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The Best Design for a Direct Evaporative Cooling System Based on Pressure Drop at Desired Saturation Efficiency: A Cost–Benefit Optimization

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Abstract

In this study, saturation efficiency and pressure drop, two critical parameters for the direct evaporative cooling phenomenon, were numerically investigated and optimized. For this purpose, the direct evaporative cooling process was simulated at inlet air velocities in the range of 1–3 m/s on different thicknesses of CELdek 7090 evaporative cooling pad from 100 to 300 mm. The mathematical model of pressure drop and saturation efficiency was developed by analyzing variance at R-squared values of 99.53% and 99.99%, respectively. Finally, the non-dominated sorting genetic algorithm II (NSGA-II) was applied to minimize the pressure drop while maximizing the saturation efficiency simultaneously. The results indicate that applying mathematical models makes it possible to predict the saturation efficiency and pressure drop of direct evaporative cooling systems with a 4% and 7.9% deviation, respectively. It can also be concluded that the pad thickness effect is more significant on the saturation efficiency than on the pressure drop. On the other hand, the inlet velocity has a greater impact on the pressure drop. NSGA-II optimization demonstrated that, regardless of the pad thickness, optimal saturation efficiency and pressure drop were obtained at the inlet air velocity of 1 m/s. Accordingly, when using direct evaporative cooling systems, efficiency and pressure drop can be optimized whenever the fan is set at a low speed. Depending on the researchers’ and designers’ goals, the findings of this research can be used in the design of direct evaporative cooling systems for different applications to achieve maximal saturation efficiency at the minimum possible energy consumption.

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Abbreviations

ANOVA:

Analysis of variance

CD:

Crowding distance

DEC:

Direct evaporative cooling

NSGA-II:

Non-dominated sorting genetic algorithm II

RSM:

Response surface method

C p :

Specific heat capacity (kJ/(kg K))

D :

Mass diffusion coefficient (m2/s)

H :

Height (mm)

h :

Specific enthalpy of moist air (kJ/kg)

h s :

Specific enthalpy of saturated air at wet-bulb temperature (kJ/kg)

k :

Thermal conductivity (W/(m K))

k a :

Volumetric mass transfer coefficient (kg/(m3 s))

L :

Width (mm)

m v :

Mass source term (Kg/m3)

P :

Pressure (pa)

q v :

Energy source term (W/m3)

T :

Temperature (°C)

d :

Pad thickness (mm)

V :

Velocity (m/s)

w :

Absolute humidity (Kgw/Kga)

w s :

Saturated air humidity (Kgw/Kga)

a:

Air

db:

Dry-bulb

in:

Inlet

out:

Outlet

w:

Water

wb:

Wet-bulb

η sat :

Saturation efficiency

ν :

Kinematic viscosity (m2/s)

ρ :

Density (Kg/m3)

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Authors

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Correspondence to Pedram Alamdari.

Appendices

Appendix A

This appendix presents the results of the unsteady DEC simulation. In Fig. 15, the temperature contours are shown in seconds 5, 10, and 15 for the 2 (m/s) inlet velocity, 37.06 (°C) inlet temperature, and 23.42 (°C) inlet wet-bulb temperature boundary condition. There is no discrepancy in the temperature contours from second 5, which indicates that the flow became steady in a few seconds.

Fig. 15
figure 15

The temperature contours in different seconds. a: second 5, b: second 10, and c: second 15

Appendix B

This appendix presents detailed saturation efficiency and pressure drop optimization output and their optimum inlet velocity and evaporative cooling pad thickness in Table 5.

Table 5 Optimum points by NSGA-II

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Alamdari, P., Rejvani, M., Alinejadi, S. et al. The Best Design for a Direct Evaporative Cooling System Based on Pressure Drop at Desired Saturation Efficiency: A Cost–Benefit Optimization. Iran J Sci Technol Trans Mech Eng (2024). https://doi.org/10.1007/s40997-023-00729-8

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  • DOI: https://doi.org/10.1007/s40997-023-00729-8

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