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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

Damage Characterization Using the Extended Finite Element Method for Structural Health Management

The development of validated multidisciplinary Integrated Vehicle Health Management (IVHM) tools, technologies, and techniques to enable detection, diagnosis, prognosis, and mitigation in the presence of adverse conditions during flight will provide effective solutions to deal with safety related challenges facing next generation aircraft. The adverse conditions include loss of control caused by environmental factors, actuator and sensor faults or failures, and damage conditions. A major concern in these structures is the growth of undetected damage/cracks due to fatigue and low velocity foreign impact that can reach a critical size during flight, resulting in loss of control of the aircraft. Hence, development of efficient methodologies to determine the presence, location, and severity of damage/cracks in critical structural components is highly important in developing efficient structural health management systems.

Krishnamurthy, Thiagarajan↗

Radiated Emissions from a Remote-Controlled Airplane-Measured in a Reverberation Chamber

A full-vehicle, subscale all-electric model airplane was tested for radiated emissions, using a reverberation chamber. The mission of the NASA model airplane is to test in-flight airframe damage diagnosis and battery prognosis algorithms, and provide experimental data for other aviation safety research. Subscale model airplanes are economical experimental tools, but assembling their systems from hobbyist and low-cost components may lead to unforseen electromagnetic compatibility problems. This report provides a guide for accommodating the on-board radio systems, so that all model airplane systems may be operated during radiated emission testing. Radiated emission data are provided for on-board systems being operated separately and together, so that potential interferors can be isolated and mitigated. The report concludes with recommendations for EMI/EMC best practices for subscale model airplanes and airships used for research.

Ely, Jay J.↗

Smart Sensor Demonstration Payload

Sensors are a critical element to any monitoring, control, and evaluation processes such as those needed to support ground based testing for rocket engine test. Sensor applications involve tens to thousands of sensors; their reliable performance is critical to achieving overall system goals. Many figures of merit are used to describe and evaluate sensor characteristics; for example, sensitivity and linearity. In addition, sensor selection must satisfy many trade-offs among system engineering (SE) requirements to best integrate sensors into complex systems [1]. These SE trades include the familiar constraints of power, signal conditioning, cabling, reliability, and mass, and now include considerations such as spectrum allocation and interference for wireless sensors. Our group at NASA s John C. Stennis Space Center (SSC) works in the broad area of integrated systems health management (ISHM). Core ISHM technologies include smart and intelligent sensors, anomaly detection, root cause analysis, prognosis, and interfaces to operators and other system elements [2]. Sensor technologies are the base fabric that feed data and health information to higher layers. Cost-effective operation of the complement of test stands benefits from technologies and methodologies that contribute to reductions in labor costs, improvements in efficiency, reductions in turn-around times, improved reliability, and other measures. ISHM is an active area of development at SSC because it offers the potential to achieve many of those operational goals [3-5].

Schmalzel, John↗

Symbolic Constraint Maintenance Grid

Version 3.1 of Symbolic Constraint Maintenance Grid (SCMG) is a software system that provides a general conceptual framework for utilizing pre-existing programming techniques to perform symbolic transformations of data. SCMG also provides a language (and an associated communication method and protocol) for representing constraints on the original non-symbolic data. SCMG provides a facility for exchanging information between numeric and symbolic components without knowing the details of the components themselves. In essence, it integrates symbolic software tools (for diagnosis, prognosis, and planning) with non-artificial-intelligence software. SCMG executes a process of symbolic summarization and monitoring of continuous time series data that are being abstractly represented as symbolic templates of information exchange. This summarization process enables such symbolic- reasoning computing systems as artificial- intelligence planning systems to evaluate the significance and effects of channels of data more efficiently than would otherwise be possible. As a result of the increased efficiency in representation, reasoning software can monitor more channels and is thus able to perform monitoring and control functions more effectively.

James, Mark↗

An Examination of Commercial Aviation Accidents and Incidents Related to Integrated Vehicle Health Management

The Integrated Vehicle Health Management (IVHM) Project is one of the four projects within the National Aeronautics and Space Administration's (NASA) Aviation Safety Program (AvSafe). The IVHM Project conducts research to develop validated tools and technologies for automated detection, diagnosis, and prognosis that enable mitigation of adverse events during flight. Adverse events include those that arise from system, subsystem, or component failure, faults, and malfunctions due to damage, degradation, or environmental hazards that occur during flight. Determining the causal factors and adverse events related to IVHM technologies will help in the formulation of research requirements and establish a list of example adverse conditions against which IVHM technologies can be evaluated. This paper documents the results of an examination of the most recent statistical/prognostic accident and incident data that is available from the Aviation Safety Information Analysis and Sharing (ASIAS) System to determine the causal factors of system/component failures and/or malfunctions in U.S. commercial aviation accidents and incidents.

Reveley, Mary S.↗

A Survey of Health Management User Objectives Related to Diagnostic and Prognostic Metrics

One of the most prominent technical challenges to effective deployment of health management systems is the vast difference in user objectives with respect to engineering development. In this paper, a detailed survey on the objectives of different users of health management systems is presented. These user objectives are then mapped to the metrics typically encountered in the development and testing of two main systems health management functions: diagnosis and prognosis. Using this mapping, the gaps between user goals and the metrics associated with diagnostics and prognostics are identified and presented with a collection of lessons learned from previous studies that include both industrial and military aerospace applications.

Wheeler, Kevin R.↗

NASA Tech Briefs, February 2005

Topics discussed include: Instrumentation for Sensitive Gas Measurements; Apparatus for Testing Flat Specimens of Thermal Insulation; Quadrupole Ion Mass Spectrometer for Masses of 2 to 50 Da; Miniature Laser Doppler Velocimeter for Measuring Wall Shear; Coherent Laser Instrument Would Measure Range and Velocity; Printed Microinductors for Flexible Substrates; Digital Receiver for Microwave Radiometry; Printed Antennas Made Reconfigurable by Use of MEMS Switches; Traffic-Light-Preemption Vehicle-Transponder Software Module; Intersection-Controller Software Module; Central-Monitor Software Module; Estimating Effects of Multipath Propagation on GPS Signals; Parallel Adaptive Mesh Refinement Library; Predicting Noise From Aircraft Turbine-Engine Combustors; Generating Animated Displays of Spacecraft Orbits; Diagnosis and Prognosis of Weapon Systems; Training Software in Artificial-Intelligence Computing Techniques; APGEN Version 5.0; Single-Command Approach and Instrument Placement by a Robot on a Target; Three-Dimensional Audio Client Library; Isogrid Membranes for Precise, Singly Curved Reflectors; Nickel-Tin Electrode Materials for Nonaqueous Li-Ion Cells; Photocatalytic Coats in Glass Drinking-Water Bottles; Fast Laser Shutters With Low Vibratory Disturbances; Series-Connected Buck Boost Regulators; Space Physics Data Facility Web Services; Split-Resonator, Integrated-Post Vibratory Microgyroscope; Blended Buffet-Load-Alleviation System for Fighter Airplane; Gifford-McMahon/Joule-Thomson Refrigerator Cools to 2.5 K; High-Temperature, High-Load-Capacity Radial Magnetic Bearing; Fabrication of Spherical Reflectors in Outer Space; Automated Rapid Prototyping of 3D Ceramic Parts; Tissue Engineering Using Transfected Growth-Factor Genes; Automation of Vapor-Diffusion Growth of Protein Crystals; Atom Skimmers and Atom Lasers Utilizing Them; Gears Based on Carbon Nanotubes; Patched Off-Axis Bending/Twisting Actuators for Thin Mirrors; and Improving Control in a Joule-Thomson Refrigerator.

Source record↗

The Challenge of Orbital Debris

Since the dawn of the Space Age more than 50 years ago, humans have been launching objects into the space environment faster than they have been removed by active means or natural decay. This has led to a proliferation of debris -- derelict satellites, discarded rocket upper stages, and pieces from satellite breakups -- in Earth orbit, especially in well-used orbital regimes. This talk will summarize the current knowledge of the debris environment and describe plans to address the challenges orbital debris raises for the future usability of near-Earth space. The talk will be structured around 4 categories: Measurements, Modeling, Shielding, and Mitigation. This will include discussions of the long-term prognosis of debris growth (i.e., the "Kessler Syndrome") as well as plans for active debris removal.

Matney, Mark↗

Model-Based Method for Sensor Validation

Fault detection, diagnosis, and prognosis are essential tasks in the operation of autonomous spacecraft, instruments, and in situ platforms. One of NASA s key mission requirements is robust state estimation. Sensing, using a wide range of sensors and sensor fusion approaches, plays a central role in robust state estimation, and there is a need to diagnose sensor failure as well as component failure. Sensor validation can be considered to be part of the larger effort of improving reliability and safety. The standard methods for solving the sensor validation problem are based on probabilistic analysis of the system, from which the method based on Bayesian networks is most popular. Therefore, these methods can only predict the most probable faulty sensors, which are subject to the initial probabilities defined for the failures. The method developed in this work is based on a model-based approach and provides the faulty sensors (if any), which can be logically inferred from the model of the system and the sensor readings (observations). The method is also more suitable for the systems when it is hard, or even impossible, to find the probability functions of the system. The method starts by a new mathematical description of the problem and develops a very efficient and systematic algorithm for its solution. The method builds on the concepts of analytical redundant relations (ARRs).

Vatan, Farrokh↗

Damage Characterization Method for Structural Health Management Using Reduced Number of Sensor Inputs

The development of validated multidisciplinary Integrated Vehicle Health Management (IVHM) tools, technologies, and techniques to enable detection, diagnosis, prognosis, and mitigation in the presence of adverse conditions during flight will provide effective solutions to deal with safety related challenges facing next generation aircraft. The adverse conditions include loss of control caused by environmental factors, actuator and sensor faults or failures, and damage conditions. A major concern in these structures is the growth of undetected damage (cracks) due to fatigue and low velocity foreign impacts that can reach a critical size during flight, resulting in loss of control of the aircraft. Hence, development of efficient methodologies to determine the presence, location, and severity of damage in critical structural components is highly important in developing efficient structural health management systems.

Krishnamurthy, T.↗

Uncertainty Management for Diagnostics and Prognostics of Batteries using Bayesian Techniques

Uncertainty management has always been the key hurdle faced by diagnostics and prognostics algorithms. A Bayesian treatment of this problem provides an elegant and theoretically sound approach to the modern Condition- Based Maintenance (CBM)/Prognostic Health Management (PHM) paradigm. The application of the Bayesian techniques to regression and classification in the form of Relevance Vector Machine (RVM), and to state estimation as in Particle Filters (PF), provides a powerful tool to integrate the diagnosis and prognosis of battery health. The RVM, which is a Bayesian treatment of the Support Vector Machine (SVM), is used for model identification, while the PF framework uses the learnt model, statistical estimates of noise and anticipated operational conditions to provide estimates of remaining useful life (RUL) in the form of a probability density function (PDF). This type of prognostics generates a significant value addition to the management of any operation involving electrical systems.

Saha, Bhaskar↗

Uncertainty Quantification in Remaining Useful Life of Aerospace Components using State Space Models and Inverse FORM

This paper investigates the use of the inverse first-order reliability method (inverse- FORM) to quantify the uncertainty in the remaining useful life (RUL) of aerospace components. The prediction of remaining useful life is an integral part of system health prognosis, and directly helps in online health monitoring and decision-making. However, the prediction of remaining useful life is affected by several sources of uncertainty, and therefore it is necessary to quantify the uncertainty in the remaining useful life prediction. While system parameter uncertainty and physical variability can be easily included in inverse-FORM, this paper extends the methodology to include: (1) future loading uncertainty, (2) process noise; and (3) uncertainty in the state estimate. The inverse-FORM method has been used in this paper to (1) quickly obtain probability bounds on the remaining useful life prediction; and (2) calculate the entire probability distribution of remaining useful life prediction, and the results are verified against Monte Carlo sampling. The proposed methodology is illustrated using a numerical example.

Sankararaman, Shankar↗

A Comparison of Filter-based Approaches for Model-based Prognostics

Model-based prognostics approaches use domain knowledge about a system and its failure modes through the use of physics-based models. Model-based prognosis is generally divided into two sequential problems: a joint state-parameter estimation problem, in which, using the model, the health of a system or component is determined based on the observations; and a prediction problem, in which, using the model, the stateparameter distribution is simulated forward in time to compute end of life and remaining useful life. The first problem is typically solved through the use of a state observer, or filter. The choice of filter depends on the assumptions that may be made about the system, and on the desired algorithm performance. In this paper, we review three separate filters for the solution to the first problem: the Daum filter, an exact nonlinear filter; the unscented Kalman filter, which approximates nonlinearities through the use of a deterministic sampling method known as the unscented transform; and the particle filter, which approximates the state distribution using a finite set of discrete, weighted samples, called particles. Using a centrifugal pump as a case study, we conduct a number of simulation-based experiments investigating the performance of the different algorithms as applied to prognostics.

prognostics↗

Requirements Flowdown for Prognostics and Health Management

Prognostics and Health Management (PHM) principles have considerable promise to change the game of lifecycle cost of engineering systems at high safety levels by providing a reliable estimate of future system states. This estimate is a key for planning and decision making in an operational setting. While technology solutions have made considerable advances, the tie-in into the systems engineering process is lagging behind, which delays fielding of PHM-enabled systems. The derivation of specifications from high level requirements for algorithm performance to ensure quality predictions is not well developed. From an engineering perspective some key parameters driving the requirements for prognostics performance include: (1) maximum allowable Probability of Failure (PoF) of the prognostic system to bound the risk of losing an asset, (2) tolerable limits on proactive maintenance to minimize missed opportunity of asset usage, (3) lead time to specify the amount of advanced warning needed for actionable decisions, and (4) required confidence to specify when prognosis is sufficiently good to be used. This paper takes a systems engineering view towards the requirements specification process and presents a method for the flowdown process. A case study based on an electric Unmanned Aerial Vehicle (e-UAV) scenario demonstrates how top level requirements for performance, cost, and safety flow down to the health management level and specify quantitative requirements for prognostic algorithm performance.

video acuity↗

Viscoelastic Response of the Titanium Alloy Ti-6-4: Experimental Identification of Time- and Rate-Dependent Reversible and Irreversible Deformation Regions

In support of an effort on damage prognosis, the viscoelastic behavior of Ti-6Al-4V (Ti-6-4) was investigated. This report documents the experimental characterization of this titanium alloy. Various uniaxial tests were conducted to low load levels over the temperature range of 20 to 538 C to define tensile, creep, and relaxation behavior. A range of strain rates (6x10(exp -7) to 0.001/s) were used to document rate effects. All tests were designed to include an unloading portion, followed by a hold time at temperature to allow recovery to occur either at zero stress or strain. The titanium alloy was found to exhibit viscoelastic behavior below the "yield" point and over the entire range of temperatures (although at lower temperatures the magnitude is extremely small). These experimental data will be used for future characterization of a viscoelastic model.

stress relaxation↗

Combinatorial Multidomain Mesoporous Chips and a Method for Fractionation, Stabilization, and Storage of Biomolecules

A new fractionation device shows desirable features for exploratory screening and biomarker discovery. The constituent MSCs may be tailored for desired pore sizes and surface properties and for the sequestration and enrichment of extremely low abundant protein and peptides in desired ranges of the mass/charge spectrum. The MSCs are effective in yielding reproducible extracts from complex biological samples as small as 10 microliter in a time as short as 30 minutes. They are inexpensive to manufacture, and allow for scaled up production to attain the simultaneous processing of a large number of samples. The MSCs are multiplexed, label-free diagnostic tools with the potential of biological recognition moiety modification for enhanced specificity. The MSCs may store, protect and stabilize biological fluids, enabling the simplified and cost-effective collection and transportation of clinical samples. The MSC-based device may serve as a diagnostic tool to complement histopathology, imaging, and other conventional clinical techniques. The MSCs mediated identification of disease-specific protein signatures may help in the selection of personalized therapeutic combinations, in the real-time assessment of therapeutic efficacy and toxicity, and in the rational modulation of therapy based on the changes in the protein networks associated with the prognosis and the drug resistance of the disease.

Ferrari, Mauro↗

Diagnostic Reasoning using Prognostic Information for Unmanned Aerial Systems

With increasing popularity of unmanned aircraft, continuous monitoring of their systems, software, and health status is becoming more and more important to ensure safe, correct, and efficient operation and fulfillment of missions. The paper presents integration of prognosis models and prognostic information with the R2U2 (REALIZABLE, RESPONSIVE, and UNOBTRUSIVE Unit) monitoring and diagnosis framework. This integration makes available statistically reliable health information predictions of the future at a much earlier time to enable autonomous decision making. The prognostic information can be used in the R2U2 model to improve diagnostic accuracy and enable decisions to be made at the present time to deal with events in the future. This will be an advancement over the current state of the art, where temporal logic observers can only do such valuation at the end of the time interval. Usefulness and effectiveness of this integrated diagnostics and prognostics framework was demonstrated using simulation experiments with the NASA Dragon Eye electric unmanned aircraft.

Diagnostics↗

Strain-Based Damage Determination Using Finite Element Analysis for Structural Health Management

A damage determination method is presented that relies on in-service strain sensor measurements. The method employs a gradient-based optimization procedure combined with the finite element method for solution to the forward problem. It is demonstrated that strains, measured at a limited number of sensors, can be used to accurately determine the location, size, and orientation of damage. Numerical examples are presented to demonstrate the general procedure. This work is motivated by the need to provide structural health management systems with a real-time damage characterization. The damage cases investigated herein are characteristic of point-source damage, which can attain critical size during flight. The procedure described can be used to provide prognosis tools with the current damage configuration.

Hochhalter, Jacob D.↗