Intelligent instrumentation for assessment and monitoring of hydrogen blend fuels in domestic boilers

大幅减少温室气体排放已成为到2050年实现净零排放的最大努力。在英国，家庭供暖本身占温室气体总排放量的17%，这与所有汽油和柴油汽车的贡献相当(BEIS，2022年1月)。因此，生活热的脱碳是一个很大的挑战。减少温室气体排放的可持续途径是用氢气(H2)取代天然气(NG)，因为H2的燃烧不会产生二氧化碳。然而，H2燃烧面临的挑战是，它的燃烧特性与NG(甲烷、CH4)有很大不同，例如，它的使用影响了燃烧稳定性、放热和NOx排放，并由于H2火焰温度较高而提高了燃烧速度。使用纯氢气也面临着各种技术挑战，如生产、安全、快速充电能力和低密度，这限制了其存储能力。在这个过渡阶段，一个可行的选择是使用氢含量更高的燃料(即与天然气混合20%以上)，这将是一个有希望的解决方案，与其他化石燃料相比，降低二氧化碳排放。然而，高富氢燃料对广泛使用的冷凝式供暖锅炉的影响还没有得到广泛的研究和充分的了解。H2的富集会导致更高的火焰自由基，如OH*、CN*、CH*和C2*，更高的燃烧温度和火焰的不稳定，从而引发更高的NOx生成。火焰自由基与燃烧结构、温度、放热和污染物排放密切相关。此外，国内的冷凝式锅炉使用预混圆柱形/表面燃烧器，这些燃烧器会产生一系列火焰。使用现有的测量系统来测量火焰阵列不同深度的火焰径向信息是极其困难的。因此，开发一种智能测量系统来评估和监测不同火焰深度处的火焰自由基排放和NOx生成过程，从而有助于深入了解不同H2/CH4混合燃料的燃烧过程。本项目将开发和实现一种基于多光谱光场成像的新型测量系统，用于评估和监测国产锅炉中不同H2/CH4混合燃料的火焰自由基和温度。将开发光场成像和深度重建模型，以生成针对不同光谱波段的不同深度的火焰自由基图像。开发的系统将提供独特的能力，在一次曝光中同时表征和量化火焰的基本信息和温度分布。该项目还将开发基于机器学习的智能数据驱动模型来预测NOx排放，从而促进国内锅炉性能的提高。首先在实验室规模的试验台上进行一系列实验，然后在不同的H2/CH4混合燃料和锅炉设置下在商用家用锅炉上进行一系列实验，以建立火焰自由基特性与NOx排放之间的关系。原型系统还将在燃气轮机试验台上进行测试，以评估其更广泛的适用性。通过实验研究了CO2、H2和NH3混合气体的燃烧特性，从而深入了解了混合气体中CO2/H2/NH3不同比例时的稳定区域和NOx排放，为深入了解H2混合气体的燃烧特性、了解国内锅炉的锅炉效率和污染物生成过程提供了依据。一旦该系统被开发出来，它将用于国内锅炉的设计，在项目期间产生的工程见解可以用于开发一种便携式诊断工具，用于混合燃料锅炉的常规监测。

Significant reduction of greenhouse gas emissions (GHG) has become the utmost endeavour to achieve net-zero emissions by 2050. In the UK, domestic heating itself is responsible for 17% of the total GHG emissions, this is comparable to the contribution of all petrol and diesel cars (BEIS, January 2022). Therefore, the decarbonization of domestic heat is a big challenge. A sustainable route to reduce GHG is to replace natural gas (NG) with hydrogen (H2) since the combustion of H2 does not produce CO2. However, the challenge for H2 combustion is that its combustion characteristics substantially differ from NG (methane, CH4), e.g., its use affects combustion stability, heat release and NOx emission, and increases the combustion rate due to a higher H2 flame temperature. Various technological challenges are also associated with using pure H2 such as its production, safety, quick charge capability and low density, which limits its storage capabilities. At this transitional stage, a practical option is the use of higher H2 enriched fuel (i.e., more than 20% blend with NG), which would be a promising solution to lower the CO2 emission compared with other fossil fuels. However, the impacts of higher H2 enriched fuels on the widely used condensing heating boilers are not extensively studied and fully understood. The H2 enrichment leads to higher flame radicals such as OH*, CN*, CH* and C2*, higher combustion temperature and flame destabilisation, thus triggering higher NOx formation. The flame radicals are closely related to the combustion structure, temperature, heat release and pollution emissions. Moreover, domestic condensing boilers use premixed cylindrical/surface burners, and these burners produce an array of flames. It is extremely difficult to measure flame radical information in different depths of the array of flames using existing measurement systems. The development of an intelligent instrumentation system has, therefore, become indispensable to assess and monitor the flame radical emissions and NOx formation process at different depths of flames, thus facilitating an in-depth understanding of the combustion process of different H2/CH4 blends.This project will develop and implement a new instrumentation system based on multi-spectral light field imaging to assess and monitor the flame radicals and temperatures with different H2/CH4 blends in domestic boilers. Light field image formation and depth reconstruction models will be developed to generate flame radical images at different depths for different spectral bands. The developed system will provide distinctive capabilities for characterising and quantifying the radical information and temperature profiles of a flame in a single exposure, simultaneously. The proposed project will also develop an intelligent data-driven model based on machine learning to predict NOx emission, thus, facilitating the improvement of domestic boiler performance. The relationships between flame radical characteristics and NOx emission will be established by conducting a series of experiments initially on a lab-scale test rig and then on commercial domestic boilers under different H2/CH4 blends and boiler settings. The prototype system will also be tested on a gas turbine test rig to evaluate its wider applicability. Experiments will be conducted to investigate the characteristics of CO2, H2 and ammonia (NH3) blend combustion, thus providing an in-depth understanding of stability regions and NOx emission with different proportions of CO2/H2/NH3 in the blend.The outcomes of this research will provide in-depth knowledge of the combustion characteristics of H2 blends, understanding of the boiler efficiency and pollutant formation process of domestic boilers. Once the system is developed, it will be used for the design of domestic boilers, and the engineering insights produced during the project could be used to develop a portable diagnostic tool for routine monitoring of blended-fuel boilers.