CAREER: Development of a Hierarchy of Optimal LES Models for Turbulent Spray Combustion

喷雾燃烧是航空发动机、燃气轮机和化学反应器等许多实际设备中普遍存在的现象。喷雾燃烧的预测模型对于评估安全和有效使用这些系统的操作范围至关重要。然而，考虑到喷雾燃烧过程的多尺度、多物理性质，开发这样的模型是一个巨大的挑战。近年来，大涡模拟(LES)已成为替代传统雷诺平均N-S(RANS)燃烧模拟方法的一种可行方法。在大涡模拟中，大尺度的运动是直接计算的，而小尺度的运动是模拟的。虽然LES在预测远未熄灭的单相火焰方面显示出相当高的准确性，但建模更复杂的过程，如喷雾燃烧或火焰熄灭，面临着与基于RANS的方法相同的难以克服的困难。造成这一僵局的主要原因是，LES燃烧模型几乎是相应RAN模型的未更改版本。这项工作的目的是开发新一代的燃烧模型，以准确地预测流动形态的所有空间统计。新的框架被称为条件过滤概率密度函数(FPDF)方法，它将为理解燃烧模拟中的建模和数值误差提供一种统计上一致的方法。PI将与悉尼大学的实验者和陶氏化学公司的研究人员密切互动，严格测试这里开发的模型。为了确保研究进展的及时传播，计划了一个多层次的教育计划。将开发一个基于网络的学习平台，提供对模型、计算数据库和研究代码的访问。还将在这一框架下开发用于课堂学习的互动工具。这些工具将用于培训工业研究人员和学生，了解计算燃烧科学的最新进展。此外，将通过该项目支持一个针对高中生的实习计划。有动力的学生，特别是来自代表人数不足的群体的学生，将有机会参与研究活动并与德克萨斯大学的学生互动。

CBET-0747427, RamanTurbulent spray combustion is a common phenomenon occurring in a number of practical devices such as aircraft engines, gas turbines, and chemical reactors. A predictive model for spray combustion is vital in estimating an operational envelope for the safe and efficient use of these systems. Development of such models, however, is a tremendous challenge given the multiscale multiphysics nature of the spray combustion process. In the recent past, large-eddy simulation (LES) has emerged as a viable alternative to conventional Reynolds-Averaged Navier-Stokes (RANS) approach to combustion modeling. In LES, the large-scale motions are directly computed while the small-scale processes are modeled. While LES has shown considerable accuracy in predicting single-phase flames far from extinction, modeling more complex processes such as spray combustion or flame extinction faces the same insurmountable difficulties as RANS-based approaches. The main reason for this impasse is that LES combustion models are nearly unaltered versions of the corresponding RANS models. The objective of this work is to develop a new generation of combustion models specifically for LES with the goal of predicting all spatial statistics of the flow configuration accurately. The new framework, termed conditionally-filtered probability density function (FPDF) approach, will provide a statistically consistent approach for understanding modeling and numerical errors in combustion modeling. The PI will closely interact with experimentalists from the University of Sydney and researchers from Dow Chemical Company to rigorously test the models developed here. To ensure timely dissemination of research advances, a multi-level educational program is planned. A web-based learning platform that provides access to models, computational databases, and research codes will be developed. Interactive tools for classroom learning will also be developed under this framework. These tools will be used to train both industrial researchers and students in the latest advances in computational combustion science. Further, an internship program for high-school students will be supported through this project. Motivated students, especially from underrepresented groups, will have an opportunity to participate in the research activities and interact with UT students.