Development of a surrogate model for dynamic risk assessment using anisotropic Taylor Kriging methodology

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Authors
Christian, Robby
Issue Date
2019-05
Type
Electronic thesis
Thesis
Language
ENG
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Nuclear engineering
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Abstract
The proposed surrogate methodology was applied on two separate research projects we work on: (1) risk assessment of spent nuclear fuel transportation, and (2) risk assessment of Accident Tolerant Fuel (ATF). As we developed the risk model of maritime spent fuel transportation, we found that dynamic trajectories of shipment route affect the risk metrics significantly. Since there is an infinite possible route combination over the sea, we leveraged the surrogate model to find the safest shipment route efficiently. The proposed surrogate method was able to identify the safest route, by avoiding risky marine traffic intersections which could lead to ship collisions and transport cask damage. Meanwhile, in the latter project, we optimized the Emergency Core Cooling System (ECCS) performance criteria to properly boost the accident-tolerance characteristics of a multi-layered SiC cladding structure. Because ATF has a better thermal margin relative to current UO2-Zr system, there is a relatively wider range of ECCS operational performance the fuel can safely tolerate. Therefore, we used the surrogate model to predict SiC clad responses over this broad range of allowable ECCS performance uncertainty. The model suggested that conservatism in ECCS performance requirements could be relaxed while still maintaining a net positive safety margin relative to UO2-Zr system, which may lead to operational cost savings to plant operators in conformance to 10 CFR 50.69.
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May 2019
School of Engineering
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Rensselaer Polytechnic Institute, Troy, NY
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