Worcester Polytechnic Institute Electronic Theses and Dissertations Collection

Title page for ETD etd-051812-120145


Document Typedissertation
Author NameCourt, Jeffrey
URNetd-051812-120145
TitleEstimation of the Concentration from a Moving Gaseous Source in the Atmosphere Using a Guided Sensing Aerial Vehicle
DegreePhD
DepartmentMechanical Engineering
Advisors
  • Michael A. Demetriou, Advisor
  • Nikolaos A. Gatsonis, Advisor
  • Mustapha S. Fofana, Committee Member
  • Nikolaos Kazantzis, Committee Member
  • Simon W. Evans, Graduate Committee Rep
  • Keywords
  • PDEs
  • Sensing Aerial Vehicle Guidance
  • State Estimation
  • Source Detection
  • Date of Presentation/Defense2012-05-11
    Availability unrestricted

    Abstract

    The estimation of the gas concentration (process-state) associated with a stationary or moving source using a sensing aerial vehicle (SAV) is considered. The dispersion from such a gaseous source into the ambient atmosphere is representative of an accidental or deliberate release of chemicals, or a release of gases from biological systems. Estimation of the concentration field provides a superior ability for source localization, assessment of possible adverse impacts, and eventual containment. The abstract and finite-dimensional approximation framework presented couples theoretical estimation and control with computational fluid dynamics methods. The gas dispersion (process) model is based on the advection-diffusion equation with variable eddy diffusivities and ambient winds. Cases are considered for a 2D and 3D domain. The state estimator is a modified Luenberger observer with a ”collocated” filter gain that is parameterized by the position of the SAV. The process-state (concentration) estimator is based on a 2D and 3D adaptive, multigrid, multi-step finite-volume method. The grid is adapted with local refinement and coarsening during the process-state estimation in order to improve accuracy and efficiency. The motion dynamics of the SAV are incorporated into the spatial process and the SAV’s guidance is directly linked to the performance of the state estimator. The computational model and the state estimator are coupled in the sense that grid-refinement is affected by the SAV repositioning, and the guidance laws of the SAV are affected by grid-refinement. Extensive numerical experiments serve to demonstrate the effectiveness of the coupled approach.

    Files
  • Dissertation.pdf

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