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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Resolving Lonsdaleite's decade-long controversy: Atomistic insights into a metastable diamond polymorph

Lonsdaleite, a theoretically proposed hexagonal diamond polymorph, has remained at the center of a five-decade scientific controversy since its 1967 identification. While some studies claim it exhibits superior hardness through compression-induced structural changes, others contend it is merely a stacking-faulted cubic diamond. Meteoritic samples and synthetic preparations have yielded conflicting evidence, with even advanced characterisation techniques like XRD and TEM failing to provide definitive proof. In this work, we employ first-principles density functional theory (DFT) and molecular dynamics (MD) simulations to generate unambiguous theoretical fingerprints through XRD, Raman, and SAED patterns that distinguish true Lonsdaleite from cubic diamond and its defective variants. Our atomistic approach quantifies the thermodynamic metastability of Lonsdaleite under realistic pressure-temperature conditions, reveals distinct spectral signatures through simulated Raman and resolves the structural ambiguity through generalised stacking fault energy analysis. By establishing clear criteria for definitive identification, this study provides long-awaited clarity to the Lonsdaleite debate while offering a robust computational framework for characterising metastable carbon phases in meteoritic, synthetic and industrial materials.

DFT↗
NASA NTRS1992

Real-time diagnostics for a reusable rocket engine

A hierarchical, decentralized diagnostic system is proposed for the Real-Time Diagnostic System component of the Intelligent Control System (ICS) for reusable rocket engines. The proposed diagnostic system has three layers of information processing: condition monitoring, fault mode detection, and expert system diagnostics. The condition monitoring layer is the first level of signal processing. Here, important features of the sensor data are extracted. These processed data are then used by the higher level fault mode detection layer to do preliminary diagnosis on potential faults at the component level. Because of the closely coupled nature of the rocket engine propulsion system components, it is expected that a given engine condition may trigger more than one fault mode detector. Expert knowledge is needed to resolve the conflicting reports from the various failure mode detectors. This is the function of the diagnostic expert layer. Here, the heuristic nature of this decision process makes it desirable to use an expert system approach. Implementation of the real-time diagnostic system described above requires a wide spectrum of information processing capability. Generally, in the condition monitoring layer, fast data processing is often needed for feature extraction and signal conditioning. This is usually followed by some detection logic to determine the selected faults on the component level. Three different techniques are used to attack different fault detection problems in the NASA LeRC ICS testbed simulation. The first technique employed is the neural network application for real-time sensor validation which includes failure detection, isolation, and accommodation. The second approach demonstrated is the model-based fault diagnosis system using on-line parameter identification. Besides these model based diagnostic schemes, there are still many failure modes which need to be diagnosed by the heuristic expert knowledge. The heuristic expert knowledge is implemented using a real-time expert system tool called G2 by Gensym Corp. Finally, the distributed diagnostic system requires another level of intelligence to oversee the fault mode reports generated by component fault detectors. The decision making at this level can best be done using a rule-based expert system. This level of expert knowledge is also implemented using G2.

Guo, T. H.↗
NASA NTRS1991

A distributed fault-detection and diagnosis system using on-line parameter estimation

The development of a model-based fault-detection and diagnosis system (FDD) is reviewed. The system can be used as an integral part of an intelligent control system. It determines the faults of a system from comparison of the measurements of the system with a priori information represented by the model of the system. The method of modeling a complex system is described and a description of diagnosis models which include process faults is presented. There are three distinct classes of fault modes covered by the system performance model equation: actuator faults, sensor faults, and performance degradation. A system equation for a complete model that describes all three classes of faults is given. The strategy for detecting the fault and estimating the fault parameters using a distributed on-line parameter identification scheme is presented. A two-step approach is proposed. The first step is composed of a group of hypothesis testing modules, (HTM) in parallel processing to test each class of faults. The second step is the fault diagnosis module which checks all the information obtained from the HTM level, isolates the fault, and determines its magnitude. The proposed FDD system was demonstrated by applying it to detect actuator and sensor faults added to a simulation of the Space Shuttle Main Engine. The simulation results show that the proposed FDD system can adequately detect the faults and estimate their magnitudes.

Guo, T.-H.↗
NASA NTRS1975

Analysis of tectonic features in US southwest from Skylab photographs

The author has identified the following significant results. Skylab photographs were utilized to study faults and tectonic lines in selected areas of the U.S. Southwest. Emphasis was on elements of the Texas Zone in the Mojave Desert and the tectonic intersection in southern Nevada. Transverse faults believed to represent the continuation of the Texas Zone were found to be anomalous in strike. This suggests that the Mojave Desert block was rotated counterclockwise as a unit with the Sierra Nevada. Left-lateral strike-slip faults in Lake Mead area are interpreted as elements of the Wasatch tectonic zone; their anomalous trend indicates that the Lake Mead area has rotated clockwise with the Colorado Plateau. A tectonic model relating major fault zones to fragmentation and rotation of crustal blocks was developed. Detailed correlation of the high resolution S190B metric camera photographs with U-2 photographs and geologic maps demonstrates the feasibility of utilizing S190B photographs for the identification of geomorphic features associated with recent and active faults and for the assessment of seismic hazards.

Abdel-Gawad, M.↗
NASA NTRS1987

Physiographic constraints on the origin of lunar wrinkle ridges

Wrinkle ridges are linear asymmetric topographic highs with considerable morphologic complexity that are commonly found on the lunar maria and the smooth plains of Mars and Mercury. The origin of planetary wrinkle ridges has been a much argued and debated topic. Early ideas suggested that wrinkle ridges resulted from volcanic intrusion and extrusion of high viscosity lavas; these early ideas were countered with suggestions that wrinkle ridges formed from tectonic processes involving folding and faulting. Combined volcanic and tectonic mechanisms have also been suggested. The identification and analysis of a number of morphologically similar structures on the earth has helped in the recent interpretation of wrinkle ridges as thrust faults that deform surface rocks. Nevertheless, there remains the uncertainty of the dominant role of thrusting versus folding in the formation of planetary wrinkle ridges. Presented is a detailed physiographic analysis of lunar wrinkle ridges in an effort to help distinguish the dominant deformation mechanism. Results agree with the findings of the earth analog study and support the hypothesis that wrinkle ridges form from thrust faults that deform surface rocks.

Golombek, M. P.↗
NASA NTRS1992

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.↗
NASA NTRS1991

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.↗
NASA NTRS2001

Integrated Neural Flight and Propulsion Control System

This paper describes an integrated neural flight and propulsion control system. which uses a neural network based approach for applying alternate sources of control power in the presence of damage or failures. Under normal operating conditions, the system utilizes conventional flight control surfaces. Neural networks are used to provide consistent handling qualities across flight conditions and for different aircraft configurations. Under damage or failure conditions, the system may utilize unconventional flight control surface allocations, along with integrated propulsion control, when additional control power is necessary for achieving desired flight control performance. In this case, neural networks are used to adapt to changes in aircraft dynamics and control allocation schemes. Of significant importance here is the fact that this system can operate without emergency or backup flight control mode operations. An additional advantage is that this system can utilize, but does not require, fault detection and isolation information or explicit parameter identification. Piloted simulation studies were performed on a commercial transport aircraft simulator. Subjects included both NASA test pilots and commercial airline crews. Results demonstrate the potential for improving handing qualities and significantly increasing survivability rates under various simulated failure conditions.

Kaneshige, John↗
NASA NTRS2005

Performance Analysis on Fault Tolerant Control System

In a fault tolerant control (FTC) system, a parameter varying FTC law is reconfigured based on fault parameters estimated by fault detection and isolation (FDI) modules. FDI modules require some time to detect fault occurrences in aero-vehicle dynamics. In this paper, an FTC analysis framework is provided to calculate the upper bound of an induced-L(sub 2) norm of an FTC system with existence of false identification and detection time delay. The upper bound is written as a function of a fault detection time and exponential decay rates and has been used to determine which FTC law produces less performance degradation (tracking error) due to false identification. The analysis framework is applied for an FTC system of a HiMAT (Highly Maneuverable Aircraft Technology) vehicle. Index Terms fault tolerant control system, linear parameter varying system, HiMAT vehicle.

Shin, Jong-Yeob↗
NASA NTRS2000

Fault Tree Analysis: A Bibliography

Fault tree analysis is a top-down approach to the identification of process hazards. It is as one of the best methods for systematically identifying an graphically displaying the many ways some things can go wrong. This bibliography references 266 documents in the NASA STI Database that contain the major concepts. fault tree analysis, risk an probability theory, in the basic index or major subject terms. An abstract is included with most citations, followed by the applicable subject terms.

Source record↗
NASA NTRS1983

Automation concepts for large space power systems

A study was undertaken to develop a methodology for analyzing, selecting, and implementing automation functions for multi-hundred-kW photovoltaic power systems intended for manned space station. The study involved identification of generic power system elements and their potential faults, definition of automation functions and their resulting benefits, and partitioning of automation functions between power subsystem, central spacecraft computer, and ground. Automation to a varying degree was concluded to be mandatory to meet the design and operational requirements of the space station. The key drivers are indefinite lifetime, modular growth, high performance flexibility, a need to accommodate different electrical user load equipment, on-orbit assembly/maintenance/servicing, and potentially large number of power subsystem components. Functions that are good candidates for automation via expert system approach includes battery management and electrical consumables management.

Imamura, M. S.↗
NASA NTRS1990

Source parameters of earthquakes and intraplate deformation beneath the Shillong Plateau and the northern Indoburman ranges

The fault-plane solutions and focal depths are determined for 17 earthquakes beneath the Shillong Plateau and the northern Indoburman ranges by combining results from the inversion of long-period P and SH waveforms and amplitudes, from polarities of first motions, and from the identification of pP and sP phases on short-period seismograms. Fault-plane solutions of 15 earthquakes show mixtures of thrust and strike-slip faulting, but the P axes for these events are nearly horizontal and consistently oriented N-NE-S-SW. All of these earthquakes occurred at depths greater than 29 km. Beneath the Shillong Plateau, one event occurred at a depth of 52 km. The relatively large depths for earthquakes in an intraplate setting suggest that the Indian lithosphere in this area is especially cold.

Chen, Wang-Ping↗
NASA NTRS1992

Fault diagnosis for the Space Shuttle main engine

A conceptual design of a model-based fault detection and diagnosis system is developed for the Space Shuttle main engine. The design approach consists of process modeling, residual generation, and fault detection and diagnosis. The engine is modeled using a discrete time, quasilinear state-space representation. Model parameters are determined by identification. Residuals generated from the model are used by a neural network to detect and diagnose engine component faults. Fault diagnosis is accomplished by training the neural network to recognize the pattern of the respective fault signatures. Preliminary results for a failed valve, generated using a full, nonlinear simulation of the engine, are presented. These results indicate that the developed approach can be used for fault detection and diagnosis. The results also show that the developed model is an accurate and reliable predictor of the highly nonlinear and very complex engine.

Duyar, Ahmet↗
NASA NTRS2000

Multi-Agent Diagnosis and Control of an Air Revitalization System for Life Support in Space

An architecture of interoperating agents has been developed to provide control and fault management for advanced life support systems in space. In this adjustable autonomy architecture, software agents coordinate with human agents and provide support in novel fault management situations. This architecture combines the Livingstone model-based mode identification and reconfiguration (MIR) system with the 3T architecture for autonomous flexible command and control. The MIR software agent performs model-based state identification and diagnosis. MIR identifies novel recovery configurations and the set of commands required for the recovery. The AZT procedural executive and the human operator use the diagnoses and recovery recommendations, and provide command sequencing. User interface extensions have been developed to support human monitoring of both AZT and MIR data and activities. This architecture has been demonstrated performing control and fault management for an oxygen production system for air revitalization in space. The software operates in a dynamic simulation testbed.

Malin, Jane T.↗
NASA NTRS1990

Object-oriented fault tree models applied to system diagnosis

When a diagnosis system is used in a dynamic environment, such as the distributed computer system planned for use on Space Station Freedom, it must execute quickly and its knowledge base must be easily updated. Representing system knowledge as object-oriented augmented fault trees provides both features. The diagnosis system described here is based on the failure cause identification process of the diagnostic system described by Narayanan and Viswanadham. Their system has been enhanced in this implementation by replacing the knowledge base of if-then rules with an object-oriented fault tree representation. This allows the system to perform its task much faster and facilitates dynamic updating of the knowledge base in a changing diagnosis environment. Accessing the information contained in the objects is more efficient than performing a lookup operation on an indexed rule base. Additionally, the object-oriented fault trees can be easily updated to represent current system status. This paper describes the fault tree representation, the diagnosis algorithm extensions, and an example application of this system. Comparisons are made between the object-oriented fault tree knowledge structure solution and one implementation of a rule-based solution. Plans for future work on this system are also discussed.

Iverson, David L.↗
NASA NTRS1989

SSME fault monitoring and diagnosis expert system

An expert system, called LEADER, has been designed and implemented for automatic learning, detection, identification, verification, and correction of anomalous propulsion system operations in real time. LEADER employs a set of sensors to monitor engine component performance and to detect, identify, and validate abnormalities with respect to varying engine dynamics and behavior. Two diagnostic approaches are adopted in the architecture of LEADER. In the first approach fault diagnosis is performed through learning and identifying engine behavior patterns. LEADER, utilizing this approach, generates few hypotheses about the possible abnormalities. These hypotheses are then validated based on the SSME design and functional knowledge. The second approach directs the processing of engine sensory data and performs reasoning based on the SSME design, functional knowledge, and the deep-level knowledge, i.e., the first principles (physics and mechanics) of SSME subsystems and components. This paper describes LEADER's architecture which integrates a design based reasoning approach with neural network-based fault pattern matching techniques. The fault diagnosis results obtained through the analyses of SSME ground test data are presented and discussed.

Ali, Moonis↗