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Mathematics & Computation
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.
2024 ANS Annual Conference
June 9–12, 2024
Las Vegas, NV|The Mirage
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The Sodium Reactor Experiment
In February 1957, construction was completed on the Sodium Reactor Experiment (SRE), a sodium-cooled, graphite-moderated reactor with an output of 20 MWt. The design of theSRE had begun three years earlier in 1954, and construction started in April 1955. On April 25, 1957, the reactor reached criticality, and the SRE operated until February 1964.
Diego Mandelli, Andrea Alfonsi, Congjian Wang, Zhegang Ma, Carlo Parisi, Tunc Aldemir, Curtis Smith, Robert Youngblood
Nuclear Technology | Volume 207 | Number 3 | March 2021 | Pages 363-375
Technical Paper | doi.org/10.1080/00295450.2020.1776030
Articles are hosted by Taylor and Francis Online.
A new generation of dynamic methods has started receiving attention for nuclear reactor probabilistic risk assessment (PRA). These methods, which are commonly referred to as dynamic PRA (DPRA) methodologies, directly employ system simulators to evaluate the impact of timing and sequencing of events (e.g., failure of components) on accident progression. Compared to classical PRA (CPRA) methods, which are based on static Boolean logic structures such as fault trees and event trees (ETs), DPRA methods can provide valuable insights from an accident management perspective. However, as of today this class of methods has received limited attention in practical applications. One factor is DPRA research and development has progressed mostly as an alternative to state-of-practice CPRA methods (i.e., disconnected from currently employed PRA methods). This disconnect is addressed in this paper by presenting several algorithms that can be employed to bridge the gap between CPRA and DPRA. First, algorithms designed to identify differences between CPRA and DPRA results are presented. The identification process compares the CPRA ET sequence or the minimal cut sets (MCSs) obtained by CPRA with the set of transients simulated by the DPRA. If inconsistencies are observed, solutions are provided to incorporate these differences back into the CPRA by employing DPRA to inform existing CPRA. We performed this incorporation either probabilistically (e.g., by updating MCS probability) or topologically (by adding new branching conditions or sequences in the ET).