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Full-Text Articles in Engineering

Measuring Radiation Protection: Partners From Across The Nuclear Enterprise Evaluate The Radiation Protection Of Us Army Vehicles, Andrew W. Decker, Robert Prins Apr 2023

Measuring Radiation Protection: Partners From Across The Nuclear Enterprise Evaluate The Radiation Protection Of Us Army Vehicles, Andrew W. Decker, Robert Prins

Faculty Publications

Recent mounting nuclear threats and postures from adversary nation-states, such as Russia, China, North Korea, and Iran, represent a clear danger to the interests and security of the United States of America and its Allies. To meet these threats, the 2022 Nuclear Posture Review requires the Department of Defense (DoD) to design, develop, and manage a combat-credible U.S. military which, among other prioritizations, is survivable. A survivable force can generate combat power despite adversary attacks. As such, the US Army must prepare today to set the conditions for successful conventional warfare on the nuclear battlefields of tomorrow. Our Army cannot …


Fast-, Light-Cured Scintillating Plastic For 3d-Printing Applications, Brian G. Frandsen, Michael Febbraro, Thomas Ruland, Theodore W. Stephens, Paul A. Hausladen, Juan J. Manfredi, James E. Bevins Mar 2023

Fast-, Light-Cured Scintillating Plastic For 3d-Printing Applications, Brian G. Frandsen, Michael Febbraro, Thomas Ruland, Theodore W. Stephens, Paul A. Hausladen, Juan J. Manfredi, James E. Bevins

Faculty Publications

Additive manufacturing techniques enable a wide range of possibilities for novel radiation detectors spanning simple to highly complex geometries, multi-material composites, and metamaterials that are either impossible or cost prohibitive to produce using conventional methods. The present work identifies a set of promising formulations of photocurable scintillator resins capable of neutron-gamma pulse shape discrimination (PSD) to support the additive manufacturing of fast neutron detectors. The development of these resins utilizes a step-by-step, trial-and-error approach to identify different monomer and cross-linker combinations that meet the requirements for 3D printing followed by a 2-level factorial parameter study to optimize the radiation detection …


Data Augmentation For Neutron Spectrum Unfolding With Neural Networks, James Mcgreivy, Juan J. Manfredi, Daniel Siefman Jan 2023

Data Augmentation For Neutron Spectrum Unfolding With Neural Networks, James Mcgreivy, Juan J. Manfredi, Daniel Siefman

Faculty Publications

Neural networks require a large quantity of training spectra and detector responses in order to learn to solve the inverse problem of neutron spectrum unfolding. In addition, due to the under-determined nature of unfolding, non-physical spectra which would not be encountered in usage should not be included in the training set. While physically realistic training spectra are commonly determined experimentally or generated through Monte Carlo simulation, this can become prohibitively expensive when considering the quantity of spectra needed to effectively train an unfolding network. In this paper, we present three algorithms for the generation of large quantities of realistic and …