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NASA NTRSDate not supplied

The Transition of Satellite Observations Assimilated in GEOS to JEDI

The Goddard Earth Observing System (GEOS) is used by NASA’s Global Modeling and Assimilation Office (GMAO) to produce weather, climate, and air quality forecasts and reanalysis datasets. In order to incorporate the Joint Effort for Data assimilation Integration (JEDI) system into GEOS it is necessary to provide a validated set of input observations in JEDI. The GMAO, in collaboration with the Joint Center for Satellite Data Assimilation (JCSDA), is developing the Unified Forward Operator (UFO) in JEDI and adding all the necessary features to replicate the existing capability of the Gridpoint Statistical Interpolation (GSI)–based GEOS atmospheric data assimilations system. GMAO has been adding, validating, and updating procedures to assimilate the vast array of satellite and conventional observations assimilated in GEOS, including the GEOS all-sky microwave radiance assimilation framework to assimilate those observations in the UFO. Robust tests have been conducted to ensure correct configurations of observational data bias correction, quality control, and observation error in UFO and good agreements between UFO and GSI results. Our work on satellite observations will be reported in this presentation.

Jianjun Jin↗
NASA NTRS1992

Navier-Stokes calculation of transonic flow past the NTF 65-deg delta wing

Viscous flow past a wind tunnel model of a 65-degree swept angle Delta wing at transonic speeds is being studied. The model was tested in the 8-foot cryogenic transonic wind tunnel at the National Transonic Facility. Aerodynamic forces and wing surface pressure data were obtained at various angles of attack, Mach numbers, and Reynold's numbers for four different leading edges of the wing. The objectives of the present investigation are: (1) to perform numerical modeling of the flow around the wing; (2) to validate the experimental data with a Navier-Stokes computational fluid dynamics code and vice versa; (3) to investigate the effects of the sting mount of the wing; (4) to evaluate the effects of leading edge radius on the flow; and (5) to explain the Reynold's number effect as indicated by the test data. Several computer programs were developed to define the surfaces of the wing, the four leading edges, and the sting mount. Based on these geometric databases, the surface grids of a single-block computational domain was generated interactively on the IRIS workstation using the GRIDGEN2D module of GRIDGEN. To refine the grids and to avoid excessive loss of grid points due to collapsed edges, a 9-block computational domain containing approximately 750,000 grid points was developed with the GRIDBLOCK module to replace the single-block grid.

Wu, Chivey↗
NASA NTRS1994

Evaluation of current tropospheric mapping functions by Deep Space Network very long baseline interferometry

To compare the validity of current algorithms that map zenith tropospheric delay to arbitrary elevation angles, 10 different tropospheric mapping functions are used to analyze the current data base of Deep Space Network Mark 3 intercontinental very long baseline interferometric (VLBI) data. This analysis serves as a stringent test because of the high proportion of low-elevation observations necessitated by the extremely long baselines. Postfit delay and delay-rate residuals are examined, as well as the scatter of baseline lengths about the time-linear model that characterizes tectonic motion. Among the functions that utilize surface meteorological data as input parameters, the Lanyi 1984 mapping shows the best performance both for residuals and baselines, through the 1985 Davis function is statistically nearly identical. The next best performance is shown by the recent function of Niell, which is based on an examination of global atmospheric characteristics as a function of season and uses no weather data at the time of the measurements. The Niell function shows a slight improvement in residuals relative to Lanyi, but also an increase in baseline scatter that is significant for the California-Spain baseline. Two variants of the Chao mapping function, as well as the Chao tables used with the interpolation algorithm employed in the Orbit Determination Program software, show substandard behavior for both VLBI residuals and baseline scatter. The length of the California-Australia baseline (10,600 km) in the VLBI solution can vary by as much as 5 to 10 cm for the 10 mapping functions.

Sovers, O. J.↗
NASA NTRS1999

TRMM Field Campaigns: Objectives and Status Report

The Tropical Rainfall Measuring Mission (TRMM) satellite has been sending valuable data since launch in November 1997. Some of the key goals of the joint NASA (US) and NASDA (Japan) mission are: (1) to estimate the four-dimensional diabatic heating in the tropical and subtropical atmosphere, (2) understand the role of latent heating in driving tropical and extratropical circulations, (3) obtain monthly area-averaged estimates of rainfall over the data-sparse oceans, and (4) estimate the relative contribution of convective and stratiform precipitation over different regions during different seasons. The overarching scientific objective is to understand and improve estimates of rainfall and latent heating profiles throughout the global tropics. This requires observations for fundamental understanding of cloud dynamics and microphysics, as well as for validation, testing assumptions and error estimates of cloud-resolving models, forward radiative transfer models, algorithms used to estimate rainfall statistics and vertical structure of precipitation from surface-based radar, and from satellites. Field experiments designed to contribute to this understanding have been conducted in Texas and the South China Sea in spring of 1998, Florida in summer of 1998, and interior Brazil in (boreal) winter 1999. In summer 1999, a major oceanic campaign will be based at Kwajalein Atoll. Some early results will be highlighted, noting some significant contrasts between oceanic and continental convective systems.

Zipser, Edward I.↗
NASA NTRS2001

Electronic Model of a Ferroelectric Field Effect Transistor

A pair of electronic models has been developed of a Ferroelectric Field Effect transistor. These models can be used in standard electrical circuit simulation programs to simulate the main characteristics of the FFET. The models use the Schmitt trigger circuit as a basis for their design. One model uses bipolar junction transistors and one uses MOSFET's. Each model has the main characteristics of the FFET, which are the current hysterisis with different gate voltages and decay of the drain current when the gate voltage is off. The drain current from each model has similar values to an actual FFET that was measured experimentally. T'he input and o Output resistance in the models are also similar to that of the FFET. The models are valid for all frequencies below RF levels. No attempt was made to model the high frequency characteristics of the FFET. Each model can be used to design circuits using FFET's with standard electrical simulation packages. These circuits can be used in designing non-volatile memory circuits and logic circuits and is compatible with all SPICE based circuit analysis programs. The models consist of only standard electrical components, such as BJT's, MOSFET's, diodes, resistors, and capacitors. Each model is compared to the experimental data measured from an actual FFET.

MacLeod, Todd C.↗
NASA NTRS2001

Advanced Thin Ionization Calorimeter (ATIC) Balloon Experiment

During grant NAG5-5064, Louisiana State University (LSU) led the ATIC team in the development, construction, testing, accelerator validation, pre-deployment integration and flight operations of the Advanced Thin Ionization Calorimeter (ATIC) Balloon Experiment. This involved interfacing among the ATIC collaborators (UMD, NRL/MSFC, SU, MSU, WI, SNU) to develop a new balloon payload based upon a fully active calorimeter, a carbon target, a scintillator strip hodoscope and a pixilated silicon solid state detector for a detailed investigation of the very high energy cosmic rays to energies beyond 10(exp 14) eV/nucleus. It is in this very high energy region that theory predicts changes in composition and energy spectra related to the Supernova Remnant Acceleration model for cosmic rays below the "knee" in the all-particle spectrum. This report provides a documentation list, details the anticipated ATIC science return, describes the particle detection principles on which the experiment is based, summarizes the simulation results for the system, describes the validation work at the CERN SPS accelerator and details the balloon flight configuration. The ATIC experiment had a very successful LDB flight from McMurdo, Antarctica in 12/00 - 1/01. The instrument performed well for the entire 15 days. Preliminary data analysis shows acceptable charge resolution and an all-particle power law energy deposition distribution not inconsistent with previous measurements. Detailed analysis is underway and will result in new data on the cosmic ray charge and energy spectra in the GeV - TeV energy range. ATIC is currently being refurbished in anticipation of another LDB flight in the 2002-03 period.

Wefel, John P.↗
NASA NTRS2011

Supersonic Retro-Propulsion Experimental Design for Computational Fluid Dynamics Model Validation

The development of supersonic retro-propulsion, an enabling technology for heavy payload exploration missions to Mars, is the primary focus for the present paper. A new experimental model, intended to provide computational fluid dynamics model validation data, was recently designed for the Langley Research Center Unitary Plan Wind Tunnel Test Section 2. Pre-test computations were instrumental for sizing and refining the model, over the Mach number range of 2.4 to 4.6, such that tunnel blockage and internal flow separation issues would be minimized. A 5-in diameter 70-deg sphere-cone forebody, which accommodates up to four 4:1 area ratio nozzles, followed by a 10-in long cylindrical aftbody was developed for this study based on the computational results. The model was designed to allow for a large number of surface pressure measurements on the forebody and aftbody. Supplemental data included high-speed Schlieren video and internal pressures and temperatures. The run matrix was developed to allow for the quantification of various sources of experimental uncertainty, such as random errors due to run-to-run variations and bias errors due to flow field or model misalignments. Some preliminary results and observations from the test are presented, although detailed analyses of the data and uncertainties are still on going.

Berry, Scott A.↗
NASA NTRS2017

Linear Subpixel Learning Algorithm for Land Cover Classification from WELD using High Performance Computing

In this work, we use a Fully Constrained Least Squares Subpixel Learning Algorithm to unmix global WELD (Web Enabled Landsat Data) to obtain fractions or abundances of substrate (S), vegetation (V) and dark objects (D) classes. Because of the sheer nature of data and compute needs, we leveraged the NASA Earth Exchange (NEX) high performance computing architecture to optimize and scale our algorithm for large-scale processing. Subsequently, the S-V-D abundance maps were characterized into 4 classes namely, forest, farmland, water and urban areas (with NPP-VIIRS-national polar orbiting partnership visible infrared imaging radiometer suite nighttime lights data) over California, USA using Random Forest classifier. Validation of these land cover maps with NLCD (National Land Cover Database) 2011 products and NAFD (North American Forest Dynamics) static forest cover maps showed that an overall classification accuracy of over 91 percent was achieved, which is a 6 percent improvement in unmixing based classification relative to per-pixel-based classification. As such, abundance maps continue to offer an useful alternative to high-spatial resolution data derived classification maps for forest inventory analysis, multi-class mapping for eco-climatic models and applications, fast multi-temporal trend analysis and for societal and policy-relevant applications needed at the watershed scale.

Subpixel↗
NASA NTRSDate not supplied

Flux Comparison of Master-8 and Ordem 3.1 Modelled Space Debris Population

With ESA’s Meteoroid And Space debris Terrestrial Environment Reference (MASTER-8) model and NASA’s Orbital Debris Engineering Model(ORDEM) 3.1, the two premier orbital debris engineering models have been officially released. The two models come with significant enhancements and now represent state-of-the-art orbital debris modelling for their respective agencies. Both models provide the community with estimates of the space debris environment from low Earth orbit (LEO) up to at least geostationary altitude. The MASTER population is an event-based simulation of all known events that generate debris and objects that are part of the U.S. Space Surveillance Network (SSN) catalog, which provides coverage of objects with diameters down to approximately 10cm in LEO and 1 m in geosynchronous Earth orbit (GEO). Different models are used to simulate the artificial objects and their orbit evolution over time. These models are called “sources” since they assign an origin to each individual object and consist of fragments, solid rocket motor (SRM) remainders, sodium-potassium(NaK) droplets, paintflakes, ejecta, and multi-layer insulation (MLI) fragments. The objects from each source are characterized by having individual release mechanisms, as well as orbital distributions, material composition, size, and mass distributions. Dedicated radar and telescope observation data is used to calibrate the model for objects larger than 1 cm in LEO and larger than 10 cm in GEO. For calibrating the small-sized objects, below 1 cm, impact data from returned surfaces are analyzed. Because the >1cm object population is dominated by fragments, the fragmentation event database was updated to include new events, as well as re-evaluate past events. Special attention was drawn to re-evaluating theFengyun-1C anti-satellite test from 2007 and Cosmos-Iridium collision event from 2009 since these events shape the fragment population because of their severity. After 2009, the two largest fragmentations in terms of number of tracked debris are the Briz-M explosion in 2012 and the NOAA-16explosion in 2015. In total, there are 261 confirmed fragmentations in the database up to November 2016.The baseline population for ORDEM 3.1 is based on the U.S. SSN catalog, and observational datasets from radar, in situ, and optical sources provide a foundation from which the model populations are statistically extrapolated to smaller size regions. These regions are not well-covered by the SSN catalog yet may pose the greatest threat to operational spacecraft. The NASA Standard Satellite Breakup Model is used to generate fragments greater than 1mm from collisions and explosions, and these fragment populations are scaled using ground-based radar data. Specific major debris-producing events, including the Fengyun-1C, Iridium 33, and Cosmos2251 debris clouds, and unique populations, such as NaK droplets, were re-examined, modelled, and added to the ORDEM environment separately. Optical measurement data is used to model the GEO population down to 10 cm. The debris environment is propagated using NASA’s LEO-to-GEO Environment Debris model, and future explosions of intact objects and collisions involving objects greater than 10 cm are assessed statistically. The environment from a few millimetres down to 10 𝜇m is modelled using a special degradation model where small particles are generated from intact spacecraft and rocket bodies, then the populations are scaled to fit in situ cratering data from Space Shuttle returned surfaces. Fragments smaller than 10 cm are differentiated based on material density categories, i.e., high-, medium-, and low-density, to better characterize the potential debris risk posed to upper stages and spacecraft. This paper will discuss the MASTER and ORDEM approaches for modelling populations and compare fluxes for specific orbits, including sun-synchronous, ISS-altitude, geosynchronous transfer, and GEO. In the end, a conclusion is drawn towards the importance of having multiple fundamentally different, yet validated, models to estimate the space debris population.

Andre Horstmann↗
NASA NTRSDate not supplied

Surface and Atmospheric Shortwave Radiative Fluxes From ISCCP Data and Fu-Liou Algorithm at Higher Spatial and Vertical Resolution

NASA/GEWEX Surface Radiation Budget (SRB) has provided surface and TOA shortwave and longwave radiative fluxes using International Satellite Cloud Climatology data as the primary input. Release 4.0 came out in 2019, with data from July 1983 through June 2017, and improved validation stats relative to Release 3.0 (Stackhouse et al., 2012). Release 4.0 used the newly reprocessed ISCCP H data set. The shortwave algorithm for versions 3 and 4 has been based on the Pinker and Laszlo (1992) algorithm, which relies on the satellite-measured shortwave radiance to produce a TOA albedo. This background TOA albedo is made utilizing the background clear-sky visible radiance (called clear-sky composite radiance in the ISCCP data) and applying narrowband-to-broadband angular distribution models. Using a climatological aerosol assumption, the surface albedo is estimated using radiative transfer based (i.e., Fu/Liou radiative transfer model; Fu and Liou, 1993) look-up tables. Using this surface albedo and an instantaneous TOA albedo, the look-up tables are used to adjust both the aerosol optical depth (for clear sky) and cloud optical depth (for cloudy sky) for each scene. These properties and look up tables are then used to generate surface fluxes. While this has worked well to provide useful fluxes, it has occasionally resulted in inaccurate direct and diffuse surface SW fluxes due to the overreliance on aerosol optical depth. With increased computational power and storage now available, a more direct approach is now possible. Here we present a different approach for a future high resolution SRB Release 5.0. We replace the Pinker-Laszlo lookup table approach with a forward call to the Fu-Liou radiative transfer model as modified by the CERES team (Rose et al., 2006). In addition to being a proven radiation code, Fu-Liou allows the calculation of fluxes at different atmospheric levels and spectral bands, which will provide more insight into the surface radiation budget, its variability and attribution. It is expected that horizontal resolution will increase to at least 0.5°x0.5° from the current 1°x1°. Here we demonstrate a preliminary look at the next SRB, and show comparisons with the current release.

Earth Radiation Budget↗
NASA NTRSDate not supplied

Detection of CH 4 Hotspots from NASA’s GEOS Composition Analysis System

Recent research indicates that 8 to 12% of the global oil and gas production methane emissions could be attributed to ultra-emitters, which result in high concentration ‘hotspots’ near point sources. Identifying these emissions in near real time provides useful information to the policy makers and private industry, who are working to reduce their impact. To meet this need, scientists are increasingly analyzing satellite data from the TROPOspheric Monitoring Instrument (TROPOMI) instrument aboard ESA’s Sentinel 5-Precursor mission. While direct analysis of TROPOMI level 2 swath data has been successful in identifying some large emission events, identifying hotpots is challenging because of the imaging noise due to a variety of artifacts and limits in daily coverage. Here we explore possible methodologies to detect methane hotspots using a new, gap-filled, and temporally continuous methane product from NASA’s Goddard Earth Observing System (GEOS) Constituent Data Assimilation System (CoDAS), which assimilates column averaged methane mole fractions from the TROPOMI with capabilities to assimilate other remote sensing measurements. The CoDAS has been expanded from a heritage of stratospheric composition and carbon dioxide assimilation allowing for the support of regional modeling, validation with non-coincident operations, and merging variety of datasets. The current work mainly explores Observing System Simulation Experiments with methane GEOS simulations without assimilation to prepare the groundwork for further experiments with assimilated TROPOMI. First, known hotspots based on the known inventory are identified to demonstrate the capability of the system to point out emission hotspots. In the next step, a variety of machine learning techniques such as Self-Organizing Maps and Deep Learning are explored to automate detection of the plumes. Finally, a few approaches to quantify emissions from the identified hotspots are presented and are evaluated against the inventory. The effort is directed toward a future evaluation of the CoDAS based methane monitoring system’s ability to successfully detect and quantify hotspots.

Nikolay Balashov↗
NASA NTRS2008

Gear Windage Modeling Progress - Experimental Validation Status

In the Subsonics Rotary Wing (SRW) Project being funded for propulsion work at NASA Glenn Research Center, performance of the propulsion system is of high importance. In current rotorcraft drive systems many gearing components operate at high rotational speed (pitch line velocity > 24000 ft/ min). In our testing of high speed helical gear trains at NASA Glenn we have found that the work done on the air - oil mist within the gearbox can become a significant part of the power loss of the system. This loss mechanism is referred to as windage. The effort described in this presentation is to try to understand the variables that affect windage, develop a good experimental data base to validate, the analytical project being conducted at Penn State University by Dr. Rob Kunz under a NASA SRW NRA. The presentation provides an update to the status of these efforts.

Kunz, Rob↗
NASA NTRS2005

Lessons Learned in the Livingstone 2 on Earth Observing One Flight Experiment

The Livingstone 2 (L2) model-based diagnosis software is a reusable diagnostic tool for monitoring complex systems. In 2004, L2 was integrated with the JPL Autonomous Sciencecraft Experiment (ASE) and deployed on-board Goddard's Earth Observing One (EO-1) remote sensing satellite, to monitor and diagnose the EO-1 space science instruments and imaging sequence. This paper reports on lessons learned from this flight experiment. The goals for this experiment, including validation of minimum success criteria and of a series of diagnostic scenarios, have all been successfully net. Long-term operations in space are on-going, as a test of the maturity of the system, with L2 performance remaining flawless. L2 has demonstrated the ability to track the state of the system during nominal operations, detect simulated abnormalities in operations and isolate failures to their root cause fault. Specific advances demonstrated include diagnosis of ambiguity groups rather than a single fault candidate; hypothesis revision given new sensor evidence about the state of the system; and the capability to check for faults in a dynamic system without having to wait until the system is quiescent. The major benefits of this advanced health management technology are to increase mission duration and reliability through intelligent fault protection, and robust autonomous operations with reduced dependency on supervisory operations from Earth. The work-load for operators will be reduced by telemetry of processed state-of-health information rather than raw data. The long-term vision is that of making diagnosis available to the onboard planner or executive, allowing autonomy software to re-plan in order to work around known component failures. For a system that is expected to evolve substantially over its lifetime, as for the International Space Station, the model-based approach has definite advantages over rule-based expert systems and limit-checking fault protection systems, as these do not scale well. The model-based approach facilitates reuse of the L2 diagnostic software; only the model of the system to be diagnosed and telemetry monitoring software has to be rebuilt for a new system or expanded for a growing system. The hierarchical L2 model supports modularity and expendability, and as such is suitable solution for integrated system health management as envisioned for systems-of-systems.

Hayden, Sandra C.↗
NASA NTRS1992

Characterization and modeling for dilute and dense sprays

The present numerical modeling of dilute and dense spray combustion solves the governing gas-phase equations in Eulerian coordinates by means of a time-marching multiple pressure correction procedure that is based on the operator-splitting technique. A sequence of validating cases involving (1) nonevaporating, (2) evaporating, (3) burning, (4) dilute, and (5) dense spray cases is undertaken; it is found that in the combusting dilute spray case, the present procedure correctly predicts the general features of flows and yields qualitative agreement with experimental data. In the other cases, reasonably good agreement with experimental results is obtained.

Chen, C. P.↗
NASA NTRS2008

Atmospheric Parameter Climatologies from AIRS: Monitoring Short-, and Longer-Term Climate Variabilities and 'Trends'

The AIRS instrument is currently the best space-based tool to simultaneously monitor the vertical distribution of key climatically important atmospheric parameters as well as surface properties, and has provided high quality data for more than 5 years. AIRS analysis results produced at the GODDARD/DAAC, based on Versions 4 & 5 of the AIRS retrieval algorithm, are currently available for public use. Here, first we present an assessment of interrelationships of anomalies (proxies of climate variability based on 5 full years, since Sept. 2002) of various climate parameters at different spatial scales. We also present AIRS-retrievals-based global, regional and 1x1 degree grid-scale "trend"-analyses of important atmospheric parameters for this 5-year period. Note that here "trend" simply means the linear fit to the anomaly (relative the mean seasonal cycle) time series of various parameters at the above-mentioned spatial scales, and we present these to illustrate the usefulness of continuing AIRS-based climate observations. Preliminary validation efforts, in terms of intercomparisons of interannual variabilities with other available satellite data analysis results, will also be addressed. For example, we show that the outgoing longwave radiation (OLR) interannual spatial variabilities from the available state-of-the-art CERES measurements and from the AIRS computations are in remarkably good agreement. Version 6 of the AIRS retrieval scheme (currently under development) promises to further improve bias agreements for the absolute values by implementing a more accurate radiative transfer model for the OLR computations and by improving surface emissivity retrievals.

Molnar, Gyula↗
NASA NTRS2010

Application of the Tor Vergata Scattering Model to L Band Backscatter During the Corn Growth Cycle

At the USDA's Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) experimental site in Beltsville, Maryland, USA) a field campaign took place throughout the 2002 corn growth cycle from May 10th (emergence of corn crops) to October 2nd (harvest). One of the microwave instruments deployed was the multi-frequency (X-, C- and L-band) quad-polarized (HH, HV, VV, VH) NASA GSFC/George Washington University (GWU) truck mounted radar. During the field campaign, this radar system provided once a week fully polarized C- and L-band (4.75 and 1.6 GHz) backscatter measurements from incidence angle of 15, 35, and 55 degrees. In support of microwave observations, an extensive ground characterization took place, which included measurements of surface roughness, soil moisture, vegetation biomass and morphology. The field conditions during the campaign are characterized by several dry downs with a period of drought in the month of August. Peak biomass the corn canopies was reached on July 24th with a total biomass of approximately 6.5 kg/sq m. This dynamic range in both soil moisture and vegetation conditions within the data set is ideal for the validation of discrete medium vegetation scattering models. In this study, we compare the L band backscatter measurements with simulations by the Tor Vergata model (ferrazzoli and Guerriero 1996). The measured soil moisture, vegetation biomass and most reliably measured vegetation morphological parameters (e.g. number of leaves, number of stems and stem height) were used as input for the Tor Vergata model. The more uncertain model parameters (e.g. surface roughness, leaf thickness) and the stem diameter were optimized using a parameter estimation routine based on the Levenberg-Marquardt algorithm. As cost function for this optimization, the HH and VV polarized backscatter measured and stimulated by the TOR Vergata model for incidence angle of 15, 35, and 55 degrees were used (6 measurements in total). The calibrated Tor Vergata model simulations are in excellent agreement with the measurements of Root Mean Squared Differences (RMSD's) of 0.8, 0.9 and 1.4 dB for incidences of 15, 35 and 55 degrees, respectively. The results from this study that a physically based scattering model with the appropriate parameterization can accurately simulate backscatter measurements and, as such, have the potential of being used for the retrieval of biophysical variables (e.g. soil moisture and vegetation biomass).

Joseph, A. T.↗
NASA NTRS2012

Physics Based Electrolytic Capacitor Degradation Models for Prognostic Studies under Thermal Overstress

Electrolytic capacitors are used in several applications ranging from power supplies on safety critical avionics equipment to power drivers for electro-mechanical actuators. This makes them good candidates for prognostics and health management research. Prognostics provides a way to assess remaining useful life of components or systems based on their current state of health and their anticipated future use and operational conditions. Past experiences show that capacitors tend to degrade and fail faster under high electrical and thermal stress conditions that they are often subjected to during operations. In this work, we study the effects of accelerated aging due to thermal stress on different sets of capacitors under different conditions. Our focus is on deriving first principles degradation models for thermal stress conditions. Data collected from simultaneous experiments are used to validate the desired models. Our overall goal is to derive accurate models of capacitor degradation, and use them to predict performance changes in DC-DC converters.

Kulkarni, Chetan S.↗
NASA NTRS2020

Autonomous Assessment and Predictive Capabilities for Low-Altitude Urban Flight Operations

The integration of unmanned aerial vehicles in the national airspace will introduce new vehicle types, technologies, and operational paradigms for which safety must be maintained and hazards mitigated. One approach is to attempt to design for possible hazards and unsafe incidents that can occur at different phases of flight (pre-flight, in-flight, and post-flight) and during ground operations. Another is to mitigate safety incidents by implementing changes to policies, procedures, regulations, and design to cover personnel, equipment, and aircraft during operations. These and other techniques, not described herein, are typically conservative or adhoc in that they reduce the likelihood of risk after safety incidents have occurred. In this work, the goal is to develop a more predictive capability to monitor and mitigate risk and hazards to safety “in-time” enough for decisions to be made. In line with NASA’s Aeronautics Mission Directorate Strategic Thrust 5 [1] (In-Time System-Wide Safety Assurance), the System-Wide Safety (SWS) project under which this work falls, is developing and demonstrating innovative and safety-oriented solutions that enable modernization and aviation transformation. To that effect, this work will detail data-driven efforts on the SWS project to develop a number of safety-critical services for in-time monitoring and mitigation of hazards to low-altitude flight operations. First, hazards to these operations are identified based on previous work by NASA [2,3] and others in the aerospace industry. These hazards include (i) unsafe proximity to other vehicles, property, and people on the ground, (ii) critical system failures such as communication signal/GPS loss, unexpected propulsion system degradation, engine/power failure, and (iii) operational/environmental issues such as severe weather and gusty winds. For these hazards, safety metrics, which can be quantified and assessed are defined, models to monitor and predict them are developed, and flight test data is generated to develop, validate, and test these models, considering the complex interplay of the different hazards that define them [4-6]. In addition, the uncertainty in the non-deterministic effects that cannot be modeled nor predicted and unknown unknowns that arise after design/testing and during operations must be handled in rigorous manner. As a result, for each of the developed safety metrics, their dependencies on one another are characterized and a framework for handling the uncertainties inherent in the modeling, algorithms, and measurements required for prediction is also developed [7]. To that effect, this presentation will describe the safety metrics and services already developed and underway under the System-Wide Safety project that utilize data-driven techniques for the identification of anomalies, precursors, and trends (APTs) to monitor and mitigate hazards to safety, in-time, for urban flight operations in low-altitude airspace.

Okolo, Wendy A.↗