Risk Achievement Worth Research Articles

Consideration of quantitative risk reduction and risk achievement measures in safe NPP design

Abstract In the models developed by probabilistic safety analyses (PSA) and in their applications associated with nuclear power plants (NPPs), the risk importance of a particular feature can be, most generally, divided into two categories: importance with respect to the risk-increase potential and importance with respect to the risk-decrease potential. A representative measure of the first category is risk achievement worth (RAW), while a representative measure of the second category is risk reduction worth (RRW). The present paper discusses the use of RAW and RRW in achieving safe design and points out some implications of their mutual dependency on the selection of a risk-reduction strategy. A simple example is provided to illustrate the differences between the two basic strategies and point out to the main issues and conclusions.

Quantifying Safety Significance: An In-Depth Analysis of Importance Measures in Level 1 PSA for the VVR 10-MW Water-Water Research Reactor

The effectiveness of contemporary strategies for conducting fault tree/event tree (FTET) analyses within the realm of probabilistic risk assessment has recently come under rigorous examination. In light of such investigation, facility managers have gained a more profound understanding of the risk and safety implications inherent in the structural and componential integrity of systems (structures, systems, and components). This comprehensive research endeavor harnesses the power of risk models, employing both FTET and binary decision diagrams, to scrutinize and optimize the operational performance of a 10-MW reference Russian research reactor [Water-Water Research Reactor (VVR)] within the framework of probabilistic safety assessment. Moreover, this investigation delves into the intricate web of interrelationships existing among an array of analytical methodologies. These encompass the Fussell-Vesely (FV) importance measure, criticality analysis, Birnbaum analysis, risk achievement worth (RAW), and the differential importance measure, all with a focus on specific foundational events and vital components. Additionally, this note delves into the analysis of multiple significant measures frequently employed for VVR. Notably, the study establishes that merely two importance measures (IMs) prove sufficient for the core damage equation. Furthermore, this note investigates various important measures often employed for VVR. It is shown that two IMs are enough for the core damage equation. In conclusion, RAW, FV importance, or a blend of the two are adequate enough to be frequently employed for the VVR.

Calculation of the System Unavailability Measures of Component Importance Using the D2T2 Methodology of Fault Tree Analysis

A recent development in Fault Tree Analysis (FTA), known as Dynamic and Dependent Tree Theory (D2T2), accounts for dependencies between the basic events, making FTA more powerful. The method uses an integrated combination of Binary Decision Diagrams (BDDs), Stochastic Petri Nets (SPN) and Markov models. Current algorithms enable the prediction of the system failure probability and failure frequency. This paper proposes methods which extend the current capability of the D2T2 framework to calculate component importance measures. Birnbaum’s measure of importance, the Criticality measure of importance, the Risk Achievement Worth (RAW) measure of importance and the Risk Reduction Worth (RRW) measure of importance are considered. This adds a vital ability to the framework, enabling the influence that components have on system failure to be determined and the most effective means of improving system performance to be identified. The algorithms for calculating each measure of importance are described and demonstrated using a pressure vessel cooling system.

Importance measures for performance shaping factors of human reliability analysis

AbstractThe crew of a nuclear‐powered submarine under development in Brasil plays an important role in its safety. For this reason, crew members must be trained in procedures against undesired events. However, information that would help to accurately decrease human error probability (HEP) on board nuclear‐powered submarines is not available in the literature. Therefore, a methodology is required to obtain this information. This study introduces importance measures to evaluate the contribution of performance shaping factors (PSFs) and their levels to HEP. Importance measures Fussell‐Vesely, risk reduction worth, risk achievement worth, and Birnbaum importance, commonly used in probabilistic safety assessment, are introduced to identify PSFs and PSF levels that contribute the most to HEP. The proposed approach is focused on identifying HEP's main contributors, oriented toward decision‐making. The methodology uses the PSFs established in the Standardized Plant Analysis Risk‐Human Reliability Analysis method and a Bayesian network to quantify HEP. Moreover, the results of an application case demonstrate the method's effectiveness in integrating expert opinions into representative values of HEP and in identifying critical PSFs and PSF levels that should be the object of the decision‐making process to improve human performance.

Availability assessment of a nuclear reactor limitation system by a Timed Petri Net

The constant evolution of instrumentation and control systems (I & C) of nuclear power plants requires a robust reliability assessment, due to the constant interaction between different systems that are demanded under normal operating, transient or accident conditions. Several methodologies have been developed to model the reliability of digital I & C systems and their dynamic behavior to better model the interaction between several equipment. In nuclear power plant design, many I & C systems work together according to priority scales and safety importance. In some designs, a Reactor Limitation System (RLS) has an important function to preserve equipment during transients and because of this, it is classified as safety related. After discussing pros and cons of the available tools for the analysis (including failure mode definition and quantitative data gathering), this paper evaluates the application of a timed Petri net to simulate RLS functions of an analog I & C design with timing on transitions. The reason for doing so is because it is possible in this model to represent the response time of components, maintenance time and periodic test behavior besides the interactions mentioned above.The results for three scenarios modeled by a timed Petri net indicate an RLS availability between 87.38% and 99.99% based on pressure transmitter, pressurizer spray valves and heater features (like component response time, failure characterization, maintenance and periodic test). The results of this work indicate that a timed Petri net can better evaluate the model of pressurizer pressure control by an RLS classified, actually, as an analog system that can be digitalized around the plant lifetime. Two importance risk metrics, namely, Risk Reduction Worth (RRW) and Risk Achievement Worth (RAW) were applied to identify the contributions for safety function failure of each type of RLS component.

Basic Relation between RAW and RRW and Some of Its Implications on Risk Reduction Strategies

In using risk-informed approaches for ensuring safety of operating nuclear power plants (NPPs), risk importance measures obtained from probabilistic safety assessments (PSAs) of the plants are integral elements of consideration in many cases. In PSA models and applications associated with NPPs the risk importance of a particular feature (e.g. function, system, component, failure mode or operator action) can be, most generally, divided into two categories: importance with respect to risk increase potential and importance with respect to risk decrease potential. The representative of the first category, as used for practical purposes, is Risk Achievement Worth (RAW). Representative of the second category, as mentioned in consideration of risk importance, is Risk Reduction Worth (RRW). It can be shown that the two risk importance measures, RAW and RRW, are dependent on each other. The only parameter in this mutual dependency is probability of failure of the considered feature. The paper discusses the relation between RAW and RRW and some of its implications, including those on the general strategies for the reduction of risk imposed for the operation of the considered facility. Two general risk reduction strategies which are considered in the discussion are: a) risk reduction by decreasing the failure probability of the considered feature; and b) risk reduction while keeping the failure probability of the considered feature at the same level. Simple examples are provided to illustrate the differences between two strategies and point to main issues and conclusions.

A fault diagnostic system based on Petri nets and gray relational analysis for train–ground wireless communication systems

The system structure of train–ground wireless communication systems (TWCSs) is extremely complicated due to the use of fault tolerant technology to improve their performance. This complex structure raises several challenges in fault diagnosis for TWCSs, such as epistemic uncertainty, dynamic fault behaviors, and common cause failure (CCF). A fault diagnostic system is proposed to deal with these challenges based on Petri nets and gray relational analysis in this paper. Specifically, the fuzzy analytic hierarchy process is used to evaluate the failure data of components to handle epistemic uncertainty. Furthermore, the dynamic fault tree of TWCSs is established and converted into a generalized stochastic Petri net to calculate several reliability parameters used for fault diagnosis. Besides, a β factor model is employed to resolve the problem of CCF in TWCSs. In addition, Birnbaum importance measure (BIM), risk achievement worth (RAW) and test cost are considered comprehensively to obtain the optimal diagnostic sequence using an improved gray relational analysis. Finally, a numerical example is presented to demonstrate the efficiency of the proposed fault diagnostic system.

Identification of Risk-Significant Components in Nuclear Power Plants to Reduce Cs-137 Radioactive Risk

The amount and frequency of Cs-137 release in a nuclear accident are regulated to enhance environmental radiation protection. While significant improvements have been accomplished, including the preparation of severe accident mitigation equipment and systems to satisfy Cs-137 regulations, no attempt has yet been made along these lines to manage the structures, systems and components (SSCs) in nuclear power plants. Therefore, this paper proposes a new approach to identify the significant SSCs by quantifying related risk importance measures using release frequency and Cs-137 radioactivity. The new approach includes a Level 1 and Level 2 probabilistic safety assessment (PSA) linked model to obtain the frequency and Cs-137 radioactivity in all accident scenarios. The developed approach was applied to an OPR-1000 full-power internal events PSA model, and as a result, the top 20 SSCs were identified based on Fussell–Vesely importance, risk reduction worth, and risk achievement worth measures. The new approach can support risk-informed management for not only Cs-137 regulations but also public risk by using early and latent cancer fatalities.

Research on Time-Dependent Component Importance Measures Considering State Duration and Common Cause Failure

Unlike the current risk monitors, Real-time Online Risk Monitoring and Management Technology is characterized by time-dependent modeling on the state duration of components. Given the real-time plant configuration, it eventually provides the time-dependent risk level and importance measures for operation and maintenance management. This paper focuses on the assessment method of time-dependent importance measures and its risk-informed applications in real-time online risk monitoring and management technology, including Fussell-Vesely (FV), risk achievement worth (RAW), and risk reduction worth (RRW). In this study, the values of component importance have been investigated with a time-dependent risk quantification model, as well as the common cause failure treatment model. Here three options of common cause failure treatment have been developed, assuming that the unavailability of a component could be due to an independent factor (Option 1), a common cause factor (Option 2), or an unconfirmed cause (Option 3). In the special case of “what if a component is out-of-service” of the RAW numerator, a hybrid method for the RAW evaluation is presented resulting in a balanced and reasonable RAW value. A simple case study was demonstrated. The results showed that the absolute values and ranking order of time-dependent importance not only reflected the effect of the cumulative state duration of component on risk, but also comprehensively accounted for all possible situations of component unavailability. Moreover, time-dependent importance measures improved and provided novel insights for online configuration management, 1) ranking SSCs/events/human actions for controlling increased risk and optimizing near–term plans; and 2) exempting or limiting temporary configurations during online operation.

ANN-Based Relaying Algorithm for Protection of SVC- Compensated AC Transmission Line and Criticality Analysis of a Digital Relay

Background:The Static VAR Compensator (SVC) has the capability of improving reliability, operation and control of the transmission system thereby improving the dynamic performance of power system. SVC is a widely used shunt FACTS device, which is an important tool for the reactive power compensation in high voltage AC transmission systems. The transmission lines compensated with the SVC may experience faults and hence need a protection system against the damage caused by these faults as well as provide the uninterrupted supply of power.Methods:The research work reported in the paper is a successful attempt to reduce the time to detect faults on a SVC-compensated transmission line to less than quarter of a cycle. The relay algorithm involves two ANNs, one for detection and the other for classification of faults, including the identification of the faulted phase/phases. RMS (Root Mean Square) values of line voltages and ratios of sequence components of line currents are used as inputs to the ANNs. Extensive training and testing of the two ANNs have been carried out using the data generated by simulating an SVC-compensated transmission line in PSCAD at a signal sampling frequency of 1 kHz. Back-propagation method has been used for the training and testing. Also the criticality analysis of the existing relay and the modified relay has been done using three fault tree importance measures i.e., Fussell-Vesely (FV) Importance, Risk Achievement Worth (RAW) and Risk Reduction Worth (RRW).Results:It is found that the relay detects any type of fault occurring anywhere on the line with 100% accuracy within a short time of 4 ms. It also classifies the type of the fault and indicates the faulted phase or phases, as the case may be, with 100% accuracy within 15 ms, that is well before a circuit breaker can clear the fault. As demonstrated, fault detection and classification by the use of ANNs is reliable and accurate when a large data set is available for training. The results from the criticality analysis show that the criticality ranking varies in both the designs (existing relay and the existing modified relay) and the ranking of the improved measurement system in the modified relay changes from 2 to 4.Conclusion:A relaying algorithm is proposed for the protection of transmission line compensated with Static Var Compensator (SVC) and criticality ranking of different failure modes of a digital relay is carried out. The proposed scheme has significant advantages over more traditional relaying algorithms. It is suitable for high resistance faults and is not affected by the inception angle nor by the location of fault.

Contribution of Human Reliability in Power Probabilistic Safety Assessment Models Versus Shutdown Models

Abstract Human reliability analysis is a method, which evaluates the human error probabilities of human failure events, which may arise when human actions are required in operation of the considered facility or system. The objective of the work is to show the contribution of human failure events in probabilistic safety assessment with focus on comparison of this contribution over the different plant operating states. The method integrates the diagnosis and action part, which are evaluated for all steps, which are needed for modeling of the human action under investigation considering the parameters, which impact the human failure probability and which are obtained from database. The results show that the risk contribution of human failure events is notably higher in low power and shutdown states than in full power operation. The results show that the human factor in shutdown plant states is the most important risk contributor regarding the contribution to the core damage frequency and regarding the risk reduction worth and risk achievement worth. Only at some plant operating states, some other groups of equipment show larger risk achievement worth than group of human failure events.

Global importance measure methodology for integrated probabilistic risk assessment

An integrated probabilistic risk assessment framework combines spatio-temporal probabilistic simulations of underlying failure mechanisms with classical probabilistic risk assessment logic consisting of event trees and fault trees. The importance measure methods commonly used in classical probabilistic risk assessment, for example, Fussell–Vesely importance measure and Risk Achievement Worth, generate the ranking of components at the basic event level utilizing the one-at-a-time and local methods. These classical importance measure methods, however, are not sufficient for integrated probabilistic risk assessment where, in addition to the component-level risk importance ranking, the ranking of risk-contributing factors (e.g. physical design parameters) associated with the underlying failure mechanisms is desired. In this research, the global importance measure method is suggested and implemented for the integrated probabilistic risk assessment framework. The global importance measure can account for four key aspects of integrated probabilistic risk assessment, including (a) ranking of input parameters at the failure mechanism level based on the contribution to the system risk metrics, (b) uncertainty of input parameters, (c) non-linearity and interactions among input parameters inside the model, and (d) uncertainty associated with the system risk estimates; therefore, it enhances the accuracy of risk importance ranking when the risk model has a high level of non-linearity, interactions, and uncertainties. This article shows (a) qualitative justifications for the selection of the global importance measure method for the integrated probabilistic risk assessment framework and (b) quantitative proof of concept using three case studies, including two illustrative fault tree examples and one practical application of the integrated probabilistic risk assessment framework for Generic Safety Issue 191 at nuclear power plants (a sump blockage issue following a loss-of-coolant accident).

An FTA Method for the Unavailability of Supply in Gas Networks Supported by Physical Models

This paper presents a fault tree analysis (FTA) method for the unavailability of supply of gas networks. The method is based on the automatic generation of fault trees, which estimate the probability of disruption of the gas delivery from terminals/storages to the demand nodes. Moreover, it allows probabilistic analyses of the availability of gas supply to individual demand nodes and to the overall gas network. To assess the importance of each network component, the risk achievement worth and the risk reduction worth importance measures are utilized. The developed method can identify weakness in the gas network and can guide expansion planning and maintenance scheduling activities. Furthermore, the developed framework is enriched by steady-state analysis of the gas network operations performed using a physical flow/pressure model. The impact of a component failure on the gas supply interruption at different demand nodes is assessed by the physical model in retrospective to the FTA results. The framework is exemplified with reference to the reduced gas network of Great Britain. The results provide insights to support a robust reliability assessment of the gas network. Moreover, the probability mapping of the most important components in the gas network informs optimal strategies for maintenance scheduling as well for prioritizing improvements of the gas network aimed at significant risk reduction. Remarkably, the failure of components identified as most important according to the FTA importance measures may not have significant effects on the gas supply. A discussion on the range of applicability and limitations of the two methodologies is provided.

An improved probabilistic method for screening safety-related human actions in nuclear power plants

Abstract For the reliability and safety of nuclear power plants (NPPs), their design and operation must follow the relevant principles of human factors engineering (HFE). As various human actions are involved in the operation of NPPs, there is a need to screen human actions first and, then, focus the analysis on the critical ones. In the past, different NPPs have adopted different standards in screening human actions and many of these standards lack theoretical support. In this study, the concept of human action risk achievement worth (HRAW) is introduced to support probabilistic screening. A new probabilistic method for screening safety-related human actions in NPPs is proposed. The results of a case study indicate that the proposed method performs well and better than the previous probabilistic screening method typically used, it also implies that this method can provides methodological support to the probabilistic screening method of human actions. On the one hand, utilizing this method to screen human actions can help identifying those actions that are critical for the safety of NPPs. On the other hand, it can reduce the workload and improve work efficiency. The method is traceable and easy to use. It not only can be used in the design of NPPs, but also can provide guidelines for reviewers to evaluate the NPPs safety.

The fault tree analysis of infectious medical waste management

Providing an efficient and reliable system of medical waste management is one of the key environmental issues not only for health-care institutions but for a wider range of organizations and communities. Medical waste produced in health care is a special kind of waste, which, if inadequately treated, can cause numerous possible health and safety hazards for people and the environment. In this paper the authors introduce an application for risk assessment of infectious medical waste management in the biggest health institution of South-East Europe – the Clinical Centre of Serbia. The fault tree analysis (FTA) method was used in the assessment regarding its three aspects – functional, qualitative and quantitative. The qualitative analysis provided the structural function of the system and minimal cut sets, whilst the quantitative analysis based on experts' evaluations defined the probability of both basic and top events (spreading of infection with medical waste). Finally, according to Birbaim's, RAW (Risk achievement worth), RRW (Risk reduction worth) and Fussell–Vesely's importance measures, the events have been ranked regarding their effect on the undesired event related to infectious medical waste management. In this paper, we have chosen the FTA approach because it enables the analysis of the individual risks (like the most of the risk assessment methods used in medical waste management – FMEA, HACCP, PHA, CREA) but it also provides the analysis of risk relationships and interdependences. Based on the obtained results we identified the basic failures in the medical waste management systems whose prevention or mitigation have the biggest influence on the observed system improvement. Furthermore, the research presented in this paper has clearly pointed out that the FTA method and importance measures can be used in the risk assessment of the medical waste and should be taken into consideration in appropriate medical waste management systems.

Sensitivity Study on Availability of I&C Components Using Bayesian Network

The objective of this study is to find out the impact of instrumentation and control (I&C) components on the availability of I&C systems in terms of sensitivity analysis using Bayesian network. The analysis has been performed on I&C architecture of reactor protection system. The analysis results would be applied to develop I&C architecture which will meet the desire reliability features and save cost. RPS architecture unavailabilityP(x=0)and availabilityP(x=1)were estimated to6.1276E-05and9.9994E-01for failure (0) and perfect (1) states, respectively. The impact of I&C components on overall system risk has been studied in terms of risk achievement worth (RAW) and risk reduction worth (RRW). It is found that circuit breaker failure (TCB), bi-stable processor (BP), sensor transmitter (TR), and pressure transmitter (PT) have high impact on risk. The study concludes and recommends that circuit breaker bi-stable processor should be given more consideration while designing I&C architecture.

Dynamic Fault Trees Analysis for Importance Measures Based on Cut Sequence Set Model

Importance Measures (IMs) for dynamic fault tree (DFT) remains widely open, for that Markov-based methodology is limited to exponential distributions as well as the state space explosion. Cut sequence describes the dynamic behaviors among components, and Cut sequence set (CSS) model provides ways to generate and calculate the probabilities of cut sequences, but it does not show how to analysis IMs using CSS model. This paper proposed a novel methodology of IMs in CSS model, including Birnbaum measure (BI), Risk Achievement Worth (RAW) and Structure Importance (SI) and an example demonstrates the superiority of the methodology. In contrast to the Markov-based methodology, the proposed methodology is combinatorial and can handle with any type of time-to-failure distributions for the system components.

Composite multilinearity, epistemic uncertainty and risk achievement worth

Risk achievement worth is one of the most widely utilized importance measures. RAW is defined as the ratio of the risk metric value attained when a component has failed over the base case value of the risk metric. Traditionally, both the numerator and denominator are point estimates. Relevant literature has shown that inclusion of epistemic uncertainty (i) induces notable variability in the point estimate ranking and (ii) causes the expected value of the risk metric to differ from its nominal value. We investigate the conditions under which the equality of the nominal and expected values of a reliability risk metric holds. We then study how the presence of epistemic uncertainty affects RAW and the associated ranking. We propose an extension of RAW (called ERAW) which allows one to obtain a ranking robust to epistemic uncertainty. We discuss the properties of ERAW and the conditions under which it coincides with RAW. We apply our findings to a probabilistic risk assessment model developed for the safety analysis of NASA lunar space missions.

최소절단집합과 최소경로집합을 이용한 구조 및 신뢰성 중요도 척도의 개발 및 적용

The research discusses interrelationship of structural and reliability importance measures which used in the probabilistic safety assessment. The most frequently used component importance measures, such as Birnbaum`s Importance (BI), Risk Reduction (RR), Risk Reduction Worth (RRW), RA (Risk Achievement), Risk Achievement Worth (RAW), Fussel Vesely (FV) and Critically Importance (CI) can be derived from two structure importance measures that are developed based on the size and the number of Minimal Path Set (MPS) and Minimal Cut Set (MCS). In order to show an effectiveness of importance measures which is developed in this paper, the three representative functional structures, such as series-parallel, k out of n and bridge are used to compare with Birnbaum`s Importance measure. In addition, the study presents the implementation examples of Total Productive Maintenance (TPM) metrics and alternating renewal process models with exponential distribution to calculate the availability and unavailability of component facility for improving system performances. System state structure functions in terms of component states can be converted into the system availability (unavailability) functions by substituting the component reliabilities (unavailabilities) for the component states. The applicable examples are presented in order to help the understanding of practitioners.

Designing a risk-informed balanced system by genetic algorithms: Comparison of different balancing criteria

This paper deals with the use of importance measures (IMs) for the risk-informed optimization of system design and operation. It builds on previous work by the authors in which IMs are incorporated in the formulation of a genetic algorithm (GA) multi-objective optimization problem to drive the design towards a solution which is ‘balanced’ in the importance values of the components. This allows designing systems that are optimal from the point of view of economics and safety, without excessively low- or unnecessarily high-performing components. Different definitions of IMs quantify the risk- or safety-significance of components according to specific views of their role in the system: depending on the optimization problem at hand (e.g. system design optimization and/or maintenance strategy optimization) the use of one IM definition as a balancing criterion may be more appropriate than another. In this regard, a comparison of the Fussell–Vesely (FV), Birnbaum (B) and risk achievement worth (RAW) IMs is performed, with respect to their appropriateness for the optimization of test/maintenance intervals. The RAW is found inappropriate for the purpose, since this measure relates to the defense of the system against the failure of components, which is independent on how often the component is tested. Instead, the use of the FV or B measures allows allocating test/maintenance activities according to the importance of the components they relate to, in agreement with the principle of the risk-informed philosophy of avoiding unnecessary regulatory burdens and defining more efficient inspection and maintenance activities.