SERI/TR-631-1330 

UC Category: 59c 

Analysis of the Adsorption 

Process and of Desiccant 

Cooling Systems - 

A Pseudo- Steady-State Model 

for Coupled Heat and 

Mass Transfer 

Robert S. Bartow 

December 1982 

Prepared Under Task No. 1131.00 and lf 32.11 

WPA Nor 01-256 and 01-315 

Solar Energy Research Institute 

A Division of Midwest Research lnstitute 

1617 Cole Boulevard 

Golden, Colorado 80401 

Prepared for the 

U.S. Department of Energy 

Contract No. EG-77-C-01-4042 
Printed in the United States of America 

Available from: 

National Technical Information Service 

U.S. Department of Commerce 

5285 Port Royal Road 

Springfield, VA 22161 

Price: 

Microfiche $3.00 

Printed Copy $8.00 

NOTICE 

This report was prepared as an account of work sponsored by the United States 

Government. Neither the United States nor the United States Department of Energy, 

nor any of their employees, nor any of their contractors, subcontractors, or their 

employees, makes any warranty, express or implied, or assumes any legal liability 

or responsibility for the accuracy, completeness or usefulness of any information, 

apparatus, product or process disclosed, or represents that its use would not 

infringe privately owned rights. 
This report documents a computer model that simulates the adiabatic adsorptionldesorption process. Developed to predict the performance of desiccant 

cooling systems, the model has been validated through comparison with experimental data for single-blow adsorption and desorption. This report also contains a literature review on adsorption analysis, detailed discussions of the 

adsorption process, and an inital assessment of the potential for performance 

improvement through advanced component development 

This research was performed under task 1131.00 of the Solar Desiccant Cooling 

Program at the Solar Energy Research Institute during fiscal year 1981. The 

author would like to acknowledge the contributions of Charles F. Kutscher, in 

charge of SERZts desiccant laboratory during this work; Harry Pohl, the 

laboratory technician; and Terry Penney, who provided a detailed and helpful 

review of the report. 

Details of the experimental work completed at SERI to validate the computer 

model are contained in a separate report, SERI/TR-253-1429. 

Approved for 

SOLAR ENERGY RESEARCH INSTITUTE 

Frank Kteith, Chief 1 -5 

Thermal Research Branch 

er, Manager 

Solar @herma1 and Xaterials Research Divf sion 

iii 
The primary objective of the research leading to this report was to develop 

and validate a computer program for predicting the performance of solar desiccant cooling systems. Major considerations in the development of the sirnulation model were to make the method of analysis as simple and versatile as possible, whfle maintaining the level of detail necessary for accurate predictions. The primary objective of this report is to provide complete documentation of this method of analysis and the computer programs. The report serves 

two additional functions. The first is to provide a detailed description of 

the adsorption process and the physical behavior of desiccant beds to facilitate a more complete understanding of the operation of the dehumidifier in a 

deci ssant cooling cycle. The second is to provide information for an initial 

assessment of the potential for performance improvements through the development of advanced, high-performance components. 

The computer model documented here is called a pseudo-steady-state model, and 

it uses a new approach to analyzing transient coupled heat and mass transfer 

as it occurs in adiabatic adsorption. Rather than deriving and solvfng a set 

of differential equations, the method uses simple effectiveness equations from 

the theory of steady-state heat exchangers and mass exchangers within a 

straight£ omard finite difference procedure. This simplifies the mathematics 

of the adsorption problem, makes the model easy to adapt to investigate a 

variety of adsorption issues, and makes it easier to keep track of the physics 

of the adsorption process. The body of the report includes a literature 

review of adsorption analysts and a review of available data and correlations 

of the properties of regular density silica gel, which appears to be the most 

suitable available desiccant for solar cooling systems 

The computer model was validated through comparison with experimental data for 

single-blow adsorption and desorption in packed beds of silica gel. Three 

data sources were used; the primary one was the SERI Desiccant Test Laboratory. Measured and predicted results for adsorption show agreement well 

within experimental uncertainty. This demonstrates that the lumped gas-side 

transfer coefficient, rather than separate gas-stde and solid-side resistances 

to mass transfer , is sufficiently accurate for adsorption cases. Experimental 

results show that a different effective transfer coefficient must be used 

during single-blow desorption cases. However, relatively good agreement 

between measured and predicted results can still be obtained. 

G major section of the report deals with the physical behavior of desiccant 

beds during single-blow adsorption or desorption and during cyclic operation, 

as in a cooling system. Of particular Importance is the fact that adsorption 

comprises the progression of two heat and mass transfer waves through a desiccant bed. Also important are the differences between the behavior of thick 

beds, typically used for industrial adsorption applications, and thin beds, as 

used fn desiccant cooling systems. Fredicted performance of thin beds is mch 
more sensitive to errors in transfer coefficients and desiccant property correlations, because only a portion of the second wave front is contained within 

the bed. The detailed discussion of the adsorption process is intended to 

facilitate a more complete understanding of the operation of the dehumidifier 

in a desiccant cooling cycle 

The pseudo-steady-state model was incorporated into a computer program for the 

simulation of a complete desiccant cooling system. Parametric studies were 

performed on two systems, one representative of existing prototypes and the 

other containing high effectiveness components. These parametric studies 

characterize the effect on performance of operating conditions, such as indoor 

conditions, outdoor conditions, dehumidifier wheel rotation speed, and 

regeneration temperature. They also provide information on the influence of 

individual component effectiveness on overall system thermal performance. 

This permits an initial assessment of the potential gains in performance that 

could be achieved through the development of advanced, high-effectiveness components. 

Major conclusions include the following: 

A simple computer model for the adiabatic adsorption/desorption process 

has been developed and validated. 

Close agreement between measured and predicted results for single-blow 

adsorption demonstrates that a lumped gas-side mass transfer coefficient 

can be used. 

Effective mass transfer coefficients must he reduced for cases of singleblow desorption, presumably because of a dynamtc hysteresis effect in 

silica gel properties. 

The thermal performance of a desiccant cooling system varies with indoor 

and outdoor temperature and humidity, and generally decreases as the difference between indoor and outdoor conditions increases. 

COPs above 1.0 are technically feasible if high-effectiveness dehumidifiers and heat exchangers are used. 

With high-performance components, the ventilation mode is clearly 

superior to the recirculation mode. Thermal COPs in the ventilation mode 

become relatively insensitive to outdoor conditions when higheffectiveness components are used. 
TABLE OF COHTEKTS 

Page 

1.0 Introduction ........................................................ 1 

1.1 Background ..................................................... 1 

1.2 Purpose and Scope .............................................. 2 

1.3 Adsorption Process and Desiccant Cooling Cycle ................. 3 

2.0 Historical Overview .............................m................... 5 

3.0 Pseudo-Steady-State Model ........................................... 9 

3.1 General Description ...........................................m 9 

3.2 Mass Transfer Calculation ...................................... 10 

3.3 Intermediate Energy Balance ...........m...................m.... 12 

3.4 Heat Transfer Calculation ............m....m.................... 13 

3.5 Transfer Coefficients ....................mm.................m.. 14 

3.6 Properties of Moist Air ........................................ 16 

3.7 Properties of Silica Gel ....................................... 18 

3.7.1 Equilibrium Properties .................................. 19 

3.7.2 Heat of Adsorption ................e....e.mm...m......... 27 

4.0 Comparison of the Model with Experimental Data ...................... 31 

4.1 Data Sources for Single-Blow Adsorption and Desorption ......... 31 

4.2 Comparison with SERI Data ...................................... 31 

4.3 Comparison with Pesaran Data ......em........................... 33 

4.4 Comparison with Koh Data ....................................... 52 

4.5 Results. ....................................................... 53 

5.0 Desiccant Cooling System Simulation ................................. 63 

5.1 System Configuration ............................................ 63 

5.2 Method of Analysis ........................+...............m... . 63 

5.3 Component Analysis and Equations ............................... 66 

6.0 The Physical Behavior of Desiccant Beds ............................. 69 

6.1 Behavior of Thick Beds During Adiabatic Adsorption .... ......... 69 

6.2 Behavior of Thick Beds During Adiabatic Desorption ............. 71 

6.3 Behavior of Thin bed^..............^^.......^.........^........ 75 

6.4 Behavior During Cyclic Operation .............................Om 80 

7.0 Parametric Studies of Desiccant Cooling Systems ..................... 85 

7.1 Effect of Simulation Parameters in the Dehumidifier Model ...... 85 

7.2 System specifications .......me.............................m... 87 

7.3 Effect of Outdoor condition^.....^...................^^........ 88 

7.4 Effect of Indoor Conditions .................................... 89 

vii 
sia + TR-1330 

TABLE OF CONTENTS (Concluded) 

Page 

7.5 Effect of Regeneration Temperature ............................. 94 

7.6 Effect of Heat Exchanger Effectiveness ......................... 94 

7.7 Effect of Evaporative Cooler 1 ................................. 95 

7.8 Summary of Parametric Studies .................................. 95 

8.0 Conclusions and Recommendations ..................................... 99 

8.1 Conclusions Regarding the Pseudo-Steady-State Model ............ 99 

8.2 Conclusions Regarding Cooling System Performance ............... 100 

8.3 Recommendations ................................................ 100 

9.0 References .......................................................... 103 

Appendix A: Users Guide to Computer Programs ............................. 107 

A-1 Overview of Computer Programs ........................... 107 

A-2 Job Control Files and Input Data ........................ 108 

A-3 A Partial Listing of FORTRAN Variables .................. 109 

Appendix B: Program Listings ............................................. 115 
LIST OF FIGURTXS 

Page 

1-1 IGT Solar-MEC@ System in Recirculation Mode ......................... 4 

2-1 Linear Approximation to Properties of Silica Gel and 

Molecular Sieve ................................................... 6 

3-1 Conveyor Belt Concept Used in Computer Elodel ........................ 9 

3-2 Concentration Profiles for Steady-State Mass Transfer Process ....... 11 

3-3 (a) Detailed Resistance Model for Mass Transfer ..................... 14 

(b) Gas-Side Resistance Model for Mass Transfer ..................... 14 

3-4 Comparison of Various Mass Transfer Correlations for Packed Beds .... 17 

3-5 Typical Iso them for Regular- and Low-Density Silica Gel ........... 20 

3-6 Isotherms Based on the Bullock and Threlkeld Correlation ........ .... 23 

3-7 Comparison of the Close and Banks Complete Correlation with 

Simplified Correlation Using fl(X) = 2.009 ........................ 24 

3-8 Comparison of the Close and Banks Simplified Expression with 

Further Simplified Expression Using Linear f2(X) .................. 25 

3-9 Comparison of the Rojas Correlation with Eqo 3-30 ................... 26 

3-10 Comparison of Various Correlations and Data for the Heat of 

Adsorption for Silica Gel ......................................... 29 

4-1 Measured and Predicted Outlet Air Conditions During 

SERI Run 85A (ICORR = 1) .......................................... 34 

4-2 Measured and Predicted Outlet Air Conditions During 

SERI Run 85A (ICORR = 2) .......................................... 35 

4-3 Measured and Predicted Outlet Air Conditions During 

SERI Run 85A (ICORR = 3). ......................................... 36 

4-4 Measured and Predicted Outlet Air Conditions During 

SEN Run 8% (ICORR = 1. Le = 3) .................................. 37 

4-5 Measured and Predicted Outlet Air Conditions During 

SERI RUN 85R (ICORR = 1. Le = 6) .................................e 38 

4-6 Measured and Predicted Outlet Air Conditions During 

SERI Run 85R (ICORR = 1. Le = 9)0*e00*m*0+*0*0*e00m0*000*0*0****0C 39 
TR-1330 

LIST OF FIGWES (Continued) 

Page 

4-7 Measured and Predicted Outlet Air Conditions During 

SERI Run 85R (ICORR = 2, Le * g).................................. 40 

4-8 Measured and Predicted Outlet Air Conditions During 

SERI Run 85R (ICORR = 3, Le = g).................................. 41 

4-9 Measured and Predicted Outlet Air Conditions During 

Pesaran Run 8............................................... 42 

4-10 Measured and Predicted Outlet Air Conditions During 

Pesaran Run 10.................................................. 43 

4-11 Measured and Predicted Outlet Air Conditions During 

Pesaran Run 11................................................... 44 

4-12 Measured and Predicted Outlet Air Conditions During 

Pesaran Run 12...................................... 45 

4-13 Measured and Predicted Outlet Air Conditions During 

Pesaran Run 18 (ICORR = I)....................................... . 46 

4-14 Measured and Predicted Outlet Air Conditions During 

Pesaran Run 18 (ICORR = 2)....................................... 47 

4-15 Measured and Predicted Outlet Air Conditions During 

Pesaran Run 18 (ICORR = 3)...................................... 48 

4-16 Measured and Predicted Outlet Air Conditions During 

Pesaran Run 22.....................................~ 49 

4-17 Measured and Predicted Outlet Air Conditions During 

Pesaran Run 24.................................................. 50 

4-18 Measured and Predicted Outlet Air Conditions During Koh Run 2....... 54 

4-19 Measured and Predicted Outlet Mr Conditions During Koh Run 4....... 55 

4-20 Measured and Predicted Outlet Air Conditions During 

Koh Run 6 (ICORR = 2)....................................... 56 

4-21 Measured and Predicted Outlet Air Conditions During 

Koh Run 6 (ICORR = 3) ............................................ 57 

4-22 Measured and Predicted Outlet Air Conditions During 

Koh Run 8 (ICORR = 1)........................................... 58 

4-23 Measured and Predicted Outlet Air Conditions During Koh Run 9.. . . . . . 59 
SE?I . 

LIST Of PIGIJBaS (Continued) 

Page 

4-24 Measured and Predicted Outlet Air Conditions During Koh Run 10 ...... 60 

4-25 Measured and Predicted Outlet Air Conditions During Koh Run 15 ...... 61 

5-1 System Schematic and Psychrometric Cycle Diagram for the 

Ventilation Mode .................................................. 64 

5-2 System Schematic and Psychrometric Cycle Diagram for the 

Recirculation ~clode ..............................m.......... 65 

5-3 Small Element Used in Simulations of Rotary Dehumidifiers ........... 67 

6-1 The First Adsorption Wave in a Thick Desiccant Bed .................. 70 

(a) Desiccant Temperature Profiles .................m......m.......m 70 

(b) Desiccant Loading Profiles ...................................... 70 

(c) Outlet Air Temperature ................I........................ 70 

(d) Outlet Air Humidity..... ......m...mm..mm..ma.mm....... .... 70 

(e) Psychrometic Path of Outlet States ............................. 70 

6-2 Two Adsorption Waves in a Thick Desiccant Bed 72 

(a) Desiccant Temperature profile^....................^........^^.. 72 

(b) Desiccant Loading profile^..............^...................... 72 

(c) Outlet Air temperature...................^^...^^^..... 72 

(d) Outlet Air hmidity .............m......mm..m.....~........... 72 

(e) Psychrometric Path of Outlet States .............mm~~e.~.m.m.... 72 

6-3 The First &sorption Wave in a Thick Desiccant Bed .................. 73 

(a) Desiccant Temperature profile^..................^.............. 73 

(b) Desiccant Loading profile^............^.^...^^..^....^...^..... 73 

(c) Outlet Air Temperature ......................................... 73 

(d) Outlet Air hmidity ............................................ 73 

(e) Psychrometric Path of Outlet state^..................^...^..... 73 

6-4 Two Desorption Waves in a Thick Desiccant Bed .........ma............ 74 

(a) Desiccant Temperature profile^...........^.^.......^^^.^....^.. 74 

(b) Desiccant Loading Profiles ..................................... 74 

(c) Outlet Air Temperature ......................................... 74 

(d) Outlet Air kmidity ............................................ 74 

(e) Psychrometric Path of Outlet States .................mmm.......m 74 

6-5 The First Adsorption Wave in a Thin Desiccant Bed ................ ... 76 

(a) Desiccant Temperature Profiles ................................. 76 

(b) Desiccant Loading profile^.............^........^.^............ 76 

(c) Outlet Air Temperature ....,.........~.~.m....~m.....m.......... 76 

(d) Outlet Air Humidity ......................m..................... 76 

(e) Psychrometric Path of Outlet state^..............^.^^^......... 76 
LIST OF FIGURES (Continued) 

Page 

6-6 Two Adsorption Waves in a Thin Desiccant 3ed ........................ 77 

(a) Desiccant Temperature Profiles ................................. 77 

(b) Desiccant Loading Profiles .................................. 77 

(c) Outlet Air Temperature ....................................... 77 

(d) Outlet Air Humidity ............................................ 77 

(e) Psychrometric Path of Outlet States ............................ 77 

6-7 The First Desorption Wave in a Thin Desiccant Bed ................... 78 

(a) Desiccant Temperature Profiles ................................. 78 

(b) Desiccant Loading Profiles .................................... 78 

(c) Outlet Air Temperature ......................................... 78 

(d) Outlet Air Humidity ............................................ 78 

(e) Psychrometric Path of Outlet States ............................ 78 

6-8 Two Desorption Waves in a Thin Desiccant Bed ........................ 79 

(a) Desiccant Temperature Profiles ................................. 79 

(b) Desiccant Loading Profiles .................................... 79 

(c) Outlet Air Temperature ......................................... 79 

(d) Outlet Air Humidity ............................................ 79 

(e) Psychrometric Path of Outlet States ............................ 79 

6-9 Behavior of a Thin Desiccant Bed During Cyclic Operation ............ 81 

(a) Temperature Profiles During Adsorption ......................... 81 

(b) Loading Profiles During Adsorption ............................. 81 

(c) Outlet Air Temperature hrring Adsorption ....................... 81 

(d) Outlet Air Humidity During Adsorption .......................... 81 

(e) Temperature Profiles During Desorption ......................... 82 

(f) Loading Profiles During Desorption ............................. 82 

(g) Outlet Air Temperature During Desorption ....................... 82 

(h) Outlet Air Humidity During Desorption .......................... 82 

(i) Psychrometric Paths of Outlet States ........................... 82 

7-1 Predicted COP vs . Simulation Time Step .............................. 85 

7-2 (a) COP vs . Regeneration Lewis Number .............................. 86 

(b) Capacity vs . Regeneration Lewis Number ......................... 86 

7-3 (a) COP vs . Half-Cycle Time ........................................ 87 

(b) Capacity vs . Half-Cycle Time ................................... 87 

7-4 Effect of Outdoor Conditions on Performance of the Base System: 

(a) COP vs . T. ambient in Ventilation Mode ......................... 90 

(b) COP vs . T. ambient in Recirculation Mode ....................... 90 

(c) Capacity vs . T. ambient in Ventilation Node .................... 90 

(d) Capacity vs . T. ambient in Recirculation Mde .................. 90 

xii 
LIST OF FIGURES (Continued) 

Page 

7-5 Effect of Outdoor Conditions on Performance of the High 

Performance System. .............................................. 91 

(a) COP vs . T. ambient in Ventilation Mode ......................... 91 

(b) COP vs . T. ambient in Recirculation Mode ....................... 91 

(c) Capacity vs . T. ambient in Ventilation Mode .................... 91 

(d) Capacity vs . T. ambient in &circulation Mode ........ .. . .. .. ... 91 

7-6 Effect of Indoor Conditions on Performance of the Base System. ...... 92 

(a) COP vs . T. room in Ventilation Mode ............................ 92 

(b) COP vs . T. room in Recirculation Mode .......................... 92 

(c) Capacity vs . T. room in Ventilation Mode ....................... 92 

(d) Capacity vs . T. room in Recirculation Mode ..................... 92 

7-7 Effect of Indoor Conditions on Performance of the High 

Performance System. ............................................... 93 

(a) COP vs . T. room in Ventilation Mde ............................ 93 

(b) COP vs . T. room in Recirculation Mode .......................... 93 

(c) Capacity vs . T. room in Ventilation Mode ....................... 93 

(d) Capacity vs . T. room in Recirculation Mode ..................... 93 

7-8 (a) Effect of Regeneration Temperature on COP ...................... 94 

(b) Effect of Regeneration Temperature on Capacity ................. 94 

7-9 (a) Effect of Heat Exchanger Effectiveness on COP ................,. 95 

(b) Effect of Heat Exchanger Effectiveness on Capacity ............. 95 

7-10 Effect of the Effectiveness of Evaporative Cooler 1 on 

Performance of the Base System .................................... 96 

(a) COP ...................................a........................ 96 

(b) Capacity ....................................................... 96 

LIST OF TABLES 

Page 

3-1 Typical Properties of Silica Gel .................................... 19 

3-2 Particle Diameter and Surface Area .................................. 19 

3-3 Constants for the Bullock and Threlkeld Correlation for 

Silica Gel ..............................a......................... 21 

4-1 Physical Properties and Dimensions for SERI Experiments ............. 32 

xiii 
LIST OF TABLES (Concluded) 

Page 

4-2 Summary of Data Runs and Computer Predictions for 

SERI Experiments on a 3.5-cm Bed..............................*... 33 

4-3 Physical Properties and Dimensions for Pesaran Experiments.......... 51 

4-4 Summary of Data Runs and Predictions for Pesaran Experiments.. . . . . . . 51 

4-5 Physical Properties for Koh Experinents............................ 52 

4-6 Summary of Data Runs and Predictions for Koh Experiments............ 52 

7-1 System Specifications for parametric Studies.. . . . . . . . . . . . . . . . . . . . . . . 88 

7-2 Nominal Operating Environment for Parametric Studies................ 88 
Su face area for heat or mass transfer within a packed bed section 5 (m 

Specific heat of desiccant bed (J/~~'c) 

Specific heat of air (J/~~OC) 

Specific heat of liquid water (J/~~OC) 

Capacity rate of air on the adsorption side of the system heat 

exchanger (w/OC) 

Capacity rate of air (w/'c or kg/s) 

Capacity rate of desiccant (WIOC or kg/s) 

Cmin'C, 

Larger capacity rate (w/'c) 

Smaller capacity rate (w/*c) 

Capacity rate of air on the regeneration side of the system heat 

exchanger (WIOC) 

Particle diameter (m) 

Effectiveness of exchange process 

Effectiveness of evaporative cooler 1 

Effectiveness of evaporative cooler 2 

Effectiveness of system heat exchanger 

2 Mass transfer coefficient (kg/m s) 

2 Mass velocity (kg/m s) 

Enthalpy of moist air (J/kg) 

Enthalpy of moist air after mass transfer calculation (J/kg) 

Heat of adsorption of water (J/kg) 

Enthalpy of moist desiccant (J/kg) 

Heat of vaporization of water (J/kg) 

Integral heat of wetting 
H Heat transf er coefficient (w/'cm2) 

k 2 Thermal conductivity of air (w/'c~ ) 

L Depth of desiccant bed (m) 

Le Lewis number 

m Mass fraction of water vapor in air 

- 

m Average mass fraction of water vapor in air 

ms 

Mass fraction of water vapor in air at equilibrium with the desiccant 

surf ace 

., 2 

mH20 Mass flux of water (kglm s) 

Ma Dry mass of air chunk (kg) 

Mb Dry mass of bed section (kg) 

% Mass of water absorbed (kg) 

Ntu Number of transfer units 

Nu Nusselt number 

'atm Atmospheric pressure (Pa) 

'sat Saturation pressure (Pa) 

'v Vapor pressure (Pa) 

've Equilibrium vapor pressure at desiccant surface (Pa) 

Q Energy transferred (J) 

Q Rate of energy transfer (W) 

Re Reynolds number 

Rg 

Gas-side mass transfer resistance (s/kg) 

R * 

g Modified gas-side mass transfer resistance 

RH Relative humidity 

2 

Rs Solid-side mass transfer resistance (m s/kg) 

Sc Schmidt number 

At Time step (s) 
TR-1330 SEPI 

Temperature (OC) 

Temperature of bed section (OC) 

Intermediate temperature of bed section (OC) 

Inlet air temperature (OC) 

Initial temperature of desiccant bed (OC) 

Wet bulb temperature (OC) 

Superficial air velocity (m/s) 

Humidity ratio (kg/kg dry air) 

Equilibrium humidity ratio at desiccant surface (kglkg dry atr) 

Inlet humidity ratio (kg/kg dry air) 

Saturation humidity ratio at wet bulb temperature (kg/kg dry air) 

Moisture ratio of water in desiccant (kg/kg dry desiccant) 

Inf ti a1 moisture content of deslccant (kg/kg dry desiccant) 

Moisture conteht at desiccant surface (kg/kg dry desiccant) 

- 

X Average moisture content of desiccant (kg/kg dry desiccant) 

Y Mass fraction of water in desiccant (XI1 + X) 

Void fraction 

P Dynamic viscosity of air (kg/m s) 

P 3 Density of air (kg/m ) 

3 

Pb Density of desiccant bed (kg/m ) 

msmms 

e Exit 

i Inlet 

1 State at beginning of time step 

2 State at end of time step 

xvii 
SECTION 1.0 

IrnODUCTLON 

Desiccants have been used for many years to provide dry air for a variety of 

industrial and commercial processes. Several manufacturers have marketed 

desiccant air conditioning systems for special situations requiring very low 

relative humidities ((10%) which cannot be provided by vapor compression 

equipment. Because there has been little competition in this market, the 

energy efficiency of drying equipment has not been a primary concern. The 

thermal efficiency of industrial and commercial drying equipment tends to be 

low, and parasitic power requirements tend to be high. A significant difference between solar cooling systems and commercial drying systems is that 

solar cooling must compete with conventional vapor compression cooling. Thus, 

the thermal coefficient of performance must be high and parasitic power 

requirements must be low. 

Although I36f [I] proposed an open-cycle , liquid-desiccant , solar-cooling system in 1955 and Dunkle [2] proposed an open-cycle, solid-desiccant, solarcooling system in 1965, active research in desiccant cooling did not begin 

until the mid-1970s. Lunde [3] developed preliminary designs for a cooling 

system using silica gel. Nelson [4] investigated the feasibility of solar 

desiccant cooling using a simple desiccant model in seasonal simulations. 

Because of an emphasis on the rapid commercialization of solar technologies, 

the national desiccant cooling research program moved quickly from these 

initial studies toward the development of prototype cooling systems in the 

capacity range of 5 to 10 kW (17000 to 34000 Btu/h) for residential and small 

commercial applications. Solid desiccant systems are a promising alternative 

for these smaller-scale applications because they are mechanically simple, can 

be driven by flat-plate collectors, and use air as the transport fluid and 

water as the refrigerant. 

Three prototype systems were designed and built under U.S. Department of 

Energy (DOE) contracts beginning in 1977. The Institute of Gas Technology 

(IGT) uses a molecular sieve impregnated wheel in its Solar-MEC@ system [5]. 

AfResearch uses a thin rotating drum packed with silica gel particles in its 

SODAC system 161. The Illinois Institute of Technology (IIT) uses Teflon@ 

bonded silica gel sheets in fixed, cross-cooled adsorbers [7]. All. three systems have performed with COPs between 0.5 and 0.6 under ARI standard operating 

conditions. 

A recent report evaluating residential and commercial solar/gas heating and 

cooling technologies, writ ten by Booz-Allen and Hamil ton for the Gas Reserch 

Institute [B], has indicated that advanced desiccant cooling systems with COPs 

near 1.2 would be competitive with vapor compression systems in the 1990s and 

would be the solar cooling system of choice for residential applications in 

regions having moderate heating and cooling loads. The current emphasis of 

the desiccant cooling program is to expand on experience gained with firstgeneration prototypes and to perform basic research and development on new 

concepts and advanced components that will lead to advanced desiccant systems 

with this prescribed performance. I 
1.2 PURPOSE AHD SCOPE 

This report documents a computer model for adsorption/desorption that was 

developed as a research tool to investigate a variety of technical areas concerning the behavior of desiccant beds and the performance of cooling systems. This model fills a need for a general-purpose desiccant simulation program to evaluate alternatives for advanced components. Specific issues that 

the model has been or will be used to investigate involve the effects of 

desiccant bed geometry, of modifying desiccant properties,* and of component 

performance on the system coefficient of performance (COP). The model uses a 

new approach to simulation of transient coupled heat and mass transfer in that 

simple equations for steady-state heat and mass exchangers are used. Hence, 

it is referred to as a pseudo-steady-state model. This approach simplifies 

the mathematics of the analysis and is intended to make the model easy to 

adapt to a variety of adsorption problems. It also should make the model more 

acceptable and thus more useful to engineers and research scientists who are 

not specialists in numerical analysis. 

The report is divided into eight sections. In the last portion of this introduction is a brief description of the physics of the adsorption problem, 

intended primarily for those with little or no experience with desiccants. 

Section 2.0 provides a detailed historical overview of adsorption analysis 

that summarizes the different mathematical approaches that various investigators have taken. Section 3.0 describes the new pseudo-steady-state adsorption 

model, presents the equati-ons used, and gives correlations for the properties 

of moist air and silica gel. Section 4.0 compares predictions using this 

model with experimentally measured outlet air conditions for single-blow 

adsorption and desorption experiments with packed beds of silica gel. Three 

independent data sources are used to provide a thorough assessment of the 

validity of the model. Section 5.0 outlines the simulation of complete desiccant cooling systems, giving equations for analysis of components other than 

the dehumidifier and describing the program logic. Section 6.0 describes the 

physical behavior of desiccant beds, both in single-blow operation and cyclic 

system operation. This description is qualitative but detailed. It is 

intended to facilitate a better understanding of the way the desiccant cooling 

cycle works and the factors that affect the performance of the desiccant bed, 

an understanding essential to making sound research decisions. Section 7.0 

presents results of parametric studies on the performance of two cooling systems, one representative of existing prototypes and the other containing 

advanced, high-effectiveness components. Section 8.0 presents conclusions and 

recommendations. A practical user's guide to the programs for single-blow 

simulations, system simulations, and parametric studies is included as 

Appendix A. Program listings are also included, as Appendix B. 

As reported here, the computer model only includes property data of regular 

density silica gel in a packed-bed geometry. The capabilities of the model 

will be expanded to include properties of other desiccant materials, such as 

molecular sieve, and to simulate heat and mass transfer in parallel-passage, 

laminar flow desiccant beds in the near future. 

*See SERI/TP-631-1157 [Ref. 491. 
1.3 ADSORPTIOH PBOCESS AND DESICCANT COOLING CYCLE 

Few people in the solar community are familiar with desiccants or the adsorption process. Therefore, a brief description of both is included here as an 

introduction. 

Desiccants are a class of adsorbents/absorbents that have a high affinity for 

water. They can be either liquids or solids. Examples of liquid desiccants 

are salt solutions, such as lithium chloride or calcium chloride, and some 

organic liquids, such as trfethylene glycol. Examples of solid desi ccants are 

silica gel, molecular sieves, and natural zeolites. This report is concerned 

only with solid desiccants and, specifically, regular density silica gel. 

However, the methods used here can be applied to a wide variety of coupled 

heat and mass transfer problems. Generally, solid desiccants are highly 

porous materials that adsorb water by mechanisms of chemical adsorption of 

water molecules onto sites on the walls of the pores, physical adsorption of 

successive layers of water molecules, and capillary condensation wlthin the 

pores. The amount of water that a desiccant will hold at equilibrium is a 

function of its temperature and the water vapor pressure or humidity of the 

air that surrounds it. At high temperatures and low humidities, a desiccant 

will contain almost no sorbed water. At room temperature in saturated air, 

silica gel wflL pick up 35% to 40Z of its weight in moisture. 

The desiccant cooling cycle takes advantage of this moisture cycling capacity 

to dehumidify air. Figure 1-1 is a diagram of the Solar-MEC@ desiccant cooling system. It consists of a dehumidifier, sensible heat exchanger, two 

evaporative coolers, a solar heating coil, and an auxiliary gas burner. 

In essence, the desiccant cycle permits evaporative cooling to be used in 

humid climates by turning hot, humid air into hot, dry air before it is sent 

through an evaporator pad. The heart of a desiccant system and the component 

that is most difficult to simulate mathematically is the dehumidifier or 

desiccant wheel. This wheel rotates between two counter-flowing air streams, 

adsorbing moisture from the conditioning stream and desorbing that moisture to 

the solar-heated air of the regeneration stream. 

Consider a dehumidifier wheel constructed of a thin, packed bed of desiccant 

particles held between two metal screens (the construction used by 

AiResearch). On the adsorption side of the system, warm, moist air is exposed 

to relatively dry desiccant. Water molecules in the air at the surface of the 

particles are adsorbed. This creates a humidity gradient in the air stream 

and causes other water molecules to migrate toward the surface where they, in 

turn, are adsorbed as the air flows through the bed. This is a convective 

mass transfer process. A second mass transport process takes place 

simultaneously within the desiccant particles. During dehumidification, the 

water concentration in the desiccant near the surface of the desiccant 

particle is higher than it is at the center. This concentration gradient 

causes water to diffuse inward. 

Thus, there are two mass transfer resistances, a gas-side resistance and a 

solid-side resistance, that determine the rate of transfer of water between 

the air and the desiccant. Both resistances are important in packed beds and 

must be accounted for In simulations3 
Air m 

From 8 O 

Ry, 

Drying 

Wheel 

Solar 

Coil 

Air - .- 

Fig- 1-1. IGT Solar-HEW System in the Recirculation Mode [Ref. 51 

In addition to the mass transfer problem, the adiabatic dehumidification process involves a heat transfer problem. When water is adsorbed by the desiccant, energy is released. For silica gel, the amount of energy, called the 

heat of adsorption, is typically 10% to 15% greater than the heat of condensation of water. This energy release elevates the temperature of the desiccant 

and causes heat to be transferred to the air stream. Fortunately, the thermal 

conductivity of most desiccants is high enough so that temperature gradients 

within the particles can be neglected, and only a single resistance to heat 

transfer, the convective resistance, need be considered. In summary, adsorption comprises simultaneous heat and mass transfer processes that are coupled 

by the equilibrium properties of the desiccant and during which thermal energy 

is generated as a consequence of the mass transfer. 

---- -- 

When-the desiccant -- wheel passes to the regeneration side, all Processes listed 

I above are reversed. i - ____I_ -2 

Energy is transferred from the solar-heated air 

stream to the desiccant. As the temperature of the desiccant increases, water 

at the surface is desorbed and picked up by the air. Water from the interior 

of the particle diffuses toward the surface where it is desorbed. 
Desiccants have been used for many years to dehumidify air for industrial processes. The analysis of air drying also has a long history, dating back to 

the late 1940s. Beyond the drying application, adsorption has many applications in the chemical industry. The governing transport equations are the 

same whether we use silica gel to remove water vapor from air or activated 

carbon to remove methane from helium. As a result, researchers have contributed to the state of the art of analysis in a variety of fields. Despite 

this long history, few modeling attempts have been completely successful, for 

two reasons. First, the mathematical formulation of the adsorption process as 

described above includes five dif ferential equations for the conservation of 

mass and energy. These equations are coupled nonlinearly by additional equations describing the properties of the desiccant. This set of equations must 

be solved numerically, and even with today's computers, their solution is computationally expensive. Second, differential equations include transport 

coefficients that must be determined experimentally. The experiments are dif - 

ficult to perform, and few data are available for some of these transport 

coefficients. This is especially true with regard to diffusion coefficients 

for water within solid desiccants. The accuracy of any model is limited by 

the accuracy of the data supplied to it. 

To make the problem manageable, the first investtgators of the adsorption process made sets of fairly restrictive assumptions about the adsorption process 

and desiccant properties. The history of modeling has been a process of 

relaxing these assumptions step by step. The first modeling work in air 

drying was conducted by Hougen and Marshall [9]. They developed an analytical 

solution for isothermal adsorption where the relationship between the vapor 

pressure in the air and the equilibrium water content of the desiccant is 

linear. Figure 2-1 compares linear isotherm with typical isotherms for molecular sfeve and silica gel. The linear approximation is relatively good for 

silica gel below relative humidities of about 50%. However, it is a poor 

approximaion for molecular sieves. Hougen and Marshall also proposed graphical methods to deal with nonlinear desiccant properties, and with adiabatic 

adsorption where the heat generated during adsorption is significant and must 

be included. An underlying assumption in this work was that a single, airside mass transfer coefficient could be used, and that the effect of diffusion 

in the solid could be included in this lumped coefficient. Hougen and 

Marshall used data from Ahlberg [lo] to produce empirical correlations for 

heat and mass transfer coefficients in packed beds of silica gel. Subsequently, several other authors have used these correlations. However, 

because the data set on which they are based is relatively limited and 

includes considerable scatter, these coefficients should probably be used only 

as a starting point. Additional problems with the correlations are discussed 

in Sec. 3.5. 

Rosen [11,12] expanded the isothermal model to include the separate effects of 

mass transfer across a fluid boundary layer and diffuston of the adsorbate 

into spherical adsorbent particles. This analytical approach leads to a 

series solution that can be evaluated numerically. However, it is still 
Relative Humidity. % 

Fig. 2-1. Linear Approximation to Properties of Silica Gel and Molecular 

Sieve 

limited to linear isotherms and applies only to cases in which the desiccant 

bed is initially uniformly dry. An alternative approach used by Eagleton and 

Bliss [13] allows for the concentration gradient in the absorbent by means of 

a hypothetical solid film coefficient. That is, the mass transfer rate in the 

solid is assumed to be proportional to the difference between the surface concentration and the average concentration of the adsorbate in the particle. 

They maintained the assumption of a linear isotherm, but allowed for a nonzero intercept. Antonson [14] obtained relatively good agreement with experimental results for the isothermal case by considering diffusion in the solid 

as the only resistance to mass transfer in a helium/ethane/molecular sieve 

system. 

After comparing the relative success of the previous approaches and concluding 

that a two-resistance model is preferable [15-171, Carter extended Rosen's 

work to include the adiabatic case [18,19]. Carter assumed a simple exponential relationship between vapor pressure and the equilibrium loading of the 

adsorbent. He used finite difference techniques to solve the resulting set of 

equations and obtained good agreement between experimental and calculated 

results for adsorption of water vapor by activated alumina. Meyer and 

Weber [20] increased the complexity and generality of adsorption modeling in a 

study of the adsorption of methane from helium by activated carbon. They 

included internal and external resistances to heat transEer as well as mass 

transfer and used a general equation for equilibrium properties containing 

eight curve-fitting parameters. Although this is a very detailed model, it 
attained only limited success. presumably because of inaccuracies in the 

experimentally measured values of the diffusion coefficient of methane in 

activated carbon. 

Noting the difficulty of obtaining accurate values for the intraparticle diffusion coefficient, Bullock and Threlkeld (211 used the lumped, effective 

external heat and mass transfer coefficients reported by Hougen and Marshall 

for the adiabatic drying of air by silica gel. To facilitate computation, 

they expressed the equilibrium data for silica gel presented by &bard [22] as 

polynomials in temperature and moisture content. Chi and Wasan [23] used the 

same approach to study air drying by a porous matrix impregnated with lithium 

chloride. More recently, Koh [24] investigated the use of solar energy for 

the regeneration of silica gel used for grain drying. Following the methods 

of Bullock and Chi, but modifying the transfer coefficients of Hougen and 

Marshall, Koh was moderately successful in matching experimental and predicted 

results for the adiabatic desorption process. 

All the researchers mentioned have investigated single-blow adsorption or 

desotption in fixed beds. Concerns about energy conservation and renewable 

resources over the past decade have stimulated research in coupled heat and 

mass transfer in total heat regenerators or enthalpy exchangers and in desiccant dehumidifiers for solar cooling. Maclaine-cross, Banks, and 

Close [25,26,27,28] used the method of characteristics to reexpress the 

governing equations for adsorption in terms of combined potentials. These 

equations are analogous to those for transfer alone, and existing solutions 

for rotary heat exchangers can be applied. This analogy method is approximate 

because linearizations are made at several points in its derivation. However, 

f t is very efficient cornputionally. Pla-Barby 129 1, Holmberg [30] , Barker and 

Kettleborough 1311, and Hathiprakasam and Lavan [32] have each analyzed the 

performance of adiabatic silica gel dehumidifiers but without comparing predictions with experimental data. Mathiprakasam 1331 predicted the performance 

of a cross-cooled silica gel dehumidifier. 

SECTION 3-0 

PSEDDO-STUDY-STATE MODEL, 

Most of the analytical approaches described in the previous section involve 

the derivation of a set of differential equations for conservation of mass and 

energy within the adsorption system, and the solution of that set of equations 

by finite difference techniques. The pseudo-steady-state model developed in 

this study uses an approach that simplifies the mathematics of the adsorption 

problem. As illustrated in Fig. 3-1, the Desiccant Simulation computer model 

(DESSIM) can be thought of as a conveyor belt that carries one chunk of air at 

a time through the desiccant bed. The passage of each air chunk through the 

bed corresponds to a single time step. The bed is divided into equal sections, and as the air chunk is exposed to each section, mass and heat transfer 

calculations are perf onned in an uncoupled manner - 

First, all temperatures are held constant while the amount of moisture transferred between the air and the bed section during the time step is determined, 

and the humidity ratio of the air chunk and moisture content of the desiccant 

section are revised. Second, an energy balance is performed that accounts for 

the amount of energy released when the water is adsorbed and determines an 

intermediate temperature for the bed section. Finally, a heat-transfer calculation is performed using this intermediate bed temperature and the original 

air temperature. Temperatures for the air and the bed are updated, and the 

air chunk is moved to the next bed section 

Although the sorption process is a transient one, these mass transfer and heat 

transfer calculations are done using equations for steady-state, counterflow 

mass exchangers and heat exchangers ; hence, the name pseudo-steady state. 

Conceptually, the model carries along a counterflow mass exchanger and a 

counterflow heat exchanger that each have surface areas for transfer equal to 

the surface area in each bed section. Final moisture contents and temperatures for the air chunk and the bed section at the end of each time step are 

taken to be the same as the outlet moisture contents and temperatures from 

simple counterflow exchangers. These have steady flows of air and desiccant 

material with inlet conditions equal to the initial conditions of the air 

Outlet 

Basket 

Air 

Fig. 3-1. Conveyor Belt Concept Used in Computer Model 

9 

Desiccant Bed 

2 3 *om N 
chunk and the bed section. Applying these exchanger equations during time 

steps that are short compared to the duration of the complete process preserves the transient character. The fact that the exchanger equations are 

analytical solutions describing the approach of an exchange process toward a 

maximum effectiveness allows relatively large time and space increments to be 

used without complicated numerical techniques. This permits simulations to be 

carried out at a very reasonable computational cost 

In the remainder of this section, we outline the equations used in the computer model. 

3.2 WS TRANS= CALCULATION 

The mass transfer calculation that is performed as each air chunk is exposed 

to a bed section is adapted from the effectiveness equations for a counterflow 

gas/liquid mass exchanger 1461. The configuration from which these equations 

are derived is shown in Fig. 3-2. 

The air at the desiccant surface is assumed to be in equilibrium with the 

desiccant. All temperatures are assumed to be constant. The moisture ratio 

in the desiccant is assumed to be uniform in the direction perpendicular to 

flow, and the transfer process is assumed to be controlled by a gas film 

resistance, which is modified to account approximately for the effect of a 

solid-side resistance to the diffusion of water. The applicability of these 

last two assumptions is discussed in Sec. 3.5. 

The rate of mass transfer per unit surface area at any point in the exchanger 

is given by 

where 

m = bulk vapor mass fraction in air 

n, = f(X,Tb), equilibrium vapor mass fraction at the desiccant surface 

g = effective gas-side mass transfer coefficient 

X = moisture ratio in desiccant (kg water/kg dry desiccant) 

Tb = temperature of bed section 

Defining the effectiveness E of the exchanger as the actual moisture transfer 

divided by the maximum possible moisture transfer, we have 

1 - exp [-Ntu(1-CC)] 

E = 1 - CCexp [-Ntu(1-CC) 1 

where 

Ntu = gAs/Cmln 

A, = surface area for mass transfer within the bed section 
i Air 

)/z 1 1 ms L I 

I J( 

1 

I 

i Desiccant i x 

I 

I t 

Fig. 3-2. Cancentrattoo Rofilea for Steady-State Mass Transfer Process 

",in and C,, are the smaller and larger of the capacity rates of the two 

streams flowing through the hypothet Ical exchanger - The capacity rate for the 

air is 

'air ' mgas, for the steady-state case 

= Ma (1 + wl)/At, for the pseudo-steady-state case. 

The capacity rate for the desiccant material is 

where 

Ma = dry mass of air chunk 

Mb = dry mass of bed section i 

Y a water mass fraction in desiccant, X/(l+X) 

At = tine step defined for the simulation. 

The partial derivative of the mass fraction of water in the desiccant with 

respect to the equilibrium vapor mass fraction at the surface replaces the 

inverse oE the Henry number used in gasjlfquid mass exchanger analysis, and is 

analogous to the specific heat in the expression for heat exchanger capacity 

rates. The calculatfon of this quantity is discussed in Sec. 3.6. 

With the effectiveness known, the mass fraction for the outlet air is 

m2 = ml - E(ml - m,) 
and the outlet humidity ratio is 

The amount of water transferred to the bed section during one time step is 

so the new moisture ratio in the bed is 

3.3 JxlmmDLPTE ENERGY 33AmNCE 

When water is adsorbed by a desiccant, energy is released. This heat of 

adsorption is usually greater than the heat of vaporization of water, and is a 

function of the water content in the desiccant. In the pseudo-steady-state 

model, an energy balance is performed after the mass transfer calculation to 

determine the change in the bed section temperature due to the adsorption or 

desorption of water. The temperature of the air is assumed to remain cons tant . The overall sorption process is assumed to be adiabatic, and no work is 

involved. Therefore, the energy balance on the air chunk and the bed section 

can be written simply as 

Here, all enthalpies are in terms of energy per unit dry mass of air or bed 

material, and 1 and * refer to states before and after the adsorption or 

desorption of the amount of water determined by Eq. 3-7. Correlations for the 

enthalpy of moist air (Sec. 3.6) use dry air and liquid water at O°C as a 

base. Therefore, the heat of vaporization is included implicitly in the 

enthalpies. Enthalpies for the desiccant bed can be defined using the same 

base, O°C and liquid water. However, water in the bed is in the sorbed state, 

not the liquid state. The energy difference between the liquid and sorbed 

states can be accounted for either by including a term for the integral heat 

of wetting directly into the expression for the enthalpy of the desiccant or 

by including an extra term in the energy balance, which accounts for the difference between the heat of adsorption and the heat of vaporization. The latter approach is used in this analysis. Hence, the enthalpy of the bed is 

defined as 

where the temperature is in degrees Celsius. Equation 3-9 becomes 

* 

where h = ha (T~ , q ) . a n 
Solving for the intermediate bed temperature 6, 

This is the initial bed temperature for the heat transfer calculation. Correlations for the ratio of the heat of adsorption and the heat of vaporization 

are given in Sec. 3.7. 

After the temperature change of the bed section caused by the heat of adsorption is determined, a heat transfer calculation is performed. As with the 

mass transfer calculation, equations for a counterflow exchanger are applied 

and the steady-state outlet temperatures are used as the final average 

temperatures of the air chunk and the bed section at the end of the time 

step. Again, the equation for the exchanger effectiveness is 

1 - exp[-Ntu(1 - CC) ] E = 1 - CC exp[-Ntu(1 - CC)] 

where, for the heat exchange problem, 

N~U = H A,/C,~~ 

CC = Cmax'Cmin 

Cair = Ma cp/At 

Cbed = Mb(cb + X2cw)/At 

H = average heat transfer coefficient. 

Since the effectiveness is the ratio of actual energy transfer to the maximum 

possible energy transfer, the total energy transfer from the air to the bed 

section during the time increment is 

Applying simple energy balances, new temperatures for the air chunk and bed 

section are 

The conditions of the bed section are stored and the air chunk is sent 1-0 the 

next bed section, where this series of calculations is repeated. 
sea TR-1330 

In both the mass transfer and heat transfer calculations, the rates of transfer are assumed to be controlled by single resistances in the gas film 

adjacent to the desiccant surface. This assumption is a good one for the heat 

transfer calculation because the heat transfer Biot number is small for 

typical packed-bed situations, and the temperature gradient within the 

particles would be minor. However, there is wide agreement that for silica 

gel particles of the size used in packed beds, there is a significant resistance to mass diffusion within the solid particle. The appropriate resistance 

model for the overall mass transfer process is shown in Fig. 3-3a. Here, Rg 

and Rs are the gas-side and solid-side resistances, respectively. In this 

case, the rate of mass transfer would be 

Solving for a value of the moisture ratio at the desiccant surface that is 

different from the average value adds significantly to the complexity and cost 

of a numerical solution to the sorption problem. Furthermore, there may be 

little benefit in accurate predictions, because diffusion coefficients for 

desiccants are difficult to measure accurately or predict theoretically. 

To simplify the analysis, the mass transfer rate is calculated as if it were 

strictly a gas-side-controlled process. However, the gas-side resistance is 

modified to account approximately for the resistance to moisture diffusion 

within the desiccant particles. This gas-side resistance model is shown in 

Fig. 3-3b. 

mj = f (ST, T) 

Fig- 3-3. (a) Detailed Resistance %del for Hass Transfer 

(b) Gas-Side Resistance Xodel for Mass Transfer 

14 
The particle is assumed to have a uniform moisture content and the equilibrium 

vapor mass fraction of the air at the surface is calculated using the average 

moisture content of the desiccant. The convective mass transfer coefffcient g 

is then reduced by some factor, which can be determined experimentally or 

approximated on the basis of theory. 

Hougen and Marshall [9], who were the first researchers to analyze the 

adiabatic adsorptfon process, used experimental data from Ahlberg [lo] to 

develop the following correlations for effective mass transfer and heat transfer coefficients for adsorption in packed beds of silica gel. 

These transfer coefficients have been used by Bullock and Threlkeld 12'11, Chi 

and Wasan 1231, Pla-Barby et al. (291, Koh [24], and Nienberg [34]. However, 

the original Ahlberg data contain a considerable amount of scatter, which 

leads to significant uncertainty Also, the correlations of Hougen and 

Harshall modify the heat transfer coefficient, as well as the mass transfer 

coefficient, to preserve a Lewis number close to unity. The kwis number, 

defined as 

is close to unity for an aidwater mixture in a strictly convective problem. 

However, in our case, there is no reason to modify the heat transfer coefficient, and consequently, modification of the mass transfer correlation 

results in an effective ZRwis number greater than unity. 

Since the heat transfer process is gas-side controlled in typical packed-bed 

situations, a correlation for heat transfer alone is used in the pseudosteady-state model. The correlation given by Handley and Heggs [3S] for the 

Nusselt number is 

where 

cV = void fraction. 

Manufacturers' data gfve a void fraction of 0.4, so the expression for the 

heat transfer coefficient used in the model is 
The mass transfer coefficient is then 

where Le is an effective Lewis number that depends on the parameters of the 

sorption situation. 

Close and Banks [27] have used this same approach for calculating mass transfer coefficients in silica gel beds. Recently, van Leersum 1471 has carried 

out an analysis to determine appropriate values of the effective Lewis number 

for rotary dehumidifiers. This analysis adapts Hausen's correction for the 

heat transfer coefficient in thermal regenerators that have a resistance to 

heat transfer within the solid matrix, and includes considerations of the convective transfer coefficient, the diffusivity of moisture in silica gel, the 

particle diameter, the equilibrium properties of silica gel, and the typical 

operating conditions of a rotating dehumidifier within a desiccant cooling 

system. Van Leersum's results indicate that a value between Le = 3 and Le = 4 

would be an appropriate average for rotary system simulations. However, the 

effective Lewis number is a function of several parameters and different 

values may be appropriate for single-blow simulations. 

Figure 3-4 compares several correlations for mass transfer in packed beds. 

Clearly, there is a considerable degree of uncertainty in characterizing this 

type of transport phenomenon. Mass transfer relationships based on the 

Handley and Heggs heat transfer correlation are included in Fig. 3-4 for three 

values of the effective Lewis number; 1, 3, and 9. With Le = 1, the Handley 

and Heggs correlation is grouped with the majority of the other correlations. With Le = 3, it is similar to the Hougen and Marshall correlation, 

which is based on silica gel adsorption data. With Le = 9 at low Re, it is 

relatively close to the Eagleton and Bliss correlation, which is also based on 

silica gel adsorption data. Thus, the use of an effective Lewis number as 

large as 9 is not out of line with previously reported mass transfer correlat ions. 

3.6 PROPERTIES OF MOIST AIR 

The properties of air that are used at various points in the calculation procedure are enthalpy, specific heat, thermal conductivity, and dynamic 

viscosity. The following an expression for the enthalpy of moist air was 

reported by Maclaine-cross [37]: 

Here, temperature T is in degrees Celsius and the enthalpy is units of joules 

per kilogram. The reported accuracy of this equation is 0.05%, as compared to 

standard tables. In the simulation of complete cooling systems, outlet temperatures from the sensible heat exchanger must be calculated from known values 

of enthalpy and humidity ratio. Solving Eq. 3-21 for temperature gives us 

sna TR-1330 

where 

The specific heat of moist air is also derived from Eq. 3-21: 

Specific heat, conductivity, and viscosity appear in the correlation for the 

heat and mass transfer coefficients. Because of the inherent uncertainty in 

this type of correlation, highly accurate expressions for air properties are 

not warranted. Properties of dry air at the inlet temperature to the bed are, 

therefore, used in calculating transfer coefficients. A constant specific 

heat and linear interpolation are used to calculate conductivity and viscosity 

from data in Holman [38] for the temperature range of interest. 

The following standard psychrometric equations are also used: 

humidity ratio w = .622 pv/(Patm - Pv) (3-27) 

relative Humidity RH = Patm w/[(CL622 + w) Psatl (3-28) 

where Pv is the vapor pressure, Patm is the ambient pressure, and Psat is the 

saturation pressure at a given temperature. 

2 The saturation pressure (N/m ) is calculated using the simple but accurate 

correlation reported by Maclaine-cross [37]. The reported accuracy of this 

equation is 0.08% as compared with standard tables. 

3.7 PROPERTIES OF SILICA GeL 

Silica gel is a highly porous, granular, amorphous form of silica that is manufactured by reacting sodium silicate with sulfuric acid. The internal structure of silica gel consists of a vast number of small pores. When used as a 

desiccant, standard grades of gel can hold up to 40% of their weight in water 

by mechanisms of physical adsorption and capillary condensation. Many different grades of silica gel are manufactured whose physical and equilibrium 

properties vary between grades. Regular-density gel, such as Davison PA40 or 

Syloide 63, is more appropriate than low-density gel for solar cooling 

applications because it demonstrates a favorable and relatively steep isotherm 

shape in the range of relative humidities typically found in desiccant 

cooling. Figure 3-5 shows this qualitative difference in gel properties. 

The physical properties of regular-density silica gel are summarized in 

Tables 3-1 and 3-2. 

18 
Table 3-1. Typical Properties of Silica 

Gel (ManufacturerT s Data, 

Grace & Co- 1431) 

Specific heat (cb) . 921 J/kg;C 

Apparent bulk density (pb) 720 kg/m 

Void fraction (E~) 0.4 

Table 3-2. Particle Mameter and Surface 

Area 1241 

Tyler Average Particle External Surface 

Diameter Area Mesh Size 

(m) 2 3 (m 

3.7.1 Equilibrium Properties 

Critical information for the simulation of the adsorption process is an 

expression for the equilibrium properties of the desiccant being modeled; 

i.e., an expression for the equilibrium vapor pressure at the desiccant surface as a function of the desiccant temperature and moisture content. There 

are several correlations available for the equilibrium properties of silica 

gel. Lunde and Kester [39] used a multilayer adsorption model along with 

experimental data For a moderate range of moisture content to predict complete 

iso therms. Ro jas [40] measured the equilibrium characteris tics of four grades 

of silica gel of different porosity, and fit polynomial expressions of the 

form ['.I ['.]i ['V]i [PvJi XxAO+A1 P +*2 i?- +*3 7 +A4 P (3-30) 

sat sat sat sa 

to this data. One of the gels investigated by Rojas is Davison grade PA-40, 

the same silica gel used in current adsorption experiments at SERI. 

Jury and Edwards 1411 fit the following equation to their data: 
Regular-Density 

0 20 40 60 80 1 00 

Relative Humidity,% 

Fig. 3-5. Typical Isotherms for Regular- and bw-Density Silica Gel 

Hubard [22] reported equilibrium data for the silica-gel/air-water system for 

temperatures between 4°C and 93°C (40°F and 200°F), and moisture contents 

between 1.5% and 35%. Bullock and Threlkeld [21] represented these data as 

polynomials of the form 

where 

've = equilibrium vapor pressure (in Hg) 

T = silica gel temperature (OF) 

X = silica gel moisture content (lb water/lb dry gel). 

The constants C1 through C8 are given in Table 3-3; m = 2 and n = 1 for X less 

than 0.05; and m = 1 and n = 0 for X greater than 0.05. 
Table 33. Constants for the kllock and Threlkeld Correlation for Silica 

Gel 

Range of 

Moisture Content Cl lo6 cq lo4 C3 C4 

(XI 

Range of )A 

Moisture Content 

(XI 
Close and Banks [27] plotted Hubard's data in the form of Othmer charts and, 

by applying the Clausius-Clapeyron equation, obtained 

where fl(X) and f2(X) are polynomials, and f2(X) is the ratio of the heat of 

adsorption to the heat of vaporization. They recommended the simplification 

of replacing fl(X) with the simple linear function 2.009X. 

The polynomial expression of Bullock and Threlkeld was 

this study, because of the convenience of calculating . However, it 

was later determined that this correlation gave 

bination of high temperature and high moisture content was encountered. 

Figure 3-6 shows a series of isotherms based on the equations of Bullock and 

Threlkeld. This demonstrates that the correlation should not be used when the 

gel moisture content is greater than 20% and the temperature is greater than 

about 50°C. 

Once this was discovered, other correlations were investigated more closely. 

Isotherms from the Close and Banks complete correlation and the simplified one 

using f (X) = 2.009X are compared in Fig. 3-7. This correlation was further 

simplifted to facilitate the calculation of (a~/am~)~ by using linear equations for h /h which are discussed in the next section. Pigure 3-8 

shows that tadas ?:&her simplification produces almost no change in the isotherms. The Rojas correlation for grade PA-40 is included for comparison in 

both figures. The Rojas data demonstrate an upper limit on the capacity of 

this grade of silica gel of about 37%, which is typical of regular-density 

gels. The other correlations do not taper off toward such a limit. However, 

the Rojas correlation does not include the fanning of isotherms at different 

temperatures, which is displayed in his data and by the other correlations. 

To combine both characteristics, the Rojas equation was recast to give vapor 

pressure as a function of moisture content, and an additional temperature 

dependence was included. 

Isotherms from this equation are shown in Fig. 3-9. 

The equilibrium vapor mass function at the surface ms used in the mass transfer calculation is determined from the equilibrium vapor pressure using the 

following psychrometric relationships: 

Also required in the mass transfer calculation is the partial derivative of 

the water mass fraction in the desiccant with respect to the equilibriun vapor 

mass fraction of the air at the surface. Reexpressing the derivative, 




Here, Y, the water mass fraction in the desiccant, is 

Y = X/(1 + X); kg water/(kg water + kg gel) , 

Equations 3-35 and 3-36 combine to give us 

m, = 0.622 Pve/(Patm + 0.378 Pv,) , 

The partial derivative (BXI~P,,) can be evaluated by differentiating the 

appropriate equation for P,, with respect to X and taking the inverse of the 

result. The reader is referred to the program listings in Appendix 3 for 

specific equations. 

The value of ( W/3tns) is determined by combining these results in Eq. 3-37. 

3.7.2 Heat of Adsorption 

The heat of adsorption of water on silica gel is a function of the water content of the gel. Close and Banks [27] plotted Bubardls data in the form of an 

Othmer chart to determine the ratio of the heat of adsorption to the heat of 

vaporization for water contents between 1% and 35%. Results were presented as 

polynomial curve fits, which were used in this study in combination with the 

equilibrf um correlations of Bullock and Threlkeld. 

Close and Banks [27] also applied the Clausius-Clapeyron equation to the vapor 

pressure data of Hougen, Watson, and Ragatz to obtain heat o.E adsorption 

information. Their conclusion was that these data must have been for a grade 

of silica gel other than the regular density type. Rojas 1401 reported heat 

of adsorption data for four grades of silica gel. Of particular interest is 

27 
his data for regular-density Grade PA-40. Low-density grades exhibit a lower 

heat of adsorption similar to the data of Hougen et al. Bullock and 

Threlkeld [21] fit two polynomials to Ewing's and Bauer's data for the integral heat of wetting. The polynomials are 

When these equations are differentiated with respect to X and the heat of 

vaporization is added, the heat of adsorption is obtained. A discontinuity in 

the heat of adsorption results from a discontinuity in slope at the intersection of the above equations. Nienberg [34] fit a linear equation to data 

reported by Beecher [42]. 

Figure 3-10 is a graph of the ratio of the heat of adsorption to the heat of 

vaporization, h,ds/\ap versus gel moisture content, which compares all the 

sources above. Agreement for regular density gel is within 5% for values of X 

between 0.1 and 0.25. However, for X less than 0.1 there is a large 

uncertainty. The following linear equations, which are shown as dashed lines 

in Fig. 3-10, were considered to give the best combination of accuracy and 

computational convenience and are used in this study in combination with the 

equilibrium correlations of Close and Ranks and those based on the Rojas data. 

In summary, the computer program includes three sets of correlations for 

equilibrium properties and the heat of adsorption. The first set combines the 

Bullock and Threlkeld polynomials for equilibrium vapor pressure with the 

Close and Banks equations for hads/hva,. The second set combines the Close 

and Banks equation for equilibrium vhpor pressure with the above linear 

expressions for hads/hvap. The third set combines the modified equation for 

Rojas' equilibrium data with the linear expressions for hads/hvap. These 

three correlation sets were included to allow comparison of the relative 

success of the different correlations in predicting experimental results. 


SECTION 4.0 

COMPARISON OF TBe MODEL ldI!lX EXPF:RZMgNTAL DATA 

4.1 DATA SOURCES FOR SINGLe-BLOW BDSQBPTION BND DESORPTIOB 

In terms of both analytical and experimental work, it is most convenient to 

deal with single-blow adsorption or desorption; i.e., the case where the 

desiccant bed is initially at some uniform state of temperature and moisture 

content, and air of constant temperature, humidity, and flow rate is passed 

through the bed. If an analytical model can predict the outlet conditions of 

process air during single-blow experiments, then the same model can be used to 

predict the periodic performance of desiccant beds in cooling systems. This 

reduces the need for complex and costly experiments on rotary desiccant wheels 

or complete cooling system prototypes. 

Simulation of the single-blow case is a straightforward application of the 

pseudo-s teady-state calculation procedure described in Sec. 3.0. The physical 

properties and dimensions of the desiccant bed are specified, along with the 

initial conditions of the bed and the inlet conditions of the air. Outlet 

conditions of the air at each point in time are simply the final conditions of 

each air chunk after being exposed to the last bed section. 

In this section, predict ions of the pseudo-steady-state model are compared to 

experimental data for single-blow adsorption and desorption cases. Three data 

sources are used to provide a thorough assessment of the validity of the model 

and the supporting information on silica gel properties and transport coefficients. The first data source is the Desiccant Test Laboratory at SERI. The 

second is Pesaran's master's thesis on "Air Dehumidification in Packed Silica 

Gel Beds" /36]. The third data source is Koh's doctoral dissertation on the 

regeneration of silica gel used for grain drying [24]. For each of these data 

sources, predictions using each of the three sets of property correlations 

described in Secs. 3.6 and 3.7 are compared. 

4.2 COMPARISON WITH SEBI DATA 

The SERI desiccant test laboratory was designed to test the performance of 

desiccants under operating conditions that would exist in desiccant cooling 

systems 1481. The data reported here were taken for a thin, packed bed of 

Davison Grade PA-40 regular density silica gel, which was held between two 

metal screens. The materials used, the dinensions of the bed, the flow rates, 

and the inlet air conditions were all chosen to be similar to those found in 

the AiResearch pro totype cooling system. The physical properties of the 

silica gel and the dimensions of the bed are given in Table 4-1. 
sea (al TR-1330 

Table 4-1. Physical Properties and Dimensions 

for SEEI Experiments 

Desiccant type: Davison Grade PA-40 Silica 

Ge 1 

Particle diameter: 0.00193 m' (8-10 mesh) 

Void fraction: 

Bulk density: 850 kg/m3* 

Surface area: 2 3 1335 m /m 

Specific heat: 921 J/kg OC* 

Bed thickness: 0.035 m 

Face area: 0.412 m2 

+From manufacturer's data. 

*Measured after settling. Note that this value 

is different from the nominal one reported in 

the manufacturer's data. 

Data from only two experimental runs, one adsorption run and one desorption 

run, are reported here. (See Ref. [48] for a complete report on the SERI 

desiccant test laboratory and a complete comparison of measured and predicted 

results.) For the adsorption run, data are compared with predictions using 

each of the three sets of silica gel property correlations described in 

Secs. 3.6 and 3.7. For the desorption run, data are compared with predictions 

using the Bullock and Threlkeld correlations with Lewis numbers of 3, 6, and 

9. Data are also compared with predictions using the other two correlations 

(ICORR = 2,3) and a Lewis number of 9. 

Table 4-2 presents a summary of the parameters for these comparisons, and 

graphical results are shown in Figs. 4-1 through 4-8. ICORR indicates which 

correlations are used in the simulation. ICORR = 1 is for the Bullock and 

Threlkeld equilibrium correlation with the Close and Banks polynomial equations for h ds/hva . ICORR = 2 is for the Close and Banks equilibrium correlation wit% line& equations for hads/hvap. ICORR = 3 is for the correlation adapted from the Ro jas data with linear equations for hads/hvap. 

Data presented here are typical of all the data obtained in the SERI desiccant 

test laboratory. Data obtained during the first one or two minutes are 

unreliable,however, because of the response characteristics of the optical dew 

point hygrometers. After this initial transient, the data follow smooth paths 

with very little scatter. The relationship between data and predictions is 

also typical in that agreement is closer for adsorption than for desorption. 

Figures 4-1 through 4-3 show predictions for the adsorption run using the 

three sets of property correlations. These figures demonstrate that there is 

little difference between these correlations in predicting outlet air conditions during adsorption. An effective Lewis number of 3.0 was used in 
Table 4-2. Summary of Data Buns and Computer Predictions for SePI Experiments on a 3. %em &da 

Previous Adsorption Simulation Parameters 

or Regeneration Conditions 

Data 

Run T 

Ga Xb ICORR 

Le ( kg/m2s) $1 (kgykg) 

a~at, = 83.4 kPa. Two-second time step and 10 bed sections used in simulations. 

b~alculated from the previous adsorption or regeneration conditions using the indicated 

equilibrt~ correlations. 

each simulation and provided a better fit to the data than 2.5 or 4.0. However, these changes in Lewis number produced only small changes in the predicted breakthrough curve. 

To obtain reasonable agreement between predicted and measured outlet condition 

during desorption, the effective Lewis number had to be increased significantly. Figures 4-4 thru 4-6 compare data to predictions using Lewis numbers of 3, 6, and 9 with the first correlation set. ie = 9 provides the best 

fit to the data, although this fit is not as good as that obtained for adsorption. Figures 4-7 and 4-8 show prediction using the second and third correlation sets. Differences between the predictions using the three correlations 

are larger than in the adsorption case. However, the differences are not 

major. These results are discussed in greater detail in Sec. 4.5. . 

Pesaran [36] conducted single-blow adsorption experiments on regular density 

silica gel in packed beds. He performed experiments with two particle sizes 

and three bed thicknesses. His range of inlet air conditions is somewhat 

limited, with inlet temperatures near room temperature and relatively low 

inlet humidities between 0.003 and 0.011 kg/kg. Predictions using the pseudosteady-state model are compared with data from seven of Pesaran's runs in 

Figs. 4-9 thru 4-17. Most of these runs were performed using the Bullock and 

Threlkeld correlation before the limitation of that correlation was discovered. Predictions using the other two correlations are given for Pesaran's 

Run 13. Again, with these operating conditions, the different correlations 

give very similar predictions. 

The physical properties of the silica gel and the dimensions of the bed as 

reported by Pesaran are summarized in Table 4-3. A summary of the parameters 

of each run is given in Table 4-4. 

















Table 4-3. Physical Roperties and Dimensions 

for Pesaran Experiaeats [36] 

Specific heat: 921 J/kg OC 

Void fraction: 0.4 

Bulk density: 745 kg/m3 

Face area: 0.01327 m 2 

Tyler mesh: 3-8 6-12 ' 

Surface area: 

2 3 919 m /m 2 3 1690 rn /m 

Particle diameter: 0.0039 m 0.0021 m 

Table 4-4. wry of Data Pune and Predictions for Pesaran ~x~erioents -- 

Data Gel . Bed 'in =o Xo Ga Simulation 

Parameters Run Yesh Depth (kg/b) (OC) (kdkg) (k8h2S) ICORR 

k 

8 3-8 0.070 24.3 0.00873 2 4 0.028 0.408 1 3 

Patm = 101235 Pa. Two-second time step and LO bed sections used in simulations. 

Results show relatively good agreement between data and predictions, although 

agreement is not as close as with the SERI data. A discrepancy that repeats 

itself is that the second predicted process line on the psychrometric chart, 

the one that is similar to a constant enthalpy line, runs parallel to the data 

but is displaced to a lower humidity in several runs. This indicates the possibility that reported inlet conditions for these runs are inaccurate, because 

the psychrometric process line must terminate at the inlet air state once the 

bed is saturated. 
To study the potential of using solar energy to regenerate silica gel used for 

grain drying, Koh performed single-blow desorption experiments on packed 

beds. The packed beds Koh studied were thick compared to those used in desiccant cooling, but his regeneration temperatures are in a range of interest. 

The physical properties of the silica gel reported by Koh are given in 

Table 4-5. A summary of the parameters from each run included here is given 

in Table 4-6. 

Table 4-5. Physical Properties for Koh 

Experiments 

Particle diameter: 0.00176 m 

Surface area: 2 3 1440 m /m 

Void fraction: 0.4 

Bulk density: 740 kg/m3 

Specific heat: 95 1 - kg 

Table 4-6. Summary of Data Runs and Predictions for Ibh Experiments 

Data Bed - - - T. W. T, X, Ga Simulation -~n ~n -(I --u -- 

Run Depth (Oc) (kg/kg) Parameters 

Le 

Pagm = 98200 Pa. Ten-second time step and ten bed sections used in simulations. 

The Koh data exhibit more scatter, particularly in humidity, than the other 

two data sources. There is generally good agreement between data and predictions on the trajectories of the psychrometric process lines. However, in 

almost all cases the predicted breakthrough curve is steeper than that measured. An effective Lewis number of 9 was used in the simulations, because it 

gave a good fit to the SERI data. Roh used finite difference methods to 
obtain computer predictions for his experimental runs. Beginning with the 

heat and mass transfer correlations of Hougen and Marshall (see Fig. 3-4), he 

found it necessary to divide both transfer coefficients by five to obtain 

reasonable agreement between predicted and experimental breakthrough curves. 

Reynolds numbers for most of Koh's data runs were less than 10; therefore, 

axial dispersion may have contributed to the spreading of the moisture wave 

that is observed I441 (see Figso 4-18 through 4-25). 

In summary, the pseudo-steady-state model and the associated correlations for 

equilibrium properties and transfer coefficients give predictions that are 

very close to measured results for adsorption cases. Based on these results, 

it may be concluded that the use of a lumped, gas-side mass transfer coefficient is satisfactory for the simulation of water vapor adsorption by silica 

gel in packed-bed situations with conditions in the range of interest in 

desiccant cooling. The desiccant cooling cycle, of course, includes both 

adsorption and desorption. Results for desorption are not nearly as satisfactory as those for adsorption. On the whole, far fewer data are available 

for desorption than for adsorption, and other investigators have had similar 

difficulty in matching predictions with experimental data. Close 1443 used 

the analogy method for heat transfer to predict single-blow adsorption and 

desorpti on, achieving relatively good agreement with adsorption data but poor 

agreement with desorption data. He attributed this discrepancy primarily to 

variations in properties of the silica gel/air/water system that are not fully 

accounted for by the analogy method. However, the pseudo-s teady-state model 

accounts for any property variations included in currently available equilibrium correlations. Furthermore, this study has demonstrated that the use of 

different property correlations has lf ttle effect on the predicted breakthrough curves. Thus, it seems that variation or uncertainty in equilibrium 

properties during the adsorption/desorption process cannot explain the need to 

use a large effective Lewis number to obtain reasonable predictions for 

desorption. 

Some silica gels exhibit a hysteresis loop in their relationship between moisture content and vapor pressure between adsorption and desorption. However, 

Rojas' data for PA-40 silica gel indicate that there is little or no 

hysteresis in the equilibrium properties of this gel [40]. Therefore, the 

fact that desorption cannot be predicted accurately by a gas-side resistance 

model using the same effective Lewis number as for adsorption indicates that 

there may be a dynamic hysteresis that acts to slow the desorption process but 

does not affect equilibrium data. This does not mean that a two-resistance 

model is necessary. The transport of water molecules within silica gel is not 

a simple solid diffusion problem, but a combination of pore diffusion, surface 

diffusion, repeated adsorption/desorption along the pore walls, and evaporation within capillaries. Consequently, a two-resistance model using a single 

diffusion coefficient may offer little improvement in accuracy over the 

lumped, gas-side resistance model. Relatively good results can be obtained 

with the pseudo-steady-state model once the appropriate value for the effective Lewis number has been determined. Xowever, the above results show that, 

at least for desorption in packed beds, it will be necessary to determine 

these values experimentally. 









SECTION 5.0 

DESICCANT COOLING SYSTEM SIMUIATION 

A single cooling system configuration was chosen for this study. This system 

consists of an adiabatic dehumidifier, a sensible heat exchanger, two evaporative coolers, and a solar heater- Two modes of operation were considered; the 

ventilation mode and the recirculation mode. The ventilation mode is illustrated in Fig. 5-1. On the conditioning side of the system, ambient air is 

dehuaidif ied, sensibly cooled, evaporatively cooled, then delivered to the 

building. On the regeneration side of the system, indoor air is evaporatively 

cooled to provide a cold sink for the cycle, heated first in the sensible heat 

exchanger, then in the solar heater, then used to regenerate or redry the 

desiccant, and finally exhausted to the atmosphere. 

In the recirculation mode, illustrated in Fig. 5-2, the same processes are 

carried out, except that indoor air is conditioned and delivered back to the 

building, while outdoor air is used for regeneration, then exhausted back to 

the atmosphere. In both modes, flow rates on the two sides of the system were 

assumed to be balanced, and no purge sections such as those used by IGT and 

AiResearch were included. Thus, the system considered in this study is the 

simplest possible desiccant cooling system. 

The dehumidifier is the heart of a desiccant cooling system. It is the most 

difficult component to characterize and the most interesting component in 

terms of research, since the state of the technology in coupled heat and mass 

transfer is much less advanced than in heat transfer alone. Therefore, the 

dehumidifier is simulated in detail using the pseudo-steady-state model, while 

the evaporative cooler and sensible heat exchanger are analyzed simply by 

specifying an effectiveness anrl applying the appropriate energy and mass 

balances. 

The inlet air states on both sides af the dehumidifier mst be known before 

the pseudo-steady-state model can be applied. Therefore, the thermodynamic 

analysis of the cooling cycle operating in either mode proceeds as follows: 

e The outlet conditions from evaporative cooler 1 (state 2) are determined 

by calculating the wet bulb temperature at state 1, calculating the 

saturation humidity at this wet bulb temperature, and using a specified 

saturation effectiveness. 

The humidity ratio at state 4 is assumed to be the same as that at 

state 2, and the temperature at state 4 (the regeneration temperature) is 

specified. 

The pseudo-steady-state model is used to determine the average outlet 

states from both sides of the humidifier (states 5 and 7). 


Outlet states from the sensible heat exchanger (states 3 and 8) are calculated based on a specified heat exchanger effectiveness. 

The outlet state from evaporative cooler 2 (state 9) is determined in the 

same manner as for evaporative cooler 1. (I.e., wet bulb temperature is 

at state 8, etc.) 

The COP and cooling capacity of the system are calculated from air 

enthalpies determined in the above manner using Eq. 3-21. 

The methods of analysis, assumptions, and equations for each component are 

discussed in greater detail in the following sections. Throughout the 

analysis, it is assumed that the states of the air streams between each component are uniform and that there is no leakage of air. 

The psychrometric process line for evaporative cooling is assumed to be a line 

of constant wet bulb temperature. It is also assumed that the performance of 

the evaporative cooler can be characterized by a saturation effectiveness, 

such that state 2 is given by 

where TI* is the wet bulb temperature at state 1 and wl* in the saturation 

humidity of that temperature. This wet bulb temperature is calculated using 

the iterative equations given by ASHRAE standards [45]. The procedure used in 

the computer program is to guess a value of TI* based on the enthalpy at 

state 1 and a polynomial relationship between enthalpy and wet bulb temperature. The humidity ratio based on this guess and the dry bulb temperature at 

state 1 is then calculated using the following equation in English units: 

The value of wcheck is compared to the known w and the bisection method is 

used in adjusting T1* and iterating through Eq. -2 until the correct value of 

TI* is found to within a narrow tolerance. 

f 

The dehumidifier is analyzed using the pseudo-steady-state model. This model 

was described in Secs. 3.0 and 4.0 in terms of the simulation of single-blow 

adsorption or desorption. The model can also be applied to cyclic operation 

of a fixed bed or to a rotating dehumidifier. To simulate the performance of 

a dehumidifier wheel, the model is applied to a small element as shown in 

Fig. 5-3. The advance of time in the simulation corresponds to the progression of this element in a circular arc through either the adsorption or 

the desorption side of the system. As the element progresses, the outlet air 

state progresses along the process lines described in Sec. 6. Once the 

element has completely traversed one side of system and crosses to the other 

side, the direction of the conveyor belt model is reversed and the inlet air 
conditions are changed. The average outlet state on each side of the 

dehumidifier is of primary interest in this study and is calculated at the end 

of each half-period. The total amount of water adsorbed or desorbed by the 

desiccant is also calculated at the end of each half-period. To predict the 

steady-state performance of the system, the computer model is cycled between 

adsorption and regeneration unti 1 the amount of water adsorbed and desorbed in 

the two half-cycles balances to within a defined convergence criterion. For 

this study, the water balance was required to be within 0.1%. 

Small Element. 

Housing 

Desiccant 

Matrix 

7 Direction of 

Air Flow 

Fig. 5-3. Small Element Used in Sfmulatioas of Rotary Dehumidifiers 

The sensible heat exchanger is modeled simply by assuming an overall heat 

transfer effectiveness. It is also assumed that no moisture is transferred 

between air streams. The capacity rates of the air streams are calculated as 

Cads ' mads cp[T(7), W(7)I (5-3) 

Greg =peg cp[T(2), W(2)J , (5-4 ) 

where rates 'ads and mreg refer to dry air. Specific heats are calculated from Eq. 3-23. The total energy transfer is 
Thus, enthalpies at states 3 and 8 are 

Temperatures at states 3 and 8 are calcylated frorp Eq. 3-22. Note that, in 

this study, balanced flow is assumed, so mads and mreg are equal. 

The solar or auxiliary heater is assumed to supply just enough energy to raise 

the regeneration stream to the specified temperature. 

The cooling capacity of the system is based on the enthalpy difference between 

the room air supplied to the system and the conditioned air delivered to the 

room. 

For the balanced-flow case, we have 

The thermal COP of the system is the ratio of the total cooling capacity to 

the total thermal energy added for regeneration: . 

Qcool COP = - . (5-10) 

Qr eg 

No estimates of parasitic power have been included in this study. Experimental data on pressure drop in the packed silica gel bed used in SERI's 

adsorption test is included in Ref. [48]. 
SECTION 6.0 

THE PHYSICAL BEHAVIOR OF DESICCANT BEDS 

This section presents a detailed discussion of the way silica gel beds behave 

during adiabatic adsorption and desorption, and how this behavior within the 

desiccant bed affects the outlet states of the process air leaving the bed. 

This detailed discussion is included because an understanding of the behavior 

of desiccant beds seems critical to achieving an understanding of desiccant 

cooling systems and to directing future research toward improving desiccant 

sys terns. 

This discussion relies heavily on graphics. A11 graphs were generated using 

the DESSIM computer programs, the DISSPLA graphics software package, and a 

CALCOMP plotter. In the plats of temperature and loading profiles, bed location refers to the 20 evenly divided bed sections used in the simulations and 

is, in effect, a nondimensional distance through the bed. 

6-1 BEHAVIOR OF THICK BEDS DUBING ADIABATIC AD!3OBPTION 

The adiabatic adsorption process involves the propagation of two waves through 

a desiccant bed. Heat transfer and mass transfer occur simultaneously during 

the passing of each wave, and both are coupled thermal and moisture waves. 

However, the first wave has a primarily thermal effect within the bed. That 

is, the temperature of the desiccant may change significantly with the passing 

of the first wave, but the moisture content of the bed changes only 

slightly. The second wave is what is usually referred to as the moisture 

wave, but the temperature and moisture content of the desiccant change sirnultaneously with the passing of this wave. 

The first wave travels much faster than the second wave in, silica gel. Therefore, two time scales are used in the two sets of figures illustrating this 

process. Figure 6-1 illustrates single-blow adsorption with a flow rate of 2 0.5 kg/m s in a 0.5-m-thick bed of 8-10 mesh silica gel. The time scale used 

in these graphs corresponds to the time it takes for the first wave to pass 

completely through the bed. Figures 6-l(a) and (b) show temperature and moisture profiles within the bed at one-minute intervals. Figure 6-l(a) shows 

that the first wave passes through the bed in about six minutes, and that a 

significant change in bed temperature accompanies its passing. Figure 6-l(b) 

demonstrates that the moisture content of the bed changes very little with the 

passing of this wave. Both figures show that the second wave has only begun 

its progression into the bed during this time. Figures 6-l(c) and (d) show 

the outlet air temperature and humidity as a function of time during the 

passing of the first wave. Both quantities change, and it is important to 

note that the air humidity changes significantly with the passing of the first 

wave, even though the first wave acts somewhat like a pure thermal wave within 

the bed, Figure 6-l(e) demonstrates that this change occurs along a psychrometric process line that is' similar to, but steeper than, a line of constant 

relative humidity. 

The same adsorption process is illustrated on a much longer time scale in 

Fig. 6-2. Temperature and loading profiles are shown at 30-minute intervals 

in Figs. 6-2(a) and (b). The second wave becomes very spread out during 

adsorption and has not left the bed even after 180 minutes, whereas a square 

wave involving the same change in conditions would pass through the bed in 

less than 90 minutes. Figures 6-2(b) and (c) show outlet air states as a 

function of time. Here, the breakthrough curve for the first wave is compressed to the far left portion of each graph. This is followed by a dwell 

period during which the outlet air remains at a constant state. After about 

25 minutes, the outlet air state begins to move slowly toward the inlet state 

as the second wave begins to pass the outlet end of the bed. 

Figure 6-2(e), the psychrometric chart, shows the two distinctly different 

process lines followed by the outlet air states as the two waves pass through 

the bed. With this relatively thick bed there is a sharp elbow at the intersection that corresponds to the dwell state. The trajectories of the two process lines are determined primarily by the physical and equilibrium properties 

of the desiccant. Close and Banks 1271 have presented a detailed analysis of 

these lines, which will not be repeated here. However, the process lines can 

be described in the following approximate manner. For pure, regular-density 

silica gel, the equilibrium water content can be described reasonably well as 

a function of the relative humidity of the surrounding air, and lines of constant relative humidity on the psychrometric chart can be translated roughly 

to lines of constant gel moisture content. As the first wave passes, the 

water content of the bed changes only slightly. Thus, the first process line 

is not far from a line of constant relative humidity. The passing of the 

second wave involves the adiabatic addition or removal of water from the air 

stream. Thus, the second process line is similar to an adiabatic saturation 

process line, which is a line of constant wet bulb temperature. ' The second 

process line differs from an adiabatic saturation line roughly by the difference between the heat of adsorption and the heat of vaporization of 

water. The heat capacity of the desiccant bed also affects the slopes of both 

process lines. As the heat capacity of the bed increases, the first process 

line becomes more verticle and the second process line becomes more horizontal. 

6.2 BEHAVIOR OF THICK BEDS DURING ADIABATIC DESOBPTION 

As was demonstrated by the experimental data from the SERI Desiccant Test Lab, 

the behavior of desiccant beds during desorption is somewhat different from 

that during adsorption. The outlet air states followed the same type of 

psychrometric lines, but the breakthrough curve for the second wave was always 

steeper than that observed during adsorption. Figures 6-3 and 6-4 show the 

predicted behavior of an 0.5-m silica ge$ bed as described above during 

desorption with the same flow rate, 0.5 kg/m s. The time scales are the same 

as for the adsorption case; Fig. 6-3 illustrates the first wave and Fig. 6-4 

illustrates the second. From Figs. 6-4(a) and (b) it is again clear that the 

passing of the first wave has only a slight effect on the water content of the 

silica gel and that this wave is primarily a thermal wave within the bed. The 

most notable difference between desorption and adsorption in relatively thick 

beds is demonstrated by comparing Fig. 6-4 with Fig. 6-2. The temperature and 

loading profiles of Figs. 6-4(a) and (b) show that the second wave in desorp- 



tion develops a constant shape that is much steeper than the second wave front 

in adsorption. This results in a longer dwell period and a steeper breakthrough curve, as illustrated in Figs. 6-4(b) and (c). 

In general, the second wave is a dispersive wave during adsorption, but a 

self-sharpening wave during desorption. This is due to the coupling of heat 

and mass transfer processes and to the fact that, as the wave passes,?the prop1- 

ercies -of the afr/water/silica gel system change. The properties determine 

wave speed, so the local wave speed changes as the wave itself passes. 

Specifically, local wave speed is affected by the local value of the partial 

derivative (aY/a m,) , taken along the path of the psychrometric process line. 

This is analogous to the specific capacity ratio for heat transfer alone. 

(Note that 3Y/ams taken in the direction of the second psychrometric process 

path is similar to y2 in the analogy method 1261.) Local wave speed decreases 

as this derivative increases. As the second wave progresses through the bed 

during adsorption, air states at a given location move to lower temperatures 

and higher humidities along a process path such as that in Fig. 6-2(e). The 

derivative (aY/ams) taken along that path increases as the second wave passes, 

causing the local wave speed to decrease. This causes spreading of the second 

wave during adsorption. During desorption, local air states move in the opposite direction. This derivative decreases, causing local wave speed to tend 

to increase as the second wave passes. The constant shape of the wave front 

shown in Figs. 6-4(a) and (b) is reached through a balance between this selfsharpening effect and the spreading effect of finite transfer coefficients . 

6- 3 BEBBVIOR OF TfIIN BEDS 

The examples above illustrate a desiccant bed many times thicker than those 

used in cooling systems. Relatively thin beds must be used in desiccant 

cooling, because of restrictions of pressure drop and parasitic power. With 

thin beds the two waves are not completely distinct. The first wave does not 

have time to pull away from the second wave, and the effects of the two are 

superimposed to some extent. Figures 6-5 and 6-6 show the predicted behavior 

of a 0.04-m packed be$ of 8-10 mesh silica gel during adsorption. Again the 

flow rate is 0.5 kg/m s, and two time scales are used to focus on the two 

waves. 

Figures 6-5(a) and (b) show that the second wave is already well into the bed 

by the the time the first wave leaves. In fact, the leading edge of the 

second wave always overlaps the tail of the first wave. This is demonstrated 

by the fact that there is no dwell period in the graphs of outlet air states 

[Figs. 6-6(b) and (c)]. This superposition of wave effects is also demonstrated by the psychrometric process paths for the outlet air states 

[Fig. 6-6(e)]. Here there is no longer a sharp elbow at the intersection of 

two equilibrium process lines as in Fig. 6-2(e). Rather, the path of outlet 

states cuts the corner near this intersection point. This intersection point 

or dwell point is the driest state achievable during adsorption. Therefore, 

the inability of a thin desiccant bed to reach and maintain that state reduces 

cooling system performance from its naxinum potential. 

Figures 6-7 and 6-8 illustrate the behavior of the same thin bed during 

desorption. Because of the self -sharpening nature of the waves during desorp- 




tion, slightly less overlapping of the two waves occurs [Figs. 6-7(a) 

and (b)]. The balance between the self-sharpening effect and the dispersive 

effect of finite transfer coefficients again leads to the formation of a constant pattern second desorption wave. This is shown in Figs. 6-8(a) and (b), 

although the effect is not as distinct as with the thicker bed. 

Figures 6-8(c) and (d) demonstrate that there is still no identifiable dwell 

period in the outlet air state, and the psychrometric process path in 

Fig. 6-8(e) does not quite reach the intersection point obtained in 

Fig. 6-4(e) with the thicker bed. 

Note that during both adsorption and desorption in the thin desiccant bed, the 

temperature and loading profiles for both waves are relatively flat. That is, 

neither the first nor the second wave is at any time contained completely 

within the desiccant bed. This is what makes the behavior of the type of beds 

used in desiccant cooling very different from that of the type of beds used in 

most industrial adsorption applications. 

6.4 BEHAVIOR DURING CYCLE OPERATION 

The examples above were for single-blow adsorption or desorption where the 

desiccant bed exhibited uniform initial conditions of temperature and moisture 

content. In a cooling system, a thin bed is continuously cycled between 

adsorption and desorption. The behavior of a thin desiccant bed in cyclic 

operation is illustrated in Fig. 6-9. Here, the DESSIM system simulation program was used to model a cooling system operating in the ventilation mode 

between ARI standard indoor and outdoor conditions. The bed thickness and air 2 flow rates were again taken to be 0.04 m and 0.5 kg/m s, respectively. The 

overall cycle time for the desiccant wheel was set at 10 minutes. Thus, 

recalling Fig. 5.3, a small axial dehumidifier element spends five minutes in 

each stream. In cyclic operation, the best performance is obtained with 

counterflow operation. Thus, flow directions during absorption and desorption 

are opposite. 

Figures 6-9(a) and (b) and 6-9(e) and (f) show the temperature and loading 

profiles in the desiccant at one-minute intervals during adsorption and 

regeneration, respectively. In each case, we see that the first wave passes 

completely through the bed in slightly over one minute, causing a large change 

in bed temperature but only a slight corresponding change in silica gel moisture content. From Figs. 6-9(b) and (f) it is clear that the average cycled 

capacity of the desiccant is only about 3% by weight. This is a consequence 

of the thinness of the bed in comparison to the second wave front. Only a 

part of the second wave is contained within the bed, and the front is pushed 

back and forth relatively little as the bed cycles between desorption and 

adsorption. 

A significant consequence of the differences between the adsorption and 

desorption processes is that the second wave is not centered within the bed. 

Rather, it is skewed toward the adsorption inlet side. Thus, during regeneration, the desiccant near the regeneration inlet is typically dried to equilibrium with the regeneration air, but the desiccant near the adsorption inlet 

is still far from equilibrium with the inlet air at the end of the adsorption 

half-cycle. The effects of this on the outlet air states on both sides of the 


dehumidifier are shorn in Fig. 6-9(i), the psychrometric chart. The process 

paths for the outlet air states during both adsorption and regeneration have 

been enhanced with symbols spaced at 6-second intervals. Each symbol corresponds to the steady-state outlet air state at a fixed circumferential position downstream of the dehumidifier. The inlet states for adsorption and 

regeneration are also shown. During adsorption the first leg of the process 

path begins at the regeneration fnlet state because that end of the bed 

reached equilibrium with the inlet air during regeneration. However, during 

regeneration the first leg of the process path does not pass through the 

adsorption inlet state. Instead, it begins at a point along the trajectory of 

the adsorption process path that corresponds to the wettest condition reached 

by the desiccant during adsorption. 

It is the average outlet air state during adsorption that is of greatest concern in desiccant cooling. The closer this average outlet state can be 

brought toward the type of intersection point or dwell state shown in 

Fig. 6-2(c)-(e), the higher the thermal performance of the system will be. 

sea !+I 

TR-1330 

SECTION 7.0 

PAMMETRIC STUDIES OF DESICCANT COOLING SYSTEMS 

A series of parametric runs as carried out using the system simulation version 

of the DESSIM computer model. These parametric studies have two objectives. 

The first is to characterize the effect on performance of various operating 

parameters, including dehumidifier wheel speed, outdoor conditions, indoor 

conditions, and regeneration temperature. The second is to provide information for an initial assessment of the potential benefits in system perfonnance 

that could be achieved through development of advanced components with higher 

effectivenesses than have been measured to date in desiccant cooling prototypes. Performance is measured by the thermal COP as defined by Eqo 5-10 and 

the cooling capacity per unit mass of conditioned air, which is equal to the 

enthalpy difference between the room air and the conditioned air. 

With any f f nite-dif f erence computational method, the choice of time and space 

increments is important and often represents a compromise between accuracy and 

computational efficiency. Figure 7-1 shows the effect of changing the sixnulation time step on the thermal COP of the base case system described in 

Sec. 7.2, operating in the ventilation mode. The spacial increment is also 

varied as a parameter. The predicted COP decreases as the time increment is 

decreased for a given number of bed sections. However, the predicted COP 

increases as the spatial increment is decreased (number of sections is 

increased) for a given time step. This conveniently allows us to use moderate 

time and space increments and still obtain predicted results quite close to 

the value that the method would converge to with very small time and space 

increments. Based on this result, all the remaining parametric studies were 

performed using 10 bed sections and a time step of two seconds. 

COP VS. TIME STEP P4 

4 0 

Number of 

Bed Sections 

0 - 10 

d 

0.0 0.5 1.0 1.5 2.0 

TIK STEP IS1 

Fig. 7-1- Predicted COP vs. Simulation Time Step 

85 
The effects on predicted performance of using different equilibrium correlations and different values for the effective Lewis number for regeneration are 

also of interest. Figures 7-2(a) and (b) show the effect of regeneration 

Lewis number on system COP and capacity, respectively. Both quantities drop 

as the regeneration Lewis number increases, but not as quickly as one might 

expect with this large change in the mass transfer coefficient. Each is only 

decreased by about 12% as the mass transfer coefficient during regeneration 

decreases by a factor of three. Because there is still some uncertainty as to 

the applicability of a high desorption Lewis number to the case of a rapidly 

cycling dehumidifier, a Lewis number of 3 is used in these parametric 

studies. This is consistent with the recommendations of van Leersum [47]. 

In Fig. 7-2, ICORR indicates which of the three equilibrium correlations 

described in Sec. 3.7 was used in the simulation. There is little difference 

between predictions using the Bullock and Threlkeld correlation (ICORR = 1) 

and the Close and Banks modified correlation (ICORR = 2). This is to be 

expected, since both correlations are based on the same data. The correlation 

based on the Rojas data (ICORR = 3) leads to somewhat poorer predicted performance. COP is lower by about 8% and capacity is lower by about 4%. Given 

that the first two correlations represent an available silica gel and that the 

modified Close and Banks correlation is simpler, the Close and Banks correlation was used in the remaining studies. 

Pig. 7-2 (a) COP w. Regeneration Levis Number 

(b) Capacity vs. Regeneration Lewis Number 

a. -v b. N 

I 

COP VS. LE, 2 2 CAPACITY VS. LE,2 c2 

9.0 

a - gREGENERATION LEWIS NO. REGENERATION LEWIS NO. 

X - 

27: 

7- 0- 

0 

o .r 

0 - 

2 - 

- 

0 - 

'2, 

- I " 

ICORR 

0- 1 

0-2 

A - 3 

- 

5 

a? 

M a, 2- 

0, 

CI) 

? 7 4- 

Y 

M 

E 0 0- ui a 

0- 

a 

o 

: 

3.0 6.0 

- 

- I 

CORA 

0- 1 

0- 2 

A-3 

9.0 3.0 6.0 
The general system configuration that the DESSIM program models was described 

in Sec. 5.1. For these parametric studies, two specific systems were considered. The first contains components that are representative of those found 

in existing prototype systems, and this system performs similarly to the 

tested prototypes. The second is a higher performance system containing components with performance levels that have not yet been obtained in desiccant 

cooling prototypes. Simulation of this system gives an indication of the 

potential gains in thermal performance that could be achieved through improved 

component design. The second system is not an optimized design, and there is 

no special significance to its component specifications other than that they 

have a higher effectiveness. In particular, the dehumidifier is assumed to be 

a packed bed, whereas it is probable that laminar-flow, parallel-passage 

designs will prove to be more appropriate for high effectiveness 

dehumidifiers . 

An important parameter that must be optimized for each system is the rotation 

speed of the desiccant wheel. Figures 7-3(a) and (b) show COP and capacity 

versus half-cycle time for desiccant beds 3 cm to 7 cm thick in a ventilation 

system having 90% effective evaporative coolers and heat exchanger and 

operating at ARI standard conditions with an 80'~ regeneration temperature. 

Each curve displays a broad optimum. Optimum COP and capacity increase as the 

thickness of the bed increases. The optimum half-cycle time also increases 

with bed thickness. For a given bed thickness, the half-cycle time giving the 

highest capacity is longer than that giving the highest COP. For example, 

with the 4 cm bed, COP peaks between 4 and 5 minutes, while capacity peaks 

between 5 and 6 minutes. 

OPTIMUM PERIOD: LE,2-3 

Bed Thickness 

n - 0.03rn 

0 - 0.04 

b. m -u 

0; 

OPTIMUM PERIOD: LE, 2-3 

I 

M I Bed Thickness I 

0.0 2.0 LO a0 0.0 t0.0 !i.o 

HflLF-CYCLE TIME (HINUTES) 

Fig. 7-3 (a) COP w. Balf-Cycle =me 

(b) Capacity vs- Ealf-Cycle Time 
The specifications of the base system and the high-performance system are summarized in Table 7-1, and nominal operating conditions are given in 

Table 7-2. The sections that follow present results of parametric studies of 

these systems. These studies cover the effects on performance of outdoor conditions, indoor conditions, regeneration temperature, heat exchanger effectiveness, and evaporative cooler effectiveness. 

7.3 EFFECT OF OUTDOOR CONDITIONS 

Characterization of the performance of a desiccant cooling system is complicated by the fact that performance is sensitive to operating conditions of 

humidity as well as temperature. In this parametric study, the outdoor conditions were varied while other conditions were held constant. Outdoor temperatures from 27.5'~ to 40'~ (81 O OF to 104'~) and outdoor humidity ratios from 

Table 7-1. System Specifications for Parametric Studies 

Base System High-Performance System 

Dehumidifer wheel 

(Packed silica gel) : 

Thickness 

Particle diameter 

Bed density 

Specific heat 

Surface area 

Air flow rate 

Half-cycle time 

Lewis number 

Heat exchanger 

effectiveness 

Effectiveness of 

evaporative cooler 1 

0.04 m 

0.00193 gj 

740 kg/m 

921 ~/$gOs 

1335 m / 1 0.5 kg/m s , 

5 min 

3 

0.10 m 

0.00193 y 

740 kg/mo 

921 J/$g 5 

1335 m /q 

0.5 kg/m s 

10 min 

3 

Table 7-2. Nominal Operating Environment for Parametric Studies 

Temperature Humidity Ratio (kg/kg) 

Indoor conditions 26.7'~ (80'~) 

(ARI standard): 

Outdoor conditions 35 .oOc (95'~) 

(ARI standard): 

Xegeneration: 80'~ (176'~) 
0.008 kg/& to 0.017 kg/kg were used. Each system was operated in both ventilation and recirculation modes. Figures 7-4(a),(b),(c), and (d) show the 

effect of outdoor conditions on the performance of the base-case system. 

Figures 7-4(b) and (d) demonstrate that in the recirculation mode, both COP 

and capacity are linearly dependent on outdoor temperature and nearly linearly 

dependent on outdoor humidity. In the recirculation mode, COP and capacity 

decrease as outdoor temperature and humidity increase. Figures 7-4(a) and (c) 

demonstrate that in the ventilation mode the ambient temperature dependence of 

system performance is again nearly linear. Bowever, particularly with COP, 

the slope of the line changes with the humidity ratio, so that at low 

humidities, COP increases slightly with increases in - temperature. 

Figure 7-4(c) also demonstrates that the base-case system is mch more sensitive to outdoor humidity in the ventilation mode than in the recirculation 

mode. 

Figure 7-5 shows the effect of outdoor conditions on the high performance system. As one would expect, performance levels, particularly COP, are higher 

than for the base system- The most interesting result is that, with high 

effectiveness components, the ventilation mode exhibits better performance 

than the recirculation mode. The opposite is often true with the base system. In particular, the COP of the high-performance system in the ventilation 

mode is relatively insensitive to both outdoor temperature and humidity. 

Capacity in the ventilation mode also becomes less sensitive to outdoor conditions when the component ef fec tivenesses are increased7.4 mECT OF ImmOB CONDITIONS 

In this study, indoor conditions were varied while other conditions were held 

constant. Indoor temperatures from 23'~ to 29'~ (73'~ to 84'~) and indoor 

humidities from 0.008 to 0.012 were used. Each system was again simulated in 

ventilation and recirculation modes. Figure 7-6 shows the effect of indoor 

conditions on the performance of the base system. All four graphs in 

Figure 7-6 demonstrate a linear dependence of COP and capacity on indoor temperature and humidity, with both quantities increasing with increasing indoor 

temperature and humidity. With the base system, performance in the ventilation mode is slightly more sensitive to changes in indoor conditions than perf ormance in the recirculation mode. Under the specified operating conditions, 

. COPs are higher in the ventilation mode but capacities are higher in the 

recirculation mode. 

Figure 7-7 shows the effect of indoor conditions on COP and on the capacity of 

the high-performance system. Again, both COP and capacity are linearly dependent on indoor temperature and humidity. As one would expect, increasing component effectiveness has the effect of moving all the performance curves up. 

However, as was observed in the parametric study on the effect of outdoor conditions, the ventilation mode benefits more from increased component effectiveness than does the recirculation mode. Figures 7-7(a) and (b) demonstrate 

that, under the other nominal operating conditions listed in Table 7-2, the 

COPs in the ventilation mode are considerably higher than those in the recirculation mode. Figures 7-7(c) and (b) demonstrate that capacities are also 

higher in the ventilation mode. 




70 5 EFFECT OF REGKNgBBTIOI TMPERATmgE 

Figures 7-8(a) and (b) show the effect of regeneration temperature on COP and 

capacity, respectively, for both systems operating in both modes. Vith the 

base system, COP reaches a broad maxima between regeneration temperatures of 

70°c and 80'~. With the high-performance system, this maxima shifts toward 

lower regeneration temperatures, which offers the potential benefit of 

allowing solar collectors to operate at lower, more efficient temperatures. 

As an example of the magnitude of potential performance gains, compare performance in the ventilation mode of the base system operating at an 80'~ 

regeneration temperature with that of the high-performance system operating at 

a 60°C regeneration temperature. The cooling capacities are similar, but the 

COP is roughly doubled through the use of high-effectiveness components. With 

both systems, capacity increases monotonically with increases in regeneration 

temperature. Again, both figures demonstrate that the ventilation mode benefits more from increased component effectiveness than does the recirculation 

mode. 

70 6 EFFECT OF HEBT EXCHANGER EFFECTIVENESS 

Measured heat exchanger effectivenesses reported by the developers of desiccant cooling prototype systems range from 0.89 to 0.93, and values up to 0.95 

have been proposed. Figures 7-9(a) and (b) show the effect of heat exchanger 

effectiveness on COP and capacity, respectively, for both systems operating in 

both modes. As one would expect, performance increases monotonically with 

increasing heat exchanger effectiveness. Again, it is clear that the ventilation mode benefits more than the recirculation mode from increased component 

effectiveness. 

9 EFFECT OF REGENERATION TEMP. 

I 

? - 

EFFECT OF REGENERATION TEMP. 

21 - Base System - Vent. --- 0 High performance 0 - Recirc. I 

d 4 1 

60.0 70.0 80.0 90.0 100.0 

REGENERATION TEHP IC1 

Fig. 7-8. (a) Effect of Regeneration Temperature on COP 

(b) Effect of Regeneration Temperature on Capacity 

94 
TR-1330 snn 

a. 

EFFECT Of HEAT EXCHANGER 

b. 

EFFECT OF HEFIT EXCHANGER 

-Base System DVent. 

- --High performance 0 Recirc. 

9 

b.#- - 0.'~ 0.~93 0 .rQ6 0.'~ 

HERT EXCHANGER EFFECTIVENESS 

Base 

High 

System 

performance 

v 

0.87 0.'~ O:W 0: ss 0:~ 

HEAT EXCHANCER EFFECTIVENESS 

Fig. 7-9. (a) effect of Heat Exchanger Effectiveness on COP 

(b) Effect of Heat Exchanger Effectiveness on Capacity 

7.7 EFFECT OF EVBFOBBTIVE COOLER 1 

The evaporative cooler at the inlet of the regneration side of the system provides a cold sink for the cooling cycle which defines the coldest temperature 

that can be achieved by the conditioned air leaving the heat exchanger. One 

would expect the performance of the system to improve as this cold sink temperature decreases. Thus, one would expect increasing performance with 

increasing effectiveness of evaporative cooler 1. Figure 7-10 shows the 

effect of the effectiveness of this evaporative cooler on the performance of 

the base system. Both COP and capacity increase as effectiveness increases. 

However, the magnitude of these increases is small. Evaporative coolers in 

the prototype system already operate in the 0.8 to 0.9 effectiveness range, 

and little improvement in system performance would be gained by improving this 

component. 

7.8 SBY OP PAEUmTEIC STUDIES 

This set of parametric studies had two objectives: to investigate the behavior 

of desiccant systems under various operating conditions, and to study the 

effect of improving individual components on overall system performance. A 

part of this second objective was to provide information for an initial 

assessment of the potential for improving desiccant system performance through 

developing advanced, high-effectiveness components. 
N EFFECT OF EVAP COOLER 1 

b. 0 

EFFECT OF EVAP COOLER 1 % 8,; 

2 - C) - Vent. 

0 - Recirc. 

o - Vent. 

0 - Rec~rc. 

d ' I 

o. a 0.90 0.95 0.96 0.99 

EFFECTIVENESS OF EVAP COOLER 1 

X, 

0.87 U. 93 0.93 0.96 0.99 

EFFECTIVENESS Of EVRP COOLER 1 

Fig. 7-10. Effect of the Effectiveness of Evaporative Cooler 1 on 

Performance of the Base System 

(a) COP 

(b) Capacity 

With regard to the general operating behavior of the desiccant systems modeled 

here, COP and capacity both decrease as the temperature and humidity differences between indoor and outdoor conditions increase, as we might expect. 

An interesting result is that in most cases there is a linear dependence 

between performance and the indoor or outdoor conditions. This simplifies the 

process of developing equations describing performance maps that can be used 

in seasonal simulations of desiccant system performance. 

With regard to the benefits of developing high-performance components, several 

important results have come from the parametric studies. First, the major 

components in terms of performance are the heat exchanger and the 

dehumidifier. The effectiveness of both these components must be high to 

achieve high system performance. The studies indicate, however, that there is 

more to be gained by increasing dehumidifier performance from levels typical 

of existing prototypes. Referring to Fig. 7-9, an increase in heat exchanger 

effectiveness from 0.9 to 0.95, which is probably the reasonable upper limit, 

does not produce as large an increase in performance as using a thicker, more 

effective desiccant bed. This underscores the importance of research into 

high-performance, low-pressure-drop dehumidifier concepts. 

The second important result is that the ventilation mode is clearly superior 

to the recirculation mode when high-effectiveness components are used. The 

ventilation mode is more compatible with low-infiltration construction and 

energy conservation methods. 
TR-1330 ssn 

The third result is that using high-ef fectiveness components allows the system 

to be operated at lower regeneration temperatures. This in turn permits the 

solar collector sys tern to operate at lower, more efficient temperatures. 

SECTION 8.0 

CONCLUSIONS AND BeCUMMENDATIONS 

8.1 CONCLUSIQMS REGAILDING THE PSEUDO-STEADY-STATE HIDEL 

A computer model for the simulation of coupled heat and mass transfer in 

adiabatic desiccant beds has been developed. 

a This computer model uses a new approach in that simple effectiveness 

equations for steady-state heat and mass exchangers are used within a 

finite difference procedure. This simplifies the mathematics of the 

adsorption analysis, making the model easy to adapt to investigate a 

variety of adsorption problems. 

a The model has been validated through comparison with experimental data 

for packed beds of silica gel from SERI's Desiccant Test Laboratory and 

from other sources. 

Agreement between measured and predicted results during adiabatic adsorption is well wgthin the uncertainty in measured values. This demonstrates that the use of a lumped, gas-si.de resistance to mass transfer is 

adequate for adsorption modeling. The lumped gas-side mass transfer 

coefficient can be obtained from heat transfer correlations and an effective Lewis number that can be estimated on the basis of theory or determined experimentally for a given dehumidifier geometry. For typical 

packed-bed adsorption situations, an effective Lewis nu~nber of about 3.0 

is appropriate 

In cases of single-blow desorption, agreement between measured and predicted results is not obtained unless the effective Lewis number is 

increased substantially (by a factor of 3) from that used in adsorption. This discrepancy cannot be explained in terms of a simple diffusion model within the desiccant particles. It appears to be caused by 

a dynamic hysteresis in the adsorption/desorption characteristics of 

silica gel* 

+ Effective mass transfer coefficients for desorption can be determined 

through experiments, but further work would be necessary to determine a 

general method of predicting useful desorption coefficients for packed 

beds, particularly for rapid cycling situations. 

Three correlations for the equilibrium properties of silica gel and two 

correlations for the heat of adsorption were compared. Relatively small 

differences in predictions using the different correlations were 

observed. Of these three, the Close and Banks correlation, as simplified 

in this report (ICORR = 2), is recommended for future studies on regulardensity silica gel. 

The pseudo-steady-state model was used to generate a series of graphs 

that illustrate the physical behavior of desiccant beds in single-blow 

cases and in cyclic operation. This series of graphs facilitates a 

clearer understanding of the adsorption process and the desiccant cooling 

cycle. 
8.2 CONCLUSIONS BEGARDING COOLING SYSm PERFORMANCZ 

a The pseudo-steady-state adsorption/desorption model was incorporated into 

a computer program simulating a complete desiccant cooling system. 

a Parametric studies were carried out to characterize the effects of operating environement on system COP and cooling capacity, and to provide 

information for an initial assessment of the potential benefits of 

advanced, high-effectiveness components. 

These studies demonstrate that the thermal performance of desiccant cooling systems can be significantly increased from levels obtained by existing prototypes. A doubling of performance to the target of 1.0 to 1.2 

COP is technically feasible. The practicality of such an increase considering the restrictions on equipment size and parasitic power remains 

to be assessed. 

The ventilation mode benefits more from increases in component effectiveness than does the recirculation mode, and the ventilation mode is 

clearly superior to the recirculation mode in a high-performance system. 

a The dehumidifier and the sensible heat exchanger are the two components 

that are critical to thermal performance. Heat exchangers with an effectiveness ranging from 0.93 to 0.95 should be considered. The state of 

technology in dehumidifiers is not as advanced as that in sensible heat 

exchangers, and the greatest potential for improving system performance 

appears to be in the development of advanced, high- effectiveness, lowpressure-drop dehumidifiers. 

a The thermal performance of a desiccant cooling system varies with indoor 

and outdoor temperature and humidity. Generally, performance degrades as 

the difference between indoor and outdoor conditions becomes greater. A 

significant exception to this is that the thermal COP of a high-performance system in the ventilation mode is relatively insensitive to outdoor 

conditions. 

a The parasitic power consumption of various systems was not considered in 

this report, because it is anticipated that packed desiccant beds will 

not be appropriate for high-effectiveness dehumidifiers. Although not 

addressed in this report, parallel-passage dehumidifiers based on 

existing heat exchanger technology are expected to demonstrate 

superiority over packed-bed designs for a given pressure drop. 

The pseudo-steady-state model should be used to evaluate the potential performance of spiral-wound, parallel-passage dehumidifiers based on Australian heat 

exchanger technology. Other low-pressure-drop geometries that seem promising 

can also be assessed. Work at UCLA has indicated that, with the small 

particles that would be used in parallel passages, the solid-side resistance 

to mass transfer is small. Thus, a Lewis number near one would be appropriate 

for both adsorption and desorption. This would eliminate the uncertainty 

regarding appropriate transfer coefficients for desorption in packed beds. 
Future evaluations of advanced dehumidifiers should include detailed considerations of parasitic power and system size. This work has been proposed 

for completion at SERI during FY 1982. 

The pseudo-steady-state model can be applied to a variety of adsorption problens(.- In particular, it can be used to assess concepts for dehumidification 

of passively cooled buildings. 

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Silica Gel Used for Grain Drying." Ph. D. Thesis. Kansas State University. University Microfilms International Order No. 7802410. 1978. 

Maclaine-cross, I. L.; Banks, P. J. "Coupled Heat and Nass Transfer in 

Regenerators--Prediction Using an Analogy with Heat Transfer." Int. J. 

Heat Mass Transfer. Vol. 15; pp. 1225-1242. 1972. 

Banks, P. J. "Coupled Equilibrium Zeat and Single Adsorbate Transfer in 

Fluid Flow through a Porous Medium--I, Characteristic Potentials and 

Specific capacity Ratios. " Chemical Engineering Science. Vol. 27; 

pp. 1143-1155. 1972. 

Close, D. J.; Banks, P. J. "Coupled Equilibrium Heat and Single 

Adsorbate Transfer in Fluid Flow through a Porous Medium--11, Predictions 

for a Silica-Gel Air-Drier Using Characteristic Charts." Chemical Engineering Science. Vol. 27; pp. 1157-1169. 1974. 

Banks, P. J. "Prediction of Heat and Water Vapor Exchanger Performance - 

from that of a Similar Heat Exchanger." Compact Heat Exchangers-- 

History, Technological Advancement and Mechanical Design Problems. ASME 

I-ITD. Vol. 10; pp. 57-64. 1980.- 

Pla-Barby, F. E.; Vliet, G. C.; Panton, R. L. "2erformance of Rotary Bed 

Silica Gel Solid Desiccant Dryers." AS:4E 78-H-36. 1978 (Xay) . 
TR-1330 sea <al 

30. Holmberg, R. Be "Combined Heat and Mass Transfer in Regenerators with 

Iiygrosco;ic Materials. " Journal of Heat Transfer. Vol. 101; 

pp. 205-210. 1979 (May). 

31- Barker, J. M.; Kettleborough, C+ F. "The Adiabatic Adsorption-- 

Desorption Characteristics of Silica Gel Beds--Part 1: Theory." ASME 

80-wA/~ol-30. Also M.S. Thesis. Texas A & M University, 1979. 

32. Mathiprakasam, Be; Lavan, 2. "Performance Predictions for Adiabatic 

Desiccant Dehumidifiers Using Linear Solutions." Journal of Solar Energy 

Engineering. Vol. 102; pp. 73-79. 1980 (February). 

33. Mathiprakasam, B. "Performance Prediction of Silica Gel Desiccant Cooling System. " Ph-D. Thesis. Illinois Institute of Technology. 1979 

(December). 

34. Nienberg, J. W. "Modeling of Desiccant Performance for Solar-DesiccantEvaporative Cooling Systems." M.S. Thesis- University of California, 

Los Angeles. 1977. 

35. Undley, D. ; Heggs, P. J. "Momentum and Heat Transfer 3lechanisrns in 

Xegularly Shaped Packings." Trans. Inst. Chem. Engr. Vol. 46; 

pp. 251-264. 1968. 

36. Pesaran, A. A. "Air Dehumidification in Packed Silica Gel Beds." M.S. 

Thesis- University of California, Los Angeles. UCIA-ENG-8038. 1380 

(June). 

37. Maclaine-cross, I. L- " A Theory of Combined Heat and Mass Transfer in 

Regenerators. " Ph. D. Thesis. Monash University, Australia. 1974- 

38. Holman, J. P. Beat Transfer. McGraw-Hill Book Company. New York. 

1972. 

39. Lunde, P. J.; Kester, F. L. "Chemical and Physical Gas Adsorption in 

~inite ~ultimolecul~r Layer. " Chem. ~ng. Science. Vol. 30; 

pp. 1497-1505. 1975. 

40. Rojas, F. "Pure Vapor Adsortpion of Water on Silica Gels of Different 

Porosity." M. S. Thesis 2342. Colorado School of Mines. 1980. 

41. Jury, . He; Edwards, HI R. "The Silica Gel Water Vapor Sorption 

Them." Canadian J. Chem. Engr. Vole 49; pp. 663-666. Oct. 1979. 

42. Beecher, Be K. "Drying Agents" Encyclopedia of Chemical Technology. 

Vol. 7; pp. 378-398. 1975. 

43 Davison Silica Gels. We R. Grace and Co. Baltimore, MI44. Close, D. J. "Prediction of the Behavior of Packed Adsorbent Beds-" 

Australian National Chemical engineering Conference. 1974. pp . 241-253. 
45. ASHRAE Handbook 1977 Fundamentals. American Society of Heating, Refrigeration, and Air-Conditioning Engineers. 

46. Edwards, D. K.; Denny, V. E.; Mills, A. F. 1973. Transfer Processes. 

Holt, Rinehart and Winston, Inc., New York. 

47. Van Leersum. Personal communication. 1981 (Oct). 

48. Kutscher, C.; Barlow, R. S. "Dynamic Performance of a Packed Bed 

Dehumidifer: Experimental Results from the SERI Desiccant Test Loop." 

SERI TR/253-1429. 1981. 

49. Barlow, R.; Collier, K. "Optimizing the Performance of Desiccant Beds 

for Solar Regenerated Cooling." SERI/TP-631-1157. Presented at the 

AS/ISES Annual Conference, 26-30 May 1981, Philadelphia, PA. 
USEB'S WIDE TO COHfUTER PRoGMMS 

Three computer programs were used in this study: DESSIM, for simulation of 

single-blow cases; DESSIM 2, for simulation of s teady-state perf ornance of 

desiccant cooling systems; and DESSIM 4, for parametric studies of cooling 

systems. The core of the adsorption/desorption analysis is identical in all 

three programs. All programs are written in standard FORTRAN 4, and complete 

listings are included in Appendix B. These programs were run on the Control 

Data Corporation Cyber 720/76 computer at SERI. The first line in each 

program is specific to the CDC system and should be removed if the progran is 

to be run on other systems. Also, all graphics are based on the DISSPLA* 

graphics software package. Sections of the programs that involve graphics 

have been identified to allow for alteration or deletion if the programs are 

to be run on a system that does not support the DISSPLA package. 

The logic and equations used in the pseudo-steady-state model and the system 

analysis were described in Secs. 3.0 and 5.0, and the program listings are 

thoroughly documented. Therefore, no further discussion of program logic will 

be included in this section. 

For most simulations in cooling or dehumidification applications, 10 bed sections should be sufficient. This can be increased to 15 or 20 if improved 

resolution in graphing temperature and loading profiles is desired. Also, it 

may be advisable to use more bed sections when simulating thick desiccant 

beds. Once NBED is specified, the time step should be chosen so as to give 

RMASS = 0.3 (0.1 WSS 0.5 is reasonable). RMASS is the dry mass ratio of 

the air chunk to the bed section. 

FLOW * DT * NBED 

IWASS = AFRONT * HEIGHT * BDENS 

Computation time depends on the parameters of the simulation. On the 

Cyber 720/76, typical single-blow simulations using DESSIM required less than 

two seconds of central processor time. Typical system simulations using 

DESSIM 2 required about 8 to 10 seconds. In parametric studies using 

DESSIM 4, the computation time per steady-state point can be reduced to about 

5 to 6 seconds, because the temperature and loading profiles are retained 

between successive simulations. 

*Display Integrated Software System and Plotting Language by Integrated 

Software Systems Corporation (ISSCO). 
8-2. JOB CONTROL FILES AND INPUT DATA 

Each of the three programs has a job control file or submit file associated 

with it that initiates the job and contains input data for the specific simulation. The commands in these files are somewhat specific to the CDC system 

at SERI, and will not be outlined in detail. However, the three files are 

listed below and the input variables and their units are identified. The 

units of each variable are listed in the index of FORTRAN variables in 

Section A-3. Lines of input data in the submit file must correspond to the 

READ lines in the programs. Note that some of the input variables are one- or 

two-dimensional arrays. 

Table A-1. Submit File for DESSM 

/dl36 

STAGE,STSBD,TSO. 

ACCOUNT 

ATTACH,HEADING. 

HEADING. BARLOW 

HEADING. DESSIM 

HEADZNG. 

HEADING. 

HEADING. 

FILE(DESSiM,RT=Z) 

GETPF,DESSI&?,TY=G,ST=CNS,UN=SEl174, PN=1131001CH=252. 

ATTACH.DISSPLA. 

AfTACH,DISSPLB. 

LIERARY,DISSPLA,DISSPLB. 

FTN,i=OESSIM.GO. 

SAVEPF,PLFILE,UN=SE!174, CH=252,PN=11310O,TY=R,ST=CNS. 

EXIT. 

SAVEPF,PLFILE,UN=SE~~~~, CH=2S2,PN=113100,TY=R,ST=CNS. 

/rioseq 

/EOR 

.4i2 .035 .00193 1335, 1. 850. 921. 

40. .Ole4 60. .0167 

.208 70. .5 70. 1. 10 

/READ,DAT85A 

AFRONT, HEIGHT, D LAM, ARATIO, FRAC, BDENS , CBED 

TIN, WIN, TB@, XB@ 

FLOW, TRUN, TPRINT, ERAPH, DT, NBED 

PATM, RLEWIS, ICORR 

Name of file containing experimental data 
Table A-2. Submit File for DeSSIM2 

/308 

DESSIM2,STSBD*T100 

ACCOUNT,DUM1234. 

HEADING. BARLOW 

HEADING. DESSIM2 

HEADING. 

HEADING. 

HEADING. 

FILE(DESSIM2,RT=Z) 

GETPF,DESSfM2,TY=G,ST=CNStUN=SE1174, 

ATTACH ,31 SSP LA. 

ATTACH,DISSPLB. 

LIBRARY,DISSPLA,DISSPLB. 

FTN,I=DESSIM2.G0. 

SAV~PF,PLFILE,UN=SE~~~~, CH=~~~,PN=~~~~OO,TY=R,ST=CNS* 

EXIT. 

SAVEPF,PLFILE,UN=SE~~?~, CH=252,PN~113100,fV=R.ST=CNS. 

/NOSEQ 

/EOR 

I 1.0 .04 .00193 1335. 1. 740. 921. 

26,7 .0111 35. .014 80- 

i .5 5. 0.1 1. 1. 55. -07 10 

19 .93 .9 1 3. 3, 1 3 

AFRONT, HEIGHT, DIAM, ARATIO, FRAC, BDENS, CBED 

TROOM, WROOM, TAMB, WAMB, TREG 

FLOW, TRUN, TPRINT, TGRAPH, DT, TBP, XBg, MBED 

EC1, EHX, EC2, MIDE, RLEWIS(l), RLEWIS(2), IPLOT, ICORR 

Table A-3. Submit File for DESSIM4 

/doe 

DESSIM4,STSBD*T100 

ACCOUNT,DUM1234. 

HEADING. BAR LO^ 

HEADING. PARAMETRIC 

HEADING. 

HEADING. 

HEADING, 

FItE(DESSIM4,8T=Z) 

GETPF,DE~SIM~,TY=G,ST~CNS,UN~SE~~~~,UP~~ARL~W~PN~~~~~O~,C%=

FTN,i=DESSIM4,GO. 

EXIT. 

/NOSEQ 

/EOR 

' 1.0 a04 -00193 1335- 1.0 740. 921. 

26.7 .0111 35.0 ,014 80. 

.5 5. 1, 55. .07 10 :1 .9 .9 .9 1 3, 3. 2 

27.5 30. 32.5 35. 37-5 40. 

,008 .011 .O1'4 .017 

AFRONT, HEIGHT, DIAM, ARATIO, FRAC, BDENS, CBED 

TROOM, WROOM, TAPB, 'GJAMB, TREG 

FLOW, TRUN, DT, TB@, XBO, NBED 

EC1, EHX, EC2, KIDE, RLEWIS(l), RLEWIS(Z), ICORR 

PARAM1 (Array) 

PARAM2 (Array) 
8-3. A PARTIBL LISTING OF PORTBAN VARIABLES 

Real variables and important integer variables are listed below in alphabetical order with definitions. Corresponding text variables, if used, are 

also given. Some variables do not appear in all three programs. Integer 

variables that are used only as counters or indices are not included, nor are 

variables that are used only for graphics. None of the graphics procedures 

are documented here and the reader is referred to the DISSPLA manual for 

further information. 

FORTRAN 

VARIABLE DEFINITION 

ADFRAC 

ADS 

ADSERR 

ADSOLD 

AF RONT 

AMASS 

ARATIO 

BDENS 

BMASS 

C A 

CADS 

CAIR 

CAP 

CB 

CBED 

CC 

CMAX 

CMIN 

COP 

Cl,C2,C3 

DAREA 

Ratio of total mass of water adsorbed or desorbed to the 

total mass of dry desiccant. 

Total mass of water adsorbed or desorbed (kg). 

Error tolerance for absorbed water (fractional). 

Mass of water adsorbed or desorbed in the previous halfcycle (kg). 

Exposed ace area of desiccant bed on each side of the 5 system (m ). 

Mass of air chunk (kg). Text: Ma. 

23' Surface area per unit volume in the desiccant bed (m /m ). 

3 Density of bed material (kg/m ). Text: pb* 

Mass of single bed section (kg). Text: Mb. 

Air capacity rate used in exchanger calculations (w/OC or 

kg/s). Text: Cair. 

Heat capacity rate of the adsorption air stream (WI0C). 

Specific heat of air (J/kgOc). Text - c 

P ' 

Cooling capacity of system (kJ/kg dry air). 

Capacity rate of bed or desiccant material (w/'c or 

kg/s). Text: Cbedg 

Specific heat of the bed (J/kgOc) Text: cb* 

Ratio of CMIN/CMAX. Text: CC. 

Larger of the capacity rates CA,CB. 

Smaller of CA,CB. 

Thermal coefficient of performance of the system. 

Heat capacity rate of regeneration air stream (W/ "C) . Specific heat of liquid water (~/kg'c). Text: C,. 

Constants from Eq. 3-40. 

2 Surface area within one bed section (m ). Text: As. 
DAT 

DELH 

DHDT 

DHREG 

DPVDX 

DYDMS 

DT 

DIAM 

Dl 

D2 

D3 

EFF 

EC1 

EHX 

EC2 

ENTH 

FLOW 

FP4C 

GTXME 

a 

HAVE 

HE AT 

Two-dimensional input array containing experimental data 

for graphics. 

Enthalpy change of air passing through the dehumidifier 

(kJ/kg dry air). 

Enthalpy difference between room air and delivered air 

(k~/kg dry air). 

In-line function for the specific heat of moist air 

(~lkgOc1 

Enthalpy increase of regeneration air due to solar heat 

input (kJ/kg dry air). 

Derivative of equilibrium vapor prgssure with respect to 

"=ve desiccant loading fraction. Text; - . 3% 

Derivative of mass fraction in desiccant with respect to 

mass fraction in air. Text: aY/amST . Timestep(s). Text: At. 

Particle diameter (m). Text: Dp. 

Array for experimental data. Contains time (minutes). 

Array for experimental data. Contains temperature (OC). 

Array for experimental data. Contains humidity ratio 

(kg/kg) 

Effectiveness of exchange process* 

Effectiveness of evaporative cooler 1. Text: Eel. 

Effectiveness of heat exchanger. Text : %, . Effectiveness of evaporative cooler 2. Text: Ec2. 

In-line function for the enthalpy of moist air (J/kg). 

Text: ha. 

Total flow rate of dry air in each process stream (kg/s). 

Mass fraction of desiccant in bed. (Equals 1.0 for packed 

bed. ) 

2 Mass transfer coefficient (kg/rn s). Text: g. 

2 Mass flow rate of dry air per unit face area (kg/m s) . Text: Ga. 

Three-dimensional array for storage of temperature and 

loading profiles in the bed. 

Elapse time clock- Reset each time that temperature and 

loading profiles are stored. 

Heat transfer coefficient (w/m2 OC) . Text: 8. 

Average enthalpy of outlet air (kJ/kg dry air). 

Thermal energy transferred to air chunk in heat transfer 

process (J). Text: Q. 
HEIGHT 

HROOM 

HSEC 

HSHV 

HSUM 

HVAP 

ICORR 

IDATA 

IPLOT 

NBED 

NCYCLE 

NPASS 

OUT1 

OUT2 

OUT3 

OUT4 

OUT5 

PARAMl 

PAW2 

PATM 

PS 

PSAT 

PTIME 

QEXCH 

QREGEN 

RH 

RK 

KLEWIS 

RMAS S 

Total thickness of desiccant bed (m). Text: L. 

Enthalpy of room air (kJ/kg dry air). 

Thickness of one bed section (m). 

Ratio of heat of adsorption to heat of vaporization. 

Text: hads/hvap. 

Sum used to calculate HAVE. 

Heat of vaporization of water (Jlkg). Text: hvapa 

Correlation number. 

Number of experimental data points to be plotted. 

1 - Plotter on. 0 - Plotter off. 

Number of bed sections. 

Number of half-cycles. 

Number of air chunks to be sent through the bed. Same as 

total number of time steps. 

Array of outlet conditions. Time (minutes). 

Array of outlet conditions. Temperature (OC) . Array of outlet conditions. Humidity ratio (kglkg). 

Array of outlet conditions. Relative humidity. 

Array of outlet conditions. Enthalpy (kJ/kg). 

Array for parametric studies. 

Array for parametric studies. 

2 Ambient pressure (N/m ). Text: Patme 

In-line function for saturation pressure. 

2 Saturation vapor pressure of water in air (N/m ). Text: 

'sat 

Elapse time clock. Beset each time outlet air conditions 

are stored for printing or graphics. 

2 Equilibrium vapor pressure (Nlm ). Text: Pve. 

Heat transfer rate in system heat exchanger. Text: 

Rate of heat addition from solar. Text: Qreg. 

Relative humidity. Text: iiH. 

Thermal conductivity of air (w/mOc). Text: k. 

Effective Lewis number. Text: Le. 

Ratio of mass of air chunk to mass of bed section. Gives 

indication of appropriate match of time and space 

increments. (0.1 < WSS < 0.5 is advised.) 

?lass fraction of water vapor in air before mass transfer 

calculation. Text: male 
RMU 

RNTU 

TGMB 

TAVE 

TA1 

TBED 

TBINT 

TBO 

TB 1 

T GRAPH 

TREG 

TROOM 

TRUN 

TWB 

WATER 

WAMB 

WAVE 

WAT 

Nass fraction of water vapor in air after mass transfer 

calculation. Text: ma2. 

Mass Fraction of water vapor in air in equilibrium with the 

desiccant surface. Text: as. 

Dynamic viscosity of air (kg/ms). Text: p . Number of transfer units. Text: Ntu. 

Ambient temperature ( OC) . Average outlet temperature ('c) . Temperature of air chunk before heat transfer calculation 

(Oc) 

Temperature of air chunk after heat transfer calculation 

(Oc) 

Array of bed section temperatures. 

Bed sectyn temperature after the energy balance (OC). 

Text: Tb .; *t 

Initial temperature of bed (OC). 

Temperature of bed section before energy balance (OC). 

Text: Tbl. 

Temperature of bed section after heat transfer calculation 

('c). Text: TbZ* 

Time interval at which temperature and loading profiles in 

the bed are stored for printing/graphing (minutes). 

Elapse time clock for complete adsorption or desorption 

process (seconds). 

Temperature of inlet air (OC). 

Time interval at which outlet air states are stored for 

printing/graphics (minutes). 

Regeneration temperature for cooling system (OC) . Room temperature (OC) . Total time for adsorption or desorption (minutes). 

Wet bulb temperature (OC). Text: T*. 

Mass of water transferred from air chunk to bed section 

(kg). Text: Mw. 

Ambient temperature (OC) . Average outlet humidity from dehumidifier wheel (kgjkg). 

Humidity ratio of air chunk before mass transfer 

calculation (kg/kg) . Text: wale 

Humidity ratio of air chunk after mass transfer calculation 

(kg/kg) . Text: wa2 

Humidity ratio of inlet air (kg/kg) . 
WROOM 

WSTAR 

WSUM 

XBED 

XBO 

XBl 

Room humidity (kg/kgle 

Room ratio humidity for a given wet bulb temperature 

(kg/kg) 

Sum used to calculate WAVE. 

Array of moisture ratios in bed section (kg/kg). 

Initial moisture ratio of the desiccant (kg/kg). 

Moisture ratio of desiccant section before mass transfer 

calculation (kg/kg) . Text: Xbl 

Moisture ratio of desiccant section after mass transfer 

calculation (kg/kg) . Text : Xb2 
APPENDIX B 

PROGRAM LISTINGS 

PROGRAM DESSIM(INPUT,OUTPUT,TAPES~IN~UT~~APE~~OUTPUT~PLFI~E) 

C 

C ****************************************************** 

C * * 

C * DESSIM: SIMULATION OF SILICA GEL BEDS * 

C * R. BARLOW, SERI, DECEMBER 1900 * 

C * * 

C *******************+************************************** 

C 

C 

C THIS VERSION OF THE DESSIM PRCGRAM IS DESIGNED TO 

C SIMULATE SINGLE BLOW ADSORPTION OR DESORPTXON IN A SILICA 

C GEL PACKED 9ED WITH UNSFORM INITIAL CONDITIONS OF MOISTURE 

C CONTENT AND TEMPERATURE, AND C3NSTANT INLET AIR CONDITIONS. 

C 

DIMENSION TBED(~O),X~ED(SQ)~GRAPH(SO~~O~~), 

~OUT~(~OO),~UT~(~QO),~UT~(~OO)~OUT~(~~~),OUT~(~OO~, 

~x(~Q~),Y(~o~)~DAT(~~~o)~D~(~~),~~(~O)~~~(S~) 

C 

C XPItTIALIZE DISSPLA GRAPHICS 

CALL COMPRS 

C 

C DEFINE CONSTANTS IN S1 UNITS 

CAIR=1006. 

CWATERr4181. 

C 

C REAO DATA. NOTE THAT DAT IS A TWO DIMENSIONAL DATA ARRAY. 

i?EAD(S,*) AFRONT,HEIGHT,D~AM,ARATIO,~~AC+BDENS,CBE~ 

READ(5,*) TIN,WIN,TBO,XBO 

READ(S,*) 'FtOW,TRUN,fPRINT,fGRAPH,DT,NBED 

READ(5,*) PATM,RLEWIS,ICORR 

REA0(5,*) IDATA 

READ(S,*) OAT 

C 

C SET UP ARRAYS FOR GRAPHING EXPERIMENTAL DATA 

IF (1DATA.EO.O) GO TO 11 

DO 13 d=I+IDATA 

Ot(J)=DAT(2,J) 

D2(J)=DAT(3, J) 

DB(J)aOAf(4,J) 

Id CONTINUE 

C 

C SET UP PARAMETEaS FOR SIMULATION 

ti i-tSEC=HEIGHT/FLoAT(NaEO) 

BMASS=HSEC*AFRONT*BDENS 

OAREA=HSEC*AFRONT*ARATIO 

AMASS=FLOW*DT 

NPASS=INT(TRUN*BO./DT) 

TIME10 

PTIWE=O. 

GTIME-0. 

ADS=O. 

i(H='O 

NN= I 

RMASS=AMASS/BMASS 

C 

C fNITIALIZE TEgPERATURE AND WATER CONTENT IN THE BED 
C- HE~T TRANSFER COEFFICIENT FROM HADLEY AND HEGGS CORRELATION. 

C MASS TRANSFER COEFFICIENT IS CALCULATED USING AN EFFECTIVE 

C VALUE FOR THE LEWIS NUMBER THAT ACCOUNTS FOR THE RESISTANCE 

C TO DIFFUSION OF WATER WITHIN THE SOLID DESICCANT. 

1.5 GA=FLOW/AFRONT 

RK=.02624+7.58E-5*(.TIN-27.) 

RMU=1.859E-5+4.32E-B*(TINN27.) 

H=.58+RK*(DIAM*GA/RMU)**.67/DIAM 

G=H/(RLEWiS*CAIR) 

C 

C MAIN CALCULATION LOOP BEGINS. NPASS IS THE NUMBER OF TIME 

C STEPS IN THE COklPLETE PROCESS AND THE NUMBER OF AIR CHUNHS 

C THAT MUST BE SENT THROUGH THE BED. TO SIMULATE VARIABLE INLET 

C AIR CONDITIONS, TIN AND WIN CAN BE MADE FUNCTIONS OF TIME. 

DO 46 N=I,NPASS 

WAI =WIN 

TAlrTIN 

C 

C ONE CHUNK CF AIR IS PASSED COMPLETELY THRU THE BED. 

C AS THE AIR IS EXPOSED TO EACH BED SECTION, CALCULATIONS ARE 

C CARRIED OUT AS FOLLOWS: 1) MASS TRANSFER CALCULATION, 

C 2) ENERGY BALANCE TO ACCOUNT FOR THE HEAT OF ADSORPTION 

C 3) HEAT TRANSFER CALCULATION BETWEEN THE BED AND THE AIR. 

DO 40 1 91, NBED 

TBI =TOED( I) 

XBl =XBED( I) 

C 

C MASS TRANSFER CALCULATION: COUNTER-FLOW EXCHANGER METHOD. 

C THE AMOUNT OF WATER TRANSFERED IN A SINGLE TIME STEP IS 

C CALCULATED USING EQUATIONS ANALOGOUS TO THOSE FOR A 

C STEADY STATE COUNTER-FLOW HEAT EXCHANGER. THE QUANTITY 

C "DYDMS" IS THE PARTIAL DERIVATIVE OF THE DESICCANT LOADING 

C FRACTION WITH RESPECT TO THE EQUILIBRIUM MASS FRACTION 

C OF HATER IN THE AIR AT THE iNTERF4CE. THIS IS ANALOGOUS TO 

C THE SPECIFIC HEAT IN iHE HEAT TRANSFER PROSLEM AND REPLACES 

C THE INVERSE OF HENRY CONSTANT USED IN GAS-LIQUID MASS EXCHANGE 

C PROBLEFIIS. 

PSAT=PS(TBI ) 

CALL PROPS(ICORR,X8l,TBl,PSAT,PVE,HSHV) 

RMS=.622*PVE/(PATM-.378*PVE) 

RMAI=WAl/(l.+WAl) 

CA=AMASS*(l.+WAl)/DT 

CALL DERIV(ICORR,XBl,fBl,R?1S,HSHV,PATM,PSAT,DYDMS) 

CB=FRAC*BMASS*(l+XBl)*OYDMS/DT 

CMIN=AhIINl (CA,CB) 

CMAX=AMAXl (CA,CB) 

CC=CMIN/CMAX 

RNTU=G*DAREA/CNIIN 

EFF=(l.-EXP(-RNTU*(l.-CC)))/(l.-CC*EXP(-RNTU*(l.-CC))) 

RMA2=R~flAI-EFF*(RMAl-RMS) 

WA2=RMAZ/(l.-RMA2) 

WATER=AMASS+(WAl-WA2) 

XB2=(XBI*FRAC*BMASS+WATER)/(FRAC*BMASS) 

C 

C ENERGY BALANCE 

C AN INTERMEDIATE TEMPERATURE IS CALCULATED FOR THE BED SECTION WHILE THE 

C AIR IS ASSUMED TO REMAIN AT ITS INITIAL TEMPERATURE. THE DIFFERENCE 

C BETWEEN THE HEAT OF ADSORPTION AND THE HEAT OF VAPORIZATION IS 

C ACCOUNTED FOR. HSHV IS THE RATIO OF THE HEAT OF ADSORPTION TO 

C THE HEAT OF VAPORIZATION AND IS RETURNED BY SUBROUTINE PROPS. 

HVAP=2358500.-2460.*(TBl-60.) 

TBINT=(TBl*BMASS*(CBED+FRAC*XB1*CYATER) 

1 +AMASS*(ENTH(TAI , wAI ) -EFITH(TAf ,!JA2) )+WATER*HVAP* 

2 (HSHV-l.))/(BMASS*tCBED+FRAC*XBZ=CWATER)) 

C 

C HEAT TRANSFER CALCULATION: 

C THE MODZL ASSUMES THAT THE FINAL TEMPERATURES OF THE AIR CHUNK 

2 AND THE BED SECTION AT THE END OF THE TIME STEP ARE THE SAME AS 

C THE STEADY STkiE OUTLET TEMPERATURES FROM A SIMPLE COUNTER FLOW 

C HEAT EXCHANGER THAT HAS STEADY FLOWS OF AIR AND DESICCANT MATERIAL 

C WITH INLET CONDITICNS EQUAL TO THE INITIAL CONDITIONS OF ThE AIR 

C CHUNK AND THE BED SECTION. THE EFFECTIVENESS OF THIS HEAT 

C EXCHANGE PROCESS IS DETERMINE3 BY THE dEAT TRANSFER COEFFICIENT, 

C THE TOTAL SURFACE AREA iK THE BED SECTION, AND THE HEAT CAPACITY 

C RATES OF THE AIR AK3 BED rd1ATERIAL. 

116 
CA=AMASS*DkIDT(TAl,WA2)/OT 

CB= BLIASS* (CSEU+X82* FRAC*CWATER) /DT 

CMIN=AMINl(CA,CB) 

C?dAX=AMAXl (CAICB) 

CC=CM IN/CMAX 

RNTU=H*OAREA/CMEN 

€FF=(l.-EXP(-RNTU*(1.-CC)))/(I.-CC*EXP(-RNTU*(l.-CC))) 

HEAT=EFF*CMIN*fTBZ-TAl)*DT 

TA~=TA~+HEAT/(DHDT(TA~,wA~)*AMASS) 

T62=TEINT-HEAT/(BMASS*(CBEO+FRAC*XB~*CWATER)) 

ADS=ADS+WATER 

TBtG(I)*TB2 

XBED(I)=X62 

WAI =MA2 

TAf =TA2 

40 CONTINUE 

C AN AIR CHUNg LEAVES THE BED AT THIS POINT. THIS CORRESPONOS TO 

c ONE TIrhE STEP IN THE OVERALL SIMULATION. 

C 

C ADVANCE THE CLOCKS. 

TXME=TIME+Df 

PTIMEzPT IblE+DT 

GTIME=GT IMEiDT 

IF (N.EQ.l) GO TO 45 

C 

C OUTLET CONDITIONS ARE STORED AT PTfME TIME INCREMENTS. 

IF (ABS(PTI~~E/GO.-TPRIN~).LT.~.E-~) GO TO 43 

GO T0 44 

43 NN=NN+t 

Pf IME=O. 

45 PSAT=PS(TA2) 

OUT1 (NN)=TIME/GO. 

OUTZ(NN)=TA2 

OUT3{NN)=WA2 

OUT4(NN)=PATM*WA2/((.622+WA2)*PSAT) 

OUT5(NN)=ENTH~TA2,WAZ)/IOOO. 

C 

C TEMPERATURE AND LOADING PROFILES IN THE BED ARE STORED AT 

C GTIME TIME INCREMENTS. 

44 IF (ABS(G1 IME/6O.-TGRAPH). LT. 1 .E-6) GO TO 44 

GO TO 46 

41 KK=KK+l 

GTIME=O. 

00 42 I=1,N8ED 

GRAPH(I,KK,t)=TBED(I) 

42 GRAPH(I,KK,Z)=XBED(I) 

IF (TIME.EO*O.) GO TO 13 

46 CONTINUE 

C THE MAIN CALCULATION LOOPS SACK FROM HERE TO SEND ANOTHER AXA 

C CHUNK THROUGH THE BED. 

C 

ADFRAC=ADS/(FRAC*SMASS*FLOAT(NB€D)) 

C 

C PRINT RESULTS 

WRITE(6,lOO) AFRONT,HEIGHT,DIAM,ARATIO,FRAC,~OENS~CBED, 

ITIN,WIN,TBO,XBO,FLO~J,TRUN~DT,NBEO~PA~M~R~E~IS~~MASS~~CORR 

WRITE(6,lOf)ADS,ADFRAC 

DO 51 I=1 ,NN 

54 WRITE(6.102) OU~~(~),OUT~(I),~~T~(~)~OU~~(~),QU~S(~I 

WRITE(6,103) 

DO 52 L=1 , KK 

TG=TGRAPH*FLOAT(L-1) 

WRIIE(6?1Q4) TG 

00 52 1st ,NBED 

52 kiRITE(6?105) ~,GRAPH(I,L,~),GRAPH(~,L*~) 

C 

C BEGIN PLOTTING ROUTINES USING DISSPLA 

STEP=I . IF (TRUN.GE.10.) STEP=2. 

IF (TRUN.GE.20.) STEP=10. 

IF (TF?I~N.GT.I~O.) STEF=30. 

IF (fRUM.GT.300.) SZEP.60. 

If (TRUN.GT.GOC.) STEP=t20. 

IF (TRUN.GT.909.) STEP=240. 

CALL TITtE{"OUTLET AIR TEMPERATURE (C)"9*22* 

1 "TIME (MINUTES)",l4,*TEMPERATURE (C)"+j5rS.,3-5) 

117 
CALL X~NTAX 

CALL YTICKS(2) 

CALL GRkF(O.,STEP,TRUN,20.,20.,100.) 

CALL CURVE(OUTl,CUT2,NN,O) 

IF (IDATA.GT.0) CALL CURVE(Dl,DZ,IDATA,-1) 

CALL FRAME 

CALL RLVEC(0. ,TIN,TRUN,TIP1,1202) 

CALL ENDPL(0) 

CALL TITLE("0UTLET AIR HUMIDITY',-19,'TIME (MINUTES)',14, 

1 "HUIIDITY (KG/KG)",16.5.,3.5) 

CALL YTICKS(5) 

CALL GRAF(O.,STEP,TRUN,O.r.01,.03) 

CALL CURVE(OUTl,OUT3,NN,O) 

IF (1DATA.GT.O) CALL CURVE(Dl,D3,1DATA,-1) 

CALL FRAME 

CALL RLVEC(O.,WIN,TRUN,WIN,1202) 

CALL ENDPL(0) 

CALL TITLE("DES1CCANT TEMP. PROFILESa+-24, 

1 "BED LOCATION",12,UTEMPERATURE (C)",15,5.,3.56) 

CALL YTICKS(2) 

RNBED=FiOAT( NEED) 

CALL GRAF(l.,1.,RNBED,20.,20.,100.) 

CALL FRAME 

DO 56 1=1 ,KK 

DO 55 K=l,NBED 

Y(K)=GHAPH(K,I,l) 

X(K)=FLOAT(K) 

CALL CLIRVE(X,Y ,NBED.O) 

CALL RLVEC(l.rTIN,RNBED,TIN,1202) 

START=FLOAT(NBED/2-NBED/lO) 

FINISH=FLOAT(NBED/2+NeED/lO) 

CALL RLVEC(START,93.,FINISH,93.,1501) 

CALL ENDPL(0) 

CALL TITLE("LOAD1NG PROFILESY,-16, 

1 "BED LOCATION",12,"WATER CONTENT (KG/KG)',21,5.,3.56) 

CALL YTICKS( I) 

CALL GRAF(l.,l-,RNBED,O.,.1,.4) 

CALL FRAME 

DO 58 I=l.KK 

DO 57 K=l ,NEED 

Y(K)=GRAPH(K,I,Z) 

X(K)=iLOAT(K) 

CALL CURVE(X,Y,NBED,G) 

CALL RLVEC(START,.35,FINISH,.35~1501) 

CALL ENDPL(0) 

CALL TITLE("PSYCHROMETR1C CHARTn,-19, 

1 "DRY BULB TEMPERATURE (C)",24, 

2 UHUMIDITY RATIO (KG/KG)",22,5.,3.5) 

CALL XTICKS( 1 ) 

CALL YTICKS(5) 

CALL GRAF(10.,10.,100 .,0.,.01,.03) 

CALL BLNK1(0.,5.,3.5,5.,0) 

CALL FRAME 

CALL CURVE(OUT2,0UT3,NN,O) 

IF (IDATA.GT.0) CALL CURVE(D2,D3,IDATA,-1) 

DO 71 1=1 ,10 

RH=.OI*FLOAT(I) 

NP=O 

DO 70 1T=10,100 

NP=NP+l 

X(NP)=FLOAT( IT) 

TCB=X(NP)+273. 

PSAT=EXP(23.28199-3780.82/TDB-225805./TDB**2) 

Y(NP)=.622*RH*PSAT/(PATM-RH*PSAT) 

IF (Y(NP).GT..040) Y(NP)=.03 

CALL CURVE(X,Y ,NP,O) 

CONTINUE 

DO 73 1=2,10 

RHnFLOAT (1)t.l 

NP=O 

DO 72 IT=10,65 

NP=NP+l 

X(NP)=FLOAT( IT) 

TDB=FLOAT(IT)+273. 

P~~~=~XP(23.28199-3780.82/TD8-225805~/fD6**2) 

Y(NP)=.622*RH*PSAT/(PATM-RH*PSAT) 

118 
72 IF ((Y(NP),GE..O35).9R.(Y(NP).LT.O.)) Y(NP)-.O3 

CALL CURVE(X,Y,NP,Q) 

73 CONTINUE 

CALL ENDPL(O) 

CALL DONEPL 

STOP 

100 FORMAT("I~,////,IX,~SHBEO PARAMETERS:rlOX+ 

122HFRONTAL AREA (M2) =,F6*49 

1/,26X,22HBED THICKNESS (M) =,F6.4* 

2/,26X,22HPARTTCLE DIAMETER (M)+,F7.5, 

2/,28X922HSURFACE AREA (M2/?43) t+f6*0, 

3/,26X,22HDESICCANT FRACTION ~~F5.3, 

4/,26Xe22HBED DENSITY (KG/M3) ~vF5.01 

S/,~~X,~~HSPECIFIC HEAT (J/KG) trF6.0, 

6//,1X,19HCONDITIONS FOR RUN:,GX,22HINLET AIR TEMP. (C) =,PS.l, 

7/,26Xt22H1NLET HUMIDITY(KG/KG)s,F6,SI 

8/,26Xt22HZNfT1AL BED TEMP* (C)=,F5.1, 

9/,26Xt22H1NfTfAL BED LOADING mtF5.3, 

1/,26X,22HFtOW RATE (KG/S) arF5.38 

2/,26X,22HCENGTH OF RUN (MIN) =,F4.0, 

3/,26X,22HTIME STEP (5) n,F3.09 

4/,26X922HNO. OF &ED SECTIONS =,I3, 

5//,26Xt22HAM0IENT PRESSURE ~~F7.0, 

6/,26X,22HtEWIS NUMBER r,F5=3* 

7/,26x,22HM,AIR/M*BED leF5.3, 

8/,26X922HSILICA GEL CORR. NO* =pI2) 

101 FORMAT(,////,1X918H~AfE~ CYCLED (KG)+rF8+5, 

25X,23HFRACTION OF BED CYCLED-,F6.4, 

4 /////,lX,IBHOUTLET CONDITIONS:,ZX, 

5 10HTIPhE (MIN),tOX,8HTOUT (C),9XV12HWOUT (KG/KG),11X,4HROUTt 

6 6X,"ENTHALPY (KJ/KG)" ,/) 

102 FORM&T(~OX,F~O.~,~~X,F~.~,~OX,~~O*~~~OX~F~-~P~~X*~~*~) 

1C3 FORMAT("1",////91X,36HTEMPERATURE AND LOADING PROFILES AT , 123HTGRAPH TIME INCRE~~ENTS:,//) 

104 FGRMAT(//,!x,~HTXME=,F~.~,~X~~H MIN.,//*IIX*~HNBEDI~~X, 

1 lCHTEf17P (C) ;9X17H~OADING9/) 

105 FCRh4AT(12X,I2,10X,F1OO2, 10X,F10-5) 

END 

C 

C FUNCTION FOR SATURATION PRESSURE AS A FUNCTION OF TEMPERATURE 

C CORRELATION FROM MACLAINE-CROSS THESIS 

FUNCTION PS(T) 

TK=T+273. 

~~=~~~t23.28199-3780.82/TK-225805./fK**2) 

RETURN 

END 

C 

C FUNCTION FOR ENTHALPY FROM TEMPERATURE AND HUMIDfTY 

C FROM hlACL.AINE-CROSS THESIS 

FUNCTlOd ENTH(T,W) 

ENTH=(10~5~22+.02615*~)*~+W*(2500800~~~868~*~) 

RETURN 

END 

C 

C FUNCTION FOR THE SPECIFIC HEAT OF AIR 

FUNCTION DHDT(T,W) 

DHDT=1005.22+.0523+T+1868.*W 

RETURN 

END 

C 

C 

C SUBROUTfNE FOR THE EQUILIBRIUM PRCJPERTIES OF REGULAR DENSITY 

C SILICA GEL. CORRELATIONS BASED ON EXPERIflIENTAL DATA ARE USED 

C TO CALCULATE THE EQUILISRIUPA VAPCR PRESSURE AT THE DESICCANT 

C SURFACE AND TO CALCULATE THE RATIO OF THE HEAT OF ADSORPTION 

C TO THE HEAT OF VAPORIZATION. THREE COARELATXONS ARE INCLUDED, 

C AND THE PASSED INTEGER "ICORR' DETERVINES WHICH ONE IS USED* 

C 

C ICORR=1 BULLOCK AND THRELKELD FIT TO HUBARDtS DATA 

C AND CLOSE AND BANKS EONS FOR HADS/HVAP* 

C 

C XCORRt2 CLOSE AND BANKS FIT TO HUBARD'S DATA. 

C F(X)=2.009*X AND LINEAR EONS FOR HADS/HVAP ARE USED. 

C 

C ICORR=3 FIT TO DATA OF F. RCJAS FOR DAVISON PA-40 

C SILICA GEL, LINEAR EQNS FOR HADS/HVAP. 
C 

SUBROUTINE PROPS(ICORR,X,TC,PSAT.PVE,HSHV) 

GO TO (10,30,40) ICORR 

C 

C ICORR-1 

C 

10 T=TC*1.8+32. 

IF(X.GT..OS) GO TO 11 

PVE=((((4.02263E-4*X+1.186214E-5)*T-8.938272E-2* 

lX-3.267901E-3)*T+7.068827*X+.322929)*T~l82.1523*X~ 

210.41436)*X 

GO TO 17 

1 IF (X.GT..I) GO TO 12 

PVE=(((-7.808642E-6*X+1.989198E-6)*T+4.312037E-3*X1 6.024537E-4)*T-.484787*X+.0580S8)*T+17.20448*X-1~836323 

GO TO 17 

12 IF (X.GT..lS) GO TO 13 

PVE=(((2.083333E-5*X-8.75E-7)*T-3.825E-3*X+2.1125E-4)*T 

1+.255417*X-.015963)*T-4.68S5*X+.352375 

GO TO 17 

13 IF (X.GT..2) GO TO 14 

PVE=(((5.333333€-5*~-5.75E-6)*T-1.38€-2*X+l.7075E-3) 

l*T+1.264657*X-.16735)*T-38.*X+5-35 

GO TO 17 

14 IF (X.GT..25) GO TO 15 

P~Er(((-8.166667E-5*X+2.125E-5)*f+2.135E-Z*X-5.322~€-3~ 

1*T-1.752333*X+.43605)*T+47.6*X-11e77 

GO TO 17 

t5 IF (X,GT..3) GO TO 16 

PVE=(((4.E-5*X-9.16667E-6)*T-8.1E-3*X+2.04€-3) 

l*T+.599*X-.1517831*T-l4.1*X+3.6S5 

GO TO 17 

16 PVE=(((2.E-5*X-3,166667E-6)*T-3*X+7.2E-4) 

l*T+.231*X-.059583)*T-6.94Xf1.495 

17 PVE=PVE*101325./29.92 

IF (X.GT..OJ) GO TO 21 

HSHV=6533.*X**3-542.rX*X+ll.79*X+11155? 

GO TO 5G 

21 IF (X.GTa.1) GO TO 22 

HSHV=45.4*X*X-8.97*X+1.5922 

GO TO 50 

22 HSHV=-9.1553*X**3+7.048*X*X-1.8966*X+l.2?89 

GO TO 50 

C 

C ICORR=2 

C 

30 IF (X.GT..l) GO TO 31 

HSHV=1.3-1.75*X 

GO TO 32 

31 HSHV=l.f4-.15*X 

32 PVE=(101325./29.91)*(29.91*2.009*X*PSAT/lO1325.)**HSHV 

GO TO 50 

C 

C ICORR.3 

C 

40 IF (X.GT..l) GO TO 41 

HSHV=1.3-1.75*X 

GO TO 42 

41 HSHV-1 .14-. 15*X 

42 R=(.616238*X+l6.7916*~*~-74.34228*X**3+116.6834*X**4) 

1 /(I.-(TC-40.)/300.) 

PVE=R*PSAT 

50 RETURN 

END 

L 

C 

C 

C SUBROUTINE FOR CALCULATING THE PARTIAL DERIVATIVE OF THE MASS 

C FRACTION 3F WATER IN THE DESICCANT WITH RESPECT TO THE MASS 
C FRACTION OF WATER IN THE AIR AT EQUILI8RIUM. THREE CORRELATIONS 

C ARE INCLUOED, AND THE PASSED INTEGER "XCORRn DETERMINES WHfCH 

C CORRELATION IS USED. 

C DERIVATIVES OF THE EQUATIONS GIVEN IN SUBROUTINE PROPS ARE USED. 

C 

SUBROUTINE DERIV(ICORR,X,TC,RMS,HSHV,PATM,PSAT,OYOMS) 

GO TO (10,20,30) ICORR 

C 

C ICORR=1 

C 

10 T=TC*1 .8+32. 

IF (X.GT..05) GO TO 11 

DPVD~=(((8.04$3E-4*~+11.862E-6)*T-.17876*X+32.679€-4)*1 

1 +14.138*X+.32293)*T-364.34*Xa10*414 

GO TO 50 

11 IF (X.GT..l) GO TO 12 

CPVDX=((-7.80S6E-S+T+43.12E-4)*T-.48479)*T+17.204 

GO TO 50 

12 IF (X.GT..lS) GO TO 13 

OPVO~s((20.833E*6*T-38.25E'4)*Tf2.5542)*T~4.6825 

GO TO 50 

93 IF (X,GT..2) GO TO 14 

DPVOX=((S3.333E-6*T-.0138)*T+t.2647)*f-38. 

GO TO 50 

14 IF (X.GT..ZS) GO TO 15 

OP~~~=((-01.667~-6*f+,O2135)*T-1.7523)*T+47.6 

GO TO SO 

15 IF (X.GT6.3) GO TO 16 

DPVDXt((4.E-S*T-8l.E-4)*T+,S99)*f't4.1 

GO TO 50 

16 DPVDX=((~.E-S*T-~?.E-~)*T+.~~?)*T~.~ 

GO TO 50 

C 

C ICQRR=2 

C 

20 C1=3388. 

C2=5,93Em4*PSAT 

C3=-1.75 

IF (X.GT..I) C3=-.I5 

DPVDX=C~*(C~*HSHV*(C~*X)**(HSHV--~~)+C~*(C~*X)**HSHV*A~OG(C~*X)) 

GO TO 50 

C 

C ICORR=3 

C 

30 DPVOXmPSAT*(.616238+33.5832*X-223.027*%*X+466.734*X**3) 

1 /(I .-(TC-40.)/300.) 

50 DYDMS=.~~~*PATM/((~.+X)**~*(.~~~+.~~~*RMS')*+~*DPVDX) 

RETGRN 

END 
TR-1330 

sca 3 

PROGRAM DESSIM~(INPUT,OUTPUT,TAPE~=~NPUT,TAPE~=OUTPUT,PL~ILE) 

C 

C ......................................................... C * * 

C * DESSIM2: SIMULATIONOF SILICA GELCOOLINGSYSTEMS * 

C * R. BARLOW, SERI, DECEMBER 1980 * 

C * * 

C ......................................................... C 

C THIS VERSION OF THE DESSIM PROGRAM SIbYdLATES THE STEADY 

C STATE PERFORMANCE OF A COMPLETE DESICCANT COOLING SYSTEM 

C COMPOSED OF A ROTARY DEHUMIDIFIER, A REGENERATIVE SENSIBLE 

C HEAT EXCHANGER, AND TWO EVAPORATIVE COOLERS. PROPERTIES OF 

C MEDIUM DENSITY SILICA GEL ARE USED. OPERATION OF THE 

C DEHUMIDIFIER IS ASSUMED TO BE ADIABATIC. THE HEAT AND MASS 

c TRANSFER PROCESSES IN THE DEHUMIDIF:ER ARE MODELED aY USING 

C PSUEDO-STEADY-STATE CALCULATIONS BASED ON THE EFFECTIVENESSC NTU METHOD FOR COUNTER-FLOW HEAT OR MASS EXCHANGERS. 

C THIS VERSION OF THE DESSIM PROGRAM INCLUDES EXTENSIVE GRAPHICS 

C CAPABILITY THAT USES THE "DISSPLA" GRAPHICS SOFTWARE PACKAGE. 

C 

C 

DIMENSION T~ED(~O),XBED(~O),TIN(~)~WIN(~),RLEWIS(~), 

~OUT~(~OC),OUT~(~OO),OUT~(~~~),OU~~(~~~)~O

~X(~OI),Y(~O:),TPA(~~~~,WPA(~~~).TPR(~~~),WPR(~OO)~T(~)~W(~),HS

LOGICAL FLAG 

C 

C INITIALIZE DISSPLA GRAPHICS PACKAGE 

CALL COMPRS 

C 

C DEFINE CONSTANTS IN Sf UNITS 

PATM= 1 0 1325. 

CAIR=lOO6. 

CWATER=4181. 

ADSOLD=O. 

NCYCLE'l 

Id= 1 

ADSERR=.OOI 

FLAG*. FALSE. 

C 

C READ DATA. NOTE THAT SOME OF THE INPUT VARIAaLES ARE ARRAYS. 

READ(5.*) AFRONT,HEIGHT,DIAM,ARATIO,FRAC,BDENS,C6ED 

READ(5,*) TROOM.WRCOM,TAMB,WARlB,TREG 

READ(S,*) FLOW,TRUN,TPRINT.TGRAPH,DT,TBO,XBO,NBED 

READ(S,*) ECl,EHX,EC2,MODE,RiEWXS,IPLOT,ICORR 

C 

C INITIALIZE TEMPERATURE AND WATER CONTENT OF DESICCANT BED. 

DO 1 I=l,NBED 

TBED(I)=TBO 

1 XBED( I ) =XBO 

C 

C DEFINE KNOkN STATE POINTS FOR SYSTEM. 

C MODE l=VENTILATION. MUDE P=RECIRCULATION 

IF (MODE.EQ.2) GO TO 2 

T( 1 )=TROO!d 

W ( 1 ) =WROOM 

T(G)=TAMB 

W(6)=WAb16 

GO TO 3 

2 T(l)=TAMB 

W( 1 ) =WAhlB 

T(B)=TROOM 

W(6)=WROOM 

3 T(4)=TREG 

HS(l)=ENTH(T(l),W(l))/lOOO. 

HS(6)=ENTH(T(6),W(S))/lOOO. 

C 

C DETERMINE OUTLET STATE FOR FIRST EVAP. COOLER. 

CALL WETBLB(T(l),W(l),HS(l),TWB,PATM) 

PSAT=PS( Tws) 

WSTAR=.622*PSAT/(?AT?+PSAT) 

T(2)=T(l)+ECl*(TWB-T(1)) 

W(2)=d(lj+EC!*(WSTAR-W(1)) 

HS(2)=ENTH(T(2) ,W(2))/1000. 

122 
C 

C HUMIDXTY RATIOS ARE UNAFFECTED BY THE HEAT EXCHANGE PROCESS. 

Wf 3)=H(2) 

W[4)=W(3] 

C 

C SET UP INLET CONDITIONS ON TWO SIOES OF DEHUMIDIFIER. 

TIN(l)=T(G) 

WIN(l )=W(6) 

TfN(2)=T(4) 

WIN(2)=W(4) 

C 

C SET UP PARAMETERS FOR DESICCANT SIMULATION* 

C SIMULATION lS @ASED ON A SMALL AXIAL ELEMENT IN THE 

C ROTATING DEHUMIDIFIER WHEEL, AND ALL CALCULATIONS 

C ARE BASED ON UNIT FACE AREA. 

GA=FLOW/AFRONT 

HSEC=HEIGHT/FLOAT(NBED) 

AMASS=GA*DT 

EMASS=HSEC*BDENS 

RMASS=AMASS/BMASS 

DAREA=HSEC*ARATIO 

C 

C INITIALIZE CQUNTERS FOR AOSORPTXON OR REGENERATXON HALF CYCLE. 

11 KPASStINT(TRUN*GO./DT) 

T IME=O . PTIME-0. 

GTIMEtO. 

ADS=O. 

TSUMgO. 

WSUM=O. 

HSUM=O . KK=O 

NN=O 

IF (TIME.EQ.0.) GO TO 43 

C 

C TRANSFER COEFFICIENTS FRGM HADLEY AND MGGS CORRELATION. 

13 RK=.o2624+7.5GE-5*(TIN(M)-27.) 

RMU=I.~S~E-~+~.~~E-~*(TIN(M)-Z~.) 

H=.56*RK*(DIR?A*GA/RMU)**.67/DIAH 

G=H/(CAIR*RLENIS(M)) 

C 

C MAIN CALCULATION LOOP FOR DEHUMIDIFIER SIMULATION. 

C NPASS IS THE NUMBER OF TIME STEP TO BE TAKEN IN THE 

C COYPtETE HUN AND THE NUMBER OF AIR CHUNKS THAT MUST 

C BE PASSED THROUGH THE BED. 

C AOSORPTION M=1 REGENERATION Ma2 

DO 46 N=1 ,NPASS 

WAl=wIN(M) 

TA1 =TIN(M) 

DO 40 II=l,NBED 

IF (M.EQ.1) 1~11 

IF (M.EQ.2) I=NBED+l-I1 

TBl zTBED(1) 

XB1 =XBED( I )

C 

2 MASS TRANSFER CALCULATION: COUNTER-FLOW EXCHANGER METHOD. 

C THE AMOUNT OF WATER TRANSFERED IN A SINGLE TIME STEP IS 

C CALCULATED USING EQUATIONS ANALOGOUS TO THOSE FOR A 

C STEADY STATE COUNTER-FLOW HEAT EXCHANGER. THE QUANTITY 

C "DYDMS" IS THE PARTIAL DERIVATIVE OF THE DESICCANT LOADING 

C FRACTION WITH 2ESPECT TO THE EQUILIBRIUM MASS FRACTION 

C OF WATER IN THE AIR AT THE INTEi3FACE. THIS IS ANALOGOUS TO 

C THE SPECIFIC HEAT IN THE HEAT TRANSFER PROBLEM AND REPLACES 

C THE INVERSE OF HENRY CONSTANT USED IN GAS-LIQUID MASS EXCHANGE 

C PROBLEMS. 

PSAT=PS(Tal) 

CALL PRO?S(fCORR,XS1,TB1,PSAT,PVE,HSHV) 

RhlS=.622*PVE/(PATM-.378*PVE) 

RM,41=WAl/(1 .+WAl) 

CA=AMASS*(l.+k4l)/DT 

CALL DEi?IV(ICCRR,Xal,T5ttRP~S,HSHV,PATM,?SAT,DYDMS) 

CS-FRAC-EMASS*( 1+XB1 )*CYDMS/OT 

CMIN=AMINl(CA,CB) 

ChIAX-AMAX1 (CA, CB) 

CC=CM!N/CMAX 

RNTU=G*DAREA/Ci'A1N 
TB2=TBINT-HEAf/(BMASS*(CBED+FRAC.XB2*CWATER)) 

HA2=ENTH(TA2,WA2)/1000. 

ADS=AGS+WATER 

TBED(I)=TB2 

XBED(I)=X82 

WAI =WA2 

TAI=TA2 

40 CONTINUE 

C 

C OUTLET CONDITIONS ARE STORED AT THE END OF EACR TIME STEP 

TIME=TIME+DT 

PTIME=PTIME+DT 

GTIME=GTXME+DT 

IF (ABS(PTiME/60.-TPRINT).LT.l.E-6) GO TO 41 

GO TO 42 

44 NN=NN+1 

PTIME=O. 

PSAT=PS(TA2) 

OUTl(NN)=TIME/60. 

' OUT2(NN)=TA2 

OUT3(NN)=WA2 

OUT4(NN)=PATM*WA2/((.622+WA2)*PSAT) 

OUT5{NN)=HA2 

42 IF (ABS(GTIME/~O.-TGRAPH).LT~~*E-~) GO TO 43 

GO TO 45 

43 KK=KK+l 

GTlir!E=O. 

DO 44 I=l ,NEED 

GRAPH(I,KK.l)=TBED(I) 

44 GRAPH(I,KK,2)=XBED(I) 

IF (TIME.EO.0.) GO TO 13 

45 TSUM=TSUM+TA2 

WSUM=WSULI+WA2 

HSUM=HSUid+HA2 

46 CONTINUE 

C 

C AVERAGE OUTLET STATES ARE CALCULATED AT THE AND OF 

C EACH HALF CYCLE. 

TAVE=TSUM/FLOAT(NPASS) 

WAVE=WSUM/FLOAT(NPASS) 

HiN=ENTH(TIN~M),WIN(M))/1000. 

HAVE=HSUM/FLOAT(NPASS) 

GELH=HAVE-HIN 

ADFRAC:ADS/( FRAC*BP<?ASS*NEED) 

IF (NCYCLE.GT.100) GO TO 47 

IF ((ABS((ADS+4DSOLD)/ADS).LT.AOSERR)-AND.( GO TO 47 

IF (FLAG) GO TO 47 

GO TO 54 

47 IF (M.EQ.2) GO TO48 

WRITE(6.98) 

T('I)=TAVE 

Y (7) =NAVE 

HS(7)tHAVE 

GO TO 49 

48 WRITE(6,99) 

T(S)=TAVE 

W(B)=WA\IE 

HS(S)=HAVE 

C 

C RESULTS ARE PRINTED FOR EACH HALF CYCLE GNCE THE CONVERGENCE 

C LIMIT FOR THE BALANCE OF WATER ADSORBED AND DESORBED IS ACHIEVED. 

49 WRITE(6.100) AFRONT,HEIGHT,DIAM,ARATIO,FRAC.BDENS,CBED, 
TR-1330 

EFF=(~.-EXP(-RNTU+(~.-CC)))/(~.-CC*~XP{~RNTU*(I,-CC))) 

RMA2=RMA1-EFF*(RMAl-RIMS) 

WA2=RMA2/(1.-RMA2) 

WATER=AMASS*(WAt-WA2) 

x~~=(x~~*FRAC*BMASS+WATER)/(FRAC*BMAS~) 

C 

C ENERGY BALANCE 

C AN IWTERMEOIATE TEMPERATURE IS CALCULATED FOR THE BED SECTION WHILE THE 

C AIf? IS ASStihIED TO REMAIN AT ITS INITIAL TEMPERATURE. THE DIFFERENCE 

C BETWEEN THE HEAT OF ADSORPTION AND THE HEAT OF VAPORIZATION IS 

C ACCOUNTED FOR. HSHV IS THE RATIO OF THE HEAT OF ADSORPTION TO 

C THE HEAT OF VAPORIZATION AND IS RETURNED BY SUBROUTINE PROPS. 

HVAP-2358500.-246O.*(TB1-60.) 

TBINT=~TBI~~MASS+~C~ED+FRAC*X~~*CWATER) 

1 +AMASS=(ENTH(TA~,WA~)-ENTH(T~:~~WA~))+WATER*HVAP* 

2 (HSHV-~.))/(~MASS+(C~E~+FRAC*XB~*CWATER)) 

C 

C HEAT TRANSFER CALCULATION: 

C THE MODEL ASSUMES THAT THE FINAL TEMPERATURES OF THE AIR CHUNK 

C AND THE BED SECTION AT THE END OF THE TIME STEP ARE THE SAME AS 

C THE STEADY STATE OUTLET TEMPERATURES FROM A SIMPLE COUNTER FLCW 

C HEAT EXCHANGER THAT HAS STEADY FLOWS OF AIR AND DESICCANT MATERIAL 

C WITH INLET CONDITICNS EQUAL TO THE INITIAL CONDITIONS OF THE AIR 

C CHUNfi AND THE BED SECTION. THE EFFECTIVENESS OF THIS HEAT 

C EXCHANGE PROCESS IS DETERMINED BY THE HEAT TRANSFER COEFFICIENT, 

C THE TOTAL SURFACE AREA IN THE BED SECTION* AND THE HEAT CAPACITY 

C RATES OF THE AIR AND BED MATERIAL. 

CA=AMASS*DHDT(TA~,WA~)/DT 

c~=BMASS* (CBED+XB~*FRAC*CWA~ER)/DT 

CMfN=AMINl(CA,CB) 

CMAX~AMAXI (CA,CB) 

CC=CMiN/CMAX 

RNTU=H*DAREA/CMIN 

EFF=(~.-EXP(-RNTU*(~.-CC~~)/(~.-CC*E~P~-~NTU*~~.-~C~)) 

HEAT~EFF*CMIN*(T~IN~-~A~)~DT 

TA~=TAI+HEAT/(PHDT(TAI,wA~)*AMASS) 

1TIN(M)fWIN(M)eFLOM,fRUNtDTtNBED~R~lASS,RLEWIS(M],ICURR 

2 , RFilASS 

WRETE(6,lOl)NCYCLE,fAVE,WAVE,HIN,HAVE,DELH,ADS,ADFRAC 

IF (IPLOT.EQ.0) GO TO 59 

IF (M.EQ.1) NA=MN 

IF (M.EQ.2) NR=NN 

DO 51 I=l ,NN 

IF (M.EQ.1) TPA(I)=OUT2(1] 

IF (M.EO.1) W?A(I)=OUT3(I) 

IF (M.EQ-2) TPR(I)=OUT2(I) 

IF (M.EQ.2) WPR(I)=OUT3(I) 

51 WRITE(6e102) UUT1(I)tO~T2(I)~0UT3(I)*OUf4(I)~OUT5{I) 

WRITE(6r 703) 

DO 52 L= 1 , KK 

TG=TGRAPH*FLOAT(t-1) 

WRITE(6,104) TG 

00 52 1=1 ,NBED 

52 WRITE(6,lCS) IeGRAPH(I,Lt1)pGRAPH~*L,2) 

C 

C BEGIN PLOTTING ROUTINES USING OISSPU 

C 

STEP=1 . IF (TRGN.GE.14.) STEP=2. 

IF (TRUN.GE.20,) STEP=10. 

CALL TITLE("0UTLET AIR TEMPERATURE (C)",-22, 

1 "TIME (h1INUTES)" ,14, 'TEMPERATURE (C)&" ,15,5. *3-5) 

.CALL XlNTAX 

CALL YTICKS(2) 

CALL GRAF(O.,STEP,TRUN,20.,20.,100.) 

CALL CUHVElOUTlf0UT2,NN,O) 

CALL FRAME 

CALL RLVEC(O*,TIN(nq)tTRUN,PfN(M),1202) 

CALL ENDPL(0) 

CALL TiTLE("@UTLET CIR HtiMIDITYU,-19,uTIME MINUTES)",^^, 

1 "HUMIDITY (KG/KG)U+16+5.f3.5) 

CALL YT ICKS(5) 

CALL GRAF(O.,STEP,TRUN,O.,.01,.03) 

CALL CURVE(OUTl,OUT3,NN,O) 

CALL FRAME 

CALL RLVEC(0. ,WfN(Ll) ,TRUN,WfN(M) ,1202) 

CALL ENOPL(0) 

125 
CALL TITLE("OES1CCANT TEMP. PROFILESN.-24, 

1 "BED LOCATION",l2,"TEMPERATURE (C)',15,5.,3.5) 

CALL YTICKS( 2) 

RNBED= FLOAT ( NED) 

CALL GRAF(l.,l..RNBED,20.~.,~00.) 

CALL FRAME 

DO 56 I=l ,KK 

DO 55 K=l ,NEED 

Y(K)=GRAPH(K,I,l) 

55 X(H)=FLOAT(K) 

56 CALL CL'RVE(X,Y ,NBED,O) 

CALL RLVEC(~. ,TIN(M) ,RNBED,TIN(M) ,1202) 

START=FLOAT(NSED/Z-3) 

FINISH=FLOAT(NBED/2+3) 

IF (M.EO.l) CALL RLVEC(START,~~.,FINISH,~~.,~~O~) 

IF (M.EQ.2) CALL RLVEC(FINISH,93.,START,93.,1501) 

CALL ENDPL(0) 

CALL TITLE(ULOADING PROFILESn,-16, 

1 "BED LOCATIONH,12,"WATER CONTENT (KG/KG)',21,5.,3.5) 

CALL YTICKS(1) 

CALL GRAF(l.,l.pRNBED,O.,.1,.4) 

CALL FRAME 

DO 58 I=l,KK 

DO 57 K=l ,NBED 

Y(K)=GRAPH(K,I,P) 

57 X(K)=FLJAT(#) 

58 CALL CURVE(X,Y,NBED,O) 

IF (M.EQ.1) CALL RLVEC(START,.~~,FINISH,.~~,~~O~) 

IF (M.EQ.2) CALL RLVEC(FINISH,.~S,START,.~~,~~O~) 

CALL ENDPL(0) 

59 IF (FLAG) GO TO 60 

FLAG=.TRUE. 

54 IF (M.EO.l) NEXT.2 

IF (M.EO.2) NEXT=I 

M=NEXT 

ADSOLD=ADS 

NCYCLE=NCYCLE+l 

GO TO 11 

C; 

C FINAL SYSTEM PERFORMANCE CALCULATIONS - 

C; 

c OUTLET STATES FROM THE SENSIBLE HEAT EXCHANGER 

30 CADS=FLOW*DHDT(T(7),W(7)) 

CREG=FLDW*DHDT(T(2),W(2)) 

CMIN=ALIINl (CADS,CREG)/IOOO. 

OEXCH=EHX*CMIN*(T(7)-T(2)) 

W(B)=W(7) 

HS(3)=HS(2)+QEXCH/FLOW 

HS(8)=HS(7)-QEXCH/FLOW 

T(3)=TH(HS(3).W(3)) 

T(E)=TH(HS(B),W(E)) 

HS(4)=ENTH(T(4),W(4))/1000. 

C 

C SOLAR OR AUXILIARY ENERGY INPUT REQUIRED TO REACH 

C THE SPECIFIED REGENERATION TEMPERATURE 

DHREGzHS(4)-HS(3) 

QREGEN=FLOW*DHREG 

C 

C OUTLET STATE FROM EVAPORATIVE COOLER 2 

CALL WET@LB(T(~),W(~),HS(~),TWBSPATM) 

PSAT=PS(TWB) 

WSTAR=.622*PSAT/(PATrJ-PSAT) 

T(9)=T(E)+EC2*(TWa-T(8)) 

W(9)=W(a)+EC2*(WSTAR-W(8)) 

HS(9)=Ef4TH(T(9),W(9))/1000. 

C 

C COOLING CAPACITY AND THERMAL COP 

HROOM=ENTH(TROOM,WROOM)/1OOO. 

DHCOOL=HEOO!d-HS(9) 

CAP=DHCOOL*FLOM 

COP=CAP/QZEGEN - 
C 

C PRINT SYSTEM RESULTS 

W2ITE(6,106) 

IF (MuOE.EO.~) WRITE(6,107) ECl,EHX,EC? 

IF (MOOE.EQ.2) WRITE(6,108) ECI,EHX,EC2 

WRITE(6,109) 

DO 80 I=1 ,9 

80 WRITE(6,llO) I,T(I)pW(I),HS(l) 

WRITE(6,lIl) DHCOOt,DHREG,OREGEN,CAP,COP 

IF (IPLOT.EQ.0) GO TO 91 

C 

C PLOT OF DEHUMlDIFtER OUTLET STATES ON THE PSYCH CHART 

CALL TITLE("PSYCHROMEfR1C CHARTm,-19t 

1 "DRY BULB TEMPERATURE (C) ,24, 

2 "HUMIDITY RAT30 (K~/KG)",22*5*,3*5) 

CALL xTICKS(~) 

CALL YTICKS(5) 

CALL GRAF(10.,10.,100.,0.~*01~*O3] 

CALL ~LNX1(0.r5b,3.5,4.0rO) 

CALL FRAME 

CALL CURVE(TPA,WPA,NA,I) 

CALL CURVE(TPR,WPR,NR,l) 

00 71 I=l,lO 

RH=.O1*FLOAT(X) 

NP=O 

DO 70 IT=10,100 

NP=NP+1 

X(NP)=FLOAT( IT) , 

TDB=X(NP)+273. 

PSAT=EXP(23.28199-3780.82/TU~-22580S ./TO0**2) 

Y(NP)=.~~~*RH*PSAT/(PATM-RH*PSAT) 

70 IF [Y(NP).GT..031) Y(NP)=.03 

CALL CURVE(X,Y,NP,O) 

71 CONTINUE 

DO 73 ;=2,10 

RH=FLOAT(I)*.l 

NP=O 

DO 72 IT=10,65 

NP=NP+I 

X(NP)=FLWAT(IT) 

TD8=FLOAT(IT)+273, 

~~~~=€~~(23.28199-3780.82/T~~-225805./T~~**2) 

Y(NP)=.~~~*RH*PSAT/(PATM-RH*PSAT) 

72 IF ((Y(NP).GE..O~~).UR.(Y(NP).LT-~*)) Y(NP)=bO3 

CALL CiJRVE(X,Y ,NP,O) 

73 CONTINUE 

CALL ENDPL(0) 

C 

C PLOT OF COMPLETE CYCLE ON THE PSYCH CHART 

CALL RESET("5LNKlU) 

CALL TITLE("PSVCHROMETR1C CHARTY,-19, 

1 "DRY 8ULB TEMPERATURE (C)",24, 

2 'HUMIDITY RATIO (KG/KG)",~~,S*~~*S) 

CALL XTICKS( 1 ) 

CALL yTICKS(5) 

CALL GRAF(1Q.,I0.,100.,0.,.01,~03) 

CALL BLNKl(O.,5.,3.5,4.0(0) 

CALL FRAME 

DO 83 I=t,10 

RH=.OI*FLOAT(I) 

NP=O 

CO 84 IT=10,100 

NP=NP+I 

X(N?)=FLOAT( IT) 

TDB=X(NP)+273. 

PSAT=EXP(23.285 99-3780.82/TD8-225805* /TDB**~] 

Y(NP)=.~~~*RH*PSAT/(PATM-RH*PSAT) 

84 IF (Y(NP).GT..0318) Y(NP)=.03 

CALL CURVE(X,Y,NP,O) 

83 CONTINUE 

DO 86 I=2,10 

RH=FLOAT(I)*. 1 

NP=O 

00 85 IT=10,65 
TR-1330 

s=,n + 

NP=NP+l 

X(NP)=FLOAT( IT) 

TDB=FLOAT ( IT )+273. 

PSAT=EXP(23.281 99-378OO82/TD8-22580S./TD8**2) 

Y(NP)=.622*RH+PSAT/(PATM-RH*PSAT) 

85 IF ((Y(NP).GE..032).0R.(Y(NP).LT.O.)) Y(NP)-.03 

CALL CURVE(X ,Y ,NP,O) 

86 CONTINUE 

DO 81 I=1,5 

X(I)=T(I) 

81 Y(I)=W(I) 

CALL CURVE(X,Y*S,l) 

DO 82 1.1.4 

X(I)=T(1+5) 

82 Y(I)=W(1+5) 

CALL CURVE(X,Y*4,1) 

CALL ENDPL(0) 

90 CALL DONEPL 

91 CONTINUE 

STOP 

C 

C FORMAT STATEMENTS FOR PRINTED OUTPUT 

98 FORMAT("ln,////,1X,15HADSORPT1ONMODE) 

99 FORMAT("1*,////,1X,l7HREGENERATION MODE) 

100 FORMAT(//,lX,lSHBED PARAMETERS:,lOX,22HFRONTAL AREA (M2) a, 

lF6.0,/,26X,22HBED THICKNESS (M) =,F5.3, 

2/,26X,22HPARTICLE DIAM. (M) =,F8.6, 

2/,26X,22HSURFACE AREA (M2/M3) =,F6.0, 

3/,26X,22HDESICCANT FRACTION 2.F5.3, 

3/,26X,22HBED DENSITY (KG/k13) =,F5.0, 

4/,26X,2fHSPECIFiC HEAT OF BED 3,F5.OI 

5//,1X,19HCONDITIONS FOR RUN:,6X18HTIN (C)r,F5.1,/,26X,4HWIN=,F6.5, 

6/,26X,17iiFLOW RATE (KG/S)=,F8.5, 

7/,26X,13WPERIOD (MIN)=,F8.1,/,26X, 

814HTIME STEP (S)=,F5.0,/,26X,5Hi4BED=112, 

9/,26X,llHMASS RATIO=,F5.3, 

1 /, 2EX, 22HLEW IS NUVSER =.F3.1, 

2/,26X,22HPHOPERTY CORRELATION =,12) 

101 FORMAT(///,1X,7HNCYCLE=,I3,10X~TAVE=,F5.ltlOX,~HWAVE~~~6.5,//, 

121H ENTHALPY IN (KJ/KG)=,F8.4,SX.I3HENTHALPY OUT=,F8.4, 

25X,7HCHAUGE=,F8.4,//, 

31X.lBHWATER CYCLED (KG)=,Fl0.5,5X,23HFRACTIDN OF BED CYCLED=,F6.4, 

4 /,U1",////,1X,18HOUTLET CONDITIONS:.2X, 

5 IOHTIME (MIN),lOX,EHTCUT (C).gX.l2HWOUT (KG/KG).llX,4HROUT, 

6 6X,"ENTHALPY (KJ/KG)",/) 

102 FORMAT(2CX,F10.3,10X.F8.2,10X,F10.6,10X,~7~4,lOX~F8.4) 

103 FORP.lAT("IU,////,1X,36HTEMPERATURE AND LOADING PROFILES AT , 123HTGRAPH TIME INCREMENTS:,//) 

104 FORMAT(//,1X,5HTIUE=,F8.l,lX,5H MIN.,//,llX,4HNBED,13X, 

11CHTE!,IP (C) ,gX,7HLOADINGI/) 

105 F0RF~AT(12X11L",1~.F10.2.10X,F10.5) 

106 FORMAT("~*,////,~X,~~HSYSTEM PERFORMANCE CHARACTERISTICS) 

107 FORMAT(/,lX,UVENTILATID~ MODE: 1-ROOM, 6-AMBIENT,", 

1 * 9-DELiVEREDn,//,1X,UEFFECTIVITIES: ECI-",F3.2,* EHX-',F3.2, 

2 " ECZ-',F3.2) 

108 FOR!vlAT(/,lX,"RECIRCULATlON MODE: 1-AMBIENT, 6-ROOM,', 

I * 9-DELIVEREDU1//,lX,"EFFECTIVSTIES: EC1-",F3.2," HX-",F3.2, 

2 iZC2-H,F3.2) 

109 FORMAT(//,lX,'STATE POINTS:U,12X,'IU,11X,''TEMP (C)',6X1 

1 'HUMIDITY (KG/KG)",3X,"ENTHALFY (KJ/KG)",//) 

110 FORMAT(26X,I1,7X,FlO.3,gX,F10.5,8X,FlO.3) 

111 FORMAT(////,26X,'DHC00L=1*,F8.3,m KJ/KG DRY AIRYt/, 

1 26X,*DHREG rt',F8.3,' KJ/KG DRY AIRY,/, 

3 26X,'QREG 08',F8.3,' KWY,/, 

4 26X.'CAP. =",F8.3," KWY,/, 

5 26X,"COP ~~~,F8.3,/,~1') 

END 

C 

C 

C SATURATION VAPOR PRESSURE AS A FUNCTION OF TEMPERATURE. 

C CORRELATION FROM MACLAINE-CROSS THESIS. 

FUNCTION PS(T) 

TK=T+273. 

PS=E~~(23.28199-3780.82/TK-2258GS./TXr*2) 

RETURN 

END 

128 
C 

C 

C ENTHAtPY OF AIR AS A FUNCTION OF TEMPERATURE AND HUMIDITY 

C CORRELATION FROM MACLAINE-CROSS THESIS 

FUNCTION ENTH(1.W) 

~~~~=(1005.22+.02615*t)*T+W*(2500800.+186~.*T) 

RETURN 

END 

C 

C 

C FUNCTION FOR TEMP. FROM ENTHALPY AND HUMIDITY RATIO. 

C FROM MACLAINE-CROSS THESIS 

FUNCTION TH(H,W) 

0=(1005.22+1868.*W)/.0523 

TH=-D+SQRT(D*D+(H*~~OO.-~~OO~OO*Y)/~~~~~S) 

RETURN 

END 

C 

C 

C FUNCTION FOR THE SPECIFIC HEAT OF AIR 

FUNCTION DHDT(f,W) 

DHOT=1005.22+.0523*t+1868-*\4 

RETURN 

END 

C 

C 

C SUBROUTINE F3R WET BULB TEMP. GIVEN DRY BULB TEMP. AND HUMfDfTY 

C BASED ON EQUATIONS FROM ASHRAE CHAPTER ON PSYCHROMETRICS, 

C THE BISECTION METHCD IS USED FOR THIS ITERATIVE SOLUTION* 

SUBROUTINE WETBLB(TDB,W,H,TWB,PATM) 

HO=H+20.1 

TSTART=(-13.9+.5696*H0-.001665*HO**2) 

THI-1START-I-2. 

TLOtTSTART-2. 

03 5 I=1,15 

TWB=(TH~+~LO)/~. 

PSAT=PS(TWB) 

wSTAR=.~~~*PSAT/(PATM-PSAT) 

TF=TWB*1.8+32-,+ 

TDF=TDB+?.8+32. 

WCHECK=((~~~~.-.~~~*TF)*WSTAR-~Z~~(TDF-TF))/(~O~~-+.~~~*~DF-~F~ 

IF (WCHECK.GT.W) THI=TWB 

IF (WCHECK. L1.W) TLO=TWB 

5 CONTINUE - b 

RETURN 

END 

C 

C SUBROUTINE FOR THE EQUILISRfUM PROPERTIES OF REGULAR DENSlTY 

C SILICA GEL. CORREtATI0NS BASED ON EXPERIMENTAL DATA ARE USED 

C TO CALCULATE THE EQUILfBRIUM VAPOR PRESSURE AT THE DESICCANT 

C SURFACE AND TO CALCULATE THE RATIO OF THE HEAT OF ADSORPTION 

C TO THE HEAT OF VAPQRIZATION. THREE CORRELATIONS ARE INCLUDED, 

C AND THE PASSED INTEGER "ICORR* DETERMIP4,ES WHICH ONE IS USED. 

C 

C ICORR=l BULLCCK AND THRELKELD FIT TO HUBARD'S DATA 

:C AND CLOSE AND BANKS EONS FOR WADS/HVAP. 

C 

C ICORR=2 CLOSE AND BANKS FIT TO HUBARD'S DATA. 

C F(X)=2.OGg*X AND LINEAR EQNS FOR HADS/HVAP ARE USED. 

C 

C ICORR=3 FIT TO DATA OF F. ROJAS FOR DAVISON PA-40 

C SILICA GEL. LINEAR EONS FOR HADS/HVAP. 

C 

SUSROUTINE PROPS(ICORR,X,TC,PSAT,PVE~HSHV~ 

GO TO (10,30,40) ICORR 

C 

C ICORR=l 

C 

10 T=TC*1 .8+32. 

IF!X.GT.*OS] GO TO 11 

PVE=((({4.022s3E-4*X+1.186214€-5)*T-BB938272E-2* 

1X-3.267901E-3)*T+7.056827*X+.322929)*T-182.1523*X210.41436)*X 

GO TO 17 
11 IF (X.GTa.1) GO TO 12 

PVE=(((-7.808642E-6*X+1.989198E-6)*T+4.312037E-3*X1 6.024537E-4)*T-.484787*X+.058058)*T+17.20448*X-l-836323 

GO TO 17 

12 IF (X.GT..lS) GO TO 13 

PVE=(((2.083333E-S*X-8.75E-7)*T-3.825€-3*X+2.1125E-4)*1 

1+.255417*X-.0!5963)*T-4.6825*X+.352375 

GO TO 17 

13 IF (X.GT..2) GO TO 14 

PVE=(((5.333333E-S*X-5.75E-6)*T-l.38E-2*X+l.7075E-3) 

l*T+1.264667*X-,16735)+T-38.*X+5.35 

GO TO 17 

14 IF (X.GT..25) GO TO 15 

PVE=(((-8.166667E-5*X+2.125E-5)*T+2.135E-2*X-5.3225E-3) 

1*T-1.752333*X+.43605)*T+47.6*X-11.77 

GO TO 17 

15 IF (X.GTa.3) GO TO 16 

PVEr(((4.E-5*X-9.16667E-6)*T-8.1E-3*X+2.04E-3) 

l*T+.599*X-.151783)*T-14,1*X+3.655 

GO TO 17 

16 PVE=(((2.E-5*X-3.166667E-6)*T-3.7E-3*X+7.2E-4) 

1 *T+.291 *X-.059383)*T-6.9*X+I ,495 

17 PVE=PVE*101325./29.92 

IF (X.GT.nO4) GO TO 21 

HSHV=8533.*X**3-542.*X*X+11.79*X+l.l557 . GO TO 50 

21 IF (X.GT6.1) GO TO 22 

HSHV=45.4*X*X-8.97*X+1.5922 

GO TO 50 

22 HSHV=-9.1553*X**3+7.048*X*Xx1.8966*X+1.2789 

GG TO SO 

C 

C ICORR-2 

C 

30 IF (X.GT..l) GO T3 31 

HSHV=1.3-1 ..?S*X 

GO TO 32 

31 HSHVtl.14-.15*X 

32 PVE=(101325./29.91)*(29.91*2.009*X*PSA~/l0i325.)**HSHV 

GO TO 50 

C 

C ICORR=3 

C 

40 IF (X.GT. .1) GO TO 41 

hSHV=1.3-1.75*X 

GO TO 42 

41 HSHV=1.14-.15*X 

42 R=(.616238*X+16.7916*~*~-74.34228*X**3+116.6834*X**4) 

1 /(I.-(TC-40.)/300.) 

PVEzR* PSAT 

50 RETURN 

END 

C 

C 

C 

C SUBROUTINE FOR CALCULATING THE PARTIAL DERIVATIVE OF THE MASS 

C FRACTION OF WATER IN THE DESICCANT WITH RESPECT TO THE MASS 

C FRACTION OF WATER IN THE AIR AT EQUILIBRIUM. THREE CORRELATIONS 

C ARE INCLUDED, AND THE PASSED INTEGER "ICORR" DETERMINES WHICH 

C CORRELATION IS USED. 

C DERIVATIVES OF THE EQUATIONS GIVEN IN SUBROUTINE PROPS ARE USED. 

C 

-SUBROUTINE DERIV(ICORR,X,TC,RMS.HSHVWM,PSAT,DYDMS) 

GO TO (10,20,30) ICORR 

C 

C ICORR=I 

C 

10 T=TC*l .8+32. 

IF (X.GT..O5) GO TO 11 

DPVDX=(((8.0453E-4*X+11.862E-6)*T-.17a76*X+32.679E-4)*T 

1 +14.138*X+.32293)*T-364.34*X-l0.414 

GO TO 50 
I IF (X.GT*.t) GO TO 72 

DPVDX=((-7.8086E-6*T+43,12E-4f*T~.48479)*T+l7.204 

GO TO 50 

12 IF (X.GT..lS) GO TO 13 

DPVDX=((20.833E-6*T-38.25E-4)*T+2.5542)*T-4.6825 

GO TO 50 

13 IF (X,GT..2) GO TO 14 

OPVDX1((53.333€-6*1-.0138)*T+t.2647)*f-38. 

GO TO 50 

14 IF (X.G1..25) GO TO 15 

DPVDX=((-01.667E-6*T+.02135)*t-t.7523)*T+47.6 

GO TO 50 

15 IF (X.GT..3) G0,TO 16 

OPVOX=((4.E-5*T-8S,~*T+.599)*T-t4=1 

GO TO 50 

16 DPVDX=((2.E-5*f-37.€-4)*T+.29f)*T-6.9 

GO TO 50 

C 

C ICQRRr2 

C 

20 C1=3388* 

C2=5.93E-4*PSAT 

C3r-I. 75 

IF (X.GT*.I) C3~-.15 

DPVDX=C~*(C~*HSHV*(C~*X)**(HSHV-~.)+C~*(C~*X)**HSHV*ALOG(C~*X)) 

GO TO SO 

C 

C ICORR=3 

C 

30 DP~DX=PSAT*(.616238+33.5832*~-223.027*X*X+466~734*X**3) 

1 /(I.-(TCa40.)/300.) 

50 OYDMS=.~~~*PATM/((~.+X)**~*(.~~~+.~~~*RMS]**~*OPVOX) 

RETURN 

END 
PROGRAM DESSIM~(INPUT,OUTP~~T,TAPE~=INPUT,TAPE~=OUTPUT) 

C 

C ......................................................... C * * 

C * DESSIM4: SIMULATION OF SILICA GEL COOLING SYSTEMS I 

C * R. BARLOW, SERI, DECEMBER 1980 I 

C * * 

C ......................................................... C 

C 

C THIS VERSION OF THE DESSIM PROGRAM IS DESIGNED TO BE USED 

C FOR PARAMETRIC STUDIES ON DESICCANT COOLING SYSTEMS. 

C NO GRAPHICS ARE INCLUDED. 

C 

C 

DIMENSION TBED(~O),XBED(~~),TIN(~),Y~N(~),RLEWIS(~). 

3T(9),W(9),HS(9),PARAM1(6),PARAM2(5) 

LOGICAL FLAG2 

C 

C DEFINE CONSTANTS IN SI UNITS 

PATM=101325. 

CAIR=1006. 

CWATER=4181. 

C 

C READ DATA. NOTE THAT SOME OF THE INPUT VARIABLES ARE ARRAYS. 

READ(S,*) ARATIO.BDENS,FRAC,DIAM,HEIGHT,AFRONT,CBED 

READ(S,*) TROOM,WROOM,TAMB,WAMB,TREG 

READ(S,*) FLOW,TRUN,DT,TBO,XBO,NBED 

READ(S,*) ECl,EHX,EC2,MODE,RLEWIS,ICORR 

READ(5, *) PARAMl 

READ(5,*) PARAM2 

C 

C INITIALIZE TEMPERATURE AND WATER CONTENT OF DESICCANT BED. 

DO 1 I=l.NBED 

TBED(I)=TBO 

1 XBED( I ) =XS0 

C 

C LOOP FOR PARAMETRIC EVALUATION 

C THESE LINES SHOULD BE MODIFIED TO CARRY OUT DIFFERENT PARAMETRIC 

C STUDIES. NOTE THAT THE DIMENTIONS OF PARAMl AND PARAM2 MAY NEED 

C TO BE CHANGED. 

DO 91 IP=l ,2 

MODE= I P 

DO 91 IP1=1,6 

TAMB=PARAMl(IPl) 

DO 91 IP2=1 ,5 

WAMB=PARAMP(IPO) 

C 

C INITIALIZE COUNTERS AND FLAG. 

ADSOLD=O. 

NCYCLE=1 

M= 1 

ADSERR=.001 

FLAG2=. FALSE. 

C 

C INITIAL SYSTEM PERFORMANCE CALCULATIONS 

IF (MGDE.EQ.2) GO TO 2 

T(l )=TROCM 

W(I)=WROOM 

T(6)=TAMB 

W(6)=WAMB 

GO TO 3 

2 T(l)=TAMB 

W ( 1 ) =WAMB 

T(6)zTROOM 

W(G)=WROOM 

3 T(4)=TREG 

HS(l)=ENTH(T(l),W(l))/lOOO. 

HS(6)=ENTH(T(6),W(S))/lOOO. 

cnLL WETBLB(T(I),W(I),HS(~),TWB.PATM) 

PSAT=PS(TWB) 

WSTAR=.622*?SAT/(PATI-PSAT) 

T(2)=T(l)+ECl*(TWB-T(1)) 

W(2)=W(1 )+ECl*(WSTkR-U(t)) 

HS(2)=ENTH(T(2),W(2))/1000. - 

132 
W(3)9W(2) 

W(4)=W(3) 

TIN(1 )=T(G) 

WIN(1 )=W(6) 

TIN(2)=T(4) 

WIN(2)=W(4) 

C 

C 

C SET UP PARAMETERS FOR GESICCANT SIMULATION. 

HSEC=HEIGHT/FLOAT(NBED) 

BMASS=HSEC*AFRONT*BW 

DAREA=HSEC*AFRONT*ARATIO 

C 

C INITIALIZE COUNTERS FOR ADSORPTION OR REGENERATION HALF CYCLE. 

1 AMASS=FLOW*DT 

NPASS=INT(TRUN*GO./DT) 

TIME=O. 

ADS=U. 

TSUM=O. 

wsurtl=o . HSUIM-0. 

RMASS=AMASS/BMASS 

C 

C TRANSFER COEFFIClENTS FROM HADLEY AND HEGGS CORRELATION* 

13 GA=FLOW/AFRONT 

RK=.02624+7.58€-S*(TIN(M)-27.) 

RMU=t.859E-5+4.32E-8*(TtN(M)-27.) 

H=.S%+RK*(DIAM*GA/RMU)**.67/DIAM 

G=H/(CAtR*RtEWIS(M)) 

C 

C MAIN CALCULATION LOOP 

DO 46 N=l,NPDSS 

WAl SWIN(M) 

TAt=TIN(M) 

DO 40 II=1 ,NBED 

IF (M.EQ.l) 1111 

IF fM.EQ.2) I=NBEO+1-11 

TBI =TOED( I) 

XB1 =XBED(Z) 

C 

C MASS TRANSFER CALCULATION: COUNTER-FLOW EXCHANGER METHOD. 

C THE AMOUNT OF WATER TRANSFERED IN A SINGLE TIME STEP IS 

C CALCULATED USING EQUATIONS ANALOGOUS TO THOSE FOR A 

C STEADY STATE COUNTER-FLOW HEAT EXCHANGER. THE QUANTITY 

C "DYDMS" IS THE PARTIAL DERIVATIVE OF THE DESICCANT LOADING 

C FRACTION WITH RESPECT TO THE EQUILIBRIUM MASS FRACTION 

C OF WATER IN THE AIR AT THE INTERFACE. THIS IS ANALOGOUS TO 

C THE SPECIFIC HEAT IN THE HEAT TRANSFER PROBLEM AND REPLACES 

C THE INVERSE OF HENRY CONSTANT USED IN GAS-LIQUID MASS EXCHANGE 

C PROBLEMS. 

PSAT=PS(TB~ ) 

CALL PROPS(~CO!~R,XB~,T~~,PSAT,PVE,HSHV) 

RMS=.622*PVE/(PATM-.378*PVE) 

RhiAl=WAl/(l .+kiAl) 

CA=AMASS*( I. +MA1 )/DT 

CALL DEZIV(ICORR,XBl,TBl +RMS,HSHV,PA~M.PSA~~DYDMS) 

CB=FRAC*BMASS*(1+XBl)*DYDMS/DT 

CMIN=AMINI (CA,CS) 

CLlAX=AMAXI (CA,CB) 

CC=CMEN/CMAX 

RNTU=G*DAREA/CivlIN 

EFF=(~.-EXP(-RNTU*(~.-CC)))/(~.-CC*EXP(~RNTU*(~.~~~))) 

R!JA2=RM41 -EFF*(RMAl-RMS) 

WA2zR,VA2/ ( 1. -RMA2) 

WATER=AhlASS* (WA1 -MA2 1 

XB~=(XBI*FRAC*B!~ASS+WA~R)/IFRACJ~BMASS) 

C 

C ENERGY BALANCE 

C A NEW TEMPERATURE IS CALCULATED FCR THE BED SECTION WHILE THE 

C AIR IS ASSUP.1E3 TO REMAIN AT ITS INITIAL TEMPERATURE. THE DIFFERENCE 

C BETWEEN THE HEAT OF ADSORPTION AND THE HEAT OF VAPORtZATION IS 

C ACCOUNTED FOR. HSHV IS THE RATIO Of THE HEAT OF ADS0RPTION TO 
C THE HEAT OF VAPORIZATION AND IS RETURNED BY SUBROUTINE PROPS. 

HVAP=2358500.-246O.*(TBl-60.) 

TBINT=(TBl*Bh~ASS*(CBED+FRAC*XBl*CWATER) 

1 +AMASS*(ENTH(TAl,WAl)-ENTH(TAl,WA2))+WATER*HVAP* 

2 (HSHV-l.))/(BMASS*(CBED+FRAC*XB2*CWATER)) 

C 

C HEAT TRANSFER CALCULATION: 

C THE MODEL ASSUMES THAT THE FINAL TEMPERATURES OF THE AIR CHUNK 

C AND THE SED SECTION AT THE END OF THE TIME STEP ARE THE SAME AS 

C THE STEADY STATE OUTLET TEMPERATURES FROM A SIMPLE COUNTER FLOW 

C HEAT EXCHANGER THAT HAS STEADY FLOWS OF AIR AND DESICCANT MATERIAL 

C WITH INLET CONDITIONS EQUAL TO THE INITIAL CONDITIONS OF THE AIR 

C CHUNK AND THE BED SECTION. THE EFFECTIVENESS OF THIS HEAT 

C EXCHANGE PROCESS IS DETERMINED BY THE HEAT TRANSFER COEFFICIENT. 

C THE TOTAL SURFACE AREA IN THE BED SECTION, AND THE HEAT CAPACITY 

C RATES OF THE AIR AND BED MATERIAL. 

CA=AMASS*DHDT(TAt,WA2)/DT 

CB=BMASS*(CBED+FRAC*XB2*CWATER)/DT 

CMIN=AMINl(CA,CB) 

CkIAX=AMAXl (CA ,CB) 

CC=CMIN/CMAX 

RNTU=H*DAREA/CMIN 

EFF=(l.-EXP(-RNTU*(l.-CC)))/(l .-CC*EXP(-RNTU*(l.-CC))) 

HEAT=EFF*CMIN*(TB2-TAl)*DT 

TA~=TA~+HEAT/(DHDT(TA~,~JA~)*AMASS) 

TB2=fBINT-HEAT/(BMASS*(CBED+FRAC*XB2*CWATER)) 

ADS=ADS+WATER 

TBED(I)=TB2 

XBED(I)=XB2 

WA1 =WA2 

PA1 =TA2 

40 CONTINUE 

C 

C OUTLET CONDITIONS ARE STORED AT THE END OF EACH TIME STEP 

TIMEsTIME+DT 

TSUM=TSUM+TA2 

WSUM=WSUM+WA2 

HSUM=HSUM+ENTH(TAZ,WA2)/1000. 

46 CONTINUE 

TAVE-TSGM/FLOAT(NPASS) 

WAVE=WSUM/FLOAT(NPASS) 

HIN=ENTH(TIN(M),WIN(M))/~~OO. 

HAVE=i-lSU!fl/FLOAT (NPASS) 

DEiHzHAVE-HIN 

ADFRAC~ADS/(FRAC*BMASS*NBED) 

IF (NCYCLE.GT.100) GO TO 47 

IF ((ABS((ADS+ADSOLD)/ADS).LT.ADSERR).AND.(M.EQ.~)) GO TO 47 

IF (FLAG2) GO TO 47 

GO TO 54 

47 IF (hl.EQ.2) GO TO48 

WRITE(6,98) 

T(7)=TAVE 

W(7) =WAVE 

HS(7ltHAVE 

GG TO 49 

48 WRITE(6.99) 

T(S)=TAVE 

W(5)sWAVE 

HS(5)=HAVE 

49 WRITE(6.100) ARATIOIAFRONT~HEIGHTvDIAMIBDENS~FRAC~ 

lTIN(M),WIN(M),FLOW,TRUN,DT,NBED,RMASS,RLEMIS(M),~CORR 

WRITE(~,~O~)NCYCLE,TAVE,WAVE,HIN,HAVE,DELH,ADS,ADFRAC 

IF (FLAG2) GO TO 60 

FLAG2=. TRUE. 

54 ADSOLD=ADS 

IF (M.EQ.l) NEXT=2 

IF (M.EQ.2) NEXT=l 

M=NEXT 

NCYCLE=NCYCLE+l 

GO TO 11 
C 

C FINAL SYSTEM PERFORMANCE CALCULATIONS 

60 CADS=F LOW*DHDT(T(7) ,~(7) 

CREG=FLOW*OHDT(T(Z),W(~)) 

CMIN=AMINl(CADS,CREG)/lWQEXCH=EHX*CMIN*(T(7)-T(2)) 

Wf8)=W(7) 

HS(3)=HS(2)+QEXCH/FLOW 

HS(S)=HS(7)-QEXCW/FLOW 

T(3)=TH[HS(3),W(3)) 

T(0)=TH(HS(B),W(8)) 

HS(4)=ENTH(T(4),W(4))/1000. 

OHREG=HS(4)-HS(3) 

QREGEN=FLOW*DHREG 

CALL VETBL3(T(8) ,U(8f ,HS(8) ,TWB*PATtA) 

PSAT=PS(TWB) 

MSTAR=.622*PSAT/(PATM=PSAT) 

7(9)=TrS)+EC2*(TWB-T(8)) 

W(5)=W(8)+€CZ*(WSTAR-W(8)) 

HS(S)=ENTH(T(9I,W(9))/1000. 

HROO:vl=ENTti [ TROOM, WROOM)/lOOo. 

DHCOOL-HRdOM-HS(9) 

CAP=OHCOOL* F LOW 

COP=CAP/OREGEN 

WRITE(6,tOG) 

IF (MODE.EP.1) WRITE(6,107) ECl,EHX,EC2 

IF (MODE.EQ.2) WRITE(6,tO8) ECl,EHX+EC2 

WRITE(6,109) 

00 80 I=t ,9 

80 WRITE(6.110) I,T(I) ,#(I) ,HS(I) 

~~ItE(6.111) DHCOOL.DHREG,OREGEN,CAP,COP 

91 CONTINUE 

STOP 

98 FORMAT(L1W,////,1X,i5HADSORPTION MODE) 

99 FORMAT("~",////,~X,~~HREGENERATION MODE) 

100 FORrGAT(//,lX,ISH8ED PARA~~~ETERS:,~OX,~~M~URFACE AREA (~2/M3) =, 

1F6.0,/,26X,22HFRONTAL AREA (M2) rtf5-3, 

2/,26X,i4HBED DEPTH (M)=,F6.4,/,26X,22HPARfICl.E DIAMETER (M)=,F8.6, 

3/,26X,22HBED DENSITY (KG/M3) =,FS.O,/*26X,19HDESICCANT FRACTION=, 

4 F6.3, 

5//, 1X,19HCONDITIONS FOR RUN: .6X,BHTIN (C)X.F;.I ,/.26X.4HWfN=,F6~St 

6/,26X,17HFLOW RATE (KG/S)=,Fe.S./, 

726X,13HIJERIOD (kIIN)=,F8,1,/ ,26X, 

814HTIME STEP (S)*,F5.0,/t26Xt5HNBED=~12~ 

9/,26Xv11HMASS RATIO=,F5.3, 

1/,26XV22HLEWIS NUMBER =,F4.1, 

2/,26X,22HPROPERiY CORRELATION r.12) 

101 FCRMAT(//,~X,~HNCYCLE=,I~~~OX,~HTAVE=~F~~~~~OX~~HWAVE~~F~~

121H ENTHACPY IN (KJ/KG)=,F8.4,SX,t3HENTHALPY OUf=,F8=$, 

25X,7HCHANGE=,F8.4,//, 

31Xt18HWATER CYCLED (KG)=,FIO.S,5X,23HFRACTION OF BED CYCLED=,F6.4, 

4 !) 

106 FORr4AT(//,IX,34HSYSTEM PERFORMANCE CHARACTERISTICS) 

107 FCRMAT(/,lX,"VENTILATlUN MODE: 1-ROQM9 ~-AMSIENT,", 

1 9-OELIVEREDW,//,tX,~1EFFECTIVfTfES: EC1-"9F3.2," EHX-*,F3.2, 

2 " EC2-I8,F3.2) 

108 FORMAT(/,lX,"8ECIRCULATIO!d MODE: 1-AMBIENT, 6-ROOM,', 

t 9-OELIVERED",//,tX,HEFFECTIVITIES: EC1-",F3.2," EHX-",F3.Z1 

2 ' EC2-"rF3.2) 

109 FOf?MAT(//,lX,'STATE PoIN~S:",~~X.'X~.~~X~~TEMP (C)@',~X. 

1 "HUMIDITY (KG/KG) ,3X, I'ENTHALPY (KJ/KG)" ,//I 

110 FORMAT(26X~11~7XlF10.3t9X~F10.5~8~~F10~3) 

1 FORMAT(////,26X,UDHCOOL="rF8.3*m KJ/KG DRY AfRU,/, 

I 26XVUOHREG =",F8.3,' Kd/KG DRY AIRM,/* 

3 26XVMQREG =",Fa.O,' KW",/, 

4 26X,I8CAP. r",F13.3t* Kwh,/, 

5 26X,"COP =",Fa.3) 

END 
C 

C 

C SATURATION VAPOR PRESSURE AS A FUNCTION OF TEMPERATURE. 

C CORRELATION FROM MACLAINE-CROSS THESIS. 

FUNCTION PS(T) 

TK=T+273. 

PS=EXP(23.28199-3780.82/7H-22580SS/TK**2) 

RETURN 

END 

C 

C ENTHALPY OF AIR AS A FUNCTION OF TEMPERATURE AND HUMIDITY 

C CORRSLATION FROM MACLAINE-CROSS THESIS 

FUNCTION ENTH(T,W) 

ENTH=(1005.22+.02615*T)*T+W*(2500800.+1868.*T) 

RETURN 

END 

C 

C FUNCTION FOR TEMP. FROM ENTHALPY AND HUMIDITY RATIO. 

C FROM MACLAINE-CROSS THESIS 

FUNCTION TH(H,W) 

D=(1005.22+1868.*W)/.0523 

TH=-D+SQRT(D*D+(H*lOOO.-2500800*Y)/.02615) 

RETURN 

END 

C 

C FUNCTION FCR THC SPECIFIC HEAT OF AIR FROM MACLAINE-CROSS 

FUNCTiON DHDT(7.W) 

DHDT~1005.22+~0523*T+1868.*W 

RETURN 

END 

C 

C 

C SUBROUTINE FOR WET BULB TEMP. GIVEN DRY BULB TEMP. AND HUMIDITY 

C EASED ON EQUATIONS FRSM ASHRAE CHAPTER ON PSYCHROMETRICS 

SUSRCUTINE UETBLB(TDB,W,H,TWB,PATr4) 

HO=H+20. I 

TSTART=(-13.9+.5696*HO-.001665*HO**2) 

THX=iSTART+3. 

TiO-TSTART-3. 

DO 5 1=1,20 

TWa=(THI+TL0)/2. 

PSAT=PS(TWB) 

WST&R=.622~PSAT/(PATI-PSAT) 

TF=TkE*1.6+32. 

TDF=TDB+1.8+32. 

WCHECK=((~~~~.-.~~~*TF)*WSTAR-.~~*(TDF-~F))/(~O~~.+.~~~*TDF-TF) 

IF (WCHECK.GT.W) THIzTWB 

IF (WCHECK.LT.W) TLO=TWB 

5 CONTINUE 

RETURN 

END 

C 

C SUBROUTINE FOR THE EQUILIBRIUM PROPERTIES OF REGULAR DENSITY 

C SILICA GEL. CORRELATICNS EASED ON EXPERIMENTAL DATA ARE USED 

C TO CALCULATE THE EQUILIBRIU$! VAPOR PRESSURE AT THE DESICCANT 

C SURFACE AND TO CALCULATE THE RATIO OF THE HEAT OF ADSORPTION 

C TO THE HEAT OF VAPORIZATION. THREE CORRELATIONS ARE INCLUDED, 

C AND THE PASSED INTEGER "ICORRU DETEZMINES WHICH ONE IS USED. 

C 

C ICGRR=I BULLOCK AND THRELKELD FIT TO HUBARD'S DATA 

C AND CLOSE AND BANKS EQNS FOR HADS/HVAP. 

C 

C ICORR=2 CLOSE AND BANKS FIT TO HUEARD'S DATA. 

C F(X)=2.OOS-X AND LINEAR EONS FOR HADS/HVAP ARE USED. 

C 

C ICORR=3 FIT TO DATA OF F. ROJAS FOR DAVISON PA-30 

C SILICA GEL. LINEAR EONS FOR HADS/HVAP. 

C 

SUBROUiINE PROPS(ICORR,X,TC,PSAT,PVE,HSHV) 

GO TO (10,30,40) ICORR 

C 

C ICORR=l 
C 

10 t=TC*1.8+32. 

IF(X.GT..OS) GO TO 11 

~~~=((((4.02263E-4*~+1.186214E-5)*T-8*938272€-2* 

1X-3.267901E-3)*T+7.068827*X+.322929]*T-102~1523*X~ 

210.41436)*X 

GO TO 17 

If IF (X.GT..l) GO TO 12 

P~E=(((-7.808642E-6*~+1.98919SE~6)*T+4.312037E~3*Xt 6.024537E-4)*T-~484787*~+~058058)*T+17~20448*X~1~836323 

GO TO f 7 

12 IF (X,GT..15) GO TO 13 

PVE=(((2.O83333E-5*X-8.75E-7)*T-3.82SE-3*X+2e1t25€-4)*T 

1+,255417*X-m015963)*f-4,6825*X+~352375 

a TO 17 

13 IF (X.GTe.2) GO TO 14 

PVE=(((5.333333E-5*X-SS7SE-6)*T-~.38E-2*X+1.7O?5E-3) 

t*T+1.264667*X-.16735)*T-38.*X+S.35 

GO TO 17 

14 IF (X.GT..25) GO TO 15 

PVEr(((-8.166667E-5*X+2.125E-5)*T+2~135E~2*X~5o3225€~3) 

t*T-1.iS2333*X+.43605)*T+47.6*Xx11.77 

GO TO 17 

15 IF (X.GT..3) GO TO 16 

PVE=(((4.€-5*X-9.16667E-6)*ff8.1E-3*X+2.04€-3) 

1*T+.599*X-.151783)*T-14.1*X+3.655 

GO TO 17 

16 PVE=(((2.€-5*X-3.166667E-6)*T-3*?€-3*X+7.2E-4) 

1*T+.291*X-.059333)*T-6.9*K+1.495 

17 PVE=PVE*101325./29.92 

IF (X.GT..04) GO TO 21 

HSHV=8533.*X**3-542.*X*X+IIm?9*X+lolSS7 

GO TO 50 

21 IF (X.GT,,l) GO TO 22 

HSHV=45.4*X*X-6.97*X+tt5922 

GO TO 50 

22 HSHV=-9.1553*X**3+7.048*X*X-1.8966*X+1.2789 

GO TO 50 

C 

C ICORR=2 

C 

30 IF (X.GT..l) GO TO 31 

HSHV=1.3-1.75*X 

GO TO 32 

31 HSHVrl.14-.15*X 

32 P~E=(101325./29.91)*(29~91*2.009*X*PSAT/101325.)**HSHV 

GO TO 50 

C 

C ICORR=3 

C 

40 IF (X.GT*.l) GO TO 41 

HSHV=l .3-1 .75*X 

GO TO 42 

41 HSWV=l. 14-, 15*X 

42 R=(.616238*X+I6.7916*X*X-74.34228*X**3+116~6834*X**4) 

1 /(I.-(TCn40.)/330.) 

PVE=R*PSAT 

50 RETURN 

END 
L 

C SUBROUTINE FOR CALCULATING THE PARTIAL DERIVATIVE OF THE MASS 

C FRACTION OF WATER IN THE DESICCANT MITH RESPECT TO THE MASS 

C FRACTION OF WATER IN THE AIR AT EQUILIBRIUM. THREE CORRELATIONS 

C ARE INCLUCED. AND THE PASSED INTEGER .ICORR' DETERMINES WHICH 

C CORRELATION IS USED. 

C DERIVATIVES OF THE EQUATIONS GIVEN IN SUBROUTINE PROPS ARE USED. 

C 

SUBROUTINE DERIV(ICORR,X,TC,RMS,HSHV,PATM,PSAT,DYDMS) 

GO TO (10,20,30) ICORR 

C 

C lCORR=l 

C 

T=TC*l .8+32. 

C 

C ICORR=3 

C 

30 DPVDX=PSAT*(.616238+33.5832*X-223.027*X*X+466.734*X**3) 

1 /(I.-(TC-40.)/300.) 

50 DYDMS=.622*PATM/((l.+X)**2*(.622+.378*RMS)**2*DPVDX) 

RETURN 

END 
1 Document Control 1 1. SERI Report NO. 1 2. NTlS Access~on No. 1 3. Rec~p~ent's Access~on No. 1 

Page I TR-631-1330 1 I 

4. Title and Subt~tle 1 5. Publication Date 

I 

7. Author@) 1 8. Pertormlng Organizat~on Rept. No. 

Analysis of the Adsorption Process and of Desiccant 

Cooling Systems -- A Pseudo-Steady-State Model for 

Coupled Heat and Mass Transfer 

December 198 2 

6. 

Robert S. Barlow 

9. Performlng Organlzat~on Name and Address 

Solar Energy Research Institute 

161 7 Cole Boulevard 

Go1 den, Colorado 80401 

Technical Report I,] 

10. ProjectlTasklWork Unlt No. 

1131 .OO and 1132.11 

11. Contract (c) or Grant (G) NO. 

(C) 

(GI 

12. Sponsor~ng Organczat~on Name and Adaress 

1 

15. Supplementary Notes 

13. Type of Report 8 Per~od Covered 

L 

16. Abstract (Limit: 200 words) 

This report documents a computer model to simulate the adiabatic adsorption/ 

desorption process. Developed to predict the performance of desiccant cooling 

systems, the model has been val idated through comparison with experimental 

data for single-blow adsorption and desorption. The report also contains a 

literature review on adsorption analysis, detailed discussions of the adsorption process, and an initial assessment of the potential for performance 

improvement through advanced component development. 

I 

4 

17 Document Analys~s 

a. Descrlptors Adiabatic processes ; Adsorption ; Computerized simulations ; D codes 

; Dessicants ; Packed beds ; Silica gel ; Solar cooling systems 

1 b. Identifiers/Open-Ended Terms 

c. UC Categories 

59c 

18. Ava~la$~lity Statement 

Natlonal Technical Information Service 

U. S. Department of Commerce 

5285 Port Royal Road 

Sprinqfield, Virainia 22161 

19. No. of Pages 

156 

20 Pr~ce 

$8.00 

Form No. 0069 (3-25-82)