Work

Heat transfer analysis of Cu-Water nanofluid in a square enclosure using Caputo fractional derivative and machine learning

Year: 2024

Type: article

Abstract: Fractional-based fluid transport modeling provides a deeper and more comprehensive understanding of the thermophysical properties of small-scale fluids and polymer solutions . Moreover, the fractional-order fluid dynamics framework finds applications in various fields, including renewable energy systems , thermal energy storage , and oil storage tanks. Inspired by these developments, the current study addresses the computational challenges inherent in modeling nanofluid dynamics within a square enclosure by introducing a fractional-order approach to enhance the simulation of buoyant flow and heat transport . Our model integrates the linear interpolation ( L 1 approach) and finite difference approximation for temporal and spatial derivatives by utilizing the Caputo time-fractional derivative instead of the conventional time derivative. This integration facilitates the use of the Backward Difference Alternating Direction Implicit (BD-ADI) method, which was specifically chosen to reduce the computational burden associated with the non-local characteristics of fractional models. Our results show that by altering the fractional order , significant improvements in heat transfer efficiency are achieved compared to classical models. For instance, compared to the integer order, a lower fractional-order parameter of γ = 0 . 80 with a 4% nanoparticle volume fraction at a Rayleigh number of 1 0 3 increases the heat transfer rate by 15.77%. However, at a Rayleigh number of 1 0 6 , the enhancement reduces to 4.15%, indicating that fractional adjustments’ influence diminishes at higher thermal buoyancy levels. This behavior of the fractional-order nanofluid model, influenced by thermal buoyancy force , has been investigated by using a Multiple Linear Regression(MLR) analysis with 258 numerical samples. Besides, MLR analysis further identifies the nanoparticle volume fraction as a critical factor, influencing the heat transfer rate by 10.48% at lower fractional-order settings.

Source: Case Studies in Thermal Engineering

DOI: 10.1016/j.csite.2024.105481

Authors: Muhammad Ismail, N. Keerthi Reddy, H. Thameem Basha, Bongsoo Jang

Institution: Ulsan National Institute of Science and Technology

Language: English

Topic: Nanofluid Flow and Heat Transfer

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,210

Funder: National Research Foundation of Korea