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The application of nanofluids in heat transfer systems is widely recognized for enhancing thermal efficiency compared to conventional fluids, representing a pivotal advancement in energy-saving strategies across a range of commercial applications. However, the selection of nanofluid concentration often lacks a systematic approach, with decisions made independently of specific application requirements, type of nanofluid, cost considerations, and economic factors such as energy cost and system lifetime. This article explores the optimization of nanoparticle concentrations in the immersion cooling system of a data center server, utilizing three distinct nanofluids (Al₂O₃-water, TiO₂-water, and CuO-water). The Iceotope immersion cooling designs were examined across various flow conditions. The investigation involved calculating heat transfer rates and pressure drops through the server by simulating a model using Computational Fluid Dynamics (CFD), Finite Element (FE), and COMSOL Multiphysics® Modeling software for varying volume fractions of nanoparticles. The study proposes a novel methodology to assess potential economic trade-offs associated with nanofluid utilization in immersed liquid-cooled data centers. This approach aims to identify the lowest overall cost within the data center and the maximum viable volume fraction of a nanofluid. Results indicate that Al2O3-water nanofluid exhibits superior thermal efficiency due to its higher thermal conductivity, while TiO₂-water and CuO-water are evaluated for comparative performance. However, it also presents challenges, such as higher viscosity leading to increased pressure drop and pumping costs. Economic considerations reveal that, despite its thermal advantages, the most cost-effective fluid is the conventional fluid (pure water). The server incurs a cost of $706.15. These findings underscore the importance of considering both thermal performance and economic factors when determining the optimal nanofluid concentration for practical application. |
