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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Crack Growth Behavior in the Threshold Region for High Cycle Fatigue Loading

This paper describes the results of a research program conducted to improve the understanding of fatigue crack growth rate behavior in the threshold growth rate region and to answer a question on the validity of threshold region test data. The validity question relates to the view held by some experimentalists that using the ASTM load shedding test method does not produce valid threshold test results and material properties. The question involves the fanning behavior observed in threshold region of da/dN plots for some materials in which the low R-ratio data fans out from the high R-ratio data. This fanning behavior or elevation of threshold values in the low R-ratio tests is generally assumed to be caused by an increase in crack closure in the low R-ratio tests. Also, the increase in crack closure is assumed by some experimentalists to result from using the ASTM load shedding test procedure. The belief is that this procedure induces load history effects which cause remote closure from plasticity and/or roughness changes in the surface morphology. However, experimental studies performed by the authors have shown that the increase in crack closure is a result of extensive crack tip bifurcations that can occur in some materials, particularly in aluminum alloys, when the crack tip cyclic yield zone size becomes less than the grain size of the alloy. This behavior is related to the high stacking fault energy (SFE) property of aluminum alloys which results in easier slip characteristics. Therefore, the fanning behavior which occurs in aluminum alloys is a function of intrinsic dislocation property of the alloy, and therefore, the fanned data does represent the true threshold properties of the material. However, for the corrosion sensitive steel alloys tested in laboratory air, the occurrence of fanning results from fretting corrosion at the crack tips, and these results should not be considered to be representative of valid threshold properties because the fanning is eliminated when testing is performed in dry air.

Forman, R. G.↗
NASA NTRS1995

A Performance Prediction Model for a Fault-Tolerant Computer During Recovery and Restoration

The modeling and design of a fault-tolerant multiprocessor system is addressed. Of interest is the behavior of the system during recovery and restoration after a fault has occurred. The multiprocessor systems are based on the Algorithm to Architecture Mapping Model (ATAMM) and the fault considered is the death of a processor. The developed model is useful in the determination of performance bounds of the system during recovery and restoration. The performance bounds include time to recover from the fault, time to restore the system, and determination of any permanent delay in the input to output latency after the system has regained steady state. Implementation of an ATAMM based computer was developed for a four-processor generic VHSIC spaceborne computer (GVSC) as the target system. A simulation of the GVSC was also written on the code used in the ATAMM Multicomputer Operating System (AMOS). The simulation is used to verify the new model for tracking the propagation of the delay through the system and predicting the behavior of the transient state of recovery and restoration. The model is shown to accurately predict the transient behavior of an ATAMM based multicomputer during recovery and restoration.

Obando, Rodrigo A.↗
NASA NTRS2014

Crack Growth Behavior in the Threshold Region for High Cycle Fatigue Loading

The research results described in this paper presents a new understanding of the behavior of fatigue crack growth in the threshold region. It is believed by some crack growth experts that the ASTM load shedding test method does not produce true or valid threshold properties. The concern involves the observed fanning of threshold region da/dN data plots for some materials in which the low R-ratio data fans out or away from the high R-ratio data. This data fanning or elevation of threshold values is obviously caused by an increase in crack closure in the low R-ratio tested specimens. This increase in crack closure is assumed by some investigators to be caused by a plastic wake on the crack surfaces that was created during the load shedding test phase. This study shows that the increase in crack closure is the result of an extensive occurrence of crack bifurcation behavior in some materials, particularly in aluminum alloys, when the crack tip cyclic yield zone size becomes less than the grain size of the alloy. This behavior is related to the high stacking fault energy (SFE) property of aluminum alloys which results in easier slip characteristics. Therefore, the particular fanning behavior in aluminum alloys is a function of intrinsic dislocation property of the materials and that the fanned data represents valid material properties. However, for corrosion sensitive steel alloys used in this study the fanning was caused by a build-up of iron oxide at the crack tip from fretting corrosion.

Forman, Royce G.↗
NASA NTRS1991

Model-based diagnostics for Space Station Freedom

An innovative approach to fault management was recently demonstrated for the NASA LeRC Space Station Freedom (SSF) power system testbed. This project capitalized on research in model-based reasoning, which uses knowledge of a system's behavior to monitor its health. The fault management system (FMS) can isolate failures online, or in a post analysis mode, and requires no knowledge of failure symptoms to perform its diagnostics. An in-house tool called MARPLE was used to develop and run the FMS. MARPLE's capabilities are similar to those available from commercial expert system shells, although MARPLE is designed to build model-based as opposed to rule-based systems. These capabilities include functions for capturing behavioral knowledge, a reasoning engine that implements a model-based technique known as constraint suspension, and a tool for quickly generating new user interfaces. The prototype produced by applying MARPLE to SSF not only demonstrated that model-based reasoning is a valuable diagnostic approach, but it also suggested several new applications of MARPLE, including an integration and testing aid, and a complement to state estimation.

Fesq, Lorraine M.↗
NASA NTRS1999

The 13th Technology of Deep Space One

On October 24th, 1998, the Deep Space One (DS-1) spacecraft launched aboard a Delta II rocket as the first step towards the bold task of testing and validating 12 new technologies for future missions. This launch also represented yet another thrilling event; namely, the successful test and validation of a 13th heretofore undisclosed technology: model-base-code-generation of the spacecraft's system-level fault-protection (FP) software from behavioral state diagrams and structural models.

model-based-code-generation↗
NASA NTRSDate not supplied

Enabling in-time Prognostics with Surrogate Modeling through Physics-enhanced Dynamic Mode Decomposition Method

Computational models provide essential quantitative tools for assessing and predicting the health and performance of physical systems. However, high-fidelity models are rarely used in real-time operations or large optimization loops, due to their time-intensive nature. A common approach to improving computational efficiency of prognosis is to employ surrogate models. Such models can significantly decrease computation time for some accuracy loss. In this context, use of Dynamic Mode Decomposition (DMD) is proposed to generate surrogate models for lithium-ion (Li-ion) battery discharge. DMD has been suggested and used successfully in the area of fluid dynamics for over a decade, but it has not been applied to the PHM domain, where far-ahead prediction of nonlinear behavior is crucial to propagate faults or predict Remaining Useful Life (RUL). For Li-ion battery health management, the standard application of DMD using only the observable quantities of interest was unable to capture the nonlinear discharge of batteries exhibited in lab testing. The Koopman theory, however, provides a mechanism to tradeoff low dimensional nonlinear models with high-dimensional linear ones in a DMD framework, by augmenting nonlinear state variables into the system representation. In this way, DMD allows for configurable simulation accuracy dependent on the dimensionality of the Koopman operator. For battery health management, we augmented the observable variables with the hidden states of a higher-fidelity physics model to build the DMD surrogate. In comparison to a high-fidelity model, the surrogate improved computational efficiency with only a minimal loss of accuracy, and enabled long-term prognostics horizons. A generalized method for this was implemented in the prog models python package.

prognostics and health management↗
NASA NTRS1993

Identification and interpretation of patterns in rocket engine data

A prototype software system was constructed to detect anomalous Space Shuttle Main Engine (SSME) behavior in the early stages of fault development significantly earlier than the indication provided by either redline detection mechanism or human expert analysis. The major task of the research project is to analyze ground test data, to identify patterns associated with the anomalous engine behavior, and to develop a pattern identification and detection system on the basis of this analysis. A prototype expert system which was developed on both PC and Symbolics 3670 lisp machine for detecting anomalies in turbopump vibration data was checked with data from ground tests 902-473, 902-501, 902-519, and 904-097 of the Space Shuttle Main Engine. The neural networks method was also applied to supplement the statistical method utilized in the prototype system to investigate the feasibility in detecting anomalies in turbopump vibration of SSME. In most cases the anomalies detected by the expert system agree with those reported by NASA. On the neural networks approach, the results are given the successful detection rate higher than 95 percent to identify either normal or abnormal running condition based on the experimental data as well as numerical simulation.

Lo, C. F.↗
NASA NTRS1973

Theory of reliable systems

The analysis and design of reliable systems are discussed. The attributes of system reliability studied are fault tolerance, diagnosability, and reconfigurability. Objectives of the study include: to determine properties of system structure that are conducive to a particular attribute; to determine methods for obtaining reliable realizations of a given system; and to determine how properties of system behavior relate to the complexity of fault tolerant realizations. A list of 34 references is included.

Meyer, J. F.↗
NASA NTRS1989

Detecting and diagnosing SSME faults using an autoassociative neural network topology

An effort is underway at the University of Tennessee Space Institute to develop diagnostic expert system methodologies based on the analysis of patterns of behavior of physical mechanisms. In this approach, fault diagnosis is conceptualized as the mapping or association of patterns of sensor data to patterns representing fault conditions. Neural networks are being investigated as a means of storing and retrieving fault scenarios. Neural networks offer several powerful features in fault diagnosis, including (1) general pattern matching capabilities, (2) resistance to noisy input data, (3) the ability to be trained by example, and (4) the potential for implementation on parallel computer architectures. This paper presents (1) an autoassociative neural network topology, i.e. the network input and output is identical when properly trained, and hence learning is unsupervised; (2) the training regimen used; and (3) the response of the system to inputs representing both previously observed and unkown fault scenarios. The effects of noise on the integrity of the diagnosis are also evaluated.

Ali, M.↗
NASA NTRS1979

Monitoring and decision making by people in man machine systems

The analysis of human monitoring and decision making behavior as well as its modeling are described. Classic and optimal control theoretical, monitoring models are surveyed. The relationship between attention allocation and eye movements is discussed. As an example of applications, the evaluation of predictor displays by means of the optimal control model is explained. Fault detection involving continuous signals and decision making behavior of a human operator engaged in fault diagnosis during different operation and maintenance situations are illustrated. Computer aided decision making is considered as a queueing problem. It is shown to what extent computer aids can be based on the state of human activity as measured by psychophysiological quantities. Finally, management information systems for different application areas are mentioned. The possibilities of mathematical modeling of human behavior in complex man machine systems are also critically assessed.

Johannsen, G.↗
NASA NTRS1993

Verification of fault-tolerant clock synchronization systems

A critical function in a fault-tolerant computer architecture is the synchronization of the redundant computing elements. The synchronization algorithm must include safeguards to ensure that failed components do not corrupt the behavior of good clocks. Reasoning about fault-tolerant clock synchronization is difficult because of the possibility of subtle interactions involving failed components. Therefore, mechanical proof systems are used to ensure that the verification of the synchronization system is correct. In 1987, Schneider presented a general proof of correctness for several fault-tolerant clock synchronization algorithms. Subsequently, Shankar verified Schneider's proof by using the mechanical proof system EHDM. This proof ensures that any system satisfying its underlying assumptions will provide Byzantine fault-tolerant clock synchronization. The utility of Shankar's mechanization of Schneider's theory for the verification of clock synchronization systems is explored. Some limitations of Shankar's mechanically verified theory were encountered. With minor modifications to the theory, a mechanically checked proof is provided that removes these limitations. The revised theory also allows for proven recovery from transient faults. Use of the revised theory is illustrated with the verification of an abstract design of a clock synchronization system.

Miner, Paul S.↗
NASA NTRS2002

Alternative Metrics for Evaluating the Resilence of Advanced Life Support Systems

Ensuring the safety of the crew is a key performance requirement of a life support system. However, a number of conceptual and practical difficulties arise when devising metrics to concretely measure the ability of a life support system to maintain critical functions in the presence of anticipated and unanticipated faults. Resilience is a dynamic property of a life support system that depends on the complex interactions between faults, controls and system hardware. We review some of the approaches to understanding the robustness or resilience of complex systems being developed in diverse fields such as ecology, software engineering and cell biology and discuss their applicability to regenerative life support systems. We also consider how approaches to measuring resilience vary depending on system design choices such as the definition and choice of the nominal operating regime. Finally, we explore data collection and implementation issues such as the key differences between the instantaneous or conditional and average or overall measures of resilience. Extensive simulation of a hybrid computational model of a water revitalization subsystem (WRS) with probabilistic, component-level faults provides data about off-nominal behavior of the system. The data are used to consider alternative measures of resilience as predictors of the system's ability to recover from component-level faults.

Bell, Ann Maria↗
NASA NTRS2002

Measuring the Resilience of Advanced Life Support Systems

Despite the central importance of crew safety in designing and operating a life support system, the metric commonly used to evaluate alternative Advanced Life Support (ALS) technologies does not currently provide explicit techniques for measuring safety. The resilience of a system, or the system s ability to meet performance requirements and recover from component-level faults, is fundamentally a dynamic property. This paper motivates the use of computer models as a tool to understand and improve system resilience throughout the design process. Extensive simulation of a hybrid computational model of a water revitalization subsystem (WRS) with probabilistic, component-level faults provides data about off-nominal behavior of the system. The data can then be used to test alternative measures of resilience as predictors of the system s ability to recover from component-level faults. A novel approach to measuring system resilience using a Markov chain model of performance data is also developed. Results emphasize that resilience depends on the complex interaction of faults, controls, and system dynamics, rather than on simple fault probabilities.

Bell, Ann Maria↗
NASA NTRS2012

HyDE Framework for Stochastic and Hybrid Model-Based Diagnosis

Hybrid Diagnosis Engine (HyDE) is a general framework for stochastic and hybrid model-based diagnosis that offers flexibility to the diagnosis application designer. The HyDE architecture supports the use of multiple modeling paradigms at the component and system level. Several alternative algorithms are available for the various steps in diagnostic reasoning. This approach is extensible, with support for the addition of new modeling paradigms as well as diagnostic reasoning algorithms for existing or new modeling paradigms. HyDE is a general framework for stochastic hybrid model-based diagnosis of discrete faults; that is, spontaneous changes in operating modes of components. HyDE combines ideas from consistency-based and stochastic approaches to model- based diagnosis using discrete and continuous models to create a flexible and extensible architecture for stochastic and hybrid diagnosis. HyDE supports the use of multiple paradigms and is extensible to support new paradigms. HyDE generates candidate diagnoses and checks them for consistency with the observations. It uses hybrid models built by the users and sensor data from the system to deduce the state of the system over time, including changes in state indicative of faults. At each time step when observations are available, HyDE checks each existing candidate for continued consistency with the new observations. If the candidate is consistent, it continues to remain in the candidate set. If it is not consistent, then the information about the inconsistency is used to generate successor candidates while discarding the candidate that was inconsistent. The models used by HyDE are similar to simulation models. They describe the expected behavior of the system under nominal and fault conditions. The model can be constructed in modular and hierarchical fashion by building component/subsystem models (which may themselves contain component/ subsystem models) and linking them through shared variables/parameters. The component model is expressed as operating modes of the component and conditions for transitions between these various modes. Faults are modeled as transitions whose conditions for transitions are unknown (and have to be inferred through the reasoning process). Finally, the behavior of the components is expressed as a set of variables/ parameters and relations governing the interaction between the variables. The hybrid nature of the systems being modeled is captured by a combination of the above transitional model and behavioral model. Stochasticity is captured as probabilities associated with transitions (indicating the likelihood of that transition being taken), as well as noise on the sensed variables.

Narasimhan, Sriram↗
NASA NTRS1985

Extensional tectonics and collapse structures in the Suez Rift (Egypt)

The Suez Rift is a 300 km long and 50 to 80 km wide basin which cuts a granitic and metamorphic shield of Precambrian age, covered by sediments of Paleozoic to Paleogene age. The rift structure is dominated by tilted blocks bounded by NW-SE normal faults. The reconstruction of the paleostresses indicates a N 050 extension during the whole stage of rifting. Rifting began 24 My ago with dikes intrusions; main faulting and subsidence occurred during Early Miocene producing a 80 km wide basin (Clysmic Gulf). During Pliocene and Quaternary times, faulting is still active but subsidence is restricted to a narrower area (Present Gulf). On the Eastern margin of the gulf, two sets of fault trends are predominant: (1) N 140 to 150 E faults parallel to the gulf trend with pure dip-slip displacement; and (2) cross faults, oriented NOO to N 30 E that have a strike-slip component consistent with the N 050 E distensive stress regime. The mean dip cross fault is steeper (70 to 80 deg) than the dip of the faults parallel to the Gulf (30 to 70 deg). These two sets of fault define diamond shaped tilted block. The difference of mechanical behavior between the basement rocks and the overlying sedimentary cover caused structural disharmony and distinct fault geometries.

Chenet, P. Y.↗
NASA NTRS1988

Accelerated convergence for synchronous approximate agreement

The protocol for synchronous approximate agreement presented by Dolev et. al. exhibits the undesirable property that a faulty processor, by the dissemination of a value arbitrarily far removed from the values held by good processors, may delay the termination of the protocol by an arbitrary amount of time. Such behavior is clearly undesirable in a fault tolerant dynamic system subject to hard real-time constraints. A mechanism is presented by which editing data suspected of being from Byzantine-failed processors can lead to quicker, predictable, convergence to an agreement value. Under specific assumptions about the nature of values transmitted by failed processors relative to those transmitted by good processors, a Monte Carlo simulation is presented whose qualitative results illustrate the trade-off between accelerated convergence and the accuracy of the value agreed upon.

Kearns, J. P.↗
NASA NTRS1993

Identification and interpretation of patterns in rocket engine data

The goal of our research is to analyze ground test data, to identify patterns associated with the anomalous engine behavior. On the basis of this analysis, it is the task of our project to develop a Pattern Identification and Detection System which detects anomalous engine behavior in the early stages of fault development significantly earlier than the indication provided by either redline detection mechanism or human expert analysis. Early detection of these anomalies is challenging because of the large amount of noise presence in the data. In the presence of this noise, early indication of anomalies becomes even more difficult to distinguish from fluctuations in normal steady state operation.

Lo, Ching F.↗