Multi-objective optimization of nanofluid-based direct absorption solar collector for low-temperature applications

• Published in: Journal of Building Engineering Vol. 72; p. 106258
• Main Authors: Baro, Rajani Kant, Kotecha, Prakash, Anandalakshmi, R.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.08.2023
• Subjects: Multi–objective differential evolution; Multi–objective genetic algorithm; Multi–objective particle swarm optimization; Nanofluid–based direct absorption solar collector; Temperature rise; Thermal efficiency; Temperature rise; Multi–objective genetic algorithm; Multi–objective differential evolution; Multi–objective particle swarm optimization; Thermal efficiency; Nanofluid–based direct absorption solar collector
• ISSN: 2352-7102; 2352-7102
• DOI: 10.1016/j.jobe.2023.106258

This article investigates the multi–objective optimization of nanofluid–based direct absorption solar collector (NDASC) for optimal thermal efficiency and temperature rise using a computational fluid dynamics-based optimization approach. The mass, momentum, and energy balance equations are solved for a three–dimensional computational model of NDASC. The wavelength–dependent radiative transport equation is numerically solved to yield the volumetric heat generation term in the energy balance equation. Thermal efficiency and temperature rise are chosen as objective functions with a maximum temperature rise of low-temperature NDASC as a constraint for multi–objective optimization. Conventional computational intelligence techniques such as the multi-objective genetic algorithm (MOGA), multi-objective particle swarm optimization (MOPSO), and multi-objective differential evolution (MODE) are employed. Decision variables such as geometrical parameters of the collector (length, width, and height), structural parameter of nanoparticles (volume fraction), and operational parameters of the collector (mass flow rate and fluid inlet temperature) showed a significant effect on the thermal efficiency and temperature rise of the NDASC. MOPSO outperformed other algorithms based on objective functions and solution convergence. Pareto solutions are obtained, and a sensitivity analysis is carried out using the corner point solutions of the Pareto determined by MOPSO as the reference. Temperature contours and profiles are also analyzed for the corner point solutions of the Pareto determined by MOPSO. The thermal efficiency of NDASC is found to be between 59.9% and 98.4%, with a temperature rise between 7.81 K and 71.93 K, subject to the constraint of Tin+ΔT<373K, where Tin and ΔT are the fluid inlet temperature and temperature rise for multi–objective optimization of NDASC. This work will aid in developing compact and efficient NDASC designs to deliver an optimal thermal efficiency and temperature rise required for a wider range of low-temperature residential and industrial applications.