Seung Cheol Jang

FAULT DETECTION COVERAGE QUANTIFICATION OF AUTOMATIC TEST FUNCTIONS OF DIGITAL I&C SYSTEM IN NPPS

Analog instrument and control systems in nuclear power plants have recently been replaced with digital systems for safer and more efficient operation. Digital instrument and control systems have adopted various fault-tolerant techniques that help the system correctly and safely perform the specific required functions regardless of the presence of faults. Each fault-tolerant technique has a different inspection period, from real-time monitoring to monthly testing. The range covered by each faulttolerant technique is also different. The digital instrument and control system, therefore, adopts multiple barriers consisting of various fault-tolerant techniques to increase the total fault detection coverage. Even though these fault-tolerant techniques are adopted to ensure and improve the safety of a system, their effects on the system safety have not yet been properly considered in most probabilistic safety analysis models. Therefore, it is necessary to develop an evaluation method that can describe these features of digital instrument and control systems. Several issues must be considered in the fault coverage estimation of a digital instrument and control system, and two of these are addressed in this work. The first is to quantify the fault coverage of each fault-tolerant technique implemented in the system, and the second is to exclude the duplicated effect of fault-tolerant techniques implemented simultaneously at each level of the system’s hierarchy, as a fault occurring in a system might be detected by one or more fault-tolerant techniques. For this work, a fault injection experiment was used to obtain the exact relations between faults and multiple barriers of faulttolerant techniques. This experiment was applied to a bistable processor of a reactor protection system.

A method for evaluating fault coverage using simulated fault injection for digitalized systems in nuclear power plants

The fault coverage for digital system in nuclear power plants is evaluated using a simulated fault injection method. Digital systems have numerous advantages, such as hardware elements share and hardware replication of the needed number of independent channels. However, the application of digital systems to safety-critical systems in nuclear power plants has been limited due to reliability concerns. In the reliability issues, fault coverage is one of the most important factors. In this study, we propose an evaluation method of the fault coverage for safety-critical digital systems in nuclear power plants. The system under assessment is a local coincidence logic processor for a digital plant protection system at Ulchin nuclear power plant units 5 and 6. The assessed system is simplified and then a simulated fault injection method is applied to evaluate the fault coverage of two fault detection mechanisms. From the simulated fault injection experiment, the fault detection coverage of the watchdog timer is 44.2% and that of the read only memory (ROM) checksum is 50.5%. Our experiments show that the fault coverage of a safety-critical digital system is effectively quantified using the simulated fault injection method.

A SOFTWARE RELIABILITY ESTIMATION METHOD TO NUCLEAR SAFETY SOFTWARE

A method for estimating software reliability for nuclear safety software is proposed in this paper. This method is based on the software reliability growth model (SRGM), where the behavior of software failure is assumed to follow a non-homogeneous Poisson process. Two types of modeling schemes based on a particular underlying method are proposed in order to more precisely estimate and predict the number of software defects based on very rare software failure data. The Bayesian statistical inference is employed to estimate the model parameters by incorporating software test cases as a covariate into the model. It was identified that these models are capable of reasonably estimating the remaining number of software defects which directly affects the reactor trip functions. The software reliability might be estimated from these modeling equations, and one approach of obtaining software reliability value is proposed in this paper.

Input-profile-based software failure probability quantification for safety signal generation systems

The approaches for software failure probability estimation are mainly based on the results of testing. Test cases represent the inputs, which are encountered in an actual use. The test inputs for the safety-critical application such as a reactor protection system (RPS) of a nuclear power plant are the inputs which cause the activation of protective action such as a reactor trip. A digital system treats inputs from instrumentation sensors as discrete digital values by using an analog-to-digital converter. Input profile must be determined in consideration of these characteristics for effective software failure probability quantification. Another important characteristic of software testing is that we do not have to repeat the test for the same input value since the software response is deterministic for each specific digital input. With these considerations, we propose an effective software testing method for quantifying the failure probability. As an example application, the input profile of the digital RPS is developed based on the typical plant data. The proposed method in this study is expected to provide a simple but realistic mean to quantify the software failure probability based on input profile and system dynamics.

Software Failure Probability Assessment by Bayesian Inference

This paper describes a method of estimating the probability of failure for trip-functioning software of a fully digitalized reactor protection system. The Bayesian inference is used to estimate and update the probability of software failure along the software development life cycle. At the requirements and design phases, the probability of software failure is estimated from qualitative quality information based on a specific verification and validation process. This probability of failure is updated at the implementation/testing phases, based on the test data for trip functions implemented by software.

Design-related influencing factors of the computerized procedure system for inclusion into human reliability analysis of the advanced control room

This paper presents major design factors of the computerized procedure system (CPS) by task characteristics/requirements, with individual relative weight evaluated by the analytic hierarchy process (AHP) technique, for inclusion into human reliability analysis (HRA) of the advanced control rooms. Task characteristics/requirements of an individual procedural step are classified into four categories according to the dynamic characteristics of an emergency situation: (1) a single-static step, (2) a single-dynamic and single-checking step, (3) a single-dynamic and continuous-monitoring step, and (4) a multiple-dynamic and continuous-monitoring step. According to the importance ranking evaluation by the AHP technique, ‘clearness of the instruction for taking action’, ‘clearness of the instruction and its structure for rule interpretation’, and ‘adequate provision of requisite information’ were rated as of being higher importance for all the task classifications. Importance of ‘adequacy of the monitoring function’ and ‘adequacy of representation of the dynamic link or relationship between procedural steps’ is dependent upon task characteristics. The result of the present study gives a valuable insight on which design factors of the CPS should be incorporated, with relative importance or weight between design factors, into HRA of the advanced control rooms.