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Numerical investigation of an ammonia-hydrogen swirl burner

アンモニア-水素スワールバーナーの数値調査 (AI 翻訳)

Mehmet Anıl Gülşan, Y. E. Böke

Journal of Thermal Engineering📚 査読済 / ジャーナル2026-05-22#水素
DOI: 10.47481/jten.0003
原典: https://doi.org/10.47481/jten.0003

🤖 gxceed AI 要約

日本語

本研究では、アンモニア-水素混合燃料(体積比50-50)を用いた工業規模の旋回バーナーを数値シミュレーションした。当量比1.2(リッチ)と0.7(リーン)の条件で、3つの異なる反応機構を用いて3つの出力レベル(10、15、20 kW)で解析。実験データとの比較で温度予測の誤差は最大9%であり、数値モデルの有効性を示した。NH3とNOxの予測には改善の余地があるが、アンモニア燃焼技術の最適化に寄与する。

English

This study numerically simulates an industrial-scale tangential swirl burner using a 50-50 ammonia-hydrogen fuel blend by volume under rich (equivalence ratio 1.2) and lean (0.7) conditions at three power levels (10, 15, 20 kW) with three reaction mechanisms. Validation against experimental data shows temperature predictions within 9% deviation, demonstrating the effectiveness of numerical models for ammonia-hydrogen combustion analysis. Discrepancies in NH3 and NOx predictions highlight the need for further mechanism refinement, but the approach can accelerate burner optimization.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

日本ではアンモニア混焼・専焼技術が水素サプライチェーンの一環として注目されており、本シミュレーション手法は実機設計や燃焼制御の効率化に貢献しうる。特にガスタービンや工業炉への応用が期待される。

In the global GX context

Ammonia as a carbon-free fuel is gaining global attention for hard-to-abate sectors (shipping, power generation). This numerical study provides a methodology for optimizing burner design and reducing experimental costs, supporting the scale-up of ammonia-based combustion technologies worldwide.

👥 読者別の含意

🔬研究者:Provides a comparative evaluation of reaction mechanisms for ammonia-hydrogen combustion, offering benchmarks for model validation.

🏢実務担当者:Demonstrates that numerical simulations can reduce experimental workload for burner optimization, useful for combustion equipment designers.

📄 Abstract(原文)

Combustion always plays a crucial role in scientific research due to its complexity and diversity. In recent years, the global trend towards decarbonization has accelerated interest in carbon-free combustion technologies. Additionally, increasing demand for energy has prompted researchers to seek alternative energy sources beyond hydrocarbons. Among these, ammonia has emerged as a promising carbon-free fuel due to its favorable thermo-chemical properties and well-established supply chain infrastructure. While extensive experimental research has been carried out on ammonia combustion, investigating all relevant parameters is still challenging due to the requirement for advanced measurement technologies. At the same time, developments in computational power have considerably improved the capabilities of numerical simulations. In this study, an industrial-scale tangential swirl burner was numerically simulated. A 50–50 ammonia-hydrogen fuel blend by volume was used under both rich (equivalence ratio of 1.2) and lean (equivalence ratio of 0.7) conditions at three different power levels (10, 15, and 20 kW). The study offers new insight by comparing different reaction mechanisms and evaluating their performance in predicting the combustion behavior of ammonia-hydrogen mixtures. The burner model was described in detail, and the simulations were carried out using three different reaction mechanisms. Experimental temperature and exhaust emission data were used for validation of the model. The results indicate that numerical models are able to predict temperature distributions with a maximum deviation of 9%, showing that numerical simulations are effective tools for analyzing ammonia-hydrogen combustion. These results emphasize the importance of validating numerical models against experimental data. The study also shows that advanced simulation approaches can contribute to optimizing ammonia-hydrogen burners while reducing the need for extensive experimental work. This may accelerate the development of ammonia-based combustion technologies. Although the results are promising, discrepancies in the prediction of NH3 and NOx suggest that the reaction mechanisms still require further refinement. In future work, artificial intelligence and advanced computational techniques could improve the accuracy of these models and support the transition toward zero-carbon energy systems.

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