Surrogate-Based Multiobjective Design Optimization of a Hydrogen Burner to Balance NOxEmissions and Temperature

Dang Khoi Le, Cong Phuong Nguyen, Min Jung Lee, Hyunguk Kwon

Research output: Contribution to journalArticlepeer-review

Abstract

In hydrogen combustion, efforts to reduce NOxemissions often lead to a decrease in combustion temperature, highlighting a fundamental trade-off between thermal efficiency and pollutant formation. This study addresses this challenge through a multiobjective optimization of a pure hydrogen-fueled burner, aiming to simultaneously minimize NOxemissions and maximize combustion temperature. Computational Fluid Dynamics (CFD), Response Surface Methodology (RSM), and a Genetic Algorithm (GA) were integrated to explore and optimize burner geometry. CFD simulations using the realizable k-ε turbulence model and eddy dissipation concept were validated against experimental data in previous work, showing good agreement with a temperature mean absolute percentage error of approximately 5% and NOxerror below 2%, confirming the reliability of the numerical approach. To enable surrogate model training, CFD simulations and sensitivity analysis were first performed. Four out of six geometric parameters were identified as influential and subsequently perturbed to generate the training data set. A third-order RSM was used to capture the highly nonlinear relationships between geometric variables and performance outcomes. Three representative optimal designs were selected from the final Pareto front generated by the GA: one prioritizing NOxminimization, one maximizing temperature, and one offering a balanced trade-off. The optimized designs achieved significant performance improvements. Among the Pareto-optimal solutions, one design achieves a 29.6% reduction in NOxemissions and a 7.8% increase in combustion temperature, demonstrating overall performance enhancement through improved air–fuel mixing and reduced residence time in the primary combustion zone. These results demonstrate the effectiveness of the proposed CFD-RSM-GA framework as a robust approach for multiobjective optimization. It enables the systematic design of hydrogen burners that meet both stringent environmental regulations and high thermal performance demands.

Original languageEnglish
Pages (from-to)19912-19923
Number of pages12
JournalEnergy and Fuels
Volume39
Issue number41
DOIs
StatePublished - 16 Oct 2025

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