Quantitative Reliability Assessment Research Articles

From defects creation to circuit reliability – A bottom-up approach (invited)

This paper presents a theoretical framework about interface states creation rate from Si–H bonds at the Si/SiO 2 interface. It includes three mains ways of bond breaking. In the first case, the bond can be broken thanks to the bond ground state rising with an electrical field. In the two others cases, incident carriers will play the main role either if there are very energetic or very numerous but less energetic. This concept allows us physically modeling the reliability of MOSFET transistors, and particularly NBTI permanent part, and Channel Hot Carrier (CHC) to Cold Carrier (CCC) damage. Finally, the translation of these physical models into reliability spice models is discussed. These models pave the way to Design-in Reliability (DiR) approach which seeks to provide a quantitative assessment of reliability – CMOS device reliability in this case – at design stage thereby enabling judicious margins to be taken beforehand.

New Considerations in Modern Protection System Quantitative Reliability Assessment

Protective relay technologies have evolved from single-function electromechanical and static relays to modern multifunction digital relays over the past few years. Protection systems play a vital role in maintaining a desirable level of reliability in power systems. Thus, their own reliability should be evaluated and any cause of their malfunction should be fully comprehended. In this paper, a new reliability model is proposed that associates protection system failures to four main causes: 1) relay hardware, 2) relay software, 3) ancillary equipment, and 4) human error. In addition, this model can take other aspects of the protection system into consideration, such as human error during tests and repair actions, routine inspections effectiveness, level of reliance on self-checking, local backup misoperation, and stuck breakers. These considerations have a significant impact on the reliability of protection systems and have been neglected in the existing research works. Various capabilities of the model are demonstrated in the case study section.

An optimized Line Sampling method for the estimation of the failure probability of nuclear passive systems

The quantitative reliability assessment of a thermal–hydraulic (T–H) passive safety system of a nuclear power plant can be obtained by (i) Monte Carlo (MC) sampling the uncertainties of the system model and parameters, (ii) computing, for each sample, the system response by a mechanistic T–H code and (iii) comparing the system response with pre-established safety thresholds, which define the success or failure of the safety function. The computational effort involved can be prohibitive because of the large number of (typically long) T–H code simulations that must be performed (one for each sample) for the statistical estimation of the probability of success or failure. In this work, Line Sampling (LS) is adopted for efficient MC sampling. In the LS method, an “important direction” pointing towards the failure domain of interest is determined and a number of conditional one-dimensional problems are solved along such direction; this allows for a significant reduction of the variance of the failure probability estimator, with respect, for example, to standard random sampling. Two issues are still open with respect to LS: first, the method relies on the determination of the “important direction”, which requires additional runs of the T–H code; second, although the method has been shown to improve the computational efficiency by reducing the variance of the failure probability estimator, no evidence has been given yet that accurate and precise failure probability estimates can be obtained with a number of samples reduced to below a few hundreds, which may be required in case of long-running models. The work presented in this paper addresses the first issue by (i) quantitatively comparing the efficiency of the methods proposed in the literature to determine the LS important direction; (ii) employing artificial neural network (ANN) regression models as fast-running surrogates of the original, long-running T–H code to reduce the computational cost associated to the determination of the LS “important direction” and (iii) proposing a new technique for identifying the LS “important direction”, based on the genetic algorithm (GA) minimization of the variance of the LS failure probability estimator. In addition, this work addresses the second issue by assessing the performance of the LS method in estimating small failure probabilities with a reduced (e.g., lower than one hundred) number of samples. The issues are investigated within two case studies: the first one deals with the estimation of the failure probability of a nonlinear structural system subject to creep and fatigue damages [1,2]; the second one regards a passive decay heat removal system in a gas-cooled fast reactor (GFR) of literature, [3].

ON THE DEVELOPMENT OF UNIFIED SCHEME FOR DISCRETE SOFTWARE RELIABILITY GROWTH MODELING

The importance of Software Reliability Growth Models to control the testing process and for quantitative assessment of software reliability is a well established fact. However, difficulties created by their underlying assumptions, their relevance and validity to real testing environment have made the selection of appropriate model an uphill task. Recently, new dimensions have been added to software reliability engineering with the development of unified modeling schemes. These schemes have proved seminal in the development of the general theory, partially because of their simplicity and mathematical tractability. In this paper, we propose a unified scheme for discrete software reliability growth modeling using the fault detection/correction rate function. Standard probability distributions have been used to model the fault correction and detection times. Initially, we have formulated the unified scheme when the fault correction is immediate to the failure observation and later we extend it to the cases where removal is a two stage process namely failure observation followed by fault detection/correction. The use of fault detection/correction rate or else known as hazard rate to represent stage wise removal of fault during testing highlights the importance of the proposed framework. Convolution of probability distribution functions has been used to represent Stage-wise removal of fault i.e. failure observation, fault detection/fault correction. Few Discrete models have been derived using the proposed methodology. Parameter estimation on two real software failure datasets has been worked out. The results obtained are fairly accurate and quite encouraging.

Risk and reliability assessment for electrical distribution systems and impacts of regulations with examples from Sweden

The introduction of performance based tariff regulations, and higher media and political pressure have increased the need for well-performed asset management in the operation and planning of electrical distribution systems. In this paper quantitative reliability assessment methods are proposed as a tool to meet these new incentives. Electrical distribution systems have compared to other technical systems several special characteristics which are important to take into consideration when introducing reliability analysis methods. Moreover, the paper gives a brief discussion on the effects and the importance of customer participation in improving system reliability by providing additional system operating reserve from the market perspective. Finally, the paper discusses the reliability analysis with the reliability test systems, and stresses the usefulness of generally known test systems for such assessments. The ideas of future work on development of these test systems to address the changing power systems are presented.

Software system reliability and safety assessment: an extended FMEA approach

This paper presents a methodology for assessing the reliability and safety of a software based on an extended Failure Modes and Effects Analysis (FMEA) approach. The methodology is described in steps with illustrative examples. The analysis starts from initial phase of the software development and evolves during the subsequent phases of software development providing valuable information to each phases. Finally, the analysis yields a quantitative assessment of reliability and safety of the software system. The paper's main objective is to support Probabilistic Safety Assessment (PSA) in assessing risk. Risk is a function of severity and failure frequency/probability. The severity is characteristic of failure effects. Failures may be analysed as functional or component failure. In this paper, it is proposed to consider severity levels at functional failure level as it is easier to understand failure effects at functional level. Moreover, various logical combinations of different functional failures can also be formed and analysed using the proposed approach.

Quantitative assessment of protection system reliability incorporating human errors

The protection system plays a vital role in maintaining a high degree of service reliability in present-day power systems. Considerable work has been done to examine different aspects of protection systems and their associated reliability. All of the reliability predictive methods are based solely on equipment failures, neglecting the human component of the protection system. In this paper, a modified Markov model is presented that incorporates human errors in reliability evaluation of protective devices. Two main types of relay failure (failure to operate and inadvertent operation) are taken into account in the proposed model. The model also considers routine test inspections, the self-checking facility of digital relays, and also common cause failures of protective devices and protected components. Numerical studies show the influence of human errors on protection system reliability.

Quantitative Reliability Assessment for Safety Critical System Software

At recent times, an essential issue in the replacement of the old analogue I&C to computer-based digital systems in nuclear power plants becomes the quantitative software reliability assessment. Software reliability models have been successfully applied to many industrial applications, but have the unfortunate drawback of requiring data from which one can formulate a model. Software that is developed for safety critical applications is frequently unable to produce such data for at least two reasons. First, the software is frequently one-of-a-kind, and second, it rarely fails. Safety critical software is normally expected to pass every unit test producing precious little failure data. The basic premise of the rare events approach is that well-tested software does not fail under normal routine and input signals, which means that failures must be triggered by unusual input data and computer states. The failure data found under the reasonable testing cases and testing time for these conditions should be considered for the quantitative reliability assessment. We presented the quantitative reliability assessment methodology of safety critical software for rare failure cases in this paper.

A mathematical modeling framework for software reliability testing†

Software reliability testing refers to various software testing activities that are driven to achieve a quantitative reliability goal given a priori or lead to a quantitative reliability assessment for the software under test. In this paper we develop a modeling framework for the software reliability testing process, comprising a simplifying model and a generalized model. In both models the software testing action selection process and the defect removal mechanism are explicitly described. Both the discrete-time domain and the continuous-time domain are involved. The generalized model is more accurate or realistic than the simplifying model since the former avoids the assumption that defects are equally detectable and the assumption that defects are removed upon being detected. However simulation examples show that the simplifying model really captures some of essential features of the software testing process after a short initial testing stage. The modeling framework is practically realistic, mathematically rigorous, and quantitatively precise. It demonstrates that the relationship between software testing and delivered software reliability, which was poor understood, can well be formulated and quantified. Rigorous examinations show that several common assumptions adopted in software reliability modeling, including the independence assumption, the exponentiality assumption, and the NHPP assumption, are theoretically false in general. This paper sets a good starting point to further formalize and quantify the software testing process and its relation to delivered software reliability.

Quantitative reliability and availability analysis for design evaluation of generic pod propulsion systems

Application of pod propulsion on a variety of vessels such as cruise ships, ropax, and tanker vessels has increased significantly over the last two decades owing to the benefits offered by pods. Despite the clear benefits, operators are still reluctant to have this innovation on board because of unknown overall reliability. Many of the published research efforts in the area of pod propulsion have been concentrated on hydrodynamics and manoeuvring aspects with little in the area of quantitative pod reliability assessment. In this paper, the applicability and appropriateness of various quantitative fault tree solution techniques (exact and approximate) for the reliability assessment of a generic pod propulsion system are investigated. Also, the paper demonstrates that the proposed quantitative reliability assessment methodology can be used to make design changes by identifying critical components in system functionality and modifying the system with improvements, where needed.

Integrating optical transport quality, availability, and cost through reliability-based optical network design

The design of the optical transport network (OTN) must meet the challenges of providing a high capacity, highly dependable and reliable network and the flexibility in bandwidth management to support multi-services in a cost-effective manner. The core objective of the OTN design activity focuses on carefully balancing these design objectives. This paper presents a comprehensive design approach that integrates the OTN design with its end-to-end reliability assessment. Quantitative reliability assessment becomes an integral part of the OTN design process when considering network survivability using various protection and restoration schemes. This value-based reliability approach provides a complete set of network reliability profiles. These profiles provide a means to: 1) drive network architecture and infrastructure design by identifying both strong and vulnerable region(s); 2) provide reliability/availability cost and worth (benefit) tradeoff by quantifying the impact of various network elements and/or protection schemes; and 3) allow design of reliability-based revenue offers or service level agreements (SLAs). We will illustrate the application and benefits of using OTN reliability-based design processes in several service provider networks featuring synchronous optical network/synchronous digital hierarchy (SONET/SDH) ring and dense wavelength division multiplexing (DWDM) mesh architectures including dedicated and shared protection/restoration schemes in backbones and in metropolitan networks.

Reliability and Availability of Pod Propulsion Systems

AbstractThe application of pod propulsion in a number of vessel types has been increasing steadily over the last two decades. This increase is attributed to the great advantages being offered by pod propulsion systems such as high manoeuvring capability, low noise and vibration, low fuel consumption, etc. Despite these advantages, operators are cautious due to the encountered teething problems, especially in the very competitive passenger ship market, where reliability and the maintainability of the service are crucial. This paper presents a reliability assessment methodology and its application to a combined four‐pod propulsion system on a vessel equipped with two fixed‐ and two rotating‐pod units. The assessment methodology made use of Failure Mode and Effect Analysis, Fault Tree Analysis (FTA) and Markov Analysis complementarily. In the FTA, minimal cut set, reliability importance measure and availability analyses were also considered. From the quantitative reliability assessment, the calculated reliabilities of each fixed‐ and rotating‐pod unit, their components' reliabilities as well as the reliability of the combined four‐pod propulsion system showed good agreement with the acceptable reliability criteria suggested by the pod manufacturers/operators based on the service experience. Copyright © 2006 John Wiley & Sons, Ltd.

A new approach to quantitative assessment of reliability of passive systems

The objective of this paper is to show how probabilistic reliability can be assessed for complex systems in the absence of statistical data on their operating experience, based on performance evaluation of the dominant underlying physical processes. The approach is to distinguish between functional and performance probabilities when dealing with the quantification of the overall probability of a system to perform a given function in a given period of time (reliability). In the case of systems where sufficient statistical operating experience data are available, one can focus the quantitative evaluation entirely on the assessment of the functional probability for a given active item (e.g. a pump) by assuming that the specification, layout, construction and installation is such that the item is providing the assigned performance, e.g. in the form of generating the required flow rate. This is how traditional probabilistic safety assessments (PSAs) focus the reliability analysis for the various safety features on the calculation of values for the availability per demand. In contrast, for various systems relevant in advanced technical applications, such as passive safety features in innovative reactor designs, it is essential to evaluate both functional and performance probabilities explicitly and combine the two probabilities later on. This is of course due to the strong reliance of passive safety systems on inherent physical principles. In practice, this means that, for example, in case of a passive cooling system based on natural circulation of a given medium, one has to evaluate and to assess the probability to have a medium condition and a flow rate such that a cladding temperature, represented by a probability distribution, can be hold at a required level. A practical example of this method is given for the case of the reliability assessment of a residual passive heat removal system. General conclusions are drawn regarding reliability estimation of complex, interconnected systems in the absence of statistical performance data, such as for infrastructures.

Promoting human reliability assessment within large engineering organisations

Effective qualitative and quantitative human reliability assessment (HRA) is required to achieve safety goals associated with complex, hazardous systems. Traditionally, awareness of HRA amongst engineers has been low. Therefore, promotion of the discipline within organisations may be necessary to maximise the benefits available from its application. A high-level promotional strategy is identified, consisting of a) informative and persuasive measures, and b) formal mandates. Multiple channels of communication, both direct and indirect, are available to promote HRA. A range of supporting approaches are helpful, such as use of system-specific evidence to demonstrate the benefits of HRA, targeting all levels of the organisational hierarchy, and use of the requirements of external customers and the regulator. It is suggested that carefully managed investment in internal promotional activities is worthwhile.

Comparison of subtransmission system reliability worth for diverse systems by including health considerations

The fundamental concepts associated with quantitative reliability assessment of electric power systems are reasonably well established and accepted by the power industry. The evaluation of the costs and benefits of competing investments has now become a standard practice in power system planning. In order to make a consistent appraisal of economics and reliability, it is imperative to compare the investment cost needed to attain a specified level of reliability with the reliability worth or benefits derived by the society at that level of system reliability. Customer interruption costs, which serve as surrogates for the perceived worth of supply reliability, have been determined for several jurisdictions, areas, provinces, and countries as diverse as Canada, United Kingdom, Nepal, and Thailand, among others. This paper extends the well-being framework to include the societal worth of electric service reliability in subtransmission systems associated with the above four countries/systems. Systems well-being is defined in terms of the three system states of healthy, marginal, and at risk, thus combining the deterministic and probabilistic approaches into a single framework. The main objective of the paper is to present results of reliability worth indices of expected cost of interruptions (ECOST) and interrupted energy assessment rate (IEAR), for both the healthy and at risk states in the well-being framework. The concepts associated with extending the well-being framework to include reliability worth parameters are illustrated by application to a small reliability test system designated RBTS. Customer interruption data from the four countries are used in conjunction with the RBTS subtransmission system in order to obtain the reliability worth indices.

An integrated framework for the assessment of network operations, reliability, and security

As a network evolves through new requirements, technology, or applications and becomes more complicated, the ability to provide cost-effective, secure, reliable operations for critical functions and to prevent internal and external assaults on the network is important for network vendors, network operators, and end users. Thus, the goal of network design is a manageable, quantifiably reliable, and secure network that balances end-user requirements and technological capabilities. Unfortunately, quantitative reliability assessment is generally not integrated into the process of designing operations and security, even though designers normally consider reliability when they evaluate various operations and security schemes. In this paper we present — with examples — an integrated framework that makes possible a quantitative reliability assessment of telecommunication services and incorporates the impacts of interruptions on both the operations and the security network infrastructures (i.e., on both the static and the dynamic aspects of the network). The static aspect of the network (i.e., operations) deals with the ability of the network to provide sufficient capacity to handle the traffic for which it was designed. The dynamic aspect (i.e., security) deals with the ability of the network to handle both sudden changes in operating conditions and the loss of components and to deal with internal and external attacks on the network.

Probabilistic Load Flow Computation Using the Method of Combined Cumulants and Gram-Charlier Expansion

Open access transmission has created a deregulated power market and brought new challenges to system planning. This paper proposes a new method to compute a probabilistic load flow in extensive power systems for the purpose of using it as a quick screening tool to determine the major investment on improving transmission system inadequacy. This innovative method combines the concept of Cumulants and Gram-Charlier expansion theory to obtain probabilistic distribution functions of transmission line flows. It has significantly reduced the computational time while maintaining a high degree of accuracy. This enables probabilistic analysis of power flow problems to be treated objectively and allows quantitative assessment of system reliability.

A method to prevent excessive numbers of Markov states in Markov models for quantitative safety and reliability assessment

This paper presents a method that will drastically reduce the calculation effort required to obtain quantitative safety and reliability assessments to determine safety integrity levels for applications in the process industry. The method described combines all benefits of Markov modeling with the practical benefits of reliability block diagrams.

Extending health considerations in subtransmission systems to include reliability worth

The basic concepts associated with quantitative reliability assessment of electric power systems are reasonably well established, and well accepted within the power industry. The evaluation of the costs and benefits of competing investments is now becoming a standard practice in power-system planning. To justify the use of new facilities and system modification specific reference to reliability has normally been included, and one approach that has received considerable attention is the evaluation of the societal worth (benefit) of system reliability, or conversely the costs incurred by consumers due to power supply interruptions. To make a consistent appraisal of economics and reliability, it is necessary to compare investment cost needed to attain a specified level of reliability with the reliability worth or benefits derived by the society at that level of system reliability. The well-being framework is extended to include the societal worth of electric service reliability in subtransmission systems. System well-being is defined in terms of three system states: (i) healthy, (ii) marginal and (iii) at risk, thus combining the deterministic and probabilistic approaches into a single framework. The determination of reliability worth indices of expected energy not supplied (EENS), expected cost of interruptions (ECOST) and interrupted energy assessment rate (IEAR) are discussed, for both the healthy and at risk states in the well-being framework. The concepts associated with extending the well-being framework to include reliability worth parameters are illustrated by application to a small reliability test system designated RBTS.

Power system reliability cost/benefit assessment and application in perspective

The basic concepts associated with quantitative reliability assessment of electric power systems are reasonably well established and well accepted by the power industry. The evaluation of the costs and benefits of competing investments is now becoming a standard practice in power system planning. The justification of new facilities and system modifications now normally includes specific reference to reliability and one approach that is receiving considerable attention is the evaluation of the societal worth (benefit) of system reliability, or conversely the costs incurred by consumers due to power supply interruptions. In order to make a consistent appraisal of economics and reliability, it is imperative to compare the investment cost needed to attain a specified level of reliability with the reliability worth or benefits derived by the society at that level of system reliability. This paper discusses the developments made in existing techniques in the area of power system reliability cost/benefit evaluation and application. Reliability worth data presently used in cost/worth evaluation are presented, and their applications in conjunction with the system reliability indices are also presented in this paper.