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.

通常，复杂的流 - 在超音速到激烈的燃烧和推进，融合技术和天体物理学中观察到的流动 - 涉及多物质混合，并跨越广泛的时空和时间尺度。参与此类流量的流体具有广泛的摩尔质量，在许多情况下，流动非常可压缩。对于当前工程工具来说，预测由于可压缩性和较大材料属性变化而产生的关键流体物理学仍然是一个挑战。对这些对湍流的影响的基本了解将显着提高我们准确地对流体物理进行建模的能力，例如在复杂的多物质流中发生的湍流混合速率，并以减少的计算费用对此类流量进行数值模拟。这些获得的能力将直接影响空间，能源和国防行业中许多高科技产品的改进和开发。因此，拟议的研究的重点是量化对重力驱动的湍流的耦合大摩尔质量比和可压缩性影响。该项目还将通过为本科和研究生级课程生成内容来提供教育组成部分。它还将支持外展活动，以促进对流体动力学和湍流的兴趣，并且在本地中学生中更广泛地在STEM中。到目前为止，多数材料的湍流主要是通过准压缩和boussinesq流的研究，其物质特性的变化很小。拟议的项目旨在描述对雷利 - 泰勒不稳定的湍流混合的流动压缩性影响，其密度变化超出了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流动流的新型直接数值模拟将以高密度比（2）进行高度可压缩的流体，使用自适应网格细化，以最佳地部署计算资源。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。所提出的模拟和统计分析将用于建立对非BoussinesQ流的湍流转变的更深入的理解，尤其是可压缩活性量表混合的小规模流量拓扑。此外，这项研究的发现有望为新的子网格规模模型和策略提供信息，以降低多物理复杂流体流量模拟的计算成本，并验证这些复杂流量的降级模型。该项目由流体动力学计划和既定的竞争研究（EPSCOR）共同资助。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响评估标准，认为值得通过评估来获得支持。