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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.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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Latest News
X-energy receives federal tax credit for TRISO fuel facility
Advanced reactor company X-energy has been awarded $148.5 million in tax credits under the Inflation Reduction Act for construction of its TRISO-X fuel fabrication facility in Oak Ridge, Tenn.
Jinkai Wang, Warren D. Reece
Nuclear Science and Engineering | Volume 167 | Number 2 | February 2011 | Pages 154-164
Technical Paper | doi.org/10.13182/NSE09-94
Articles are hosted by Taylor and Francis Online.
The relative yields of delayed neutrons and the half-lives of their precursor nuclei are usually determined indirectly by the least-squares method based on the differences between experimental and fitted data. It is noted that the recommended values from ENDF/B-VII, ENDF/B-VI.8, JENDL-3.3, JEF-2.2, and JEFF-3.1 are significantly different. To evaluate these parameters, the measured data sets used in this research were simulated by the Monte Carlo method, and they were strict Poisson distributed data generated from Keepin's six-group data. Three different numerical methods (matrix inverse with singular value decomposition, Levenberg-Marquardt, and quasi Newton) with different regularization techniques were applied to estimate the parameter values. The fitted results were proven to be very unstable, and their calculated results were very different even for the same data set. Further investigation found ill-conditioned problems to be the reason for this instability. A better numerical method was suggested in this research.