coefﬁcient of correlation 0.97 0.98 0.99 0.98 0.99 0.98 RMS error 3.88 6.57 2.61 5.27 1.34 5.13

3.2. Temperature Distributions According to the tobacco curing process, it can be divided into four stages, 1 s to 210,000 s, 210,001 s to 255,000 s, 255,001 s to 315,000 s, 315,000 s to 397,200 s. Each stage can be divided into temperature rise and temperature control, and the temperature control takes much longer than the temperature rise. The temperature distributions comparing three different cross-sections of the tobacco curing chamber at 108,000 s are presented in Figure9. The cross-section Y1 (0.75 m from the ahead vertical wall) cross the middle of three left porous zones. And the cross-sections Y2 (1.35 m from the ahead vertical wall) and cross-sections Y3 (1.45 m from the ahead vertical wall) cross the edge of three left porous zones and the middle of the tobacco curing chamber, respectively. It can be observed from Figure9 that the temperature of bottom region is higher than the top region, and the temperature of inlet region is higher compared to the outlet region. The temperature distributions on cross-section Y1 are more uniform compared to the cross-section Y2 and Y3. And the direction of airflow is from right to left. The average temperatures on cross-section Y1, cross-section Y2 and cross-section Y3 are 312.55 K, 313.12 K and 313.82 K, respectively. This demonstrates that the inside of the porous zones stays about 1 K cooler than the outside temperature; this could be the reason of water evaporating and heat absorption inside the porous zones. The temperature profiles across three different cross-sections at 97,200 s, 217,200 s, 277,200 s and 337,200 s of tobacco curing time are presented in Figure 10. The left cross-section is 1.3 m from the left wall, the middle cross-section is 4.2 m from the left wall, and the right cross-section is 6.7 m from the left wall. It can be seen from the Figure 10 that the temperatures of porous zones increase with the increase of temperature in the curing barn, and the average temperature differentials on the left cross-section, middle cross-section and right cross-section are 6 K, 4.5 K and 1.5 K, respectively. The temperature differential on the left cross-section is 4.5 K more compared to the right cross-section, which may be due to the direction of airflow. The temperatures in the top region of the tobacco curing barn are slightly less compared to the bottom region, and the low temperature regions on the top of middle cross-section are larger compared to the left cross-section and right cross-section, which may be due to the cool air accumulation at the top. Also, the temperature gradients on the left cross-section are obvious, with low temperatures on the top and high temperatures on the bottom. It can be observed from Figure 10 that the temperature distributions in the tobacco curing barn are similar in both sides of the porous zones and in the four stages of the tobacco curing process. According to the simulated temperature profiles, the temperature distributions in the tobacco curing barn can be predicted using the measurements taken by temperature sensors. Sensors 2017, 17, 279 10 of 15

for temperature and 5.66% for relative humidity, while the average coefficient of correlation between the simulated values and the measured values were 0.98 and 0.98 for temperature and relative humidity, respectively. Because of the high coefficient of correlation and low RMS error, the predicted temperature and humidity profiles can be used to estimate and analyze the temperature and humidity distributions in the tobacco curing barn.

Table 2. Root mean square (RMS) error and coefficient of correlation compared to the measured temperature and relative humidity.

P-2 (T/K) P-2 (RH/%) P-3 (T/K) P-3 (RH/%) P-4 (T/K) P-4 (RH/%) Coefficient of correlation 0.97 0.98 0.99 0.98 0.99 0.98 RMS error 3.88 6.57 2.61 5.27 1.34 5.13

Sensors 2017, 17, 279 11 of 15

The temperature profiles across three different cross-sections at 97,200 s, 217,200 s, 277,200 s and 337,200 s of tobacco curing time are presented in Figure 10. The left cross-section is 1.3 m from the left wall, the middle cross-section is 4.2 m from the left wall, and the right cross-section is 6.7 m from the left wall. It can be seen from the Figure 10 that the temperatures of porous zones increase with the increase of temperature in the curing barn, and the average temperature differentials on the left cross-section, middle cross-section and right cross-section are 6 K, 4.5 K and 1.5 K, respectively. The temperature differential on the left cross-section is 4.5 K more compared to the right cross-section, which may be due to the direction of airflow. The temperatures in the top region of the tobacco curing barn are slightly less compared to the bottom region, and the low temperature regions on the top of middle cross-section are larger compared to the left cross-section and right cross-section, which may be due to the cool air accumulation at the top. Also, the temperature gradients on the left cross-section are obvious, with low temperatures on the top and high temperatures on the bottom. It can be observed from Figure 10 that the temperature distributions in the tobacco curing barn are similar in both sides of the porous zones and in the four stages of the tobacco curing process. According to the simulated temperature profiles, the temperature distributionsFigure 9.9. Temperature in the tobacco distributions curing comparing barn can three be predicted different cross cross-sections usin-sectionsg the measurements( (Y1,Y1, Y2 and Y3 Y3)) of taken the by temperaturetobacco curing sensors. chamber at 108 108,000,000 s s..

FigureFigure 10 10.. TemperatureTemperature profiles proﬁles across across three three different different cross cross-sections-sections ( (1.31.3 m, m, 4.2 4.2 m, m, and and 6.7 6.7 m m from from the the leftleft wall) wall) at at ( (aa)) 97 97,200,200 s s;; ( (bb)) 217 217,200,200 s s;; ( (cc)) 277 277,200,200 s s and and ( (d)) 337 337,200,200 s s..

3.3. Water Vapor Mass Fraction Distributions 3.3. Water Vapor Mass Fraction Distributions The water vapor mass fraction distributions on the cross-section Y1, cross-section Y2 and The water vapor mass fraction distributions on the cross-section Y1, cross-section Y2 and cross-section Y3 at 108,000 s are presented in Figure 11. It can be seen from Figure 11 that the mass cross-section Y3 at 108,000 s are presented in Figure 11. It can be seen from Figure 11 that the mass fraction of vapor near the top wall is more when compared to the center and bottom of the tobacco curing barn due to the low density of vapor and the direction of air flow. The temperature gradients on the left side are more obvious compared to the right side on the cross-section Y1, cross-section Y2 and cross-section Y3 with high vapor mass fraction on the top and low vapor mass fraction on the bottom. The average water vapor mass fractions on cross-section Y1, cross-section Y2 and cross-section Y3 are 0.0371 kg/kg, 0.0369 kg/kg and 0.0366 kg/kg, respectively. This demonstrates that the inside of the porous zones stays about 0.0005 kg/kg more than the outside water vapor mass fraction, and this also can be the result of water evaporating inside the porous zones. Water

Sensors 2017, 17, 279 12 of 16 fraction of vapor near the top wall is more when compared to the center and bottom of the tobacco curing barn due to the low density of vapor and the direction of air ﬂow. The temperature gradients on the left side are more obvious compared to the right side on the cross-section Y1, cross-section Y2 and cross-section Y3 with high vapor mass fraction on the top and low vapor mass fraction on the bottom. The average water vapor mass fractions on cross-section Y1, cross-section Y2 and cross-section Y3 are 0.0371 kg/kg, 0.0369 kg/kg and 0.0366 kg/kg, respectively. This demonstrates that the inside of the porousSensors 2017 zones, 17, stays279 about 0.0005 kg/kg more than the outside water vapor mass fraction, and this12 alsoof 15 can be the result of water evaporating inside the porous zones. Water vapor accumulations form the highvapor vapor accumulation mass fractions form regions the high on the vapor top ofmass the tobaccofraction curingregions barn. on the The top high ofvapor the tobacco mass fraction curing regionsbarn. The have high low vapor temperature mass fraction because regions of the have water low evaporating. temperature The because same of result the water can be evaporating obtained in. FigureThe same9. This result means can that be the obtained water vapor in Figure mass fraction 9. This distributionsmeans that arethe relatedwater with vapor the mass temperature fraction distributionsdistributions onare the related same with position. the temperature distributions on the same position.

FigureFigure 11.11.Water Water vapor vapor mass mass fraction fraction distributions distributions on the on cross-sections the cross-sections (Y1, Y2, (Y1 and, Y2 Y3), and of theY3 tobacco) of the curingtobacco chamber curing chamber at 108,000 ats. 108,000 s.

3.4.3.4. PorosityPorosity andand ParticleParticle AverageAverage DiameterDiameter TheThe porosity can can be be calculated calculated with with Equation Equation (12), (12), and and tobacco tobacco leaves leaves with with higher higher porosity porosity had hadlower lower loading loading density. density. Figure Figure 12 shows 12 shows the temperature the temperature profiles proﬁles on the on cross the- cross-sectionsection (0.8 m (0.8 from m fromground) ground) at 3000 at 3000 s with s with different different porosities porosities of ofporous porous zones. zones. The The average average temperatures temperatures on the the cross-sectioncross-section withwith differentdifferent porositiesporosities (a(a == 0.79,0.79, bb == 0.85,0.85, cc == 0.88, and d = 0.93) are 303.92 K,K, 305.22 K,K, 304.98304.98 KK andand 306.78306.78 K, K, respectively. respectively. The The average average temperature temperature differential differential between between Figure Figure 12a,d 12a, cand can be 2.86be 2.86 K under K under thesame the same circumstance. circumstance The average. The average temperature temperature increases increases with the with increase the increaseof porosity. of Theporosity. average The temperature average temperature in Figure 12 inb isFigure slightly 12b higher is slightly compared higher to compared Figure 12c, to because Figurethe 12c, air because which heatthe air is absorbedwhich heat by is water absorbed evaporation by water moves evaporation more slowly.moves more The temperature slowly. The proﬁlestemperature in Figure profiles 12 in Figure 12 clearly emphasize that increase in porosity causes an enhanced heat transfer. This shows that with higher tobacco loading density, there is a negative effect on heat transfer. The particle average diameter had a relationship with the flow resistivity and the bulk density, affecting the movement of airflow [22]. In this model, the particle average diameter is relative to thickness of tobacco leaves, and different thicknesses of tobacco leaves are assumed to have the same capacity of moisture retention. Figure 13 depicts the temperature profiles on the cross-section (0.8 m from ground) at 38,400 s with different particles average diameters (a = 0.008 m, b = 0.01 m, c = 0.02 m, and d = 0.05 m) of porous zones. It can be seen from the Figure 13 that the low temperature region (the green area in Figure 13) appears at 1.9 m, 2.1 m, 2.4 m and 2.9 m from the right wall with the increase of the particle average diameter, and the direction of airflow is from right to left. The low temperature region means position of the air which heat is absorbed by water

Sensors 2017, 17, 279 13 of 16 Sensors 2017, 17, 279 13 of 15 evaporation.clearly emphasize The air that in increaseFigure 13 ind porositymoves faster causes than an the enhanced air in Figure heat transfer. 13a. This This shows shows that that the withheat transferhigher tobacco become loading faster with density, the increase there is a of negative thickness effect of tobacco on heat leaves. transfer.

Figure 12.12. TemperatureTemperature profiles proﬁles on the cross cross-section-section (0.8 (0.8 m from ground) at 3000 s with different porosities (a = 0.79, b = 0.85, 0.85, c c = = 0.88, 0.88, and and d d = = 0.93) 0.93) of of porous porous zones zones..

The particle average diameter had a relationship with the flow resistivity and the bulk density, affecting the movement of airflow [22]. In this model, the particle average diameter is relative to thickness of tobacco leaves, and different thicknesses of tobacco leaves are assumed to have the same capacity of moisture retention. Figure 13 depicts the temperature profiles on the cross-section (0.8 m from ground) at 38,400 s with different particles average diameters (a = 0.008 m, b = 0.01 m, c = 0.02 m, and d = 0.05 m) of porous zones. It can be seen from the Figure 13 that the low temperature region (the green area in Figure 13) appears at 1.9 m, 2.1 m, 2.4 m and 2.9 m from the right wall with the increase of the particle average diameter, and the direction of airflow is from right to left. The low temperature region means position of the air which heat is absorbed by water evaporation. The air in Figure 13d moves faster than the air in Figure 13a. This shows that the heat transfer become faster with the increase of thickness of tobacco leaves.

Figure 13. Temperature profiles on the cross-section (0.8 m from ground) at 38,400 s with different particles average diameters (a = 0.008 m, b = 0.01 m, c = 0.02 m, and d = 0.05 m) of porous zones.

Sensors 2017, 17, 279 13 of 15 evaporation. The air in Figure 13d moves faster than the air in Figure 13a. This shows that the heat transfer become faster with the increase of thickness of tobacco leaves.

SensorsFigure2017, 17 1,2 279. Temperature profiles on the cross-section (0.8 m from ground) at 3000 s with different14 of 16 porosities (a = 0.79, b = 0.85, c = 0.88, and d = 0.93) of porous zones.

Figure 1 13.3. Temperature profiles proﬁles on the cross cross-section-section (0.8 m from ground) at 38 38,400,400 s with different particles average diameters (a = 0.008 m, b = 0.01 0.01 m, m, c c = = 0.02 0.02 m, m, and and d d = = 0.05 0.05 m) m) of of porous porous zones zones..

4. Conclusions A 3D transient CFD model was developed for the new bulk tobacco curing barn using porous medium, species transport, κ–ε turbulence and discrete phase models in the present study. This model can realize the water droplets evaporating inside the porous zones just like the actual situation where the water evaporates inside tobacco. The following conclusions will be helpful to optimize the process of tobacco curing. (1) The CFD model was validated using the temperature and relative humidity data that were recorded during the tobacco curing process using integrated temperature and humidity sensors. Comparison of simulation results with experimental data showed a fairly close agreement. The CFD model is able to produce a good qualitative insight into the temperature and humidity distribution in the new bulk tobacco curing barn. (2) The temperature of the bottom region was higher than the top region in the barn. The temperature decreased following the direction of airﬂow, and the temperatures inside porous zones were higher than outside porous zones. According to the temperature distribution in tobacco curing chamber, thick leaves which need higher temperature can load on the bottom and inlet area, and thin leaves which need lower temperature can load on the top and outlet area. Water vapor concentrated on the top and outlet area in the barn, and the position of moisture discharged holes can be adjusted due to the distribution of water vapor. (3) Tobacco loading density and thickness of tobacco leaves had an explicit effect on the temperature distributions in the barn. Tobacco loading density had negative effect on heat transfer, and thickness of tobacco leaves had a positive effect on heat transfer. The curing technology can be adjusted due to the actual tobacco loading density and thickness of tobacco leaves. The temperature and humidity distributions in the tobacco curing barn can be studied by using the CFD model. Additionally, during the curing process, the temperature and humidity distributions can be predicted by the measurements measured by limited temperature and humidity sensors. This can Sensors 2017, 17, 279 15 of 16 be used for tobacco curing process and barn design optimization, and it can save the cost and improve the tobacco curing quality and production efﬁciency.

Acknowledgments: This work was supported by Natural Science Foundation of China (31671965), cooperation project with Xi’an Senwas Agricultural Science & Technology Company. Author Contributions: Zhipeng Bai, Yaohua Hu have contributed to all phases of the work (CFD modelling, experiments, data analysis, and report writing); Zhipeng Bai, Duoduo Guo, Shoucang Li performed the experiments and analyzed the data; Zhipeng Bai, Yaohua Hu contributed to the CFD modeling and report writing. Conﬂicts of Interest: The authors declare no conﬂict of interest.

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