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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
Utility Working Conference and Vendor Technology Expo (UWC 2024)
August 4–7, 2024
Marco Island, FL|JW Marriott Marco Island
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
August 2024
Nuclear Technology
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Latest News
Constellation seeks rezone for property adjacent to Illinois plant
While no development details have been released, Constellation is asking to rezone 658.8 acres of land it owns around the Byron nuclear plant in Illinois for possible long-term use.
Mauricio Tano, Pablo Rubiolo (Univ of Grenoble-Alpes), Julien Giraud, Veronique Ghetta (LPSC, CNRS/IN2P3)
Proceedings | 2018 International Congress on Advances in Nuclear Power Plants (ICAPP 2018) | Charlotte, NC, April 8-11, 2018 | Pages 533-542
Inverse problem methods deal with the evaluation of the causal factors that result on a set of measurements or observations. Inverse problems found in nuclear reactors involve non-linear and coupled physical phenomena, making the causation effects complicated to de assessed. Furthermore, the extent of the experimental data collected is limited and this data is subjected to experimental noise. In the following paper, a method for solving inverse problems in nuclear reactors with coupled physical phenomena is developed. In the proposed approach, the inverse problem is solved through the minimization of a performance function. The minimization of this performance function is achieved with a preconditioned gradient descendent method. The generalized gradient of the performance function is obtained using the adjoint of the multiphysics equations of the system. Furthermore, for reducing the sensitivity to noise of the inverse problem, a preconditioner based in a Kalman Filter is developed. As an example, the methodology is applied for solving the inverse problem of finding the heat flux in the wall of a natural convection experiment.