Advancing our understanding and capability to predict the dispersion of small particles in turbulent flows is important for many applications, including air quality assessments, pollutant dispersion, human health, and weather forecasting. The goal of this project is to develop and validate a Lagrangian particle dispersion solver within a pre-existing large-eddy simulation framework. The solver will then be used to study pollutant dispersion within urban environments at the neighborhood scale. As part of this project, the student will (i) learn basic theory underpinning particle dispersion in turbulent flows, (ii) become a proficient user of an in-house computational fluid dynamics (CFD) solver, and (iii) implement a Lagrangian stochastic particle dispersion model within the CFD solver. Results from the model will be validated against measurements of dust dispersion in an urban area. The student will be given access to high performance computing resources and weekly discussion meetings will be held in either remote or in-person mode. The student can also register for research credits as part of this project.
Name of Lab: Environmental Flow Physics Laboratory
Direct Supervisor: Marco Giometto and Gurpreet Singh Hora
Hours per week: 35 hr/week
Position type: Hybrid (both remote and on site)
Qualifications: Fluid Mechanics and Programming Languages
Eligibility: Sophomore, Junior, Senior
SEAS students only: Yes