Initial Probabilistic Evaluation of Reactor Pressure Vessel Fracture with Grizzly and Raven

Spencer, Benjamin¹  Hoffman, William²  Sen, Sonat¹  Rabiti, Cristian¹  Dickson, Terry³  Bass, Richard³ 

[1] Idaho National Lab. (INL), Idaho Falls, ID (United States);Univ. of Idaho, Moscow, ID (United States);Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

关键词: PRESSURE VESSELS;    PROBABILISTIC ESTIMATION;    FRACTURES;    DEFECTS;    NUCLEAR POWER PLANTS;    PROBABILITY DENSITY FUNCTIONS;    FRACTURE PROPERTIES;    EVALUATION;    TRANSIENTS;    STRESS INTENSITY FACTORS;    BOUNDARY CONDITIONS;    CRACK PROPAGATION;    RISK ASSESSMENT;    THERMAL SHOCK;    BENCHMARKS;    INTEGRALS;    SAMPLING;    COMPUTERIZED SIMULATION;    R CODES;    G CODES;    EMBRITTLEMENT Fracture Mechanics;    Pressurized Thermal Shock;    Probabilistic;    Reactor Pressure Vessel;   

DOI  :  10.2172/1244643
RP-ID  :  INL/EXT--15-37121
PID  :  OSTI ID: 1244643
Others  :  TRN: US1601167

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来源: SciTech Connect

【 摘 要 】

The Grizzly code is being developed with the goal of creating a general tool that can be applied to study a variety of degradation mechanisms in nuclear power plant components. The first application of Grizzly has been to study fracture in embrittled reactor pressure vessels (RPVs). Grizzly can be used to model the thermal/mechanical response of an RPV under transient conditions that would be observed in a pressurized thermal shock (PTS) scenario. The global response of the vessel provides boundary conditions for local models of the material in the vicinity of a flaw. Fracture domain integrals are computed to obtain stress intensity factors, which can in turn be used to assess whether a fracture would initiate at a pre-existing flaw. These capabilities have been demonstrated previously. A typical RPV is likely to contain a large population of pre-existing flaws introduced during the manufacturing process. This flaw population is characterized stastistically through probability density functions of the flaw distributions. The use of probabilistic techniques is necessary to assess the likelihood of crack initiation during a transient event. This report documents initial work to perform probabilistic analysis of RPV fracture during a PTS event using a combination of the RAVEN risk analysis code and Grizzly. This work is limited in scope, considering only a single flaw with deterministic geometry, but with uncertainty introduced in the parameters that influence fracture toughness. These results are benchmarked against equivalent models run in the FAVOR code. When fully developed, the RAVEN/Grizzly methodology for modeling probabilistic fracture in RPVs will provide a general capability that can be used to consider a wider variety of vessel and flaw conditions that are difficult to consider with current tools. In addition, this will provide access to advanced probabilistic techniques provided by RAVEN, including adaptive sampling and parallelism, which can dramatically decrease run times.