Multi-Objective Optimization of Heat Transfer and Entropy Generation in Bio-Inspired Tubes via Hybrid Multi-Criteria Decision-Making

Passive enhancement techniques are crucial for improving the energy efficiency of heat exchangers. In this study, the thermodynamic performance of novel bio-inspired turbulators (FishScale, DragonEgg, and WavyCell) was experimentally investigated in the turbulent flow regime (Re: 10500–15000). A novel Consensus Multi-Criteria Decision-Making (MCDM) strategy was employed to identify the robust optimal design. The MEREC method determined the criteria weights as 0.4744 for the friction factor, 0.2997 for the Nusselt number, and 0.2286 for the total entropy generation. Results revealed a 'methodological sensitivity' among VIKOR, WASPAS, and MABAC, which initially identified different optimal designs. To resolve this, a Rank Sum consensus method was implemented. The consensus analysis demonstrated that the FishScale-2 Piece design at Re=15,000 achieved the most robust performance across all methodologies. This study highlights that relying on a single MCDM method in thermodynamic optimization can lead to biased results, whereas the proposed consensus-based approach provides a definitive solution by balancing heat transfer enhancement (Nu) against hydraulic (f) and thermodynamic (Sgen,total) penalties with high mathematical reliability.