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Division members promote the advancement of mathematical and computational methods for solving problems arising in all disciplines encompassed by the Society. They place particular emphasis on numerical techniques for efficient computer applications to aid in the dissemination, integration, and proper use of computer codes, including preparation of computational benchmark and development of standards for computing practices, and to encourage the development on new computer codes and broaden their use.
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First astatine-labeled compound shipped in the U.S.
The Department of Energy’s National Isotope Development Center (NIDC) on March 31 announced the successful long-distance shipment in the United States of a biologically active compound labeled with the medical radioisotope astatine-211 (At-211). Because previous shipments have included only the “bare” isotope, the NIDC has described the development as “unleashing medical innovation.”
Hany S. Abdel-Khalik, Paul J. Turinsky, Matthew A. Jessee
Nuclear Science and Engineering | Volume 159 | Number 3 | July 2008 | Pages 256-272
Technical Paper | doi.org/10.13182/NSE159-256
Articles are hosted by Taylor and Francis Online.
This paper introduces the concepts and derives the mathematical theory of efficient subspace methods (ESMs) applied to the simulation of large-scale complex models, of which nuclear reactor simulation will serve as a test basis. ESMs are intended to advance the capabilities of predictive simulation to meet the functional requirements of future energy system simulation and overcome the inadequacies of current design methods. Some of the inadequacies addressed by ESM include lack of rigorous approach to perform comprehensive validation of the multitudes of models and input data used in the design calculations and lack of robust mathematical approaches to enhance fidelity of existing and advanced computational codes. To accomplish these tasks, the computational tools must be capable of performing the following three applications with both accuracy and efficiency: (a) sensitivity analysis of key system attributes with respect to various input data; (b) uncertainty quantification for key system attributes; and (c) adaptive simulation, also known as data assimilation, for adapting existing models based on the assimilated body of experimental information to achieve the best possible prediction accuracy. These three applications, involving large-scale computational models, are now considered computationally infeasible if both the input data and key system attributes or experimental information fields are large. This paper will develop the mathematical theory of ESM-based algorithms for these three applications. The treatment in this paper is based on linearized approximation of the associated computational models. Extension to higher-order approximations represents the focus of our ongoing research.