04/22/2021
By Sokny Long

The Francis College of Engineering, Department of Electrical Engineering, invites you to attend a master’s thesis defense by Angela Bertolino on “ Parameter estimation techniques for the Gaussian plume model of pollutant dispersion.”

Master’s Candidate Name: Angela Bertolino
Defense Date: Monday, April 26, 2021
Time: 6:30 to 7:30 p.m. EST
Location: This will be a virtual defense via Zoom. Those interested in attending should contact Angela_Bertolino@student.uml.edu and committee advisor, Kavitha_Chandra@uml.edu, at least 24 hours prior to the defense to request access to the meeting.

Committee Chair (Advisor): Kavitha Chandra, Associate Dean of Undergraduate Studies, Department of Electrical Engineering, UMass Lowell

Committee Members:

  • Charles Thompson, Professor, Department of Electrical Engineering, UMass Lowell
  • Joshua Levy, Adjunct Professor, Operations and Information Systems, UMass Lowell

Brief Abstract:
The Gaussian plume model represents an approximate solution to the partial differential equation that governs the atmospheric dispersion of pollutant particles generated by a point source. The early detection of the dispersed particles using a sensor network and identification of the parameters of this model which includes the source location has been an important problem in the many applications where pollutants are generated, measured and monitored. The assumptions made in deriving the solution to the partial differential equation that models the advection and diffusion of the concentration of the pollutant are presented . The resultant shape of the plume in the crosswind and vertical directions is visualized. The estimation of the source location and dispersion parameters using measurements from a set of sensors is presented using Bayesian estimators and Monte Carlo based particle filtering techniques. The performance of the estimator is examined with respect to sensor positions, number of sensors and the measurement noise.

All interested students and faculty members are invited to attend the online defense via remote access.