Login / Signup

Study of Morphological, Structural, and Strength Properties of Model Prototypes of New Generation TRISO Fuels.

Inesh KenzhinaPetr BlynskiyArtem L KozlovskiyMeiram BegentayevSaulet AskerbekovZhanna ZaurbekovaAktolkyn Tolenova
Published in: Materials (Basel, Switzerland) (2022)
The purpose of this work is to characterize the morphological, structural, and strength properties of model prototypes of new-generation TRi-structural ISOtropic particle fuel (TRISO) designed for Generation IV high-temperature gas reactors (HTGR-type). The choice of model structures consisting of inner pyrolytic carbon (I-PyC), silicon carbide (SiC), and outer pyrolytic carbon (O-PyC) as objects of research is motivated by their potential use in creating a new generation of fuel for high-temperature nuclear reactors. To fully assess their full functional value, it is necessary to understand the mechanisms of resistance to external influences, including mechanical, as in the process of operation there may be external factors associated with deformation and leading to the destruction of the surface of fuel structures, which will critically affect the service life. The objective of these studies is to obtain new data on the fuel properties, as well as their resistance to external influences arising from mechanical friction. Such studies are necessary for further tests of this fuel on corrosion and irradiation resistance, as closely as possible to real conditions in the reactor. The research revealed that the study samples have a high degree of resistance to external mechanical influences, due to the high strength of the upper layer consisting of pyrolytic carbon. The presented results of the radiation resistance of TRISO fuel testify to the high resistance of the near-surface layer to high-dose irradiation.
Keyphrases
  • high temperature
  • high dose
  • healthcare
  • mental health
  • low dose
  • risk assessment
  • electronic health record
  • machine learning
  • radiation induced
  • stem cell transplantation
  • wastewater treatment
  • big data
  • climate change