Date of Award
2026
Document Type
Thesis
Degree Name
Master of Science in Engineering (MSE)
Department
Mechanical and Aerospace Engineering
Committee Chair
Robert Frederick Jr.
Committee Member
Dale Thomas
Committee Member
Jason Cassibry
Research Advisor
Robert Frederick Jr.
Subject(s)
Nuclear propulsion, Multiphase flow, Bubbles--Thermodynamics, Image processing--Digital techniques
Abstract
Accurate measurement of bubble size and rise velocity is essential for characterizing multiphase flow behavior in Centrifugal Nuclear Thermal Rocket (CNTR) experiments, where dynamic imaging conditions complicate traditional analysis methods. This thesis presents the development and validation of an automated image-based framework for extracting bubble equivalent diameter and rise velocity from high-speed experimental videos of injected gas bubbles rising through controlled liquid-filled volumes. Representative datasets include air bubbles injected into water and Sodium Polytungstate (SPT-3). The framework employs a staged analysis workflow with instance-level bubble segmentation using a Mask R-CNN model, secondary classification for detection verification, multi-object tracking, and velocity post-processing. Model training incorporates synthetic datasets with known physical properties and operator-annotated experimental data. Validation using synthetic ground truth, hand-labeled comparisons, physics-based checks, and uncertainty analysis yields bounded uncertainties of 2–5% in case-mean diameter and 2–11% in rise velocity under representative imaging conditions.
Recommended Citation
Williams, Olivia, "Development and validation of an automated image-based framework for bubble size and velocity measurement in centrifugal nuclear thermal rocket experiments" (2026). Theses. 817.
https://louis.uah.edu/uah-theses/817