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: 1803845
• 负责人: Huidan Yu
• 金额: $ 19.19万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Continuing 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=1803845&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.

脉冲流在自然和工程系统中无处不在。了解脉动流中的湍流对于知识的进步和技术创新至关重要。但是，由于缺乏适当的湍流计算模型，挑战一直存在，从而解决了从层流到湍流的连续过渡，然后在脉动过程中恢复到层流流。层次或过渡性或湍流从固定管流中发展的流动流量标准不适用于脉冲流；现有的基于Kolmogorov理论的湍流模型也不适合用于完全发达的湍流。在实验室实验的支持下，该项目是为时间脉动流动建立一种新的自变义湍流建模方法。这项研究的一个重要影响将是基于图像的患者特异性非侵入性诊断和评估心血管疾病的精确药物。该项目将为研究生/本科生的多学科培训提供各种机会，以及印第安纳大学普尔德大学，印第安纳波利斯和纽约市学院的课程开发。该项目的目的是开发和验证一种新的基于动力学的自动湍流模型，以在脉冲流中求解层状腹部 - 驱动式延迟过渡，在该脉冲流中，当空间或时间分辨率不足以使整个范围内的范围不足时，对小规模运动进行建模的需求自动激活/取消。显式过滤应用于过渡流中的分解尺度解决方案，以使子网格比例模型适应动态的时间和空间分辨率要求。亚网格量表模型嵌入基于动力学的晶格玻尔兹曼方法中，以通过在图形处理单元上进行大规模并行化实现快速的计算速度。将通过并发数值模拟和实验室实验探索惯性和粘性效果，脉动频率，几何曲率和分叉的各种影响，脉动效果，脉动频率，几何曲率和分叉的深入了解。 不稳定的脉动流中层次，过渡性和湍流行为的一般标准将被揭幕，这对于基于软件的计算流体动态至关重要，对于基于软件的计算流体动力学对于脉动流动至关重要，在传统上，层状或动荡的流量必须在模拟之前进行预定的Inforts Infort of The Internation。更广泛的影响审查标准。

项目成果

Laminar and Turbulent Behavior Captured by A 3-D Kinetic-Based Discrete Dynamic System

• 作者: Xiaoyu Zhang;J. M. McDonough

Inlet and Outlet Boundary Conditions and Uncertainty Quantification in Volumetric Lattice Boltzmann Method for Image-Based Computational Hemodynamics

• DOI: 10.3390/fluids7010030
• 发表时间: 2022-01
• 期刊: Fluids
• 影响因子: 1.9
• 作者: Huidan Yu;Monsurul Khan;Hao Wu;Chunze Zhang;X. Du;Rou Chen;Xin Fang;Jianyun Long;A. Sawchuk

Role of flow reversals in transition to turbulence and relaminarization of pulsatile flows

• DOI: 10.1017/jfm.2021.269
• 发表时间: 2021-04-26
• 期刊: JOURNAL OF FLUID MECHANICS
• 影响因子: 3.7
• 作者: Gomez, Joan;Yu, Huidan;Andreopoulos, Yiannis
• 通讯作者: Andreopoulos, Yiannis

Physics-Based Regression vs. CFD for Hagen-Poiseuille and Womersley Flows and Uncertainty Quantification

Hagen-Poiseuille 和 Womersley 流以及不确定性量化的基于物理的回归与 CFD

• 发表时间: 2022
• 期刊: Eleventh International Conference on Computational Fluid Dynamics (ICCFD11
• 作者: Li, H.;Islam, M.;Yu, H.;Du, X.
• 通讯作者: Du, X.