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Who’s in the running for DOE Nuclear Lifecycle Innovation Campuses?
Today is the Department of Energy’s deadline for states to respond to a request for information on proposed Nuclear Lifecycle Innovation Campuses. Issued on January 28, the RFI marks the first step toward potentially establishing voluntary federal-state partnerships designed to build a coherent, end-to-end nuclear fuel cycle strategy for the country, including waste management, according to the DOE.
Makoto Ishikawa, Tetsuo Ikegami, Toshio Sanda
Nuclear Science and Engineering | Volume 178 | Number 3 | November 2014 | Pages 335-349
Technical Paper | doi.org/10.13182/NSE14-9
Articles are hosted by Taylor and Francis Online.
Under the International Reactor Physics Experiment Evaluation Project (IRPhEP) framework, in the cooperative JUPITER program between the United States and Japan, benchmarks are established to study large fast breeder reactor (FBR) core physics utilizing nine Zero Power Plutonium Reactor (ZPPR) critical experimental cores. These benchmarks cover a wide variety of core concepts including homogeneous and heterogeneous configurations, clean and engineering mock-up cores of 600- to 1000-MW(electric)–class sizes, and various core parameters such as criticality, reaction rate, and reactivity. Recently, detailed experimental information from original documents from Argonne National Laboratory has been scrutinized very carefully to establish the benchmark model and to evaluate quantitatively the experimental uncertainty. The benchmarks supply users with heterogeneous cell models and three-dimensional (3-D) core configurations, which are simplified to a degree that preserves the important physical features of the ZPPR cores such as plate heterogeneity, different drawer types, and 3-D core arrangement. Further, the benchmark handbook includes as-built information of the ZPPR cores as a complete set of electronic form; therefore, a user can develop his or her own benchmark model if necessary. The analysis of the benchmark with the deterministic or Monte Carlo method demonstrates its usefulness both for improving analytical methods and for validating nuclear data.