A Multiscale Simulation Approach to Tackle Fuel Spray Atomisation and Combustion

作为产生世界80%电力的技术，化石燃料的燃烧将在未来几十年内继续在能源生产中发挥关键作用，并对碳排放做出重大贡献。在用于公路、空中和水上运输的移动的内燃机和用于发电站发电的固定式燃气轮机中，化石燃料的燃烧广泛地通过液体燃料喷射来实现，这决定了燃料效率和排放。它涉及复杂的多尺度，多物理，多相现象的级联，并已被确定为这些燃烧装置的基本研究需求。随着燃料市场中引入更多替代生物燃料，使得燃料性质更加复杂并且液体燃料喷射的控制更加困难，这种需求变得更加迫切。因此，未来的智能发动机需要精确控制各种燃料的喷射，这比迄今为止所能实现的要微妙得多。目前对燃料喷雾过程的数值研究可以分为两大类：（1）采用欧拉方法模拟密集喷雾区的初始破碎;（2）采用拉格朗日方法模拟连续燃烧--液滴相互作用在稀喷雾制度。然而，系统地研究燃油喷雾雾化和燃烧不能通过这两种方法实现。由于小液滴和薄带的分辨率要求，使用欧拉方法跟踪大量雾化液滴是困难的。对于拉格朗日方法，广泛使用的计算配置是均匀的各向同性/剪切湍流，或时间/空间发展的混合层或喷流满载点源液滴。由于缺少由密集喷雾区的一次破碎所决定的喷雾初始条件，喷雾燃烧的研究目前还处于早期的理论阶段，与指导和优化喷油设计的预期目标相距甚远，本项目提出了一种弥合两种方法之间的差距的思路来模拟燃油喷雾的雾化和燃烧，保持两种方法的优点，互补其缺点。集成的、多尺度的、混合的欧拉-拉格朗日模拟方法可用于在当前和未来的超级计算机上对燃料喷雾雾化和燃烧现象进行高保真模拟，并研究雾化液体燃料射流、雾化蒸发液滴、燃烧和湍流之间复杂的多边相互作用。开发这样的预测数值工具是实现完整的、预测模拟能力，用于设计和优化节能和清洁发动机。它可以广泛影响包括非公路发动机在内的运输发动机的设计，并有助于加速燃料市场中使用的各种生物燃料，为英国生物能源的关键新兴产业做出贡献。液体喷雾工艺也广泛用于其他研究学科，如医疗技术和先进制造。预测性数值工具有助于提高这些优先研究领域中喷涂过程的科学理解、设计和控制。

As the technology to generate the world's 80% power, combustion of fossil fuels will continue to play a key role in energy production over the next several decades and contributes heavily to carbon emission. In mobile internal combustion engines for road, air and water transportation and stationary gas turbines for electricity generation in power stations, the burning of fossil fuels is widely achieved by liquid fuel injection, which dictates fuel efficiency and emissions. It involves a cascade of complex multiscale, multiphysics, multiphase phenomena, and has been identified as a basic research need for these combustion devices. The need is becoming more urgent as more alternative biofuels are introduced in the fuel market, making the fuel properties more complex and the control of liquid fuel injection more difficult. Therefore, future smart engines require precise control of the injection of a broad variety of fuels that is far more subtle than what can be achieved to date.Currently numerical research on the fuel spray process can be divided in two principal categories: (1) using an Eulerian approach to simulate primary breakup in the dense spray regime and (2) using a Lagrangian approach to simulate turbulence-combustion-droplets interaction in the dilute spray regime. However, to systematically study fuel spray atomisation and combustion cannot be achieved by either approach. To track a large amount of atomised droplets using an Eulerian approach is difficult due to the resolution requirement for small droplets and thin ligaments. For Lagrangian approaches, the widely used computational configurations are homogeneous isotropic/shear turbulence, or temporally/spatially developing mixing layers or jets laden with point-source droplets. Missing important initial conditions of the atomising spray which are determined by primary breakup in the dense spray zone, the research on spray combustion is currently in an early theoretical stage and far from the expected goal of guiding and optimising the design of fuel injection.This project proposes an idea to bridge the gap between the two approaches to simulate fuel spray atomisation and combustion, by keeping the advantages of the two approaches and complementarily remedying their disadvantages with each other. The integrated, multiscale, hybrid Eulerian-Lagrangian simulation approach can be used to perform high-fidelity simulation of the fuel spray atomisation and combustion phenomena and investigate complex multilateral interactions among an atomising liquid-fuel jet, atomised evaporating droplets, combustion, and turbulence on current and future supercomputers.Developing such a predictive numerical tool is an essential first step toward the goal of a complete, predictive simulation capability for the design and optimisation of fuel-efficient and clean engines. It can impact broadly the design of transportation engines including off-highway engines and help the acceleration of diverse biofuels being used in the fuel market, contributing to key emerging industries of bioenergy in the UK. A liquid spray process is also widely used in other research disciplines such as Healthcare Technologies and Advanced Manufacturing. A predictive numerical tool can contribute to improving the scientific understanding, design and control of the spray processes in these prioritised research areas.