| Modeling Convective Heat Transfer Augmentation of TiO2 Nanofluids Using Neural Networks |
| کد مقاله : 1027-CEC1402 |
| نویسندگان |
|
زینب پورامینی *1، زهره شهریاری2، مطهره وکیلی فتح آبادی3 1دانشگاه صنعتی سیرجان سیرجان ایران 2شرکت اوید انزیم پارس، شیراز،ایران 3دانشگاه آزاد اسلامی ،کرمان،ایران |
| چکیده مقاله |
| In this study, a neural network methodology was employed to estimate the forced convective heat transfer coefficient of nanofluids. Various operational parameters, including heat flux, thermal conductivity of fluids, nanoparticle concentration, and flow Reynolds number, were investigated to quantify the convective heat transfer coefficient. These operational parameters were introduced as inputs into an artificial neural network (ANN) to model the convective heat transfer coefficient. The addition of nanoparticles to the base fluid enhanced the forced convective heat transfer coefficient, with more significant effects observed in base fluids with lower thermal conductivity and flows characterized by higher Reynolds numbers and elevated heat fluxes. Good agreement between experimental data and the predicted results of the ANN demonstrates that the ANN can accurately model this process, except for higher heat flux. |
| کلیدواژه ها |
| Nanofluids, Forced convection, artificial neural networks, TiO2 nanoparticles |
| وضعیت: پذیرفته شده برای ارائه شفاهی |