Collaborative Research: Kinetic-based self-transitioning turbulence modeling for pulsatile flows

合作研究：基于动力学的脉动流自转变湍流建模

• 批准号: 1803294
• 负责人: Yiannis Andreopoulos
• 金额: $ 15.91万
• 依托单位: CUNY City College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-15 至 2022-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1803294&HistoricalAwards=false
• 关键词: Collaborative; Research; Kinetic; based; self

Pulsatile flows are omnipresent in nature and engineering systems. Understanding turbulence in pulsatile flows is critically important to both knowledge advancement and technological innovation. However, challenges have remained due to the lack of appropriate turbulence computational models that solve the inherent unsteadiness with successive transitions from laminar to turbulent, and then back to laminar flow during pulsation. The prevailing flow criteria of either laminar, or transitional, or turbulent flow developed from stationary pipe flows are not appropriate for pulsatile flows; the existing turbulence models based on Kolmogorov theory for fully-developed turbulence are not suitable, either. With the support of laboratory experiment, this project is to establish a new self-transitioning turbulence modeling method for time-wise pulsatile flows. An important impact of this research will be on the precision medicine of image-based patient-specific noninvasive diagnose and assessment of cardiovascular diseases. The project will provide various opportunities for multidisciplinary training for graduate/undergraduate students, as well as for curriculum development at both Indiana University-Purdue University, Indianapolis and City College of New York. The goal of this project is to develop and validate a new kinetic-based self-transitional turbulence model for solving the laminar-turbulent-laminar transition in pulsatile flows, in which the need of modeling for small scale motion is automatically activated/deactivated when the spatial or temporal resolution is insufficient/sufficient to resolve the entire range of scales when flow is accelerating/decelerating in a pulsation. Explicit filtering is applied to resolved-scale solutions in transitional flows to adapt the sub-grid scale model to dynamic temporal and spatial resolution requirements. The sub-grid scale model is embedded in the kinetic-based lattice Boltzmann method to achieve disruptively fast computation speed through massive parallelization on graphic processing units. In-depth understanding of turbulence in pulsatile flows under various influences of inertia and viscous effects, pulsating frequency, geometric curvature and bifurcations will be explored through concurrent numerical simulation and laboratory experiment. General criteria of laminar, transitional, and turbulent behaviors in unsteady pulsatile flows will be unveiled, which are critically important to software-based computational fluid dynamics for pulsatile flows where, conventionally, laminar or turbulent flow must be predefined before the simulation.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.

脉动流在自然界和工程系统中无处不在。了解脉动流中的湍流对知识进步和技术创新都至关重要。然而，由于缺乏适当的湍流计算模型，解决了固有的不稳定性，从层流连续过渡到湍流，然后回到层流在脉动过程中，仍然存在挑战。从静止管流发展的层流、过渡流或湍流的主流流动准则不适用于脉动流;现有的基于Kolmogorov理论的充分发展湍流湍流模型也不适用。本课题在实验室实验的支持下，建立了一种新的时间脉动流的自转换湍流模拟方法。该研究将对基于图像的心血管疾病患者特异性无创诊断和评估的精准医学产生重要影响。该项目将为研究生/本科生提供多学科培训的各种机会，并为印第安纳波利斯的印第安纳州普渡大学和纽约城市学院的课程编制提供各种机会。该项目的目标是开发和验证一种新的基于动力学的自过渡湍流模型，用于解决脉动流中的层流-湍流-层流过渡，其中当空间或时间分辨率不足以/足以解决脉动中流动加速/减速时的整个尺度范围时，自动激活/停用小尺度运动建模的需要。显式过滤适用于过渡流的分辨率尺度的解决方案，以适应动态的时间和空间分辨率要求的亚网格尺度模型。亚网格尺度模型嵌入在基于动力学的格子玻尔兹曼方法中，通过图形处理单元上的大规模并行化来实现破坏性的快速计算速度。通过并行数值模拟和实验室实验，深入了解脉动流中的湍流在惯性和粘性效应、脉动频率、几何曲率和分叉的各种影响下的情况。 将揭示非定常脉动流中层流、过渡和湍流行为的一般准则，这对基于软件的脉动流计算流体动力学至关重要，传统上，层流或湍流必须在模拟之前预先确定。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进行评估，被认为值得支持的搜索.