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2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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Latest News
Disease-resistant cauliflower created through nuclear science
International Atomic Energy Agency researchers have helped scientists on the Indian Ocean island nation of Mauritius to develop a variety of cauliflower that is resistant to black rot disease. The cauliflower was developed through innovative radiation-induced plant-breeding techniques employed by the Joint Food and Agriculture Organization (FAO)/IAEA Centre of Nuclear Techniques in Food and Agriculture.
William J. Walters, Nathan J. Roskoff, Alireza Haghighat
Nuclear Science and Engineering | Volume 192 | Number 1 | October 2018 | Pages 21-39
Technical Paper | doi.org/10.1080/00295639.2018.1497395
Articles are hosted by Taylor and Francis Online.
The Real-time Analysis for Particle transport and In-situ Detection (RAPID) code uses a unique, extremely fast, fission matrix–based methodology to compute the eigenvalue, and three-dimensional, pinwise fission source distribution for reactor, spent fuel pool, and spent fuel cask problems. In this paper, the RAPID fission matrix method is described and analyzed for application to several large pressurized water reactor problems, based on the Organisation for Economic Co-operation and Development/Nuclear Energy Agency Monte Carlo Performance Benchmark problem. In the RAPID methodology, fission matrix coefficients precalculated using the Serpent Monte Carlo code, are then coupled together and solved for different core arrangements. A boundary correction method is used to obtain more accurate fission matrix values near the radial and axial reflectors. Eigenvalues and fission source distributions are compared between RAPID and Serpent reference calculations. In most cases, the eigenvalue differences between methods are less than 10 pcm. For a uniform core model, pinwise fission distributions between the methods differ by a root-mean-square value of , compared to a Serpent uncertainty of . The pinwise, axially dependent (100 axial levels) differences are , compared to a similar Serpent uncertainty of . To achieve these levels of uncertainty, the RAPID calculations are over 2500 times faster than Serpent, not counting the precalculation time.