Forthcoming, 3:00 ~ 4:00 pm (ET)
- May 23, 2024, Dr. Ken Dayman (Nonproliferation Data Scientist, Oak Ridge National Laboratory).
April 25, 2024
- Dr. Vincent DiNova (Senior Nuclear Engineer, Savannah River National Laboratory), “Re-Imagining Qualification for Additive Manufacturing”
Abstract: Additive manufacturing offers exciting potential for the future of materials science and component design; however, qualification remains a major hurdle to widespread adaptation and usage. To fully realize the potential additive manufacturing poses, new analytical tools must be developed. The aim of our research at Savannah River National Laboratory is to develop software and technical solutions to better understand AM materials and components and ultimately develop a pathway to qualify AM parts for insertion. From software development to machine learning solutions: past/present/future NDE and analytical techniques developed at SRNL will be presented.
January 25, 2024
- Dr. Evangelina Brayfindley (Senior Data Scientist, Pacific Northwest National Laboratory), “Data Science for Safeguards”
Abstract: This will be an introduction to the IAEA, Safeguards, and the challenges of building data science approaches to safeguards questions. This will include an overview of several data science projects–including NLP and synthetic data generation projects–happening both at the US national labs as well as at the IAEA.
November 30, 2023
- Dr. Robert Lascola (Senior Fellow Scientist and Group Lead, Online Monitoring, Savannah River National Laboratory), “Raman Spectroscopy – A Valuable Tool for Monitoring Nuclear Materials Processing”
Abstract: Raman spectroscopy is an optical analysis technique that is complementary to infrared (IR) absorbance spectroscopy for the analysis of molecular species. Although the Raman scattering signal is far weaker per molecule than IR absorbance, the technique has certain properties that make it well suited for applications related to nuclear materials processing. For example, Raman spectroscopy is usually practiced using visible light, which makes it suitable for use with optical fibers. In this way, instruments and personnel can be kept out of radiological environments. Of the optical-based techniques, Raman is uniquely sensitive to molecules like N2, O2, and the various isotopologues of H2. And, in the last 20-30 years Raman has been the subject of intense commercial development, such that Raman spectrometers are being used for process monitoring in many industries. In this talk, I will introduce the method and provide three examples of how it is being used or developed to support nuclear materials processing at SRNL. These examples include: monitoring nuclear fuel dissolution, isotopic hydrogen analysis for tritium processing, and tracking of key constituents in actinide separations.
October 26, 2023
- Zach Condon (Prof. Richard Vasques’s group, The Ohio State University), “Unfolding Neutron Energy Spectra using Neural Networks”
Abstract: Acquiring accurate neutron energy spectrum information is of vital importance to national security as well as personal safety. Unfolding neutron energy spectra from detector responses is a heavily researched area due to the importance of neutron energy for determining radiation dose received. A novel detection system, the passive neutron spectrometer (PNS), is being investigated for use in energy spectrum unfolding techniques. The benefit of this detector is the passive detection of neutrons through the use of 55 thermoluminescent dosimeters or gold foils contained within a single polyethylene sphere. Multiple experimental PNS detector responses were unfolded using the well-established MAXED and GRAVEL algorithm as well as through neural network technique. The neural networks used for this research will be trained and optimized using training data from the IAEA. To increase the accuracy of the unfolded network, techniques for developing artificial training data will also be explored.