Exergy efficiency enhancement in platinum–stainless steel microscale combustors via treed Gaussian process modeling

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This study investigates the optimization of a micro-combustion system by using a treed Gaussian process (TGP) to explore a multidimensional parameter space and thereby enhance performance. A platinum-coated stainless steel micro-reactor is analyzed, with the aim of optimizing entropy generation and second-law efficiency. The TGP model reduces prediction uncertainty by 70 %, facilitating efficient parameter exploration. The hydrogen equivalence ratio is found to contribute 65 % of the variance in the second law efficiency, and the methane velocity is also discovered to be crucial, with a first-order sensitivity index of 0.60 for thermal-conduction-related entropy generation. The optimized conditions lead to a second law efficiency of higher than 80 % under hydrogen and methane flow velocities of 0.5–0.9 m/s and equivalence ratios of 0.4–0.6. Hydrogen's role in promoting high-stability combustion is crucial, and the catalyst improves fuel oxidation and extends combustion limits. These findings provide a robust framework for designing high-efficiency micro-combustion systems and offer guidelines for minimizing irreversibility and maximizing the energy conversion efficiency. • TGP model used for exploring parameter space in micro-combustion systems. • Achieved exergy efficiency of over 80 % under optimal flow conditions (V H2 : 0.5–0.9). • TGP model reduced prediction uncertainty by 70 % with 10 sampling rounds. • Hydrogen equivalence ratio contributed 65 % to variance in second-law efficiency. • Second-law efficiency reached 80–90 % at V H2 and V CH4 of 0.5–0.9 with Φ H2 and Φ CH4 near 0.6.

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