Award Date
5-1-2020
Degree Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Mechanical Engineering
First Committee Member
Alexander Barzilov
Second Committee Member
Yi-Tung Chen
Third Committee Member
William Culbreth
Fourth Committee Member
Woosoon Yim
Fifth Committee Member
Moses Karakouzian
Number of Pages
140
Abstract
Remote sensing of ionizing radiation has a significant role in waste management, nuclear material management and nonproliferation, radiation safety, and accident response in situations such as the Fukushima nuclear power plant accident. Robotic platforms are able to surpass the number of tasks that could be achieved by humans. With the use of robots, the operator’s radiation exposure can be considerably decreased. Remote sensing allows for the evaluation and monitoring of radiological contamination in hazardous and hard to reach areas and locating radiation sources. In this work, gamma-ray and neutron sensors were integrated onto the unmanned aerial systems (UAS) making it possible to assay the unsafe zones remotely. Radiation data were automatically processed onboard of the smart sensor (segregation of photon and neutron signatures, gamma spectra analysis) and fused with the GPS data. This approach allows for the radiation sensor data to be dynamically tracked and mapped thus enabling further analysis of the radiation flux in the time and space domains. Maximum likelihood estimation (MLE) technique was used to locate the position of the radiation source based on the signal intensities measured in three or more locations by a single UAS or simultaneously by multiple UAS. The probabilities to locate a source with an unknown yield in an assayed area were calculated. If the robotic platforms are exposed to ionizing radiation, radiation damage occurs in the electronics components, limiting the platform’s operational time. The estimation of radiation damage of the components is important in order to optimize the robot’s operational lifetime in contaminated zones. Displacement per atom (DPA) characterizes the displacement damage on materials incurred by the radiation, which affects the macroscopic crystal defects. DPA depicts how many times atoms have been displaced from their lattice sites, representing the damage-based exposure unit. The FLUKA and SRIM/TRIM codes were used to analyze the DPA and ions transport processes in components of UAS and ground platforms. Packaging and the shielding designs were determined so that the operational time of the robot is increased.
Keywords
Computation Modeling; Radiation Damage; Radiation Detectors; Remote Sensing; Robotic Platforms; Source Search Methods
Disciplines
Mechanical Engineering | Nuclear Engineering
File Format
File Size
11.1 MB
Degree Grantor
University of Nevada, Las Vegas
Language
English
Repository Citation
Kazemeini, Monia, "Remote Radiation Sensing using Robotic Platforms" (2020). UNLV Theses, Dissertations, Professional Papers, and Capstones. 3911.
http://dx.doi.org/10.34917/19412101
Rights
IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/