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All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Evidence-Based Approach to the Analysis of Serious Decompression Sickness with Application to EVA Astronauts

It is important to understand the risk of serious hypobaric decompression sickness (DCS) in order to develop procedures and treatment responses to mitigate the risk. Since it is not ethical to conduct prospective tests about serious DCS with humans, the necessary information was gathered from 73 published reports. We hypothesize that a 4-hr 100% oxygen (O2) prebreathe results in a very low risk of serious DCS, and test this through analysis. We evaluated 258 tests containing information from 79,366 exposures in attitude chambers. Serious DCS was documented in 918 men during the tests. Serious DCS are signs and symptoms broadly classified as Type II DCS. A risk function analysis with maximum likelihood optimization was performed to identify significant explanatory variables, and to create a predictive model for the probability of serious DCS [P(serious DCS)]. Useful variables were Tissue Ratio, the planned time spent at altitude (T(sub alt)), and whether or not repetitive exercise was performed at altitude. Tissue Ratio is P1N2/P2, where P1N2 is calculated nitrogen (N2) pressure in a compartment with a 180-min half-time for N2 pressure just before ascent, and P2 is ambient pressure after ascent. A prebreathe and decompression profile Shuttle astronauts use for extravehicular activity (EVA) includes a 4-hr prebreathe with 100% O2, an ascent to P2 = 4.3 lb per sq. in. absolute, and a T(sub alt) = 6 hr. The P(serious DCS) is: 0.0014 (0.00096 - 0.00196, 95% confidence interval) with exercise and 0.00025 (0.00016 - 0.00035) without exercise. Given 100 Shuttle EVAs to date and no report of serious DCS, the true risk is less than 0.03 with 95% confidence (Binomial Theorem). It is problematic to estimate the risk of serious DCS since it appears infrequently, even if the estimate is based on thousands of altitude chamber exposures. The true risk to astronauts may lie between the extremes of the confidence intervals (0.00016 - 0.00196) since the contribution of other factors, particularly exercise, to the risk of serious DCS during EVA is unknown. A simple model that only accounts for four important variables in retrospective data is still helpful to increase our understanding about the risk of serious DCS.

Conkin, Johnny↗
NASA NTRS2001

Rotation of EOFs by the Independent Component Analysis: Towards A Solution of the Mixing Problem in the Decomposition of Geophysical Time Series

The Independent Component Analysis is a recently developed technique for component extraction. This new method requires the statistical independence of the extracted components, a stronger constraint that uses higher-order statistics, instead of the classical decorrelation, a weaker constraint that uses only second-order statistics. This technique has been used recently for the analysis of geophysical time series with the goal of investigating the causes of variability in observed data (i.e. exploratory approach). We demonstrate with a data simulation experiment that, if initialized with a Principal Component Analysis, the Independent Component Analysis performs a rotation of the classical PCA (or EOF) solution. This rotation uses no localization criterion like other Rotation Techniques (RT), only the global generalization of decorrelation by statistical independence is used. This rotation of the PCA solution seems to be able to solve the tendency of PCA to mix several physical phenomena, even when the signal is just their linear sum.

Aires, Filipe↗
NASA NTRS2000

Rotation of EOFs by the Independent Component Analysis: Towards a Solution of the Mixing Problem in the Decomposition of Geophysical Time Series

The Independent Component Analysis is a recently developed technique for component extraction. This new method requires the statistical independence of the extracted components, a stronger constraint that uses higher-order statistics, instead of the classical decorrelation, a weaker constraint that uses only second-order statistics. This technique has been used recently for the analysis of geophysical time series with the goal of investigating the causes of variability in observed data (i.e. exploratory approach). We demonstrate with a data simulation experiment that, if initialized with a Principal Component Analysis, the Independent Component Analysis performs a rotation of the classical PCA (or EOF) solution. This rotation uses no localization criterion like other Rotation Techniques (RT), only the global generalization of decorrelation by statistical independence is used. This rotation of the PCA solution seems to be able to solve the tendency of PCA to mix several physical phenomena, even when the signal is just their linear sum.

Aires, Filipe↗
NASA NTRS2003

Three-dimensional ocular kinematics during eccentric rotations: evidence for functional rather than mechanical constraints

Previous studies have reported that the translational vestibuloocular reflex (TVOR) follows a three-dimensional (3D) kinematic behavior that is more similar to visually guided eye movements, like pursuit, rather than the rotational VOR (RVOR). Accordingly, TVOR rotation axes tilted with eye position toward an eye-fixed reference frame rather than staying relatively fixed in the head like in the RVOR. This difference arises because, contrary to the RVOR where peripheral image stability is functionally important, the TVOR like pursuit and saccades cares to stabilize images on the fovea. During most natural head and body movements, both VORs are simultaneously activated. In the present study, we have investigated in rhesus monkeys the 3D kinematics of the combined VOR during yaw rotation about eccentric axes. The experiments were motivated by and quantitatively compared with the predictions of two distinct hypotheses. According to the first (fixed-rule) hypothesis, an eye-position-dependent torsion is computed downstream of a site for RVOR/TVOR convergence, and the combined VOR axis would tilt through an angle that is proportional to gaze angle and independent of the relative RVOR/TVOR contributions to the total eye movement. This hypothesis would be consistent with the recently postulated mechanical constraints imposed by extraocular muscle pulleys. According to the second (image-stabilization) hypothesis, an eye-position-dependent torsion is computed separately for the RVOR and the TVOR components, implying a processing that takes place upstream of a site for RVOR/TVOR convergence. The latter hypothesis is based on the functional requirement that the 3D kinematics of the combined VOR should be governed by the need to keep images stable on the fovea with slip on the peripheral retina being dependent on the different functional goals of the two VORs. In contrast to the fixed-rule hypothesis, the data demonstrated a variable eye-position-dependent torsion for the combined VOR that was different for synergistic versus antagonistic RVOR/TVOR interactions. Furthermore, not only were the eye-velocity tilt slopes of the combined VOR as much as 10 times larger than what would be expected based on extraocular muscle pulley location, but also eye velocity during antagonistic RVOR/TVOR combinations often tilted opposite to gaze. These results are qualitatively and quantitatively consistent with the image-stabilization hypothesis, suggesting that the eye-position-dependent torsion is computed separately for the RVOR and the TVOR and that the 3D kinematics of the combined VOR are dependent on functional rather than mechanical constraints.

Non-NASA Center↗
NASA NTRS2006

The Virtual Space Physics Observatory: Quick Access to Data and Tools

The Virtual Space Physics Observatory (VSPO; see http://vspo.gsfc.nasa.gov) has grown to provide a way to find and access about 375 data products and services from over 100 spacecraft/observatories in space and solar physics. The datasets are mainly chosen to be the most requested, and include most of the publicly available data products from operating NASA Heliophysics spacecraft as well as from solar observatories measuring across the frequency spectrum. Service links include a "quick orbits" page that uses SSCWeb Web Services to provide a rapid answer to questions such as "What spacecraft were in orbit in July 1992?" and "Where were Geotail, Cluster, and Polar on 2 June 2001?" These queries are linked back to the data search page. The VSPO interface provides many ways of looking for data based on terms used in a registry of resources using the SPASE Data Model that will be the standard for Heliophysics Virtual Observatories. VSPO itself is accessible via an API that allows other applications to use it as a Web Service; this has been implemented in one instance using the ViSBARD visualization program. The VSPO will become part of the Space Physics Data Facility, and will continue to expand its access to data. A challenge for all VOs will be to provide uniform access to data at the variable level, and we will be addressing this question in a number of ways.

Cornwell, Carl↗
NASA NTRS2008

Residual Strahls in Solar Wind Electron Dropouts: Signatures of Magnetic Connection to the Sun, Disconnection, or Interchange Reconnection?

A recent assessment of suprathermal electron heat flux dropouts (HFDs) in the solar wind eliminated 90% as possible signatures of field lines disconnected from the Sun at both ends (Pagel et al., 2005b). The primary reason for elimination was the presence of a residual field-aligned strahl presumably signaling field lines connected to the Sun. Using high-time-resolution data from the Wind spacecraft, this paper tests whether the residual strahls were an artifact of averaging over pitch angle distributions (PADs) with and without strahls. An automated search for PADs without strahls (flat PADs) yields an occurrence rate of only 14% within HFDs, but a detailed case study shows that these flat PADs are imbedded within intervals of nearly flat PADs, that is, PADS with residual strahls that cannot be artifacts of averaging. An attractive alternative is that the residual strahls result from intermixing of originally back-scattered fluxes (haloes) of unequal intensities on field lines that have either disconnected or interchange reconnected at the Sun. A reevaluation of reported streaming of higher-energy electrons in HFDs suggests a similar cause. While the high-time-resolution data show high variability of PAD profiles within HFDs, this paper reopens the possibility that a substantial fraction signal disconnection or interchange reconnection. Estimated occurrence rates of fields having undergone these processes based upon published HFD rates are of the same order of magnitude as the surprisingly low values of 1-5% recently predicted by a model of a balanced heliospheric flux budget (Owens and Crooker, 2007).

Crooker, N. U.↗
NASA NTRS2011

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↗
NASA NTRS2012

Assessment of Global Cloud Datasets from Satellites: Project and Database Initiated by the GEWEX Radiation Panel

Clouds cover about 70% of the Earth's surface and play a dominant role in the energy and water cycle of our planet. Only satellite observations provide a continuous survey of the state of the atmosphere over the whole globe and across the wide range of spatial and temporal scales that comprise weather and climate variability. Satellite cloud data records now exceed more than 25 years in length. However, climatologies compiled from different satellite datasets can exhibit systematic biases. Questions therefore arise as to the accuracy and limitations of the various sensors. The Global Energy and Water cycle Experiment (GEWEX) Cloud Assessment, initiated in 2005 by the GEWEX Radiation Panel, provided the first coordinated intercomparison of publically available, standard global cloud products (gridded, monthly statistics) retrieved from measurements of multi-spectral imagers (some with multiangle view and polarization capabilities), IR sounders and lidar. Cloud properties under study include cloud amount, cloud height (in terms of pressure, temperature or altitude), cloud radiative properties (optical depth or emissivity), cloud thermodynamic phase and bulk microphysical properties (effective particle size and water path). Differences in average cloud properties, especially in the amount of high-level clouds, are mostly explained by the inherent instrument measurement capability for detecting and/or identifying optically thin cirrus, especially when overlying low-level clouds. The study of long-term variations with these datasets requires consideration of many factors. A monthly, gridded database, in common format, facilitates further assessments, climate studies and the evaluation of climate models.

Stubenrauch, C. J.↗
NASA NTRS2014

From Earth to Space: Application of Biological Treatment for the Removal of Ammonia from Water

Managing ammonia is often a challenge in both drinking water and wastewater treatment facilities. Ammonia is unregulated in drinking water, but its presence may result in numerous water quality issues in the distribution system such as loss of residual disinfectant, nitrification, and corrosion. Ammonia concentrations need to be managed in wastewater effluent to sustain the health of receiving water bodies. Biological treatment involves the microbiological oxidation of ammonia to nitrate through a two‐step process. While nitrification is common in the environment, and nitrifying bacteria can grow rapidly on filtration media, appropriate conditions, such as the presence of dissolved oxygen and required nutrients, need to be established. This presentation will highlight results from two ongoing research programs - one at NASA's Johnson Space Center, and the other at a drinking water facility in California. Both programs are designed to demonstrate nitrification through biological treatment. The objective of NASA's research is to be able to recycle wastewater to potable water for spaceflight mission. To this end, a biological water processor (BWP) has been integrated with a forward osmosis secondary treatment system (FOST). Bacteria mineralize organic carbon to carbon dioxide as well as ammonia‐nitrogen present in the wastewater to nitrogen gas, through a combination of nitrification and denitrification. The effluent from the BWP system is low in organic contaminants, but high in total dissolved solids. The FOST system, integrated downstream of the BWP, removes dissolved solids through a combination of concentration‐driven forward osmosis and pressure driven reverse osmosis. The integrated system testing planned for this year is expected to produce water that requires only a polishing step to meet potable water requirements for spaceflight. The pilot study in California is being conducted on Golden State Water Company's Yukon wellsthat have hydrogen sulfide odor, color, total organic carbon, bromide, iron and manganese in addition to ammonia. A treatment evaluation, conducted in 2011, recommended the testing of biological oxidation filtration for the removal of ammonia and production of biologically stable water. A 8‐month pilot testing program was conducted to develop and optimize key design and operational variables. Steadystate operational data was collected to demonstrate long‐term performance and inform California Department of Public Health permitting of the full‐scale process. As ammonia continues to present challenges to water and wastewater systems, innovative strategies such as biological treatment can be applied to successfully manage it. This presentation will discuss application of cutting‐age research being conducted by NASA that will bridge existing information gaps, and benefit municipal utilities.

Ghosh, Amlan↗
NASA NTRS2014

From Earth to Space: Application of Biological Treatment for the Removal of Ammonia from Water

Managing ammonia is often a challenge in both drinking water and wastewater treatment facilities. Ammonia is unregulated in drinking water, but its presence may result in numerous water quality issues in the distribution system such as loss of residual disinfectant, nitrification, and corrosion. Ammonia concentrations need to be managed in wastewater effluent to sustain the health of receiving water bodies. Biological treatment involves the microbiological oxidation of ammonia to nitrate through a two‐step process. While nitrification is common in the environment, and nitrifying bacteria can grow rapidly on filtration media, appropriate conditions, such as the presence of dissolved oxygen and required nutrients, need to be established. This presentation will highlight results from two ongoing research programs - one at NASA's Johnson Space Center, and the other at a drinking water facility in California. Both programs are designed to demonstrate nitrification through biological treatment. The objective of NASA's research is to be able to recycle wastewater to potable water for spaceflight missions. To this end, a biological water processor (BWP) has been integrated with a forward osmosis secondary treatment system (FOST). Bacteria mineralize organic carbon to carbon dioxide as well as ammonia‐nitrogen present in the wastewater to nitrogen gas, through a combination of nitrification and denitrification. The effluent from the BWP system is low in organic contaminants, but high in total dissolved solids. The FOST system, integrated downstream of the BWP, removes dissolved solids through a combination of concentration‐driven forward osmosis and pressure driven reverse osmosis. The integrated system testing planned for this year is expected to produce water that requires only a polishing step to meet potable water requirements for spaceflight. The pilot study in California is being conducted on Golden State Water Company's Yukon wells that have hydrogen sulfide odor, color, total organic carbon, bromide, iron and manganese in addition to ammonia. A treatment evaluation, conducted in 2011, recommended the testing of biological oxidation filtration for the removal of ammonia and production of biologically stable water. An 8‐month pilot testing program was conducted to develop and optimize key design and operational variables. Steadystate operational data was collected to demonstrate long‐term performance and inform California Department of Public Health permitting of the full‐scale process. As ammonia continues to present challenges to water and wastewater systems, innovative strategies such as biological treatment can be applied to successfully manage it. This presentation will discuss application of cutting‐age research being conducted by NASA that will bridge existing information gaps, and benefit municipal utilities.

Pickering, Karen↗
NASA NTRS2013

Arctic Tundra Vegetation Functional Types Based on Photosynthetic Physiology and Optical Properties

Non-vascular plants (lichens and mosses) are significant components of tundra landscapes and may respond to climate change differently from vascular plants affecting ecosystem carbon balance. Remote sensing provides critical tools for monitoring plant cover types, as optical signals provide a way to scale from plot measurements to regional estimates of biophysical properties, for which spatial-temporal patterns may be analyzed. Gas exchange measurements were collected for pure patches of key vegetation functional types (lichens, mosses, and vascular plants) in sedge tundra at Barrow, AK. These functional types were found to have three significantly different values of light use efficiency (LUE) with values of 0.013 plus or minus 0.0002, 0.0018 plus or minus 0.0002, and 0.0012 plus or minus 0.0001 mol C mol (exp -1) absorbed quanta for vascular plants, mosses and lichens, respectively. Discriminant analysis of the spectra reflectance of these patches identified five spectral bands that separated each of these vegetation functional types as well as nongreen material (bare soil, standing water, and dead leaves). These results were tested along a 100 m transect where midsummer spectral reflectance and vegetation coverage were measured at one meter intervals. Along the transect, area-averaged canopy LUE estimated from coverage fractions of the three functional types varied widely, even over short distances. The patch-level statistical discriminant functions applied to in situ hyperspectral reflectance data collected along the transect successfully unmixed cover fractions of the vegetation functional types. The unmixing functions, developed from the transect data, were applied to 30 m spatial resolution Earth Observing-1 Hyperion imaging spectrometer data to examine variability in distribution of the vegetation functional types for an area near Barrow, AK. Spatial variability of LUE was derived from the observed functional type distributions. Across this landscape, a fivefold variation in tundra LUE was observed. LUE calculated from the functional type cover fractions was also correlated to a spectral vegetation index developed to detect vegetation chlorophyll content. The concurrence of these alternate methods suggest that hyperspectral remote sensing can distinguish functionally distinct vegetation types and can be used to develop regional estimates of photosynthetic LUE in tundra landscapes.

VEGETATION↗
NASA NTRS2016

Multispacecraft Observations and Modeling of the 22/23 June 2015 Geomagnetic Storm

The magnetic storm of 22-23 June 2015 was one of the largest in the current solar cycle. We present in situ observations from the Magnetospheric Multiscale Mission (MMS) and the Van Allen Probes (VAP) in the magnetotail, field-aligned currents from AMPERE (Active Magnetosphere and Planetary Electrodynamics Response), and ionospheric flow data from Defense Meteorological Satellite Program (DMSP). Our real-time space weather alert system sent out a "red alert," correctly predicting Kp indices greater than 8. We show strong outflow of ionospheric oxygen, dipolarizations in the MMS magnetometer data, and dropouts in the particle fluxes seen by the MMS Fast Plasma Instrument suite. At ionospheric altitudes, the AMPERE data show highly variable currents exceeding 20 MA. We present numerical simulations with the Block Adaptive Tree-Solarwind - Roe - Upwind Scheme (BATS-R-US) global magnetohydrodynamic model linked with the Rice Convection Model. The model predicted the magnitude of the dipolarizations, and varying polar cap convection patterns, which were confirmed by DMSP measurements.

Reiff, P. H.↗
NASA NTRS2017

Operational Implementation of Sea Ice Concentration Estimates from the AMSR2 Sensor

An operation implementation of a passive microwave sea ice concentration algorithm to support NOAA's operational mission is presented. The NASA team 2 algorithm, previously developed for the NASA advanced microwave scanning radiometer for the Earth observing system (AMSR-E) product suite, is adapted for operational use with the JAXA AMSR2 sensor through several enhancements. First, the algorithm is modified to process individual swaths and provide concentration from the most recent swaths instead of a 24-hour average. A latency (time since observation) field and a 24-hour concentration range (maximum-minimum) are included to provide indications of data timeliness and variability. Concentration from the Bootstrap algorithm is a secondary field to provide complementary sea ice information. A quality flag is implemented to provide information on interpolation, filtering, and other quality control steps. The AMSR2 concentration fields are compared with a different AMSR2 passive microwave product, and then validated via comparison with sea ice concentration from the Suomi visible and infrared imaging radiometer suite. This validation indicates the AMSR2 concentrations have a bias of 3.9% and an RMSE of 11.0% in the Arctic, and a bias of 4.45% and RMSE of 8.8% in the Antarctic. In most cases, the NOAA operational requirements for accuracy are met. However, in low-concentration regimes, such as during melt and near the ice edge, errors are higher because of the limitations of passive microwave sensors and the algorithm retrieval.

Arctic↗
NASA NTRS2018

The Kepler Light Curves of AGN: A Detailed Analysis

We present a comprehensive analysis of 21 light curves of Type 1 active galactic nuclei (AGN) from the Kepler spacecraft. First, we describe the necessity and development of a customized pipeline for treating Kepler data of stochastically variable sources like AGN. We then present the light curves, power spectral density functions (PSDs), and flux histograms. The light curves display an astonishing variety of behaviors, many of which would not be detected in ground-based studies, including switching between distinct flux levels. Six objects exhibit PSD flattening at characteristic timescales that roughly correlate with black hole mass. These timescales are consistent with orbital timescales or free-fall accretion timescales. We check for correlations of variability and high-frequency PSD slope with accretion rate, black hole mass, redshift, and luminosity. We find that bolometric luminosity is anticorrelated with both variability and steepness of the PSD slope. We do not find evidence of the linear rms-flux relationships or lognormal flux distributions found in X-ray AGN light curves, indicating that reprocessing is not a significant contributor to optical variability at the 0.1%-10% level.

power spectral density functions(PSDs)↗
NASA NTRS2018

Quantifying Long-Term Changes in Carbon Stocks and Forest Structure from Amazon Forest Degradation

Despite sustained declines in Amazon deforestation, forest degradation from logging and firecontinues to threaten carbon stocks, habitat, and biodiversity in frontier forests along the Amazon arcof deforestation. Limited data on the magnitude of carbon losses and rates of carbon recoveryfollowing forest degradation have hindered carbon accounting efforts and contributed to incompletenational reporting to reduce emissions from deforestation and forest degradation (REDD+). Wecombined annual time series of Landsat imagery and high-density airborne lidar data to characterizethe variability, magnitude, and persistence of Amazon forest degradation impacts on abovegroundcarbon density (ACD) and canopy structure. On average, degraded forests contained 45.1% of thecarbon stocks in intact forests, and differences persisted even after 15 years of regrowth. Incomparison to logging, understory fires resulted in the largest and longest-lasting differences in ACD.Heterogeneity in burned forest structure varied by fire severity and frequency. Forests with a historyof one, two, and three or more fires retained only 54.4%, 25.2%, and 7.6% of intact ACD,respectively, when measured after a year of regrowth. Unlike the additive impact of successive fires,selective logging before burning did not explain additional variability in modeled ACD loss andrecovery of burned forests. Airborne lidar also provides quantitative measures of habitat structure thatcan aid the estimation of co-benefits of avoided degradation. Notably, forest carbon stocks recoveredfaster than attributes of canopy structure that are critical for biodiversity in tropical forests, includingthe abundance of tall trees. We provide the first comprehensive look-up table of emissions factors forspecific degradation pathways at standard reporting intervals in the Amazon. Estimated carbon lossand recovery trajectories provide an important foundation for assessing the long-term contributionsfrom forest degradation to regional carbon cycling and advance our understanding of the currentstate of frontier forests.

Rappaport, Danielle I.↗
NASA NTRS2019

Modeling Atmosphere-Ocean Radiative Transfer: A PACE Mission Perspective

The research frontiers of radiative transfer (RT) in coupled atmosphere-ocean systems are explored to enable new science and specifically to support the upcoming Plankton, Aerosol, Cloud ocean Ecosystem (PACE) satellite mission. Given (i) the multitude of atmospheric and oceanic constituents at any given moment that each exhibits a large variety of physical and chemical properties and (ii) the diversity of light-matter interactions (scattering, absorption, and emission), tackling all outstanding RT aspects related to interpreting and/or simulating light reflected by atmosphere-ocean systems becomes impossible. Instead, we focus on both theoretical and experimental studies of RT topics important to the science threshold and goal questions of the PACE mission and the measurement capabilities of its instruments. We differentiate between (a) forward (FWD) RT studies that focus mainly on sensitivity to influencing variables and/or simulating data sets, and (b) inverse (INV) RT studies that also involve the retrieval of atmosphere and ocean parameters. Our topics cover (1) the ocean (i.e., water body): absorption and elastic/inelastic scattering by pure water (FWD RT) and models for scattering and absorption by particulates (FWD RT and INV RT); (2) the air-water interface: variations in ocean surface refractive index (INV RT) and in whitecap reflectance (INV RT); (3) the atmosphere: polarimetric and/or hyperspectral remote sensing of aerosols (INV RT) and of gases (FWD RT); and (4) atmosphere-ocean systems: benchmark comparisons, impact of the Earth's sphericity and adjacency effects on space-borne observations, and scattering in the ultraviolet regime (FWD RT). We provide for each topic a summary of past relevant (heritage) work, followed by a discussion (for unresolved questions) and RT updates.

Chowdhary, Jacek↗
NASA NTRS2019

Health Management and Prognostics for Electric Aircraft Powertrain

W and c Any air borne vehicle needs incorporating safety as key parameter of measure, and inclusion of autonomy raises the critical need for safety under autonomous operations. Management of faults and component degradation is key as complexity in autonomous operations grow over the period of time. Therefore, in addition to basic operational requirements, an autonomous electric vehicle should be able to make accurate estimates of its current system health and take the correct decisions to complete its mission successfully. Real-time safety and state-awareness tools are therefore essential for the vehicle to be able to reach its destination in a safe and successful manner. The need for safety assurance and health management capabilities is particularly relevant for aircraft electric propulsion systems, which are relatively new and with limited historical to learn. They are critical systems requiring high power density along with reliability, resilience, efficient management of weight, and operational costs. A model- based fault diagnosis and prognostics approach of complex critical systems can successfully accomplish the safety and state awareness goal for such electric propulsion systems, enabling autonomous decision making capability for safe and efficient operation. To identify critical components in the system a Qualitative Bayesian approach using FMECA is implemented. This requires the assessment of some quantities representing the state of the electric unmanned aerial systems (e-UAS), as well as look-ahead forecasts of such states during the entire flight, presented in form of safety metrics (SM). In-service data and performance data gathered from degraded components sup- ports diagnostic and prognostic methods for these systems, but this data can be difficult to obtain as weight and packaging restrictions reduce redundancy and instrumentation on-board the vehicle. Therefore, an model-based framework should be capable or operating with limited data. In addition to data scarcity, the variability of such complex critical systems re- quires the model-based framework to reason in the presence of uncertainty, such as sensor noise, and modeling imperfections. Quantification of errors and uncertainties in the measured states and quantities is therefore a fundamental step for a precise estimation of such SMs; un-modeled uncertainty may result in erroneous state assessment and un- reliable predictions of future states of e-UAVs. Typical, centralized model-based schemes suffer from inherent disadvantages such as computational complexity, single point of failure, and scalability issues, and therefore may fail in such a complex scenario. This paper presents a methodology for developing a system level diagnostics and prognostics approach using a Qualitative Bayesian FMECA approach along with a formal uncertainty management framework for an e-UAS. In this work we demonstrate the efficacy of the framework to predict effects of sub-system level degradation on vehicle operation incorporating uncertainty management to predict future behavior under different operating conditions.

Kulkarni, Chetan↗
NASA NTRS2017

Intermediate Fidelity Solid State Recorder Modeling for NISAR

At 26Tb/day return average, NISAR (National Aero- nautics and Space Administration (NASA) and the In- dian Space Research Organization (ISRO) Synthetic Aperture Radar) will stress ground station facilities with a variable cadence of data generation observing nearly all of earth's land and ice to produce global time- series maps of cryospheric, solid-Earth and ecosystem phenomena. Between the instrument data generation source and downlink sink lies the primary science data bu er, the SSR (Solid State Recorder). The SSR has deferred, discrete le deletion events that occur only after a le is played back to all required ground segments (sometimes both NASA and ISRO). A forward dispatch, advancing frontier repropagation playback scheduler is proposed as a model of the SSR's greedy playback scheduling behavior. Schedules based on the existing low delity model and new intermediate delity model are compared to assess the impact of deferred, discrete deletion on planning. The low delity model is found to produce unfeasible schedules that exceed SSR capacity, causing 3.87% of all observations in a 12 day simulation to be removed by repair actions.

Doubleday, Joshua R.↗