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Effects of initial mist conditions on simulation accuracy of humidity distribution in an environmental chamber
Building and Environment 47 (2012) 217e222
Contents lists available at ScienceDirect
Building and Environment journal homepage: www.elsevier.com/locate/buildenv
Effects of initial mist conditions on simulation accuracy of humidity distribution in an environmental chamber Liang Pu a, b, *, Fu Xiao a, **, Yanzhong Li b, Zhenjun Ma a a b
Department of Building Services Engineering, The Hong Kong Polytechnic University, Hong Kong Institute of Refrigeration and Cryogenic Engineering, Xi’an Jiaotong University, Xi’an 710049, China
a r t i c l e i n f o
a b s t r a c t
Article history: Received 31 March 2011 Received in revised form 12 June 2011 Accepted 22 July 2011
This paper firstly presents experimental study of humidity distribution in an environmental chamber at different inlet temperatures and humidity. Experiment results show that, under fixed inlet temperature condition, the uniformity of the relative humidity (RH) in the chamber is better when the inlet RH is higher. It is mainly because of the coupled heat and mass transfer occurred between water droplets and air. In practice, direct measurement of humidity distribution in a chamber is infeasible and CFD simulation is a possible way to predict the humidity distribution. However, the use of CFD tools for predicting humidity field is rarely reported. Boundary and initial mist conditions are critical to the accuracy and computation efficiency of CFD simulation. This study then presents a CFD simulation method of the humidity distribution inside chamber using FLUENT based on some assumptions and simplification. Moreover, droplet sizes were measured by laser diffraction analyzer. The simplified droplet size distribution is used as initial condition for CFD simulation. Experiment results and CFD simulation results are compared and it can be concluded that the CFD simulation method can achieve satisfactory accuracy with reasonable computation load. Ó 2011 Elsevier Ltd. All rights reserved.
Keywords: Humidity distribution Environmental chamber Droplet size distribution CFD simulation
1. Introduction Environmental test chambers play essential roles in testing advanced devices, equipment and materials [1e3]. To satisfy various test purposes, environment parameters, such as temperature, humidity and air velocity, in chambers must be precisely controlled at required set-points. Temperature, air velocity and particle distribution in built environment were well studied using experiment tests and CFD simulation tools. Stable and uniform humidity distribution in a test chamber is often required for many tests [3]. Inlet conditions have significant effects on the humidity distribution in an environmental chamber. Inappropriate inlet conditions may cause undesired humidity distribution and consequently unreliable test results. Though the CFD method has been proved to be powerful and reliable for simulating fluid fields, research work on estimation of simultaneous heat and moisture transfer and resulting humidity distribution are limited. J. Liu [4] applied a new method to study
* Corresponding author. Institute of Refrigeration and Cryogenic Engineering, Xi’an Jiaotong University, Xi’an 710049, China. ** Corresponding author. E-mail addresses: [email protected] (L. Pu), [email protected] (F. Xiao). 0360-1323/$ e see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.buildenv.2011.07.020
heat and moisture transfer between free water surface and surrounding air by experiment and CFD simulation. The influence of surrounding air temperature and humidity, water temperature and water surface area on the moisture and heat transfer was studied. Sureshkumar et al. [5,6] researched the heat and mass transfer processes between a water spray and surrounding air. The results showed that, under a given water flow rate, a smaller nozzle with higher pressures can produce more cooling than a large nozzle with lower pressures. Manzan and Saro [7] analyzed the numerical simulation of temperature field, flow field and humidity diffusion of the indoor air. An original approach to solve a coupled heat and mass transfer problem was presented in order to obtain an estimate of the thermal cooling flux on the wet surface using CFX 4.4 commercial program. A few of experimental studies and numerical predictions have been conducted to study humidity distribution and temperature field. The literature [8] studied the heat demand and the heat and mass transfer based on the public baths. A parametric study showed that the temperature and RH in the building strongly influence the heating demand inside room. B.W. Zingano [9] carried the experimental studies and discussed the importance of humidity to the thermal comfort temperatures. The influence of the indoor and outdoor temperature difference on the loss of moisture content and change of humidity in the air-conditioning system was studied
218
L. Pu et al. / Building and Environment 47 (2012) 217e222
by Aristov et al. [10]. Mutual influence among the parameters exists in the control of ambient humidity. The influence of ambient humidity and indoor humidity to the indoor temperature, i.e. the interacting relationship of all kinds of aspects such as humidity, temperature and other factors, was studied by Gaur et al. [11]. The interacting among the conduction, convection, and radiation heat transfer to the heat-mass exchange was researched by Vasile et al. [12] through the porous media. An initial approach to above problem by attempting to describe the influence of moisture level on heat transfers occurring through bricks was presented. Recently, in order to get optimization results and requirements of comfort or energy saving, influence of different boundary conditions, like inlet locations, airflow rate and others, on the parameter fields was also studied in the simulation study on parameter field and contaminate distribution. In order to supply fresh, humidified air to each person on airplane, P. Zitek et al. [13] presented a novel design method and system to simulate personalized and humidified fresh air for airliner passengers. In this system, every seat in the cabin has a separate air supply inlet and exhaust outlet. To choose the best project, several different inlet and exhaust locations and types were investigated by J.A. Khan et al. [14], and room concentration patterns were calculated by CFD simulations for various inlet and exhaust positions. The results showed that inlet and exhaust locations influenced the contaminant concentrations in a workroom. Further study on accurate thermal boundary conditions on predictive accuracy in air field simulations of indoor room was carried out by K. Chow [15]. Heat transfer through the walls and internal radiation transfer were considered in simulation studies by corresponding experimental tests. To find the effective way that can simulate the humidity distribution inside chamber simply, quickly and precisely needs to establish a calculation model firstly, and verify the simulation results with experiment study. In this study, the humidity distribution inside environmental chamber is studied simultaneously by experiments and CFD simulation. Moreover, influence of different initial particle-size on the contaminate distribution was rarely considered. In this study, water droplets size and distribution from ultrasonic mist blower are measured accurately by the laser diffraction particle-size analyzer firstly, and the different initial conditions, including the simplification distributions of mist conditions are offered to the CFD simulation model and the comparison studies are carried out. In addition, under different initial mist conditions, the comparison studies on computation time consumption of humidity simulation inside chamber are carried out finally.
outlet vent (500 mm 100 mm). In this study, the middle inlet vent is studied for the experimental research and numerical simulation. The airflow rates can be measured by hot-wire type anemometer located at inlet vent position. In this study, the time-dependent temperature and humidity value were measured by 15 measurement points (i.e. sample points) including inlet vent and outlet vent, which were distributed in three horizontal sections inside the chamber. The positions of the measurement points are shown in Fig. 1. The cuboids, numbering from 1 to 13, are samples to observe the humidity distribution in the working area and the dimension of the effective working area is 0.6m 0.6m 1.1 m. The temperature and humidity sensors were accurate to 0.5 C and 1.0% respectively. Water mist was produced by an ultrasonic humidifier and sprayed into chamber at the inlet vent. The quantity (amount) of water droplet generated from humidifier was controlled and measured. Twelve series of experiments were carried out, under a variety of inlet temperature and humidity, which maybe concerned with heat and moisture transfer and factors of humidity distribution inside chamber. Some of the primary results have been reported in Refs. [16,17]. The experimental conditions were chosen carefully to avoid condensation occurring on the wall during experiments. All experiments continued until temperature and humidity distributions within the chamber reached steady state. The experimental conditions are as follows: ambient temperature is 28 C, and the local atmosphere pressure keeps 98.1 kPa. The thermal balance experiment and calculation are carried firstly and the suitable thermal boundary conditions are offered for the latter CFD simulation studies. As an advanced measurement tool, laser diffraction particle-size analyzer is applied to the particle-size distribution analysis and micro-scale measurement widely due to its non-contact characteristic. It is based on the principle of dynamic image analysis and the innovative time-of-transition theory. 2.2. CFD simulation In this study, the CFD calculation tool was used to simulate the flow field, temperature field and humidity distribution inside chamber of the cases corresponding to the experiments mentioned
2. Research methods 2.1. Description of the experimental system Considering the obstacles to precisely simulating the humidity distribution in a chamber, experiment tests were conducted to study the characteristics of humidity distribution in a chamber at different inlet mist temperatures and humidities. Moreover, the experiment results are used to validate a simplified CFD simulation method. The experimental test rig is firstly introduced as followed. The experimental test rig consists of an environmental chamber with the dimensions of 1.0 m (L) 1.0 m (W) 1.5 m (H). The chamber is made of polyurethane and supported by stainless steel frame, so absorption of water droplets by its internal surface can be ignored. Three supply vents (300 mm 100 mm) are set at the upper, middle and lower Air can be supplied from inlet vent into the chamber (i.e. upper, middle and lower vents independently), and exhausted to the air handling system that was located at a lower
Fig. 1. The environmental chamber and position of measured points.
L. Pu et al. / Building and Environment 47 (2012) 217e222
above. The objectives of these simulation studies were to develop a method of simulating humidity distribution inside chamber quickly and precisely. In this study, CFD software Fluent was chosen to simulate temperature field and humidity distribution inside chamber. The boundary conditions are listed in Table 1 [18,19]. Steady state simulations were taken into account in this paper. The thermal boundary conditions (wall structure) are confirmed through the thermal balance experimental and pre-simulations have been carried out to confirm grid-independence. In this study, water mist produced from ultrasonic humidifier is taken into account the flexible particle when they meet the wall. In the simulation study with the Lagrangian coordinates, the discrete phase model of the two-fluid model is applied to all the bubbles, droplets and the particle load flow in size of less than 10% in CFD calculation [20]. The spherical droplets or bubbles constitute the second phase, and distributing in the continuous phase. As the particles pass through the control body, the momentum, heat and mass exchange of the particles for getting those values of mist droplet (discrete phase) transferred by wet air (continuous phase) are calculated respectively. As a “sink”, these exchange values will effect into the calculation of the subsequent fluid momentum and the conservation of energy and mass. In this study, the following assumptions are used in this CFD simulation: The flow is stable inside chamber; The fluid flow meets the Boussinesq assumption; The fluid inside chamber is incompressible Newtonian fluid; The mist droplets are considered to be constant and the ideal collision is treated when they meet the solid wall; (5) The computational fluid is the ideal gas mixture of dry air and water droplets. The liquid droplets do not contain dissolved air and the existence of air will not affect the balance between water vapor and gathered steam. The average humidity and the partial pressure are calculated corresponding to the saturation temperature; (6) The molecular viscosity can be ignored in the zone which has a certain distance from the wall; (7) Heat radiation is neglected.
(1) (2) (3) (4)
In this study, a standard ke3 model was used to predict turbulent flow inside chamber. Mass Conservation Equation [18]:
vr þ Vru ¼ 0 vt
(1)
Fig. 2. Measured mist size distribution (Distribution 1).
where, F is the general variable which represents u, v, w, T, K, 3 ; GF is the generalized diffusion coefficient; SF is the generalized source term. The droplet evaporation capacity is determined by the gradient diffusion, i.e. the diffusion velocity of droplets into the gas phase is correlated with the steam concentration gradient between the droplet surface and the principle body of airflow:
Ni ¼ ki Ci;s Ci;N
3 Results and discussion 3.1. Measured and simplified droplet size distributions To describe initial condition of humidifying progress precisely, in this paper, Malvern laser diffraction particle-size analyzer was applied to measure the water droplets size and distribution. Fig. 3 shows the measured result of mist size distribution and the droplet size is from 1 to 54 mm and the weighted average droplet size of the whole water mists is 9.2 mm. Weighted average (dw) and arithmetic mean (d) of droplet size are defined by Eqs. (4) and (5) respectively in this study.
(2)
Table 1 Boundary and calculation conditions. Term
Condition
Turbulence model CFD grid points Numerical schemes Convective terms Outlet vent
Standard ke3 model 51(X) 51(Y) 76(Z) ¼ 197,676 Semi-implicit SIMPLER Second order upwind differential scheme Pressure outlet; the local atmosphere pressure (98.1 kPa) Velocity inlet, velocity and temperature No-slip; heat transfer coefficient 0.246e0.293 W/m2 K Measured by laser diffraction analyzer Absolute residuals less than 1.0 106
Inlet vent Wall structure Mist size condition Convergence criterion
(3)
where, Ni is the mass flow velocity of steam (kg/m2 s), ki is the mass transfer coefficient (m/s), Ci,s is the saturated steam concentration of water (kg/m3), Ci;N is the steam concentration of the principle body of gas phase (kg/m3).
General form of governing equation:
vðrfÞ þ divðrU fÞ ¼ div Gf grdf þ Sf vt
219
Fig. 3. Simplified distribution of droplet size (Distribution 2).
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L. Pu et al. / Building and Environment 47 (2012) 217e222
as approximate normal distribution from 1 to 54 mm. To simply this problem legitimately, four simplified distributions are tried to apply to the CFD simulation study of humidity distribution as different initial conditions. In this study, mist droplet distribution simplified by the statistics principle is shown in Fig. 3 mentioned in reference [17] (Distribution 2), and the other three representative identical droplet sizes (10 mm, 20 mm and 30 mm) are tried to apply as the initial conditions in the CFD calculation. Here, 10 mm means the weighted average of measured water mist size (Distribution 3), and 20 mm and 30 mm represent the arithmetic mean of actual size distribution (Distribution 4 and 5).
Table 2 Experimental and CFD results data. Case
Inlet T ( C)
Inlet RH (%)
Average RH of experiment (%)
Average RH of simulation (%)
Relative deviation (%)
1-1 1-2 1-3 1-4 2-1 2-2 2-3 2-4 3-1 3-2 3-3 3-4
20 20 20 20 40 40 40 40 60 60 60 60
20 40 60 80 20 40 60 80 20 40 60 80
21.6 43.5 62.7 82.3 22.0 42.1 63.8 84.9 19.4 42.1 63.8 85.9
21.4 39.5 58.5 84.7 21.1 38.5 57.5 78.1 20.4 41.1 58.7 85.2
<1.0% <10.0% <7.0% <3.0% <5.0% <9.0% <7.0% <3.0% <5.0% <3.0% <8.0% <1.0%
dw ¼
n X
3.2. Experimental and CFD results
di $fi
(4)
. di n
(5)
Under twelve typical cases with different experimental conditions (i.e. inlet temperature and inlet RH value), the average humidity values of 13 measurement points inside chamber are shown in Table 2. As mentioned above, the measured error of RH value is within 1.0% and average RH of experimental results is also kept 1.0%. The experiment results show that, at the middle inlet vent, the difference between inlet humidity value and average humidity inside chamber is RH2% (inlet RH20%), RH4% (inlet RH40%), RH5% (inlet RH60%) and RH6% (inlet RH80%) respectively. Certainly, relative deviation between inlet and average humidity value is less than 10%. To evaluate the uniformity of humidity distribution inside chamber, in this study, the standard deviation of RH was used to analyze the uniformity of the RH distribution. In this paper, y
i¼1
d ¼
n X i¼1
where, di is every diameter of measured droplets; fi is the percentage of di. In this study, mist droplets distribution mentioned above is named Distribution 1 and shown in Fig. 2. In the simulation study mentioned above, the mist size and distribution of humidity initial condition is measured and treated
0.045
0.035 0.030
Non-uniformity of RH
0.050
Non-uniformity of RH
b
Case1-1 Case1-2 Case1-3 Case1-4
0.055
0.040
Case2-1 Case2-2 Case2-3 Case2-4
0.025
0.035
0.020
0.030 0.025
0.015
0.020
0.010
0.015 0.010
0
5
10
15
20
25
30
35
40
0.005
0
5
10
Time/min
15
20
25
30
Time/min
Inlet temperature of 40°C
Inlet temperature of 20°C
c 0.025 Case3-1 Case3-2 Case3-3 Case3-4
Non-uniformity of RH
a
0.020
0.015
0.010
0.005 0
5
10
15
20
25
30
35
Time/min Inlet temperature of 60°C Fig. 4. Non-uniformity of RH with time in experimental study.
40
35
40
L. Pu et al. / Building and Environment 47 (2012) 217e222
221
Fig. 5. Simulation result of water mist distribution.
represents non-uniformity of RH inside chamber. “y” is smaller, the uniformity of RH is better. Here, non-uniformity of RH is defined by Eq. (6).
controlled within 10.0%. The results show that the assumptions for CFD simulation are reliable.
sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi Pn 2 i ¼ 1 ð4i 4Þ y ¼ n
3.3. Comparison of CFD simulation using different droplet size distributions
(6)
where, 4i means RH at measuring point; 4 means the average RH; and n means the number of measuring points. As the example of middle inlet vent, Fig. 4 shows that “y” of high inlet humidity is always low at different inlet temperature (20 C, 40 C and 60 C) and “y” of low inlet humidity decreases with the increase of inlet temperature. Fig. 5 shows that, as an example of middle inlet vent, the simulation result of humidity distribution at the section of x ¼ 0.5 m and y ¼ 0.5 m respectively. The average RH values of 13 sample points of simulation result are also shown in Table 2. Moreover, the comparison studies show that the differences of average RH value between experiment and simulation results are not large. The relative deviations of two data are completely
Non-uniformity of RH
0.25 0.20 0.15 0.10 0.05
In this simulation study, the comparison result is shown in Fig. 6 using above five distributions of mist size. The results indicate the non-uniformities of simulation under the initial condition of Distribution 1, 2 and 3 agree with the calculation results of measurement very well, and y values gained from Distribution 4 and 5 are higher than the measurement and simulation results. In addition, the results of latter two initial conditions increase sharply. Thus, taking the former two simplified initial mist distributions (Distribution 2 and 3) as the initial conditions is acceptable in this simulation study of humidity distribution inside chamber. In this study, the comparison study on the computation time consumption of simulation studies with different mist initial conditions (i.e. different mist size distribution) mentioned above is performed. Here, the same computation conditions of CPU (Intel Core 2, 1.6G Hz) and 1.0 GB of RAM are adopted in simulation studies of humidity distribution inside chamber, and the simulation time consumption while convergence condition is achieved in simulation studies are listed in Table 3. The results show that the computation quantity can be reduced sharply and the time consumption can be saved effectively using the simplified initial mist size distribution (Distribution 2e5), especially using identical mist size distribution (Distribution 3e5). Furthermore, treating Distribution 3 as mist initial condition in CFD simulation studies, the precise result of humidity distribution can be gained and the computation time can be also saved.
Table 3 Time consumption under different initial mist distributions.
0.00 t 1 4 2 3 5 rimen tribution tribution tribution tribution tribution Expe Dis Dis Dis Dis Dis
Droplets size distribution Fig. 6. The comparison simulation result under different droplet size distribution.
Mist initial condition
Time consumption (h)
Distribution Distribution Distribution Distribution Distribution
About About About About About
1 2 3 4 5
72e96 36e48 24 24 24
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L. Pu et al. / Building and Environment 47 (2012) 217e222
4. Conclusions The objective of this paper was to simulate the humidity distribution inside a chamber with more accurate initial conditions of water droplets size and try to simply the initial condition. Thus the computational load is greatly reduced and acceptable results can be gained. A series of experiments and CFD simulations has been carried out. Based on the calculation and experiment results and comparison discussions, the following conclusions can be drawn: (1) The experiment studies on temperature and humidity distribution are carried out, and the experiment results show that relative deviation between inlet and average measured RH value is less than 10%. The experimental study also indicates that, under different inlet temperature, non-uniformity of high inlet humidity is always small, and that of low inlet humidity decreases with the increase of inlet temperature. (2) The simulation method is developed, and the comparison studies between the CFD results and experiment results are carried out. The comparison results indicate that the simulation result has a good agreement with that of experiment. The CFD method will be a good way in the humidity distribution study of chamber. (3) The sensible simplified mist size distribution is applied to CFD simulation study as the initial condition. The results show that a good agreement is obtained from the comparison studies between experiment and simulations of three kinds of initial mist distribution conditions, including Distribution 2 and 3. Using novel mist distribution as initial mist condition, the calculation quantity can be reduced and the time consumption can be saved in simulation study of humidity distribution, and the simulation result is approved at the same time in this study. Based on above research work, more detailed CFD simulation studies and experiments should be carried out for practical cases. Under different initial mist condition and novel simplification of mist size distribution, more comparison studies between different inlet conditions and different inlet positions should be carried in the further studies. Acknowledgment The research work presented in this paper was jointly supported by the President Foundation of Xi’an Jiaotong University
(XJJ2008045) and an Internal Competitive Research Grant from the Hong Kong Polytechnic University (1-ZV6J), Hong Kong SAR. References [1] Lee SC, Lam Sanches, Fai Ho Kin. Characterization of VOCs, ozone, and PM10 emissions from office equipment in an environmental chamber. Build Environ August 2001;36(7):837e42. [2] Yu KP, Lee GW, Hsieh CP, Lin CC. Evaluation of ozone generation and indoor organic compounds removal by air cleaners based on chamber tests. Atmos Environ 2011;45(1):35e42. [3] Gu Lei, Huang Qing-An, Qin Ming. A novel capacitive-type humidity sensor using CMOS fabrication technology. Sensor Actuator B Chem 1 May 2004; 99(2e3):491e8. [4] Liu J, Aizawa Y, Yoshino H. Experimental and numerical study on indoor temperature and humidity with free water surface. Energy Build 2005;37:383e8. [5] Sureshkumar R, Kale SR, Dhar PL. Heat and mass transfer processes between a water spray and ambient air e I. Experimental data. Appl Therm Eng 2008; 28:349e60. [6] Sureshkumar R, Kale SR, Dhar PL. Heat and mass transfer processes between a water spray and ambient air e II. Simulations. Appl Therm Eng 2008;28: 361e71. [7] Manzan M, Saro O. Numerical analysis of heat and mass transfer in a passive building component cooled by water evaporation. Energy Build 2002;34(4): 369e75. [8] Westerlund L, Dahl J, Johansson L. A theoretical investigation of the heat demand for public baths. Energy 1996;21(7/8):731e7. [9] Zingano BW. A discussion on thermal comfort with reference to bath water temperature to deduce a midpoint of the thermal comfort temperature zone. Renew Energy 2001;23(1):41e7. [10] Aristov YI, Mezentsev IV, Mukhin VA. A new approach to regenerating heat and moisture in ventilation systems. Energy Build 2007;37(1):1e5. [11] Gaur RC, Bansal NK. Effect of moisture transfer across building components on room temperature. Build Environ 2002;37(1):11e7. [12] Vasile C, Lorente S, Perrin B. Study of convective phenomena inside cavities coupled with heat and mass transfers through porous mediaeapplication to vertical hollow bricksea first approach. Energy Build 1998;28(3):229e35. [13] Zitek P, Vyhlidal T, Simeunovic G, Novakova L, Cizek J. Novel personalized and humidified air supply for airliner passengers. Build Environ 2010;45:2345e53. [14] Khan JA, Feigley CE, Lee E, Ahmed MR, Tamanna S. Effects of inlet and exhaust locations and emitted gas density on indoor air contaminant concentrations. Build Environ 2006;41:851e63. [15] Chow K, Holdo AE. On the influence of boundary conditions and thermal radiation on predictive accuracy in numerical simulations of indoor ventilation. Build Environ 2010;45:437e44. [16] L. Pu, Y.Z. Li, C.Y. Gao, J. Wen. Experimental study of humidity measurement and humidity field based on environmental chamber, The 6th International Conference on Compressor and Refrigeration, 2008, Xi’an, China. [17] Pu L, Li YZ, Zhu YH, Gao CY. Experimental and numerical investigation on humidity distribution in an environmental chamber. JSME J Environ Eng 2009; 4(2):326e37. [18] Tao WQ. Numerical heat transfer. 2nd ed. Xi’an, China: Xi’an Jiaotong University Press; 2001. [19] Lu ZQ. Tow-phase flow and boiling heat transfer. Beijing, China: Tsinghua University Press; 2002. [20] Han ZZ, Wang J, Lan XP. FLUENTeemulational example and application on the fluid engineering. Beijing, China: Beijing Institute of Technology Press; 2004.
Contents lists available at ScienceDirect
Building and Environment journal homepage: www.elsevier.com/locate/buildenv
Effects of initial mist conditions on simulation accuracy of humidity distribution in an environmental chamber Liang Pu a, b, *, Fu Xiao a, **, Yanzhong Li b, Zhenjun Ma a a b
Department of Building Services Engineering, The Hong Kong Polytechnic University, Hong Kong Institute of Refrigeration and Cryogenic Engineering, Xi’an Jiaotong University, Xi’an 710049, China
a r t i c l e i n f o
a b s t r a c t
Article history: Received 31 March 2011 Received in revised form 12 June 2011 Accepted 22 July 2011
This paper firstly presents experimental study of humidity distribution in an environmental chamber at different inlet temperatures and humidity. Experiment results show that, under fixed inlet temperature condition, the uniformity of the relative humidity (RH) in the chamber is better when the inlet RH is higher. It is mainly because of the coupled heat and mass transfer occurred between water droplets and air. In practice, direct measurement of humidity distribution in a chamber is infeasible and CFD simulation is a possible way to predict the humidity distribution. However, the use of CFD tools for predicting humidity field is rarely reported. Boundary and initial mist conditions are critical to the accuracy and computation efficiency of CFD simulation. This study then presents a CFD simulation method of the humidity distribution inside chamber using FLUENT based on some assumptions and simplification. Moreover, droplet sizes were measured by laser diffraction analyzer. The simplified droplet size distribution is used as initial condition for CFD simulation. Experiment results and CFD simulation results are compared and it can be concluded that the CFD simulation method can achieve satisfactory accuracy with reasonable computation load. Ó 2011 Elsevier Ltd. All rights reserved.
Keywords: Humidity distribution Environmental chamber Droplet size distribution CFD simulation
1. Introduction Environmental test chambers play essential roles in testing advanced devices, equipment and materials [1e3]. To satisfy various test purposes, environment parameters, such as temperature, humidity and air velocity, in chambers must be precisely controlled at required set-points. Temperature, air velocity and particle distribution in built environment were well studied using experiment tests and CFD simulation tools. Stable and uniform humidity distribution in a test chamber is often required for many tests [3]. Inlet conditions have significant effects on the humidity distribution in an environmental chamber. Inappropriate inlet conditions may cause undesired humidity distribution and consequently unreliable test results. Though the CFD method has been proved to be powerful and reliable for simulating fluid fields, research work on estimation of simultaneous heat and moisture transfer and resulting humidity distribution are limited. J. Liu [4] applied a new method to study
* Corresponding author. Institute of Refrigeration and Cryogenic Engineering, Xi’an Jiaotong University, Xi’an 710049, China. ** Corresponding author. E-mail addresses: [email protected] (L. Pu), [email protected] (F. Xiao). 0360-1323/$ e see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.buildenv.2011.07.020
heat and moisture transfer between free water surface and surrounding air by experiment and CFD simulation. The influence of surrounding air temperature and humidity, water temperature and water surface area on the moisture and heat transfer was studied. Sureshkumar et al. [5,6] researched the heat and mass transfer processes between a water spray and surrounding air. The results showed that, under a given water flow rate, a smaller nozzle with higher pressures can produce more cooling than a large nozzle with lower pressures. Manzan and Saro [7] analyzed the numerical simulation of temperature field, flow field and humidity diffusion of the indoor air. An original approach to solve a coupled heat and mass transfer problem was presented in order to obtain an estimate of the thermal cooling flux on the wet surface using CFX 4.4 commercial program. A few of experimental studies and numerical predictions have been conducted to study humidity distribution and temperature field. The literature [8] studied the heat demand and the heat and mass transfer based on the public baths. A parametric study showed that the temperature and RH in the building strongly influence the heating demand inside room. B.W. Zingano [9] carried the experimental studies and discussed the importance of humidity to the thermal comfort temperatures. The influence of the indoor and outdoor temperature difference on the loss of moisture content and change of humidity in the air-conditioning system was studied
218
L. Pu et al. / Building and Environment 47 (2012) 217e222
by Aristov et al. [10]. Mutual influence among the parameters exists in the control of ambient humidity. The influence of ambient humidity and indoor humidity to the indoor temperature, i.e. the interacting relationship of all kinds of aspects such as humidity, temperature and other factors, was studied by Gaur et al. [11]. The interacting among the conduction, convection, and radiation heat transfer to the heat-mass exchange was researched by Vasile et al. [12] through the porous media. An initial approach to above problem by attempting to describe the influence of moisture level on heat transfers occurring through bricks was presented. Recently, in order to get optimization results and requirements of comfort or energy saving, influence of different boundary conditions, like inlet locations, airflow rate and others, on the parameter fields was also studied in the simulation study on parameter field and contaminate distribution. In order to supply fresh, humidified air to each person on airplane, P. Zitek et al. [13] presented a novel design method and system to simulate personalized and humidified fresh air for airliner passengers. In this system, every seat in the cabin has a separate air supply inlet and exhaust outlet. To choose the best project, several different inlet and exhaust locations and types were investigated by J.A. Khan et al. [14], and room concentration patterns were calculated by CFD simulations for various inlet and exhaust positions. The results showed that inlet and exhaust locations influenced the contaminant concentrations in a workroom. Further study on accurate thermal boundary conditions on predictive accuracy in air field simulations of indoor room was carried out by K. Chow [15]. Heat transfer through the walls and internal radiation transfer were considered in simulation studies by corresponding experimental tests. To find the effective way that can simulate the humidity distribution inside chamber simply, quickly and precisely needs to establish a calculation model firstly, and verify the simulation results with experiment study. In this study, the humidity distribution inside environmental chamber is studied simultaneously by experiments and CFD simulation. Moreover, influence of different initial particle-size on the contaminate distribution was rarely considered. In this study, water droplets size and distribution from ultrasonic mist blower are measured accurately by the laser diffraction particle-size analyzer firstly, and the different initial conditions, including the simplification distributions of mist conditions are offered to the CFD simulation model and the comparison studies are carried out. In addition, under different initial mist conditions, the comparison studies on computation time consumption of humidity simulation inside chamber are carried out finally.
outlet vent (500 mm 100 mm). In this study, the middle inlet vent is studied for the experimental research and numerical simulation. The airflow rates can be measured by hot-wire type anemometer located at inlet vent position. In this study, the time-dependent temperature and humidity value were measured by 15 measurement points (i.e. sample points) including inlet vent and outlet vent, which were distributed in three horizontal sections inside the chamber. The positions of the measurement points are shown in Fig. 1. The cuboids, numbering from 1 to 13, are samples to observe the humidity distribution in the working area and the dimension of the effective working area is 0.6m 0.6m 1.1 m. The temperature and humidity sensors were accurate to 0.5 C and 1.0% respectively. Water mist was produced by an ultrasonic humidifier and sprayed into chamber at the inlet vent. The quantity (amount) of water droplet generated from humidifier was controlled and measured. Twelve series of experiments were carried out, under a variety of inlet temperature and humidity, which maybe concerned with heat and moisture transfer and factors of humidity distribution inside chamber. Some of the primary results have been reported in Refs. [16,17]. The experimental conditions were chosen carefully to avoid condensation occurring on the wall during experiments. All experiments continued until temperature and humidity distributions within the chamber reached steady state. The experimental conditions are as follows: ambient temperature is 28 C, and the local atmosphere pressure keeps 98.1 kPa. The thermal balance experiment and calculation are carried firstly and the suitable thermal boundary conditions are offered for the latter CFD simulation studies. As an advanced measurement tool, laser diffraction particle-size analyzer is applied to the particle-size distribution analysis and micro-scale measurement widely due to its non-contact characteristic. It is based on the principle of dynamic image analysis and the innovative time-of-transition theory. 2.2. CFD simulation In this study, the CFD calculation tool was used to simulate the flow field, temperature field and humidity distribution inside chamber of the cases corresponding to the experiments mentioned
2. Research methods 2.1. Description of the experimental system Considering the obstacles to precisely simulating the humidity distribution in a chamber, experiment tests were conducted to study the characteristics of humidity distribution in a chamber at different inlet mist temperatures and humidities. Moreover, the experiment results are used to validate a simplified CFD simulation method. The experimental test rig is firstly introduced as followed. The experimental test rig consists of an environmental chamber with the dimensions of 1.0 m (L) 1.0 m (W) 1.5 m (H). The chamber is made of polyurethane and supported by stainless steel frame, so absorption of water droplets by its internal surface can be ignored. Three supply vents (300 mm 100 mm) are set at the upper, middle and lower Air can be supplied from inlet vent into the chamber (i.e. upper, middle and lower vents independently), and exhausted to the air handling system that was located at a lower
Fig. 1. The environmental chamber and position of measured points.
L. Pu et al. / Building and Environment 47 (2012) 217e222
above. The objectives of these simulation studies were to develop a method of simulating humidity distribution inside chamber quickly and precisely. In this study, CFD software Fluent was chosen to simulate temperature field and humidity distribution inside chamber. The boundary conditions are listed in Table 1 [18,19]. Steady state simulations were taken into account in this paper. The thermal boundary conditions (wall structure) are confirmed through the thermal balance experimental and pre-simulations have been carried out to confirm grid-independence. In this study, water mist produced from ultrasonic humidifier is taken into account the flexible particle when they meet the wall. In the simulation study with the Lagrangian coordinates, the discrete phase model of the two-fluid model is applied to all the bubbles, droplets and the particle load flow in size of less than 10% in CFD calculation [20]. The spherical droplets or bubbles constitute the second phase, and distributing in the continuous phase. As the particles pass through the control body, the momentum, heat and mass exchange of the particles for getting those values of mist droplet (discrete phase) transferred by wet air (continuous phase) are calculated respectively. As a “sink”, these exchange values will effect into the calculation of the subsequent fluid momentum and the conservation of energy and mass. In this study, the following assumptions are used in this CFD simulation: The flow is stable inside chamber; The fluid flow meets the Boussinesq assumption; The fluid inside chamber is incompressible Newtonian fluid; The mist droplets are considered to be constant and the ideal collision is treated when they meet the solid wall; (5) The computational fluid is the ideal gas mixture of dry air and water droplets. The liquid droplets do not contain dissolved air and the existence of air will not affect the balance between water vapor and gathered steam. The average humidity and the partial pressure are calculated corresponding to the saturation temperature; (6) The molecular viscosity can be ignored in the zone which has a certain distance from the wall; (7) Heat radiation is neglected.
(1) (2) (3) (4)
In this study, a standard ke3 model was used to predict turbulent flow inside chamber. Mass Conservation Equation [18]:
vr þ Vru ¼ 0 vt
(1)
Fig. 2. Measured mist size distribution (Distribution 1).
where, F is the general variable which represents u, v, w, T, K, 3 ; GF is the generalized diffusion coefficient; SF is the generalized source term. The droplet evaporation capacity is determined by the gradient diffusion, i.e. the diffusion velocity of droplets into the gas phase is correlated with the steam concentration gradient between the droplet surface and the principle body of airflow:
Ni ¼ ki Ci;s Ci;N
3 Results and discussion 3.1. Measured and simplified droplet size distributions To describe initial condition of humidifying progress precisely, in this paper, Malvern laser diffraction particle-size analyzer was applied to measure the water droplets size and distribution. Fig. 3 shows the measured result of mist size distribution and the droplet size is from 1 to 54 mm and the weighted average droplet size of the whole water mists is 9.2 mm. Weighted average (dw) and arithmetic mean (d) of droplet size are defined by Eqs. (4) and (5) respectively in this study.
(2)
Table 1 Boundary and calculation conditions. Term
Condition
Turbulence model CFD grid points Numerical schemes Convective terms Outlet vent
Standard ke3 model 51(X) 51(Y) 76(Z) ¼ 197,676 Semi-implicit SIMPLER Second order upwind differential scheme Pressure outlet; the local atmosphere pressure (98.1 kPa) Velocity inlet, velocity and temperature No-slip; heat transfer coefficient 0.246e0.293 W/m2 K Measured by laser diffraction analyzer Absolute residuals less than 1.0 106
Inlet vent Wall structure Mist size condition Convergence criterion
(3)
where, Ni is the mass flow velocity of steam (kg/m2 s), ki is the mass transfer coefficient (m/s), Ci,s is the saturated steam concentration of water (kg/m3), Ci;N is the steam concentration of the principle body of gas phase (kg/m3).
General form of governing equation:
vðrfÞ þ divðrU fÞ ¼ div Gf grdf þ Sf vt
219
Fig. 3. Simplified distribution of droplet size (Distribution 2).
220
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as approximate normal distribution from 1 to 54 mm. To simply this problem legitimately, four simplified distributions are tried to apply to the CFD simulation study of humidity distribution as different initial conditions. In this study, mist droplet distribution simplified by the statistics principle is shown in Fig. 3 mentioned in reference [17] (Distribution 2), and the other three representative identical droplet sizes (10 mm, 20 mm and 30 mm) are tried to apply as the initial conditions in the CFD calculation. Here, 10 mm means the weighted average of measured water mist size (Distribution 3), and 20 mm and 30 mm represent the arithmetic mean of actual size distribution (Distribution 4 and 5).
Table 2 Experimental and CFD results data. Case
Inlet T ( C)
Inlet RH (%)
Average RH of experiment (%)
Average RH of simulation (%)
Relative deviation (%)
1-1 1-2 1-3 1-4 2-1 2-2 2-3 2-4 3-1 3-2 3-3 3-4
20 20 20 20 40 40 40 40 60 60 60 60
20 40 60 80 20 40 60 80 20 40 60 80
21.6 43.5 62.7 82.3 22.0 42.1 63.8 84.9 19.4 42.1 63.8 85.9
21.4 39.5 58.5 84.7 21.1 38.5 57.5 78.1 20.4 41.1 58.7 85.2
<1.0% <10.0% <7.0% <3.0% <5.0% <9.0% <7.0% <3.0% <5.0% <3.0% <8.0% <1.0%
dw ¼
n X
3.2. Experimental and CFD results
di $fi
(4)
. di n
(5)
Under twelve typical cases with different experimental conditions (i.e. inlet temperature and inlet RH value), the average humidity values of 13 measurement points inside chamber are shown in Table 2. As mentioned above, the measured error of RH value is within 1.0% and average RH of experimental results is also kept 1.0%. The experiment results show that, at the middle inlet vent, the difference between inlet humidity value and average humidity inside chamber is RH2% (inlet RH20%), RH4% (inlet RH40%), RH5% (inlet RH60%) and RH6% (inlet RH80%) respectively. Certainly, relative deviation between inlet and average humidity value is less than 10%. To evaluate the uniformity of humidity distribution inside chamber, in this study, the standard deviation of RH was used to analyze the uniformity of the RH distribution. In this paper, y
i¼1
d ¼
n X i¼1
where, di is every diameter of measured droplets; fi is the percentage of di. In this study, mist droplets distribution mentioned above is named Distribution 1 and shown in Fig. 2. In the simulation study mentioned above, the mist size and distribution of humidity initial condition is measured and treated
0.045
0.035 0.030
Non-uniformity of RH
0.050
Non-uniformity of RH
b
Case1-1 Case1-2 Case1-3 Case1-4
0.055
0.040
Case2-1 Case2-2 Case2-3 Case2-4
0.025
0.035
0.020
0.030 0.025
0.015
0.020
0.010
0.015 0.010
0
5
10
15
20
25
30
35
40
0.005
0
5
10
Time/min
15
20
25
30
Time/min
Inlet temperature of 40°C
Inlet temperature of 20°C
c 0.025 Case3-1 Case3-2 Case3-3 Case3-4
Non-uniformity of RH
a
0.020
0.015
0.010
0.005 0
5
10
15
20
25
30
35
Time/min Inlet temperature of 60°C Fig. 4. Non-uniformity of RH with time in experimental study.
40
35
40
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221
Fig. 5. Simulation result of water mist distribution.
represents non-uniformity of RH inside chamber. “y” is smaller, the uniformity of RH is better. Here, non-uniformity of RH is defined by Eq. (6).
controlled within 10.0%. The results show that the assumptions for CFD simulation are reliable.
sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi Pn 2 i ¼ 1 ð4i 4Þ y ¼ n
3.3. Comparison of CFD simulation using different droplet size distributions
(6)
where, 4i means RH at measuring point; 4 means the average RH; and n means the number of measuring points. As the example of middle inlet vent, Fig. 4 shows that “y” of high inlet humidity is always low at different inlet temperature (20 C, 40 C and 60 C) and “y” of low inlet humidity decreases with the increase of inlet temperature. Fig. 5 shows that, as an example of middle inlet vent, the simulation result of humidity distribution at the section of x ¼ 0.5 m and y ¼ 0.5 m respectively. The average RH values of 13 sample points of simulation result are also shown in Table 2. Moreover, the comparison studies show that the differences of average RH value between experiment and simulation results are not large. The relative deviations of two data are completely
Non-uniformity of RH
0.25 0.20 0.15 0.10 0.05
In this simulation study, the comparison result is shown in Fig. 6 using above five distributions of mist size. The results indicate the non-uniformities of simulation under the initial condition of Distribution 1, 2 and 3 agree with the calculation results of measurement very well, and y values gained from Distribution 4 and 5 are higher than the measurement and simulation results. In addition, the results of latter two initial conditions increase sharply. Thus, taking the former two simplified initial mist distributions (Distribution 2 and 3) as the initial conditions is acceptable in this simulation study of humidity distribution inside chamber. In this study, the comparison study on the computation time consumption of simulation studies with different mist initial conditions (i.e. different mist size distribution) mentioned above is performed. Here, the same computation conditions of CPU (Intel Core 2, 1.6G Hz) and 1.0 GB of RAM are adopted in simulation studies of humidity distribution inside chamber, and the simulation time consumption while convergence condition is achieved in simulation studies are listed in Table 3. The results show that the computation quantity can be reduced sharply and the time consumption can be saved effectively using the simplified initial mist size distribution (Distribution 2e5), especially using identical mist size distribution (Distribution 3e5). Furthermore, treating Distribution 3 as mist initial condition in CFD simulation studies, the precise result of humidity distribution can be gained and the computation time can be also saved.
Table 3 Time consumption under different initial mist distributions.
0.00 t 1 4 2 3 5 rimen tribution tribution tribution tribution tribution Expe Dis Dis Dis Dis Dis
Droplets size distribution Fig. 6. The comparison simulation result under different droplet size distribution.
Mist initial condition
Time consumption (h)
Distribution Distribution Distribution Distribution Distribution
About About About About About
1 2 3 4 5
72e96 36e48 24 24 24
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4. Conclusions The objective of this paper was to simulate the humidity distribution inside a chamber with more accurate initial conditions of water droplets size and try to simply the initial condition. Thus the computational load is greatly reduced and acceptable results can be gained. A series of experiments and CFD simulations has been carried out. Based on the calculation and experiment results and comparison discussions, the following conclusions can be drawn: (1) The experiment studies on temperature and humidity distribution are carried out, and the experiment results show that relative deviation between inlet and average measured RH value is less than 10%. The experimental study also indicates that, under different inlet temperature, non-uniformity of high inlet humidity is always small, and that of low inlet humidity decreases with the increase of inlet temperature. (2) The simulation method is developed, and the comparison studies between the CFD results and experiment results are carried out. The comparison results indicate that the simulation result has a good agreement with that of experiment. The CFD method will be a good way in the humidity distribution study of chamber. (3) The sensible simplified mist size distribution is applied to CFD simulation study as the initial condition. The results show that a good agreement is obtained from the comparison studies between experiment and simulations of three kinds of initial mist distribution conditions, including Distribution 2 and 3. Using novel mist distribution as initial mist condition, the calculation quantity can be reduced and the time consumption can be saved in simulation study of humidity distribution, and the simulation result is approved at the same time in this study. Based on above research work, more detailed CFD simulation studies and experiments should be carried out for practical cases. Under different initial mist condition and novel simplification of mist size distribution, more comparison studies between different inlet conditions and different inlet positions should be carried in the further studies. Acknowledgment The research work presented in this paper was jointly supported by the President Foundation of Xi’an Jiaotong University
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