NEUP CINR-18-15346: Big Data For Operation and Maintenance Cost Reduction

This research develops a first-of-a-kind framework to integrate Big Data capability into the daily activities of nuclear power plants. Big Data consists of data sets with high volume, velocity and heterogeneity. In the nuclear industry, data heterogeneity constitutes the major challenge, addressed in this proposal through machine learning. The information extracted is then used to generate plans automatically that provide input to plant management and reduces operation and maintenance costs.

Additional Info

Field	Value
Awarded Institution	The Ohio State University
PI	Carol Smidts