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Materials Science & Technology
The objectives of MSTD are: promote the advancement of materials science in Nuclear Science Technology; support the multidisciplines which constitute it; encourage research by providing a forum for the presentation, exchange, and documentation of relevant information; promote the interaction and communication among its members; and recognize and reward its members for significant contributions to the field of materials science in nuclear technology.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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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Latest News
Securing the advanced reactor fleet
Physical protection accounts for a significant portion of a nuclear power plant’s operational costs. As the U.S. moves toward smaller and safer advanced reactors, similar protection strategies could prove cost prohibitive. For tomorrow’s small modular reactors and microreactors, security costs must remain appropriate to the size of the reactor for economical operation.
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.