• Nuclear Engineering and Technology
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• 제35권3호
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• pp.179-190
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• 2003

The multiple steam generator tube rupture (SGTR) event scenario with available safety systems was experimentally and analytically evaluated. The experiment was conducted on the large scaled test facility to simulate the multiple SGTR event and investigate the effectiveness of operator actions. As a result, it indicated that the opening of pressurizer power operated relief valve was significantly effective in quickly terminating the primary-to-secondary break flow even for the 6.5 tubes rupture. In the analysis, the recent version of RELAP5 code was assessed with the test data. It indicated that the calculations agreed well with the measured data and that the plant responses such as the water level and relief valve cycling in the damaged steam generator were reasonably predicted. Finally, sensitivity study on the number of ruptured tubes up to 10 tubes was performed to investigate the coolant release into atmosphere. It indicated that the integrated steam mass released was not significantly varied with the number of ruptured tubes although the damaged steam generator was overfilled for more than 3 tubes rupture. These findings are expected to provide useful information in understanding and evaluating the plant ability to mitigate the consequence of multiple SGTR event.

• Nuclear Engineering and Technology
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• 제54권1호
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• pp.152-161
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• 2022

We analyzed mitigation strategies for steam generator tube rupture (SGTR) accidents using MARS code under both full-power and low-power and shutdown (LPSD) conditions. In general, there are two approaches to mitigating SGTR accidents: supplementing the reactor coolant inventory using safety injection systems and depressurizing the reactor coolant system (RCS) by cooling it down using the intact steam generator. These mitigation strategies were compared from the viewpoint of break flow from the ruptured steam generator tube, the core integrity, and the possibility of the main steam safety valves opening, which is associated with the potential release of radiation. The "cooldown strategy" is recommended for break flow control, whereas the "RCS make-up strategy" is better for RCS inventory control. Under full power, neither mitigation strategy made a significant difference except for on the break flow while, in LPSD modes, the RCS cooldown strategy resulted in lower break and discharge flows, and thus less radiation release. As a result, using the cooldown strategy for an SGTR under LPSD conditions is recommended. These results can be used as a fundamental guide for mitigation strategies for SGTR accidents according to the operational mode.

• Nuclear Engineering and Technology
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• 제50권6호
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• pp.981-988
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• 2018

An experiment was performed for the OECD/NEA ROSA-2 Project with the large-scale test facility (LSTF), which simulated a steam generator tube rupture (SGTR) accident due to a double-ended guillotine break of one of steam generator (SG) U-tubes with operator recovery actions in a pressurized water reactor. The relief valve of broken SG opened three times after the start of intact SG secondary-side depressurization as the recovery action. Multi-dimensional phenomena specific to the SGTR accident appeared such as significant thermal stratification in a cold leg in broken loop especially during the operation of high-pressure injection (HPI) system. The RELAP5/MOD3.3 code overpredicted the broken SG secondary-side pressure after the start of the intact SG secondary-side depressurization, and failed to calculate the cold leg fluid temperature in broken loop. The combination of the number of the ruptured SG tubes and the HPI system operation difference was found to significantly affect the primary and SG secondary-side pressures through sensitivity analyses with the RELAP5 code.

• Nuclear Engineering and Technology
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• 제41권1호
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• pp.63-70
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• 2009

A steam generator tube rupture (SGTR) accident, which is a partial reactor building bypass scenario, has a low probability and high consequences. SAMG has been used to manage the progression of severe accidents and the release of fission products induced by an SGTR at the Wolsong plants. Four of the six SAGs in the SAMG are used to manage the progression of a severe accident induced by an SGTR at the Wolsong plants. The results of the ISAAC code calculation have shown that the proper use the SAMG can stop a severe accident from progressing and keep the reactor building intact during a severe accident. These results confirm that the SAMG is an effective means of managing the progression of severe accidents initiated by an SGTR at the Wolsong plants.

• Nuclear Engineering and Technology
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• 제54권7호
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• pp.2702-2713
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• 2022

A steam generator tube rupture accompanying a core damage may cause the fission product to be released to environment bypassing the containment. In such an accident, the steam generator is the major path of the radioactive aerosol release. AEOLUS facility, the scaled-down model of Korean type steam generator, was built to examine the aerosol removal in the steam generator during the steam generator tube rupture accident. Integral and separate effect tests were performed with the facility for the dry and flooded conditions, and the decontamination factors were presented for different tube configurations and submergences. The dry test results were compared with the existing test results and with the analyses to investigate the aerosol retention physics by the tube bundle, with respect to the particle size and the bundle geometry. In the flooded tests, the effect of submergence were shown and the retention in the jet injection region were presented with respect to the Stokes number. The test results are planned to be used to constitute the aerosol retention model, specifically applicable for the analysis of the steam generator tube rupture accident in Korean nuclear power plants to evaluate realistic fission product behavior.

• Nuclear Engineering and Technology
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• 제34권4호
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• pp.358-369
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• 2002

Abundant information about analyses of single steam generator tube rupture (SGTR) events is available because of its importance in terms of safety. However, there are few literatures available on analyses of multiple steam generator tube rupture (MSGTR) events. In addition, knowledge of transients and consequences following a MSGTR event are very limited as there has been no occurrence of MSGTR event in the commercial operation of nuclear reactors. In this study, a postulated MSGTR event in an APR1400 is analyzed using thermal-hydraulic system code MARSI.4. The present study aims to examine the effects of affected steam generator selection. The main steam safety valve (MSSV) lift time for four cases are compared in order to examine how long operator response time is allowed depending on which steam generate. (S/G) is affected. The comparison shows that the cases where two steam generators are simultaneously affected allow longer time for operator action compared with the cases where a single steam generator is affected. Furthermore, the tube ruptures in the steam generator where a pressurizer is connected leads to the shortest operator response time.

• Nuclear Engineering and Technology
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• 제48권4호
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• pp.870-880
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• 2016

A steam generator tube rupture (SGTR) event with a stuck-open safety relief valve constitutes one of the most serious accident sequences in pressurized water reactors (PWRs) because it may create an open path for radioactive aerosol release into the environment. The release may be mitigated by the deposition of fission product particles on a steam generator's (SG's) dry tubes and structures or by scrubbing in the secondary coolant. However, the absence of empirical data, the complexity of the geometry, and the controlling processes have, until recently, made any quantification of retention difficult to justify. As a result, past risk assessment studies typically took little or no credit for aerosol retention in SGTR sequences. To provide these missing data, the Paul Scherrer Institute (PSI) initiated the Aerosol Trapping In Steam GeneraTor (ARTIST) Project, which aimed to thoroughly investigate various aspects of aerosol removal in the secondary side of a breached steam generator. Between 2003 and 2011, the PSI has led the ARTIST Project, which involved intense collaboration between nearly 20 international partners. This summary paper presents key findings of experimental and analytical work conducted at the PSI within the ARTIST program.

• Nuclear Engineering and Technology
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• 제53권3호
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• pp.812-824
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• 2021

In order to reduce risks from the Steam Generator Tube Rupture (SGTR) accident and to meet safety targets, various measures have been analyzed to minimize the amount of fission product (FP) release. In this paper, we propose an introduction of a Containment Filtered Venting System (CFVS) connected to the steam generator secondary side, which can reduce the amount of FP release while minimizing adverse effects identified in the previous studies. In order to compare the effect of new equipment with the existing strategy, accident simulations using MELCOR were performed. As a result of simulations, it is confirmed that CFVS operation lowers FP release into the environment, and the release fractions are lower (minimum 0.6% of the initial inventory for Cs) than that of the strategy which intends to depressurize the primary system directly (minimum 15.2% for Cs). The sensitivity analyses identify that refill of the CFVS vessel is a dominant contributor reducing the amount of FP released. As the new strategy has the possibility of hydrogen combustion and detonation in CFVS, the installation of an igniter inside the CFVS vessel may be considered in reducing such hydrogen risk.

• Nuclear Engineering and Technology
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• 제49권2호
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• pp.306-312
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• 2017

The purpose of this research is to introduce the technical standard of accident sequence precursor (ASP) analysis, and to propose a case study using the dynamic-probabilistic safety assessment (D-PSA) approach. The D-PSA approach can aid in the determination of high-risk/low-frequency accident scenarios from all potential scenarios. It can also be used to investigate the dynamic interaction between the physical state and the actions of the operator in an accident situation for risk quantification. This approach lends significant potential for safety analysis. Furthermore, the D-PSA approach provides a more realistic risk assessment by minimizing assumptions used in the conventional PSA model so-called the static-PSA model, which are relatively static in comparison. We performed risk quantification of a steam generator tube rupture (SGTR) accident using the dynamic event tree (DET) methodology, which is the most widely used methodology in D-PSA. The risk quantification results of D-PSA and S-PSA are compared and evaluated. Suggestions and recommendations for using D-PSA are described in order to provide a technical perspective.

• Nuclear Engineering and Technology
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• 제55권9호
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• pp.3423-3440
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• 2023

In this work, a multivariate time-series machine learning meta-model is developed to predict the transient response of a typical nuclear power plant (NPP) undergoing a steam generator tube rupture (SGTR). The model employs Recurrent Neural Networks (RNNs), including the Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and a hybrid CNN-LSTM model. To address the uncertainty inherent in such predictions, a Bayesian Neural Network (BNN) was implemented. The models were trained using a database generated by the Best Estimate Plus Uncertainty (BEPU) methodology; coupling the thermal hydraulics code, RELAP5/SCDAP/MOD3.4 to the statistical tool, DAKOTA, to predict the variation in system response under various operational and phenomenological uncertainties. The RNN models successfully captures the underlying characteristics of the data with reasonable accuracy, and the BNN-LSTM approach offers an additional layer of insight into the level of uncertainty associated with the predictions. The results demonstrate that LSTM outperforms GRU, while the hybrid CNN-LSTM model is computationally the most efficient. This study aims to gain a better understanding of the capabilities and limitations of machine learning models in the context of nuclear safety. By expanding the application of ML models to more severe accident scenarios, where operators are under extreme stress and prone to errors, ML models can provide valuable support and act as expert systems to assist in decision-making while minimizing the chances of human error.