Create a preeminent research & education hub dedicated to the development of enabling technologies and technical talent for meeting the present and future grand challenges of nuclear nonproliferation.
Through an intimate mix of innovative research and development (R&D) and education activities, CNEC will enhance national capabilities in the detection and characterization of special nuclear material (SNM) and facilities processing SNM to enable the U.S. to meet its international nonproliferation goals, as well as to investigate the replacement of radiological sources so that they could not be misappropriated and used in dirty bombs or other deleterious uses.
The challenge problem for the Data Fusion and Analytic Techniques (DFAT) thrust area is to detect and characterize proliferation events and proliferation enterprise networks. DFAT focuses on the application of data science to nonproliferation problems.
S&O addresses the location of a point source of radiation in an urban environment containing fluctuating background and nuisance sources. S&O is concerned with improving existing and future detector systems by conducting multi-disciplinary research in uncertainty quantification and by analyzing individual sensor systems.
The Simulation, Analysis, and Modeling (SAM) team’s challenge problem is to develop methods that will enable the rapid localization of a radiation source in a cluttered, noisy urban environment.
Oil well logging tools are used around the world and, typically, contain curie-level Am-Be and Cs-137 sources. Our challenge problem is to find a suitable replacement for these radioisotope sources.
Total ambient dose equivalent buildup factors determination for NBS04 concrete
Duckic P, Hayes RB. Total ambient dose equivalent buildup factors determination for NBS04 concrete. Health Phys. 114, 569-581, 2018
Bayesian Metropolis Methods for Source Localization in an Urban Environment
J. Hite and J. Mattingly, “Bayesian Metropolis Methods for Source Localization in an Urban Environment,” Radiation Physics and Chemistry, accepted June 2018, available online at https://www.sciencedirect.com/science/article/pii/S0969806X17307867.
Fusing Heterogeneous Data -- A Case for Remote Sensing and Social Media
H. Wang, E. Skau, H. Krim, G. Cervone, “Fusing Heterogeneous Data- A Case for Remote Sensing and Social Media,” to appear in the July-August issue of IEEE Transactions on Geoscience and Remote Sensing.
Slowing-down and stopped charged particles cause angular dependence for absorbed dose measurements
Amir A. Bahadori, Rajarshi Pal Chowdhury, Martin Kroupa, Thomas Campbell-Ricketts, Ana Firan, Dan J. Fry, Ramona Gaza, Stuart P. George, Lawrence S. Pinsky, Nicholas N. Stoffle, Ryan R. Rios, Cary J. Zeitlin, “Slowing-down and stopped charged particles cause angular dependence for absorbed dose measurements”, Radiation Physics and Chemistry, 2018.