Abstract
Oak Ridge National Laboratory (ORNL) receives, archives, and analyzes data from radiation portal monitors (RPMs). Over time the amount of data submitted for analysis has grown significantly, and in fiscal year 2013, ORNL received 545 gigabytes of data representing more than 230,000 RPM operating days. This data comes from more than 900 RPMs. ORNL extracts this data into a relational database, which is accessed through a custom software solution called the Desktop Analysis and Reporting Tool (DART). DART is used by data analysts to complete a monthly lane-by-lane review of RPM status. Recently ORNL has begun to extend its data analysis based on program-wide data processing in addition to the lane-by-lane review. Program-wide data processing includes the use of classification algorithms designed to identify RPMs with specific known issues and clustering algorithms intended to identify as-yet-unknown issues or new methods and measures for use in future classification algorithms. This paper provides an overview of the architecture used in the management of this data, performance aspects of the system, and additional requirements and methods used in moving toward an increased program-wide analysis paradigm.
