DNS-driven development of predictive LES models for gas turbine emissions

减少污染物排放是燃气轮机燃烧室发展面临的主要挑战之一。在这种背景下，大涡模拟(LES)有助于降低开发成本和加快开发进程。因此，该项目的目标是改进航空发动机和固定式燃气轮机的LES排放模型。目前的提案是一个为期2年+2年的项目的第二阶段。对于航空发动机，重点是碳烟的建模。在第一阶段研究了碳烟的形成和氧化之后，第二阶段将对碳烟从富集区到贫油区的突破有更好的了解。由于航空发动机的湍流程度很高，当湍流涡流将烟尘从燃料丰富区域通过火焰输送到燃料贫化区域时，就会发生烟尘突破，速度足够快，无法使烟尘颗粒完全氧化。目前的LES模型不能足够准确地描述这些事件，因此严重低估了烟尘排放。在这个项目中，文献中现有的和在以前的项目阶段开发的最先进的LES模型将被扩展到考虑烟尘突破现象。这将通过三个步骤完成：1)为三种不同水平的烟尘突破生成一个域名系统数据库；2)基于域名系统对当前模型进行评估，并开发考虑烟尘突破的模型扩展；3)通过大涡模拟对实验室规模的喷射火焰配置和全模型燃烧室进行模型验证。在固定式燃气轮机中，将调查一氧化碳(CO)排放。这一阶段的目的是研究氢气(H2)加成甲烷(CH4)对CO排放的影响及其模拟。出发点是氢气作为未来能源载体的重要性。在这里，我们将考虑在固定燃气轮机中向天然气中添加少量氢气作为燃料。以前的工作已经表明，由于火焰速度的提高，即使是少量的H2也能显著减少CO排放。对CH4/H2混合气的湍流燃烧进行了一系列的数值模拟。将对DNS数据进行分析，以扩展目前的CO模型，以充分考虑H2添加的影响。整个模型将在两个模型燃烧室的大涡模拟中使用，并用实验数据进行验证。这一项目的资金是由发展集团和志愿人员联合会共同申请的。虽然拟议的两个工作方案涉及不同环境中的污染物形成，但通过将工作方案嵌入FVV的工业合作伙伴提供的项目支持中，可以建立牢固的联系。对于CO和碳烟的预测，将使用类似的建模方法和研究方法，以便联合模型开发可以导致对污染物形成的通用描述。

The reduction of pollutant emissions is one of the main challenges in the development of gas turbine combustors. In this context, large-eddy simulations (LES), can contribute to reducing development cost and accelerating development processes. Therefore, the aim of this project is the improvement of emission models for LES of both aeroengines and stationary gas turbines. The present proposal is for the second phase of a 2+2-year project. For aeroengines, the focus is on modeling of soot. After soot formation and oxidation have been investigated in the first project phase, a better understanding for the breakthrough of soot from rich to fuel-lean regions is intended in the second phase. Soot breakthrough occurs when, due to the high turbulence levels in aeroengines, turbulent eddies transport soot pockets from fuel rich regions through the flame to fuel lean regions fast enough that a complete oxidation of soot particles cannot take place. Current LES models cannot describe these events with sufficient accuracy, thus significantly underpredicting soot emissions. In this project, state of the art LES models available in the literature and developed in previous project phases will be extended to consider soot breakthrough phenomena. This will be done in a three-step process: 1) generation of a DNS data base for three different levels of soot breakthrough; 2) assessment of current models based on the DNS and development of model extensions considering soot breakthrough; 3) model validation via LES of a lab-scale jet flame configuration and of a full model combustor. In stationary gas turbines, carbon monoxide (CO) emissions will be investigated. The aim in this phase is to study the effect of the hydrogen (H2) addition to methane (CH4) on CO emissions and their modeling. Starting point is the importance of H2 as future energy carrier. Here, we will consider the addition of small amounts of H2 to natural gas as fuel in stationary gas turbines. Previous work has shown the ability of even small amounts of H2 to significantly reduce CO emissions as a result of the increased flame speeds. A series of DNS of turbulent combustion of CH4/H2 mixtures will be performed. The DNS data will be analyzed to extend the present CO model to adequately consider the effects of H2 addition. The full model will be used in the LES of two model combustion chambers and validated with experimental data. Funding for this project is requested jointly from the DFG and the FVV. While the two proposed work packages address pollutant formation in different environments, strong connections are given by the embedding of the work packages in the project support provided by industrial partners of the FVV. Similar modeling approaches and research methodologies will be used for the prediction of CO and soot, so that the joint model development can lead to a generic description of pollutant formation.