Particulate flow is ubiquitous in nature and many aspects of human life. For example, sandstorms have severe environmental and economic consequences, and the efficiency of a fluidized particle reactor determines the production rates in many chemical and food industries. A critical issue is that particles in nature are usually non-spherical and may behave differently from theoretical predictions as existing theories are largely based on spherical particle models. Furthermore, the problem is challenging because dense particulate flows are usually opaque and cannot be measured with advanced optical flow diagnostic technologies. The objective of this experimental project is to develop a novel magnetic-based technology to measure the particle shape and motion and provide a better understanding of complex particulate flows. This project will also encompass significant educational and outreach activities, including museum exhibitions and visits to under-represented minority communities.

The proposed research aims to quantify the kinetic energy and shape effect of non-spherical particles in complex flows using magnetic-based particle tracking. Magnetic fields can penetrate opaque materials, thus the proposed technique works with particles of any shape or concentration. For higher accuracy, a highly-accurate magnetometry based on photoluminescence of quantum bits will be employed to reconstruct the motion of multiple magnetic particles in a shear flow. The Lagrangian trajectory orientation and angular velocity of the particle will be obtained with this technique. The results will be used to test the hypothesis that a large particle aspect ratio leads to energy equal partition, to measure the influence of sphericity, and to examine the energy transfer among translational and rotational degrees of freedom. Finally, this project contributes to experimental fluid dynamics by developing a non-optical particle tracking technology that can be used in a variety of multiphase flow studies.

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.

Project Start
Project End
Budget Start
2020-02-01
Budget End
2025-01-31
Support Year
Fiscal Year
2019
Total Cost
$394,504
Indirect Cost
Name
University of Kansas
Department
Type
DUNS #
City
Lawrence
State
KS
Country
United States
Zip Code
66045