A Foundational Step Towards the Development of a Predictive Framework for Particle Deposition in Wall-Bounded Turbulent Flows

University Of Missouri-Kansas City, Columbia MO

Investigators

Abstract

Deposition of small particles, also denoted as particulate fouling, is a fundamental challenge in many traditional and emerging industries such as petrochemical industries and modern geothermal systems. More specifically, particulate fouling significantly reduces the efficiency and prevents optimization and full utilization of such systems. Several studies have shown that particulate fouling significantly contributes to global CO2 anthropogenic emissions. To date, there is a lack of fundamental understanding of this phenomenon. Therefore, the overriding aim of this project is to identify and understand major underlying mechanisms of the deposition process using high-fidelity numerical simulations using state-of-the-art techniques for turbulent wall-bounded dispersed flows at moderate/high Reynolds numbers, as detailed experimental measurements are not currently possible. The project also includes relevant educational activities that help increase the readiness of K-12 students for college education by addressing the shortage of adequately trained high school teachers. The research aims to take a foundational step to address the existing lack of fundamental knowledge on characteristics of turbulent dispersed flows of small particles at high Reynolds numbers. The proposed research leverages an advanced and accurate Euler-Lagrangian approach, i.e., Point-Particle Direct Numerical Simulation (PP-DNS) via one-way coupling, to gain fundamental insights into the complex dynamics of small particles dispersion and deposition inside highly turbulent wall-bounded flows and to use this knowledge to guide the development and validation of first generation of reliable and computationally affordable modelling framework. Particular focus will be on a Point-Particle based Euler-Lagrangian framework that uses an advanced turbulence modeling strategy i.e., hybrid Unsteady Reynolds-averaged-Navier-Stokes/Large Eddy Simulation methodology to capture complex dynamics of the fluid phase. The resulting framework provides a unique tool to study and understand small particle transport and deposition dynamics in high Reynolds number turbulent flows that otherwise would not be possible and yet, essential for an optimized design of Thermo-Fluid systems. Further, the current study will cover particles in a size range that encompasses typical size range most responsible for particulate fouling in majority of emerging technologies. Finally, the knowledge on dispersion and deposition of small particles is expected to serve as a bridge to combine fluid dynamics and virology to help understand transmission of deadly viruses such as COVID-19. 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.