Collective impact of radiation on tetra hybrid nanofluid flow over a stretching sheet: Solar-powered charging station

Abstract

An enclosure with thermal radiation is widely engaged in the current decade due to the role of solar energy applications like photovoltaic panels, renewable power, solar light poles, oil recovery, solar vehicles, and solar pumps for water extraction. After getting motivated by these uses, the current scientific research is designed to address the energy crisis issue by capturing the high-level performance in solar-powered charging stations and to reveal the implications of thermal conduction together with the radiation influence on the flow of tetra hybrid nanofluid in a porous medium. This recent physical advancement is witnessed by employing conservation laws in the mathematical representation of nonlinear partial differential equations. The governed equations are turned into nondimensional ordinary differential equations by making use of the ideally suited similarity variables and cracked numerically. The scientific outcomes acquired in a specific scenario coincide with the findings retrieved from the earlier literature in order to standardize the deployed numerical approach. Moreover, the measurement of engineering concern is forecasted through the execution of both the multiple linear regression and multi-layer perceptron concerning energy in solar-powered charging stations. The current findings exhibit that the ( Ag ‐ Ti O 2 ‐ Cu ‐ A l 2 O 3 / EG ) provides a superior heat source than ( Si O 2 ‐ Ti O 2 ‐ Cu ‐ A l 2 O 3 / EG ) tetra hybrid nanofluid flow over an expandable sheet in solar power charging station. The coefficient of determination values of multiple linear regression and multi-layer perceptron models were developed to estimate the skin friction coefficient value for case 1 as 94.74 and 99.21 % , whereas these models for case 2 were obtained as 94.84 and 98.35 % , respectively. It shows that the proposed multi-layer perceptron model can forecast with higher precision and is a powerful engineering tool that can be effectively employed in tetra-hybrid nanofluid.