Evaluation of Artificial Intelligence to Dynamic Loading Predictions
We are looking for highly motivated students (one undergraduate and one MS) who are interested in a summer research opportunity related to failure of materials used in ships and submarines. This is a 10-week computational project with compensation. Students must be fluent in python and Matlab and interested to learn “Deep Learning” computational programs. The students need to be US citizens and be willing to work at the government research lab during summer. This summer, the students will work in Storrs. The undergraduate applicants must have GPA greater than 3.0, graduating in May 2020, and be willing to apply for a 2-year MS degree. We are also looking for Masters students graduating in May 2020 and be willing to apply for a 3-year PhD program.
The proposed work will investigate the predictive capabilities of Artificial Intelligence (AI) to incoming dynamic loading profiles. Predicting incoming dynamics loads will pave the way to highly advanced active damping systems that uses surrounding sensing network and AI to improve the safety and performance of the payloads in the United States Navy (USN). Moreover, the AI’s predictive capabilities would also improve the autonomy of undersea weaponry systems. The emphasis of this work will be on understanding the fundamental mechanisms of applying AI networks to sensor data and determine methods of extrapolating future performance of the payload structure from this data. During this effort, existing published experimental data from implosion events will be used as the data needed for the AI analysis. The outcomes from these efforts will then be used to construct and validate methods of coupling AI systems to sensor data.
If you are interested, please email Prof. George Lykotrafitis by April 20.