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Study on the performance of silica gel dehumidification system with ultrasonic-assisted regeneration
Energy 66 (2014) 799e809
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Study on the performance of silica gel dehumidification system with ultrasonic-assisted regeneration Ye Yao a, b, *, Kun Yang a, Shiqing Liu c a
Institute of Refrigeration and Cryogenics, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China, 200240 Key Laboratory of Energy Thermal Conversion and Control, Ministry of Education, School of Energy and Environment, Southeast University, Nanjing, China, 210096 c School of Mathematics and Physics, Zhejiang Normal University, Jinhua, Zhejiang Province 321004, China b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 3 July 2013 Received in revised form 26 November 2013 Accepted 18 January 2014 Available online 20 February 2014
A theoretic model is developed to describe the moisture desorption-and-adsorption cycle of silica gel dehumidification system with or without ultrasonic-assisted regeneration. The model has been validated by a series of experiments. The AMRC (additional moisture removal capacity) and the DCOP (dehumidification coefficient of performance) are suggested to illustrate the performance of silica gel dehumidification system with ultrasonic radiation. The effects of ultrasonic-assisted regeneration on the performance of the dehumidification system are investigated with the model under different conditions. Some crucial conclusions have been drawn from the simulation results, e.g., the higher regeneration temperature is conducive to increasing the AMRC; the higher ambient air temperature is conducive to increasing the AMRC and DCOP of the system; the higher ambient air humidity level will result in the bigger AMRC and the lower DCOP of the system; the higher initial moisture ratio of silica gel is in its favor for improving the DCOP, but unfavorable for increasing the AMRC; the optimal regeneration time aiming at the maximum AMRC or DCOP decreases as the regeneration temperature or the air velocity increases. And it increases as the ambient air temperature or humidity or the initial moisture content of silica gel increases. Ó 2014 Elsevier Ltd. All rights reserved.
Keywords: Silica gel Ultrasonic-assisted Regeneration Dehumidification system Regeneration time
1. Introduction The electricity consumption on air-conditioning system grows rapidly in recent years. The dehumidification, as an important airhandling process, can even consume about 40% of total electricity used in the air-conditioning system. Therefore, the development of a dehumidification technology under the concept of energy-saving would make sense. Compared to traditional cooling dehumidification method, independent desiccant-based air handling unit can improve the energy efficiency of air-conditioners and allows the utilization of waste heat or renewable energy [1]. As one of many dehumidifiers, the solid packed bed can deal with a great amount of moisture adsorption and can be applied to dehumidification processes. Silica gel, with great moisture adsorption capacity, has been widely utilized in dehumidifiers because its regeneration temperature is not very high. After the silica gel has been saturated with * Corresponding author. Institute of Refrigeration and Cryogenics, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China, 200240. Tel.: þ86 21 13641943577; fax: þ86 21 34206814. E-mail addresses: [email protected], [email protected] (Y. Yao). http://dx.doi.org/10.1016/j.energy.2014.01.061 0360-5442/Ó 2014 Elsevier Ltd. All rights reserved.
moisture, it needs to be regenerated to recover its adsorption capacity. The dehumidification performance of silica packed bed is influenced by many factors, e.g. bed configurations, regeneration method, operation conditions and so on. The investigators studied and provided many suggestions to improve the performance of packed bed dehumidification unit. For example, Hamed [2e4] presented the influences of bed configuration and investigated the dehumidification performances of vertical bed and radial flow hollow cylindrical bed. Singh [5] investigated the regeneration of silica gel in a multi-shelf dehumidifier and optimized the operation conditions to minimize the energy input. Kubota [6] has focused on the application of microwave heating as a regeneration energy source and pointed out the direct and rapid microwave heating method may achieve higher energy efficiency. Tian et al. [7,8] have studied the electro-osmotic regeneration for solid desiccant, which is described as a novel energy-saving and simple-structure regeneration method. Another novel hybrid regeneration process combining ultrasonic irradiation and conventional hot-air regeneration has been proposed by Yao [9]. The power ultrasound (above 16 kHz in frequency) is a kind of sound wave with good transmission directivity and strong
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Nomenclature a au A AMRC cp dm D DA DCOP G h DHwv k K LH m MRC pq P(z) Pe Pult S t u U/NU V w x Y z
area per unit bed volume, m2/m3 absorption coefficient of ultrasonic, dimensionless vertical cross-sectional area, m2 additional moisture removal capacity, kg/s specific heat capacity, kJ/(kg$K) average diameter of silica gel particles, m mass diffusivity coefficient, m2/s dry air dehumidification coefficient of performance mass flow rate of air, kg/s enthalpy, kJ/kg desorption/adsorption heat of water vapor, kJ/kg thermal conductivity, W/(m$ C) mass transfer coefficient, m/s latent heat of water vapor at the temperature of silica gel, kJ/kg mass, kg moisture removal capacity, kg/s saturation vapor pressure, Pa sound pressure, Pa electric power input, kW power of ultrasonic generator, W horizontal cross-sectional area, m2 temperature, C air speed, m/s with/without ultrasound volume of silica gel bed, m3 absolute humidity of air, kg water/(kg DA) distance from the windward side of bed, m moisture ratio, kg water/kg silica gel distance from the bottom of bed, m
penetration ability. When it propagates in solid material, the sound wave causes high frequency vibration, which can reduce thickness of the boundary layer near the surface of solid material and enhance the heat and mass transfer process. Meanwhile, part of the ultrasonic energy will be directly absorbed and cause a temperature rise in packed bed, which will increase the vapor pressure in equilibrium with desiccants. It has been proved that the way of applying ultrasound in silica gel regeneration process can decrease the regeneration temperature and make it easier to utilize lowgrade thermal energy [10]. However, the performance of the dehumidification system with ultrasonic regeneration is not investigated yet. For applications in which silica gel undergoes repeated water adsorption/regeneration cycles, data on regeneration conditions and time are needed to optimize the design of a desiccant system. Marciniak et al. [11] have made an economic analysis on the operating cost of a silica gel bed. Chang et al. [12] have made an adsorption performance analysis on the regeneration condition of a kind of modified silica gel. Meanwhile, the relevant theoretic studies have been performed by some researchers. San and Jiang [13] tested and analytically modeled a packed-bed silica gel dehumidification system based on the assumption of solid-side resistance method. They analyzed the heat and mass transfer process in the system at different temperatures. Fujii and Lior [14] developed a transient two-dimensional numerical model. The heat and mass transfer between a humid laminar air stream and a solid parallel desiccant bed were conjugated. In this model, an empirical correlation was used to calculate the water adsorption
Z
characteristic acoustic impedance, N$s/m3
Greek symbols ah convective heat transfer coefficient, W/(m2$ C) d working efficiency of ultrasonic transducer, dimensionless ε porosity of bed, dimensionless ht efficiency of electric heater, dimensionless m dynamic viscosity, kg/(m$s) v sound speed, m/s x attenuation coefficient, dimensionless r density, kg/m3 s time, s f relative humidity, % Superscripts e average * equilibrium with the silica gel Subscripts a air properties ads adsorption process amb ambient ave average dry dry sample f final of regeneration i initial of regeneration in inlet out outlet reg regeneration process s silica gel properties U/NU with/without ultrasound v water vapor properties
rate. The numerical model demonstrated that the conjugated method produced less error in thick-bed (i.e., order of 2 cm) desiccant systems compared to conventional, non-conjugated method. Peng et al. [15] tested and modeled the adsorption and dissolution process due to air flow through granular potash beds at non-equilibrium conditions. They built a one-dimensional transient heat and mass transfer model and found that non-equilibrium internal moisture and heat transfer processes can exist with significant property differences between the interstitial bed pore air and the potash particles. The objectives of this paper are as follows: 1) A model describing the ultrasonic-assisted regeneration and adsorption process of a dehumidification system is developed and experimentally validated; 2) The effects of ultrasonic-assisted regeneration on the performance of silica gel dehumidification system are investigated by the model simulations under a wide range of conditions. And the optimal regeneration time for achieving the greatest effect by the ultrasonic-assisted regeneration is particularly discussed.
2. Modeling and analysis method 2.1. Governing equations The heat and mass transfer model was developed based on the following assumptions:
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1) A single film mass transfer coefficient controls the transfer rate between the flowing air and the silica gel particles [4]; 2) Heat conduction as well as the mass diffusion within both air stream and desiccant material is negligible.; 3) Effects of other adsorbents in the air on the regeneration process are neglected; 4) The dynamic viscosity and specific heat capacity of dry air are assumed constant along the bed; 5) The bed is well thermal insulated; 6) The ambient atmosphere pressure is assumed to be 101 kPa and the pressure loss of the air stream is negligible.
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2.2. Boundary and initial conditions The initial and boundary conditions are given as below:
t ¼ 0 Yðx; 0Þ ¼ Y0 ts ðx; 0Þ ¼ ts;0 ; wðx; 0Þ ¼ w* ts;0 ; Y0 ta ðx; 0Þ ¼ ts;0 x ¼ 0
wð0; tÞ ¼ w0 ; ta ð0; tÞ ¼ ta;0
(9)
(10)
where, Y0 ¼ Yi,ta,0 ¼ ta,in for the regeneration process; Y0 ¼ Yf,ta,0 ¼ tamb for the following adsorption process.
Mass and energy balance for the drying air and desiccant materials can be expressed as follows:
vw 1 vw ¼ Ka w* w ε vx u vt vðYÞ Kara * w w ¼ vs ð1 εÞrs Kacp;v * vta ε vta ah a=1000 w w ðta ts Þ ¼ ðta ts Þ þ ra ucp;a u vs vx ucp;a ah a=1000 DHwv K ra a * vts ðta ts Þ w w þ bt s ¼ ð1 εÞrs cp;s ð1 εÞrs cp;s vs
2.3. Model parameters
(1a)
(2)
(3a)
The density and specific heat capacity of drying air are calculated by Eqs. (11)and (12), respectively [16].
ra ¼
101*ð1 þ wÞ 0:287ðt þ 273:15Þð1 þ 1:607858wÞ
cp;a ¼ 1:884w þ 1:005
(11) (12)
The saturation vapor pressure and moisture content of air, pq (Pa), can be gotten from Eq. (13) [17]:
(4)
where, bt s is the increase rate of silica gel temperature cased by the absorption of ultrasound. For regeneration process, bt s ¼ au dPult =1000ð1 εÞrs Vcp;s ; for adsorption process, bt s ¼ 0. Since the humidity and temperature of the drying air in the differential elements has little change, it can be neglected as well. Thus, the mass and the energy balance equation of the drying air (Eq. (1a) and Eq. (3a)) can be simplified as:
18:678t t 2 =234:5 pq ¼ 6:1121 exp 257:14 þ t
And the moisture content of air, w, can be calculated by Eq. (14):
w ¼
0:622$4$pq 101000 4$pq
(1b)
a a=1000 Kacp;v * vta ¼ h w w ðta ts Þ ðt t Þ þ ra ucp;a a s vx ucp;a
(3b)
(14)
The specific heat capacity of silica gel is given by Eq. (15) [18]:
cp;s ¼ 4:178 q þ 0:921
vw 1 ¼ Ka w* w vx u
(13)
(15)
The heat and mass transfer coefficients for the gas side in the silica gel bed are presented as:
ah ¼ Nu$ka =dm
(16)
All the governing equations are dispersed using a backward finite difference scheme as shown from Eqs. (5)e(8) and solved by Newton-Gauss method. Constant time step of 1 s and constant grid number of 50 are adopted in the simulation. An object-oriented programming language, C, on a personal computer is adopted to solve the mathematical model.
K ¼ Sh$D=dm
(17)
Nu ¼ 2 þ 0:6Pr 1=3 ,Re1=2
(18)
wji wji1 1 *j j Ka wi wi Dx u
Sh ¼ 2 þ 0:6Sc1=3 $Re1=2
(19)
j Yi
j
j1 Yi
Ds
Kara *j1 j wi ¼ wi ð1 εÞrs
j
ta;i ta;i1
Dx
(5)
(6)
Kac a a=1000 j p;v j j j ¼ h ta;i ts;i þ w*j wji ta;i ts;i i rs ucp;a ucp;a (7)
j
j1
ts;i ta;i1
Ds
a a=1000 j1 j1 t ¼ h ts;i ð1 εÞrs cp;s a;i DHwv K ra a *j1 j1 wi þ bt s wi þ ð1 εÞrs cp;s
(8)
The Nusselt number (Nu) and the Sherwood number (Sh) are calculated by Eqs.(18) and (19), respectively [19].
where, Pr is the Prandtl number, Sc is the Schmidt number, Re is the Reynolds number. The average velocity of air (u) is the synthesis speed of apparent horizontal velocity and vertical vibration velocity of air.
rffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 u ¼ u2 þ PðzÞ=Z
(20)
where, P(z) is the sound pressure at the height of z. It will decay by exponential law when the ultrasonic propagates in medium. Z is the characteristic acoustic impedance. They can be calculated, respectively, by Eq. (21) and Eq. (22).
PðzÞ ¼ P0 expð xzÞ
(21)
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Z ¼ rs vs
(22)
The sound pressure, P0, at the position of z ¼ 0 is given as:
P0 ¼
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ðPult d=SÞ$Z
(23)
The relative humidity of air in equilibrium with silica gel particles, 4*, can be expressed as a function of the moisture ratio (Y) and surface temperature (ts) of silica gel:
4* ¼ s1 ts Y 2 þ s2 ts Y þ s3 Y 4 þ s4 Y 3 þ s5 Y 2 þ s6 Y þ s7 LnðYÞ
(24)
where, the empirical constants, s1, s2, s3, s4, s5, s6, s7, can be determined by experiments. They are identified as 82.9, 4.64, 252148.6, 125044.6, 16001.7, 173.4, and 0.863, respectively, in the previous study [10]. The equality holds only for 0.045 (kg H2O/ kg dry silica gel)
DHwv
¼ LH$ 1 þ 0:2843e10:28Y
(25)
The attenuation coefficient, x, is measured as 0.07 in this study. The measurement method for the attenuation coefficient has been illustrated in Ref. [10].
(additional moisture removal capacity) brought by ultrasound and the DCOP (dehumidification coefficient of performance). The moisture removal capacity, MRC, is the mass flow rate of moisture removed by the desiccant system:
MRC ¼ Gðwin wout Þsads = sreg þ sads
(26)
where, the mass flow rate of process air, G, is calculated by:
G ¼ ra uA
(27)
The additional moisture removal capacity brought by ultrasound, AMRC, is defined as:
AMRC ¼ MRCU MRCNU
(28)
The dehumidification coefficient of performance, DCOP, represents the ratio of air enthalpy change during the dehumidification process to the energy consumption required for the regeneration process, which is written as:
DCOP ¼
G hamb hout;ads Pe
(29)
where, Pe is the power input. In the presence of ultrasound, Pe ¼ Pult =1000 þ Gðhin;reg hamb Þ=ht ; In the absence of ultrasound, Pe ¼ G(hin,reg hamb)/ht. Taking into account the heat loss of air duct, the efficiency of the electric heating system, ht, can be approximately set as 0.8 during the calculation.
2.4. Analysis method 3. Model validation To study the influence of ultrasound on the performance of the desiccant system under different conditions (e.g., the regeneration and process air conditions, the regeneration time), some performance-related indexes are necessarily put forward. They mainly include the MRC (moisture removal capacity), the AMRC
3.1. Experimental setup The schematic diagram and photo of experimental system is presented in Fig. 1. The basic information of the instruments is
Fig. 1. Schematic diagram of the experimental system.
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Table 1 Instruments and equipments in the experimental study. Name
Basic information
Type/Manufacturer
Air flow sensor Temperature & humidity sensor
0.3% of the measured data 0.8 in relative humidity (%); 0.1 C in temperature 0.1 g in absolute error Produce ultrasonic ranging from 0 to 100 MHz in frequency and 0e300 W in Power Compatible frequency: 23 kHz Maximum power input: 150 W Rated power: 800 W Wind pressure: 700 Pa Atomizing rate: 0.25 kg/h
ETFM-20/Shanghai CaoYi Ltd., China HHC2-S/OTRONIC Ltd, Sweden
Electronic balance Ultrasonic producer Ultrasonic transducer Centrifugal fan Atomizing humidifier
BS1500M/Shanghai Yousheng Ltd UGD/Taheda Hi-tech Company, China UGD/Taheda Hi-tech Company, China SYDF/Shanghai Yingda Fan Company Shiteng Electronic Ltd.
listed in Table 1, respectively. As known from Fig. 1, the experiments of desiccant regeneration/adsorption with and without ultrasonic radiation can be performed simultaneously. The inlet air conditions (temperature and humidity) for the experiments can be adjusted through the electric heater and atomizing humidifier. And the air flow rate in the two branch ducts can be regulated by the air valve.
The ducts in the experimental system are thermally insulated to reduce the influence of ambient environment on the air conditions during the experiments. In addition, the distance between the Tbend of duct and the air flow sensor is long enough to guarantee a laminar air flow passing through the air flow sensor to ensure the measurement precision. The merit of the experimental system design is that the air states before the two desiccant beds can be easily kept consistent. The silica gel (a kind of desiccant) used in this study has the particle size distribution of 5.0 1.0 mm in diameter. The basic physical properties of the trial sample are provided by the
Fig. 2. Simulated results versus experimental data for (a) regeneration processes; (b) adsorption processes.
Fig. 3. Effect of regeneration temperature on (a) MRC (moisture removal capacity); (b) DCOP (dehumidification coefficient of performance).
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manufacturer as follows: specific surface area ¼ 300e400 m2/g; pore diameter 8e10 nm; specific pore volume ¼ 0.8e1.0 mL/g. The vertical and horizontal cross section area of the silica gel packed bed is 0.007 m2 and 0.0038 m2, respectively. 3.2. Experiment results The experimental uncertainly analysis in our previous paper [10] shows that the largest experimental error is no more than 30%, so the results gotten from the experimental data are reliable. The regeneration conditions investigated include different temperatures (40, 50, 60 and 70 C) and humidity ratios (0.01, 0.015 and 0.02 kg water/kg DA) of the regeneration air and different regeneration time (20, 30 and 40 min). The relative humidity of the moist air for the adsorption experiments changes from 70% to 80% and the adsorption time varies from 10 min to 60 min. The comparisons of model results and experimental data are summarily plotted in Fig. 2. The results show that the model errors are less than 10% in most cases. It indicates that the calculated results by the model have a good agreement with the experimental data and can be safely used for a theoretical study.
with the model simulations. The simulation conditions are summarized as below: the air temperature for the silica gel regeneration ranges from 50 to 90 C; the air temperature and relative humidity for the silica gel adsorption ranges from 20 to 35 C and from 70 to 95%, respectively; the air velocity for the regeneration and adsorption process ranges from 0.5 to 4.5 m/s; the initial moisture ratio of silica gel for the regeneration process, which equals to the final one for the adsorption process, ranges from 0.10 to 0.20. The ultrasonic frequency and power is set as 23 kHz and 30 W, respectively. 4.1. Effect of operation conditions on system performance
The effects of ultrasonic-assisted regeneration on the performance of desiccant system under different conditions are studied
4.1.1. Effect of regeneration temperature The performances of dehumidification system with and without ultrasonic regeneration under different regeneration temperatures are presented in Fig. 3. The AMRC (additional moisture removal capacity), which demonstrates the enhancement of dehumidification capacity brought by ultrasound, is the difference of MRC (moisture removal capacity) between the ultrasonic and nonultrasonic situation. The legend ‘U’ and ‘NU’ denotes, respectively, the regeneration with and without ultrasonic radiation. Obviously, the MRC of the desiccant system will increase with the regeneration temperature. The curve of AMRC in Fig. 3(a) manifests that the applying of ultrasound can bring about more increase of dehumidification capacity under the higher regeneration temperature,
Fig. 4. Effect of temperature of ambient air on (a) MRC (moisture removal capacity); (b) DCOP (dehumidification coefficient of performance).
Fig. 5. Effect of relative humidity of ambient air on (a) MRC (moisture removal capacity); (b) DCOP (dehumidification coefficient of performance).
4. Simulation and discussion
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and the AMRC brought by ultrasound tends to be constant with the regeneration temperature increasing. The regeneration temperature will produce great influence on the DCOP (dehumidification coefficient of performance) of the system. As shown in Fig. 3(b), the DCOP first increases and then decreases with the regeneration temperature. It indicates that for any specific conditions, there should be an optimal regeneration temperature at which the system’s DCOP will be the highest. And it can be seen that the optimal regeneration temperature (aiming at the highest DCOP) under the ‘U’ case will be higher than that under the ‘NU’ case. Taking the conditions of Fig. 3 for example, the optimal regeneration temperature is about 62 C for the ‘U’ case and about 50 C for the ‘NU’ case. In addition, it can be also found that it may be not energy saving by applying ultrasound to the regeneration process if the regeneration temperature is lower than a critical point. In this case study, the critical regeneration temperature is identified as about 57 C. Usually, the MRC and the AMRC brought by the ultrasonic should be considered together with the DCOP. Therefore, the regeneration temperature between 65 C and 85 C is recommended for this case study.
4.1.2. Effect of conditions of ambient air The effects of ambient air conditions (i.e., air temperature and relative humidity) on the MRC and DCOP of the system are shown in Figs. 4 and 5. Basically, the MRC and DCOP will increase with the
Fig. 6. Effect of air velocity on (a) MRC (moisture removal capacity); (b) DCOP (dehumidification coefficient of performance).
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ambient air temperature. It is because increasing ambient air temperature means the increase of air humidity ratio as the air relative humidity is kept unchanged, which promotes the adsorption process and causes the MRC to rise. Meanwhile, the increase of ambient air temperature will decrease the energy consumption for regeneration. So, the higher ambient air temperature will result in the higher DCOP of the system. However, the DCOP seems to decrease with the increase of the ambient air relative humidity (See Fig. 5(b)). This is because more energy will be consumed for the regeneration under the higher humidity ratio of ambient air. The curve of AMRC (due to the ultrasonic-assisted regeneration) in Fig. 4(a) and Fig. 5(a) shows that the AMRC increases with the ambient air temperature and humidity, which indicates that the applying of ultrasound to the regeneration process can bring about more improvement of dehumidification capacity of the system under a more humid climate.
4.1.3. Effect of air velocity The air velocity will produce great influence on the MRC and DCOP of the system. It can be seen from Fig. 6 that the MRC has a remarkable increase with the air velocity and it is reverse for the DCOP. The increasing air velocity, on one hand, enhances the heat and mass transfer and hence causes the MRC to rise; on the other hand, increases the energy consumption for regeneration. As a result, the DCOP decreases with the air velocity.
Fig. 7. Effect of initial water content of silica gel on (a) MRC (moisture removal capacity); (b) DCOP (dehumidification coefficient of performance).
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As also shown in Fig. 6(a), the AMRC increases with the air velocity in the beginning and begins to drop when the air velocity is higher than a critical value (about 2.5 m/s in this case study). It indicates that there should be a best air velocity under which the ultrasonic-assisted regeneration will bring about the biggest AMRC. 4.1.4. Effect of initial moisture ratio of silica gel Fig. 7 gives the MRC and DCOP of the system under different initial moisture ratios of silica gel ranging from 0.11 kg water/(kg dry sample) to 0.2 kg water/(kg dry sample). The results show that the MRC decreases with the initial moisture ratio of silica gel. That is because the time required for adsorption process increases greatly as the initial moisture ratio of silica gel increases at the beginning of regeneration. For the DCOP, the higher initial moisture ratio of silica gel is in its favor since the dehumidification capacity of silica gel will be improved in such case. The AMRC in Fig. 7(a) manifests that more increase of moisture removal capacity can be brought by the ultrasonic-assisted regeneration under the larger initial moisture ratio of silica gel. The average vapor pressure difference between silica gel and process air is larger in the regeneration process under larger initial moisture ratio, so the ultrasonic-assisted regeneration will produce more dehumidification capacity.
4.2. Optimization of regeneration time The regeneration time is a key parameter affecting the performance of the system. The variations of MRC, AMRC and DCOP against the regeneration time ranging from 60 s to 600 s have been investigated under different conditions. Fig. 8 shows the results for the regeneration air temperature of 70 C, 80 C and 90 C. The AMRC and DCOP first rises and then drops with the regeneration time. The regeneration time corresponding to the peak value of AMRC and DCOP is found to decrease with the regeneration temperature increasing. For the regeneration temperature of 70 C, 80 C and 90 C, the maximum AMRC occurs at about 450 s, 360 s and 320 s in the regeneration time, respectively. And the regeneration time corresponding to the maximum DCOP is about 240 s, 210 s and 200 s, respectively. Under the higher regeneration temperature, the moisture adsorbed in the silica gel is easier to be desorbed. As a result, the regeneration time by applying ultrasound will be shorter. In addition, the energy-saving advantage of the system with ultrasound-assisted regeneration will disappear gradually with the increasing of regeneration time. It can be seen from Fig. 8(b) that there exists a critical regeneration time after which the DCOP in the presence of ultrasonic radiation will be lower than that in the absence of ultrasonic radiation. It indicates that the regeneration time should not exceed the critical time when the ultrasound is applied to the regeneration for improving the DCOP.
(a)
(b)
Fig. 8. Variations of MRC, AMRC and DCOP against regeneration time under different regeneration temperatures.
Fig. 9. Variations of MRC, AMRC and DCOP against regeneration time under different ambient air temperatures.
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Fig. 9 shows the results for different ambient air temperatures (20 C, 25 C, 30 C and 35 C). It can be seen that the higher AMRC is achieved and the more regeneration time is required for obtaining the maximum AMRC under the higher ambient air temperature. In this case, the regeneration time corresponding to the maximum AMRC is about 360 s, 370 s, 390 s and 420 s, respectively, for the ambient air temperature of 20 C, 25 C, 30 C and 35 C. It seems that the regeneration time corresponding to the maximum DCOP is affected little by the ambient air temperature, which is identically about 200 s for all the ambient air temperatures. The critical regeneration time (which is the upper limit time for the ultrasonic-assisted regeneration to get a higher DCOP) increases with the ambient air temperature increasing. As shown in Fig. 9(b), the critical regeneration time is estimated as about 380 s, 400 s, 420 s and 430 s, respectively, for the ambient air temperature of 20 C, 25 C, 30 C and 35 C. When the relative humidity is kept constant, the water content in air increases rapidly with the increasing of air temperature. Therefore, the silica gel can adsorb more water, and the regeneration time will be longer. Fig. 10 gives the results for different relative humidity levels of ambient air (70%, 80%, 90%). The results manifest the regeneration time corresponding to the maximum AMRC and DCOP has a small increase (from 260 s to 280 s and from 150 s to 160 s, respectively) as the relative humidity of ambient air rises from 70% to 90%. And so
is the case with the critical regeneration time only within which the ultrasonic-assisted regeneration helps to improve the DCOP. In Fig. 11, it can be seen that the optimal regeneration time for the maximum AMRC increases with the decrease of the air velocity, which is about 220 s, 270 s, 370 s and 620 s, respectively, for the air velocity of 2.0 m/s, 1.5 m/s, 1.0 m/s and 0.5 m/s. And the same regular pattern can be found for the optimal regeneration time aiming at the maximum DCOP (about 120 s, 150 s, 190 s and 310 s corresponding to the air velocity of 2.0 m/s, 1.5 m/s, 1.0 m/s and 0.5 m/s). In the regeneration process, the moisture content of silica gel decreases with time and it decreases much faster in the system with ultrasound. When it comes to a critical point, the moisture content becomes so small that it limits the regeneration rate of the ultrasound-assisted system. Under the larger air velocity, the moisture content of silica gel decreases faster and the critical time come earlier. Therefore, the optimal regeneration time should be shorter to maximize the AMRC. Fig. 12 shows that the lower initial moisture ratio of silica gel in the beginning of the regeneration process results in the shorter optimal regeneration time for the maximum AMRC and DCOP. In this case study, the regeneration time corresponding to the maximum AMRC and DCOP increases, respectively, from about 200 s to 350 s and from about 120 s to 180 as the initial moisture ratio of silica gel rises from 0.12 kg water/(kg dry sample) to 0.18 kg water/(kg dry sample). The AMRC reflects the contribution of ultrasonic-assisted regeneration to the dehumidification ability of desiccant material. The AMRC is expected to be as large as possible when the
Fig. 10. Variations of MRC, AMRC and DCOP against regeneration time under different ambient air humidity levels.
Fig. 11. Variations of MRC, AMRC and DCOP against regeneration time under different air velocities.
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respectively, the air velocity for the regeneration and adsorption process ranging from 0.5 to 4.5 m/s, the initial moisture ratio of silica gel for the regeneration process ranging from 0.10 to 0.20. Particularly, the optimal regeneration time aiming at the maximum AMRC and DCOP is particularly discussed. The main regular patterns can be summarized according to the simulation results: 1) The higher regeneration temperature is conducive to increasing the AMRC brought by the ultrasonic-assisted regeneration. And there is an appropriate regeneration temperature to get the highest DCOP. For this case study, the regeneration temperature between 65 C and 85 C is recommended. 2) The higher ambient air temperature is conducive to increasing the AMRC and DCOP of the dehumidification system. 3) The higher ambient air humidity level will result in the bigger AMRC and the lower DCOP of the dehumidification system. 4) The DCOP of the dehumidification system will decrease with the air velocity increasing. And there is an appropriate air velocity to get the biggest AMRC (about 2.5 m/s in this case study). 5) The higher initial moisture ratio of silica gel is in its favor for improving the DCOP, but unfavorable for increasing the AMRC. 6) The optimal regeneration time aiming at the maximum AMRC or DCOP decreases as the regeneration temperature or the air velocity increases. And situation is the opposite as the ambient air temperature or humidity or the initial moisture content of silica gel increases. Acknowledgments This work was supported by Shanghai Pujiang Program (2012) and a grant from the National Natural Science Foundation of China (No.11274279). Fig. 12. Variations of MRC, AMRC and DCOP against regeneration time under different initial moisture ratios.
ultrasound is applied to the regeneration process. At the same time, the DCOP must be taken into account from the perspective of energy saving. As indicated from Figs. 8e12, the optimal regeneration time required for the maximum AMRC is not consistent with that for the maximum DCOP. And the former is longer than the latter for all the simulation conditions. To achieve a relatively high AMRC and DCOP simultaneously, the recommended regeneration time should be between the optimal regeneration time for the maximum AMRC and that for the maximum DCOP. Combined the effect of all parameters, the recommended regeneration time is about 250e300 s for the baseline operation conditions as below: 80 C in the regeneration temperature, 25 C and 80%, respectively, in the process air temperature and humidity, and 1.0 m/s in the regeneration air velocity. 5. Conclusions A theoretical model is developed for predicting the performance of silica gel dehumidification system with ultrasonic-assisted regeneration. The model has been validated by a series of experiments, which shows that the model errors are mostly less than 10%. Afterwards, the model is used to investigate the effects of ultrasonic-assisted regeneration on the performance of silica gel dehumidification system under a wide range of conditions including the regeneration temperature ranging from 50 to 90 C, the air temperature and relative humidity for the silica gel adsorption ranging from 20 to 35 C and from 70 to 95%,
References [1] Zhang LZ. Energy performance of independent air dehumidification systems with energy recovery measures. Energy 2006;31(8e9):1228e42. [2] Hamed AM. Theoretical and experimental study on the transient adsorption characteristics of a vertical packed porous bed. Renew Energy 2002;27(4): 525e41. [3] Hamed AM. Experimental investigation on the adsorption/desorption processes using solid desiccant in an inclined-fluidized bed. Renew Energy 2005;30(12):1913e21. [4] Awad MM, Ramzy AK, Hamed AM, Bekheit MM. Theoretical and experimental investigation on the radial flow desiccant dehumidification bed. Appl Therm Eng 2008;28(1):75e85. [5] Singh S, Singh PP. Regeneration of silica gel in multi-shelf regenerator. Renew Energy 1998;13(1):105e19. [6] Kubota M, Takuya Hanada, Satoshi Yabe, Dalibor Kuchar, Hitoki Matsuda. Water desorption behavior of desiccant rotor under microwave irradiation. Appl Therm Eng 2011;31(8e9):1482e6. [7] Qi RH, Tian CQ, Shao ShQ, Tang MSh, Lu L. Experimental investigation on performance improvement of electro-osmotic regeneration for solid desiccant. Appl Energy 2011;88(8):2816e23. [8] Qi RH, Tian CQ, Shao ShQ. Experimental investigation on possibility of electroosmotic regeneration for solid desiccant. Appl Energy 2010;87(7):2266e72. [9] Yao Y. Using power ultrasound for the regeneration of dehumidizers in desiccant air-conditioning systems: a review of prospective studies and unexplored issues. Renew Sustain Energy Rev 2010;14(7):1860e73. [10] Yang K, Yao Y, Liu SQ. Effect of applying ultrasonic on the regeneration of silica gel under different air conditions. Int J Therm Sci 2012;61(0):67e78. [11] Marciniak TJ, Grolmes MA, Epstein M. Solid desiccant dehumidification systems for residential applications. In: Final Report, Oct. 1983eMar. 1985. Burr Ridge, IL: Fauske and Associates, Inc.; 1985. [12] Chang KS, Wang HC, Chung TW. Effect of regeneration conditions on the adsorption dehumidification process in packed silica gel beds. Appl Therm Eng 2004;24(5e6):735e42. [13] San JY, Jiang GD. Modeling and testing of a silica gel packed-bed system. Int J Heat Mass Transf 1994;37(8):1173e9. [14] Fujii Y, Lior N. Conjugate heat and mass transfer in a desiccant-airflow system: a numerical solution method. Numer Heat Transf Part A Appl 1996;29(7): 689e706.
Y. Yao et al. / Energy 66 (2014) 799e809 [15] Pen S-W, Besant RW, Strathdee G. Heat and mass transfer in granular potash fertilizer with a surface dissolution reaction. Can J Chem Eng 2000;78(6): 1076e86. [16] ASHRAE. ASHRAE handbook, in psychrometrics; 2009. pp. 20e1. [17] Buck AL. New equations for computing vapor pressure and enhancement factor. J Appl Meteor 1981;20(12):1527e32.
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[18] Pesaran AA, Mills AF. Moisture transport in silica gel packed bedsdI.Theoretical study. Int J Heat Mass Transf 1987;30(6):1037e49. [19] Bird RB, Stewart WE, Lightfoot EN. Transport phenomena. New York: Wiley; 1960. [20] San JY. Heat and mass transfer in a two-dimensional cross-flow regenerator with a solid conduction effect. Int J Heat Mass Transf 1993;36(3):633e43.
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Energy journal homepage: www.elsevier.com/locate/energy
Study on the performance of silica gel dehumidification system with ultrasonic-assisted regeneration Ye Yao a, b, *, Kun Yang a, Shiqing Liu c a
Institute of Refrigeration and Cryogenics, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China, 200240 Key Laboratory of Energy Thermal Conversion and Control, Ministry of Education, School of Energy and Environment, Southeast University, Nanjing, China, 210096 c School of Mathematics and Physics, Zhejiang Normal University, Jinhua, Zhejiang Province 321004, China b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 3 July 2013 Received in revised form 26 November 2013 Accepted 18 January 2014 Available online 20 February 2014
A theoretic model is developed to describe the moisture desorption-and-adsorption cycle of silica gel dehumidification system with or without ultrasonic-assisted regeneration. The model has been validated by a series of experiments. The AMRC (additional moisture removal capacity) and the DCOP (dehumidification coefficient of performance) are suggested to illustrate the performance of silica gel dehumidification system with ultrasonic radiation. The effects of ultrasonic-assisted regeneration on the performance of the dehumidification system are investigated with the model under different conditions. Some crucial conclusions have been drawn from the simulation results, e.g., the higher regeneration temperature is conducive to increasing the AMRC; the higher ambient air temperature is conducive to increasing the AMRC and DCOP of the system; the higher ambient air humidity level will result in the bigger AMRC and the lower DCOP of the system; the higher initial moisture ratio of silica gel is in its favor for improving the DCOP, but unfavorable for increasing the AMRC; the optimal regeneration time aiming at the maximum AMRC or DCOP decreases as the regeneration temperature or the air velocity increases. And it increases as the ambient air temperature or humidity or the initial moisture content of silica gel increases. Ó 2014 Elsevier Ltd. All rights reserved.
Keywords: Silica gel Ultrasonic-assisted Regeneration Dehumidification system Regeneration time
1. Introduction The electricity consumption on air-conditioning system grows rapidly in recent years. The dehumidification, as an important airhandling process, can even consume about 40% of total electricity used in the air-conditioning system. Therefore, the development of a dehumidification technology under the concept of energy-saving would make sense. Compared to traditional cooling dehumidification method, independent desiccant-based air handling unit can improve the energy efficiency of air-conditioners and allows the utilization of waste heat or renewable energy [1]. As one of many dehumidifiers, the solid packed bed can deal with a great amount of moisture adsorption and can be applied to dehumidification processes. Silica gel, with great moisture adsorption capacity, has been widely utilized in dehumidifiers because its regeneration temperature is not very high. After the silica gel has been saturated with * Corresponding author. Institute of Refrigeration and Cryogenics, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China, 200240. Tel.: þ86 21 13641943577; fax: þ86 21 34206814. E-mail addresses: [email protected], [email protected] (Y. Yao). http://dx.doi.org/10.1016/j.energy.2014.01.061 0360-5442/Ó 2014 Elsevier Ltd. All rights reserved.
moisture, it needs to be regenerated to recover its adsorption capacity. The dehumidification performance of silica packed bed is influenced by many factors, e.g. bed configurations, regeneration method, operation conditions and so on. The investigators studied and provided many suggestions to improve the performance of packed bed dehumidification unit. For example, Hamed [2e4] presented the influences of bed configuration and investigated the dehumidification performances of vertical bed and radial flow hollow cylindrical bed. Singh [5] investigated the regeneration of silica gel in a multi-shelf dehumidifier and optimized the operation conditions to minimize the energy input. Kubota [6] has focused on the application of microwave heating as a regeneration energy source and pointed out the direct and rapid microwave heating method may achieve higher energy efficiency. Tian et al. [7,8] have studied the electro-osmotic regeneration for solid desiccant, which is described as a novel energy-saving and simple-structure regeneration method. Another novel hybrid regeneration process combining ultrasonic irradiation and conventional hot-air regeneration has been proposed by Yao [9]. The power ultrasound (above 16 kHz in frequency) is a kind of sound wave with good transmission directivity and strong
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Nomenclature a au A AMRC cp dm D DA DCOP G h DHwv k K LH m MRC pq P(z) Pe Pult S t u U/NU V w x Y z
area per unit bed volume, m2/m3 absorption coefficient of ultrasonic, dimensionless vertical cross-sectional area, m2 additional moisture removal capacity, kg/s specific heat capacity, kJ/(kg$K) average diameter of silica gel particles, m mass diffusivity coefficient, m2/s dry air dehumidification coefficient of performance mass flow rate of air, kg/s enthalpy, kJ/kg desorption/adsorption heat of water vapor, kJ/kg thermal conductivity, W/(m$ C) mass transfer coefficient, m/s latent heat of water vapor at the temperature of silica gel, kJ/kg mass, kg moisture removal capacity, kg/s saturation vapor pressure, Pa sound pressure, Pa electric power input, kW power of ultrasonic generator, W horizontal cross-sectional area, m2 temperature, C air speed, m/s with/without ultrasound volume of silica gel bed, m3 absolute humidity of air, kg water/(kg DA) distance from the windward side of bed, m moisture ratio, kg water/kg silica gel distance from the bottom of bed, m
penetration ability. When it propagates in solid material, the sound wave causes high frequency vibration, which can reduce thickness of the boundary layer near the surface of solid material and enhance the heat and mass transfer process. Meanwhile, part of the ultrasonic energy will be directly absorbed and cause a temperature rise in packed bed, which will increase the vapor pressure in equilibrium with desiccants. It has been proved that the way of applying ultrasound in silica gel regeneration process can decrease the regeneration temperature and make it easier to utilize lowgrade thermal energy [10]. However, the performance of the dehumidification system with ultrasonic regeneration is not investigated yet. For applications in which silica gel undergoes repeated water adsorption/regeneration cycles, data on regeneration conditions and time are needed to optimize the design of a desiccant system. Marciniak et al. [11] have made an economic analysis on the operating cost of a silica gel bed. Chang et al. [12] have made an adsorption performance analysis on the regeneration condition of a kind of modified silica gel. Meanwhile, the relevant theoretic studies have been performed by some researchers. San and Jiang [13] tested and analytically modeled a packed-bed silica gel dehumidification system based on the assumption of solid-side resistance method. They analyzed the heat and mass transfer process in the system at different temperatures. Fujii and Lior [14] developed a transient two-dimensional numerical model. The heat and mass transfer between a humid laminar air stream and a solid parallel desiccant bed were conjugated. In this model, an empirical correlation was used to calculate the water adsorption
Z
characteristic acoustic impedance, N$s/m3
Greek symbols ah convective heat transfer coefficient, W/(m2$ C) d working efficiency of ultrasonic transducer, dimensionless ε porosity of bed, dimensionless ht efficiency of electric heater, dimensionless m dynamic viscosity, kg/(m$s) v sound speed, m/s x attenuation coefficient, dimensionless r density, kg/m3 s time, s f relative humidity, % Superscripts e average * equilibrium with the silica gel Subscripts a air properties ads adsorption process amb ambient ave average dry dry sample f final of regeneration i initial of regeneration in inlet out outlet reg regeneration process s silica gel properties U/NU with/without ultrasound v water vapor properties
rate. The numerical model demonstrated that the conjugated method produced less error in thick-bed (i.e., order of 2 cm) desiccant systems compared to conventional, non-conjugated method. Peng et al. [15] tested and modeled the adsorption and dissolution process due to air flow through granular potash beds at non-equilibrium conditions. They built a one-dimensional transient heat and mass transfer model and found that non-equilibrium internal moisture and heat transfer processes can exist with significant property differences between the interstitial bed pore air and the potash particles. The objectives of this paper are as follows: 1) A model describing the ultrasonic-assisted regeneration and adsorption process of a dehumidification system is developed and experimentally validated; 2) The effects of ultrasonic-assisted regeneration on the performance of silica gel dehumidification system are investigated by the model simulations under a wide range of conditions. And the optimal regeneration time for achieving the greatest effect by the ultrasonic-assisted regeneration is particularly discussed.
2. Modeling and analysis method 2.1. Governing equations The heat and mass transfer model was developed based on the following assumptions:
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1) A single film mass transfer coefficient controls the transfer rate between the flowing air and the silica gel particles [4]; 2) Heat conduction as well as the mass diffusion within both air stream and desiccant material is negligible.; 3) Effects of other adsorbents in the air on the regeneration process are neglected; 4) The dynamic viscosity and specific heat capacity of dry air are assumed constant along the bed; 5) The bed is well thermal insulated; 6) The ambient atmosphere pressure is assumed to be 101 kPa and the pressure loss of the air stream is negligible.
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2.2. Boundary and initial conditions The initial and boundary conditions are given as below:
t ¼ 0 Yðx; 0Þ ¼ Y0 ts ðx; 0Þ ¼ ts;0 ; wðx; 0Þ ¼ w* ts;0 ; Y0 ta ðx; 0Þ ¼ ts;0 x ¼ 0
wð0; tÞ ¼ w0 ; ta ð0; tÞ ¼ ta;0
(9)
(10)
where, Y0 ¼ Yi,ta,0 ¼ ta,in for the regeneration process; Y0 ¼ Yf,ta,0 ¼ tamb for the following adsorption process.
Mass and energy balance for the drying air and desiccant materials can be expressed as follows:
vw 1 vw ¼ Ka w* w ε vx u vt vðYÞ Kara * w w ¼ vs ð1 εÞrs Kacp;v * vta ε vta ah a=1000 w w ðta ts Þ ¼ ðta ts Þ þ ra ucp;a u vs vx ucp;a ah a=1000 DHwv K ra a * vts ðta ts Þ w w þ bt s ¼ ð1 εÞrs cp;s ð1 εÞrs cp;s vs
2.3. Model parameters
(1a)
(2)
(3a)
The density and specific heat capacity of drying air are calculated by Eqs. (11)and (12), respectively [16].
ra ¼
101*ð1 þ wÞ 0:287ðt þ 273:15Þð1 þ 1:607858wÞ
cp;a ¼ 1:884w þ 1:005
(11) (12)
The saturation vapor pressure and moisture content of air, pq (Pa), can be gotten from Eq. (13) [17]:
(4)
where, bt s is the increase rate of silica gel temperature cased by the absorption of ultrasound. For regeneration process, bt s ¼ au dPult =1000ð1 εÞrs Vcp;s ; for adsorption process, bt s ¼ 0. Since the humidity and temperature of the drying air in the differential elements has little change, it can be neglected as well. Thus, the mass and the energy balance equation of the drying air (Eq. (1a) and Eq. (3a)) can be simplified as:
18:678t t 2 =234:5 pq ¼ 6:1121 exp 257:14 þ t
And the moisture content of air, w, can be calculated by Eq. (14):
w ¼
0:622$4$pq 101000 4$pq
(1b)
a a=1000 Kacp;v * vta ¼ h w w ðta ts Þ ðt t Þ þ ra ucp;a a s vx ucp;a
(3b)
(14)
The specific heat capacity of silica gel is given by Eq. (15) [18]:
cp;s ¼ 4:178 q þ 0:921
vw 1 ¼ Ka w* w vx u
(13)
(15)
The heat and mass transfer coefficients for the gas side in the silica gel bed are presented as:
ah ¼ Nu$ka =dm
(16)
All the governing equations are dispersed using a backward finite difference scheme as shown from Eqs. (5)e(8) and solved by Newton-Gauss method. Constant time step of 1 s and constant grid number of 50 are adopted in the simulation. An object-oriented programming language, C, on a personal computer is adopted to solve the mathematical model.
K ¼ Sh$D=dm
(17)
Nu ¼ 2 þ 0:6Pr 1=3 ,Re1=2
(18)
wji wji1 1 *j j Ka wi wi Dx u
Sh ¼ 2 þ 0:6Sc1=3 $Re1=2
(19)
j Yi
j
j1 Yi
Ds
Kara *j1 j wi ¼ wi ð1 εÞrs
j
ta;i ta;i1
Dx
(5)
(6)
Kac a a=1000 j p;v j j j ¼ h ta;i ts;i þ w*j wji ta;i ts;i i rs ucp;a ucp;a (7)
j
j1
ts;i ta;i1
Ds
a a=1000 j1 j1 t ¼ h ts;i ð1 εÞrs cp;s a;i DHwv K ra a *j1 j1 wi þ bt s wi þ ð1 εÞrs cp;s
(8)
The Nusselt number (Nu) and the Sherwood number (Sh) are calculated by Eqs.(18) and (19), respectively [19].
where, Pr is the Prandtl number, Sc is the Schmidt number, Re is the Reynolds number. The average velocity of air (u) is the synthesis speed of apparent horizontal velocity and vertical vibration velocity of air.
rffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 u ¼ u2 þ PðzÞ=Z
(20)
where, P(z) is the sound pressure at the height of z. It will decay by exponential law when the ultrasonic propagates in medium. Z is the characteristic acoustic impedance. They can be calculated, respectively, by Eq. (21) and Eq. (22).
PðzÞ ¼ P0 expð xzÞ
(21)
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Z ¼ rs vs
(22)
The sound pressure, P0, at the position of z ¼ 0 is given as:
P0 ¼
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ðPult d=SÞ$Z
(23)
The relative humidity of air in equilibrium with silica gel particles, 4*, can be expressed as a function of the moisture ratio (Y) and surface temperature (ts) of silica gel:
4* ¼ s1 ts Y 2 þ s2 ts Y þ s3 Y 4 þ s4 Y 3 þ s5 Y 2 þ s6 Y þ s7 LnðYÞ
(24)
where, the empirical constants, s1, s2, s3, s4, s5, s6, s7, can be determined by experiments. They are identified as 82.9, 4.64, 252148.6, 125044.6, 16001.7, 173.4, and 0.863, respectively, in the previous study [10]. The equality holds only for 0.045 (kg H2O/ kg dry silica gel)
DHwv
¼ LH$ 1 þ 0:2843e10:28Y
(25)
The attenuation coefficient, x, is measured as 0.07 in this study. The measurement method for the attenuation coefficient has been illustrated in Ref. [10].
(additional moisture removal capacity) brought by ultrasound and the DCOP (dehumidification coefficient of performance). The moisture removal capacity, MRC, is the mass flow rate of moisture removed by the desiccant system:
MRC ¼ Gðwin wout Þsads = sreg þ sads
(26)
where, the mass flow rate of process air, G, is calculated by:
G ¼ ra uA
(27)
The additional moisture removal capacity brought by ultrasound, AMRC, is defined as:
AMRC ¼ MRCU MRCNU
(28)
The dehumidification coefficient of performance, DCOP, represents the ratio of air enthalpy change during the dehumidification process to the energy consumption required for the regeneration process, which is written as:
DCOP ¼
G hamb hout;ads Pe
(29)
where, Pe is the power input. In the presence of ultrasound, Pe ¼ Pult =1000 þ Gðhin;reg hamb Þ=ht ; In the absence of ultrasound, Pe ¼ G(hin,reg hamb)/ht. Taking into account the heat loss of air duct, the efficiency of the electric heating system, ht, can be approximately set as 0.8 during the calculation.
2.4. Analysis method 3. Model validation To study the influence of ultrasound on the performance of the desiccant system under different conditions (e.g., the regeneration and process air conditions, the regeneration time), some performance-related indexes are necessarily put forward. They mainly include the MRC (moisture removal capacity), the AMRC
3.1. Experimental setup The schematic diagram and photo of experimental system is presented in Fig. 1. The basic information of the instruments is
Fig. 1. Schematic diagram of the experimental system.
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Table 1 Instruments and equipments in the experimental study. Name
Basic information
Type/Manufacturer
Air flow sensor Temperature & humidity sensor
0.3% of the measured data 0.8 in relative humidity (%); 0.1 C in temperature 0.1 g in absolute error Produce ultrasonic ranging from 0 to 100 MHz in frequency and 0e300 W in Power Compatible frequency: 23 kHz Maximum power input: 150 W Rated power: 800 W Wind pressure: 700 Pa Atomizing rate: 0.25 kg/h
ETFM-20/Shanghai CaoYi Ltd., China HHC2-S/OTRONIC Ltd, Sweden
Electronic balance Ultrasonic producer Ultrasonic transducer Centrifugal fan Atomizing humidifier
BS1500M/Shanghai Yousheng Ltd UGD/Taheda Hi-tech Company, China UGD/Taheda Hi-tech Company, China SYDF/Shanghai Yingda Fan Company Shiteng Electronic Ltd.
listed in Table 1, respectively. As known from Fig. 1, the experiments of desiccant regeneration/adsorption with and without ultrasonic radiation can be performed simultaneously. The inlet air conditions (temperature and humidity) for the experiments can be adjusted through the electric heater and atomizing humidifier. And the air flow rate in the two branch ducts can be regulated by the air valve.
The ducts in the experimental system are thermally insulated to reduce the influence of ambient environment on the air conditions during the experiments. In addition, the distance between the Tbend of duct and the air flow sensor is long enough to guarantee a laminar air flow passing through the air flow sensor to ensure the measurement precision. The merit of the experimental system design is that the air states before the two desiccant beds can be easily kept consistent. The silica gel (a kind of desiccant) used in this study has the particle size distribution of 5.0 1.0 mm in diameter. The basic physical properties of the trial sample are provided by the
Fig. 2. Simulated results versus experimental data for (a) regeneration processes; (b) adsorption processes.
Fig. 3. Effect of regeneration temperature on (a) MRC (moisture removal capacity); (b) DCOP (dehumidification coefficient of performance).
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manufacturer as follows: specific surface area ¼ 300e400 m2/g; pore diameter 8e10 nm; specific pore volume ¼ 0.8e1.0 mL/g. The vertical and horizontal cross section area of the silica gel packed bed is 0.007 m2 and 0.0038 m2, respectively. 3.2. Experiment results The experimental uncertainly analysis in our previous paper [10] shows that the largest experimental error is no more than 30%, so the results gotten from the experimental data are reliable. The regeneration conditions investigated include different temperatures (40, 50, 60 and 70 C) and humidity ratios (0.01, 0.015 and 0.02 kg water/kg DA) of the regeneration air and different regeneration time (20, 30 and 40 min). The relative humidity of the moist air for the adsorption experiments changes from 70% to 80% and the adsorption time varies from 10 min to 60 min. The comparisons of model results and experimental data are summarily plotted in Fig. 2. The results show that the model errors are less than 10% in most cases. It indicates that the calculated results by the model have a good agreement with the experimental data and can be safely used for a theoretical study.
with the model simulations. The simulation conditions are summarized as below: the air temperature for the silica gel regeneration ranges from 50 to 90 C; the air temperature and relative humidity for the silica gel adsorption ranges from 20 to 35 C and from 70 to 95%, respectively; the air velocity for the regeneration and adsorption process ranges from 0.5 to 4.5 m/s; the initial moisture ratio of silica gel for the regeneration process, which equals to the final one for the adsorption process, ranges from 0.10 to 0.20. The ultrasonic frequency and power is set as 23 kHz and 30 W, respectively. 4.1. Effect of operation conditions on system performance
The effects of ultrasonic-assisted regeneration on the performance of desiccant system under different conditions are studied
4.1.1. Effect of regeneration temperature The performances of dehumidification system with and without ultrasonic regeneration under different regeneration temperatures are presented in Fig. 3. The AMRC (additional moisture removal capacity), which demonstrates the enhancement of dehumidification capacity brought by ultrasound, is the difference of MRC (moisture removal capacity) between the ultrasonic and nonultrasonic situation. The legend ‘U’ and ‘NU’ denotes, respectively, the regeneration with and without ultrasonic radiation. Obviously, the MRC of the desiccant system will increase with the regeneration temperature. The curve of AMRC in Fig. 3(a) manifests that the applying of ultrasound can bring about more increase of dehumidification capacity under the higher regeneration temperature,
Fig. 4. Effect of temperature of ambient air on (a) MRC (moisture removal capacity); (b) DCOP (dehumidification coefficient of performance).
Fig. 5. Effect of relative humidity of ambient air on (a) MRC (moisture removal capacity); (b) DCOP (dehumidification coefficient of performance).
4. Simulation and discussion
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and the AMRC brought by ultrasound tends to be constant with the regeneration temperature increasing. The regeneration temperature will produce great influence on the DCOP (dehumidification coefficient of performance) of the system. As shown in Fig. 3(b), the DCOP first increases and then decreases with the regeneration temperature. It indicates that for any specific conditions, there should be an optimal regeneration temperature at which the system’s DCOP will be the highest. And it can be seen that the optimal regeneration temperature (aiming at the highest DCOP) under the ‘U’ case will be higher than that under the ‘NU’ case. Taking the conditions of Fig. 3 for example, the optimal regeneration temperature is about 62 C for the ‘U’ case and about 50 C for the ‘NU’ case. In addition, it can be also found that it may be not energy saving by applying ultrasound to the regeneration process if the regeneration temperature is lower than a critical point. In this case study, the critical regeneration temperature is identified as about 57 C. Usually, the MRC and the AMRC brought by the ultrasonic should be considered together with the DCOP. Therefore, the regeneration temperature between 65 C and 85 C is recommended for this case study.
4.1.2. Effect of conditions of ambient air The effects of ambient air conditions (i.e., air temperature and relative humidity) on the MRC and DCOP of the system are shown in Figs. 4 and 5. Basically, the MRC and DCOP will increase with the
Fig. 6. Effect of air velocity on (a) MRC (moisture removal capacity); (b) DCOP (dehumidification coefficient of performance).
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ambient air temperature. It is because increasing ambient air temperature means the increase of air humidity ratio as the air relative humidity is kept unchanged, which promotes the adsorption process and causes the MRC to rise. Meanwhile, the increase of ambient air temperature will decrease the energy consumption for regeneration. So, the higher ambient air temperature will result in the higher DCOP of the system. However, the DCOP seems to decrease with the increase of the ambient air relative humidity (See Fig. 5(b)). This is because more energy will be consumed for the regeneration under the higher humidity ratio of ambient air. The curve of AMRC (due to the ultrasonic-assisted regeneration) in Fig. 4(a) and Fig. 5(a) shows that the AMRC increases with the ambient air temperature and humidity, which indicates that the applying of ultrasound to the regeneration process can bring about more improvement of dehumidification capacity of the system under a more humid climate.
4.1.3. Effect of air velocity The air velocity will produce great influence on the MRC and DCOP of the system. It can be seen from Fig. 6 that the MRC has a remarkable increase with the air velocity and it is reverse for the DCOP. The increasing air velocity, on one hand, enhances the heat and mass transfer and hence causes the MRC to rise; on the other hand, increases the energy consumption for regeneration. As a result, the DCOP decreases with the air velocity.
Fig. 7. Effect of initial water content of silica gel on (a) MRC (moisture removal capacity); (b) DCOP (dehumidification coefficient of performance).
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As also shown in Fig. 6(a), the AMRC increases with the air velocity in the beginning and begins to drop when the air velocity is higher than a critical value (about 2.5 m/s in this case study). It indicates that there should be a best air velocity under which the ultrasonic-assisted regeneration will bring about the biggest AMRC. 4.1.4. Effect of initial moisture ratio of silica gel Fig. 7 gives the MRC and DCOP of the system under different initial moisture ratios of silica gel ranging from 0.11 kg water/(kg dry sample) to 0.2 kg water/(kg dry sample). The results show that the MRC decreases with the initial moisture ratio of silica gel. That is because the time required for adsorption process increases greatly as the initial moisture ratio of silica gel increases at the beginning of regeneration. For the DCOP, the higher initial moisture ratio of silica gel is in its favor since the dehumidification capacity of silica gel will be improved in such case. The AMRC in Fig. 7(a) manifests that more increase of moisture removal capacity can be brought by the ultrasonic-assisted regeneration under the larger initial moisture ratio of silica gel. The average vapor pressure difference between silica gel and process air is larger in the regeneration process under larger initial moisture ratio, so the ultrasonic-assisted regeneration will produce more dehumidification capacity.
4.2. Optimization of regeneration time The regeneration time is a key parameter affecting the performance of the system. The variations of MRC, AMRC and DCOP against the regeneration time ranging from 60 s to 600 s have been investigated under different conditions. Fig. 8 shows the results for the regeneration air temperature of 70 C, 80 C and 90 C. The AMRC and DCOP first rises and then drops with the regeneration time. The regeneration time corresponding to the peak value of AMRC and DCOP is found to decrease with the regeneration temperature increasing. For the regeneration temperature of 70 C, 80 C and 90 C, the maximum AMRC occurs at about 450 s, 360 s and 320 s in the regeneration time, respectively. And the regeneration time corresponding to the maximum DCOP is about 240 s, 210 s and 200 s, respectively. Under the higher regeneration temperature, the moisture adsorbed in the silica gel is easier to be desorbed. As a result, the regeneration time by applying ultrasound will be shorter. In addition, the energy-saving advantage of the system with ultrasound-assisted regeneration will disappear gradually with the increasing of regeneration time. It can be seen from Fig. 8(b) that there exists a critical regeneration time after which the DCOP in the presence of ultrasonic radiation will be lower than that in the absence of ultrasonic radiation. It indicates that the regeneration time should not exceed the critical time when the ultrasound is applied to the regeneration for improving the DCOP.
(a)
(b)
Fig. 8. Variations of MRC, AMRC and DCOP against regeneration time under different regeneration temperatures.
Fig. 9. Variations of MRC, AMRC and DCOP against regeneration time under different ambient air temperatures.
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Fig. 9 shows the results for different ambient air temperatures (20 C, 25 C, 30 C and 35 C). It can be seen that the higher AMRC is achieved and the more regeneration time is required for obtaining the maximum AMRC under the higher ambient air temperature. In this case, the regeneration time corresponding to the maximum AMRC is about 360 s, 370 s, 390 s and 420 s, respectively, for the ambient air temperature of 20 C, 25 C, 30 C and 35 C. It seems that the regeneration time corresponding to the maximum DCOP is affected little by the ambient air temperature, which is identically about 200 s for all the ambient air temperatures. The critical regeneration time (which is the upper limit time for the ultrasonic-assisted regeneration to get a higher DCOP) increases with the ambient air temperature increasing. As shown in Fig. 9(b), the critical regeneration time is estimated as about 380 s, 400 s, 420 s and 430 s, respectively, for the ambient air temperature of 20 C, 25 C, 30 C and 35 C. When the relative humidity is kept constant, the water content in air increases rapidly with the increasing of air temperature. Therefore, the silica gel can adsorb more water, and the regeneration time will be longer. Fig. 10 gives the results for different relative humidity levels of ambient air (70%, 80%, 90%). The results manifest the regeneration time corresponding to the maximum AMRC and DCOP has a small increase (from 260 s to 280 s and from 150 s to 160 s, respectively) as the relative humidity of ambient air rises from 70% to 90%. And so
is the case with the critical regeneration time only within which the ultrasonic-assisted regeneration helps to improve the DCOP. In Fig. 11, it can be seen that the optimal regeneration time for the maximum AMRC increases with the decrease of the air velocity, which is about 220 s, 270 s, 370 s and 620 s, respectively, for the air velocity of 2.0 m/s, 1.5 m/s, 1.0 m/s and 0.5 m/s. And the same regular pattern can be found for the optimal regeneration time aiming at the maximum DCOP (about 120 s, 150 s, 190 s and 310 s corresponding to the air velocity of 2.0 m/s, 1.5 m/s, 1.0 m/s and 0.5 m/s). In the regeneration process, the moisture content of silica gel decreases with time and it decreases much faster in the system with ultrasound. When it comes to a critical point, the moisture content becomes so small that it limits the regeneration rate of the ultrasound-assisted system. Under the larger air velocity, the moisture content of silica gel decreases faster and the critical time come earlier. Therefore, the optimal regeneration time should be shorter to maximize the AMRC. Fig. 12 shows that the lower initial moisture ratio of silica gel in the beginning of the regeneration process results in the shorter optimal regeneration time for the maximum AMRC and DCOP. In this case study, the regeneration time corresponding to the maximum AMRC and DCOP increases, respectively, from about 200 s to 350 s and from about 120 s to 180 as the initial moisture ratio of silica gel rises from 0.12 kg water/(kg dry sample) to 0.18 kg water/(kg dry sample). The AMRC reflects the contribution of ultrasonic-assisted regeneration to the dehumidification ability of desiccant material. The AMRC is expected to be as large as possible when the
Fig. 10. Variations of MRC, AMRC and DCOP against regeneration time under different ambient air humidity levels.
Fig. 11. Variations of MRC, AMRC and DCOP against regeneration time under different air velocities.
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respectively, the air velocity for the regeneration and adsorption process ranging from 0.5 to 4.5 m/s, the initial moisture ratio of silica gel for the regeneration process ranging from 0.10 to 0.20. Particularly, the optimal regeneration time aiming at the maximum AMRC and DCOP is particularly discussed. The main regular patterns can be summarized according to the simulation results: 1) The higher regeneration temperature is conducive to increasing the AMRC brought by the ultrasonic-assisted regeneration. And there is an appropriate regeneration temperature to get the highest DCOP. For this case study, the regeneration temperature between 65 C and 85 C is recommended. 2) The higher ambient air temperature is conducive to increasing the AMRC and DCOP of the dehumidification system. 3) The higher ambient air humidity level will result in the bigger AMRC and the lower DCOP of the dehumidification system. 4) The DCOP of the dehumidification system will decrease with the air velocity increasing. And there is an appropriate air velocity to get the biggest AMRC (about 2.5 m/s in this case study). 5) The higher initial moisture ratio of silica gel is in its favor for improving the DCOP, but unfavorable for increasing the AMRC. 6) The optimal regeneration time aiming at the maximum AMRC or DCOP decreases as the regeneration temperature or the air velocity increases. And situation is the opposite as the ambient air temperature or humidity or the initial moisture content of silica gel increases. Acknowledgments This work was supported by Shanghai Pujiang Program (2012) and a grant from the National Natural Science Foundation of China (No.11274279). Fig. 12. Variations of MRC, AMRC and DCOP against regeneration time under different initial moisture ratios.
ultrasound is applied to the regeneration process. At the same time, the DCOP must be taken into account from the perspective of energy saving. As indicated from Figs. 8e12, the optimal regeneration time required for the maximum AMRC is not consistent with that for the maximum DCOP. And the former is longer than the latter for all the simulation conditions. To achieve a relatively high AMRC and DCOP simultaneously, the recommended regeneration time should be between the optimal regeneration time for the maximum AMRC and that for the maximum DCOP. Combined the effect of all parameters, the recommended regeneration time is about 250e300 s for the baseline operation conditions as below: 80 C in the regeneration temperature, 25 C and 80%, respectively, in the process air temperature and humidity, and 1.0 m/s in the regeneration air velocity. 5. Conclusions A theoretical model is developed for predicting the performance of silica gel dehumidification system with ultrasonic-assisted regeneration. The model has been validated by a series of experiments, which shows that the model errors are mostly less than 10%. Afterwards, the model is used to investigate the effects of ultrasonic-assisted regeneration on the performance of silica gel dehumidification system under a wide range of conditions including the regeneration temperature ranging from 50 to 90 C, the air temperature and relative humidity for the silica gel adsorption ranging from 20 to 35 C and from 70 to 95%,
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