MARC ayrıntıları
| 000 -BAŞLIK |
|---|
| Sabit Uzunluktaki Kontrol Alanı |
03910nam a22003137a 4500 |
| 003 - KONTROL NUMARASI KİMLİĞİ |
|---|
| Kontrol Alanı |
KOHA_MİRAKIL |
| 005 - EN SON İŞLEM TARİHİ ve ZAMANI |
|---|
| Kontrol Alanı |
20221226090234.0 |
| 008 - SABİT UZUNLUKTAKİ VERİ ÖGELERİ - GENEL BİLGİ |
|---|
| Sabit Alan |
211019d2021 cy ||||| m||| 00| 0 eng d |
| 040 ## - KATALOGLAMA KAYNAĞI |
|---|
| Özgün Kataloglama Kurumu |
CY-NiCIU |
| Kataloglama Dili |
eng |
| Çeviri Kurumu |
CY-NiCIU |
| Açıklama Kuralları |
rda |
| 041 ## - DİL KODU |
|---|
| Metin ya da ses kaydının dil kodu |
eng |
| 090 ## - Yerel Tasnif No |
|---|
| tasnif no |
D 258 |
| Cutter no |
A38 2021 |
| 100 1# - KİŞİ ADI |
|---|
| Yazar Adı (Kişi adı) |
Adun, Humphrey |
| 245 10 - ESER ADI BİLDİRİMİ |
|---|
| Başlık |
UTILIZATION OF THREE-PARTICLE (TERNARY) NANOFLUID FOR COOLING IN PHOTOVOLTAIC/THERMAL COLLECTORS / |
| Sorumluluk Bildirimi |
Humphrey ADUN; Supervisor: Prof. Dr. Mustafa DAGBASI |
| 264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Date of production, publication, distribution, manufacture, or copyright notice |
2021 |
| 300 ## - FİZİKSEL TANIMLAMA |
|---|
| Sayfa, Cilt vb. |
181 sheets; |
| Boyutları |
31 cm. |
| Birlikteki Materyal |
Includes CD |
| 336 ## - CONTENT TYPE |
|---|
| Source |
rdacontent |
| Content type term |
text |
| Content type code |
txt |
| 337 ## - MEDIA TYPE |
|---|
| Source |
rdamedia |
| Media type term |
unmediated |
| Media type code |
n |
| 338 ## - CARRIER TYPE |
|---|
| Source |
rdacarrier |
| Carrier type term |
volume |
| Carrier type code |
nc |
| 502 ## - TEZ NOTU |
|---|
| Tez Notu |
Thesis (PHD) - Cyprus International University. Institute of Graduate Studies and Research Department of Energy Systems Engineering |
| 504 ## - BİBLİYOGRAFİ NOTU |
|---|
| Bibliyografi Notu |
Includes bibliography (sheets 151-181) |
| 520 ## - ÖZET NOTU |
|---|
| Özet notu |
ABSTRACT The current situation of significantly higher fossil fuel production for meeting growing energy demands, as against renewable energy sources, despite the global consensus on their adverse environmental effects, is a monumental issue. Also, considering depleting fossil fuel reserves, the need to produce efficient renewable energy technologies is crucial. The abundance of solar energy makes it an important renewable energy in meeting growing global energy demands. Solar radiation is a source of both heat and light, for which photovoltaic (PV) cells have been constructed to utilize the visual part of the light to produce electricity. The incorporation of thermal collectors in PV systems has further increased their total efficiencies. While significant progress has been made in the structural designs of photovoltaic/thermal (PV/T) systems, the invention of nanofluids, have allowed extracting more heat from panels, due to their significant higher thermophysical properties, as compared to conventional heat transfer fluids (HTFs). This study undergoes a comprehensive experimental and numerical study on novel ternary hybrid nanofluids (THNF) (3-particle nanofluids), and their application as HTFs in PV/T systems. A novel Al2O3-ZnO-Fe3O4 nanofluid is synthesized, with characterization and stability tests, carried out. The effect of mixture ratio, volume fraction, particle size, and temperature on their thermophysical properties are investigated. Furthermore, machine learning algorithms are developed to accurately estimate the behaviour of the fluid. This study also numerically investigates the efficiency of the PV/T system, assessing the effects of mass flow rate, solar radiation, and volume fraction. Meteorological data retrieved from the Cyprus International University was used in validating the model designed for the PV/T system. The result in this study showed that the mixture ratio of THNF has a huge effect in achieving an optimum thermophysical property for HTF application in the PV/T system. The optimum mixture ratio retrieved was for the 1:1:1 mixture ratio. Also, this study concludes that the advantage of THNF over conventional and hybrid nanofluids is their higher efficiency at higher volume fractions. Furthermore, this study developed an accurate artificial neural network model, for estimating the thermal conductivity of hybrid nanofluids, across different combinations of nanoparticles, and base fluids. Conclusively, this study gives a clear path for future experimental works that will incorporate hybrid nanofluids, as the optimum volume fraction, temperature, and mixture ratio is discussed. |
| 650 #0 - KONU BAŞLIĞI EK GİRİŞ - KONU TERİMİ |
|---|
| Konusal terim veya coğrafi ad |
Neural networks (Computer science) |
| Alt başlık biçimi |
Dissertations, Academic |
| 650 #0 - KONU BAŞLIĞI EK GİRİŞ - KONU TERİMİ |
|---|
| Konusal terim veya coğrafi ad |
Nanofluids |
| Alt başlık biçimi |
Dissertations, Academic |
| 650 #0 - KONU BAŞLIĞI EK GİRİŞ - KONU TERİMİ |
|---|
| Konusal terim veya coğrafi ad |
Photovoltaics |
| Alt başlık biçimi |
Dissertations, Academic |
| 650 #0 - KONU BAŞLIĞI EK GİRİŞ - KONU TERİMİ |
|---|
| Konusal terim veya coğrafi ad |
Thermal conductivity |
| Alt başlık biçimi |
Dissertations, Academic |
| 700 1# - EK GİRİŞ - KİŞİ ADI |
|---|
| Yazar Adı (Kişi adı) |
Dağbaşı, Mustafa |
| İlişkili Terim |
supervisor |
| 9 (RLIN) |
1666 |
| 942 ## - EK GİRİŞ ÖGELERİ (KOHA) |
|---|
| Sınıflama Kaynağı |
Dewey Onlu Sınıflama Sistemi |
| Materyal Türü |
Thesis |