Modelling differential diffusion using sparse particle methods

使用稀疏粒子方法模拟微分扩散

• 批准号: 439610422
• 负责人: Professor Dr. Andreas Kronenburg
• 金额: --
• 依托单位: Institut für Technische Verbrennung (ITV)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/439610422?language=en
• 关键词: Modelling; differential; diffusion; using; sparse

Diffusion is one of the key mechanisms that govern – at molecular scale - the mixture composition and therefore the dynamics of combustion processes. Due to the varying size of the molecules, species diffuse at different velocities (differential diffusion) and this leads to -opposite equal diffusivity cases – a decorrelation of species and therefore to different ignition characteristics, flame structures and flame dynamics. Despite ample evidence of these effects, the vast majority of combustion simulations assumes equal diffusivities. This is justified by the assumption of dominant turbulent mixing the opposes the effects of differential diffusion. Conversely, differences between simulations and experiments are often justified by differential diffusion: this, however, remains hypothetical as proof cannot be given due to a lack of convincing models for closure of differential diffusion effects in turbulent flames.Carbon reduced or even carbon-free combustion renders the topic of varying transport characteristics once again timely and topical. Not only hydrogen enriched combustion (e.g. hydrogen addition to our natural gas supply networks) but also alternative concepts based on e.g. nitrogen containing fuels rely on hydrogen as the real energy carrier. And it is foremost hydrogen that significantly contributes to differential diffusion due to its small molecule size.The development of accurate modelling strategies for differential diffusion seems therefore crucial, but it is far from being trivial as turbulent mixing interacts with molecular diffusion. The proposed work will now address the modelling of differential diffusion effects in the context of a stochastic sparse particle method. The stochastic Monte-Carlo particles represent an instantaneous and local solution of a fluid element and allow for tracking the history of a fluid element, and the varying local Effects of turbulent and molecular mixing and their “integral” character can be considered.The models shall be developed with the aid of statistically zero- and one-dimensional direct numerical simulations (DNS) of non-reacting and reacting flows. The initial zero-dimensional DNS setups allow for a separation of the model development for the different terms that describe diffusion (and also differential diffusion) in the species transport equations. In a final step, the models shall be validated by comparison of simulations with high quality experimental data of species mass fractions in a series of turbulent diffusion flames where differential diffusion effects were measured.

扩散是在分子尺度上控制混合物组成并因此控制燃烧过程动力学的关键机制之一。由于分子的大小不同，物种以不同的速度扩散（差分扩散），这导致-相反的相等扩散率的情况下-物种的去相关性，因此不同的点火特性，火焰结构和火焰动力学。尽管有充分的证据表明这些影响，绝大多数的燃烧模拟假设相等的扩散系数。这是合理的假设占主导地位的湍流混合，反对差分扩散的影响。相反，模拟和实验之间的差异往往是合理的微分扩散：然而，这仍然是假设的证据不能给出，由于缺乏令人信服的模型关闭的微分扩散效应在湍流flames.Carbon减少，甚至无碳燃烧呈现不同的传输特性的主题再次及时和热门。不仅富氢燃烧（例如将氢添加到我们的天然气供应网络中），而且基于例如含氮燃料的替代概念也依赖于氢作为真实的能量载体。由于氢分子的小尺寸，它对微分扩散有着重要的贡献。因此，发展微分扩散的精确建模策略显得至关重要，但它远不是微不足道的，因为湍流混合与分子扩散相互作用。拟议的工作现在将解决差分扩散效应的随机稀疏粒子方法的背景下建模。随机蒙特-卡罗粒子代表流体元素的瞬时和局部解，并允许跟踪流体元素的历史，可以考虑湍流和分子混合的不同局部效应及其“积分”特征。应借助非反应和反应流的统计零维和一维直接数值模拟（DNS）开发模型。初始的零维DNS设置允许在物质输运方程中描述扩散（以及微分扩散）的不同项的模型开发的分离。在最后一步中，应通过将模拟结果与一系列湍流扩散火焰中物种质量分数的高质量实验数据进行比较来验证模型，其中测量了不同的扩散效应。