Affiliation:
1. JSC “All-Russian Research Institute for Nuclear Power Plants Operation” (JSC VNIIAES)
Abstract
The destruction of equipment metal by a brittle fracture mechanism is a probabilistic event at nuclear power plants (NPP). The calculation for resistance to brittle destruction is performed for NPP equipment exposed to neutron irradiation; for example, for a reactor plant such as a water-water energetic reactor (WWER), this is a reactor pressure vessel. The destruction of the reactor pressure vessel leads to a beyond design-basis accident, therefore, the determination of the probability of brittle destruction is an important task. The research method is probabilistic analysis of brittle destruction, which takes into account statistical data on residual defectiveness of equipment, experimental results of equipment fracture toughness and load for the main operating modes of NPP equipment. Residual defectiveness (a set of remaining defects in the equipment material that were not detected by non-destructive testing methods after manufacturing (operation), control and repair of the detected defects) is the most important characteristic of the equipment material that affects its strength and service life. A missed defect of a considerable size admitted into operation can reduce the bearing capacity and reduce the time of safe operation from the nominal design value down to zero; therefore, any forecast of the structure reliability without taking into account residual defectiveness will be incorrect. The application of the developed method is demonstrated on the example of an NPP reactor pressure vessel with a WWER-1000 reactor unit when using the maximum allowable operating loads, in the absence of load dispersion in different operating modes, and taking into account the actual values of the distributions of fracture toughness and residual defectiveness. The practical significance of the developed method lies in the possibility of obtaining values of the actual probability of destruction of NPP equipment in order to determine the reliability of equipment operation, as well as possible reliability margins for their subsequent optimization.
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