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NASA NTRSDate not supplied

Multiclass Flight Anomaly Detection Using Sensor Fusion Based on Dempster-Shafer Theory

As aviation systems in commercial operations continue to grow in complexity, the anomalies exhibited by these systems become more elaborate and difficult to detect. To address the challenge of detecting these complex anomalies, deep learning models have been used extensively in aviation anomaly detection studies, at the expense of end-user interpretability. Aiming to maintain the same level of interpretability as traditional threshold-exceedance methods, we continue our development of prediction models using ordinal patterns and their distributions throughout the flight. Specifically, this study extends our work into multiclass anomaly detection using sensor fusion based on Dempster-Shafer theory (DST), a second-order probability theory used to combine information from different sources of evidence. Our approach uses DST toreduce the uncertainty in the class predictions of an ensemble of classifiers. These classifiers rely on the similarity between flight data and class templates to make a prediction of the state of the aircraft. Our approach aims to take advantage of simple models trained on interpretable features (ordinal patterns) to correctly predict an anomaly and identify the flight dynamics linked to the anomaly. Our results show an improvement when using DST-based sensor fusion over simple majority voting. Additionally, our results provide insight into aircraft states linked to rare high-risk anomalies.

Risk detection↗
NASA NTRSDate not supplied

Architecture Options for Navigation in Cislunar Space for Human Landing System Vehicles

As part of architecture studies and insight analysis focused on requirements development into Human Landing System lunar architecture designs, multiple studies are underway to understand the sensitivities and options for achieving high precision landing on the lunar surface. The baseline approach utilizes a combination of multiple sensors to capture autonomous state observations of the lander with respect to the lunar surface. These systems are typically constrained in terms of operational altitudes by parameters such as onboard map size, camera focus, or sensor transmitted power (for altimeter observations). While these sensor suites do enable high precision landing, they are typically very complex and expensive. For a human-rated vehicle, fault detection algorithms are needed in addition to redundant sensors drive additional design complexity. Conversely, for these early missions, mass performance is key, so extended analysis is required to identify numbers of sensors, their ideal placement, and integration algorithms. A key part of this analysis is to help identify key sensor suites and options to help alleviate this design tension. An alternate approach is to take advantage and build out in-situ assets to allow for GPS-like navigation within the lunar regime through the use of navigation references or beacons. This can be achieved through the integration of navigation services into potential relays and pre-placed lunar surface assets. This research focuses on the capability of this infrastructure to support navigation in all areas of cislunar space such as: approach to the moon, in orbit around the moon, and ascent/descent operations to the surface. An augmented state linear covariance analysis (LinCov) and navigation state covariance analysis (NavCov) tools were used to assess a variety of navigation reference locations and how they can support vehicle operations through both understanding of state uncertainties and trajectory dispersions. This research helps to supplement existing studies focused on communication link analysis by providing additional insight into specific vehicle operational scenarios that are tied closely to potential Human Landing System scenarios. Key aspect of this analysis focus on the sensitivity to state knowledge of the references, the accuracy of inter-asset measurements, and placement in support of the various scenarios.

Evan J Anzalone↗
NASA NTRS2002

The Retrospective Iterated Analysis Scheme for Nonlinear Chaotic Dynamics

Atmospheric data assimilation is the name scientists give to the techniques of blending atmospheric observations with atmospheric model results to obtain an accurate idea of what the atmosphere looks like at any given time. Because two pieces of information are used, observations and model results, the outcomes of data assimilation procedure should be better than what one would get by using one of these two pieces of information alone. There is a number of different mathematical techniques that fall under the data assimilation jargon. In theory most these techniques accomplish about the same thing. In practice, however, slight differences in the approaches amount to faster algorithms in some cases, more economical algorithms in other cases, and even give better overall results in yet some other cases because of practical uncertainties not accounted for by theory. Therefore, the key is to find the most adequate data assimilation procedure for the problem in hand. In our Data Assimilation group we have been doing extensive research to try and find just such data assimilation procedure. One promising possibility is what we call retrospective iterated analysis (RIA) scheme. This procedure has recently been implemented and studied in the context of a very large data assimilation system built to help predict and study weather and climate. Although the results from that study suggest that the RIA scheme produces quite reasonable results, a complete evaluation of the scheme is very difficult due to the complexity of that problem. The present work steps back a little bit and studies the behavior of the RIA scheme in the context of a small problem. The problem is small enough to allow full assessment of the quality of the RIA scheme, but it still has some of the complexity found in nature, namely, its chaotic-type behavior. We find that the RIA performs very well for this small but still complex problem which is a result that seconds the results of our early studies.

Todling, Ricardo↗
NASA NTRSDate not supplied

Structural Dynamics Observations in Space Launch System Green Run Hot Fire Testing

The Space Launch System (SLS) Core Stage (CS) Thrust Vector Control (TVC) system is comprised of eight mechanical feedback Shuttle heritage Type III TVC actuators and four RS-25 engines, each attached to a Shuttle heritage gimbal block/bearing. Two actuators are used to move each engine in two planes perpendicular to one another (i.e., pitch and yaw). The TVC system design leverages hardware from the Space Shuttle program as well as new hardware designed specifically for the Core Stage. The Green Run Hot Fire (GRHF) of the SLS Core Stage provided a flight-like ground test environment for verification of integrated vehicle TVC performance. A TVC model coupled to a vehicle structural dynamic model has been developed previously and incrementally validated in subsystem tests and simulations. Still, some aspects of TVC performance in GRHF were not anticipated. The ensuing investigation demonstrated the need for well-instrumented test environments, various levels of modeling fidelity, test-representative structural models, and caution in reuse of legacy components. This paper is the sixth installment in a seven-paper series surveying the design, engineering, test validation, and flight performance of the Core Stage Thrust Vector Control system. It introduces the salient structural dynamic phenomena uncovered in ambient and hot fire testing. During the Green Run test campaign, a comparison of ambient and hot fire step responses showed a significant change in apparent damping due to the presence of friction, challenging long standing assumptions that friction could be neglected. Additionally, the characteristic response of the engine and thrust structure during GRHF proved to be more complex than anticipated, as evidenced by the available actuator, thrust structure, and engine measurements. While the string-potentiometer based test instrumentation was intended to allow for reconstruction of the engine angles along the two control axes, the geometric placement, location uncertainty, and responses in overlapping frequency spectra revealed additional phenomena requiring further analysis and post-processing. The observations from both modal and frequency response testing during the Green Run ambient and hot fire configurations led to Engine and Core Stage FEM (finite element model) updates. When evidence of unexpected engine motion was found in engine section accelerometer data, the authors pursued additional structural analysis leading to FEM updates associated with the TVC gimbal and thrust structure. Through collaboration between structures, TVC, and flight control disciplines, the test-informed models and root-cause analysis led to confident flight rationale for the first flight of the SLS launch vehicle.

Richard K. Moore↗
NASA NTRSDate not supplied

Structural Dynamics Observations in Space Launch System Green Run Hot Fire Testing

The Space Launch System (SLS) Core Stage (CS) Thrust Vector Control (TVC) system is comprised of eight mechanical feedback Shuttle heritage Type III TVC actuators and four RS-25 engines, each attached to a Shuttle heritage gimbal block/bearing. Two actuators are used to move each engine in two planes perpendicular to one another (i.e., pitch and yaw). The TVC system design leverages hardware from the Space Shuttle program as well as new hardware designed specifically for the Core Stage. The Green Run Hot Fire (GRHF) of the SLS Core Stage provided a flight-like ground test environment for verification of integrated vehicle TVC performance. A TVC model coupled to a vehicle structural dynamic model has been developed previously and incrementally validated in subsystem tests and simulations. Still, some aspects of TVC performance in GRHF were not anticipated. The ensuing investigation demonstrated the need for well-instrumented test environments, various levels of modeling fidelity, test-representative structural models, and caution in reuse of legacy components. This paper is the sixth installment in a seven-paper series surveying the design, engineering, test validation, and flight performance of the Core Stage Thrust Vector Control system. It introduces the salient structural dynamic phenomena uncovered in ambient and hot fire testing. During the Green Run test campaign, a comparison of ambient and hot fire step responses showed a significant change in apparent damping due to the presence of friction, challenging long standing assumptions that friction could be neglected. Additionally, the characteristic response of the engine and thrust structure during GRHF proved to be more complex than anticipated, as evidenced by the available actuator, thrust structure, and engine measurements. While the string-potentiometer based test instrumentation was intended to allow for reconstruction of the engine angles along the two control axes, the geometric placement, location uncertainty, and responses in overlapping frequency spectra revealed additional phenomena requiring further analysis and post-processing. The observations from both modal and frequency response testing during the Green Run ambient and hot fire configurations led to Engine and Core Stage FEM (finite element model) updates. When evidence of unexpected engine motion was found in engine section accelerometer data, the authors pursued additional structural analysis leading to FEM updates associated with the TVC gimbal and thrust structure. Through collaboration between structures, TVC, and flight control disciplines, the test-informed models and root-cause analysis led to confident flight rationale for the first flight of the SLS launch vehicle.

Richard Moore↗
NASA NTRSDate not supplied

Multiclass Flight Anomaly Detection Using Sensor Fusion Based on Dempster-Shafer Theory

As aviation systems in commercial operations continue to grow in complexity, the anomalies exhibited by these systems become more elaborate and difficult to detect. To address the challenge of detecting these complex anomalies, deep learning models have been used extensively in aviation anomaly detection studies, at the expense of end-user interpretability. Aiming to maintain the same level of interpretability as traditional threshold-exceedance methods, we continue our development of prediction models using ordinal patterns and their distributions throughout the flight. Specifically, this study extends our work into multiclass anomaly detection using sensor fusion based on Dempster-Shafer theory (DST), a second-order probability theory used to combine information from different sources of evidence. Our approach uses DST to reduce the uncertainty in the class predictions of an ensemble of classifiers. These classifiers rely on the similarity between flight data and class templates to make a prediction of the state of the aircraft. Our approach aims to take advantage of simple models trained on interpretable features (ordinal patterns) to correctly predict an anomaly and identify the flight dynamics linked to the anomaly. Our results show an improvement when using DST-based sensor fusion over simple majority voting. Additionally, our results provide insight into aircraft states linked to rare high-risk anomalies.

Risk detection↗
NASA NTRS1994

Neutral hydrogen and optical properties of three amorphous galaxies

We present new interferometric H I and optical observations of three amorphous galaxies, systems with a smooth, high surface brightness but an asymmetrical distribution of light. All three galaxies are forming stars and have LMC-like emission-line ratios, low dust content, and high H I velocity dispersions. NGC 1140 has a boxy inner morphology with a hook off one corner. At low light levels unusual extensions of starlight are seen curving to the northwest and southeast. The galaxy contains a very luminous central star-forming region and a small chain of H II regions that coincide with the hook. The central H II region has broad H(alpha) velocity profiles full width at half maximum (FWHM) less than or equal to 140 km/s, and it is a radio continuum source. There is a rotating H I gas disk, 40 kpc in radius, at a position angle 51 deg from the optical major axis. The central gas ridge follows the chain of H II regions, and the H I peak is on the hook. The outer gas on the southeast side curves away from the H I major axis. The central gas density is high, and the surface density declines very slowly with radius. The rotation velocity yields a mass of 1 x 10(exp 11) solar mass at 3.3 Holmberg radii (R(sub H)). NGC 1800 has a hook that coincides with a large H II region, and an r(exp 1/4) luminosity distribution. There are numerous H II regions along the major axis and extraordinary filaments of ionized gas. Emanating from the major axis on either side of the galaxy are H(alpha) fingers approximately 750 pc long. About 2.3 kpc to the north is a web of filaments approximately 3 kpc in extent. H(alpha) profiles of H II regions and filaments are narrow. The H I gas disk has a position angle that is approximately 13 deg different from that of the optical axis. There are two peaks near the center, one of which is near the largest H II region. Beyond the Holmberg radius to the west is a 6 x 10(exp 6) solar mass H I cloud. Its velocity indicates a mass of approximately 6 x 10(exp 9) solar mass for NGC 1800 at 1.5 R(sub H). At approximately R(sub 25) to the east there is a large H I shell. Also at approximately R(sub 25) on both sides the velocity gradient switches by 90 deg, and in the interior the rotation is about the major axis. The central gas density is low and falls off slowly. In the inner regions NGC 4670 resembles an S0/a galaxy seen rather edge-on. It contains a central supergiant H II region with very high velocity widths (FWHM less than or equal to 180 km/s) and complex velocity structures. It is a radio continuum source as well. The H I gas is a single spherical cloud or a disk at low inclination centered on the galaxy with a slight elongation along the optical major axis and rotation about the minor axis. The central gas density is high, and there is a high degree of concentration. The rotation speed indicates a total mass of 5 x 10(exp 10) solar mass at 1.1 R(sub H). We compare these characteristics with properties of gas in the presence of stellar bar potentials, gas warps, and interacting and merging galaxy models. Although there are inconsistencies and uncertainties, we conclude that NGC 1140 is a spiral of low surface brightness that has undergone a merger, while NGC 1800 and NGC 4670 are, respectively, probably an Im system and a spiral that had an encounter of the Noguchi (1988a) kind.

Hunter, Deidre A.↗
NASA NTRS2024

Mineral Dust Optical Properties for Remote Sensing and Global Modeling: A Review

Dust plays a key role in many Earth system processes and is ubiquitous in the Martian atmosphere. Various intensive field campaigns, laboratory analyses, space-based remote sensing missions, and global modeling efforts aim to characterize dust optical properties. This is a bountiful time for dust scientists, and yet the interpretation of retrievals and comparison to models remains complicated by various conflicting assumptions that are part of each algorithm. For example, the conversion of satellite radiance measurements into products like aerosol optical depth for model evaluation depends upon aerosol properties like particle size and shape that are often prescribed and not part of the retrieval. Conversely, the model calculation of aerosol optical depth often uses different assumptions. The goal of this review is to first document algorithmic assumptions by various satellite retrieval products and models, and identify where there is consistency and where there are differences. In general, the differences documented in this paper reflect uncertainties resulting from incomplete observational characterization of dust aerosols and limitations in our understanding. Second, we note what observations might reduce uncertainties in our knowledge and bring greater consistency to retrievals and models, allowing for a more rigorous and harmonious comparison. The lack of comprehensive and realistic shape models for dust is an outstanding issue, such that closure between forward modeling from particle refractive index, shape, and size and observed optical properties cannot be achieved. Limitations in the computational methods that must be applied to model scattering from complex shapes also makes accurate optical modeling for dust challenging. Field observations indicate the persistence of coarse and giant dust particles at higher altitudes and farther downwind from their source than previously expected. Remote sensing retrieval algorithms based on observations at visible wavelengths have limited sensitivity to these particles and generally do not consider them, although a recent product based on longwave radiances is encouraging. Current measurements of the refractive index of bulk dust and fundamental dust minerology components such as hematite vary widely, inhibiting attempts to represent the variability in dust optical properties and forcing, as expected from different major dust source regions on Earth that have varying mineralogical composition. Some remote sensing retrieval algorithms allow for limited refractive index variability in their inversion solutions through mixing with other fine mode aerosol models, or optimizing the single scattering albedo, but Earth system models surveyed for this paper assume a globally uniform, size-invariant refractive index. Although no Martian dust samples have yet been returned to Earth, remote sensing observations indicate that Martian dust is globally homogenous in composition, and a single spectral refractive index assumption has been widely adopted to represent Martian dust. The lack of comprehensive, statistically representative measurements of dust particle microphysical properties (size distribution, morphology, complex index of refraction spectra, internal structure heterogeneity), and the resulting optical properties, limits our ability to verify the fidelity of these assumptions. A chain of measurements is needed, ranging from characterizing individual dust mineralogy components (e.g., pure hematite and goethite) to in situ sampling of complex atmospheric aerosol mixtures. Such results could be applied to both remote sensing retrievals that characterize the optical properties of the total aerosol burden in the atmosphere from total radiance measurements, and to global models that represent the total aerosol burden in the atmosphere by building it up from the balance of individual aerosol sources and sinks.

Aeolian dust↗
NASA NTRS2022

Diagnosing Challenges and Setting Priorities for Sustainable Water Resource Management Under Climate Change

Managing transboundary river basins requires balancing tradeoffs of sustainable water use and coping with climate uncertainty. We demonstrate an integrated approach to exploring these issues through the lens of a social-ecological system, combining remote and in-situ earth observations, hydrologic and climate models, and social surveys. Specifically, we examine how climate change and dam development could impact the Se Kong, Se San and Sre Pok rivers in the Mekong region. We find that climate change will lead to increased precipitation, necessitating a shift in dam operations, from maintaining low flows to reducing flood hazards. We also find that existing water governance systems in Laos, Vietnam, and Cambodia are ill-prepared to address the problem. We conclude that the solution space for addressing these complex issues will be highly constrained unless major deficiencies in transboundary water governance, strategic planning, financial capacity, information sharing, and law enforcement are remedied in the next decades.

Ibrahim Nourein Mohammed↗
NASA NTRS2015

Why Is Improvement of Earth System Models so Elusive? Challenges and Strategies from Dust Aerosol Modeling

Past decades have seen an accelerating increase in computing efficiency, while climate models are representing a rapidly widening set of physical processes. Yet simulations of some fundamental aspects of climate like precipitation or aerosol forcing remain highly uncertain and resistant to progress. Dust aerosol modeling of soil particles lofted by wind erosion has seen a similar conflict between increasing model sophistication and remaining uncertainty. Dust aerosols perturb the energy and water cycles by scattering radiation and acting as ice nuclei, while mediating atmospheric chemistry and marine photosynthesis (and thus the carbon cycle). These effects take place across scales from the dimensions of an ice crystal to the planetary-scale circulation that disperses dust far downwind of its parent soil. Representing this range leads to several modeling challenges. Should we limit complexity in our model, which consumes computer resources and inhibits interpretation? How do we decide if a process involving dust is worthy of inclusion within our model? Can we identify a minimal representation of a complex process that is efficient yet retains the physics relevant to climate? Answering these questions about the appropriate degree of representation is guided by model evaluation, which presents several more challenges. How do we proceed if the available observations do not directly constrain our process of interest? (This could result from competing processes that influence the observed variable and obscure the signature of our process of interest.) Examples will be presented from dust modeling, with lessons that might be more broadly applicable. The end result will either be clinical depression or there assuring promise of continued gainful employment as the community confronts these challenges.

Climate models↗
NASA NTRS1974

Research on infrared astrophysics and X ray and XUV astronomy

The infrared research was divided into two related subjects, observations at wavelengths less than 34 microns and millimeter wavelength observations. A new complex of infrared sources in the Orion Nebula observed along with a broad range of galactic and extragalactic objects. The Comet Kohoutek was measured in the 1-20 micron wavelength region and its thermal properties agreed closely with those of Comet Ikeya-Seki. Combined infrared and photoelectric studies of the Makarian galaxies showed them to have a composite spectrum with a large emission feature in the far infrared. The development of one millimeter photometry and composited bolometers is described. A technique of reconstructing two dimensional surface brightness distributions with appropriate errors from individual strip scans was developed. Model parameters were determined by fitting data in non-linear systems. Results show spectral parameter uncertainties are underestimated or incorrectly evaluated in most studies.

Source record↗
NASA NTRS2012

Blade Displacement Measurement Technique Applied to a Full-Scale Rotor Test

Blade displacement measurements using multi-camera photogrammetry were acquired during the full-scale wind tunnel test of the UH-60A Airloads rotor, conducted in the National Full-Scale Aerodynamics Complex 40- by 80-Foot Wind Tunnel. The objectives were to measure the blade displacement and deformation of the four rotor blades as they rotated through the entire rotor azimuth. These measurements are expected to provide a unique dataset to aid in the development and validation of rotorcraft prediction techniques. They are used to resolve the blade shape and position, including pitch, flap, lag and elastic deformation. Photogrammetric data encompass advance ratios from 0.15 to slowed rotor simulations of 1.0, thrust coefficient to rotor solidity ratios from 0.01 to 0.13, and rotor shaft angles from -10.0 to 8.0 degrees. An overview of the blade displacement measurement methodology and system development, descriptions of image processing, uncertainty considerations, preliminary results covering static and moderate advance ratio test conditions and future considerations are presented. Comparisons of experimental and computational results for a moderate advance ratio forward flight condition show good trend agreements, but also indicate significant mean discrepancies in lag and elastic twist. Blade displacement pitch measurements agree well with both the wind tunnel commanded and measured values.

Abrego, Anita I.↗
NASA NTRS1982

Space power subsystem automation technology

The technology issues involved in power subsystem automation and the reasonable objectives to be sought in such a program were discussed. The complexities, uncertainties, and alternatives of power subsystem automation, along with the advantages from both an economic and a technological perspective were considered. Whereas most spacecraft power subsystems now use certain automated functions, the idea of complete autonomy for long periods of time is almost inconceivable. Thus, it seems prudent that the technology program for power subsystem automation be based upon a growth scenario which should provide a structured framework of deliberate steps to enable the evolution of space power subsystems from the current practice of limited autonomy to a greater use of automation with each step being justified on a cost/benefit basis. Each accomplishment should move toward the objectives of decreased requirement for ground control, increased system reliability through onboard management, and ultimately lower energy cost through longer life systems that require fewer resources to operate and maintain. This approach seems well-suited to the evolution of more sophisticated algorithms and eventually perhaps even the use of some sort of artificial intelligence. Multi-hundred kilowatt systems of the future will probably require an advanced level of autonomy if they are to be affordable and manageable.

Graves, J. R.↗
NASA NTRS1995

A fuzzy logic intelligent diagnostic system for spacecraft integrated vehicle health management

Due to the complexity of future space missions and the large amount of data involved, greater autonomy in data processing is demanded for mission operations, training, and vehicle health management. In this paper, we develop a fuzzy logic intelligent diagnostic system to perform data reduction, data analysis, and fault diagnosis for spacecraft vehicle health management applications. The diagnostic system contains a data filter and an inference engine. The data filter is designed to intelligently select only the necessary data for analysis, while the inference engine is designed for failure detection, warning, and decision on corrective actions using fuzzy logic synthesis. Due to its adaptive nature and on-line learning ability, the diagnostic system is capable of dealing with environmental noise, uncertainties, conflict information, and sensor faults.

Wu, G. Gordon↗
NASA NTRS2016

Evidence for the Thermal Sunyaev Zeldovich Effect Associated with Quasar Feedback

Using a radio-quiet subsample of the Sloan Digital Sky Survey spectroscopic quasar catalogue, spanning redshifts 0.5-3.5, we derive the mean millimetre and far-infrared quasar spectral energy distributions (SEDs) via a stacking analysis of Atacama Cosmology Telescope and Herschel-Spectral and Photometric Imaging REceiver data. We constrain the form of the far-infrared emission and find 3 sigma-4 sigma evidence for the thermal Sunyaev-Zel'dovich (SZ) effect, characteristic of a hot ionized gas component with thermal energy (6.2 plus or minus 1.7) × 10 (exp 60) erg. This amount of thermal energy is greater than expected assuming only hot gas in virial equilibrium with the dark matter haloes of (1-5) × 10(exp 12) h(exp −1) solar mass that these systems are expected to occupy, though the highest quasar mass estimates found in the literature could explain a large fraction of this energy. Our measurements are consistent with quasars depositing up to (14.5 +/- 3.3)tau (sub 8)(exp -1) per cent of their radiative energy into their circumgalactic environment if their typical period of quasar activity is tau(sub 8) x 108 yr. For high quasar host masses, approximately 10(exp 13) h(exp −1) solar mass, this percentage will be reduced. Furthermore, the uncertainty on this percentage is only statistical and additional systematic uncertainties enter at the 40 per cent level. The SEDs are dust dominated in all bands and we consider various models for dust emission. While sufficiently complex dust models can obviate the SZ effect, the SZ interpretation remains favoured at the 3 sigma-4 sigma level for most models.

Sunyaev-Zeldovich (SZ)↗
NASA NTRS2005

Monte Carlo Simulation of Markov, Semi-Markov, and Generalized Semi- Markov Processes in Probabilistic Risk Assessment

A standard tool of reliability analysis used at NASA-JSC is the event tree. An event tree is simply a probability tree, with the probabilities determining the next step through the tree specified at each node. The nodal probabilities are determined by a reliability study of the physical system at work for a particular node. The reliability study performed at a node is typically referred to as a fault tree analysis, with the potential of a fault tree existing.for each node on the event tree. When examining an event tree it is obvious why the event tree/fault tree approach has been adopted. Typical event trees are quite complex in nature, and the event tree/fault tree approach provides a systematic and organized approach to reliability analysis. The purpose of this study was two fold. Firstly, we wanted to explore the possibility that a semi-Markov process can create dependencies between sojourn times (the times it takes to transition from one state to the next) that can decrease the uncertainty when estimating time to failures. Using a generalized semi-Markov model, we studied a four element reliability model and were able to demonstrate such sojourn time dependencies. Secondly, we wanted to study the use of semi-Markov processes to introduce a time variable into the event tree diagrams that are commonly developed in PRA (Probabilistic Risk Assessment) analyses. Event tree end states which change with time are more representative of failure scenarios than are the usual static probability-derived end states.

English, Thomas↗
NASA NTRS1967

Review of the Lightning Strike Incident at Launch Complex 37 on July 27, 1967, and Comparison to a Gemini Lightning Strike

The Launch Complex 37 lightning strike of July 27, 1967, was reviewed and compared to a similar incident on the Gemini Program. Available data indicate little likelihood of damaging currents having been present in SA-204 Launch Vehicle or the ground equipment during the July 27th incident. Based on the results of subsystem and system testing after the strike, anticipated results of future testing, the six months elapsed time between the strike-and launch, and the fact that much of the critical airborne electrical/electronic equipment has been removed since the strike for other reasons, no new actions are considered necessary at this time in the Gemini case, significant failures occurred in both airborne and ground circuits. Due to the resultant semi, condlictor uncertainty, and the relatively' short time prior to planned launch, all critical airborne components containing semiconduetors were replaced, and a sophisticated data comparison task was implemented.

Llewellyn, J. A.↗
NASA NTRS2016

Using Multimodal Input for Autonomous Decision Making for Unmanned Systems

Autonomous decision making in the presence of uncertainly is a deeply studied problem space particularly in the area of autonomous systems operations for land, air, sea, and space vehicles. Various techniques ranging from single algorithm solutions to complex ensemble classifier systems have been utilized in a research context in solving mission critical flight decisions. Realized systems on actual autonomous hardware, however, is a difficult systems integration problem, constituting a majority of applied robotics development timelines. The ability to reliably and repeatedly classify objects during a vehicles mission execution is vital for the vehicle to mitigate both static and dynamic environmental concerns such that the mission may be completed successfully and have the vehicle operate and return safely. In this paper, the Autonomy Incubator proposes and discusses an ensemble learning and recognition system planned for our autonomous framework, AEON, in selected domains, which fuse decision criteria, using prior experience on both the individual classifier layer and the ensemble layer to mitigate environmental uncertainty during operation.

Neilan, James H.↗