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At least 127 records · Page 7

The Diagnostic Challenge Competition: Probabilistic Techniques for Fault Diagnosis in Electrical Power Systems

Reliable systems health management is an important research area of NASA. A health management system that can accurately and quickly diagnose faults in various on-board systems of a vehicle will play a key role in the success of current and future NASA missions. We introduce in this paper the ProDiagnose algorithm, a diagnostic algorithm that uses a probabilistic approach, accomplished with Bayesian Network models compiled to Arithmetic Circuits, to diagnose these systems. We describe the ProDiagnose algorithm, how it works, and the probabilistic models involved. We show by experimentation on two Electrical Power Systems based on the ADAPT testbed, used in the Diagnostic Challenge Competition (DX 09), that ProDiagnose can produce results with over 96% accuracy and less than 1 second mean diagnostic time.

Ricks, Brian W.↗

Application of Analytical Hierarchy Process for Narrowing Down Nep Candidate Reactor Designs

Nuclear electric propulsion (NEP)-powered vehicles have been contemplated for human Mars missions. The nuclear power system contemplates using a high temperature light-weight nuclear reactor for the production of electrical power in the range of 2-5 MWe with a 3-10 year service life. A myriad of technology options exist for achieving these mission objectives. The analytic hierarchy process (AHP), a multi-attribute decision method, is being used to narrow down the candidate designs. The AHP is a structured decision process that fuses model-supplied quantitative data with subjective assessments to facilitate decisions that involve multiple competing criteria. Proven end-to-end nuclear design and systems analysis tools will be used to provide quantitative performance data such as end-to-end system reliability, system robustness to recover from off-normal conditions, system specific weight (α in kg/kWe), and the ability to meet the service life-time and power level requirements. Three high assay low enriched uranium (HALEU) reactor concepts, namely, gas-, heat pipe- and pumped liquid-cooled nuclear cores coupled to a He/Xe gas or supercritical CO2- Brayton power conversion system are being modeled using the AHP to understand the trade-offs associated with these design combinations. In addition to the reactor and power conversion options, there are a myriad of additional components and subsystems – e.g., radiators, heat exchangers, and recuperators – that also figure into the evaluation process. The choice of the right overall system is a multidimensional problem that has to include not only quantitative data, but also the so called “external factors”, examples of which include the component and subsystem Technology Readiness Levels (TRLs), the associated Advancement Degrees of Difficulty (AD2), the cost and schedule required to achieve a technical maturity consistent with mission infusion, alignment with the priorities of NASA’s Space Nuclear Propulsion program, and alignment with other ongoing government and commercial investments in micro reactors. Focused expert elicitations form the basis for qualitative data set. As a final step, decision-makers individually express their opinions regarding the relative importance of the criteria and preferences among the alternatives through pairwise comparisons. The paper will describe the AHP approach, progress to-date applying it to the NEP human Mars mission problem, and preliminary results. Use of AHP provides sufficient flexibility for incorporating industry input at different stages as the technologies evolve through additional research and development. It is expected that the decision process will be ongoing and expanded to examine additional options and technology choices, culminating in a defensible set of candidate reactor concepts that will form the basis for developing a multi-year NEP technology maturation strategy. .

Dasari V Rao↗

Trends in reliability modeling technology for fault tolerant systems

Reliability modeling for fault tolerant avionic computing systems was developed. The modeling of large systems involving issues of state size and complexity, fault coverage, and practical computation was discussed. A novel technique which provides the tool for studying the reliability of systems with nonconstant failure rates is presented. The fault latency which may provide a method of obtaining vital latent fault data is measured.

Bavuso, S. J.↗

User's guide to the Reliability Estimation System Testbed (REST)

The Reliability Estimation System Testbed is an X-window based reliability modeling tool that was created to explore the use of the Reliability Modeling Language (RML). RML was defined to support several reliability analysis techniques including modularization, graphical representation, Failure Mode Effects Simulation (FMES), and parallel processing. These techniques are most useful in modeling large systems. Using modularization, an analyst can create reliability models for individual system components. The modules can be tested separately and then combined to compute the total system reliability. Because a one-to-one relationship can be established between system components and the reliability modules, a graphical user interface may be used to describe the system model. RML was designed to permit message passing between modules. This feature enables reliability modeling based on a run time simulation of the system wide effects of a component's failure modes. The use of failure modes effects simulation enhances the analyst's ability to correctly express system behavior when using the modularization approach to reliability modeling. To alleviate the computation bottleneck often found in large reliability models, REST was designed to take advantage of parallel processing on hypercube processors.

Nicol, David M.↗

Development and testing of a performance evaluation methodology to assess the reliability of occupancy sensor systems in residential buildings

With the emergence of advanced occupancy sensor technologies to better detect occupancy in buildings, a universal methodology and metrics are required to evaluate and report sensor systems’ reliability and compare the performance across multiple sensor systems. Herein this research presents a methodology to assess the reliability of occupancy sensor systems in residential buildings in a controlled laboratory environment, including both “typical” and “failure” testing scenarios. The developed methodology was then implemented to evaluate a novel occupancy detection sensor system’s reliability. “Typical” testing evaluates the overall accuracy of the sensor system, which suggest how reliable the occupancy sensor system is over time. Results show that on average, the precision and recall are 0.75 and 0.70, indicating similar numbers of false positives and false negatives across the dataset. The overall accuracy of the tested sensor system was 62.4% to 76.4%. Failure testing results indicate whether there are influential variables impacting the sensor performance. For the tested sensor system, the number of occupants, presence of large objects, presence of interior light sources, and number of doors are not influential, while lighting level, location of occupants, additional door in the entry/exit area, and having the TV on are variables determined to impact the sensor system performance.

47 OTHER INSTRUMENTATION↗

On reliable control system designs

A research effort is summarized which addresses some of the current problems in interfacing systems theory and reliability. Reliability is roughly the probability that a system will perform according to specifications for a given amount of time. The reliability of a system depends on the structure of its components. Systems theory and control theory deal with the response characteristics of a system, which depend on the system dynamics. The concepts necessary to unify the structural and the dynamic properties of a system are defined. The result is a definition of what constitutes a reliable systems, from the viewpoint of systems theory, and a methodology which can be used to determine if a given design allows a reliable control system design.

Birdwell, J. Douglas↗

An Approach to Automate tools for the Risk Assessment of Digital Instrumentation and Control Systems

Reliable digital instrumentation and control systems (DI&C) are integral for sustaining the continued operation of nuclear power plants. These systems ensure that nuclear reactors operate safely, efficiently, and within regulatory requirements. Yet, the cost of designing and licensing new nuclear DI&C can be prohibitively expensive. Under the U.S. Department of Energy Light Water Reactor Sustainability Program, Idaho National Laboratory has developed a framework for supporting the risk-informed design of DI&C systems by offering methods to support the identification, quantification, and evaluation of risks for various DI&C design architectures. The framework indicates potential software failure modes and provides pathways for quantifying the potential for these software failures, including common cause failures. Using the framework’s systematic approach, challenges for assessing risks within new and existing nuclear DI&C systems can be reduced. Nevertheless, the current framework can be further improved using the convenience of automation. This paper introduces the development of Software for the Hazard Identification and Evaluation of Digital Systems (SHIELDS). SHIELDS is an engineering software package that enables the identification, elimination, and mitigation of potential risks and reduces the burden of deploying reliable DI&C systems. This work introduces plans and techniques to digitize and improve the manual risk assessment modules of the framework. These improvements will save time and increase the repeatability and usability of the framework, making it more accessible to a wider range of users. Ultimately, this introduces SHIELDS and how its modules support efficient development of safe and reliable DI&C systems.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗