Measurement of inter-scale molecular fluxes in supercritical reacting turbulence

了解湍流中特定长度尺度的波动如何影响其他长度尺度的现象，对于通过数值模拟准确预测流动特性至关重要。在湍流燃烧中，这是用于运输和发电应用的将化学能转化为热能的主要模式，与非反应湍流相比，出现了额外的挑战，因为波动的化学反应速率发生在非常小的长度尺度上，这通常不能通过模拟来解决。由于希望在越来越高的压力（通常跨越到超临界压力条件）下操作燃烧系统，这个问题变得更加严重。虽然增加压力对效率和功率密度有重要的好处，但它也会将波动集中在越来越小的尺度上，并在临界点附近引入热力学性质的强烈变化。为了更好地理解这一现象，该项目将使用激光诊断和数据分析技术的新组合来测量分子氮密度的波动如何在初始超临界条件下燃烧反应物的预混火焰中在长度尺度之间移动。 空间过滤的氮数密度和速度场的时间分辨测量将在交叉平面使用突发模式自发拉曼散射。观测过程的滤波效果将通过图像反卷积来确定和调整。因此，所得到的数据将允许基于滤波场的动态来明确确定通过滤波器尺度的子滤波器波动的通量。这些信息将确定传统的建模范式是否适用于超临界反应湍流，并在必要时，使物理上更准确的模型的发展。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

Understanding how fluctuations at a specific length scale in a turbulent flow affect the phenomena at other length scales is critical to accurately predict flow properties by numerical simulation. In turbulent combustion, which is the predominant mode of converting chemical energy to thermal energy for transportation and power generation applications, additional challenges arise in comparison to non-reacting turbulent flows because the fluctuating chemical reaction rates occur at very small length scales that typically are not resolved by simulations. This problem is exacerbated by the desire to operate combustion systems at increasingly high pressures, often spanning in to the supercritical pressure conditions. While increasing the pressure has important benefits for efficiency and power density, it also concentrates fluctuations at increasingly small scales and introduces strong variations in thermodynamic properties around the critical point. To better understand this phenomenon, this project will use a novel combination of laser diagnostic and data analysis techniques to measure how fluctuations in molecular nitrogen density move between length scales in premixed flames burning reactants at initially supercritical conditions. Time-resolved measurements of the spatially filtered nitrogen number density and velocity fields will be made in crossed planes using burst-mode spontaneous Raman scattering. The filtering effect of the observation process will be determined and tuned through image deconvolution. Hence, the resultant data will allow explicit determination of the flux of sub-filter fluctuations through the filter scale based on the dynamics of the filtered fields. This information will identify whether traditional modeling paradigms hold for supercritical reacting turbulence and, where necessary, enable the development of more physically accurate models. It also will provide a unique data set against which to benchmark simulations of supercritical turbulent combustion.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.