<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:dc="http://purl.org/dc/elements/1.1/" version="2.0">
<channel>
<title>PhD Thesis</title>
<link>http://dspace.mist.ac.bd:8080/xmlui/handle/123456789/282</link>
<description/>
<pubDate>Tue, 21 Apr 2026 03:14:37 GMT</pubDate>
<dc:date>2026-04-21T03:14:37Z</dc:date>
<item>
<title>HEAT TRANSFER PERFORMANCE OF COOLING TOWER WITH  NANOFLUIDS</title>
<link>http://dspace.mist.ac.bd:8080/xmlui/handle/123456789/1038</link>
<description>HEAT TRANSFER PERFORMANCE OF COOLING TOWER WITH  NANOFLUIDS
RAHMAN, MD. HABIBUR
Cooling towers are evaporative heat transfer devices in which atmospheric air cools &#13;
warm water with direct contact between the air and the water by evaporating cooling of &#13;
water. The main objective of this study is to analysis the cooling tower performance, &#13;
with induced draft cooling tower and finding out the effect of adding nanofluids of Al &#13;
Oxide (Al2O3), Zn Oxide (ZnO), and Ti Oxide (Ti2O3) with base fluid as water. This &#13;
was done by establishing experimental set up supported with computer program and &#13;
varying the quality of circulating fluids by adding together at different ratio. Recently &#13;
large numbers of experiments have been carried out to evaluate the effect of nanofluid &#13;
in enhancement of the heat transfer rate in various heat exchangers. The heat transfer &#13;
enhancement using nanofluid mainly depends on type of nanoparticles, size of &#13;
nanoparticles, shape of nanoparticles, and type of base fluid and concentration of &#13;
nanoparticles in the base fluid. Therefore, this study deals with several experimental &#13;
investigation of the thermal performance of a prototype mechanical wet cooling tower &#13;
with a counter flow arrangement. Different volume concentrations ranging from 0.18 to &#13;
0.50 vol. % of stable Al Oxide (Al2O3), Zn Oxide (ZnO), and Ti Oxide (Ti2O3) &#13;
nanoparticles of 80, 35, and 70 nm diameter were considered. Water was taken as a &#13;
base fluid, and the experiment was carried out at 60, 70, and 80 °C, respectively, in &#13;
laboratory conditions. The study revealed that an increase in the volume concentration &#13;
of the nanofluids increased the cooling range, cooling efficiency, convective heat &#13;
transfer coefficient, tower characteristic called number of transfer unit (NTU), and &#13;
effectiveness of the cooling tower compared with water at the same mass flow rate and &#13;
inlet temperature. However, increasing the volume concentration increased the viscosity &#13;
of the nanofluids, leading to an increase in friction factor. From the result it has been &#13;
obtained a comparative study on terms of tower characteristics (kav/L), water to air &#13;
flow ratio (L/G), efficiency, range, percentage of make-up water and evaporation heat &#13;
loss are presented in graphical form. The graph shows that the performance of cooling &#13;
tower is affected by the type of cooling tower and the quality of circulating fluids. The &#13;
graphical analysis shows the cooling tower characteristics and efficiency decreases with &#13;
an increase in (L/G), the induced draft cooling tower shows better performance than &#13;
natural draft cooling tower. It is revealed that at higher volume concentration of &#13;
nanofluid, cooling range would increase by 29% at low flow rates which is also &#13;
vi &#13;
accompanied by the heat lost by water, and thereby, average increase in efficiency is &#13;
27% at temperature 80°C. This happens more significantly with Al2O3 and ZnO &#13;
nanoparticles when they are added in base fluid with different ratios. For instance, for &#13;
0.18% volume concentration of ZnO, at an inlet water temperature of 66.4 °C and &#13;
water/air (L/G) flow ratio of 1.93, the cooling range increased by 3.62%, cooling &#13;
efficiency increased by 33.3%, and NTU increased by 50.5% compared with fresh &#13;
water (FW). &#13;
Prediction of thermal performance is necessary for thermo-fluid engineering &#13;
applications as well as manufacturing industries. Hence, the validation of the developed &#13;
mathematical model in this study has been carried out by making comparison of the &#13;
measured and predicted thermal performance. This study presents an intelligent &#13;
approach based on fuzzy expert system (FES) of a cooling tower. FES links between &#13;
volumetric concentration (VC), mass flow rate of liquid to air ratio (L/G) and flow rate &#13;
(FR) and cooling efficiency (CE) and range (CR). To validate the mathematical model, &#13;
the thermal performance in terms of cooling efficiency (CE) and cooling range (CR), &#13;
L/G and liquid flow rate are measured on the developed cooling tower and compared &#13;
with the predicted ones. Values are obtained from experiments on an induced draft &#13;
cooling tower with nanofluids in different VC of 0%, 0.06%, 0.18% and 0.30%, &#13;
respectively. The efficiency of nanofluids slightly increases about 5.04–8.82% with the &#13;
growth of VC related to water at the highest value of L/G. Whereas, the efficiency &#13;
significantly increased about 11–50% with the increase of VC at the lowest value of &#13;
L/G. FES model has been developed for the prediction of cooling efficiency and range &#13;
with nanofluid in different VC. For instance, in case of CE, the mean of measured &#13;
(experiment) and predicted (FES) values have been found as 15.84% and 15.90%, &#13;
respectively. Similarly, for CR, the values have been found as 3.30°C and 3.28°C, &#13;
respectively. The correlation coefficients of cooling efficiency and cooling range are &#13;
found as 0.961, and 0.997, respectively. The mean relative error of measured and &#13;
predicted values from the FES model on cooling efficiency and cooling range are found &#13;
as 9.0 % and 5.87 %, respectively. For all parameters, the relative error of predicted &#13;
values are found to be less than the acceptable limits of 10 %. The goodness of fit of the &#13;
prediction values from the FES model on cooling efficiency and cooling range are &#13;
found as 0.960 and 0.987, respectively, which are found to be close to 1.0 as projected. &#13;
The results indicate that there is less variability of the measured data and predicted data &#13;
vii &#13;
of the counter flow induced draft cooling tower with water and with nanofluids in &#13;
different volume concentration. It also indicates that the predicted data over the &#13;
measured data has a good agreement and thus substantiates the validity of the &#13;
mathematical model. In this study, according to assessment principles of predicted &#13;
performance of the developed fuzzy expert system based intelligent model has been &#13;
found to be valid. It is an innovative adaption leading to technological capacity building &#13;
which has a remarkable contribution to enhance the machine life, better-efficient &#13;
outcome and friendly to the aquatic and environmental system.
At first, the author expresses his heartiest thanks to the Almighty Allah for giving the &#13;
patience and potentiality to complete the thesis work. I also express my appreciation to &#13;
all the people who have given their hearts whelming full support in preparing and &#13;
completing the study. &#13;
I am highly pleased to express my sincere and profound gratitude to my supervisor Dr. &#13;
Mohammad Ali, Professor, Department of Mechanical Engineering, Bangladesh &#13;
University of Engineering &amp; Technology (BUET), Dhaka, Bangladesh for providing me &#13;
the opportunity to conduct research on nanofluids for cooling tower. I wish to express &#13;
my deepest thanks to him for his continuous with patience guidance, suggestions, &#13;
inspiring advice, constructive suggestions with enthusiastic supervision and &#13;
wholehearted help throughout the course of the work. &#13;
I am also thankful to Lt Col Md. Altab Hossain, PhD, Associate Professor, Dept of &#13;
Nuclear Science and Engineering (NSE), Military Institute of Science and Technology &#13;
(MIST), Dhaka for his continuous guidance to shape my research work. I am also &#13;
grateful to Head and all Faculty Members, Dept of Mechanical Engineering for their &#13;
dedicated and relentless support both for literature and experimental work. &#13;
I would also express my deepest gratitude to my wife, my beloved sons and other &#13;
family members for their support and encouragement. &#13;
Finally, I am grateful to almighty Allah for enabling me to complete the thesis.
</description>
<pubDate>Tue, 01 Jul 2025 00:00:00 GMT</pubDate>
<guid isPermaLink="false">http://dspace.mist.ac.bd:8080/xmlui/handle/123456789/1038</guid>
<dc:date>2025-07-01T00:00:00Z</dc:date>
</item>
</channel>
</rss>
