April (2017)—The SC State University Department of Nuclear Engineering was awarded a $288,060 grant from the U.S. Department of Energy, in order to conduct research that involves the usage of ‘Big Data’ to help predict nuclear accidents weeks before they occur. These predictions could prevent nuclear spills that would result in dangerous levels of radiation that could affect the health and safety of the public.
Operating in real time, this new system will be a direct link between SC State’s nuclear department and Savannah River Site’s National Laboratory (SRSNL), located in Jackson, South Carolina.
Dr. Zaijing Sun, principal investigator of the project and assistant professor of nuclear engineering, affirmed that this research has tremendous public value.
“This project is distinctive, in that for the first time, it will allow the combination of real-time data gathering, temporal data mining (TDM) and possible remote control access in a nuclear deactivation and decommission scene,” he said.
“The implementation of this project will greatly improve the speed of emergency response in the case of a nuclear accident and cut costs within the nuclear industry with the use of less nuclear personnel on site,” Sun continued.
‘Big Dat’a is defined as extremely large and complex data sets that need to be analyzed by a computer, in order to reveal patterns, trends and associations. In-situ monitoring and decommissioning of nuclear sites, like automobile assembly lines, generate large amounts of data, which are time-specific, age-specific and developmental stage-specific. This large amount of data is useful for finding unknown patterns of material failure, system breakdown and radiation leaking with TDM techniques. TDM is an active and rapidly evolving area in the ‘Big Data’ science.
As part of the project, researchers will test TDM theory on the In-Situ Decommissioning (ISD) sensor test bed located at the SRSNL. The ISD test bed is a unique, small-scale environment that can be used to effectively test prospective sensors needed to predict nuclear accidents on a real ISD system with minimal cost.
Sun hopes the research will help to enhance the university’s nuclear engineering program by expanding degree and course offerings as well as providing additional academic opportunities for students.
Sun said, “I want this program to grow, and this funding is a huge step in that direction. As, the only historically black college offering a nuclear engineering program, we want more students to join and contribute to significant developments within the nuclear industry.”
In addition to being the only such program offered at a historically black college, the Bachelor of Science in nuclear engineering, is the only undergraduate degree of its kind offered in the state of South Carolina. The program also ranks among the nation’s top 25 nuclear engineering programs. Holding #22, SC State’s nuclear engineering program joins the likes of MIT, Georgia Institute of Technology and the University of California Berkeley, according to collegechoice.net.
Sun is confident that students who have the opportunity to work on this project will leave the program highly skilled and will have a background in nuclear engineering as well as computer science. SC State’s Dr. Yong-Gyun Kim, associate professor of computer science, serves as co-principal investigator. Dr. Andrew Duncan is the lead engineer at the ISD Sensor Network Test Bed located at SRSNL. With his expertise, Duncan provides scientific and technical advice.