Intelligent design of high-performance fluids for thermal management: integrating response surface methodology,...

Area of Science:

• Materials Science
• Thermodynamics
• Chemical Engineering

Background:

• Optimizing nanofluid thermophysical properties (TPPs) is crucial for enhancing heat transfer applications.
• Existing studies often limit optimization to two objectives, hindering practical implementation.
• A need exists for a comprehensive framework to optimize multiple TPPs simultaneously.

Purpose of the Study:

• To develop and validate a novel multi-objective optimization framework for nanofluid TPPs.
• To integrate Response Surface Methodology (RSM) with Enhanced Hill Climbing (EHC) and Strength Pareto Evolutionary Algorithm II (SPEA-II).
• To utilize the Weighted Tchebycheff Method (WTM) for decision-making in selecting optimal nanofluids based on prioritized objectives.

Main Methods:

• Response Surface Methodology (RSM) was employed to model key thermophysical properties.
• Enhanced Hill Climbing (EHC) and Strength Pareto Evolutionary Algorithm II (SPEA-II) were integrated for multi-objective optimization.
• The Weighted Tchebycheff Method (WTM) facilitated the selection of optimal nanofluid configurations.

Main Results:

• RSM models exhibited high predictive accuracy (R² > 0.99) for density ratio, viscosity ratio, specific heat capacity ratio, and thermal conductivity ratio.
• The multi-objective optimization framework successfully identified optimal nanofluid compositions and operating conditions for various prioritization scenarios.
• Specific optimal conditions were determined for ZnO and CeO2 nanofluids, balancing properties like density, viscosity, specific heat capacity, and thermal conductivity.

Conclusions:

• The developed framework provides a reliable and accurate method for multi-objective optimization of nanofluid TPPs.
• The study demonstrates the capability to select optimal nanofluids tailored to specific engineering requirements and priorities.
• Findings highlight the versatility of ZnO, the heat storage advantage of Al2O3, and the high-temperature performance of CeO2 nanofluids.