A New Integrated Approach to Measurements and Modelling of Combustion Generated Particulate Matter

颗粒物排放对我们星球及其人口的健康都很重要。关于颗粒物（PM）的立法越来越严格，并且变化最大。然而，颗粒物排放是最难测量和最具挑战性的模型。简而言之，颗粒物本质上是烟尘（碳），其上吸附有未燃烧的碳氢化合物等物质，并且是所有燃烧过程所固有的。PM与全球变暖和严重的流行病问题有关，这导致了许多监管。最令人担忧的是不可见的亚微米颗粒，但正是这些小颗粒在人体呼吸系统中具有最大的沉积效率。虽然社会还不能取代燃烧，但技术发展可以寻求最大限度地减少PM排放。测量和建模PM排放的复杂性意味着建模者依赖于已发表的实验数据，这些数据可能是旧的和不完整的。此外，建模者没有机会具体说明实验。我们已经在非正式基础上进行了合作，但由于没有具体的资金，这种合作非常有限。该项目中的集成方法将使建模人员能够指定实验，确定最重要的测量，并创建一个可以填充相关实验数据的数据库。这将使建模人员能够立即访问完整的数据。Oxford拥有一台具有全面光学访问功能的火花点火发动机，以及一系列燃烧器：预混平焰（McKenna型）和并流（Santoro型，扩散火焰）。质量流量控制器允许我们改变核心流的当量比（纯燃料到弱极限，可选择稀释剂）和环形流的成分和流量（富氧或贫氧空气）。相同的燃料可用于发动机和燃烧器，在这两种情况下，燃料成分都可以控制测量能力- Oxford混合了专有和独特的PM测量设备。我们可以测量粒度分布、质量负载、组成、形态和表面积。我们还有一个独特的差分迁移率分析仪，允许在PM表征之前进行尺寸分离。我们有测量温度的技术，因为建模者认为这是最重要的。最重要的是，我们将应用新技术-激光诱导光栅光谱，LIGS温度测量的高精度和精度。在LIGS中，相干的、类似激光的信号光束提供了对背景散射和亮度的高分辨力，从而在炭黑火焰中提供了良好的信噪比。存在开发用于实验室或技术燃烧系统（如发动机、燃气轮机、焚化炉等）中火焰温度测量的可移动仪器的潜力。计算建模-剑桥将创建和改进描述燃烧化学和烟灰颗粒形成的计算模型。燃烧化学涉及成千上万的化学反应;模型必须包含足够的细节来描述重要的物种，但必须足够简洁，使数值评估成为可能。这样的模型存在，但包含许多参数，需要通过实验数据进一步完善。模拟烟尘颗粒的形成和生长更具挑战性。气相物质和颗粒表面之间的化学反应必须与粒子数平衡模型相结合，以预测颗粒的质量和尺寸。最终，详细的粒子和化学模型必须包括在发动机模型中。这些模型将用于进一步了解发动机中颗粒形成的机理，并由此找到减少颗粒形成并提高发动机效率的操作模式。

Particulate Matter emissions are important for the health of both our planet and its population. Legislation on Particulate Matter (PM) is increasingly stringent and subject to the greatest change. However, Particulate Matter emissions are both the most difficult to measure and the most challenging to model. In simple terms, Particulate Matter is essentially soot (carbon) onto which species such as unburned hydrocarbons are adsorbed, and is intrinsic to all combustion processes.PM has been linked to global warming and serious epidemiological issues, and this has led to much regulation. Of greatest concern are the sub-micron particles that are invisible, yet it is these small particles that have the greatest deposition efficiency in the human respiratory system. While society is not yet able to replace combustion, technological developments can seek to minimise PM emissions.The complexity of measuring and modelling PM emissions means that modellers are dependent on published experimental data which can be old and incomplete. Furthermore, the modellers have no opportunity to specify the experiments. We have already collaborated on an informal basis, but without specific funding this has been very restricted. The integrated approach in this project will enable the modellers to specify the experiments, identify the most important measurements, and create a database that can be populated with the relevant experimental data. This will provide the modellers with immediate access to complete data.Oxford has a spark ignition engine with comprehensive optical access, and a range of burners: pre-mixed flat-flame (McKenna type), and co-flow (Santoro type, diffusion flame). Mass flow controllers allow us to vary the equivalence ratio of the core flow (pure fuel to the weak limit, with a choice of diluents) and the composition and flow of the annular flow (oxygen enriched or depleted air). The same fuels can be used in both the engine and burners, and in both cases the fuel composition can be controlled Measurement Capabilities - Oxford has a mix of proprietary and unique equipment for PM measurements. We can measure size distributions, mass loadings, composition, morphology and surface area. We also have a unique Differential Mobility Analyser that allows size segregation prior to PM characterisation. We have techniques for measuring temperature, as this has been identified by the modellers as of paramount importance. Most significantly, we will apply the novel technique - Laser Induced Grating Spectroscopy, LIGS temperature measurements of high accuracy and precision. In LIGS, the coherent, laser-like signal beam offers high discrimination against background scattering and luminosity to give a good signal-to-noise ratio in sooting flames. Potential exists for developing a transportable instrument for thermometry of flames in laboratory or technical combustion systems such as engines, gas turbines, incinerators etc.Computational modelling - Cambridge will create and improve computational models which describe combustion chemistry and soot particle formation. Combustion chemistry involves thousands of chemical reactions; the model must contain enough detail to describe the species which are important but must be concise enough to make numerical evaluation possible. Such models exist, but contain many parameters which need further refinement via experimental data. Modelling the formation and growth of soot particles is even more challenging. The chemical reactions between gas phase species and particle surfaces have to be combined with a population balance model to predict the particle mass and size. Eventually a detailed particle and chemistry model must be included in an engine model. These models are to be used to understand the mechanism of particle formation in an engine further and with this find operating modes which reduce particle formation and increase the efficiency of the engine.