Analysis of Steam Line Break Accident Using PCTRAN Model of VVER-1200 NPP

The investigation of thermal-hydraulic parameters during steam-line break (SLB) accidents is performed by applying the personal computer transient analyzer (PCTRAN) simulator model of the VVER-1200 nuclear power plant (NPP). Five cases, namely, 0.005 m2 (Case-1), 0.01 m2 break (Case-2), 0.02 m2 break (Case-3), 0.04 m2 (Case-4), and 0.08 m2 (case-5) of SLB accident inside containment with the concurrent loss of AC power have been simulated. There was no variation in the timing of the trip of the reactor coolant pumps, the main feedwater pumps, or the turbine in any of the five SLB accidents. However, the reactor scram's onset time varies slightly between the five scenarios. Pressure and temperature in the reactor coolant system (RCS) quickly reached a peak following the start of the SLB accident, fell shortly after the reactor scram, and eventually stabilized in all cases. In comparison to the larger breaks in the SLB accident, the smaller breaks result in a higher RCS temperature and pressure. After the SLB accident, the pressurizer's liquid level rises and then quickly drops in all cases. The break mass flow rate from the steam line rapidly increases until the occurrence of the reactor scram and then decreases to a stabilized value. Steam generator A has a faster rate of heat removal rate than steam generator B, and its pressure and liquid level decrease more quickly than those of steam generator B. The thermal power of the reactor, peak cladding temperature, and fuel temperature showed a rapid drop after the initiation of the SLB accident. There was no increase in these parameters from the initial state of the simulation. The radiation in the air of the reactor building and steam line was very low during the simulation period. Therefore, there was no violation of the safety aspects of the SLB accident of the PCTRAN simulation of the VVER-1200 NPP model

Reliability Assessment of NPP Safety Class Equipment Considering the Manufacturing Quality Assurance Process

Quality and safety are intensely related and go hand in hand. Quality of the safety-grade equipment is very important for the safety of a nuclear power plant (NPP) and achieving production goals. During manufacturing of plant components or equipment, deviation from the design might occur at different stages of manufacturing for various reasons, such as a lack of skilled manpower, deviation of materials, human errors, malfunction of equipment, violation of manufacturing procedure, etc. These deviations can be assessed cautiously and taken into consideration in the final safety analysis report (FSAR) before issuing an operating license. In this paper, we propose a Bayesian belief network for quality assessment of safety class equipment of NPPs with a few examples. The proposed procedure is a holistic approach for estimation of equipment failure probability considering manufacturing deviations and errors. Case studies for safety-class dry transformers and reactor pressurizers employing the proposed method are also presented in this article. This study provides insights for probabilistic safety assessment engineers and nuclear plant regulators for improved assessment of NPP safety