Optimization of Systems Repair Plans and Assessment of the Useful Life of Nuclear Power Plant Equipment

image_print
DOI https://doi.org/10.15407/pmach2020.04.072
Journal Journal of Mechanical Engineering
Publisher A. Pidhornyi Institute for Mechanical Engineering Problems
National Academy of Science of Ukraine
ISSN  2709-2984 (Print), 2709-2992 (Online)
Issue Vol. 23, no. 4, 2020 (December)
Pages 72-78
Cited by J. of Mech. Eng., 2020, vol. 23, no. 4, pp. 72-78

 

Authors

Leonid I. Zevin, A. Pidhornyi Institute of Mechanical Engineering Problems of NASU (2/10, Pozharskyi St., Kharkiv, 61046, Ukraine), e-mail: leonid.zevin@gmail.com

Hennadii H. Krol, A. Pidhornyi Institute of Mechanical Engineering Problems of NASU (2/10, Pozharskyi St., Kharkiv, 61046, Ukraine)

 

Abstract

This paper presents a computer-aided method of planning the volumes of repairs of systems of nuclear power units and a method for calculating their gamma-percentile life. This planning is carried out on the basis of predicting the reliability indicator, the probability of no-failure operation for a certain time period, with the gamma-percentile life of the equipment being determined by solving the corresponding equations. The tasks considered are related to an important energy problem of extending the operation of nuclear power units. Its importance is determined mainly by economic feasibility: it is cheaper to assess the useful life of a nuclear power unit and, on this research basis, extend its operation, than create a new unit. It is also shown that the calculation of the probability of a radiation accident at a nuclear power unit is associated with the results of planning the repairs of its systems, with assessment of its useful life. An optimization problem is formulated: it is required to find such a plan for the volumes of repair of a system that, with limited repair costs, its reliability indicator for a given duration deviates least from the maximum permissible value. The solution to the problem is based on calculating the structural reliability of the system. A graphological image of the system is built in the form of a composition of graphological images of typical structures. After the reliability indicator of typical structures has been calculated, the structures are replaced with individual structural elements, which makes it possible to simplify the initial graphological image of the system in a computational scenario and calculate its reliability indicator. The determination of the repair volume is carried out by applying a version of the coordinate-wise optimization method. To assess the gamma-percentile life, a model is adopted, in which the recoverable equipment components have an unlimited life, although, of course, they “age”, and the non-recoverable components spend their life up to the level when their replacement becomes conditioned by the violation of the requirement for the maximum permissible value of the system reliability indicator. Estimates of the gamma-percentile life of the equipment are calculated by planning system repairs on a sequence of intervals of annual energy production by a nuclear power unit.

 

Keywords: nuclear power plant, power unit, system, repair plan, useful life, optimization.

 

Full text: Download in PDF

 

References

  1. Rast, J. & Weevir, L. (1980). Bezopasnost yadernoy energetiki [Safety of nuclear energy]. Moscow: Atomizdat, 183 p. (in Russian).
  2. Ostreykovskiy, V. A. (1994). Stareniye i prognozirovaniye resursa oborudovaniya atomnykh stantsiy [Aging and forecasting of the resource of equipment of nuclear power plants]. Moscow: Atomizdat, 288 p. (in Russian).
  3. Polovko, A. M. & Gurov, S. V. (2006). Osnovy teorii nadezhnosti [Basics of reliability theory]. St. Petersburg: BKHV-Peterburg, 704 p. (in Russian).
  4. Venttsel, Ye. S. (1972). Issledovaniye operatsiy [Operations research]. Moscow: Sovetskoye radio, 550 p. (in Russian).
  5. Zevin, L. I. & Krol, H. H. (2019). Calculation of indicators of reliability of technical systems by the typical structural scheme method. Journal of Mechanical Engineering, vol. 22, no. 2, pp. 53–59. https://doi.org/10.15407/pmach2019.02.053.

 

Received 28 April 2020

Published 30 December 2020