INTEGRITY EVALUATION OF SPENT NUCLEAR FUEL CLADDING IN USE OF MACHINE LEARNED EMBRITTLED PROPERTIES

Integrity of spent nuclear fuel (SNF) cladding should be remained during transportation as well as long-term storage and disposal. At first, this paper addresses machine learning to predict degraded mechanical properties of an advanced zirconium alloy. Subsequently, taking into account the estimated data, finite element analyses of a typical fuel rod were carried out under hypothetical drop accident conditions and resulting integrity was discussed.
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