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Flow Dynamics in Buoyancy-Driven Variable-Density Turbulent Mixing with Compressibility Effects

具有压缩效应的浮力驱动变密度湍流混合中的流动动力学

基本信息

批准号：
2234415
负责人：
Denis Aslangil
金额：
$ 29.91万
依托单位：
University of Alabama Tuscaloosa
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2023
资助国家：
美国
起止时间：
2023-01-01 至 2025-12-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2234415&HistoricalAwards=false
关键词：
Flow Dynamics Buoyancy Driven Variable

项目摘要

In general, complex flows - those observed in supersonic-to-hypersonic combustion and propulsion, fusion technologies, and astrophysics - involve multi-material mixing and span a broad range of space and time scales. Fluids participating in such flows have a wide range of molar masses, and in many cases, the flow is highly compressible. It is still a challenge for current engineering tools to predict the key flow physics that arise due to the compressibility and large material property variations. A stronger fundamental understanding of these effects on turbulent flows will significantly increase our ability to model the flow physics accurately, such as the rate of turbulent mixing that occurs in complex multi-material flows, and to perform numerical simulations of such flows with a decreased computational expense. These gained abilities will have a direct impact on the improvement and development of many high-tech products in the space, energy, and defense industries. Therefore, the focus of the proposed study is to quantify the coupled large molar-mass ratio and compressibility effects on the gravitationally driven turbulent flows. The project will also deliver an educational component by generating content for undergraduate- and graduate-level courses. It will also support outreach activities to promote interest in fluid dynamics and turbulence, and more broadly in STEM among local middle-school students.Multi-material turbulence has so far mostly been studied with quasi-incompressible and Boussinesq flows with small variations in material properties. The proposed project aims to describe flow compressibility effects on Rayleigh-Taylor unstable turbulent mixing with large density variations beyond the Boussinesq approximation and the incompressible assumption. Novel direct numerical simulations of buoyancy-driven flow that resolve all spatial and temporal scales will be performed at large density ratios (2) with highly compressible fluids using the adaptive mesh refinement to optimally deploy computational resources. Unique statistical tools will be developed to quantify the non-Boussinesq turbulent compressible mixing dynamics. The proposed simulations and statistical analyses will be used to establish a deeper understanding of turbulence transition for non-Boussinesq flows, and in particular, the small-scale flow topology of the compressible active-scalar mixing. In addition, the findings of this research are expected to inform new sub-grid-scale models and strategies to decrease the computational cost of the multi-physics complex fluid-flow simulations and validate the reduced-order models for these complex flows. This project is jointly funded by Fluid Dynamics program and the Established Program to Stimulate Competitive Research (EPSCoR).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.

一般来说，复杂的流动-那些在超音速到高超音速燃烧和推进，聚变技术和天体物理学中观察到的-涉及多材料混合，并跨越广泛的空间和时间尺度。参与这种流动的流体具有广泛的摩尔质量，并且在许多情况下，流动是高度可压缩的。由于可压缩性和大的材料性质变化，预测关键的流动物理现象对当前的工程工具仍然是一个挑战。对湍流的这些影响有更强的基本理解，将显著提高我们准确模拟流动物理的能力，例如复杂多物质流中发生的湍流混合速率，并以更低的计算费用对此类流动进行数值模拟。这些能力的获得将直接影响到航天、能源、国防等诸多高科技产品的改进和发展。因此，建议的研究重点是量化耦合的大摩尔质量比和压缩性对重力驱动的湍流的影响。该项目还将提供教育内容，为本科生和研究生课程提供内容。该项目还将支持开展外展活动，以提高当地中学生对流体动力学和湍流的兴趣，并更广泛地提高他们对STEM的兴趣。迄今为止，多材料湍流的研究主要是利用准不可压缩流和Boussinesq流，这些流的材料特性变化很小。该项目的目的是描述流动压缩性的影响瑞利-泰勒不稳定的湍流混合与大的密度变化超出Boussinesq近似和不可压缩的假设。解决所有空间和时间尺度的浮力驱动流的新的直接数值模拟将在大密度比（2）下使用高度可压缩流体进行，使用自适应网格细化以优化部署计算资源。将开发独特的统计工具来量化非Boussinesq湍流可压缩混合动力学。建议的模拟和统计分析将用于建立一个更深入的了解湍流过渡的非Boussinesq流，特别是，小尺度流动拓扑结构的可压缩主动标量混合。此外，这项研究的结果有望为新的亚网格尺度模型和策略提供信息，以降低多物理场复杂流体流动模拟的计算成本，并验证这些复杂流动的降阶模型。该项目由流体动力学计划和激励竞争研究的既定计划（EPSCoR）共同资助。该奖项反映了NSF的法定使命，并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，被认为值得支持。