Department
Electrical and Computer Engineering
Major
Electrical Engineering
Research Advisor
Huang, Jie
Advisor's Department
Electrical and Computer Engineering
Funding Source
Army Research Lab
Abstract
The proposed research is to create a real-time sensor for detecting aluminum degradation due to gallium infiltration attacks, specifically in military vehicles and structures. Gallium acts as a poison to aluminum, leading to catastrophic failures of structural integrity. The proliferation of educational material on this subject raises security concerns for the United States Military, where nearly all structures utilize aluminum due to its high-strength, light-weight profile. Utilizing Fiber-Bragg Grating (FBG) sensors and machine learning techniques, this research aims to develop a real-time sensor to detect these attacks.
Biography
Peter Holtmann is a graduating senior in Electrical Engineering. Peter is part of the Lightwave Technology Lab, a lab dedicated to the research and development of optical and microwave sensors applied to energy, intelligent infrastructures, clean-environment, and biomedical applications. Besides this, Peter is involved with the Intelligent Systems Center, where he has worked as the webmaster, and New Student Programs, where he is a PRO Leader. His research interests include applying machine learning and artificial intelligence to engineering applications, sensing techniques, and optics.
Research Category
Engineering
Presentation Type
Oral Presentation
Document Type
Presentation
Award
Engineering oral presentation, Second place
Presentation Date
27 Apr 2017, 1:45 pm - 2:00 pm
Included in
Realtime Sensor for detecting Gallium Infiltration Attack
The proposed research is to create a real-time sensor for detecting aluminum degradation due to gallium infiltration attacks, specifically in military vehicles and structures. Gallium acts as a poison to aluminum, leading to catastrophic failures of structural integrity. The proliferation of educational material on this subject raises security concerns for the United States Military, where nearly all structures utilize aluminum due to its high-strength, light-weight profile. Utilizing Fiber-Bragg Grating (FBG) sensors and machine learning techniques, this research aims to develop a real-time sensor to detect these attacks.
