Search NASA⌕ Search

SEARCH · Search NASA

Results for “condition based monitoring”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 379 records · Page 21

Durability Characterization of Advanced Polymeric Composites at Cryogenic Temperatures

The next generation of reusable launch vehicles will require technology development in several key areas. Of these key areas, the development of polymeric composite cryogenic fuel tanks promises to present one of the most difficult technical challenges. It is envisioned that a polymer matrix composite (PMC) tank would be a large shell structure capable of containing cryogenic fuels and carrying a range of structural loads. The criteria that will be imposed on such a design include reduced weight, conformal geometry, and impermeability. It is this last criterion, impermeability, that will provide the focus of this paper. The essence of the impermeability criterion is that the tank remains leak free throughout its design lifetime. To address this criterion, one of the first steps is to conduct a complete durability assessment of the PMC materials. At Langley Research Center, a durability assessment of promising new polyimide-based PMCs is underway. This durability program has focused on designing a set of critical laboratory experiments that will determine fundamental material properties under combined thermal-mechanical loading at cryogenic temperatures. The test program provides measurements of lamina and laminate properties, including strength, stiffness, and fracture toughness. The performance of the PMC materials is monitored as a function of exposure conditions and aging time. Residual properties after exposure are measured at cryogenic temperatures and provide quantitative values of residual strength and stiffness. Primary degradation mechanisms and the associated damage modes are measured with both destructive and nondestructive techniques. In addition to mechanical properties, a range of physical properties, such as weight, glass transition, and crack density, are measured and correlated with the test conditions. This paper will report on the progress of this research program and present critical results and illustrative examples of current findings.

Gates, T. S.↗

Analysing the Advantages of High Temporal Resolution Geostationary MSG SEVIRI Data Compared to Polar Operational Environmental Satellite Data for Land Surface Monitoring in Africa

Since 1972, satellite remote sensing of the environment has been dominated by polar-orbiting sensors providing useful data for monitoring the earth s natural resources. However their observation and monitoring capacity are inhibited by daily to monthly looks for any given ground surface which often is obscured by frequent and persistent cloud cover creating large gaps in time series measurements. The launch of the Meteosat Second Generation (MSG) satellite into geostationary orbit has opened new opportunities for land surface monitoring. The Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on-board MSG with an imaging capability every 15 minutes which is substantially greater than any temporal resolution that can be obtained from existing polar operational environmental satellites (POES) systems currently in use for environmental monitoring. Different areas of the African continent were affected by droughts and floods in 2008 caused by periods of abnormally low and high rainfall, respectively. Based on the effectiveness of monitoring these events from Earth Observation (EO) data the current analyses show that the new generation of geostationary remote sensing data can provide higher temporal resolution cloud-free (less than 5 days) measurements of the environment as compared to existing POES systems. SEVIRI MSG 5-day continental scale composites will enable rapid assessment of environmental conditions and improved early warning of disasters for the African continent such as flooding or droughts. The high temporal resolution geostationary data will complement existing higher spatial resolution polar-orbiting satellite data for various dynamic environmental and natural resource applications of terrestrial ecosystems.

Fensholt, R.↗

MODIS Aerosol Optical Depth Bias Adjustment Using Machine Learning Algorithms

To monitor the earth atmosphere and its surface changes, satellite based instruments collect continuous data. While some of the data is directly used, some others such as aerosol properties are indirectly retrieved from the observation data. While retrieved variables (RV) form very powerful products, they don't come without obstacles. Different satellite viewing geometries, calibration issues, dynamically changing atmospheric and earth surface conditions, together with complex interactions between observed entities and their environment affect them greatly. This results in random and systematic errors in the final products.

Albayrak, Arif↗

A Simulation Architecture for Air Traffic Over Urban Environments Supporting Autonomy Research in Advanced Air Mobility

NASA is conducting investigations into Advanced Air Mobility (AAM) concepts, aircraft, and operations. One of the most challenging scenarios for AAM will be enabling safe routine access into densely populated urban centers. To address challenges in the urban environment, a moderately high-fidelity simulation capability is needed to investigate AAM flight operations over a regional area for the development and evaluation of autonomy technologies. This paper describes a system to simulate flight operations around regions such as the San Francisco-Oakland Bay area at a moderately-high scale (10's-100's of flights) that incorporates detailed vehicle models and control necessary to support research in airborne autonomy. The flight vehicle utilizes NASA AAM concept vehicle dynamics integrated with a custom flight management system and flight control system to accurately simulate all phases of flight. Glass cockpit displays have been developed for monitoring aircraft operation over a detailed simulated urban environment. Simulation models have been integrated to simulate air and ground-based sensors, such as radar and LIDAR. The commercial X-Plane software package is used as a rendering engine to mimic vision-based sensors (such as onboard and ground-based cameras) at various times of day and in various weather conditions over a relatively detailed graphical model of the city. The paper presents a detailed illustration of the simulation and software architecture used for traffic over this urban region. This system is enabling the evaluation of NASA research concepts in autonomy for urban AAM operations on the path toward aircraft flight test evaluation.

Keerthana Kannan↗

Atmospheric Temperature from Raman Scattering

Raman scattering signatures are functions of the scattering-gas temperature, and are therefore of potential use for practical atmospheric temperature probes. The method described uses either ratios of pure rotational Raman scattering intensities for air utilizing various spectral bandpasses, or, alternatively, ratios of air-rotational to nitrogen-vibrational scattering intensities. Three aspects of work relating to the development of such probes are discussed in this presentation: (1) fundamental absolute Raman data, (2) construction of air spectra from these data, and (3) temperature-sensitivity of the signature. The fundamental data described are the absolute rotational and vibrational scattering cross sections. Recent measurements in this laboratory of rotational cross sections for N2, O2, and CO2 are emphasized, as are their use in predicting absolute magnitudes of Raman scattering signals. Next is described the computation of air rotational Raman spectra as a function of temperature calculated through use of the experimentally-measured cross sections. The spectra are based additively upon nitrogen and oxygen contributions, since pure rotational Raman scattering from water vapor is very weak. Finally, the sensitivity of the scattering intensity ratios to temperature is explored as a function of choice of spectral bandpass for the monitored rotational Raman scattering. Various compromises will be discussed which must be made in choosing bandpasses appropriate for specific purposes and experimental conditions.

Lapp, M.↗

Remote Recession Sensing of Ablative Heat Shield Materials

Tests were performed to demonstrate the feasibility of a new method of measuring surface recession of a material sample during arc-jet testing in the NASA Ames mARC subscale developmental facility. The measurement principle was inspired through tracer elements such as Ca and Na which were seen in the spectra taken during the airborne observation campaign of the Stardust re-entry and which could be clearly observed standing out against the emission spectra emitted by postshock layer and glowing surface of the re-entry capsule. The measurement principle involves seeding of the heat shield materials at a defined depth with tracer elements which show strong and characteristic emission lines in the post shock plasma. Once the material recession reaches the seeding depth, these elements get into the hot plasma and show up in the emission spectra. The methodology was successfully demonstrated during arc-jet testing of phenolic impregnated carbonablator (PICA) material which was seeded in depth with a mixture of NaCl and MgCl in powder form. In the emission spectroscopy data, the emission lines of Mg and Na showed up about 1.5 seconds after probe insertion into the arc-jet plasma and vanished after another 2.5 seconds when recessionhad consumed the seeding material. From these data, a recession rate of about 1 mm/s is estimated.The heat flux during the test was measured to be 2575 W/sq cm on a hemispherical heat flux probewhich corresponds to a heat flux of 1036 W/sq cm on the rectangular test articles. An estimate for a lower limit of the surface temperature of 2800K during the test was obtained by fitting Planck radiation to the continuum spectra emitted by the PICA sample. Typical recession rates of PICA during testing in the large arc-jet facilities at similar test conditions are reported to be on the order of 0.05 to 0.1 cm/s which agrees well with the recession rates of 0.05-0.06 cm/s estimated from the emission spectroscopy data. Further tests under better controlled conditions are suggested to quantify this measurement method. Through a different choice of seeding materials with lower melting point, an extension of the measurement principle to monitor char depth seems feasible but was not yet demonstrated. Possible applications besides ground testing are recession and possibly char depth measurements during real re-entry. Detection through emission spectroscopy could be accomplished through ground based or airborne observation as performed during the Stardust and Hayabusa re-entries, or through on-board spectrometers. A suitable mission would be the re-entryof the OSIRIS-REX mission planned for late 2023. The measured data are presented and interpreted, the results and details of future applications are discussed.

instrumentation↗

A Simulation Architecture for Air Traffic Over Urban Environments Supporting Autonomy Research in Advanced Air Mobility

As part of its research, NASA investigates concepts, aircraft, and operations related to Advanced Air Mobility (AAM). One of the most challenging scenarios for AAM will be enabling safe routine access near densely populated urban centers. AAM flight operations over a regional area require a moderately high-fidelity simulation capability to develop and evaluate autonomy technologies in the urban environment. This paper aims to describe a system to simulate flight operations around regions such as the San Francisco-Oakland Bay area at a moderately-high scale (tens to hundreds of flights) that incorporates detailed vehicle models and control necessary to support research in airborne autonomy. The flight vehicle utilizes NASA AAM concept vehicle dynamics integrated with a custom flight management system and flight control system to simulate all flight phases accurately. The simulation incorporates a detailed simulated urban environment and includes glass cockpit displays to monitor aircraft operations. Simulation models integrate to simulate air and ground-based sensors, such as Radar and LiDAR. As a commercially available rendering engine, X-Plane 11 is used as the renderer to simulate vision-based sensors (such as onboard and ground-based cameras) with a detailed graphical model of a city at different times of the day and weather conditions. This paper presents the simulation and software architecture used for simulating AAM traffic over this urban region. This system enables the evaluation of NASA research concepts in autonomy for urban AAM operations on the path toward flight test evaluation.

distributed sensing↗

A Simulation Architecture for Air Traffic Over Urban Environments Supporting Autonomy Research in Advanced Air Mobility

As part of its research, NASA investigates concepts, aircraft, and operations related to Advanced Air Mobility (AAM). One of the most challenging scenarios for AAM will be enabling safe routine access near densely populated urban centers. AAM flight operations over a regional area require a moderately high-fidelity simulation capability to develop and evaluate autonomy technologies in the urban environment. This paper aims to describe a system to simulate flight operations around regions such as the San Francisco-Oakland Bay area at a moderately-high scale (tens to hundreds of flights) that incorporates detailed vehicle models and control necessary to support research in airborne autonomy. The flight vehicle utilizes NASA AAM concept vehicle dynamics integrated with a custom flight management system and flight control system to simulate all flight phases accurately. The simulation incorporates a detailed simulated urban environment and includes glass cockpit displays to monitor aircraft operations. Simulation models integrate to simulate air and ground-based sensors, such as Radar and LiDAR. As a commercially available rendering engine, X-Plane 11 is used as the renderer to simulate vision-based sensors (such as onboard and ground-based cameras) with a detailed graphical model of a city at different times of the day and weather conditions. This paper presents the simulation and software architecture used for simulating AAM traffic over this urban region. This system enables the evaluation of NASA research concepts in autonomy for urban AAM operations on the path toward flight test evaluation.

Distributed sensing↗

Monitoring Drought Conditions in the Navajo Nation Using NASA Earth Observations

The Navajo Nation, a 65,700 sq km Native American territory located in the southwestern United States, has been increasingly impacted by severe drought events and changes in climate. These events are coupled with a lack of domestic water infrastructure and economic resources, leaving approximately one-third of the population without access to potable water in their homes. Current methods of monitoring drought are dependent on state-based monthly Standardized Precipitation Index value maps calculated by the Western Regional Climate Center. However, these maps do not provide the spatial resolution needed to illustrate differences in drought severity across the vast Nation. To better understand and monitor drought events and drought regime changes in the Navajo Nation, this project created a geodatabase of historical climate information specific to the area, and a decision support tool to calculate average Standardized Precipitation Index values for user-specified areas. The tool and geodatabase use Tropical Rainfall Monitoring Mission (TRMM) and Global Precipitation Monitor (GPM) observed precipitation data and Parameter-elevation Relationships on Independent Slopes Model modeled historical precipitation data, as well as NASA's modeled Land Data Assimilation Systems deep soil moisture, evaporation, and transpiration data products. The geodatabase and decision support tool will allow resource managers in the Navajo Nation to utilize current and future NASA Earth observation data for increased decision-making capacity regarding future climate change impact on water resources.

Ly, Vickie↗

Experiment 1: Orbital Processing of High-Quality Zn-Alloyed CdTe Compound Semiconductors

Zinc-alloyed cadmium telluride (Zn:CdTe) crystals were grown in unit gravity and in microgravity for comparative analysis. Two crystals were grown on USML-1/STS-50 in 1992, and two additional crystals were grown on USML-2/STS-73 in 1995. The Crystal Growth Furnace (CGF) in the seeded Bridgman-Stockbarger crystal growth geometry was utilized on both missions. Crystals grown on USML-1/STS-50 were found to have solidified with partial wall contact due to the near-absence of the hydrostatic pressure in microgravity, a residual g-vector that was not axial, and the nonwetting sample/ampoule wetting conditions. Crystals grown on USML-2/STS-73 included: a sample/ampoule identical to the USML-1/STS-73 sample/ampoule, with the addition of a restraining spring to simulate hydrostatic pressure internally, and a tapered ampoule which accomplished 2.2 cm of crystal growth without wall contact. Infrared transmission of all ground and flight samples was found to be 63-66 percent, very close to the theoretical 66 percent, suggesting good stoichiometric control. Infrared microscopy confirmed that the primary precipitates were Te and their size (1-10 microns) and density suggested that the flight- and ground-base samples experienced similar thermal histories. Longitudinal macrosegregation, calculated using scaling analysis, was predicted to be low. Nearly diffusion controlled growth was achieved even in unit gravity and macrosegregation data could be fit with a diffusion controlled model. Radial segregation was monitored and was found to vary with fraction solidified, particularly through the shoulder region, where the sample cross section was varying significantly. It was also disturbed in the flight samples in regions where asymmetric wall contact was noted. In regions where a steady state was established, the radial segregation was invariant within our experimental measurement error. Flight samples were found to be much higher in structural perfection than samples processed in unit gravity under identical growth conditions. In regions where solidification had occurred without wall contact, the free surfaces evidenced virtually no twinning, although twins appeared in the flight samples in regions of wall contact and were pervasive in the ground samples. These results were confirmed using optical microscopy and synchrotron x-ray white beam topography. Full-width half-maximum rocking curve widths (FWHM), recorded in arc-seconds, were significantly reduced from 20 a-s (1 g) to 9 a-s (micro-g) for the best regions of the crystals. The 9 a-s (FWHM) rocking curve value in the unconfined flight samples equals the best value reported terrestrially for this material. The ground samples exhibited a fully developed (111)[110] dislocation mosaic structure, whereas dislocations within the flight samples were discrete and no mosaic structure was evident. The defect density was quantitatively reduced from 75,000 (1 g) to 800 (micro-g) +/-50 percent. Dislocation etch pit density results were confirmed using transmission synchrotron white beam and monochromated beam topography. The low defect density is thought to have resulted from the near absence of hydrostatic pressure, which allowed the molten boule to solidify with little or no wall contact. This minimized the transfer of hoop stresses during solidification and post-solidification processing.

Larson, D. J., Jr.↗

SEMS: System for Environmental Monitoring and Sustainability

The goal of this project was to establish a computational and data management system, SEMS, building on our existing system and MTPE-related research. We proposed that the new system would help support Washington University's efforts in environmental sustainability through use in: (a) Problem-based environmental curriculum for freshmen and sophomores funded by the Hewlett Foundation that integrates scientific, cultural, and policy perspectives to understand the dynamics of wetland degradation, deforestation, and desertification and that will develop policies for sustainable environments and economies; (b) Higher-level undergraduate and graduate courses focused on monitoring the environment and developing policies that will lead to sustainable environmental and economic conditions; and (c) Interdisciplinary research focused on the dynamics of the Missouri River system and development of policies that lead to sustainable environmental and economic floodplain conditions.

Arvidson, Raymond E.↗

Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate expected sensor values for targeted fault scenarios. Taken together, this information provides an efficient condensation of the engineering experience and engine flow physics needed for sensor selection. The systematic sensor selection strategy is composed of three primary algorithms. The core of the selection process is a genetic algorithm that iteratively improves a defined quality measure of selected sensor suites. A merit algorithm is employed to compute the quality measure for each test sensor suite presented by the selection process. The quality measure is based on the fidelity of fault detection and the level of fault source discrimination provided by the test sensor suite. An inverse engine model, whose function is to derive hardware performance parameters from sensor data, is an integral part of the merit algorithm. The final component is a statistical evaluation algorithm that characterizes the impact of interference effects, such as control-induced sensor variation and sensor noise, on the probability of fault detection and isolation for optimal and near-optimal sensor suites.

Source record↗

A Tool Measuring Remaining Thickness of Notched Acoustic Cavities in Primary Reaction Control Thruster NDI Standards

Stress corrosion cracking in the relief radius area of a space shuttle primary reaction control thruster is an issue of concern. The current approach for monitoring of potential crack growth is nondestructive inspection (NDI) of remaining thickness (RT) to the acoustic cavities using an eddy current or remote field eddy current probe. EDM manufacturers have difficulty in providing accurate RT calibration standards. Significant error in the RT values of NDI calibration standards could lead to a mistaken judgment of cracking condition of a thruster under inspection. A tool based on eddy current principle has been developed to measure the RT at each acoustic cavity of a calibration standard in order to validate that the standard meets the sample design criteria.

Sun, Yushi↗

Validation of SO2 Retrievals from the Ozone Monitoring Instrument over NE China

The Dutch-Finnish Ozone Monitoring Instrument (OMI) launched on the NASA Aura satellite in July 2004 offers unprecedented spatial resolution, coupled with contiguous daily global coverage, for space-based UV measurements of sulfur dioxide (SO2). We present a first validation of the OMI SO2 data with in situ aircraft measurements in NE China in April 2005. The study demonstrates that OMI can distinguish between background SO2 conditions and heavy pollution on a daily basis. The noise (expressed as the standard deviation,sigma) is approximately 1.5 DU (Dobson units; 1 DU = 2.69 10 (exp 16) molecules/cm (exp 2)) for instantaneous field of view boundary layer (PBL) SO2 data. Temporal and spatial averaging can reduce the noise to sigma approximetly 0.3 DU over a remote region of the South Pacific; the long-term average over this remote location was within 0.1 DU of zero. Under polluted conditions collection 2 OMI data are higher than aircraft measurements by a factor of two. Improved calibrations of the radiance and irradiance data (collection 3) result in better agreement with aircraft measurements on polluted days. The air mass corrected collection 3 data still show positive bias and sensitivity to UV absorbing aerosols. The difference between the in situ data and the OMI SO2 measurements within 30 km of the aircraft profiles was about 1 DU, equivalent to approximately 5 ppb from 0 to 3000 m altitude. Quantifying the SO2 and aerosol profiles and spectral dependence of aerosol absorption between 310 and 330 nm are critical for an accurate estimate of SO2 from satellite UV measurements.

Krotkov, Nickolay A.↗

Use of TEMPO as a Proxy for Hyperspectral Geostationary Ocean Color Measurements from the GeoXO OCX Instrument: Harnessing Machine Learning and Principal Component Techniques for Atmospheric and Glint Correction

Retrievals of ocean color from space are important for better understanding the ocean ecosystem. The launch of atmospheric geostationary hyperspectral sensors such as TEMPO, provides a unique opportunity to examine the diurnal variability in ocean ecology. While TEMPO does not have as high spatial resolution or full spectral coverage as planned coastal ocean sensors such as the Geosynchronous Littoral Imaging and Monitoring Radiometer (GLIMR) or GeoXO Ocean Color instrument (OCX), its hourly measurements provide coverage of regions such as Lake Erie and the Gulf of Mexico at spatial scales of approximately 5 km. These data can be useful for testing new algorithms. We will apply our newly developed machine learning based atmospheric correction approach for ocean color retrievals to TEMPO data. Our approach begins by decomposing measured radiances from hyperspectral sensors into spectral features that describe the scattering and absorption of the atmosphere as well as the underlying surface reflectance. The coefficients of the principal components are then used to train a neural network to predict ocean color properties derived from collocated MODIS/VIIRS physically-based retrievals. This machine learning approach does not rely on radiative transfer modeling, and the use of MODIS/VIIRS data for training accounts for possible calibration b in hyperspectral data. Previously, we applied our approach using blue and UV wavelengths with the Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) to show that it can estimate ocean color properties in less-than-ideal conditions such as lightly to moderately clouded conditions as well as sun glint and thus improve the spatial coverage of ocean color measurements. TEMPO provides an opportunity to improve on this approach since it will provide collocated measurements at green and red wavelengths that were not available from OMI and TROPOMI and are important particularly for coastal waters. Additionally, our technique can be applied early in the mission and has potential to demonstrate the value of near real time ocean color products that are important for monitoring of harmful algae blooms and other oceanic phenomena.

Zachary Fasnacht↗

Predeployment validation of fault-tolerant systems through software-implemented fault insertion

Fault injection-based automated testing (FIAT) environment, which can be used to experimentally characterize and evaluate distributed realtime systems under fault-free and faulted conditions is described. A survey is presented of validation methodologies. The need for fault insertion based on validation methodologies is demonstrated. The origins and models of faults, and motivation for the FIAT concept are reviewed. FIAT employs a validation methodology which builds confidence in the system through first providing a baseline of fault-free performance data and then characterizing the behavior of the system with faults present. Fault insertion is accomplished through software and allows faults or the manifestation of faults to be inserted by either seeding faults into memory or triggering error detection mechanisms. FIAT is capable of emulating a variety of fault-tolerant strategies and architectures, can monitor system activity, and can automatically orchestrate experiments involving insertion of faults. There is a common system interface which allows ease of use to decrease experiment development and run time. Fault models chosen for experiments on FIAT have generated system responses which parallel those observed in real systems under faulty conditions. These capabilities are shown by two example experiments each using a different fault-tolerance strategy.

Czeck, Edward W.↗

Health Monitoring and Prognostics in Li-ion Batteries

Space applications need to overcome a very critical challenge of predicting remaining useful life of its critical systems/subsystems, with batteries being one of them. Batteries, power electronics conditioning system and motors and one of the most critical systems. Similarly in case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to accurately predict the future state of any system, it is required to possess knowledge of its current and future operations. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prior stated prediction problem. Two approaches are presented with battery prognostics application. The first approach presentation covers a physics based-modeling approach implemented for battery prognostics. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making. A second hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems i.e. batteries is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Batteries↗

Structural Loading on the QCM/SAW Instrument Aboard the ER-2 Used for Atmospheric Testing

Several experiments have been proposed to capture and evaluate samples of the atmosphere where SST's travel. One means to achieve this is to utilize the quartz crystal microbalance (QCM) / surface acoustical wave (SAW) instrument installed aboard the ER-2, formerly the U-2 reconnaissance aircraft. The QCM is a cascade impactor designed to perform in-situ, real-time measurements of aerosols and chemical vapors at an altitude of 60,000-70,000 feet. The primary use of the ER-2 is by NASA for Earth resources to test new sensor systems before being placed aboard satellites. One of the main reasons the ER-2 is used for this flight experiment is its capability to fly approximately twelve miles above the sea level (can reach an altitude of 78,000 feet). Because the ER-2 operates at such a high altitude, it is of special interest to scientists interested in space exploration or supersonic aircraft. The purpose of some of the experiments is to extinct data from the atmosphere around the ER-2. For the current CSTEA flight experiment, the housing of the QCM is in a frame that connects to an outer pod that attaches to the fuselage of the ER-2. Due to the location of the QCM within the housing frame and the location of the pod on the ER-2, the pod and its contents are subject to structural loads. In addition to structural loads, structural vibrations are also of importance because the QCM output data is based on the determination of beat frequencies between a pair of oscillators (one coated, the second uncoated, according to the chemical reaction being monitored). A structural analysis of this system can indicate whether potential resonances may exist between the (higher) structural modal frequencies and the beat frequencies. In addition undesirable deformations may result due to maximum expected static or dynamic loads during typical flight conditions. If the deformations are excessive they may adversely affect the accuracy the instrumentation output.

Bainum, Peter M.↗