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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 253 records · Page 14

All sources NASA NTRS DOE OSTI

NASA NTRS1989

Logistics resupply and emergency crew return system for Space Station Freedom

Sometime in the late 1990's, if all goes according to plan, Space Station Freedom will allow the United States and its cooperating partners to maintain a permanent presence in space. Acting as a scientific base of operations, it will also serve as a way station for future explorations of the Moon and perhaps even Mars. Systems onboard the station will have longer lifetimes, higher reliability, and lower maintenance requirements than seen on any previous space flight vehicle. Accordingly, the station will have to be resupplied with consumables (air, water, food, etc.) and other equipment changeouts (experiments, etc.) on a periodic basis. Waste materials and other products will also be removed from the station for return to Earth. The availability of a Logistics Resupply Module (LRM), akin to the Soviet's Progress vehicle, would help to accomplish these tasks. Riding into orbit on an expendable launch vehicle, the LRM would be configured to rendezvous autonomously and dock with the space station. After the module is emptied of its cargo, waste material from the space station would be loaded back into it. The module would then begin its descent to a recovery point on Earth. Logistics Resupply Modules could be configured in a variety of forms depending on the type of cargo being transferred. If the LRM's were cycled to the space station in such a way that at least one vehicle remained parked at the station at all times, the modules could serve double duty as crew emergency return capsules. A pressurized LRM could then bring two or more crew-persons requiring immediate return (because of health problems, system failure, or unavoidable catastrophes) back to Earth. Large cost savings would be accrued by combining the crew return function with a logistics resupply system.

Ahne, D.↗

NASA NTRS2012

The HAL 9000 Space Operating System Real-Time Planning Engine Design and Operations Requirements

In support of future deep space manned missions, an autonomous/automated vehicle, providing crew autonomy and an autonomous response planning system, will be required due to the light time delays in communication. Vehicle capabilities as a whole must provide for tactical response to vehicle system failures and space environmental effects induced failures, for risk mitigation of permanent loss of communication with Earth, and for assured crew return capabilities. The complexity of human rated space systems and the limited crew sizes and crew skills mix drive the need for a robust autonomous capability on-board the vehicle. The HAL 9000 Space Operating System[2] designed for such missions and space craft includes the first distributed real-time planning / re-planning system. This paper will detail the software architecture of the multiple planning engine system, and the interface design for plan changes, approval and implementation that is performed autonomously. Operations scenarios will be defined for analysis of the planning engines operations and its requirements for nominal / off nominal activities. An assessment of the distributed realtime re-planning system, in the defined operations environment, will be provided as well as findings as it pertains to the vehicle, crew, and mission control requirements needed for implementation.

Stetson, Howard↗

NASA NTRS1998

Accommodating Actuator Failures in Flight Control Systems

A technique for the design of flight control systems that can accommodate a set of actuator failures is presented. As employed herein, an actuator failure is defined as any change in the parametric model of the actuator which can adversely affect actuator performance. The technique is based upon the formulation of a fixed feedback topology which ensures at least stability in the presence of the failures in the set. The fixed compensation is obtained from a loop-shaping design procedure similar to Quantitative Feedback Theory and provides stability robustness in the presence of uncertainty in the vehicle dynamics caused by the failures. System adaptation to improve performance after actuator failure(s) occurs through a static gain adjustment in the compensator followed by modification of the system prefilter. Precise identification of the vehicle dynamics is unnecessary. Application to a single-input, single-output design using a simplified model of the longitudinal dynamics of the NASA High Angle of Attack Research Vehicle is discussed. Non-real time simulations of the system including a model of the pilot demonstrate the effectiveness and limitations of the approach.

Hess, R. A.↗

NASA NTRS1993

Hidden Markov models for fault detection in dynamic systems

The invention is a system failure monitoring method and apparatus which learns the symptom-fault mapping directly from training data. The invention first estimates the state of the system at discrete intervals in time. A feature vector x of dimension k is estimated from sets of successive windows of sensor data. A pattern recognition component then models the instantaneous estimate of the posterior class probability given the features, p(w(sub i) perpendicular to x), 1 less than or equal to i is less than or equal to m. Finally, a hidden Markov model is used to take advantage of temporal context and estimate class probabilities conditioned on recent past history. In this hierarchical pattern of information flow, the time series data is transformed and mapped into a categorical representation (the fault classes) and integrated over time to enable robust decision-making.

Smyth, Padhraic J.↗

NASA NTRS1995

Hidden Markov models for fault detection in dynamic systems

The invention is a system failure monitoring method and apparatus which learns the symptom-fault mapping directly from training data. The invention first estimates the state of the system at discrete intervals in time. A feature vector x of dimension k is estimated from sets of successive windows of sensor data. A pattern recognition component then models the instantaneous estimate of the posterior class probability given the features, p(w(sub i) (vertical bar)/x), 1 less than or equal to i isless than or equal to m. Finally, a hidden Markov model is used to take advantage of temporal context and estimate class probabilities conditioned on recent past history. In this hierarchical pattern of information flow, the time series data is transformed and mapped into a categorical representation (the fault classes) and integrated over time to enable robust decision-making.

Smyth, Padhraic J.↗

NASA NTRS2017

Emergency Locator Transmitter Survivability and Reliability Study

A comprehensive study of Emergency Locator Transmitter (ELT) performance was conducted over a three year period concluding in 2016 in support of the Search and Rescue (SAR) Mission Office at National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC). The study began with a review of reported performance cited in a collection of works published as early as 1980 as well as analysis of a focused set of contemporary aviation crash reports. Based on initial research findings, a series of subscale and fullscale system tests were performed at NASA Langley Research Center (LaRC) with the goals of investigating ELT system failure modes and developing recommended improvements to the Radio Technical Commission for Aeronautics (RTCA) Minimum Operational Performance Specification (MOPS) that will result in improved system performance. Enhanced performance of ELT systems in aviation accidents will reduce unnecessary loss of human life and make SAR operations safer and less costly by reducing the amount of time required to locate accident sites.

Stimson, Chad M.↗

NASA NTRS2018

Evaluating Expected Performance and Graceful Degradation in Distributed Spacecraft Missions

Distributed Spacecraft Missions (DSMs) have largely garnered interest due to lower cost and new technical capabilities. However, another important attribute in DSMs is the potential of graceful degradation where a failure of one or more spacecraft (or instruments) in the DSM can reduce total performance, but the remaining functional spacecraft can maintain a limited science return. The potential for retaining some mission value in the event of partial failures leads to enhanced lifetime value. Here, an approach is developed to analyze graceful degradation and performance of DSM used for Earth observation. The system performance is defined through metrics of coverage and average revisit time of points of interest. Graceful degradation is quantified through total change and rate of change in performance metrics with increasing sub-system failures over the lifetime of a mission. An Expected Performance measure is formulated for conducting comparison of DSM architectures for early stage conceptual mission design and trade studies.

Distributed Spacecraft Missions↗

NASA NTRS2018

Evaluating Expected Performance and Graceful Degradation in Distributed Spacecraft Missions

Distributed Spacecraft Missions; constellations; p↗

DOE OSTI2025

Using a Large Language Model for Accurate Technical Language Generation in the Predictive Maintenance of Circulating Water Systems in Nuclear Power Plants

Machine learning (ML) methods for predictive maintenance (PdM) are emerging as effective proactive strategies for diagnosing equipment degradation and enabling effective decision-making. However, explainability and trustworthiness of artificial intelligence are two salient challenges that need to be addressed for wider deployment of these technologies in nuclear power plants (NPPs). Large language models (LLMs) offer a unique approach to tackle these challenges by explaining PdM, work orders, diagnosis results, and ML algorithms to users, who may not be familiar with ML and PdM in general. Moreover, by dynamically retrieving relevant information from technical documents and evaluating factuality of LLM generation, the accuracy and relevance of LLM generations can be improved. This work demonstrates using LLMs to explain the causes and consequences of circulating water system failures based on multiyear NPP work orders. This work tests the capability of multimodal LLM approaches in explaining the differences in the circulating water system from both the Salem and Hope Creek NPPs using both text and image resources. This work also demonstrates the use of multimodal LLMs in describing the diagnosis tab of a predictive maintenance software named VIsualization for PrEdictive maintenance Recommendation (VIPER) to users.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1990

Rocket engine failure detection using system identification techiques

The theoretical foundation and application of two univariate failure detection algorithms to Space Shuttle Main Engine (SSME) test firing data is presented. Both algorithms were applied to data collected during steady state operation of the engine. One algorithm, the time series algorithm, is based on time series techniques and involves the computation of autoregressive models. Times series techniques have been previously applied to SSME data. The second algorithm is based on standard signal processing techniques. It consists of tracking the variations in the average signal power with time. The average signal power algorithm is a newly proposed SSME failure detection algorithm. Seven nominal test firings were used to develop failure indication thresholds for each algorithm. These thresholds were tested using four anomalous firings and one additional nominal firing. Both algorithms provided significantly earlier failure indication times than did the current redline limit system. Neither algorithm gave false failure indications for the nominal firing. The strengths and weaknesses of the two algorithms are discussed and compared. The average signal algorithm was found to have several advantages over the time series algorithm.

Meyer, Claudia M.↗

NASA NTRS1990

Rocket engine failure detection using system identification techniques

The theoretical foundation and application of two univariate failure detection algorithms to Space Shuttle Main Engine (SSME) test firing data is presented. Both algorithms were applied to data collected during steady state operation of the engine. One algorithm, the time series algorithm, is based on time series techniques and involves the computation of autoregressive models. Time series techniques have been previously applied to SSME data. The second algorithm is based on standard signal processing techniques. It consists of tracking the variations in the average signal power with time. The average signal power algorithm is a newly proposed SSME failure detection algorithm. Seven nominal test firings were used to develop failure indication thresholds for each algorithm. These thresholds were tested using four anomalous firings and one additional nominal firing. Both algorithms provided significantly earlier failure indication times than did the current redline limit system. Neither algorithm gave false failure indications for the nominal firing. The strengths and weaknesses of the two algorithms are discussed and compared. The average signal algorithm was found to have several advantages over the time series algorithm.

Meyer, Claudia M.↗

NASA NTRS2009

Lunar Surface Operations: Post-Touchdown Lunar Surface and System Checkouts - Part 1

This slide presentation reviews the first part of the post-touchdown lunar surface and system checkout tasks. A stay/no stay decision for the lunar lander was made based on the questions: "Is the Lunar Module (LM) stable on the lunar surface?"; "Are there any time critical systems failures or trends indicating impending loss of capability to ascent and achieve a safe lunar orbit?"; and "Is there loss of capability in critical LM systems?" The sequence of these decisions is given as a time after touchdown on the surface of the moon. After the decision to stay is made the next task is to checkout status of the lunar module. While the status of the lunar module is checking out certain conditions, the Command Service Module was also engaged in certain checkout activities.

Interbartolo, Michael↗

NASA NTRS2020

Application of Sparse Identification of Nonlinear Dynamics for Physics-Informed Learning

Advances in machine learning and deep neural networks has enabled complex engineering tasks like image recognition, anomaly detection, regression, and multi-objective optimization, to name but a few. The complexity of the algorithm architecture, e.g., the number of hidden layers in a deep neural network, typically grows with the complexity of the problems they are required to solve, leaving little room for interpreting (or explaining) the path that results in a specific solution. This drawback is particularly relevant for autonomous aerospace and aviation systems, where certifications require a complete understanding of the algorithm behavior in all possible scenarios. Including physics knowledge in such data-driven tools may improve the interpretability of the algorithms, thus enhancing model validation against events with low probability but relevant for system certification. Such events include, for example, spacecraft or aircraft sub-system failures, for which data may not be available in the training phase. This paper investigates a recent physics-informed learning algorithm for identification of system dynamics, and shows how the governing equations of a system can be extracted from data using sparse regression. The learned relationships can be utilized as a surrogate model which, unlike typical data-driven surrogate models, relies on the learned underlying dynamics of the system rather than large number of fitting parameters. The work shows that the algorithm can reconstruct the differential equations underlying the observed dynamics using a single trajectory when no uncertainty is involved. However, the training set size must increase when dealing with stochastic systems, e.g., nonlinear dynamics with random initial conditions.

Corbetta, Matteo↗

NASA NTRS1992

Shear failure and impact resistance in graphite fiber laminates

The multispan beam (MSB) test was evaluated as a predictor of damage resistance and damage tolerance in quasi-isotropic graphite laminates. Materials studied were five commercial prepreg system using high-strain and intermediate-modulus carbon fibers, as well as an amorphous thermoplastic system. Failure loads and displacements in the MSB tests showed little rate dependence. Values of compressive strength after a standard low-velocity impact correlated fairly well with the MSB results.

Srinivasan, Krishna↗

NASA NTRS1988

Threshold computations for detection of failures in SISO systems with transfer function errors

The author considers the problem of detecting failures in SISO systems using analytic redundancy concepts. Since the models used are subject to error, a method of determining the detection thresholds that account for these errors is sought. The methodology presented utilizes a straightforward application of Parseval's relation to develop a threshold computation that is performed online as a function of the input signal. The threshold is set at a quiescent value to account for sensor noise and is adjusted (upward) according to the activity of the input signal. An application to detection of actuator failures is presented.

Weiss, Jerold L.↗

NASA NTRS2003

Fault Tree Analysis Application for Safety and Reliability

Many commercial software tools exist for fault tree analysis (FTA), an accepted method for mitigating risk in systems. The method embedded in the tools identifies a root as use in system components, but when software is identified as a root cause, it does not build trees into the software component. No commercial software tools have been built specifically for development and analysis of software fault trees. Research indicates that the methods of FTA could be applied to software, but the method is not practical without automated tool support. With appropriate automated tool support, software fault tree analysis (SFTA) may be a practical technique for identifying the underlying cause of software faults that may lead to critical system failures. We strive to demonstrate that existing commercial tools for FTA can be adapted for use with SFTA, and that applied to a safety-critical system, SFTA can be used to identify serious potential problems long before integrator and system testing.

Wallace, Dolores R.↗

NASA NTRS2015

Service Life Extension of the ISS Propulsion System Elements

The International Space Station (ISS) is a result of international collaboration in building a sophisticated laboratory of an unprecedented scale in Low Earth Orbit. After a complex assembly sequence spanning over a decade, some of the early modules launched at the beginning of the program would reach the end of their certified lives, while the newer modules were just being commissioned into operation. To maximize the return on global investments in this one-of-a-kind orbiting platform that was initially conceived for a service life until 2016, it is essential for the cutting edge research on ISS to continue as long as the station can be sustained safely in orbit. ISS Program is assessing individual modules in detail to extend the service life of the ISS to 2024, and possibly to 2028. Without life extension, Functional Cargo Block (known by its Russian acronym as FGB) and the Service Module (SM), two of the early modules on the Russian Segment, would reach the end of their certified lives in 2013 and 2015 respectively. Both FGB and SM are critical for the propulsive function of the ISS. This paper describes the approach used for the service life extension of the FGB propulsion system. Also presented is an overview of the system description along with the process adopted for developing the life test plans based on considerations of system failure modes, fault tolerance and safety provisions. Tests and analyses performed, important findings and life estimates are summarized. Based on the life extension data, FGB propulsion system, in general, is considered ready for a service life until 2028.

Kamath, Ulhas↗

NASA NTRS1990

Analysis of field data on computer failures

This paper emphasizes the importance of making field measurements for effective and realistic dependability evaluations. Two examples are given, both based on real data from IBM mainframes. The first evaluates the impact of the operating environment on system failure characteristics and the second shows how an accurate model depicting this interaction can be extracted from real data.

Iyer, Ravishankar K.↗