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NASA NTRS2008

Boundary-Layer-Ingesting Inlet Flow Control

An experimental study was conducted to provide the first demonstration of an active flow control system for a flush-mounted inlet with significant boundary-layer-ingestion in transonic flow conditions. The effectiveness of the flow control in reducing the circumferential distortion at the engine fan-face location was assessed using a 2.5%-scale model of a boundary-layer-ingesting offset diffusing inlet. The inlet was flush mounted to the tunnel wall and ingested a large boundary layer with a boundary-layer-to-inlet height ratio of 35%. Different jet distribution patterns and jet mass flow rates were used in the inlet to control distortion. A vane configuration was also tested. Finally a hybrid vane/jet configuration was tested leveraging strengths of both types of devices. Measurements were made of the onset boundary layer, the duct surface static pressures, and the mass flow rates through the duct and the flow control actuators. The distortion and pressure recovery were measured at the aerodynamic interface plane. The data show that control jets and vanes reduce circumferential distortion to acceptable levels. The point-design vane configuration produced higher distortion levels at off-design settings. The hybrid vane/jet flow control configuration reduced the off-design distortion levels to acceptable ones and used less than 0.5% of the inlet mass flow to supply the jets.

Owens, Lewis R.↗

NASA NTRS2009

Rb-Sr and Sm-Nd Studies of Olivine-Phyric Shergottites RBT 04262 and LAR 06319: Isotopic Evidence for Relationship to Enriched Basaltic Shergottites

RBT 04262 and LAR 06319 are two Martian meteorites recently discovered in Antarctica. Both contain abundant olivines, and were classified as olivine-phyric shergottites. A detailed petrographic study of RBT 04262 suggested it should be reclassified as a lherzolitic shergottite. However, the moderately LREE-depleted REE distribution pattern indicated that it is closely related to enriched basaltic shergottites like Shergotty, Zagami, Los Angeles, etc. In earlier studies of a similarly olivinephyric shergottite NWA 1068 which contains 21% modal olivine, it was shown that it probably was produced from an enriched basaltic shergottite magma by olivine accumulation . As for LAR 06319, recent petrographic studies suggested that it is different from either lherzolitic shergottites or the highly LREE-depleted olivine-phyric shergottites. We performed Rb-Sr and Sm-Nd isotopic analyses on RBT 04262 and LAR 06319 to determine their crystallization ages and Sr and Nd isotopic signatures, and to better understand the petrogenetic relationships between them and other basaltic, lherzolitic and depleted olivine-phyric shergottites.

Nyquist, L.E.↗

NASA NTRS2010

Bird Migration Under Climate Change - A Mechanistic Approach Using Remote Sensing

The broad-scale reductions and shifts that may be expected under climate change in the availability and quality of stopover habitat for long-distance migrants is an area of increasing concern for conservation biologists. Researchers generally have taken two broad approaches to the modeling of migration behaviour to understand the impact of these changes on migratory bird populations. These include models based on causal processes and their response to environmental stimulation, "mechanistic models", or models that primarily are based on observed animal distribution patterns and the correlation of these patterns with environmental variables, i.e. "data driven" models. Investigators have applied the latter technique to forecast changes in migration patterns with changes in the environment, for example, as might be expected under climate change, by forecasting how the underlying environmental data layers upon which the relationships are built will change over time. The learned geostatstical correlations are then applied to the modified data layers.. However, this is problematic. Even if the projections of how the underlying data layers will change are correct, it is not evident that the statistical relationships will remain the same, i.e. that the animal organism may not adapt its' behaviour to the changing conditions. Mechanistic models that explicitly take into account the physical, biological, and behaviour responses of an organism as well as the underlying changes in the landscape offer an alternative to address these shortcomings. The availability of satellite remote sensing observations at multiple spatial and temporal scales, coupled with advances in climate modeling and information technologies enable the application of the mechanistic models to predict how continental bird migration patterns may change in response to environmental change. In earlier work, we simulated the impact of effects of wetland loss and inter-annual variability on the fitness of migratory shorebirds in the central fly ways of North America. We demonstrated the phenotypic plasticity of a migratory population of Pectoral sandpipers consisting of an ensemble of 10,000 individual birds in response to changes in stopover locations using an individual based migration model driven by remotely sensed land surface data, climate data and biological field data. With the advent of new computing capabilities enabled hy recent GPU-GP computing paradigms and commodity hardware, it now is possible to simulate both larger ensemble populations and to incorporate more realistic mechanistic factors into migration models. Here, we take our first steps use these tools to study the impact of long-term drought variability on shorebird survival.

Smith, James A.↗

NASA NTRS2012

Detection Thresholds of Falling Snow from Satellite-Borne Active and Passive Sensors

Precipitation, including rain and snow, is a critical part of the Earth's energy and hydrology cycles. Precipitation impacts latent heating profiles locally while global circulation patterns distribute precipitation and energy from the equator to the poles. For the hydrological cycle, falling snow is a primary contributor in northern latitudes during the winter seasons. Falling snow is the source of snow pack accumulations that provide fresh water resources for many communities in the world. Furthermore, falling snow impacts society by causing transportation disruptions during severe snow events. In order to collect information on the complete global precipitation cycle, both liquid and frozen precipitation must be collected. The challenges of estimating falling snow from space still exist though progress is being made. These challenges include weak falling snow signatures with respect to background (surface, water vapor) signatures for passive sensors over land surfaces, unknowns about the spherical and non-spherical shapes of the snowflakes, their particle size distributions (PSDs) and how the assumptions about the unknowns impact observed brightness temperatures or radar reflectivities, differences in near surface snowfall and total column snow amounts, and limited ground truth to validate against. While these challenges remain, knowledge of their impact on expected retrieval results is an important key for understanding falling snow retrieval estimations. Since falling snow from space is the next precipitation measurement challenge from space, information must be determined in order to guide retrieval algorithm development for these current and future missions. This information includes thresholds of detection for various sensor channel configurations, snow event system characteristics, snowflake particle assumptions, and surface types. For example, can a lake effect snow system with low (approx 2.5 km) cloud tops having an ice water content (IWC) at the surface of 0.25 g / cubic m and dendrite snowflakes be detected? If this information is known, we can focus retrieval efforts on detectable storms and concentrate advances on achievable results. Here, the focus is to determine thresholds of detection for falling snow for various snow conditions over land and lake surfaces. The results rely on simulated Weather Research Forecasting (WRF) simulations of falling snow cases since simulations provide all the information to determine the measurements from space and the ground truth. Sensitivity analyses were performed to better ascertain the relationships between multifrequency microwave and millimeter-wave sensor observations and the falling snow/underlying field of view. In addition, thresholds of detection for various sensor channel configurations, snow event system characteristics, snowflake particle assumptions, and surface types were studied. Results will be presented for active radar at Ku, Ka, and W-band and for passive radiometer channels from 10 to 183 GHz.

Gail Skofronick-Jackson↗

NASA NTRS2012

Comparative Study of Aerosol and Cloud Detected by CALIPSO and OMI

The Ozone Monitoring Instrument (OMI) on the Aura Satellite detects the presence of desert dust and smoke particles (also known as aerosols) in terms of a parameter known as the UV Aerosol Index (UV AI). The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission measures the vertical distribution of aerosols and clouds. Aerosols and clouds play important roles in the atmosphere and climate system. Accurately detecting their presence, altitude, and properties using satellite radiance measurements is a very important task. This paper presents a comparative analysis of the CALIPSO Version 2 Vertical Feature Mask (VFM) product with the (OMI) UV Aerosol Index (UV AI) and reflectivity datasets for a full year of 2007. The comparison is done at regional and global scales. Based on CALIPSO arid OMI observations, the vertical and horizontal extent of clouds and aerosols are determined and the effects of aerosol type selection, load, cloud fraction on aerosol identification are discussed. It was found that the spatial-temporal correlation found between CALIPSO and OMI observations, is strongly dependent on aerosol types and cloud contamination. CALIPSO is more sensitivity to cloud and often misidentifies desert dust aerosols as cloud, while some small scale aerosol layers as well as some pollution aerosols are unidentified by OMI UV AI. Large differences in aerosol distribution patterns between CALIPSO and OMI are observed, especially for the smoke and pollution aerosol dominated areas. In addition, the results found a significant correlation between CALIPSO lidar 1064 nm backscatter and the OMI UV AI over the study regions.

Chen, Zhong↗

NASA NTRS2011

A Sensitivity Study on the Effects of Particle Chemistry, Asphericity and Size on the Mass Extinction Efficiency of Mineral Dust in the Earth's Atmosphere: From the Near to Thermal IR

To determine a plausible range of mass extinction efficiencies (MEE) of terrestrial atmospheric dust from the near to thermal IR, sensitivity analyses are performed over an extended range of dust microphysical and chemistry perturbations. The IR values are subsequently compared to those in the near-IR, to evaluate spectral relationships in their optical properties. Synthesized size distributions consistent with measurements, model particle size, while composition is defined by the refractive indices of minerals routinely observed in dust, including the widely used OPAC/Hess parameterization. Single-scattering properties of representative dust particle shapes are calculated using the T-matrix, Discrete Dipole Approximation and Lorenz-Mie light-scattering codes. For the parameterizations examined, MEE ranges from nearly zero to 1.2 square meters per gram, with the higher values associated with non-spheres composed of quartz and gypsum. At near-IR wavelengths, MEE for non-spheres generally exceeds those for spheres, while in the thermal IR, shape-induced changes in MEE strongly depend on volume median diameter (VMD) and wavelength, particularly for MEE evaluated at the mineral resonant frequencies. MEE spectral distributions appear to follow particle geometry and are evidence for shape dependency in the optical properties. It is also shown that non-spheres best reproduce the positions of prominent absorption peaks found in silicates. Generally, angular particles exhibit wider and more symmetric MEE spectral distribution patterns from 8-10 micrometers than those with smooth surfaces, likely due to their edge-effects. Lastly, MEE ratios allow for inferring dust optical properties across the visible-IR spectrum. We conclude the MEE of dust aerosol are significant for the parameter space investigated, and are a key component for remote sensing applications and the study of direct aerosol radiative effects.

Hansell, R. A., Jr.↗

NASA NTRS2013

Longitudinally Jointed Edge-wise Compression Honeycomb Composite Sandwich Coupon Testing and FE Analysis: Three Methods of Strain Measurement, and Comparison

Three means (i.e., typical foil strain gages, fiber optic sensors, and a digital image correlation (DIC) system) were implemented to measure strains on the back and front surfaces of a longitudinally jointed curved test article subjected to edge-wise compression testing, at NASA Goddard Space Flight Center, according to ASTM C364. The Pre-test finite element analysis (FEA) was conducted to assess ultimate failure load and predict strain distribution pattern throughout the test coupon. The predicted strain pattern contours were then utilized as guidelines for installing the strain measurement instrumentations. The strain gages and fiber optic sensors were bonded on the specimen at locations with nearly the same strain values, as close as possible to each other, so that, comparisons between the measured strains by strain gages and fiber optic sensors, as well as the DIC system are justified. The test article was loaded to failure (at approximately 38 kips), at the strain value of approximately 10,000mu epsilon As a part of this study, the validity of the measured strains by fiber optic sensors is examined against the strain gage and DIC data, and also will be compared with FEA predictions.

Farrokh, Babak↗

NASA NTRS2013

Longitudinally Jointed Edge-Wise Compression HoneyComb Composite Sandwich Coupon Testing And Fe Analysis: Three Methods of Strain Measurement, And Comparison

Three distinct strain measurement methods (i.e., foil resistance strain gages, fiber optic strain sensors, and a three-dimensional digital image photogrammetry that gives full field strain and displacement measurements) were implemented to measure strains on the back and front surfaces of a longitudinally jointed curved test article subjected to edge-wise compression testing, at NASA Goddard Space Flight Center, according to ASTM C364. The pre-test finite element analysis (FEA) was conducted to assess ultimate failure load and predict strain distribution pattern throughout the test coupon. The predicted strain pattern contours were then utilized as guidelines for installing the strain measurement instrumentations. The foil resistance strain gages and fiber optic strain sensors were bonded on the specimen at locations with nearly the same analytically predicted strain values, and as close as possible to each other, so that, comparisons between the measured strains by strain gages and fiber optic sensors, as well as the three-dimensional digital image photogrammetric system are relevant. The test article was loaded to failure (at ~167 kN), at the compressive strain value of ~10,000 micro epsilon. As a part of this study, the validity of the measured strains by fiber optic sensors is examined against the foil resistance strain gages and the three-dimensional digital image photogrammetric data, and comprehensive comparisons are made with FEA predictions.

Farrokh, Babak↗

NASA NTRS2013

From BASE-ASIA Toward 7-SEAS: A Satellite-Surface Perspective of Boreal Spring Biomass-Burning Aerosols and Clouds in Southeast Asia

In this paper, we present recent field studies conducted by NASA's SMART-COMMIT (and ACHIEVE, to be operated in 2013) mobile laboratories, jointly with distributed ground-based networks (e.g., AERONET, http://aeronet.gsfc.nasa.gov/ and MPLNET, http://mplnet.gsfc.nasa.gov/) and other contributing instruments over northern Southeast Asia. These three mobile laboratories, collectively called SMARTLabs (cf. http://smartlabs.gsfc.nasa.gov/, Surface-based Mobile Atmospheric Research & Testbed Laboratories) comprise a suite of surface remote sensing and in-situ instruments that are pivotal in providing high spectral and temporal measurements, complementing the collocated spatial observations from various Earth Observing System (EOS) satellites. A satellite-surface perspective and scientific findings, drawn from the BASE-ASIA (2006) field deployment as well as a series of ongoing 7-SEAS (2010-13) field activities over northern Southeast Asia are summarized, concerning (i) regional properties of aerosols from satellite and in situ measurements, (ii) cloud properties from remote sensing and surface observations, (iii) vertical distribution of aerosols and clouds, and (iv) regional aerosol radiative effects and impact assessment. The aerosol burden over Southeast Asia in boreal spring, attributed to biomass burning, exhibits highly consistent spatial and temporal distribution patterns, with major variability arising from changes in the magnitude of the aerosol loading mediated by processes ranging from large-scale climate factors to diurnal meteorological events. Downwind from the source regions, the tightly coupled-aerosolecloud system provides a unique, natural laboratory for further exploring the micro- and macro-scale relationships of the complex interactions. The climatic significance is presented through large-scale anti-correlations between aerosol and precipitation anomalies, showing spatial and seasonal variability, but their precise cause-and-effect relationships remain an open-ended question. To facilitate an improved understanding of the regional aerosol radiative effects, which continue to be one of the largest uncertainties in climate forcing, a joint international effort is required and anticipated to commence in springtime 2013 in northern Southeast Asia.

biomass burning aerosols↗

NASA NTRS2013

First Evaluation of the Climatological Calibration Algorithm in the Real-time TMPA Precipitation Estimates over Two Basins at High and Low Latitudes

The TRMM Multi-satellite Precipitation Analysis (TMPA) system underwent a crucial upgrade in early 2009 to include a climatological calibration algorithm (CCA) to its realtime product 3B42RT, and this algorithm will continue to be applied in the future Global Precipitation Measurement era constellation precipitation products. In this study, efforts are focused on the comparison and validation of the Version 6 3B42RT estimates before and after the climatological calibration is applied. The evaluation is accomplished using independent rain gauge networks located within the high-latitude Laohahe basin and the low-latitude Mishui basin, both in China. The analyses indicate the CCA can effectively reduce the systematic errors over the low-latitude Mishui basin but misrepresent the intensity distribution pattern of medium-high rain rates. This behavior could adversely affect TMPA's hydrological applications, especially for extreme events (e.g., floods and landslides). Results also show that the CCA tends to perform slightly worse, in particular, during summer and winter, over the high-latitude Laohahe basin. This is possibly due to the simplified calibration-processing scheme in the CCA that directly applies the climatological calibrators developed within 40 degrees latitude to the latitude belts of 40 degrees N-50 degrees N. Caution should therefore be exercised when using the calibrated 3B42RT for heavy rainfall-related flood forecasting (or landslide warning) over high-latitude regions, as the employment of the smooth-fill scheme in the CCA bias correction could homogenize the varying rainstorm characteristics. Finally, this study highlights that accurate detection and estimation of snow at high latitudes is still a challenging task for the future development of satellite precipitation retrievals.

TMPA-RT Precipitation Estimates↗

NASA NTRS2016

Convection from Hemispherical and Conical Model Ice Roughness Elements in Stagnation Region Flows

To improve ice accretion prediction codes, more data regarding ice roughness and its effects on convective heat transfer are required. The Vertical Icing Studies Tunnel (VIST) at NASA Glenn Research was used to model realistic ice roughness in the stagnation region of a NACA 0012 airfoil. In the VIST, a test plate representing the leading 2% chord of the airfoil was subjected to flows of 7.62 m/s (25 ft/s), 12.19 m/s (40 ft/s), and 16.76 m/s (55 ft/s). The test plate was fitted with multiple surfaces or sets of roughness panels, each with a different representation of ice roughness. The sets of roughness panels were constructed using two element distribution patterns that were created based on a laser scan of an iced airfoil acquired in the Icing Research Tunnel at NASA Glenn. For both roughness patterns, surfaces were constructed using plastic hemispherical elements, plastic conical elements, and aluminum conical elements. Infrared surface thermometry data from tests run in the VIST were used to calculate area averaged heat transfer coefficient values. The values from the roughness surfaces were compared to the smooth control surface, showing convective enhancement as high as 400% in some cases. The data gathered during this study will ultimately be used to improve the physical modeling in LEWICE or other ice accretion codes and produce predictions of in-flight ice accretion on aircraft surfaces with greater confidence.

Icing Physics↗

NASA NTRS2019

Extending XBAER Algorithm to Aerosol and Cloud Condition

The retrieval of cloud optical properties for aerosol contaminated water cloud is challenging because of the complexity of physical processes in such situations. Conventionally, cloud optical data products are typically derived, ignoring the aerosol impacts on radiative transfer in the retrieval process. This is potentially a significant source of error. In this paper, the eXtensible Bremen Aerosol Retrieval (XBAER) algorithm has been optimized for the retrieval of aerosol/cloud properties for the aerosol contaminated cloud (ACC) scenarios. This version of XBAER delivers cloud optical thickness (COT) and cloud effective radius (CER) for ACCs and simultaneously retrieves aerosol optical thickness (AOT). The surface parameterization and aerosol types used in the standard XBAER algorithm have been adapted in this retrieval to account for the ACC conditions. Aerosol types in XBAER for the retrieval of ACC scenarios have been parameterized to comprise weak and strong absorptions. The comparisons of COT, CER, and AOT retrieved using this adapted XBAER algorithm and two new NASA algorithms show good agreements, especially for biomass burning aerosol. The correlation coefficients are >0.9 for AOT, ~0.8 for CER, and ~0.7 for COT. There is also a good agreement for dust plume contaminated cloud scene. The XBAER derived AOT values for dust aerosols are systematically smaller than the NASA retrieval, but both products have the same spatial distribution patterns. The comparison of COT retrieved using the adapted XBAER algorithm and that retrieved from ground-based microwave radiometer (MWR) measurements shows much better agreement for ACC conditions with high AOT.

satellite↗

NASA NTRS2019

Pulsed Plasma Acceleration Modeling in Detonation and Deflagration Modes

Gas-fed electromagnetic pulsed plasma accelerators discharge electrical energy into a gas to ionize and electromagnetically accelerate propellant in the domain. Efforts to model pulsed accelerators have either assumed that the discharge is short and completely transient, accelerating the gas by entraining it in a moving current sheet, or that the discharge is relatively long, establishing a stable quasi-steady current distribution pattern that accelerates a plasma flowing through it. There have been pulsed plasma accelerator tests that appear to fit somewhere between these two bounds, exhibiting some properties that are associated with the purely transient devices while also showing others that are associated with quasi-steady-state plasma acceleration. A model is presented based upon the premise that all pulsed plasma accelerators first form an accelerating current sheet (detonation mode accelerator). Depending upon the pulse length and the gas conditions in the dis- charge channel, the plasma sheet may reach the end of the accelerator before the discharge has completed a full half-cycle, wherein the proposed model transitions to a quasi-steady description of the acceleration process (deflagration mode accelerator). A review of the entire model is presented, highlighting improvements and upgrades implemented to aid in the stability of the numerical scheme used to model the gas flow in the channel and an improved treatment of current sheet mass shedding, which adds gas to the wake of the sheet. The assumptions employed to model the transition from detonation to deflagration mode are presented and used to generate solutions to the governing equations. The modeling of the deflagration-mode under the present assumptions results in very low deflagration impulse bits relative to those obtained at the end of the detonation mode, implying that the present assumptions and modeling of the deflagration mode may not represent a fruitful approach.

Polzin, Kurt A.↗

NASA NTRS2019

Pulsed Plasma Acceleration Modeling in Detonation and Deflagration Modes

Gas-fed electromagnetic pulsed plasma accelerators discharge electrical energy into a gas to ionize and electromagnetically accelerate propellant in the domain. Efforts to model pulsed accelerators have either assumed that the discharge is short and completely tran- sient, accelerating the gas by entraining it in a moving current sheet, or that the discharge is relatively long, establishing a stable quasi-steady current distribution pattern that accel- erates a plasma flowing through it. There have been pulsed plasma accelerator tests that appear to fit somewhere between these two bounds, exhibiting some properties that are associated with the purely transient devices while also showing others that are associated with quasi-steady-state plasma acceleration. A model is presented based upon the premise that all pulsed plasma accelerators first form an accelerating current sheet (detonation mode accelerator). Depending upon the pulse length and the gas conditions in the dis- charge channel, the plasma sheet may reach the end of the accelerator before the discharge has completed a full half-cycle, wherein the proposed model transitions to a quasi-steady description of the acceleration process (deflagration mode accelerator). A review of the entire model is presented, highlighting improvements and upgrades implemented to aid in the stability of the numerical scheme used to model the gas flow in the channel and an im- proved treatment of current sheet mass shedding, which adds gas to the wake of the sheet. The assumptions employed to model the transition from detonation to deflagration mode are presented and used to generate solutions to the governing equations. The modeling of the deflagration-mode under the present assumptions results in very low deflagration im- pulse bits relative to those obtained at the end of the detonation mode, implying that the present assumptions and modeling of the deflagration mode may not represent a fruitful approach.

Polzin, Kurt A.↗

NASA NTRS2021

Extensive Characterization of Aerosol Optical Properties and Chemical Component Concentrations: Application of the GRASP/Component Approach to Long-term AERONET Measurements

A recently developed GRASP/Component approach (GRASP: Generalized Retrieval of Atmosphere and Surface Properties) was applied to AERONET (Aeronet Robotic Network) sun photometer measurements in this study. Unlike traditional aerosol component retrieval, this approach allows the inference of some information about aerosol composition directly from measured radiance, rather than indirectly through the inversion of optical parameters, and has been integrated into the GRASP algorithm. The newly developed GRASP/Component approach was applied to 13 AERONET sites for different aerosol types under the assumption of aerosol internal mixing rules to analyze the characteristics of aerosol components and their distribution patterns. The results indicate that the retrievals can characterize well the spatial and temporal variability of the component concentration for different aerosol types. A reasonable agreement between GRASP BC retrievals and MERRA-2 BC products is found for all different aerosol types. In addition, the relationships between aerosol component content and aerosol optical parameters such as aerosol optical depth (AOD), fine-mode fraction (FMF), absorption Ångström exponent (AAE), scattering Ångström exponent (SAE), and single scattering albedo (SSA) are also analyzed for indirect verifying the reliability of the component retrieval. It was demonstrated the GRASP/Component optical retrievals are in good agreement with AERONET standard products [e.g., correlation coefficient (R) of 0.93–1.0 for AOD, fine-mode AOD (AODF), coarse-mode AOD (AODC) and Ångström exponent (AE); R = ~ 0.8 for absorption AOD (AAOD) and SSA; RMSE (root mean square error) < 0.03 for AOD, AODF, AODC, AAOD and SSA]. Thus, it is demonstrated the GRASP/Component approach can provide aerosol optical products with comparable accuracy as the AERONET standard products from the ground-based sun photometer measurements as well as some additional important inside on aerosol composition.

Xindan Zhang↗

NASA NTRSDate not supplied

Capturing Complex Multivariate Time Series Interactions to Detect High-Risk Adverse Events During Flight

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗

NASA NTRSDate not supplied

Capturing Multivariate Time Series Interactions to Detect High‑Risk Instability During Approach

Risk detection↗

NASA NTRSDate not supplied

Ice-Over-Water Cloud Identification in an Artificial Neural Network Approach

An artificial neural network (ANN) algorithm, employing several Aqua MODIS channels, the retrieved cloud phase and total cloud visible optical depth, and temperature and humidity vertical profiles is trained to detect multilayer (ML) ice-over-water cloud systems identified by matched 2008 CloudSat and CALIPSO (CC) data. The trained MLANN was applied to 2009 MODIS data resulting in combined ML and single layer detection accuracies of 87% (89%) and 86% (89%) for snow-free (snow-covered) regions during the day and night, respectively. When corrected for the viewing-zenith-angle dependence of each parameter, the ML fraction detected is relatively invariant across the swath. Compared to the CC ML variability, the MLANN is robust seasonally and interannually, and produces similar distribution patterns over the globe, except in the polar regions. Additional research is needed to conclusively evaluate the VZA dependence and further improve the MLANN accuracy. This approach should greatly improve the monitoring of cloud vertical structure using operational passive sensors.

MODIS↗