Sensitivity analysis and modeling of thermophysical properties of a hybrid nanofluid by use of different intelligent techniques
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27730%2F25%3A10258191" target="_blank" >RIV/61989100:27730/25:10258191 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S2590123025026684" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2590123025026684</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ijheatfluidflow.2025.109982" target="_blank" >10.1016/j.ijheatfluidflow.2025.109982</a>
Alternative languages
Result language
angličtina
Original language name
Sensitivity analysis and modeling of thermophysical properties of a hybrid nanofluid by use of different intelligent techniques
Original language description
The thermal conductivity and dynamic viscosity of nanofluids are essential factors in determining heat transfer and fluid flow characteristics. Intelligent methods have demonstrated great effectiveness for the precise estimation and modeling of these properties. The purpose of this study is to model both thermal conductivity and dynamic viscosity of a hybrid nanofluid, TiO2-SiO2/water-ethylene glycol, by application of three intelligent approaches namely Group Method of Data Handling (GMDH), Particle Swarm Optimization-Adaptive Neuro Fuzzy Inference System (PSO-ANFIS) and Genetic Algorithm-Adaptive Neuro Fuzzy Inference System (GA-ANFIS). The outcome of the study shows significant precision of the proposed models in estimation of the thermophysical properties. The most accurate models for thermal conductivity and dynamic viscosity are PSO-ANFIS and GMDH, respectively. R2 & and Average Absolute Relative Deviation (AARD) for the thermal conductivity and dynamic viscosity of the nanofluids with the most accurate models are 0.9907 & 0.41% and 0.9889 & 2.45%, respectively. Furthermore, sensitivity analysis is conducted on both properties of the nanofluid by considering temperature, concentration, and mixture ratio of the hybrid nanofluids and it is found that for both properties, temperature has the highest effect and is followed by the concentration.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20200 - Electrical engineering, Electronic engineering, Information engineering
Result continuities
Project
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Continuities
O - Projekt operacniho programu
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Journal of Heat and Fluid Flow
ISSN
0142-727X
e-ISSN
1879-2278
Volume of the periodical
116
Issue of the periodical within the volume
Volume 27, September 2025
Country of publishing house
US - UNITED STATES
Number of pages
11
Pages from-to
nestránkováno
UT code for WoS article
001534223000001
EID of the result in the Scopus database
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