This paper presents adsorption and desorption characteristics of two different working pairs—activated carbon–methanol and activated carbon–R134a—determined experimentally. Dubinin–Radushkevich (D–R) equation is used to correlate the adsorption isotherms and to form the pressure, temperature, and concentration diagrams for both the assorted working pairs. The results show that the maximum adsorption capacity of activated carbon–R134a working pair is 1.21 times that of activated carbon–methanol. Temperature and pressure distribution throughout the adsorbent bed and their variation with adsorption time are also predicted. Use of artificial neural network (ANN) is proposed to determine the uptake from measured pressure and temperature. The back propagation algorithm with three different variants, namely, scaled conjugate gradient (SCG), Pola–Ribiere conjugate gradient (CGP), and Levenberg–Marquardt (LM) and logistic sigmoid transfer function are used, so that the best approach could be found out. After training, it is found that LM algorithm with 11 neurons is the most suitable for modeling adsorption refrigeration system. The adsorption and desorption uptake obtained experimentally are compared with the uptake predicted by D–R equation and ANN modeling.

References

References
1.
Anyanwu
,
E. E.
,
2000
, “
Environmental Pollution: Restricting the Refrigeration Industry as a Way Out
,”
Environ. Prot. Eng.
,
4
, pp.
1
27
.
2.
Saha
,
B. B.
,
Koyama
,
S.
,
Kashiwagi
,
T.
,
Akisawa
,
A.
,
Ng
,
K. C.
, and
Chua
,
H. T.
,
2003
, “
Waste Heat Driven Dual-Mode, Multi-Stage, Multi-Bed Regenerative Adsorption System
,”
Int. J. Refrig.
,
26
(
7
), pp.
749
757
.10.1016/S0140-7007(03)00074-4
3.
Wang
,
R. Z.
,
Jia
,
J. P.
,
Zhu
,
Y. H.
,
Teng
,
Y.
,
Wu
,
J. Y.
,
Cheng
,
J.
, and
Wang
,
Q. B.
,
1997
, “
Study on a New Solid Absorption Refrigeration Pair: Active Carbon Fiber–Methanol Pair
,”
Trans. ASME
,
119
(
3
), pp.
214
218
.
4.
Jing
,
H.
, and
Exell
,
R. H. B.
,
1993
, “
Adsorptive Properties of Activated/Charcoal/Methanol Combinations
,”
Renewable Energy
,
3
(
6,7
), pp.
567
575
.10.1016/0960-1481(93)90062-L
5.
El-Sharkawy
,
I.
,
Kuwahara
,
I. I.
,
Saha
,
K.
, and
Koyama
,
B. B.
,
2006
, “
Experimental Investigation of Activated Carbon Fibers/Ethanol Pairs for Adsorption Cooling System Application
,”
Appl. Therm. Eng.
,
26
(
8
), pp.
859
865
.10.1016/j.applthermaleng.2005.10.010
6.
El-Sharkawy
,
I.
,
Kuwahara
,
I. I.
,
Saha
,
K.
, and
Koyama
,
B. B.
,
2006
, “
A Study on the Kinetics of Ethanol-Activated Carbon Fiber: Theory and Experiments
,”
Int. J. Heat Mass Transfer
,
49
(
17
), pp.
3104
3110
.10.1016/j.ijheatmasstransfer.2006.02.029
7.
El-Sharkawy
,
I.
,
Kuwahara
,
I. I.
,
Saha
,
K.
, and
Koyama
,
B. B.
,
2008
, “
Experimental Investigation on Activated Carbon–Ethanol Pair for Solar Powered Adsorption Cooling Applications
,”
Int. J. Refrig.
,
31
(
8
), pp.
1407
1413
.10.1016/j.ijrefrig.2008.03.012
8.
Clausse
,
M.
,
Alam
,
K. C. A.
, and
Meunier
,
F.
,
2008
, “
Residential Air Conditioning and Heating by Means of Enhanced Solar Collectors Coupled to an Adsorption System
,”
Sol. Energy
,
82
(
10
), pp.
885
892
.10.1016/j.solener.2008.04.001
9.
Akkimaradi
,
B. S.
,
Prasad
,
M.
,
Dutta
,
P.
, and
Srinivasan
,
K.
,
2001
, “
Adsorption of 1,1,1,2-Tetrafluoro Ethane on Activated Charcoal
,”
J. Chem. Eng. Data
,
46
(
2
), pp.
417
422
.10.1021/je000277e
10.
Vasiliev
,
L. L.
,
Mishkinis
,
D. A.
,
Antukh
,
A. A.
, and
Vasiliev
,
L. L.
, Jr.
,
2001
,”
Solar–Gas Solid Sorption Heat Pump
,”
Appl. Therm. Eng.
,
21
(
5
), pp.
573
583
.10.1016/S1359-4311(00)00069-7
11.
Pons
,
M.
, and
Guilleminot
,
J. J.
,
1986
, “
Design of an Experimental Solar Powered, Solid Adsorption Ice Maker
,”
ASME J. Sol. Energy Eng.
,
103
(
4
), pp.
332
337
.10.1115/1.3268115
12.
Lin
,
S. H.
, and
Lin
,
R. C.
,
1999
, “
Prediction and Experimental Verification of HFC-134a Adsorption by Activated Carbons
,”
J. Environ. Sci. Health A
,
34
(
1
), pp.
183
200
.10.1080/10934529909376830
13.
Riffat
,
S. B.
,
Williams
,
M. D.
, and
Corr
,
S.
,
1997
, “
Adsorption Heat Pump Using HFC Refrigerants
,”
Int. J. Energy Res.
,
21
(
6
), pp.
481
495
.10.1002/(SICI)1099-114X(199705)21:6<481::AID-ER277>3.0.CO;2-7
14.
Gregg
,
S. J.
, and
Sing
,
K. S. W.
,
1984
,
Adsorption Surface Area and Porosity
,
Academic Press
,
London
.
15.
Sozen
,
A.
,
Menlik
,
T.
, and
Unvar
,
S.
,
2008
, “
Determination of Efficiency of Flat-Plate Solar Collectors Using Neural Network Approach
,”
Expert Syst. Appl.
,
35
(
4
), pp.
1533
1539
.10.1016/j.eswa.2007.08.080
16.
Kalogirou
,
S. A.
, and
Bojic
,
M.
,
2000
, “
Artificial Neural Networks for the Prediction of the Energy Consumption of a Passive Solar Building
,”
Energy
,
25
(
5
), pp.
479
491
.10.1016/S0360-5442(99)00086-9
17.
Bechtler
,
H.
,
Browne
,
M. W.
,
Bansal
,
P. K.
, and
Kecman
,
V.
,
2001
, “
New Approach to Dynamic Modeling of Vapour-Compression Liquid Chillers: Artificial Neural Networks
,”
Appl. Therm. Eng.
,
21
(
9
), pp.
941
953
.10.1016/S1359-4311(00)00093-4
18.
Holman
,
J. P.
,
2009
,
Experimental Methods for Engineers
,
7th ed.
,
Tata McGraw-Hill
,
New Delhi, India
.
You do not currently have access to this content.