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Fuel Cycle & Waste Management
Devoted to all aspects of the nuclear fuel cycle including waste management, worldwide. Division specific areas of interest and involvement include uranium conversion and enrichment; fuel fabrication, management (in-core and ex-core) and recycle; transportation; safeguards; high-level, low-level and mixed waste management and disposal; public policy and program management; decontamination and decommissioning environmental restoration; and excess weapons materials disposition.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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Latest News
Former Exelon CEO Chris Crane remembered for “transformational milestones”
Crane
Exelon announced that Chris Crane, the company’s former chief executive, passed away on Saturday in Chicago at the age of 65.
Crane served as the company’s president and CEO from 2012 until his retirement in December 2022. During his tenure, he steered the energy company through several transformational milestones, including the successful mergers with Constellation Energy in 2012 and Pepco Holdings in 2016, creating the largest utility business by customer count in the United States.
In 2022, with the spin-off of Constellation as the generation and retail side of energy business (with the largest U.S. nuclear fleet), Crane led the creation of a stand-alone transmission and delivery energy company.
Quentin Newell, Charlotta Sanders
Nuclear Science and Engineering | Volume 179 | Number 3 | March 2015 | Pages 253-263
Technical Paper | doi.org/10.13182/NSE13-44
Articles are hosted by Taylor and Francis Online.
The Monte Carlo (MC) method is becoming popular for three-dimensional fuel depletion analyses to compute quantities of interest in used nuclear fuel including isotopic compositions. However, there are some questions concerning the effect of MC uncertainties on predicted results in MC depletion calculations. The MC method introduces stochastic uncertainty in the computed fluxes. These fluxes are used to collapse cross sections, estimate power distributions, and deplete the fuel within depletion calculations; therefore, the predicted number densities also contain random and propagated uncertainties due to the MC solution to the neutron transport equation. The linear uncertainty nuclide group approximation (LUNGA) method was developed to calculate the propagated stochastic uncertainty in the nuclear isotopics, using the time-varying flux subjected to the power normalization constraint. Verification of the LUNGA method demonstrated that the standard deviation in the number densities and infinite multiplication factor (kinf) predicted by this method agree well with the uncertainty obtained from the statistical analysis of 100 different simulations performed with coupled MC depletion calculations. Future research includes (a) expanding the LUNGA methodology to include more nuclides, (b) fully automating the methodology, and (c) investigating the use of an axial segmented fuel rod.