MONTE CARLO-BASED SENSITIVITY ANALYSIS OF FORCED CONVECTION HEAT TRANSFER IN METAL FOAM-COATED TUBE BANKS

Industrial heat exchangers, such as pre-coolers, require compact designs capable of delivering high thermal performance with minimal pressure loss. However, achieving this balance is challenging, especially when incorporating porous structures like metal foams that enhance heat transfer but introduce additional flow resistance. This study addresses the need for an optimized design by numerically and probabilistically analyzing forced convection in aluminum metal foam-coated tube banks under varying operating conditions. Using commercial computational fluid dynamics tools, the effects of metal foam thicknesses (0.75, 2, and 3.25 mm), porosities (0.90-0.95), and free-stream velocities (5-25 m/s) were evaluated on key performance indicators, i.e., Nusselt number, pressure drop, and outlet temperature. The Darcy-Forchheimer-Brinkman model and local thermal equilibrium energy model were used to capture flow and heat transfer within the porous domain. A Monte Carlo simulation framework, integrated with Sobol sensitivity analysis, quantified the influence of design parameters on thermal-hydraulic performance. Quantitatively, the metal foam-C configuration (2-mm thickness, 95% porosity) enhanced heat transfer by 30% with only a 15% increase in pressure drop compared to a bare tube, offering the best overall performance. Thicker foams (metal foam-A and metal foam-B, 3.25 mm) improved Nusselt number sensitivity by up to 50% but also increased pressure drop sensitivity by 35%- 40%, demonstrating the trade-off between enhancement and resistance. Foam thickness and porosity were identified as dominant factors influencing performance variability. The novelty of this study lies in its probabilistic sensitivity framework for heat exchanger optimization, a departure from conventional deterministic studies. The integration of Monte Carlo and Sobol analysis enables a robust, uncertainty-aware approach to metal foam selection and thermal design. These insights contribute to the development of energy-efficient heat exchangers optimized for performance and reliability under real-world variability.