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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 NTRS2012

An Integrated Framework for Model-Based Distributed Diagnosis and Prognosis

Diagnosis and prognosis are necessary tasks for system reconfiguration and fault-adaptive control in complex systems. Diagnosis consists of detection, isolation and identification of faults, while prognosis consists of prediction of the remaining useful life of systems. This paper presents a novel integrated framework for model-based distributed diagnosis and prognosis, where system decomposition is used to enable the diagnosis and prognosis tasks to be performed in a distributed way. We show how different submodels can be automatically constructed to solve the local diagnosis and prognosis problems. We illustrate our approach using a simulated four-wheeled rover for different fault scenarios. Our experiments show that our approach correctly performs distributed fault diagnosis and prognosis in an efficient and robust manner.

Bregon, Anibal↗

NASA NTRS2017

A Diagnosis-Prognosis Feedback Loop for Improved Performance Under Uncertainties

The feed-forward relationship between diagnosis and prognosis is the foundation of both aircraft structural health management and the digital twin concept. Measurements of structural response are obtained either in-situ with mounted sensor networks or offline using more traditional techniques (e.g., nondestructive evaluation). Diagnosis algorithms process this information to detect and quantify damage and then feed this data forward to a prognostic framework. A prognosis of the structure's future operational readiness (e.g., remaining useful life or residual strength) is then made and is used to inform mission- critical decision-making. Years of research have been devoted to improving the elements of this process, but the process itself has not changed significantly. Here, a new approach is proposed in which prognosis information is not only fed forward for decision-making, but it is also fed back to the forthcoming diagnosis. In this way, diagnosis algorithms can take advantage of a priori information about the expected state of health, rather than operating in an uninformed condition. As a feasibility test, a diagnosis-prognosis feedback loop of this manner is demonstrated. The approach is applied to a numerical example in which fatigue crack growth is simulated in a simple aluminum alloy test specimen. A prognosis was derived from a set of diagnoses which provided feedback to a subsequent set of diagnoses. Improvements in accuracy and a reduction in uncertainty in the prognosis- informed diagnoses were observed when compared with an uninformed diagnostic approach.

Leser, Patrick E.↗

NASA NTRS2016

Probabilistic Prognosis of Non-Planar Fatigue Crack Growth

Quantifying the uncertainty in model parameters for the purpose of damage prognosis can be accomplished utilizing Bayesian inference and damage diagnosis data from sources such as non-destructive evaluation or structural health monitoring. The number of samples required to solve the Bayesian inverse problem through common sampling techniques (e.g., Markov chain Monte Carlo) renders high-fidelity finite element-based damage growth models unusable due to prohibitive computation times. However, these types of models are often the only option when attempting to model complex damage growth in real-world structures. Here, a recently developed high-fidelity crack growth model is used which, when compared to finite element-based modeling, has demonstrated reductions in computation times of three orders of magnitude through the use of surrogate models and machine learning. The model is flexible in that only the expensive computation of the crack driving forces is replaced by the surrogate models, leaving the remaining parameters accessible for uncertainty quantification. A probabilistic prognosis framework incorporating this model is developed and demonstrated for non-planar crack growth in a modified, edge-notched, aluminum tensile specimen. Predictions of remaining useful life are made over time for five updates of the damage diagnosis data, and prognostic metrics are utilized to evaluate the performance of the prognostic framework. Challenges specific to the probabilistic prognosis of non-planar fatigue crack growth are highlighted and discussed in the context of the experimental results.

Leser, Patrick E.↗

NASA NTRS1981

Detection, Diagnosis and Prognosis: Contribution to the energy challenge: Proceedings of the Meeting of the Mechanical Failures Prevention Group

The contribution of failure detection, diagnosis and prognosis to the energy challenge is discussed. Areas of special emphasis included energy management, techniques for failure detection in energy related systems, improved prognostic techniques for energy related systems and opportunities for detection, diagnosis and prognosis in the energy field.

Shives, T. R.↗

NASA NTRS1996

Continuum Fatigue Damage Modeling for Critical Design, Control, and Fault Prognosis

This paper develops a simplified continuum (continuous with respect to time, stress, etc.) fatigue damage model for use in critical design, Life Extending Control and fault prognosis. The work is based on the local strain cyclic damage modeling method. New nonlinear explicit equation forms of cyclic damage in terms of stress amplitude are derived to facilitate the continuum modelling. Stress based continuum models are derived. Extension to plastic strain-strain rate models is also presented. Progress toward a non-zero mean stress based is presented. Also new nonlinear explicit equation forms in terms of stress amplitude are derived for this case. Application of the various models to design, control, and fault prognosis is considered.

Lorenzo, Carl F.↗

NASA NTRS2009

An Overview of Prognosis Health Management Research at Glenn Research Center for Gas Turbine Engine Structures With Special Emphasis on Deformation and Damage Modeling

Herein a general, multimechanism, physics-based viscoelastoplastic model is presented in the context of an integrated diagnosis and prognosis methodology which is proposed for structural health monitoring, with particular applicability to gas turbine engine structures. In this methodology, diagnostics and prognostics will be linked through state awareness variable(s). Key technologies which comprise the proposed integrated approach include (1) diagnostic/detection methodology, (2) prognosis/lifing methodology, (3) diagnostic/prognosis linkage, (4) experimental validation, and (5) material data information management system. A specific prognosis lifing methodology, experimental characterization and validation and data information management are the focal point of current activities being pursued within this integrated approach. The prognostic lifing methodology is based on an advanced multimechanism viscoelastoplastic model which accounts for both stiffness and/or strength reduction damage variables. Methods to characterize both the reversible and irreversible portions of the model are discussed. Once the multiscale model is validated the intent is to link it to appropriate diagnostic methods to provide a full-featured structural health monitoring system.

Arnold, Steven M.↗

NASA NTRS2009

An Overview of Prognosis Health Management Research at GRC for Gas Turbine Engine Structures With Special Emphasis on Deformation and Damage Modeling

Herein a general, multimechanism, physics-based viscoelastoplastic model is presented in the context of an integrated diagnosis and prognosis methodology which is proposed for structural health monitoring, with particular applicability to gas turbine engine structures. In this methodology, diagnostics and prognostics will be linked through state awareness variable(s). Key technologies which comprise the proposed integrated approach include 1) diagnostic/detection methodology, 2) prognosis/lifing methodology, 3) diagnostic/prognosis linkage, 4) experimental validation and 5) material data information management system. A specific prognosis lifing methodology, experimental characterization and validation and data information management are the focal point of current activities being pursued within this integrated approach. The prognostic lifing methodology is based on an advanced multi-mechanism viscoelastoplastic model which accounts for both stiffness and/or strength reduction damage variables. Methods to characterize both the reversible and irreversible portions of the model are discussed. Once the multiscale model is validated the intent is to link it to appropriate diagnostic methods to provide a full-featured structural health monitoring system.

Arnold, Steven M.↗

NASA NTRS2009

An Overview of Prognosis Health Management Research at Glenn Research Center for Gas Turbine Engine Structures With Special Emphasis on Deformation and Damage Modeling

Arnold, Steven M.↗

NASA NTRS2013

Model-Based Diagnosis and Prognosis of a Water Recycling System

A water recycling system (WRS) deployed at NASA Ames Research Center s Sustainability Base (an energy efficient office building that integrates some novel technologies developed for space applications) will serve as a testbed for long duration testing of next generation spacecraft water recycling systems for future human spaceflight missions. This system cleans graywater (waste water collected from sinks and showers) and recycles it into clean water. Like all engineered systems, the WRS is prone to standard degradation due to regular use, as well as other faults. Diagnostic and prognostic applications will be deployed on the WRS to ensure its safe, efficient, and correct operation. The diagnostic and prognostic results can be used to enable condition-based maintenance to avoid unplanned outages, and perhaps extend the useful life of the WRS. Diagnosis involves detecting when a fault occurs, isolating the root cause of the fault, and identifying the extent of damage. Prognosis involves predicting when the system will reach its end of life irrespective of whether an abnormal condition is present or not. In this paper, first, we develop a physics model of both nominal and faulty system behavior of the WRS. Then, we apply an integrated model-based diagnosis and prognosis framework to the simulation model of the WRS for several different fault scenarios to detect, isolate, and identify faults, and predict the end of life in each fault scenario, and present the experimental results.

Roychoudhury, Indranil↗

NASA NTRS2013

Remaining Useful Life Estimation in Prognosis: An Uncertainty Propagation Problem

The estimation of remaining useful life is significant in the context of prognostics and health monitoring, and the prediction of remaining useful life is essential for online operations and decision-making. However, it is challenging to accurately predict the remaining useful life in practical aerospace applications due to the presence of various uncertainties that affect prognostic calculations, and in turn, render the remaining useful life prediction uncertain. It is challenging to identify and characterize the various sources of uncertainty in prognosis, understand how each of these sources of uncertainty affect the uncertainty in the remaining useful life prediction, and thereby compute the overall uncertainty in the remaining useful life prediction. In order to achieve these goals, this paper proposes that the task of estimating the remaining useful life must be approached as an uncertainty propagation problem. In this context, uncertainty propagation methods which are available in the literature are reviewed, and their applicability to prognostics and health monitoring are discussed.

Uncertainty Quantification↗

NASA NTRS1980

Comparative assessment of prognosis of the stop stimulus and trapezoidal rotation programs

For prognosis of the diagnostic possibilities of the stop stimulus and trapezoidal rotation programs with respect to the nystagmus response, 24 healthy young persons with normal auditory and vestibular analysers were studied experimentally. The trapezoidal program more accurately reflects the function and tone balance of the vestibular system than the stop stimulus program and causes the subject no unpleasant sensations during the study. Some optimum couples, acceleration and armchair rotation rate, necessary for effective deviation of the cupuloendolymphatic system were determined. The maximum angular velocity of the slow nystagmus component was more informative than nystagmus duration. The trapezoidal program is recommended for otoneurological practice and the maximum angular velocity of the slow nystagmus component as the basic index.

Grigorova, V. K.↗

NASA NTRS1980

Integrated CAD/CAM: Problems, prognosis, and role of IPAD

Major technology problems impede the development and evolution of totally integrated interactive CAD/CAM systems. IPAD is playing an important role in the identification of these problems and is contributing significantly to their solution. It is the purpose of this presentation to examine some of these issues, look at the prognosis of obtaining effective solutions, and point up some of the past and expected contributions of IPAD to this technology.

Nilson, E. N.↗

NASA NTRS1990

Background, current status, and prognosis of the ongoing slush hydrogen technology development program for the NASP

Among the Hydrogen Projects at the NASA Lewis Research Center (NASA LeRC), is the task of implementing and managing the Slush Hydrogen (SLH2) Technology Program for the United States' National AeroSpace Plane Joint Program Office (NASP JPO). The objectives of this NASA LeRC program are to provide verified numerical models of fluid production, storage, transfer, and feed systems and to provide verified design criteria for other engineered aspects of SLH2 systems germane to a NASP. The pursuit of these objectives is multidimensional, covers a range of problem areas, works these to different levels of depth, and takes advantage of the resources available in private industry, academia, and the U.S. Government. A summary of the NASA LeRC overall SLH2 program plan, is presented along with its implementation, the present level of effort in each of the program areas, some of the results already in hand, and the prognosis for the effort in the immediate future.

Dewitt, R. L.↗

NASA NTRS1994

A Feasibility Study for Perioperative Ventricular Tachycardia Prognosis and Detection and Noise Detection Using a Neural Network and Predictive Linear Operators

To locate the accessory pathway(s) in preexicitation syndromes, epicardial and endocardial ventricular mapping is performed during anterograde ventricular activation via accessory pathway(s) from data originally received in signal form. As the number of channels increases, it is pertinent that more automated detection of coherent/incoherent signals is achieved as well as the prediction and prognosis of ventricular tachywardia (VT). Today's computers and computer program algorithms are not good in simple perceptual tasks such as recognizing a pattern or identifying a sound. This discrepancy, among other things, has been a major motivating factor in developing brain-based, massively parallel computing architectures. Neural net paradigms have proven to be effective at pattern recognition tasks. In signal processing, the picking of coherent/incoherent signals represents a pattern recognition task for computer systems. The picking of signals representing the onset ot VT also represents such a computer task. We attacked this problem by defining four signal attributes for each potential first maximal arrival peak and one signal attribute over the entire signal as input to a back propagation neural network. One attribute was the predicted amplitude value after the maximum amplitude over a data window. Then, by using a set of known (user selected) coherent/incoherent signals, and signals representing the onset of VT, we trained the back propagation network to recognize coherent/incoherent signals, and signals indicating the onset of VT. Since our output scheme involves a true or false decision, and since the output unit computes values between 0 and 1, we used a Fuzzy Arithmetic approach to classify data as coherent/incoherent signals. Furthermore, a Mean-Square Error Analysis was used to determine system stability. The neural net based picking coherent/incoherent signal system achieved high accuracy on picking coherent/incoherent signals on different patients. The system also achieved a high accuracy of picking signals which represent the onset of VT, that is, VT immediately followed these signals. A special binary representation of the input and output data allowed the neural network to train very rapidly as compared to another standard decimal or normalized representations of the data.

Moebes, T. A.↗

NASA NTRS2005

Diagnosis and Prognosis of Weapon Systems

The Prognostics Framework is a set of software tools with an open architecture that affords a capability to integrate various prognostic software mechanisms and to provide information for operational and battlefield decision-making and logistical planning pertaining to weapon systems. The Prognostics NASA Tech Briefs, February 2005 17 Framework is also a system-level health -management software system that (1) receives data from performance- monitoring and built-in-test sensors and from other prognostic software and (2) processes the received data to derive a diagnosis and a prognosis for a weapon system. This software relates the diagnostic and prognostic information to the overall health of the system, to the ability of the system to perform specific missions, and to needed maintenance actions and maintenance resources. In the development of the Prognostics Framework, effort was focused primarily on extending previously developed model-based diagnostic-reasoning software to add prognostic reasoning capabilities, including capabilities to perform statistical analyses and to utilize information pertaining to deterioration of parts, failure modes, time sensitivity of measured values, mission criticality, historical data, and trends in measurement data. As thus extended, the software offers an overall health-monitoring capability.

Nolan, Mary↗

NASA NTRS1977

Atmospheric sounding with passive microwaves: Review and prognosis

Global maps of temperature profiles from 0 to 20 km altitude and of total water vapor and liquid water over the ocean were obtained from satellite-borne microwave spectrometers. Future satellites will extend the altitude range above 100 km and permit monitoring of H2O, O3, CO, N2O, and other trace constituents. Operational microwave temperature sounding spectrometers are scheduled for launch on both military and civilian U.S. satellites, and future improvements can be expected.

Staelin, D. H.↗

NASA NTRS1977

Prognosis of the state of health of a person under spaceflight conditions

Methods of predicting the state of health and human efficiency during space flight are discussed. Diversity of reactions to the same conditions, development of extrapolation methods of prediction, and isolation of informative physiological indexes are among the factors considered.

Source record↗

NASA NTRS1977

Atmospheric sounding with passive microwaves - Review and prognosis

Global maps of temperature profiles 0-20 km and of total water vapor and liquid water over ocean have been obtained from satellite-borne microwave spectrometers. Future satellites should extend the altitude range above 100 km and permit monitoring of H2O, O3, CO, N2O, and other trace constituents. Operational microwave temperature-sounding spectrometers are scheduled for launch on both military and civilian U.S. satellites, and future improvements can be expected.

Staelin, D. H.↗