A comprehensive optimization and energy conservation assessment of R1234yf-based hybrid nanorefrigerants for sustainable HVAC applications: Thermodynamic, economic, environmental and AI

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In this study, authors present a complete energy system optimization framework of R1234yf based hybrid nanorefrigerant and hybrid nanolubricant system for improving the thermodynamic, economic, environmental and energy performance of vapor compression refrigeration system for Indian operating conditions. Six nano-particles (Al₂O₃, TiO₂, CuO, SiO₂, graphene nanoplatelets (GNP) and multi-walled carbon nanotubes (MWCNT)) were assessed for the thermophysical parameters, dispersion stability, coefficient of performance (COP) of the system, exergy efficiency, energy consumption of the compressor, life-cycle economics, environmental impact, and artificial intelligence-based prediction. The results show that the thermal conductivities of nanorefrigerants are significantly better than those of the conventional refrigerants, and the COP of the R1234yf system is improved closer to the COP of the conventional refrigerants, with the Al₂O₃–SiO₂/PAG hybrid nanolubricant being more stable, while also reducing the power consumption of the compressor and improving the exergy efficiency. Both economic analysis and environmental assessment show good payback periods and significant reductions in indirect carbon emissions. The energy optimization of the system can be performed quickly and accurately with high reliability using the artificial neural network models. The proposed hybrid nanorefrigerant approach not only enables energy conservation and sustainable cooling but also paved a way for the HVAC systems to be compatible with renewable energy resources and to become low-carbon refrigeration technologies, directly contributing to Sustainable Development Goal 7 (Affordable and Clean Energy) via its high energy efficiency and its contribution to cooling in an environmentally friendly way.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.