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，产量的脱碳是社会的命令。用无碳替代品代替化石燃料是一种权宜且实用的解决方案，因为它将利用有限的修改来利用现有的燃气轮机技术。虽然氨和氢是两个最有生存的无碳燃料，但与应用相关的制度中，它们的燃烧行为和污染物排放尚未开发，这阻碍了进度。该项目将提供有关此类混合物的燃烧的全面理论，从而支持其部署基于无碳的电力生产。尽管它们的重要性，但发电的关键方面（例如对经济，健康和气候变化的影响）在很大程度上远远超出了公共话语。拟议的工作将通过利用播客内容生产来提高对基于燃烧的发电的关键问题的认识和理解。拟议的工作将加速氨/氢燃料混合物的部署，以实现两个特定的目标，从而为基于燃烧的电力生产提供基于燃烧的电力。第一个研究目标是通过大尺度高效率直接数值模拟和基于激光器的光学诊断的大规模高效率直接数值模拟和实验测量。通过考虑与丰富的涡流式燃烧相关的丰富预混合漩涡状的湍流火焰，并隔离湍流对氮（NOX）氧化氧化物的影响和形成的影响，可以实现这一目标。第二个研究目标是利用数值和实验数据来通过基于相似性理论应用创新的统计学习方法来制定氨/氢混合的湍流火焰的无限尺度定律。该方法将经典错误中的错误统计模型与渐近参数的相似性理论结合在一起。关于相似性制度的假设将通过贝叶斯模型选择评估。如果成功，提出的研究将导致对氨/氢混合物中关键湍流化学相互作用的系统理解，并证明了一种全新的统计学习方法，从中，目的是发现无限制尺度定律的极限形式在渐近参数中的限制形式。这一奖项反映了NSF的法定任务，反映了经过评估的范围，这是通过评估的范围来进行的。