1、Volume 15, Number 3, May 2009An International Journal of Heating, Ventilating,Air-Conditioning and Refrigerating ResearchAmerican Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc.Volume 15, Number 3, May 2009HVAC support of research, educational, and outreach programs; and train
2、ing and certification programs for the implementation of new technology and the associated service and support infrastructure. A society-wide systems approachnot monolithic solutions or silver bulletsis required and should be supported through stimulus funds. We caution, however, that what is being
3、advocated is not assistance to return to the days and the ways of plenty but a way to engender a new, sustainable steady state that treads softly on natural resources while benefitting personal prosperity through innovative technologies without sacrificing quality of life.VOLUME 15, NUMBER 3 HVAC ac
4、cepted February 12, 2009A new theoretical model is presented for the performance of dehumidifier wheels. The model is aimed at providing design guidance for manufacturers and selection and operation advice for HVAC system designers. To characterize the performance of dehumidifier wheels, water vapor
5、 effectiveness, , and water vapor mass ratio, , are defined. The theoretical model uses the transient response characteristics of the flow channel in the wheel matrix to predict the base case physical characteristics for fully developed laminar flow through the matrix where the heat transfer charact
6、eristics are first decoupled from the water vapor transfer. The simple alge-braic equations, deduced for this base case of a dehumidifier wheel water vapor effectiveness, , and water vapor mass ratio, , show that the mass rate of the supply and regenera-tor flows should be equal and that both and go
7、 toward zero as the wheel speed decreases to low values. Corrections are made to these base case performance factors, which account for the coupling of the heat and water vapor transfer, as well as other smaller factors caused by entrance, heat conduction, carryover, and flow channel variation effec
8、ts. It is con-cluded that more dehumidifier wheel performance data, along with a thorough analysis of uncertainties, will permit researchers to decrease the range of physical factor coefficients used in this model.INTRODUCTIONTraditionally, dehumidification equipment was used in some spaces with spe
9、cial require-ments, such as in some electronic component manufacturing shops and some ICUs in hospitals. Dehumidification can be accomplished using either active desiccants (solid or liquid) or cooling coils (Mumma 2001). As a general HVAC design rule for commercial and institutional build-ings, coo
10、ling coils have been a better choice when the required dew-point temperature is above 40F (4C). On the other hand, active desiccants are a better choice when the dew-point temper-ature is below 40F (4C). Sensitized by litigation regarding indoor air quality problems that are often related to mold an
11、d moisture problems, building owners have been more willing to invest in better HVAC designs with improved dehumidification capabilities. Their interest is also prompted by comfort problems caused by the high internal relative humidity and moisture load caused by higher ventilation rates and buildin
12、g envelope leakage rates (Harriman et al. 2001 and Harriman and Judge 2002).Dehumidifier wheels, or desiccant dryer wheels, must have their desiccant-coated surfaces periodically regenerated to a dry condition once every rotation cycle, using a hot regenerative air. Although the literature for regen
13、erative heat wheels has been developed over 85 years, the literature for regenerative dehumidifier and energy wheels goes back only 35 years. During this time, rigorous test standards have evolved for heat and energy wheels using effectiveness as the most important wheel performance factor (ASHRAE 2
14、008). ANSI/ASHRAE Standard 139-1998, Wei Shang is with the Petroleum Engineering Department, University of Tulsa, Tulsa, OK. Robert W. Besant is profes-sor emeritus in the Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, SK, Canada.wWW*wWW*wWW*2009, American Society of He
15、ating, Refrigerating and Air-Conditioning Engineers, Inc. (www.ashrae.org). Published in HVAC however, typical graphical time-dependent outlet gas temperatures were shown for several cycles after a cold start and at steady state for counter-current flow.Collier et al. (1990), Worek et al. (1991), Be
16、lding et al. (1991), Zheng and Worek (1993), and Zheng et al. (1993) used mostly numerical methods to investigate the performance of dehumidi-fier wheels using various desiccant types, a defined nondimensional time or wheel speed factor, number of transfer units, etc. as independent variables where
17、the COP of the system and cooling capacity were investigated as dependent performance factors. They concluded that type 1A des-iccants were best for dehumidifier wheels. Other findings from these papers are difficult to use by designers because the functional relationships between wheel design varia
18、bles and perfor-mance factors remains hidden in the numerical code. There are no comparisons between mea-sured data and numerical predictions; rather, their predictions are compared to other simulations and show good agreement. Example designs, defining all of the dimensional variables, are not pres
19、ented.Using a small portion of a dehumidifier wheel, Czachorski et al. (1997) used a transient test method similar to the single-blow test method in a stationary dehumidifier wheel of Collier et al. (1992) where the airflow into the two-wheel test sections is reversed at a selected time and all of t
20、he inlet and outlet temperatures, humidities, and flow rates are measured. Using the numerical model of Zheng and Worek (1993) and the results of Zheng et al. (1993), they predicted an opti-mum wheel speed of 16 rph for their particular wheel.Zhang and Niu (2002) developed a two-dimensional, transie
21、nt numerical model to study the effects of rotary speed, NTU, and exchanger surface area on rotary wheel performance. They found that the heat and mass transfer response for rotary desiccant-coated wheels depends on the speed of the wheel, as well as the inlet air conditions. Typical cyclic internal
22、 air temperature and humidity simulations were presented for energy and dehumidifier wheels that are similar to those of Zhang and Scott (1993) for heat transfer. For energy wheels, they presented simulated sensible and latent effectiveness versus NTU, specific area, and wheel speed. Their effective
23、-ness results for the effect of wheel speed are not consistent with the data and simulations of Simonson et al. (2000) and the theoretical model of Shang and Besant (2008, 2009a, 2009b).Gao et al. (2005) used a numerical control volume method for the one-dimensional Navier-Stokes equations to predic
24、t the transient and steady state of the outlet air temperature and humidity of a dehumidifier wheel moisture transport in each half of this wheel. Assuming fully developed turbulent flow in each flow channel of a dehumidifier wheel, they compared their simulations with measured data, but the agreeme
25、nt was not good. This disagreement may be due to their assumption of turbulent flow for flows that were laminar. Also, their sensitivity investi-gation and conclusion on the effect of the shape of the flow channels in the wheel matrix does not appear to be consistent with the simulation models of Si
26、monson and Besant (1998) and other researchers or the theoretical models of Shang and Besant (2008, 2009a, 2009b) where flow channel total surface area per unit face area of the wheel was shown to be the dominant flow channel geometry factor. For dehumidifier wheels, they made similar comparisons us
27、ing a non-standard definition of dehumidification effectiveness and dehumidification power, so direct VOLUME 15, NUMBER 3, MAY 2009 439comparisons are not possible. Nonetheless, their prediction of the effect of wheel speed does not appear to be consistent with the predictions of Shang and Besant (2
28、009a, 2009b).Jia et al. (2006) presented property data and parametric data for two nonstandard performance indices for two similar dehumidifier wheels: one coated with silica gel (approximate particle size range ) and another coated with composite silica gel and LiCl particles (approximate size rang
29、e ). They concluded that there was a 50% improvement in the moisture removal capacity for the wheel coated with their new composite coating compared to the silica gel-coated wheel. It is not clear from this paper just what mass fractions of each par-ticle species were used in their composite coating
30、, nor what was the average mass density and thickness of the two coatings. Shang and Besant (2009a and 2009b) discuss how particle size differences may be very important for water vapor sorption, because the specific surface area in a particle bed will vary inversely with the particle diameter. So,
31、the performance difference in Jias measured test data may have been strongly influenced by this particle size difference and the composition. In addition, since LiCl has a very low deliquenscence humidity, the perfor-mance of any dehumidifier wheel that uses LiCl in its coating can be expected to de
32、teriorate with the number of cycles of exposure at high humidities (Belding et al. 1991).Wang et al. (2005) and Abe et al. (2006a, 2006b) used a different transient test to determine the time response of small sections of stationary energy wheels in order to predict their effec-tiveness using a theo
33、retical model that employed well known parallel and counterflow heat exchanger effectiveness equations where NTU and airflow capacitance ratio are the two inde-pendent parameters.Using basic equations and wheel flow channel properties, Shang and Besant (2008) presented a mathematical model to predic
34、t the sensible effectiveness of a rotary regenerative wheel for equal flow areas and mass flow rates in the supply and exhaust streams. They presented an ana-lytical equation for predicting the fully developed flow sensible effectiveness of an energy wheel that only depends on the wheel speed and ti
35、me constant and includes corrections for entrance, axial conduction, carry-over, sorption phase change, and manufacturing effects. Com-parisons of this model with data show agreement within the uncertainty bounds for energy wheels.Shang and Besant (2009a and 2009b) also presented a mathematical mode
36、l based on funda-mental heat and mass transfer for predicting the latent effectiveness of energy wheels that have equal airflow areas and balanced flows. The equation for the transient humidity step response of an energy wheel is developed from physical principles using a similar model to that used
37、for the sensible energy response. This fully developed flow model is used to derive a simple character-istic moisture transfer time constant in terms of the flow channel and its desiccant-coating prop-erties and the airflow velocity. Scanning electron microscope (SEM) images and photos for one typic
38、al desiccant coating showed particles bonded on to one aluminum matrix. Isotherm data presented for the moisture content of these coatings and similar desiccant particles at several temperatures show significantly lower moisture content isotherms for the coatings than the for the particles. Calculat
39、ed equilibrium isotherm moisture content changes, when compared to transient moisture content change correlations for a step change in humidity, showed agreement within the uncertainty limits for time periods of 1000 s or more. These long-duration tests are akin to the behavior or characteristics of
40、 some dehumidifier or desiccant dryer wheels. For very short time exposures (e.g., 1 s or 2 s), which is typical for energy wheels, the sorption character-istics or time constants appear to change and become more uncertain, so a new, more convenient to use and accurate method was used to deduce the
41、sorption time constants from measured data. This time constant and the wheel speed were then used to determine the predicted effectiveness, which compared well with measured data for two typical energy wheels.30 dp 60 nmsw12wsswsw 0sws swws 1.0= K10.1=K20.05= 0.026= K10.05= K20.025= 0.014=ws 2.0=K1K
42、212VOLUME 15, NUMBER 3, MAY 2009 457SUMMARY AND CONCLUSIONIn this paper, new performance factors are defined for dehumidifier wheels (i.e., the sensible and modified water vapor effectiveness and water vapor change mass ratio) and other heater-wheel system performance factors, such as COP, are discu
43、ssed.A new theoretical model is developed for dehumidifier wheels, which is comprised of a base case, assuming fully developed laminar flow in each flow channel, and a decoupling of the heat transfer and water vapor transfer. This base case results in simple algebraic relationships between sensible
44、energy and water vapor effectiveness and a dimensionless ratio of wheel speed times the time constant for the flow channel divided by the wheel sector angle for regeneration (or supply) airflow. New dimensionless graphs show these base case effectiveness relationships for each per-formance factor fo
45、r both parallel and counterflow. These graphs are very similar to those found in heat transfer textbooks, but they differ in that the independent variables are explicit functions of wheel speed, time constants, and wheel flow sector angle. It is shown from this base case model that the mass flow rat
46、e of air through the supply and regenerator wheel sectors should be equal for maximum dehumidifying performance. Guidance is provided to manufacture wheel matrix designs that will have a sensible energy transfer time constant that is smaller than the water vapor transfer time constant. Methods are s
47、tated to determine or measure these resulting heat and water vapor time constants.The base case models for heat and water vapor effectiveness and water vapor mass ratio are corrected for the effects of flow channel entrance and heat conduction effects, as well as carry-Figure 11. Sensible energy (1a
48、nd s) and water vapor (2and w) effectiveness as a function of with K1and K2as iteration coefficients where H* = 0.70 and and and .1u-uT-TM 0.42= 110 s= 230 s=458 HVAC February 15, 2009In this study, backward-curved airfoil centrifugal blowers were numerically simulated and com-pared with experimenta
49、lly measured data. Simulation settings and boundary conditions arestated, and the measurements follow ANSI/AMCA Standard 210-07/ANSI/ASHRAE Standard51-07, Laboratory Methods of Testing Fans for Certified Aerodynamic Performance Rating(AMCA/ASHRAE 2007). Comparing simulation results with measured data, it was found thatthe deviation of the static pressure curve at each specified flow rate was within 4.8% and thedeviation of the efficiency curve was within 15.1%. After the simulation scheme was provenvalid, the effects of
