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Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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Powering the future: How the DOE is fueling nuclear fuel cycle research and development
As global interest in nuclear energy surges, the United States must remain at the forefront of research and development to ensure national energy security, advance nuclear technologies, and promote international cooperation on safety and nonproliferation. A crucial step in achieving this is analyzing how funding and resources are allocated to better understand how to direct future research and development. The Department of Energy has spearheaded this effort by funding hundreds of research projects across the country through the Nuclear Energy University Program (NEUP). This initiative has empowered dozens of universities to collaborate toward a nuclear-friendly future.
P. D. Krishnani, K. R. Srinivasan
Nuclear Science and Engineering | Volume 78 | Number 1 | May 1981 | Pages 97-103
Technical Note | doi.org/10.13182/NSE81-A19614
Articles are hosted by Taylor and Francis Online.
A method based on interface current formalism has been developed for solving the integral transport equation for cylindered pressurized heavy water reactor fuel lattices. In this a fuel cluster is divided into various rings, which are further subdivided into homogeneous zones like fuel, cladding, and associated coolant. The region outside the fuel cluster is also divided into a number of concentric annular (homogeneous) regions. A cosine current approximation is assumed at all the interfaces of the rings and annular regions while interactions between zones within a ring are directly calculated by the Pij method. In addition to this, the usual flat flux approximation is assumed for each of the homogeneous zones/regions. Based on this method, we have developed a one-group code, ANPROB, for calculating the flux distribution. The results obtained from the present method for 19- and 28-rod cluster lattices have been compared with the exact collision probability (Pij) method for clusters. It is found that the present method reduces the computational time considerably without sacrificing much of the accuracy.