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This division promotes the development and timely introduction of fusion energy as a sustainable energy source with favorable economic, environmental, and safety attributes. The division cooperates with other organizations on common issues of multidisciplinary fusion science and technology, conducts professional meetings, and disseminates technical information in support of these goals. Members focus on the assessment and resolution of critical developmental issues for practical fusion energy applications.
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June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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Excelsior University student section awarded community education grant
The American Nuclear Society Student Section at Excelsior University in Albany, N.Y., was awarded a $5,000 grant from the ANS Student Section Strategic Fund initiative for its program, Empowering Tomorrow’s Nuclear Innovators: A Collaborative Approach to Nuclear Technology Education and Awareness.
Jeffrey A. Favorite
Nuclear Science and Engineering | Volume 146 | Number 1 | January 2004 | Pages 51-70
Technical Paper | doi.org/10.13182/NSE02-96
Articles are hosted by Taylor and Francis Online.
A new iterative inverse method for gamma-ray transport problems is presented. The method, based on a novel application of the Schwinger variational functional, is developed as a perturbation problem in which the current model (in the iterative process) is considered the initial, unperturbed system, and the actual model is considered the perturbed system. The new method requires the solution of a set of uncoupled one-group forward and adjoint transport equations in each iteration. Four inverse problems are considered: determination of (a) interface locations in a multilayer source/shield system, (b) the isotopic composition of an unknown source (including inert elements), (c) interface locations and the source composition simultaneously, and (d) the composition of an unknown layer in the shield. Only the first two problems were actually solved in numerical one-dimensional (spherical) test cases. The method worked well for the unknown interface location problem and extremely well for the unknown source composition problem. Convergence of the method was heavily dependent on the initial guess.