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Fusion Science and Technology
Latest News
In transition: Commercializing fusion power
Commercial fusion power is closer than ever. There are now around 30 U.S. fusion companies, several of which claim to be on track to connect to the grid as early as the 2030s.
Tokamak and laser inertial confinement approaches benefit from decades of research at facilities such as the National Ignition Facility (NIF) at Lawrence Livermore National Laboratory and ITER, with alternative concepts including stellarator, magnetic mirror, and Z-pinch confinement also making notable progress as private and government funding for fusion increases.
Ioannis A. Papazoglou, Elias P. Gyftopoulos
Nuclear Science and Engineering | Volume 73 | Number 1 | January 1980 | Pages 1-18
Technical Paper | doi.org/10.13182/NSE80-A18703
Articles are hosted by Taylor and Francis Online.
A methodology for the assessment of uncertainties about reliability of nuclear reactor systems described by Markov models is developed, and the uncertainties about the failure probability of the shutdown system of the Clinch River Breeder Reactor (CRBR) are assessed. Failure and repair rates and all other inputs of reliability analysis are taken as random variables with known probability distribution functions (pdf's). The pdf of reliability is calculated by both a Monte Carlo simulation and a Taylor series expansion approximation. Three techniques are developed to reduce the computational effort: (a) ordering of system states, (b) merging of Markov processes, and (c) judicious choice of time steps. A Markov model has been used for reliability analysis under uncertainty of the shut- down system of the CRBR. It accounts for common-cause failures, interdependences between unavailability of the system and occurrence of transients, and inspection and maintenance procedures that depend on the state of the system and that include possibility of human errors. Under these conditions, the failure probability of the shutdown system differs significantly from that computed without common-cause failures, human errors, and input uncertainties.