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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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NASA NTRS1990

Reliable and Efficient Parallel Processing Algorithms and Architectures for Modern Signal Processing

Least-squares (LS) estimations and spectral decomposition algorithms constitute the heart of modern signal processing and communication problems. Implementations of recursive LS and spectral decomposition algorithms onto parallel processing architectures such as systolic arrays with efficient fault-tolerant schemes are the major concerns of this dissertation. There are four major results in this dissertation. First, we propose the systolic block Householder transformation with application to the recursive least-squares minimization. It is successfully implemented on a systolic array with a two-level pipelined implementation at the vector level as well as at the word level. Second, a real-time algorithm-based concurrent error detection scheme based on the residual method is proposed for the QRD RLS systolic array. The fault diagnosis, order degraded reconfiguration, and performance analysis are also considered. Third, the dynamic range, stability, error detection capability under finite-precision implementation, order degraded performance, and residual estimation under faulty situations for the QRD RLS systolic array are studied in details. Finally, we propose the use of multi-phase systolic algorithms for spectral decomposition based on the QR algorithm. Two systolic architectures, one based on triangular array and another based on rectangular array, are presented for the multiphase operations with fault-tolerant considerations. Eigenvectors and singular vectors can be easily obtained by using the multi-pase operations. Performance issues are also considered.

Liu, Kuojuey Ray↗

NASA NTRS2005

Response to MRO's end-to-end data accountability challenges

(MRO) on August 12, 2005. It carries six science instruments and three engineering payloads. Because MRO will produce an unprecedented number of science products, it will transmit a much higher data volume via high data rate than any other deep space mission to date. Keeping track of MRO products as well as relay products would be a daunting, expensive task without a well-planned data-product tracking strategy. To respond to this challenge, the MRO project developed the End-to- End Data Accountability System by utilizing existing information available from both ground and flight elements. Therefore, a capability to perform first-order problem diagnosis is essential in order for MRO to answer the questions, where is my data? and when will my data be available? This paper details the approaches taken, design and implementation of the tools, procedures and teams that track data products from the time they are predicted until they arrive in the hands of the end users.

data delivery status tracking↗

NASA NTRS2001

Particle Filters for Real-Time Fault Detection in Planetary Rovers

Planetary rovers provide a considerable challenge for robotic systems in that they must operate for long periods autonomously, or with relatively little intervention. To achieve this, they need to have on-board fault detection and diagnosis capabilities in order to determine the actual state of the vehicle, and decide what actions are safe to perform. Traditional model-based diagnosis techniques are not suitable for rovers due to the tight coupling between the vehicle's performance and its environment. Hybrid diagnosis using particle filters is presented as an alternative, and its strengths and weakeners are examined. We also present some extensions to particle filters that are designed to make them more suitable for use in diagnosis problems.

Dearden, Richard↗

NASA NTRS2015

Transformational Phenomena as Predictors of Aircraft Accidents: What Goes Around Comes Around

Flight crew confusion, excessive stressworkload, and ineffective Crew Resource Management among other issues arising from dependence on automated systems on the flight deck have been identified as major causal factors in multiple fatal accidents, significant incidents and near misses. Many Loss of Control events have been traced to display of erroneous flight data and auto-flight system mode status to the crew. Safety was compromised by not having sufficiently obvious and unambiguous information available in order to permit quick diagnosis of aircraft status and then appropriate action to regain control of the aircraft energy state or trajectory. Continually evolving training and operational requirements related to aircraft automation have also presented critical challenges to commercial aviation. During times of high demand and low supply of experienced pilots (which is today the case in South-East Asia, for instance), basic training in manual flight may be minimal and as low as a few hundred flight hours on light aircraft before beginning training on advanced, highly automated aircraft. Predominant use of automation may cause aircrew trained in this way to have trouble performing traditionally simple operations such as manually switching to other runways or overriding the autopilot in tight situations. Inadequate crew training andor experience coupled with attempted manual flight in highly automated airplanes may more easily lead to loss of aircraft control in unusual situations such as high-altitude stallsupsets, traffic avoidance or maneuvering. Loss of basic piloting skills through increasing dependence on automation may exacerbate this problem. Finally, design changes by nature take a long time and are very costly. Incorporating novel automated functionality into new aircraft designs is technically feasible and desirable. However, it may take many years for these changes to have a significant impact on tomorrows fleet, given the time it takes to develop a new aircraft and for these aircraft to become a significant fraction of the fleet. This paper will review and summarize the findings and recommendations from a 2004 study of the topic, Increasing reliance on flight deck automation conducted by the Future Aviation Safety Team at the behest of the Joint Safety Strategy Initiative (JSSI) within the Joint Aviation Authorities (JAA) organization that existed at the time. Although this study was conducted more than ten years ago, its findings and recommendations are as relevant now as then and into the future.

safety↗

NASA NTRS2014

Integrated Diagnostics and Prognostics for the Electrical Power System of a Planetary Rover

For electric vehicles, technology for monitoring, diagnosis, and prognosis of the electrical power system (EPS) becomes essential for safe and efficient operation. To this end, we develop a general system-level integrated diagnosis and prognosis framework, which detects, isolates, and identifies EPS faults, and predicts when the EPS will fail to deliver sufficient power. The approach takes advantage of recent work in structural model decomposition in order to distribute the global diagnosis and prognosis problems into local subproblems that can be solved in parallel, thus enabling implementation on distributed computational platforms. The framework is applied to the EPS of a planetary rover testbed, and is demonstrated using data from field experiments.

Daigle, Matthew↗

NASA NTRS2009

Climate-Related Trends, Human Induced Trends, and False-Trends in Seven Years of Terrestrial Water Storage Observations from GRACE

GRACE is unique among remote sensing systems in its ability to "see" below the first few centimeters of the land surface, and it has provided the first global observations of total terrestrial water storage variations. Now that we have more than seven years of GRACE measurements, it is tempting to look for trends in the data. Auxiliary information is almost always required in order to arrive at the correct diagnosis of an apparent trend. Here we will present a map of GRACE derived terrestrial water storage tendencies since 2002 and attempt to explain which are likely to continue due to climatic or human pressures, and which are short-term expressions of natural interannual variability.

Rodell, Matt↗

NASA NTRS2011

Distributed Damage Estimation for Prognostics based on Structural Model Decomposition

Model-based prognostics approaches capture system knowledge in the form of physics-based models of components, and how they fail. These methods consist of a damage estimation phase, in which the health state of a component is estimated, and a prediction phase, in which the health state is projected forward in time to determine end of life. However, the damage estimation problem is often multi-dimensional and computationally intensive. We propose a model decomposition approach adapted from the diagnosis community, called possible conflicts, in order to both improve the computational efficiency of damage estimation, and formulate a damage estimation approach that is inherently distributed. Local state estimates are combined into a global state estimate from which prediction is performed. Using a centrifugal pump as a case study, we perform a number of simulation-based experiments to demonstrate the approach.

Daigle, Matthew↗

NASA NTRS1993

Automated system function allocation and display format: Task information processing requirements

An important consideration when designing the interface to an intelligent system concerns function allocation between the system and the user. The display of information could be held constant, or 'fixed', leaving the user with the task of searching through all of the available information, integrating it, and classifying the data into a known system state. On the other hand, the system, based on its own intelligent diagnosis, could display only relevant information in order to reduce the user's search set. The user would still be left the task of perceiving and integrating the data and classifying it into the appropriate system state. Finally, the system could display the patterns of data. In this scenario, the task of integrating the data is carried out by the system, and the user's information processing load is reduced, leaving only the tasks of perception and classification of the patterns of data. Humans are especially adept at this form of display processing. Although others have examined the relative effectiveness of alphanumeric and graphical display formats, it is interesting to reexamine this issue together with the function allocation problem. Currently, Johnson Space Center is the test site for an intelligent Thermal Control System (TCS), TEXSYS, being tested for use with Space Station Freedom. Expert TCS engineers, as well as novices, were asked to classify several displays of TEXSYS data into various system states (including nominal and anomalous states). Three different display formats were used: fixed, subset, and graphical. The hypothesis tested was that the graphical displays would provide for fewer errors and faster classification times by both experts and novices, regardless of the kind of system state represented within the display. The subset displays were hypothesized to be the second most effective display format/function allocation condition, based on the fact that the search set is reduced in these displays. Both the subset and the graphic display conditions were hypothesized to be processed more efficiently than the fixed display conditions.

Czerwinski, Mary P.↗

NASA NTRS1990

An expert system for fault diagnosis in a Space Shuttle main engine

The detection and diagnosis of SSME faults in an early stage is important in order to allow enough time for fault preventive or corrective measurements. Since most of the faults in a complex system like SSME develop rapidly, early detection and diagnosis of faults is critical for the survival of space vehicles. An expert system has been designed for automatic learning, detection, identification, verification, and correction of anomalous propulsion system operations. This paper describes an innovative machine learning approach which is employed for the automatic training of this expert system.

Ali, Moonis↗

NASA NTRS1990

Knowledge assisted diagnosis of mood disorders using DSM-3

As part of an Expert Systems class at the University of Houston Clear Lake, a system has been developed using CLIPS to allow a clinical psychologist or psychiatrist to diagnose mood disturbances by providing answers to questions corresponding to branches of a DSM-III criteria tree. Experienced clinicians may assert indications of the client's behavior in order to circumvent multiple levels of the tree, thus speeding diagnosis. An explanation facility was developed for validation of the diagnosis . It also allows for 'what if' scenarios by allowing the clinician to move backwards from the diagnosis to any decision branch and alter the answer previously provided. The system was implemented with a limited vocabulary of symptoms associated primarily with depressive disorders. However, the design supports the addition of vocabulary modules and knowledge bases for other types of disorders. The system currently has applicability in an instructional setting. With the addition of a more complete vocabulary, it could have applicability in a clinical setting. The overall design will support any application where determinations are made via a decision tree.

Fritz, Robert H.↗

NASA NTRS2017

Near Real-Time Probabilistic Damage Diagnosis Using Surrogate Modeling and High Performance Computing

This work investigates novel approaches to probabilistic damage diagnosis that utilize surrogate modeling and high performance computing (HPC) to achieve substantial computational speedup. Motivated by Digital Twin, a structural health management (SHM) paradigm that integrates vehicle-specific characteristics with continual in-situ damage diagnosis and prognosis, the methods studied herein yield near real-time damage assessments that could enable monitoring of a vehicle's health while it is operating (i.e. online SHM). High-fidelity modeling and uncertainty quantification (UQ), both critical to Digital Twin, are incorporated using finite element method simulations and Bayesian inference, respectively. The crux of the proposed Bayesian diagnosis methods, however, is the reformulation of the numerical sampling algorithms (e.g. Markov chain Monte Carlo) used to generate the resulting probabilistic damage estimates. To this end, three distinct methods are demonstrated for rapid sampling that utilize surrogate modeling and exploit various degrees of parallelism for leveraging HPC. The accuracy and computational efficiency of the methods are compared on the problem of strain-based crack identification in thin plates. While each approach has inherent problem-specific strengths and weaknesses, all approaches are shown to provide accurate probabilistic damage diagnoses and several orders of magnitude computational speedup relative to a baseline Bayesian diagnosis implementation.

Warner, James E.↗

NASA NTRS2021

On-Board Model Based Fault Diagnosis for CubeSat Attitude Control Subsystem: Flight Data Results

Self-sufficient, robotic spacecraft require estimates of their hardware health state in order to project future system state and plan actions toward achieving mission goals. In this paper, we report on integration of a Model-Based Fault Diagnosis (MBFD) model and reasoning engine into flight software leveraging the Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) mission, including test results against captured flight data using the ASTERIA system testbed. Our effort integrated the Model-based Off-Nominal State Identification and Detection (MONSID) model-based reasoning system, developed by Okean Solutions, into ASTERIA flight software using the F Prime software framework. The MONSID engine was supplied with a model of the Blue Canyon Technologies XACT attitude control system (ACS) and tested against flight data and seeded fault tests. While we were unable to conduct an on-board experiment due to the premature loss of ASTERIA, our effort proved the feasibility of on-board model-based fault management, demonstrating reliable and accurate diagnosis using captured data, and further supporting a closed-loop spacecraft autonomy demonstration including autonomous navigation in off-nominal conditions.

Prather, Maurice↗

NASA NTRS1989

Efficient diagnosis of multiprocessor systems under probabilistic models

The problem of fault diagnosis in multiprocessor systems is considered under a probabilistic fault model. The focus is on minimizing the number of tests that must be conducted in order to correctly diagnose the state of every processor in the system with high probability. A diagnosis algorithm that can correctly diagnose the state of every processor with probability approaching one in a class of systems performing slightly greater than a linear number of tests is presented. A nearly matching lower bound on the number of tests required to achieve correct diagnosis in arbitrary systems is also proven. Lower and upper bounds on the number of tests required for regular systems are also presented. A class of regular systems which includes hypercubes is shown to be correctly diagnosable with high probability. In all cases, the number of tests required under this probabilistic model is shown to be significantly less than under a bounded-size fault set model. Because the number of tests that must be conducted is a measure of the diagnosis overhead, these results represent a dramatic improvement in the performance of system-level diagnosis techniques.

Blough, Douglas M.↗

NASA NTRS1988

Fault diagnosis in sparse multiprocessor systems

The problem of fault diagnosis in multiprocessor systems is considered under a uniformly probabilistic model in which processors are faulty with probability p. This work focuses on minimizing the number of tests that must be conducted in order to correctly diagnose the state of every processor in the system with high probability. A diagnosis algorithm that can correctly diagnose the state of every processor with probability approaching one in a class of systems performing slightly greater than a linear number of tests is presented. A nearly matching lower bound on the number of tests required to achieve correct diagnosis in arbitrary systems is also proven. The number of tests required under this probabilistic model is shown to be significantly less than under a bounded-size fault set model. Because the number of tests that must be conducted is a measure of the diagnosis overhead, these results represent a dramatic improvement in the performance of system-level diagnosis technique.

Blough, Douglas M.↗

NASA NTRS1976

Ambulance Handbook

Johnson Space Center has devised a checklist for the skylab inflight medical support system that has been transferred for public emergencies. The checklist illustrates a procedure for diagnosis, treatment, and stabilization of a wide variety of emergencies. Handbook presents comprehensive ordered description of emergency medical equipment and its use in treating victims. Paramedics assigned to the Houston Fire Department are now using the checklist.

Source record↗

NASA NTRS1994

A Logical Account of Diagnosis with Multiple Theories

Model-based diagnosis is a powerful, first-principles approach to diagnosis. The primary drawback with model-based diagnosis is that it is based on a system model, and this model might be inappropriate. The inappropriateness of models usually stems from the fundamental tradeoff between completeness and efficiency. Recently, Struss has developed an elegant proposal for diagnosis with multiple models. Struss characterizes models as relations and develops a precise notion of abstraction. He defines relations between models and analyzes the effect of a model switch on the space of possible diagnoses. In this paper we extend Struss's proposal in three ways. First, our account of diagnosis with multiple models is based on representing models as more expressive first-order theories, rather than as relations. A key technical contribution is the use of a general notion of abstraction based on interpretations between theories. Second, Struss conflates component modes with models, requiring him to define models relations such as choices which result in non-relational models. We avoid this problem by differentiating component modes from models. Third, we present a more general account of simplifications that correctly handles situations where the simplification contradicts the base theory.

Pandurang, P.↗

NASA NTRS2016

Closing the Contrast Gap Between Testbed and Model Prediction with WFIRST-CGI Shaped Pupil Coronagraph

JPL has recently passed an important milestone in its technology development for a proposed NASA WFIRST mission: demonstration of a better than 1x10-8 contrast over broad bandwidth (10%) on both shaped pupil coronagraph (SPC) and hybrid Lyot coronagraph (HLC) testbeds with WFIRST telescope optics. Challenges remain, however, in the technology readiness for the proposed mission. One such is the discrepancy between the achieved contrast on testbeds and their corresponding model predictions. A series of testbed diagnosis and modeling activity were planned and (some) carried out on SPC testbed in order to close the gap. A very useful tool we developed was to analyze the measured testbed Jacobian and compare with its model version that was used to control image plane speckle pattern. The difference between these two is the error in the control Jacobian. When the error, which includes both amplitude and phase, was inserted into a separate prediction model with nominal Jacobian, the model prediction became closely matching the SPC testbed behavior in both contrast floor and contrast convergence speed. This offers a new perspective and is a step closer toward model validation for high contrast coronagraph. Further Jacobian analysis and modeling provided clues to the possible sources for the mismatch: the DM misregistration and the underrepresented testbed optics wavefront error (WFE) and the deformable mirror (DM) setting for correcting this WFE. These analyses suggested that high contrast coronagraph has a tight tolerance in the accuracy of its control Jacobian. Modifications to both testbed control model as well as prediction model are being implemented and future works discussed.

diffraction modeling↗

NASA NTRS2004

Explanation Constraint Programming for Model-based Diagnosis of Engineered Systems

We can expect to see an increase in the deployment of unmanned air and land vehicles for autonomous exploration of space. In order to maintain autonomous control of such systems, it is essential to track the current state of the system. When the system includes safety-critical components, failures or faults in the system must be diagnosed as quickly as possible, and their effects compensated for so that control and safety are maintained under a variety of fault conditions. The Livingstone fault diagnosis and recovery kernel and its temporal extension L2 are examples of model-based reasoning engines for health management. Livingstone has been shown to be effective, it is in demand, and it is being further developed. It was part of the successful Remote Agent demonstration on Deep Space One in 1999. It has been and is being utilized by several projects involving groups from various NASA centers, including the In Situ Propellant Production (ISPP) simulation at Kennedy Space Center, the X-34 and X-37 experimental reusable launch vehicle missions, Techsat-21, and advanced life support projects. Model-based and consistency-based diagnostic systems like Livingstone work only with discrete and finite domain models. When quantitative and continuous behaviors are involved, these are abstracted to discrete form using some mapping. This mapping from the quantitative domain to the qualitative domain is sometimes very involved and requires the design of highly sophisticated and complex monitors. We propose a diagnostic methodology that deals directly with quantitative models and behaviors, thereby mitigating the need for these sophisticated mappings. Our work brings together ideas from model-based diagnosis systems like Livingstone and concurrent constraint programming concepts. The system uses explanations derived from the propagation of quantitative constraints to generate conflicts. Fast conflict generation algorithms are used to generate and maintain multiple candidates whose consistency can be tracked across multiple time steps.

Narasimhan, Sriram↗