Highlights
Enabling Technology and Innovation Highlights
1. Textual data, such as nuclear science manuscripts, contains information that can enable nuclear proliferation detection. Topic modeling is a technique within natural language processing that can be applied to this type of corpus to understand active areas of research. However, given the dynamic nature of scientific literature, a dynamic approach is needed to automatically model emerging trends and detect anomalies in high-volume streaming data. To this end, we have developed a scalable tool based on dynamic topic models and computational geometry for visualizing trends and anomalies. This work modified a prior model, which was demonstrated on Twitter data, for use on Office of Scientific and Technical Information scientific abstract data. Illustrations from this analysis are provided in Figure 1. On the left, we depict word clouds for the nine topics identified during the period 1940–2020. On the right, the 2-dimensional similarity between topics is measured by Potential of Heat-diffusion for Affinity-based Transition Embedding dimension reduction and colored by year. As seen in this figure, topic one evolves significantly more than other topics over the 80 years.
2. As an additional highlight, PNNL also worked with Enabling Technology and Innovation (ETI) colleagues to help build out and deliver the curriculum for “ETI 101 - Fundamentals of Nuclear Science and Engineering for Nonproliferation.” In particular, PNNL completed the organization and content for “ETI 101 Module 4 - Overview of Nuclear Security and Nonproliferation” which featured a live “tour” of PNNL’s Shallow Underground Laboratory for Trace Detection by Emily Mace. Also, PNNL’s Sarah Frazer helped to organize a new set of topics for “ETI 101 Module 5 - Nexus of Technology and Policy” which featured two different lectures by staff at PNNL – “History and Development of Nonproliferation System” by Robert Marek and “International Treaty Context of Nonproliferation and Arms Control” by Kate Doty.
Monitoring, Technology, and Verification Highlights
- At the 2021 NNSA University Program Review, University of Michigan student Patrick Skrodzki was presented the Best National Laboratory Collaboration Award for MTV in recognition of his collaborative work with PNNL, as presented in Generation and Characterization of Nonproliferation Signatures in Laser-Produced Plasmas at the meeting.
Other Highlights
- PNNL participants joined the 2022 NNSA University Program Review held at the University of Michigan.