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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

The width of fault zones in a brittle-viscous lithosphere: Strike-slip faults

A fault zone in an ideal brittle material overlying a very weak substrate could, in principle, consist of a single slip surface. Real fault zones have a finite width consisting of a number of nearly parallel slip surfaces on which deformation is distributed. The hypothesis that the finite width of fault zones reflects stresses due to quasistatic flow in the ductile substrate of a brittle surface layer is explored. Because of the simplicity of theory and observations, strike-slip faults are examined first, but the analysis can be extended to normal and thrust faulting.

Parmentier, E. M.↗

Implementation of a model based fault detection and diagnosis for actuation faults of the Space Shuttle main engine

In a previous study, Guo, Merrill and Duyar, 1990, reported a conceptual development of a fault detection and diagnosis system for actuation faults of the space shuttle main engine. This study, which is a continuation of the previous work, implements the developed fault detection and diagnosis scheme for the real time actuation fault diagnosis of the space shuttle main engine. The scheme will be used as an integral part of an intelligent control system demonstration experiment at NASA Lewis. The diagnosis system utilizes a model based method with real time identification and hypothesis testing for actuation, sensor, and performance degradation faults.

Duyar, A.↗

Fault detection and fault tolerance in robotics

Robots are used in inaccessible or hazardous environments in order to alleviate some of the time, cost and risk involved in preparing men to endure these conditions. In order to perform their expected tasks, the robots are often quite complex, thus increasing their potential for failures. If men must be sent into these environments to repair each component failure in the robot, the advantages of using the robot are quickly lost. Fault tolerant robots are needed which can effectively cope with failures and continue their tasks until repairs can be realistically scheduled. Before fault tolerant capabilities can be created, methods of detecting and pinpointing failures must be perfected. This paper develops a basic fault tree analysis of a robot in order to obtain a better understanding of where failures can occur and how they contribute to other failures in the robot. The resulting failure flow chart can also be used to analyze the resiliency of the robot in the presence of specific faults. By simulating robot failures and fault detection schemes, the problems involved in detecting failures for robots are explored in more depth.

Visinsky, Monica↗

Implementation of a model based fault detection and diagnosis technique for actuation faults of the SSME

In a previous study, Guo, Merrill and Duyar, 1990, reported a conceptual development of a fault detection and diagnosis system for actuation faults of the Space Shuttle main engine. This study, which is a continuation of the previous work, implements the developed fault detection and diagnosis scheme for the real time actuation fault diagnosis of the Space Shuttle Main Engine. The scheme will be used as an integral part of an intelligent control system demonstration experiment at NASA Lewis. The diagnosis system utilizes a model based method with real time identification and hypothesis testing for actuation, sensor, and performance degradation faults.

Duyar, A.↗

Implementation and test of an automated control hunting fault correction algorithm in a fault detection and diagnostics tool

Control hunting due to improper proportional–integral–derivative (PID) parameters in the building automation system (BAS) is one of the most common faults identified in commercial buildings. It can cause suboptimal performance and early failure of heating, ventilation, and air conditioning (HVAC) equipment. Commercial fault detection and diagnostics (FDD) software represents one of the fastest growing market segments in smart building technologies in the United States. Implementation of PID retuning procedures as an auto-correction algorithm and integration into FDD software has the potential to mitigate control hunting across a heterogeneous portfolio of buildings with different BAS in a scalable way. This paper presents the development, implementation, and field testing of an automated control hunting fault correction algorithm based on lambda tuning open-loop rules. The algorithm was developed in a commercial FDD software and successfully tested among nine variable air volume boxes in an office building in the United States. The paper shows the feasibility of using FDD tools to automatically correct control hunting faults, discusses scalability considerations, and proposes a path forward for the HVAC industry and academia to further improve this technology.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Fault Injection Campaign for a Fault Tolerant Duplex Framework

Fault tolerance is an efficient approach adopted to avoid or reduce the damage of a system failure. In this work we present the results of a fault injection campaign we conducted on the Duplex Framework (DF). The DF is a software developed by the UCLA group [1, 2] that uses a fault tolerant approach and allows to run two replicas of the same process on two different nodes of a commercial off-the-shelf (COTS) computer cluster. A third process running on a different node, constantly monitors the results computed by the two replicas, and eventually restarts the two replica processes if an inconsistency in their computation is detected. This approach is very cost efficient and can be adopted to control processes on spacecrafts where the fault rate produced by cosmic rays is not very high.

fault injector↗

Line Faults Classification Using Machine Learning on Three Phase Voltages Extracted from Large Dataset of PMU Measurements

An end-to-end supervised learning method is developed to classify transmission line faults in a twoyear field-recorded dataset that includes synchronized measurements of three-phase voltages recorded by 38 Phasor Measurement Units (PMU) sparsely located in in the US Western Grid interconnection. Statistical analysis is performed to extract features from this large dataset to train Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) classifiers initially. The training further leverages a simulated dataset from a synthetic grid with 12 PMUs to increase the number of faults of types infrequently seen in the field-recorded dataset. Training the classification models with the combined dataset resulted in a classification accuracy of 97.7%. This is a significant improvement over 89.7% to 92.5% accuracy obtained by relying on the field-recorded dataset alone.

47 OTHER INSTRUMENTATION↗

Fault tolerant filtering and fault detection for quantum systems driven by fields in single photon states

The purpose of this paper is to solve the fault tolerant filtering and fault detection problem for a class of open quantum systems driven by a continuous-mode bosonic input field in single photon states when the systems are subject to stochastic faults. Optimal estimates of both the system observables and the fault process are simultaneously calculated and characterized by a set of coupled recursive quantum stochastic differential equations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A cosine-based correlation information entropy approach for building automatic fault detection baseline construction

Building automatic fault detection and diagnosis (AFDD) technologies have shown great potential for energy savings. To enable AFDD, a baseline depicting the normal operation mode is needed to detect whether the building operation deviates from normality. Existing research using physics-based knowledge and models for AFDD has mainly taken a trial-and-error approach to determine if a given baseline is sufficient via empirical experiments. A mechanism to support decisions such as how many samples and what samples should be included in the baseline is currently lacking. In this study, a data-driven method for AFDD baseline construction based on information entropy is developed. The entropy is derived based on cosine similarity among typical building automation system measurements in conjunction with outdoor weather information. The performance of the proposed method is evaluated using real building data. Evaluation results indicate that the fault detection strategy adopting the proposed method has similar or better accuracy in detecting faults compared to the same fault detection strategy using the baseline construction method from the literature. Additionally, the use of entropy enables the proposed method to automatically construct and assess the baseline consisting of information-rich samples.

42 ENGINEERING↗

Lunar Mascon Loading: an Example of the Importance of Fault Initiation Depth on Fault Type Predictions from Stresses on Planetary Surfaces

Geophysical models that predict fault type from stresses calculated at the planetary surface (zero depth) can be misleading because faults generally initiate at depth under a different stress regime and propagate to the surface. The generally accepted and most commonly employed criteria for fault prediction from calculated stresses on planetary surfaces points out problems in neglecting the effects of non-isotropic overburden stresses and the use of realistic material constants and shows a well known example (mascon loading on the moon) where neglecting this effect predicts a different type of fault than is actually observed.

Golombek, M. P.↗

A nonlinear least-squares inverse analysis of strike-slip faulting with application to the San Andreas fault

A nonlinear weighted least-squares analysis was performed for a synthetic elastic layer over a viscoelastic half-space model of strike-slip faulting. Also, an inversion of strain rate data was attempted for the locked portions of the San Andreas fault in California. Based on an eigenvector analysis of synthetic data, it is found that the only parameter which can be resolved is the average shear modulus of the elastic layer and viscoelastic half-space. The other parameters were obtained by performing a suite of inversions for the fault. The inversions on data from the northern San Andreas resulted in predicted parameter ranges similar to those produced by inversions on data from the whole fault.

Williams, Charles A.↗

Dynamic characteristics of a 20 kHz resonant power system - Fault identification and fault recovery

A detailed simulation of a dc inductor resonant driver and receiver is used to demonstrate the transient characteristics of a 20 kHz resonant power system during fault and overload conditions. The simulated system consists of a dc inductor resonant inverter (driver), a 50-meter transmission cable, and a dc inductor resonant receiver load. Of particular interest are the driver and receiver performance during fault and overload conditions and on the recovery characteristics following removal of the fault. The information gained from these studies sets the stage for further work in fault identification and autonomous power system control.

Wasynczuk, O.↗

The morphology of strike-slip faults - Examples from the San Andreas Fault, California

The dilatational strains associated with vertical faults embedded in a horizontal plate are examined in the framework of fault kinematics and simple displacement boundary conditions. Using boundary element methods, a sequence of examples of dilatational strain fields associated with commonly occurring strike-slip fault zone features (bends, offsets, finite rupture lengths, and nonuniform slip distributions) is derived. The combinations of these strain fields are then used to examine the Parkfield region of the San Andreas fault system in central California.

Bilham, Roger↗

Simulated fault injection - A methodology to evaluate fault tolerant microprocessor architectures

A simulation-based fault-injection method for validating fault-tolerant microprocessor architectures is described. The approach uses mixed-mode simulation (electrical/logic analysis), and injects transient errors in run-time to assess the resulting fault impact. As an example, a fault-tolerant architecture which models the digital aspects of a dual-channel real-time jet-engine controller is used. The level of effectiveness of the dual configuration with respect to single and multiple transients is measured. The results indicate 100 percent coverage of single transients. Approximately 12 percent of the multiple transients affect both channels; none result in controller failure since two additional levels of redundancy exist.

Choi, Gwan S.↗

Managing systems faults on the commercial flight deck: Analysis of pilots' organization and prioritization of fault management information

In rare instances, flight crews of commercial aircraft must manage complex systems faults in addition to all their normal flight tasks. Pilot errors in fault management have been attributed, at least in part, to an incomplete or inaccurate awareness of the fault situation. The current study is part of a program aimed at assuring that the types of information potentially available from an intelligent fault management aiding concept developed at NASA Langley called 'Faultfinde' (see Abbott, Schutte, Palmer, and Ricks, 1987) are an asset rather than a liability: additional information should improve pilot performance and aircraft safety, but it should not confuse, distract, overload, mislead, or generally exacerbate already difficult circumstances.

Rogers, William H.↗

Fault Injection and Monitoring Capability for a Fault-Tolerant Distributed Computation System

The Configurable Fault-Injection and Monitoring System (CFIMS) is intended for the experimental characterization of effects caused by a variety of adverse conditions on a distributed computation system running flight control applications. A product of research collaboration between NASA Langley Research Center and Old Dominion University, the CFIMS is the main research tool for generating actual fault response data with which to develop and validate analytical performance models and design methodologies for the mitigation of fault effects in distributed flight control systems. Rather than a fixed design solution, the CFIMS is a flexible system that enables the systematic exploration of the problem space and can be adapted to meet the evolving needs of the research. The CFIMS has the capabilities of system-under-test (SUT) functional stimulus generation, fault injection and state monitoring, all of which are supported by a configuration capability for setting up the system as desired for a particular experiment. This report summarizes the work accomplished so far in the development of the CFIMS concept and documents the first design realization.

Torres-Pomales, Wilfredo↗