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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Incorporation of a progressive failure analysis method in the CSM testbed software system

Analysis of the postbuckling behavior of composite shell structures pose many difficult and challenging problems in the field of structural mechanics. Current analysis methods perform well for most cases in predicting the postbuckling response of undamaged components. To predict component behavior accurately at higher load levels, the analysis must include the effects of local material failures. The CSM testbed software system is a highly modular structural analysis system currently under development at Langley Research Center. One of the primary goals of the CSM testbed is to provide a software environment for the development of advanced structural analysis methods and modern numerical methods which will exploit advanced computer architecture such as parallel-vector processors. Development of a progressive failure analysis method consists of the design and implementation of a processor which will perform the ply-level progressive failure analysis and the development of a geometrically nonlinear analysis procedure which incorporates the progressive failure processor. Regarding the development of the progressive failure processor, two components are required: failure criteria and a degradation model. For the initial implementation, the failure criteria of Hashin will be used. For a matrix failure which typically indicates the development of transverse matrix cracks, the ply properties will be degraded. Work to date includes the design of the progressive failure analysis processor and initial plans for the controlling geometrically nonlinear analysis procedure. The implementation of the progressive failure analysis has begun. Access to the model database and the Hashin failure criteria are completed. Work is in progress on the input/output operations for the processor related data and the finite element model updating procedures. In total the progressive failure processor is approximately one-third complete.

Arenburg, Robert T.↗
DOE OSTI2020

Safety Risk Reliability Model Library

SR2ML is a software package which contains a set of safety and reliability models designed to be interfaced with the INL developed RAVEN code. These models can be employed to perform both static and dynamic system risk analysis and determine risk importance of specific elements of the considered system. Two classes of reliability models have been developed; the first class includes all classical reliability models (Fault-Trees, Event-Trees, Markov models and Reliability Block Diagrams) which have been extended to deal not only with Boolean logic values but also time dependent values. The second class includes several components aging models. Models of these two classes are designed to be included in a RAVEN ensemble model to perform time dependent system reliability analysis (dynamic analysis). Similarly, these models can be interfaced with system analysis codes to determine failure time of systems and evaluate accident progression (static analysis).

Wang, Congjian↗
NASA NTRS1977

Prevention of design flaws in multicomputer systems

Report summarizes research on failure mode analysis for multicomputer systems where two or more computers may serve as redundant set. Failure modes such as data bus monopolization, shutdown due to transients, loss of control system equalization, memory alteration, and software errors are discussed.

Romberg, J. M.↗
NASA NTRS1992

Fault management for the Space Station Freedom control center

This paper describes model based reasoning fault isolation in complex systems using automated digraph analysis. It discusses the use of the digraph representation as the paradigm for modeling physical systems and a method for executing these failure models to provide real-time failure analysis. It also discusses the generality, ease of development and maintenance, complexity management, and susceptibility to verification and validation of digraph failure models. It specifically describes how a NASA-developed digraph evaluation tool and an automated process working with that tool can identify failures in a monitored system when supplied with one or more fault indications. This approach is well suited to commercial applications of real-time failure analysis in complex systems because it is both powerful and cost effective.

Clark, Colin↗
NASA NTRS2006

A Taxonomy of Fallacies in System Safety Arguments

Safety cases are gaining acceptance as assurance vehicles for safety-related systems. A safety case documents the evidence and argument that a system is safe to operate; however, logical fallacies in the underlying argument may undermine a system s safety claims. Removing these fallacies is essential to reduce the risk of safety-related system failure. We present a taxonomy of common fallacies in safety arguments that is intended to assist safety professionals in avoiding and detecting fallacious reasoning in the arguments they develop and review. The taxonomy derives from a survey of general argument fallacies and a separate survey of fallacies in real-world safety arguments. Our taxonomy is specific to safety argumentation, and it is targeted at professionals who work with safety arguments but may lack formal training in logic or argumentation. We discuss the rationale for the selection and categorization of fallacies in the taxonomy. In addition to its applications to the development and review of safety cases, our taxonomy could also support the analysis of system failures and promote the development of more robust safety case patterns.

Greenwell, William S.↗
NASA NTRS1993

Real-time automated failure analysis for on-orbit operations

A system which is to provide real-time failure analysis support to controllers at the NASA Johnson Space Center Control Center Complex (CCC) for both Space Station and Space Shuttle on-orbit operations is described. The system employs monitored systems' models of failure behavior and model evaluation algorithms which are domain-independent. These failure models are viewed as a stepping stone to more robust algorithms operating over models of intended function. The described system is designed to meet two sets of requirements. It must provide a useful failure analysis capability enhancement to the mission controller. It must satisfy CCC operational environment constraints such as cost, computer resource requirements, verification, and validation. The underlying technology and how it may be used to support operations is also discussed.

Kirby, Sarah↗
DOE OSTI2021

A Machine Learning-Based Vulnerability Analysis for Cascading Failures of Integrated Power-Gas Systems

This article proposes a cascading failure simulation (CFS) method and a hybrid machine learning method for vulnerability analysis of integrated power-gas systems (IPGSs). The CFS method is designed to study the propagating process of cascading failures between the two systems, generating data for machine learning with initial states randomly sampled. The proposed method considers generator and gas well ramping, transmission line and gas pipeline tripping, island issue handling and load shedding strategies. Then, a hybrid machine learning model with a combined random forest (RF) classification and regression algorithms is proposed to investigate the impact of random initial states on the vulnerability metrics of IPGSs. Extensive case studies are carried out on three test IPGSs to verify the proposed models and algorithms. Simulation results show that the proposed models and algorithms can achieve high accuracy for the vulnerability analysis of IPGSs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2014

Investigation of HZETRN 2010 as a Tool for Single Event Effect Qualification of Avionics Systems

NASA's future missions are focused on long-duration deep space missions for human exploration which offers no options for a quick emergency return to Earth. The combination of long mission duration with no quick emergency return option leads to unprecedented spacecraft system safety and reliability requirements. It is important that spacecraft avionics systems for human deep space missions are not susceptible to Single Event Effect (SEE) failures caused by space radiation (primarily the continuous galactic cosmic ray background and the occasional solar particle event) interactions with electronic components and systems. SEE effects are typically managed during the design, development, and test (DD&T) phase of spacecraft development by using heritage hardware (if possible) and through extensive component level testing, followed by system level failure analysis tasks that are both time consuming and costly. The ultimate product of the SEE DD&T program is a prediction of spacecraft avionics reliability in the flight environment produced using various nuclear reaction and transport codes in combination with the component and subsystem level radiation test data. Previous work by Koontz, et al.1 utilized FLUKA, a Monte Carlo nuclear reaction and transport code, to calculate SEE and single event upset (SEU) rates. This code was then validated against in-flight data for a variety of spacecraft and space flight environments. However, FLUKA has a long run-time (on the order of days). CREME962, an easy to use deterministic code offering short run times, was also compared with FLUKA predictions and in-flight data. CREME96, though fast and easy to use, has not been updated in several years and underestimates secondary particle shower effects in spacecraft structural shielding mass. Thus, this paper will investigate the use of HZETRN 20103, a fast and easy to use deterministic transport code, similar to CREME96, that was developed at NASA Langley Research Center primarily for flight crew ionizing radiation dose assessments. HZETRN 2010 includes updates to address secondary particle shower effects more accurately, and might be used as another tool to verify spacecraft avionics system reliability in space flight SEE environments.

Rojdev, Kristina↗
NASA NTRS1981

Logic analysis of complex systems by characterizing failure phenomena to achieve diagnosis and fault-isolation

A recent result shows that, for a certain class of systems, the interdependency among the elements of such a system together with the elements constitutes a mathematical structure a partially ordered set. It is called a loop free logic model of the system. On the basis of an intrinsic property of the mathematical structure, a characterization of system component failure in terms of maximal subsets of bad test signals of the system was obtained. Also, as a consequence, information concerning the total number of failure components in the system was deduced. Detailed examples are given to show how to restructure real systems containing loops into loop free models for which the result is applicable.

Wong, J. T.↗
NASA NTRS1985

Analytical investigation of solid rocket nozzle failure

On April 5, 1983, an Inertial Upper Stage (IUS) spacecraft experienced loss of control during the burn of the second of two solid rocket motors. The anomaly investigation showed the cause to be a malfunction of the solid rocket motor. This paper presents a description of the IUS system, a failure analysis summary, an account of the thermal testing and computer modeling done at Marshall Space Flight Center, a comparison of analysis results with thermal data obtained from motor static tests, and describes some of the design enhancement incorporated to prevent recurrence of the anomaly.

Mccoy, K. E.↗
NASA NTRS2006

Vulnerabilities, Influences and Interaction Paths: Failure Data for Integrated System Risk Analysis

We describe graph-based analysis methods for identifying and analyzing cross-subsystem interaction risks from subsystem connectivity information. By discovering external and remote influences that would be otherwise unexpected, these methods can support better communication among subsystem designers at points of potential conflict and to support design of more dependable and diagnosable systems. These methods identify hazard causes that can impact vulnerable functions or entities if propagated across interaction paths from the hazard source to the vulnerable target. The analysis can also assess combined impacts of And-Or trees of disabling influences. The analysis can use ratings of hazards and vulnerabilities to calculate cumulative measures of the severity and importance. Identification of cross-subsystem hazard-vulnerability pairs and propagation paths across subsystems will increase coverage of hazard and risk analysis and can indicate risk control and protection strategies.

Malin, Jane T.↗
DOE OSTI2023

Degradation Modeling of SOEC Systems

This presentation was delivered at the 2023 AICHE Annual Meeting. This presentation focuses on dynamic modeling of physical degradation of solid oxide cell systems and failure analysis.

Le, Quang↗
NASA NTRSDate not supplied

From BERTopic to SysML: Informing Model-Based Failure Analysis With Natural Language Processing for Complex Aerospace Systems

The development of emerging complex aerospace systems will require new approaches for capturing safety incident scenarios as early as possible in the design phase. However, for novel systems, relevant data available is limited. In this work, we propose a framework informing model-based mission assurance activities with historical incident reports, lessons learned, or other relevant engineering documents using natural language processing. In doing so, we investigate whether there is useful information in data sets that are relevant, if not identical, to the system under design and whether, through rigorous systems engineering practice, this information can be effectively leveraged through model-based failure analysis. In a worked case study, we apply state-of-the-art topic modeling techniques to two data sets, a mission relevant data set and a system relevant data set. The sets of topics are merged and interpreted to form a preliminary list of failure topics that can be used to inform the identification of off-nominal modes in the model-based failure modes and effects analysis development. Once data from the system in operation is available, it can be used to update the topics identified. By extracting information about likely failures from relevant historical data sets and utilizing model-based mission assurance to ensure relevance and rigor, unanticipated failures can be reduced, and projects can more effectively learn from past missions.

Failure Analysis↗
NASA NTRSDate not supplied

From BERTopic to SysML: Informing Model-Based Failure Analysis With Natural Language Processing for Complex Aerospace Systems

The development of emerging complex aerospace systems will require new approaches for capturing safety incident scenarios as early as possible in the design phase. However, for novel systems, relevant data available is limited. In this work, we propose a framework informing model-based mission assurance activities with historical incident reports, lessons learned, or other relevant engineering documents using natural language processing. In doing so, we investigate whether there is useful information in data sets that are relevant, if not identical, to the system under design and whether, through rigorous systems engineering practice, this information can be effectively leveraged through model-based failure analysis. In a worked case study, we apply state-of-the-art topic modeling techniques to two data sets, a mission relevant data set and a system relevant data set. The sets of topics are merged and interpreted to form a preliminary list of failure topics that can be used to inform the identification of off-nominal modes in the model-based failure modes and effects analysis development. Once data from the system in operation is available, it can be used to update the topics identified. By extracting information about likely failures from relevant historical data sets and utilizing model-based mission assurance to ensure relevance and rigor, unanticipated failures can be reduced, and projects can more effectively learn from past missions.

Failure Analysis↗
NASA NTRS1971

Direct modeling parameter signature analysis and failure mode prediction of physical systems using hybrid computer optimization

High speed automated identification and design of dynamic systems, both linear and nonlinear, are discussed. Special emphasis is placed on developing hardware and techniques which are applicable to practical problems. The basic modeling experiment and new results are described. Using the improvements developed successful identification of several systems, including a physical example as well as simulated systems, was obtained. The advantages of parameter signature analysis over signal signature analysis in go-no go testing of operational systems were demonstrated. The feasibility of using these ideas in failure mode prediction in operating systems was also investigated. An improved digital controlled nonlinear function generator was developed, de-bugged, and completely documented.

Drake, R. L.↗
DOE OSTI2024

Common Cause Failure Analysis for Nuclear Power Plant Instrumentation and Control Systems

This presentation is prepared for the IAEA Virtual Consultancy Meeting on Preparation of a Coordinated Research Project on Common Cause Failures in Nuclear Power Plant Instrumentation and Control Systems from February 5 ? 8, 2024. It provides an overview of the INL activities on the common cause failure analysis for instrumentation and control system in nuclear power plants.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1990

Failure analysis and modeling of a VAXcluster system

This paper discusses the results of a measurement-based analysis of real error data collected from a DEC VAXcluster multicomputer system. In addition to evaluating basic system dependability characteristics such as error and failure distributions and hazard rates for both individual machines and for the VAXcluster, reward models were developed to analyze the impact of failures on the system as a whole. The results show that more than 46 percent of all failures were due to errors in shared resources. This is despite the fact that these errors have a recovery probability greater than 0.99. The hazard rate calculations show that not only errors, but also failures occur in bursts. Approximately 40 percent of all failures occur in bursts and involved multiple machines. This result indicates that correlated failures are significant. Analysis of rewards shows that software errors have the lowest reward (0.05 vs 0.74 for disk errors). The expected reward rate (reliability measure) of the VAXcluster drops to 0.5 in 18 hours for the 7-out-of-7 model and in 80 days for the 3-out-of-7 model.

Tang, Dong↗
NASA NTRS2006

JSC Materials Laboratory Reproduction and Failure Analysis of Cracked Orbiter Reaction Control System Niobium Thruster Injectors

In April 2004 a Space Shuttle Orbiter Reaction Control System (RCS) thruster was found to be cracked while undergoing a nozzle (niobium/C103 alloy) retrofit. As a failure resulting from an in-flight RCS thruster burn-through (initiated from a crack) could be catastrophic, an official Space Shuttle Program flight constraint was issued until flight safety could be adequately demonstrated. This paper describes the laboratory test program which was undertaken to reproduce the cracking in order to fully understand and bound the driving environments. The associated rationale developed to justify continued safe flight of the Orbiter RCS system is also described. The laboratory testing successfully reproduced the niobium cracking, and established specific bounding conditions necessary to cause cracking in the C103 thruster injectors. Each of the following conditions is necessary in combination together: 1) a mechanically disturbed / cold-worked free surface, 2) an externally applied sustained tensile stress near yield strength, 3) presence of fluorine-containing fluids on exposed tensile / cold-worked free surfaces, and 4) sustained exposure to temperatures greater than 400 F. As a result of this work, it was concluded that fluorine-containing materials (e.g. HF acid, Krytox , Brayco etc.) should be carefully controlled or altogether eliminated during processing of niobium and its alloys.

Castner, Willard L.↗