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Decommissioning & Environmental Sciences
The mission of the Decommissioning and Environmental Sciences (DES) Division is to promote the development and use of those skills and technologies associated with the use of nuclear energy and the optimal management and stewardship of the environment, sustainable development, decommissioning, remediation, reutilization, and long-term surveillance and maintenance of nuclear-related installations, and sites. The target audience for this effort is the membership of the Division, the Society, and the public at large.
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Conference on Nuclear Training and Education: A Biennial International Forum (CONTE 2025)
February 3–6, 2025
Amelia Island, FL|Omni Amelia Island Resort
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Latest News
Feinstein Institutes to research novel radiation countermeasure
The Feinstein Institutes for Medical Research, home of the research institutes of New York’s Northwell Health, announced it has received a five-year, $2.9 million grant from the National Institutes of Health to investigate the potential of human ghrelin, a naturally occurring hormone, as a medical countermeasure against radiation-induced gastrointestinal syndrome (GI-ARS).
Jaakko Leppänen
Nuclear Technology | Volume 205 | Number 11 | November 2019 | Pages 1416-1432
Technical Paper | doi.org/10.1080/00295450.2019.1603710
Articles are hosted by Taylor and Francis Online.
A deterministic importance solver has been implemented as an internal subroutine in the Serpent 2 Monte Carlo code for the purpose of producing weight-window meshes for variance reduction. The routine solves the adjoint transport problem using the response matrix method with coupling coefficients obtained from a conventional forward Monte Carlo simulation. The methodology can be applied to photon and neutron external source problems, and the solver supports multiple energy groups and several mesh types. Importances can be generated with respect to multiple responses, and an iterative global variance reduction sequence enables distributing the transported particle population evenly throughout the geometry. This paper describes the methodology applied in the response matrix solver and presents a verification for the generated importance functions through simple demonstrations. A practical example involving a photon shielding problem is included for performance evaluation.