The DOE Office of Nuclear Energys (NE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program, in cooperation with the U.S. Nuclear Regulatory Commission (NRC) and in- dustry, develops, demonstrates, and deploys usable advanced modeling and simulation capabilities to accelerate the deployment of advanced nuclear energy technologies, including light-water reactors (LWRs), non-light-water reactors (non-LWRs), and advanced fuels. The availability of the NEAMS codes has enabled transformative scientific discovery and insights otherwise not attainable or af- fordable. These capabilities present enormous opportunities for researchers in design, operation, regulation, safety margin characterization, and performance optimization. However, analyzing the resulting large-scale, complex data into actionable insights is a real challenge for the researcher. The ability of computational experiments to generate large datasets has far exceeded analysis ca- pabilities. Thus, only a small amount of the data is actually employed to create insights. The rich information encapsulated in the simulation data is often neglected for the lack of human resources required to perform tedious and systematic data exploration. We seek to expose user-friendly advanced analytics and visualizations to allow end-users to achieve the best return on investment (ROI) from their NEAMS-enabled activities. We propose to provide an easy-to-use platform to create bespoke visual analytics of NEAMS code capabilities and contribute them to the Virtual Test Bed (VTB) of the National Reactor Innovation Center (NRIC) for the broader nuclear energy community consumption. In our proposed Phase I project, we will build bespoke visual analytics prototypes deployable on a desktop, an HPC supercomputer, and the cloud. We will enhance interactive exploration, pushing the boundaries of possible solutions with large-scale datasets leveraging state-of-the-art technologies for scientific and information analysis and visualization. We propose extending our key innovation of dynamic switching between local and remote analysis and visualization with new NEAMS code-specific components to deliver production-ready bespoke visual analytics through various computational environments. The work proposed here addresses the deficiencies in current platforms to grow a substan- tial share of this market. In particular, we are targeting both the nuclear energy industry and manufacturing and engineering firms that can benefit from the underlying technology to improve productivity.
