STANDARDIZING FUNCTIONAL SAFETY ASSESSMENTS FOR OFF-THE-SHELF INSTRUMENTATION AND CONTROLS

It is typical for digital instrumentation and controls, used to manage significant risk, to undergo substantial amounts of scrutiny. The equipment must be proven to have the necessary level of design integrity. The details of the scrutiny vary based on the particular industry, but the ultimate goal is to provide sufficient evidence that the equipment will operate successfully when performing their required functions. To be able to stand up to the scrutiny and more importantly, successfully perform the required safety functions, the equipment must be designed to defend against random hardware failures and also to prevent systematic faults. These design activities must also have been documented in a manner that sufficiently proves their adequacy. The variability in the requirements of the different industries makes this task difficult for instrumentation and controls equipment manufacturers. To assist the manufacturers in dealing with these differences, a standardization of requirements is needed to facilitate clear communication of expectations. The IEC 61508 set of standards exists to fulfill this role, but it is not yet universally embraced. After that occurs, various industries, from nuclear power generation to oil & gas production, will benefit from the existence of a wider range of equipment that has been designed to perform in these critical roles and that also includes the evidence necessary to prove its integrity. The manufacturers will then be able to enjoy the benefit of having a larger customer base interested in their products. The use of IEC 61508 will also help industries avoid significant amounts of uncertainty when selecting commercial off-the-shelf equipment. It is currently understood that it cannot be assumed that a typical commercial manufacturer’s equipment designs and associated design activities will be adequate to allow for success in these high risk applications. In contrast, a manufacturer that seeks to comply with IEC 61508 and seeks to achieve certification by an independent third party can be assumed to be better suited for meeting the needs of these demanding situations. Use of these manufacturers help to avoid substantial uncertainty and risk

Methods and Systems for Fault Diagnosis in Nuclear Power Plants

This research mainly deals with fault diagnosis in nuclear power plants (NPP), based on a framework that integrates contributions from fault scope identification, optimal sensor placement, sensor validation, equipment condition monitoring, and diagnostic reasoning based on pattern analysis. The research has a particular focus on applications where data collected from the existing SCADA (supervisory, control, and data acquisition) system is not sufficient for the fault diagnosis system. Specifically, the following methods and systems are developed. A sensor placement model is developed to guide optimal placement of sensors in NPPs. The model includes 1) a method to extract a quantitative fault-sensor incidence matrix for a system; 2) a fault diagnosability criterion based on the degree of singularities of the incidence matrix; and 3) procedures to place additional sensors to meet the diagnosability criterion. Usefulness of the proposed method is demonstrated on a nuclear power plant process control test facility (NPCTF). Experimental results show that three pairs of undiagnosable faults can be effectively distinguished with three additional sensors selected by the proposed model. A wireless sensor network (WSN) is designed and a prototype is implemented on the NPCTF. WSN is an effective tool to collect data for fault diagnosis, especially for systems where additional measurements are needed. The WSN has distributed data processing and information fusion for fault diagnosis. Experimental results on the NPCTF show that the WSN system can be used to diagnose all six fault scenarios considered for the system. A fault diagnosis method based on semi-supervised pattern classification is developed which requires significantly fewer training data than is typically required in existing fault diagnosis models. It is a promising tool for applications in NPPs, where it is usually difficult to obtain training data under fault conditions for a conventional fault diagnosis model. The proposed method has successfully diagnosed nine types of faults physically simulated on the NPCTF. For equipment condition monitoring, a modified S-transform (MST) algorithm is developed by using shaping functions, particularly sigmoid functions, to modify the window width of the existing standard S-transform. The MST can achieve superior time-frequency resolution for applications that involves non-stationary multi-modal signals, where classical methods may fail. Effectiveness of the proposed algorithm is demonstrated using a vibration test system as well as applications to detect a collapsed pipe support in the NPCTF. The experimental results show that by observing changes in time-frequency characteristics of vibration signals, one can effectively detect faults occurred in components of an industrial system. To ensure that a fault diagnosis system does not suffer from erroneous data, a fault detection and isolation (FDI) method based on kernel principal component analysis (KPCA) is extended for sensor validations, where sensor faults are detected and isolated from the reconstruction errors of a KPCA model. The method is validated using measurement data from a physical NPP. The NPCTF is designed and constructed in this research for experimental validations of fault diagnosis methods and systems. Faults can be physically simulated on the NPCTF. In addition, the NPCTF is designed to support systems based on different instrumentation and control technologies such as WSN and distributed control systems. The NPCTF has been successfully utilized to validate the algorithms and WSN system developed in this research. In a real world application, it is seldom the case that one single fault diagnostic scheme can meet all the requirements of a fault diagnostic system in a nuclear power. In fact, the values and performance of the diagnosis system can potentially be enhanced if some of the methods developed in this thesis can be integrated into a suite of diagnostic tools. In such an integrated system, WSN nodes can be used to collect additional data deemed necessary by sensor placement models. These data can be integrated with those from existing SCADA systems for more comprehensive fault diagnosis. An online performance monitoring system monitors the conditions of the equipment and provides key information for the tasks of condition-based maintenance. When a fault is detected, the measured data are subsequently acquired and analyzed by pattern classification models to identify the nature of the fault. By analyzing the symptoms of the fault, root causes of the fault can eventually be identified

DETAM for accident sequence analysis

Includes bibliographical references (pages 133-138)Final reportSupported by the United States Nuclear Regulatory Commission. NRC-04-88-14

Development of a computer-aided fault tree synthesis methodology for quantitative risk analysis in the chemical process industry

There has been growing public concern regarding the threat to people and environment from industrial activities, thus more rigorous regulations. The investigation of almost all the major accidents shows that we could have avoided those tragedies with effective risk analysis and safety management programs. High-quality risk analysis is absolutely necessary for sustainable development. As a powerful and systematic tool, fault tree analysis (FTA) has been adapted to the particular need of chemical process quantitative risk analysis (CPQRA) and found great applications. However, the application of FTA in the chemical process industry (CPI) is limited. One major barrier is the manual synthesis of fault trees. It requires a thorough understanding of the process and is vulnerable to individual subjectivity. The quality of FTA can be highly subjective and variable. The availability of a computer-based FTA methodology will greatly benefit the CPI. The primary objective of this research is to develop a computer-aided fault tree synthesis methodology for CPQRA. The central idea is to capture the cause-and-effect logic around each item of equipment directly into mini fault trees. Special fault tree models have been developed to manage special features. Fault trees created by this method are expected to be concise. A prototype computer program is provided to illustrate the methodology. Ideally, FTA can be standardized through a computer package that reads information contained in process block diagrams and provides automatic aids to assist engineers in generating and analyzing fault trees. Another important issue with regard to QRA is the large uncertainty associated with available failure rate data. In the CPI, the ranges of failure rates observed could be quite wide. Traditional reliability studies using point values of failure rates may result in misleading conclusions. This dissertation discusses the uncertainty with failure rate data and proposes a procedure to deal with data uncertainty in determining safety integrity level (SIL) for a safety instrumented system (SIS). Efforts must be carried out to obtain more accurate values of those data that might actually impact the estimation of SIL. This procedure guides process hazard analysts toward a more accurate SIL estimation and avoids misleading results due to data uncertainty

Common cause analysis : a review and extension of existing methods

The quantitative common cause analysis code, MOBB, is extended to include uncertainties arising from modelling uncertainties and data uncertainties. Two methods, Monte Carlo simulation and the Method-of-Moments are used to propagate uncertainties through the analysis. The two different capabilities of the code are then compared. When component failure rates are assumed lognormallv distributed, bounded lognormal (Sb) distributions are used to evaluate higher moment terms, as required by the Method-of-Moments, in order to minimize the effect of the tail of the lognormal. A code using the discrete probability distribution (DPD) method is developed for analyzing system unavailability due to common initiating events (internal and external). Sample problems demonstrating each approach are also presented

Nuclear Propulsion Technical Interchange Meeting, volume 2

The purpose of the meeting was to review the work performed in fiscal year 1992 in the areas of nuclear thermal and nuclear electric propulsion technology development. These proceedings are an accumulation of the presentations provided at the meeting along with annotations provided by authors. The proceedings cover system concepts, technology development, and system modeling for nuclear thermal propulsion (NTP) and nuclear electric propulsion (NEP). The test facilities required for the development of the nuclear propulsion systems are also discussed

Aerospace medicine and biology: A continuing bibliography with indexes, supplement 204

This bibliography lists 140 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1980