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Division Spotlight
Accelerator Applications
The division was organized to promote the advancement of knowledge of the use of particle accelerator technologies for nuclear and other applications. It focuses on production of neutrons and other particles, utilization of these particles for scientific or industrial purposes, such as the production or destruction of radionuclides significant to energy, medicine, defense or other endeavors, as well as imaging and diagnostics.
Meeting Spotlight
2024 ANS Winter Conference and Expo
November 17–21, 2024
Orlando, FL|Renaissance Orlando at SeaWorld
Standards Program
The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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Nuclear Science and Engineering
September 2024
Nuclear Technology
Fusion Science and Technology
August 2024
Latest News
Nuclear supply chain innovation and collaboration: Keeping the nuclear supply chain viable through change
The next nuclear renaissance may be upon us, but with it comes a perfect storm. The industry is unprepared for a surge in demand for goods and services from both the existing light water fleet and the next generation of reactors. We are currently teetering on the edge of severe supply chain issues, but if the nuclear industry can understand the sources of our challenges, we can mitigate them.
Jorge Navarro, Terry A. Ring, David W. Nigg
Nuclear Technology | Volume 190 | Number 2 | May 2015 | Pages 183-192
Technical Paper | Fuel Cycle and Management | doi.org/10.13182/NT14-4
Articles are hosted by Taylor and Francis Online.
A deconvolution methodology aimed to reduce the uncertainty for nondestructively predicting fuel burnup using gamma spectra collected with LaBr3 scintillators was developed. Deconvolution techniques have been used in the past to improve photopeak resolution of data collected using gamma detectors; however, they have not been used as a tool to more accurately predict fuel burnup. The deconvolution methodology consisted of calculating the detector response function using Monte Carlo simulations, validating the detector response function against experimental data, and implementing the maximum likelihood expectation maximization algorithm to enhance the LaBr3 gamma spectra. The deconvolution methodology was first tested on single-isotopic simulated data; later it was applied to fuel simulated data that were based on Advanced Test Reactor (ATR) fuel gamma spectra. The study showed that LaBr3 gamma spectra photopeak resolution and quality can be improved significantly using deconvolution methods, in addition to proving that enhancement techniques can be used to nondestructively predict ATR fuel burnup more accurately than using LaBr3 data without enhancements.