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<p>Hydrogen-enriched natural gas (methane) combustion is currently the most viable low-carbon combustion approach for gas turbine systems. However, the significantly different combustion characteristics of hydrogen compared to methane lead to complex effects of their mixing methods on NOx emission characteristics among combustion pollutants, rendering traditional rapid NOx emission prediction models no longer applicable. Based on an analysis of the flow field characteristics in a swirl combustor, this paper proposes a rapid prediction model using a chemical reactor network (CRN) to forecast NOx emissions under various hydrogen blending conditions. First, CFD simulations were employed to analyze the self-similar flow field structure of the swirl combustor. Subsequently, a simple and general CRN topology was developed to predict the impact of different hydrogen blending ratios and hydrogen injection methods on NOx emissions. The results demonstrate that the simplified CRN model constructed in this work can accurately predict NOx emission trends under different hydrogen blending strategies, exhibiting particularly strong predictive capability at high hydrogen blending ratios, thereby serving as an effective tool for the optimized design of hydrogen-enriched gas turbines.</p>

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Research on reduced-order modeling for prediction NOx emissions in a hydrogen-enriched methane swirl combustor

  • 期刊论文

  • 发表日期：

    2026年7月11日

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  • Tao Zhang,
  • Lianbo Cao,
  • Jiaxing Wu,
  • Yong Liu

摘要

Hydrogen-enriched natural gas (methane) combustion is currently the most viable low-carbon combustion approach for gas turbine systems. However, the significantly different combustion characteristics of hydrogen compared to methane lead to complex effects of their mixing methods on NOx emission characteristics among combustion pollutants, rendering traditional rapid NOx emission prediction models no longer applicable. Based on an analysis of the flow field characteristics in a swirl combustor, this paper proposes a rapid prediction model using a chemical reactor network (CRN) to forecast NOx emissions under various hydrogen blending conditions. First, CFD simulations were employed to analyze the self-similar flow field structure of the swirl combustor. Subsequently, a simple and general CRN topology was developed to predict the impact of different hydrogen blending ratios and hydrogen injection methods on NOx emissions. The results demonstrate that the simplified CRN model constructed in this work can accurately predict NOx emission trends under different hydrogen blending strategies, exhibiting particularly strong predictive capability at high hydrogen blending ratios, thereby serving as an effective tool for the optimized design of hydrogen-enriched gas turbines.