Graphical Abstract Figure
Graphical Abstract Figure
Close modal

Abstract

The wet bulb efficiency is an essential parameter in the performance of Indirect evaporative cooling systems, as it impacts efficiently cool air while minimizing energy usage. This paper focuses on model and optimizing multi-tubular-type wet channels for indirect evaporative cooler system. The optimized wet bulb efficiency is based on Box–Behnken experimental design model and response surface method. The methodology included predicting and optimizing input process and working flow parameters of indirect evaporative cooling system to maximize wet bulb efficiency. A quadratic model of response surface method was used to evaluate the influence of each factor on wet bulb efficiency, which was validated through analysis of variance results. The study found a maximum wet bulb efficiency of 89.65% under specific conditions, with a relative error of 3.25% between predicted and experimental results. This optimization process, governed by response surface method, determined essential parameters for enhancing the efficiency of the system. These parameters include inlet process temperature of 28 °C, working air velocity of 3.5 m/s, relative humidity of 45%, and inlet working air temperature of 24 °C. These results demonstrate practical significance of current research, providing useful insights for optimal design and optimization of indirect evaporative cooling systems to fulfill cooling requirements while minimizing energy consumption.

References

1.
Mehere
,
S. V.
,
Mudafale
,
K. P.
, and
Prayagi
,
S. V.
,
2014
, “
Review of Direct Evaporative Cooling System With Its Applications
,”
Int. J. Eng. Res. General Sci.
,
2
(
6
), pp.
995
999
. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=b2a663580f7a92390e335e83992472041ace09b6
2.
Watt
,
J. R.
, and
Brown
,
W. K.
,
1997
,
Evaporative Air Conditioning Handbook
, 3rd ed.,
The Fairmont Press
,
Lilburn, GA
.
3.
Santamouris
,
M.
, and
Vasilakopoulou
,
K.
,
2021
, “
Present and Future Energy Consumption of Buildings: Challenges and Opportunities Towards Decarbonization
,”
e-Prime—Adv. Electr. Eng., Electronics and Energy
,
1
(
11
), p.
100002
.
4.
Chen
,
Y.
,
Luo
,
Y.
, and
Yang
,
H.
,
2015
, “
A Simplified Analytical Model for Indirect Evaporative Cooling Considering Condensation From Fresh Air: Development and Application
,”
Energy Build.
,
108
(
12
), pp.
387
400
.
5.
Jaber
,
S.
, and
Ajib
,
S.
,
2011
, “
Evaporative Cooling as an Efficient System in the Mediterranean Region
,”
Appl. Therm. Eng.
,
31
(
14–15
), pp.
2590
2596
.
6.
Krüger
,
E.
,
Cruz
,
E. G.
, and
Givoni
,
B.
,
2010
, “
Effectiveness of Indirect Evaporative Cooling and Thermal Mass in a Hot Arid Climate
,”
Build. Environ.
,
45
(
6
), pp.
1422
1433
.
7.
Singh
,
V. K.
, and
Kumar
,
D.
,
2024
, “
An Experimental Investigation and Thermo-Economic Performance Analysis of Solar Desalination System by Using Nano-Enhanced PCM
,”
Mater. Today Sustain.
,
27
(
9
), p.
100884
.
8.
Delfani
,
S.
,
Esmaeelian
,
J.
,
Pasdarshahri
,
H.
, and
Karami
,
M.
,
2010
, “
Energy Saving Potential of an Indirect Evaporative Cooler as a Pre-Cooling Unit for Mechanical Cooling Systems in Iran
,”
Energy Build.
,
42
(
11
), pp.
2169
2176
.
9.
Liu
,
Z.
,
Allen
,
W.
, and
Modera
,
M.
,
2013
, “
Simplified Thermal Modeling of Indirect Evaporative Heat Exchangers
,”
HVAC&R Res.
,
19
(
3
), pp.
257
267
.
10.
Porumb
,
B.
,
Ungureşan
,
P.
,
Tutunaru
,
L. F.
,
Şerban
,
A.
, and
Bălan
,
M.
,
2016
, “
A Review of Indirect Evaporative Cooling Technology
,”
Energy Procedia
,
85
(
1
), pp.
461
471
.
11.
Tulsidasani
,
T. R.
,
Sawhney
,
R. L.
,
Singh
,
S. P.
, and
Sodha
,
M. S.
,
1997
, “
Recent Research on an Indirect Evaporative Cooler (IEC) Part 1: Optimization of the COP
,”
Int. J. Energy Res.
,
21
(
12
), pp.
1099
1108
.
12.
Jain
,
D.
,
2007
, “
Development and Testing of Two-Stage Evaporative Cooler
,”
Build. Environ.
,
42
(
7
), pp.
2549
2554
.
13.
Tripathi
,
R. J.
, and
Kumar
,
D.
,
2023
, “
Performance Assessment of Solar-Driven Indirect Evaporative Cooling With a Novel Wet Channel: An Experimental Study
,”
J. Build. Eng.
,
78
(
11
), p.
107674
.
14.
Zhang
,
Y.
,
Zhang
,
H.
,
Yang
,
H.
,
Chen
,
Y.
, and
Leung
,
C. W.
,
2022
, “
Counter-Crossflow Indirect Evaporative Cooling-Assisted Liquid Desiccant Dehumidifier: Model Development and Parameter Analysis
,”
Appl. Therm. Eng.
,
217
(
11
), p.
119231
.
15.
Wan
,
Y.
,
Huang
,
Z.
,
Soh
,
A.
, and
Jon Chua
,
K.
,
2023
, “
On the Performance Study of a Hybrid Indirect Evaporative Cooling and Latent-Heat Thermal Energy Storage System Under Commercial Operating Conditions
,”
Appl. Therm. Eng.
,
221
(
2
), p.
119902
.
16.
Zhou
,
B.
,
Lv
,
J.
,
Zhu
,
M.
,
Wang
,
L.
,
Liang
,
L.
, and
Chen
,
Q.
,
2023
, “
Simulation Study of a Thin Membrane Inclined Automatic Wicking Dew-Point Evaporative Cooling Device
,”
J. Build. Eng.
,
72
(
8
), p.
106601
.
17.
Pacak
,
A.
,
Baran
,
B.
,
Sierpowski
,
K.
,
Malecha
,
Z.
, and
Pandelidis
,
D.
,
2023
, “
Application of Computational Fluid Dynamics (CFD) Methods to Analyze Energy Efficiency of Indirect Evaporative Coolers
,”
Int. Commun. Heat Mass Transfer
,
143
(
4
), p.
106727
.
18.
Min
,
Y.
,
Chen
,
Y.
,
Shi
,
W.
, and
Yang
,
H.
,
2021
, “
Applicability of Indirect Evaporative Cooler for Energy Recovery in Hot and Humid Areas: Comparison With Heat Recovery Wheel
,”
Appl. Energy
,
287
(
4
), p.
116607
.
19.
Kiran
,
T. R.
, and
Rajput
,
S. P. S.
,
2011
, “
An Effectiveness Model for an Indirect Evaporative Cooling (IEC) System: Comparison of Artificial Neural Networks (ANN), Adaptive Neuro Fuzzy Inference System (ANFIS) and Fuzzy Inference System (FIS) Approach
,”
Appl. Soft Comput.
,
11
(
4
), pp.
3525
3533
.
20.
Pakari
,
A.
, and
Ghani
,
S.
,
2019
, “
Regression Models for Performance Prediction of Counter Flow Dew Point Evaporative Cooling Systems
,”
Energy Convers. Manage.
,
185
(
4
), pp.
562
573
.
21.
Baakeem
,
S. S.
,
Orfi
,
J.
, and
Mohamad
,
A.
,
2019
, “
The Possibility of Using a Novel Dew Point Air Cooling System (M-Cycle) for A/C Application in Arab Gulf Countries
,”
Build. Environ.
,
148
(
1
), pp.
185
197
.
22.
Yan
,
W.
,
Meng
,
X.
,
Cui
,
X.
,
Liu
,
Y.
,
Chen
,
Q.
, and
Jin
,
L.
,
2022
, “
Evaporative Cooling Performance Prediction and Multi-Objective Optimization for Hollow Fiber Membrane Module Using Response Surface Methodology
,”
Appl. Energy
,
325
(
11
), p.
119855
.
23.
Sun
,
T.
,
Tang
,
T.
,
Yang
,
C.
,
Yan
,
W.
,
Cui
,
X.
, and
Chu
,
J.
,
2023
, “
Cooling Performance and Optimization of a Tubular Indirect Evaporative Cooler Based on Response Surface Methodology
,”
Energy Build.
,
285
(
4
), p.
112880
.
24.
Chen
,
Y.
,
Yang
,
H.
, and
Luo
,
Y.
,
2017
, “
Parameter Sensitivity Analysis and Configuration Optimization of Indirect Evaporative Cooler (IEC) Considering Condensation
,”
Appl. Energy
,
194
(
5
), pp.
440
453
.
25.
Zhou
,
Y.
,
Zhang
,
T.
,
Wang
,
F.
, and
Yu
,
Y.
,
2020
, “
Numerical Study and Optimization of a Combined Thermoelectric Assisted Indirect Evaporative Cooling System
,”
J. Therm. Sci.
,
29
(
10
), pp.
1345
1354
.
26.
Chen
,
Q.
,
Ja
,
M. K.
,
Burhan
,
M.
,
Shahzad
,
M. W.
,
Ybyraiymkul
,
D.
,
Zheng
,
H.
, and
Ng
,
K. C.
,
2022
, “
Experimental Study of a Sustainable Cooling Process Hybridizing Indirect Evaporative Cooling and Mechanical Vapor Compression
,”
Energy Rep.
,
8
(
11
), pp.
7945
7956
.
27.
Shi
,
W.
,
Min
,
Y.
,
Ma
,
X.
,
Chen
,
Y.
, and
Yang
,
H.
,
2022
, “
Performance Evaluation of a Novel Plate-Type Porous Indirect Evaporative Cooling System: An Experimental Study
,”
J. Build. Eng.
,
48
(
5
), p.
103898
.
28.
Kousar
,
R.
,
Ali
,
M.
,
Amjad
,
M. K.
,
Sheikh
,
N. A.
, and
Ahmad
,
W.
,
2021
, “
Performance Characterization and Optimization of Counter-Flow Dew Point Indirect Evaporative Cooler Through Response Surface Methodology
,”
Proc. Inst. Mech. Eng., Part A: J. Power Energy
,
7
(
235
), pp.
1789
1805
.
29.
Sohani
,
A.
,
Sayyaadi
,
H.
, and
Zeraatpisheh
,
M.
,
2019
, “
Optimization Strategy by a General Approach to Enhance Improving Potential of Dew-Point Evaporative Coolers
,”
Energy Convers. Manage.
,
188
(
5
), pp.
177
213
.
30.
Heidarinejad
,
G.
, and
Moshari
,
S.
,
2015
, “
Novel Modeling of an Indirect Evaporative Cooling System With Cross-Flow Configuration
,”
Energy Build.
,
92
(
4
), pp.
351
362
.
31.
Woods
,
J.
, and
Kozubal
,
E.
,
2013
, “
A Desiccant-Enhanced Evaporative Air Conditioner: Numerical Model and Experiments
,”
Energy Convers. Manage.
,
65
(
1
), pp.
208
220
.
32.
Pakari
,
A.
, and
Ghani
,
S.
,
2019
, “
Comparison of 1D and 3D Heat and Mass Transfer Models of a Counter Flow Dew Point Evaporative Cooling System: Numerical and Experimental Study
,”
Int. J. Refrige.
,
99
(
3
), pp.
114
125
.
33.
Pandelidis
,
D.
, and
Anisimov
,
S.
,
2015
, “
Numerical Analysis of the Heat and Mass Transfer Processes in Selected M-Cycle Heat Exchangers for the Dew Point Evaporative Cooling
,”
Energy Convers. Manage.
,
90
(
1
), pp.
62
83
.
34.
Wan
,
Y.
,
Ren
,
C.
, and
Xing
,
L.
,
2017
, “
An Approach to the Analysis of Heat and Mass Transfer Characteristics in Indirect Evaporative Cooling With Counter Flow Configurations
,”
Int. J. Heat Mass Transfer
,
108
(
5
), pp.
1750
1763
.
35.
Tripathi
,
R. J.
, and
Kumar
,
D.
,
2024
, “
A Holistic Approach for Solar-Driven HVAC Evaporative Cooling System: Comparative Study of Dry and Wet Channel
,”
J. Build. Eng.
,
83
(
4
), p.
108465
.
36.
Reji
,
M.
, and
Kumar
,
R.
,
2022
, “
Response Surface Methodology (RSM): An Overview to Analyze Multivariate Data
,”
Ind. J. Microbiol. Res.
,
3
(
9
), pp.
241
248
.
37.
Khuri
,
A. I.
, and
Mukhopadhyay
,
S.
,
2010
, “
Response Surface Methodology
,”
Wiley Interdiscipl. Rev.: Comput. Stat.
,
2
(
2
), pp.
128
149
.
38.
Dean
,
A.
,
Voss
,
D.
, and
Draguljić
,
D.
,
2017
, “Response Surface Methodology: Design and Analysis of Experiments,”
Springer Texts in Statistics
,
Springer
,
Cham
.
39.
Ferreira
,
S. C.
,
Bruns
,
R. E.
,
Ferreira
,
H. S.
,
Matos
,
G. D.
,
David
,
J. M.
,
Brandão
,
G. C.
,
Dos Santos
,
W. N. L.
, et al
,
2007
, “
Box-Behnken Design: An Alternative for the Optimization of Analytical Methods
,”
Anal. Chim. Acta
,
2
(
597
), pp.
179
186
.
40.
Hill
,
W. J.
, and
Hunter
,
W. G.
,
1966
, “
A Review of Response Surface Methodology: A Literature Survey
,”
Technometrics
,
4
(
8
), pp.
571
590
.
41.
Baş
,
D.
, and
Boyacı
,
İH
,
2007
, “
Modeling and Optimization I: Usability of Response Surface Methodology
,”
J. Food Eng.
,
3
(
78
), pp.
836
845
.
42.
Boudjabi
,
A. F.
,
Maalouf
,
C.
,
Moussa
,
T.
,
Abada
,
D.
,
Rouag
,
D.
,
Lachi
,
M.
, and
Polidori
,
G.
,
2021
, “
Analysis and Multi-Response Optimization of Two Dew Point Cooler Configurations Using the Desirability Function Approach
,”
Energy Rep.
,
7
(
11
), pp.
5289
5304
.
You do not currently have access to this content.