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

用于无碳能源应用的氨/氢混合物的湍流涡流稳定燃烧的基础知识

• 批准号: 2301485
• 负责人: Fabrizio Bisetti
• 金额: $ 55.5万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2301485&HistoricalAwards=false
• 关键词: Fundamentals; turbulent; swirl; stabilized; combustion

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.

由于二氧化碳对气候的负面影响，电力生产脱碳已成为社会当务之急。用无碳替代品替代化石燃料是一种便捷且实用的解决方案，因为它将利用现有的燃气轮机技术并进行有限的修改。虽然氨和氢是两种最可行的无碳燃料，但它们在与应用相关的制度中的燃烧行为和污染物排放尚未得到探索，阻碍了进展。该项目将提供此类混合物燃烧的全面理论，从而支持它们在无碳燃烧电力生产中的部署。尽管发电的关键方面很重要，例如其对经济、健康和气候变化的影响，但很大程度上不在公众讨论范围之内。拟议的工作将通过利用播客内容制作，提高人们对燃烧发电关键问题的认识和理解。拟议的工作将通过实现两个具体目标，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，生成实际配置中氨/氢混合物湍流火焰中关键湍流化学相互作用的综合数据库。该目标将通过考虑与富-快-稀分级燃烧相关的富预混涡流稳定湍流火焰并隔离湍流对火焰传播和氮氧化物（NOx）形成的影响来实现。第二个研究目标是通过应用基于相似理论的创新统计学习方法，利用数值和实验数据制定氨/氢混合物湍流火焰的可推广无量纲标度定律。该方法将经典的变量误差统计模型与渐近参数的相似性理论相结合。关于相似性机制的假设将通过贝叶斯模型选择进行评估。如果成功，拟议的研究将导致对氨/氢混合物中关键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定律的极限形式。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。