Joon-Eon Yang

Application of genetic algorithm for reliability allocation in nuclear power plants

Abstract Reliability allocation is an optimization process of minimizing the total plant costs subject to the overall plant safety goal constraints. Reliability allocation was applied to determine the reliability characteristics of reactor systems, subsystems, major components and plant procedures that are consistent with a set of top-level performance goals; the core melt frequency, acute fatalities and latent fatalities. Reliability allocation can be performed to improve the design, operation and safety of new and/or existing nuclear power plants. Reliability allocation is a kind of a difficult multi-objective optimization problem as well as a global optimization problem. The genetic algorithm, known as one of the most powerful tools for most optimization problems, is applied to the reliability allocation problem of a typical pressurized water reactor in this article. One of the main problems of reliability allocation is defining realistic objective functions. Hence, in order to optimize the reliability of the system, the cost for improving and/or degrading the reliability of the system should be included in the reliability allocation process. We used techniques derived from the value impact analysis to define the realistic objective function in this article.

Optimization of the surveillance test interval of the safety systems at the plant level

Up to now, the optimization of surveillance test intervals (STIs) is performed at the system level. In other words, the STI of a system is optimized considering only the conditions related to that system. For instance, the STI of an emergency diesel generator (EDG) is determined considering only the availability of an EDG and the costs related to the changed STI. However, such an approach can cause problems when the effects of each system’s optimized STI are combined. That is, the core damage frequency can increase to a level that cannot be accepted by the regulatory body when the STIs optimized at the system level are all adopted together. In this paper, STIs of the systems are optimized at the plant level based on the simplified probabilistic safety assessment (PSA) model of a pressurized water reactor. The PSA model includes most of the important safety systems. It is a nonlinear and multimodal optimization problem with constraints that it optimizes the STIs of various systems based on the PSA model at the plant level. Most conventional optimization techniques have difficulties in handling such multimodal and nonlinear optimization problems. Therefore, we applied a genetic algorithm to the optimization of STIs. The genetic algorithms guarantee the global optimum and find the solution very effectively. In addition, the fault trees used in PSA have some limitations in representing the real world; i.e., in estimating the unavailability of standby systems and the effects of maintenance strategies. So, the analytical unavailability model is implemented to overcome such limits of the conventional fault tree approach. The analytical unavailability model enables us to accurately estimate the effect of a maintenance strategy on the unavailability of systems. The optimized STIs based on the conventional fault tree and the analytical unavailability model are compared.

Analytic method to break logical loops automatically in PSA

Abstract In Probabilistic Safety Assessment (PSA), when the fault trees of support systems are merged, logical loops are generated due to the mutual dependencies of support systems. KAERI (Korea Atomic Energy Research Institute) has developed a method to break such logical loops automatically. The developed method provides the criteria to identify parts of the fault trees that cause the logical loops. Using a top-down approach, the logic of fault tree is expanded. During the expansion, the terms that cause the logical loops are identified based on the given criteria and are deleted automatically. By using the above procedure, we will get the new logic of fault trees without the logical loops. This method is implemented in KIRAP (KAERI Integrated Reliability Analysis Package) and tested for sample cases. The results obtained by the developed method are compared to ones obtained by the conventional method that has been used previously to break the logical loops in PSA.

FUKUSHIMA DAI-ICHI ACCIDENT: LESSONS LEARNED AND FUTURE ACTIONS FROM THE RISK PERSPECTIVES

The Fukushima Dai-Ichi accident in 2011 has affected various aspects of the nuclear society worldwide. The accident revealed some problems in the conventional approaches used to ensure the safety of nuclear installations. To prevent such disastrous accidents in the future, we have to learn from them and improve the conventional approaches in a more systematic manner. In this paper, we will cover three issues. The first is to identify the key issues that affected the progress of the Fukushima Dai-Ichi accident greatly. We examine the accident from a defense-in-depth point of view to identify such issues. The second is to develop a more systematic approach to enhance the safety of nuclear installations. We reexamine nuclear safety from a risk point of view. We use the concepts of residual and unknown risks in classifying the risk space. All possible accident scenarios types are reviewed to clarify the characteristics of the identified issues. An approach is proposed to improve our conventional approaches used to ensure nuclear safety including the design of safety features and the safety assessments from a risk point of view. Finally, we address some issues to be improved in the conventional risk assessment and management framework and/or practices to enhance nuclear safety.

A new method to evaluate alternate AC power source effects in multi-unit nuclear power plants

Abstract In order to evaluate accurately a station blackout (SBO) event frequency of a multi-unit nuclear power plant that has a shared alternate AC (AAC) power source, an approach has been developed which accommodates the complex inter-unit behavior of the shared AAC power source under multi-unit loss of offsite power conditions. The SBO frequency at a target unit of probabilistic safety assessment could be underestimated if the inter-unit dependency of the shared AAC power source is not properly modeled. The approach is illustrated for two cases, 2 units and 4 units at a single site, and generalized for a multi-unit site. Furthermore, the SBO frequency of the first unit of the 2-unit site is quantified. The methodology suggested in the present paper is believed to be very useful in evaluating the SBO frequency and the core damage frequency resulting from the SBO event. This approach is also applicable to the probabilistic evaluation of the other shared systems in a multi-unit nuclear power plant.

FAST BDD TRUNCATION METHOD FOR EFFICIENT TOP EVENT PROBABILITY CALCULATION

A Binary Decision Diagram (BDD) is a graph-based data structure that calculates an exact top event probability (TEP). It has been a very difficult task to develop an efficient BDD algorithm that can solve a large problem since it is highly memory consuming. In order to solve a large reliability problem within limited computational resources, many attempts have been made, such as static and dynamic variable ordering schemes, to minimize BDD size. Additional effort was the development of a ZBDD (Zero-suppressed BDD) algorithm to calculate an approximate TEP. The present method is the first successful application of a BDD truncation. The new method is an efficient method to maintain a small BDD size by a BDD truncation during a BDD calculation. The benchmark tests demonstrate the efficiency of the developed method. The TEP rapidly converges to an exact value according to a lowered truncation limit.

Development of measures to estimate truncation error in fault tree analysis

Abstract The fault tree quantification uncertainty from the truncation error has been of great concern for the reliability evaluation of large fault trees in the probabilistic safety analysis (PSA) of nuclear plants. The truncation limit is used to truncate cut sets of the gates when quantifying the fault trees. This paper presents measures to estimate the probability of the truncated cut sets, that is, the amount of truncation error. The functions to calculate the measures are programmed into the new fault tree quantifier FTREX (Fault Tree Reliability Evaluation eXpert) and a Benchmark test was performed to demonstrate the efficiency of the measures. The measures presented in this study are calculated by a single quantification of the fault tree with the assigned truncation limit. As demonstrated in the Benchmark test, lower bound of truncated probability (LBTP) and approximate truncation probability (ATP) are efficient estimators of the truncated probability. The truncation limit could be determined or validated by suppressing the measures to be less than the assigned upper limit. The truncation limit should be lowered until the truncation error is less than the assigned upper limit. Thus, the measures could be used as an acceptability of the fault tree quantification results. Furthermore, the developed measures are easily implemented into the existing fault tree solvers by adding a few subroutines to the source code.

DEVELOPMENT OF AN INTEGRATED RISK ASSESSMENT FRAMEWORK FOR INTERNAL/EXTERNAL EVENTS AND ALL POWER MODES

From the PSA point of view, the Fukushima accident of Japan in 2011 reveals some issues to be re-considered and/or improved in the PSA such as the limited scope of the PSA, site risk, etc. KAERI (Korea Atomic Energy Research Institute) has performed researches on the development of an integrated risk assessment framework related to some issues arisen after the Fukushima accident. This framework can cover the internal PSA model and external PSA models (fire, flooding, and seismic PSA models) in the full power and the low power-shutdown modes. This framework also integrates level 1, 2 and 3 PSA to quantify the risk of nuclear facilities more efficiently and consistently. We expect that this framework will be helpful to resolve the issue regarding the limited scope of PSA and to reduce some inconsistencies that might exist between (1) the internal and external PSA, and (2) full power mode PSA and low power-shutdown PSA models. In addition, KAERI is starting researches related to the extreme external events, the risk assessment of spent fuel pool, and the site risk. These emerging issues will be incorporated into the integrated risk assessment framework. In this paper the integrated risk assessment framework and the research activities on the emerging issues are outlined.

Investigating the effect of communication characteristics on crew performance under the simulated emergency condition of nuclear power plants

It is well known that the safety of large process control systems could be significantly affected by the communication characteristics of crews that have a responsibility for their operations. Accordingly, many researchers have spent huge amount of effort to grasp the relationship between the characteristics of crew communications and the associated crew performance. Unfortunately, in the case of nuclear power plants (NPPs), it seems that most of existing studies have tried to identify the relationship between the characteristics of crew communications and the associated crew performance using empirical observations without a firm technical underpinning. For these reasons, Park suggested a novel framework that is able to represent the characteristics of crew communications based on social network analysis (SNA) metrics. In order to confirm the appropriateness of the suggested framework, in this study, the characteristics of crew communications that are gathered from the simulated emergency condition of NPPs are additionally compared with the associated crew performance data. As a consequence, it is observed that there are significant relationships between communication characteristics and the associated crew performance. Therefore, it is reasonable to expect that the characteristics of crew communications can be properly grasped using the suggested framework.

Development of a new quantification method for a fire PSA

Abstract For an internal fire analysis, fire scenarios are developed carefully and quantified in a sequential and iterative way in a traditional fire Probabilistic Safety Assessment (PSA). However, there has been no proven explicit method to avoid these iterative quantifications till now. This study presents the Jungs Single Top And Run (JSTAR) method that facilitates a simultaneous single quantification of all fire scenarios. The JSTAR method could be employed at the fire PSA phases of a quantitative screening or detailed analysis. Using the JSTAR method, accurate fire risks of a fault tree that has many negates could be calculated by avoiding the frequent house event propagations of the fire scenario conditions. Furthermore, the proposed JSTAR method is a simple and explicit method to build a single-top external event PSA model for a risk-monitoring system. The JSTAR method could be implemented easily by developing a small automatic conversion tool. Depending on the maintenance policy of a fire PSA model, a single-top fire PSA model that is created by the conversion tool could be maintained permanently or it could be temporarily generated and discarded. The use of the JSTAR method is recommended for all external event PSAs such as an internal flooding risk analysis.