Multiscale plenoptic imaging and direct computation of turbulent channel flows laden with finite-size solid particles

含有有限尺寸固体颗粒的湍流通道流的多尺度全光成像和直接计算

• 批准号: 1706130
• 负责人: Lian-Ping Wang
• 金额: $ 30万
• 依托单位: University of Delaware
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1706130&HistoricalAwards=false
• 关键词: Multiscale; plenoptic; imaging; direct; computation

CBET - 1706130PI: Wang, Lian-PingTurbulent flows that contain particles occur in a variety of industrial, biological, and environmental processes. The analysis of these flows is challenging, because interactions between the suspended particles and the surrounding fluid not only affect dynamics of the particles, but also influence characteristics of the overall flow. This award will support development of computational and experimental tools to better understand how particle-fluid interactions at the particle scale influence transport in turbulent flow at large scales. An imaging system will be constructed to record three-dimensional velocity fields of particle-laden fluids in turbulent open-channel flow. Experimental results will be compared with numerical simulations of the identical flow to validate the simulation methods and provide additional insight into relationships between particle dynamics and flow. The research team will incorporate results from the project in a new short course that will combine computational fluid dynamics with new techniques in computational imaging and computer vision. An instructional module illustrating these methods will be developed for high school students and teachers participating in the High School Summer Research program at the University of Delaware.A plenoptic particle tracking velocimetry system will be constructed that can measure the three-component velocity fields in three-dimensional, turbulent, particle-laden flows at both micro- and macro-scales. This velocimetry method uses a plenoptic camera that can record many images of a collection of particles from different viewpoints and angles at the same time. Then, computer vision algorithms are applied to recover accurately the instantaneous positions of the particles in three dimensions, which can be used to find the velocity fields. In addition, the particle tracking system in this project will be designed to capture the rotational velocity of individual particles. In parallel, a highly scalable particle-resolved simulation tool based on the mesoscopic lattice Boltzmann approach will be applied to resolve the three-dimensional motion at all scales. Results from the simulations will be compared with experimental data at all scales. At the particle scale, these data include trajectories, velocities, accelerations, and angular velocities of particles, particle-wall and particle-free surface interactions, as well as local flow statistics near the surface of a solid particle. At the system scale, the tools will be used to study turbulence modulation, flow drag, and flow transition in the presence of the finite-size solid particles.

CBET -1706130 PI：Wang，Lian-Ping含有颗粒的湍流发生在各种工业、生物和环境过程中。 这些流动的分析是具有挑战性的，因为悬浮颗粒和周围流体之间的相互作用不仅影响颗粒的动力学，而且影响整体流动的特性。 该奖项将支持计算和实验工具的开发，以更好地了解颗粒尺度的颗粒-流体相互作用如何影响大尺度湍流中的传输。 本文将建立一套成像系统，用以记录明渠紊流中含颗粒流体的三维速度场。 将实验结果与相同流量的数值模拟进行比较，以验证模拟方法，并提供更多的洞察粒子动力学和流量之间的关系。 研究小组将把该项目的成果纳入一个新的短期课程，该课程将把联合收割机计算流体动力学与计算成像和计算机视觉的新技术结合起来。 将为参加特拉华大学高中暑期研究项目的高中学生和教师开发一个演示这些方法的教学模块。将构建一个全光粒子跟踪测速系统，该系统可以测量微观和宏观尺度上三维湍流颗粒流的三分量速度场。该测速方法使用全光相机，其可以同时从不同视点和角度记录粒子集合的许多图像。 然后，应用计算机视觉算法精确地恢复三维粒子的瞬时位置，可以用来找到速度场。 此外，本项目中的粒子跟踪系统将被设计为捕获单个粒子的旋转速度。与此同时，一个高度可扩展的粒子分辨的模拟工具的基础上的介观格子玻尔兹曼方法将被应用到解决在所有尺度的三维运动。 模拟结果将与所有尺度的实验数据进行比较。 在颗粒尺度上，这些数据包括颗粒的轨迹、速度、加速度和角速度，颗粒与壁和无颗粒表面的相互作用，以及固体颗粒表面附近的局部流动统计。在系统尺度上，这些工具将被用来研究湍流调制，流动阻力和流动过渡中存在的有限尺寸的固体颗粒。

项目成果

Effects of turbulence modulation and gravity on particle collision statistics

湍流调制和重力对粒子碰撞统计的影响

• DOI: 10.1016/j.ijmultiphaseflow.2020.103334
• 发表时间: 2020-08
• 期刊: International Journal of Multiphase Flow
• 影响因子: 3.8
• 作者: Rosa Bogdan;Pozorski Jacek;Wang Lian-Ping
• 通讯作者: Wang Lian-Ping

Understanding Particle-fluid interaction dynamics in turbulent flow

了解湍流中的粒子-流体相互作用动力学

• DOI: 10.26320/scientia43
• 发表时间: 2017
• 期刊: Scientia
• 作者: Wang, L-P

Force-amplified, single-sided diffused-interface immersed boundary kernel for correct local velocity gradient computation and accurate no-slip boundary enforcement

力放大、单侧扩散界面浸入边界内核，用于正确的局部速度梯度计算和精确的无滑移边界执行

• DOI: 10.1103/physreve.101.053305
• 发表时间: 2020
• 期刊: PHYSICAL REVIEW E
• 影响因子: 2.4
• 作者: Peng Cheng;Wang Lian-Ping
• 通讯作者: Wang Lian-Ping

Estimation of the dissipation rate of turbulent kinetic energy: A review

• DOI: 10.1016/j.ces.2020.116133
• 发表时间: 2021-01
• 期刊: Chemical Engineering Science
• 影响因子: 4.7
• 作者: Guichao Wang;Fan Yang;Ke Wu;Yong-Feng Ma;Cheng Peng;Tianshu Liu;Lian-Ping Wang

Relations between skin friction and other surface quantities in viscous flows

粘性流中的表面摩擦力与其他表面量之间的关系

• DOI: 10.1063/1.5120454
• 发表时间: 2019
• 期刊: Physics of Fluids
• 影响因子: 4.6
• 作者: Tao Chen;Tianshu Liu;Lian-Ping Wang;Shiyi Chen
• 通讯作者: Shiyi Chen