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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1971

On reliability modeling and analysis of ultrareliable fault-tolerant digital systems.

The processes of protective redundancy, namely, standby replacement (SR) redundancy and hybrid redundancy (a combination of SR and multiple-line voting redundancy), find application in the architecture of fault-tolerant digital computers and enable them to be ultrareliable and self-repairing. The claims to ultrareliability lead to the challenge of quantitatively evaluating and assigning a value to the probability of survival as a function of the mission durations intended. This note presents various mathematical models, and derives and displays quantitative evaluations of system reliability as a function of various mission parameters of interest to the system designer.

Mathur, F. P.↗
NASA NTRS1974

Orbital maneuvering subsystem functional path analysis for performance monitoring fault detection and annunciation

The functional paths of the Orbital Maneuver Subsystem (OMS) is defined. The operational flight instrumentation required for performance monitoring, fault detection, and annunciation is described. The OMS is a pressure fed rocket engine propulsion subsystem. One complete OMS shares each of the two auxiliary propulsion subsystem pods with a reaction control subsystem. Each OMS is composed of a pressurization system, a propellant tanking system, and a gimbaled rocket engine. The design, development, and operation of the system are explained. Diagrams of the system are provided.

Keesler, E. L.↗
NASA NTRS1983

Unified analysis methods for a fault tolerant redundant strapdown inertial measurement unit

The use of a redundant strapdown inertial measurement unit (RSDIMU) has been considered as a source of sensor information for future aircraft. It is pointed out that failure detection and isolation (FDI) should be accomplished at the sensor level to ensure the accurate transfer of information to elements of the integrated avionics system. The present investigation is concerned with the impact of the FDI algorithm on system reliability and vice versa. A description is given of a technique to identify and assess critical areas of reliability requirements for the RSDIMU. Attention is given to the development of an FDI algorithm to meet these requirements.

Morrell, F. R.↗
NASA NTRS1987

Analysis of typical fault-tolerant architectures using HARP

Difficulties encountered in the modeling of fault-tolerant systems are discussed. The Hybrid Automated Reliability Predictor (HARP) approach to modeling fault-tolerant systems is described. The HARP is written in FORTRAN, consists of nearly 30,000 lines of codes and comments, and is based on behavioral decomposition. Using the behavioral decomposition, the dependability model is divided into fault-occurrence/repair and fault/error-handling models; the characteristics and combining of these two models are examined. Examples in which the HARP is applied to the modeling of some typical fault-tolerant systems, including a local-area network, two fault-tolerant computer systems, and a flight control system, are presented.

Bavuso, Salvatore J.↗
NASA NTRS1988

Evaluate the application of modal test and analysis processes to structural fault detection in MSFC-STS project elements

The Space Transportation System (STS) is a very complex and expensive flight system which is intended to carry payloads into low Earth orbit and return. A catastrophic failure of the STS (such as experienced in the 51-L incident) results in the loss of both human life as well as very expensive hardware. One impact of this incident was to reaffirm the need to do everything possible to insure the integrity and reliability of the STS is sufficient to produce a safe flight. One means of achieving this goal is to expand the number of inspection technologies available for use on the STS. The purpose was to begin to evaluate the possible use of assessing the structural integrity of STS components for which Marshall Space Flight Center (MSFC) has responsibility. This entailed reviewing the available literature and determining a low-level experimental program which could be performed by MSFC and would help establish the feasibility of using this technology for structural fault detection.

Springer, William T.↗
NASA NTRS2018

Advanced Symbolic Analysis Tools for Fault-Tolerant Integrated Distributed Systems

The project aims to develop advanced model-checking algorithms and tools to automate the verification of fault-tolerant distributed systems for avionics. We present a new method called Property-Directed K-Induction (PD-KIND) for synthesizing K-inductive invariants of state-transition systems. PD-KIND builds upon Satifiability Modulo Theories (SMT) to generalize Bradley's IC3 method and its variants. This method is implemented in a new tool called SALLY. Case studies show that PD-KIND can automatically verify fault-tolerant algorithms under a variety of fault models and that SALLY is competitive with other SMT-based model checkers.

Dutertre, Bruno↗
NASA NTRS2019

Achieving Improved Reliability with Failure Analysis

Reliability is the ability of a product to properly function, within specified performance limits, for a specified period of time, under the life cycle application conditions. Failure analysis is a vital tool in the effort to ensure reliability of electronic products and systems throughout their product lifecycle. Today, organizations involved in activities within the electronics supply chain are facing new challenges, not just from complex assembly styles, harsher lifecycle environments, and sophisticated supply chains, but also from customers who are demanding a quicker turn-around. Unfortunately, root cause failure analysis is often performed incompletely, leading to a poor understanding of failure mechanisms and causes and, customer dissatisfaction due to recurring failures. The PDC (Professional Development Course) starts with an introduction to reliability concepts, physics of failure and an overview of failure mechanisms that affect PCBs (Printed Circuit Boards), PCBAs (Printed Circuit Board Assembly) and components. The PDC then dives into root cause hypothesizing techniques (Pareto, FMEA (Failure Modes and Effects Analysis), fishbone (Cause-And-Effect Diagram), FTA (Fault Tree Analysis)), non-destructive and destructive analysis and, materials characterization will be discussed. Numerous failure analysis case studies will be used to illustrate the techniques and analysis principles to arrive at the root cause(s) of field failures on printed circuit boards, active components, and assemblies. What Attendees will Learn: Topics include: Overview of Reliability Concepts Failure mechanisms of electronic products Root cause analysis Failure analysis techniques -Non-destructive techniques (optical, CSAM (Confocal Scanning Electron Microscopy) etc.) -Destructive analysis (DPA (Destructive Physical Analysis), Decap (Decapsulation), FIB (Focused Ion Beam) etc.) -Materials characterization (XRF (X-Ray Fluorescence) , EDS (Error Detection Sequential), TMA/DSC (Thermal Mechanical Analysis/Differential Scanning Calorimetry) etc.)

PCB quality↗
NASA NTRS1990

Model authoring system for fail safe analysis

The Model Authoring System is a prototype software application for generating fault tree analyses and failure mode and effects analyses for circuit designs. Utilizing established artificial intelligence and expert system techniques, the circuits are modeled as a frame-based knowledge base in an expert system shell, which allows the use of object oriented programming and an inference engine. The behavior of the circuit is then captured through IF-THEN rules, which then are searched to generate either a graphical fault tree analysis or failure modes and effects analysis. Sophisticated authoring techniques allow the circuit to be easily modeled, permit its behavior to be quickly defined, and provide abstraction features to deal with complexity.

Sikora, Scott E.↗
NASA NTRS2016

Functional Fault Model Development Process to Support Design Analysis and Operational Assessment

A functional fault model (FFM) is an abstract representation of the failure space of a given system. As such, it simulates the propagation of failure effects along paths between the origin of the system failure modes and points within the system capable of observing the failure effects. As a result, FFMs may be used to diagnose the presence of failures in the modeled system. FFMs necessarily contain a significant amount of information about the design, operations, and failure modes and effects. One of the important benefits of FFMs is that they may be qualitative, rather than quantitative and, as a result, may be implemented early in the design process when there is more potential to positively impact the system design. FFMs may therefore be developed and matured throughout the monitored system's design process and may subsequently be used to provide real-time diagnostic assessments that support system operations. This paper provides an overview of a generalized NASA process that is being used to develop and apply FFMs. FFM technology has been evolving for more than 25 years. The FFM development process presented in this paper was refined during NASA's Ares I, Space Launch System, and Ground Systems Development and Operations programs (i.e., from about 2007 to the present). Process refinement took place as new modeling, analysis, and verification tools were created to enhance FFM capabilities. In this paper, standard elements of a model development process (i.e., knowledge acquisition, conceptual design, implementation & verification, and application) are described within the context of FFMs. Further, newer tools and analytical capabilities that may benefit the broader systems engineering process are identified and briefly described. The discussion is intended as a high-level guide for future FFM modelers.

Verification↗
NASA NTRS2004

Abstractions for Fault-Tolerant Distributed System Verification

Four kinds of abstraction for the design and analysis of fault tolerant distributed systems are discussed. These abstractions concern system messages, faults, fault masking voting, and communication. The abstractions are formalized in higher order logic, and are intended to facilitate specifying and verifying such systems in higher order theorem provers.

Pike, Lee S.↗
NASA NTRS2007

Testing for Software Safety

This research focuses on testing whether or not the hazardous conditions identified by design-level fault tree analysis will occur in the target implementation. Part 1: Integrate fault tree models into functional specifications so as to identify testable interactions between intended behaviors and hazardous conditions. Part 2: Develop a test generator that produces not only functional tests but also safety tests for a target implementation in a cost-effective way. Part 3: Develop a testing environment for executing generated functional and safety tests and evaluating test results against expected behaviors or hazardous conditions. It includes a test harness as well as an environment simulation of external events and conditions.

Chen, Ken↗
NASA NTRS2024

Failure-Tolerant Avionics for Crewed Space Systems Recommended Best Practices

This paper provides an overview of some of the major steps needed to mature and justify the design of an avionics system for crewed spacecraft. It is organized as a collection of artifacts or pieces of evidence that NASA needs to assess the system at design reviews, including a functional failure modes and effects analysis (FFMEA), fault containment region (FCR) definitions, the failure hypothesis, and reliability analysis. This paper is intended as a reference for designers working on NASA crewed spaceflight projects, reliability engineers responsible for avionics system assessments, and program managers wanting to understand what evidence is required at design reviews to ensure crew safety and mission success.

Avionics↗
NASA NTRS1992

A study of mapping exogenous knowledge representations into CONFIG

Qualitative reasoning is reasoning with a small set of qualitative values that is an abstraction of a larger and perhaps infinite set of quantitative values. The use of qualitative and quantitative reasoning together holds great promise for performance improvement in applications that suffer from large and/or imprecise knowledge domains. Included among these applications are the modeling, simulation, analysis, and fault diagnosis of physical systems. Several research groups continue to discover and experiment with new qualitative representations and reasoning techniques. However, due to the diversity of these techniques, it is difficult for the programs produced to exchange system models easily. The availability of mappings to transform knowledge from the form used by one of these programs to that used by another would open the doors for comparative analysis of these programs in areas such as completeness, correctness, and performance. A group at the Johnson Space Center (JSC) is working to develop CONFIG, a prototype qualitative modeling, simulation, and analysis tool for fault diagnosis applications in the U.S. space program. The availability of knowledge mappings from the programs produced by other research groups to CONFIG may provide savings in CONFIG's development costs and time, and may improve CONFIG's performance. The study of such mappings is the purpose of the research described in this paper. Two other research groups that have worked with the JSC group in the past are the Northwest University Group and the University of Texas at Austin Group. The former has produced a qualitative reasoning tool named SIMGEN, and the latter has produced one named QSIM. Another program produced by the Austin group is CC, a preprocessor that permits users to develop input for eventual use by QSIM, but in a more natural format. CONFIG and CC are both based on a component-connection ontology, so a mapping from CC's knowledge representation to CONFIG's knowledge representation was chosen as the focus of this study. A mapping from CC to CONFIG was developed. Due to differences between the two programs, however, the mapping transforms some of the CC knowledge to CONFIG as documentation rather than as knowledge in a form useful to computation. The study suggests that it may be worthwhile to pursue the mappings further. By implementing the mapping as a program, actual comparisons of computational efficiency and quality of results can be made between the QSIM and CONFIG programs. A secondary study may reveal that the results of the two programs augment one another, contradict one another, or differ only slightly. If the latter, the qualitative reasoning techniques may be compared in other areas, such as computational efficiency.

Mayfield, Blayne E.↗
NASA NTRS2016

Functional Fault Model Development Process to Support Design Analysis and Operational Assessment

A functional fault model (FFM) is an abstract representation of the failure space of a givensystem. As such, it simulates the propagation of failure effects along paths between the origin ofthe system failure modes and points within the system capable of observing the failure effects. Asa result, FFMs may be used to diagnose the presence of failures in the modeled system. FFMsnecessarily contain a significant amount of information about the design, operations, and failuremodes and effects. One of the important benefits of FFMs is that they may be qualitative, ratherthan quantitative and, as a result, may be implemented early in the design process when there ismore potential to positively impact the system design. FFMs may therefore be developed andmatured throughout the monitored system's design process and may subsequently be used toprovide real-time diagnostic assessments that support system operations. This paper provides anoverview of a generalized NASA process that is being used to develop and apply FFMs. FFMtechnology has been evolving for more than 25 years. The FFM development process presented inthis paper was refined during NASA's Ares I, Space Launch System, and Ground SystemsDevelopment and Operations programs (i.e., from about 2007 to the present). Process refinementtook place as new modeling, analysis, and verification tools were created to enhance FFMcapabilities. In this paper, standard elements of a model development process (i.e., knowledgeacquisition, conceptual design, implementation & verification, and application) are describedwithin the context of FFMs. Further, newer tools and analytical capabilities that may benefit thebroader systems engineering process are identified and briefly described. The discussion isintended as a high-level guide for future FFM modelers.

Melcher, Kevin J.↗