Abstract
In this paper, estimating of hydrodynamics and heat transfer nanofluid flow through heated tube has been conducted by using Adaptive Neuro-Fuzzy Inference System (ANFIS). The CFD data related to three types of nanofluids (Al2O3, SiO2 and TiO2) flow in horizontal tube with 19 mm diameter and 2000 mm length. Heat flux around tube is fixed at 5000W/m2, the range of Reynolds number is (3000–30,000) and volume concentrations are (1% and 2%). ANFIS model has three input data presented by Reynolds number, volume concentration of nanofluids and materials and two output presented predicting friction factor and Nusselt number in the tube. The simulation results of proposed algorithm have been compared with CFD simulator in which the mean relative errors (MRE) are 0.1232% and 0.1123 for friction factor and Nusselt number respectively. Finally, ANFIS models can predict hydrodynamics and heat transfer of the higher accuracy than the developed correlations.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
