Fundamentals of turbulent swirl-stabilized combustion of ammonia/hydrogen blends for carbon-free energy applications

由于二氧化碳对气候的负面影响，电力生产的脱碳是社会的当务之急。用无碳替代品替代化石燃料是一种权宜之计和实用的解决方案，因为它可以利用现有的燃气轮机技术，只需进行有限的修改。虽然氨和氢是两种最可行的无碳燃料，但它们的燃烧行为和污染物排放在与应用相关的制度中尚未得到探索，阻碍了进展。该项目将提供此类混合物燃烧的综合理论，从而支持其在无碳燃烧电力生产中的应用。尽管发电很重要，但其关键方面，如对经济、健康和气候变化的影响，在很大程度上不在公众讨论之列。拟议的工作将通过利用播客内容生产，提高对燃烧发电关键问题的认识和理解。拟议的工作将通过满足两个具体目标，加速用于燃烧发电的氨/氢燃料混合物的部署。第一个研究目标是通过大规模高保真直接数值模拟和基于激光光学诊断的实验测量，在实际配置中生成氨/氢混合湍流火焰中关键湍流化学相互作用的综合数据库。这一目标将通过考虑与富-快-贫阶段燃烧相关的富预混涡流稳定湍流火焰来实现，并分离湍流对火焰传播和氮氧化物（NOx）形成的影响。第二个研究目标是利用数值和实验数据，应用基于相似理论的创新统计学习方法，为氨/氢混合物湍流火焰制定可推广的无量纲标度定律。该方法将经典的变量误差统计模型与渐近参数相似理论相结合。关于相似性的假设将通过贝叶斯模型选择进行评估。如果成功，所提出的研究将导致对氨/氢混合物中临界湍流化学相互作用的系统理解，并展示一种全新的统计学习方法，其目标是发现渐近参数中无量纲标度律的极限形式。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Due to the negative impact of carbon dioxide on climate, decarbonization of electricity production is a societal imperative. Replacement of fossil fuels with carbon-free alternatives is an expedient and practical solution because it would leverage existing gas turbine technology with limited modifications. While ammonia and hydrogen are two most viable carbon-free fuels, their combustion behavior and pollutants emissions in regimes relevant to applications are unexplored, hindering progress. This project will provide a comprehensive theory of the combustion of such blends, thereby supporting their deployment for carbon-free combustion-based electricity production. Despite their importance, key aspects of power generation, such as its impacts on economy, health, and climate change, are largely outside of the public discourse. Proposed work will lead to more awareness and understanding of key issues in combustion-based electricity generation by leveraging podcast content production.The proposed work will accelerate the deployment of ammonia/hydrogen fuel blends for combustion-based electricity production by meeting two specific objectives. The first research objective is to generate a comprehensive database of key turbulence-chemistry interactions in turbulent flames of ammonia/hydrogen blends in practical configurations via large-scale high-fidelity Direct Numerical Simulations and experimental measurements with laser-based optical diagnostics. This objective will be achieved by considering rich premixed swirl-stabilized turbulent flames relevant to Rich-Quick-Lean staged combustion and isolate the effects of turbulence on flame propagation and formation of oxides of nitrogen (NOx). The second research objective is to leverage numerical and experimental data to formulate generalizable dimensionless scaling laws for turbulent flames of ammonia/hydrogen blends by applying an innovative statistical learning approach based on similarity theory. The approach combines classical error-in-variables statistical models with the theory of similarity in asymptotic parameters. Hypotheses on regimes of similarity will be evaluated via Bayesian model selection. If successful, proposed research will lead to the systematic understanding of critical turbulence-chemistry interactions in ammonia/hydrogen mixtures and demonstrate an entirely new approach to statistical learning, whereby the objective is to discover limit forms of dimensionless scaling laws in asymptotic parameters.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.