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At least 343 records · Page 19

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NASA NTRS2016

Decision Manifold Approximation for Physics-Based Simulations

With the recent surge of success in big-data driven deep learning problems, many of these frameworks focus on the notion of architecture design and utilizing massive databases. However, in some scenarios massive sets of data may be difficult, and in some cases infeasible, to acquire. In this paper we discuss a trajectory-based framework that quickly learns the underlying decision manifold of binary simulation classifications while judiciously selecting exploratory target states to minimize the number of required simulations. Furthermore, we draw particular attention to the simulation prediction application idealized to the case where failures in simulations can be predicted and avoided, providing machine intelligence to novice analysts. We demonstrate this framework in various forms of simulations and discuss its efficacy.

Wong, Jay Ming↗

NASA NTRS1973

Image analysis techniques associated with automatic data base generation.

This paper considers some basic problems relating to automatic data base generation from imagery, the primary emphasis being on fast and efficient automatic extraction of relevant pictorial information. Among the techniques discussed are recursive implementations of some particular types of filters which are much faster than FFT implementations, a 'sequential similarity detection' technique of implementing matched filters, and sequential linear classification of multispectral imagery. Several applications of the above techniques are presented including enhancement of underwater, aerial and radiographic imagery, detection and reconstruction of particular types of features in images, automatic picture registration and classification of multiband aerial photographs to generate thematic land use maps.

Bond, A. D.↗

NASA NTRS2004

Lunar and Planetary Science XXXV: Meteorites

The session "Meteorites" included the following reports:Description of a New Stony Meteorite Find from Bulloch County, Georgia; Meteorite Ablation Derived from Cosmic Ray Track Data Dhofar 732: A Mg-rich Orthopyroxenitic Achondrite Halogens, Carbon and Sulfur in the Tagish Lake Meteorite: Implications for Classification and Terrestrial Alteration; Electromagnetic Scrape of Meteorites and Probably Columbia Tiles; Pre-Atmospheric Sizes and Orbits of Several Chondrites; Research of Shock-Thermal History of the Enstatite Chondrites by Track, Thermoluminescence and Neutron-Activation (NAA) Methods; Radiation and Shock-thermal History of the Kaidun CR2 Chondrite Glass Inclusions; On the Problem of Search for Super-Heavy Element Traces in the Meteorites: Probability of Their Discovery by Three-Prong Tracks due to Nuclear Spontaneous Fission Trace Element Abundances in Separated Phases of Pesyanoe, Enstatite Achondrite; Evaluation of Cooling Rate Calculated by Diffusional Modification of Chemical Zoning: Different Initial Profiles for Diffusion Calculation; Mineralogical Features and REE Distribution in Ortho- and Clinopyroxenes of the HaH 317 Enstatite Chondrite Dhofar 311, 730 and 731: New Lunar Meteorites from Oman; The Deuterium Content of Individual Murchison Amino Acids; Clues to the Formation of PV1, an Enigmatic Carbon-rich Chondritic Clast from the Plainview H-Chondrite Regolith Breccia ;Numerical Simulations of the Production of Extinct Radionuclides and ProtoCAIs by Magnetic Flaring.

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NASA NTRS1990

Expert systems and imaging - NASA's start-up work in intelligent image management

The problem of image management for NASA's Space Shuttle program and the future role of expert systems are considered. The difficulties involved in the storage and retrieval of the estimated 100,000 color photographs used for verification of essential installation, test, and repair procedures for Space Shuttle prelaunch are discussed. It is noted that the collection, classification, storage, and retrieval of high-quality pictoral images is possible through the use of pixels and an expert systems-assisted relational data base management system. The development of a query by pictorial example process is discussed. The NASA Intelligent Interactive Visual Data Base Management Systems project is detailed. It aims to conduct a systems analysis of a large-scale traditional image processing operation, collect data on critical human performance factors in the areas of image creation, processing, classification, storage, and retreival, and validate the attributes identified through the creation and testing of prototype models.

Ragusa, James M.↗

NASA NTRS1985

KARL: A Knowledge-Assisted Retrieval Language

Data classification and storage are tasks typically performed by application specialists. In contrast, information users are primarily non-computer specialists who use information in their decision-making and other activities. Interaction efficiency between such users and the computer is often reduced by machine requirements and resulting user reluctance to use the system. This thesis examines the problems associated with information retrieval for non-computer specialist users, and proposes a method for communicating in restricted English that uses knowledge of the entities involved, relationships between entities, and basic English language syntax and semantics to translate the user requests into formal queries. The proposed method includes an intelligent dictionary, syntax and semantic verifiers, and a formal query generator. In addition, the proposed system has a learning capability that can improve portability and performance. With the increasing demand for efficient human-machine communication, the significance of this thesis becomes apparent. As human resources become more valuable, software systems that will assist in improving the human-machine interface will be needed and research addressing new solutions will be of utmost importance. This thesis presents an initial design and implementation as a foundation for further research and development into the emerging field of natural language database query systems.

Dominick, Wayne D.↗

NASA NTRS1989

Steps toward interstellar silicate dust mineralogy

One of the most certain facts on interstellar dust is that it contains grains with silicon oxygen tetrahedra (SOT), the internal vibrations of which cause the well known silicate bands at 10 and 18 microns. The broad and almost structureless appearance of them demonstrates lack of translation symmetry in these solids that must be considered amorphous or glassy silicates. There is no direct information on the cations in these interstellar silicates and on the number of bridging oxygens per tetrahedron (NBO). Comparing experimental results gained on amorphous silicates, e.g., silicate glasses, of cosmically most abundant metals (Mg, Fe, Ca, Al) with the observations is the only way to investigate interstellar silicate dust mineralogy (cf, Dorschner and Henning, 1986). At Jena University Observatory IR spectra of submicrometer-sized grains of pyroxene glasses (SSG) were studied. Pyroxenes are common minerals in asteroids, meteorites, interplanetary, and supposedly also cometary dust particles. Pyroxenes consist of linearly connected SOT (NBO=2). In the vitreous state reached by quenching melted minerals, the SOT remain nearly undistorted (Si-O bond length unchanged); the Si-O-Si angles at the bridging oxygens of pyroxenes, however, scatter statistically. Therefore, the original cation oxygen symmetry of the crystal (octahedral and hexahedral coordination by O) is completely lost. The blended bands at 10 and 18 microns lose their diagnostic differences and become broad and structureless. This illustrates best the basic problem of interstellar silicate mineral diagnostics. Optical data of glasses of enstatite, bronzite, hypersthene, diopside, salite, and hedenbergite have been derived. Results of enstatite (E), bronzite (B), and hypersthene (H) show very good agreement with the observed silicate features in the IR spectra of evolutionarily young objects that show P-type silicate signature according to the classification by Gurtler and Henning (1986). Compositional parameters and main characteristics of experimental SSG spectra in IR for the glasses E, B, and H are shown in tabular form. Results fit excellently the relations derived by Koike and Hasegawa (1987) and suggest that the band ratio of the astronomical silicate by Draine and Lee (1984) is too low.

Dorschner, J.↗

NASA NTRS1989

Use of robust estimators in parametric classifiers

The parametric approach to density estimation and classifier design is a well studied subject. The parametric approach is desirable because basically it reduces the problem of classifier design to that of estimating a few parameters for each of the pattern classes. The class parameters are usually estimated using maximum-likelihood (ML) estimators. ML estimators are, however, very sensitive to the presence of outliers. Several robust estimators of mean and covariance matrix and their effect on the probability of error in classification are examined. Comments are made about alpha-ranked (alpha-trimmed) estimators.

Safavian, S. Rasoul↗

NASA NTRS2004

The Tropical Convective Spectrum: Archetypal Vertical Structures - 1

A taxonomy of tropical convective vertical structures is constructed through cluster analysis of three years of Tropical Rainfall Measuring Mission [TRMM] Precipitation Radar [PR] vertical profiles, their surface rainfall and associated radar-based classifiers (convective/stratiform and bright band existence). archetypal profile types are identified. These include nine convective types, divided into warm, "just cold", midlevel, deep and deep/wet-growth categories, seven stratiform types, divided into warm, "just cold", midlevel and deep categories, three "mixed" types (deep profiles with low reflectivity aloft), and six fragment types (non-precipitating anvils and sheared deep convective profiles). The taxonomy allows for description of any storm or local Convective spectrum by the nine primary convective and stratiform types, a significant reduction over full three-dimensional radar data which nonetheless retains vertical structure information. The analysis provides a quasi-independent corroboration of the TRMM 2A23 convective/stratiform classification. The global frequency of occurrence and contribution to rainfall for the profile types is presented, demonstrating primary rainfall contribution by midlevel glaciated convection and similar depth decaying/stratiform stages. Close correspondence is found between deep convective profile frequency and annualized lightning production. Passive microwave and lightning properties associated with the profiles are reported, and cases presented illustrating known nonuniqueness problems with 85 and 37 GHz brightness temperature pairs (the same pairs corresponding to both convective and stratiform profiles), and how supplementary lightning information might be used to mitigate these problems.

Boccippio, Dennis J.↗

NASA NTRSDate not supplied

Physics Informed Neural Nets for Systems Health Management

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Development in data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. The research work presents application of physics-informed neural nets application to a representative electric powertrain for unmanned aerial vehicles. The model is composed of physics-derived and empirical equations, integrated with connected networks that are strategically placed within the model to substitute equations that are subject to large uncertainty. Polynomial fit driven by heuristics or empirical observations can be substituted by more flexible networks that can minimize the error between model predictions and observations without being restricted to a predefined functional form. This modeling strategy allows training of networks deep inside the model and unknown parameters in a single learning stage.

Physics Informed↗

NASA NTRS1981

Contextual classification of multispectral image data

A general method is presented for exploiting both spatial and spectral information when classifying multispectral image data. This statistical classification algorithm utilizes the tendency of certain ground cover classes to be more likely to occur in some contexts than others. The theoretical model assumes the two-dimensional array of random observations and a 0-1 loss function, a distribution of the p-context array that is spatially invariant, and class-conditional independence for the observations. The problems that prevent the immediate use of this context classifier are the need for a generally applicable method for making adequate estimates of the context distribution and a reduction in the computational intensivity of the classifier. The former problem is being approached by a method that raises the relative frequency value for each class configuration to a power and uses the result as the context distribution estimate. The second is being approached by searching for a less computationally intensive algorithm.

Tilton, J. C.↗

NASA NTRS1986

Airborne trace contaminants of possible interest in CELSS

One design goal of Closed Ecological Life Support Systems (CELSS) for long duration space missions is to maintain an atmosphere which is healthy for all the desirable biological species and not deleterious to any of the mechanical components in that atmosphere. CELESS design must take into account the interactions of at least six major components; (1) humans and animals, (2) higher plants, (3) microalgae, (4) bacteria and fungi, (5) the waste processing system, and (6) other mechanical systems. Each of these major components can be both a source and a target of airborne trace contaminants in a CELSS. A range of possible airborne trace contaminants is discussed within a chemical classification scheme. These contaminants are analyzed with respect to their probable sources among the six major components and their potential effects on those components. Data on airborne chemical contaminants detected in shuttle missions is presented along with this analysis. The observed concentrations of several classes of compounds, including hydrocarbons, halocarbons, halosilanes, amines and nitrogen oxides, are considered with respect to the problems which they present to CELSS.

Garavelli, J. S.↗

NASA NTRS2006

Classification and Prediction of RF Coupling inside A-320 and A-319 Airplanes using Feed Forward Neural Networks

Neural Network Modeling is introduced in this paper to classify and predict Interference Path Loss measurements on Airbus 319 and 320 airplanes. Interference patterns inside the aircraft are classified and predicted based on the locations of the doors, windows, aircraft structures and the communication/navigation system-of-concern. Modeled results are compared with measured data and a plan is proposed to enhance the modeling for better prediction of electromagnetic coupling problems inside aircraft.

Jafri, Madiha↗

NASA NTRS1973

The long-term motion of artificial Jovian satellites

This paper is a description of a preliminary study aimed at the classification and establishment of realistic orbit design criteria of artificial satellites of Jupiter. The work is concentrated on investigation of the factors that will affect the long-term motion, and particularly the dynamic lifetime, of the first Jupiter orbiters. Included is a perturbation analysis describing the effects of the Jovian gravity, the Galilean satellites, and the solar gravitational perturbations. An unusual problem is identified in the great difficulty of avoiding near-collisions with the Galilean satellites. The results of the perturbation and dynamic lifetime analyses are used in brief discussions of some possible Jupiter orbit missions.

Uphoff, C.↗

NASA NTRS1985

What are the best radar wavelengths, incidence angles and polarizations for geologic applications? A statistical approach

Linear discriminant analysis of multifrequency and multipolarization radar scatterometer data of lava flows and sedimentary rocks indicates that the lava flows can be separated by age and the sedimentary rocks can be discriminated from one another. The optimum wavelengths, polarizations and incidence angles among those available for these problems was determined by the discriminant analysis program. For separation of the lava flows, shorter wavelengths, smaller incidence angles and horizontal polarization are best. A SIR-C radar configuration could provide nearly complete discrimination of these lava flows. Conversely, the longer wavelengths, larger incidence angles and vertical polarization was preferred for sedimentary rocks, perhaps due to the slight vegetation cover. Satisfactory classification of sedimentary rocks requires more radar data than for the lavas. These results are potentially useful both for radar system configuration and for geological applications. The method developed here may provide a rationale for user specification of imaging system parameters.

Blom, R.↗

NASA NTRS1999

A Neural Network Aero Design System for Advanced Turbo-Engines

An inverse design method calculates the blade shape that produces a prescribed input pressure distribution. By controlling this input pressure distribution the aerodynamic design objectives can easily be met. Because of the intrinsic relationship between pressure distribution and airfoil physical properties, a Neural Network can be trained to choose the optimal pressure distribution that would meet a set of physical requirements. Neural network systems have been attempted in the context of direct design methods. From properties ascribed to a set of blades the neural network is trained to infer the properties of an 'interpolated' blade shape. The problem is that, especially in transonic regimes where we deal with intrinsically non linear and ill posed problems, small perturbations of the blade shape can produce very large variations of the flow parameters. It is very unlikely that, under these circumstances, a neural network will be able to find the proper solution. The unique situation in the present method is that the neural network can be trained to extract the required input pressure distribution from a database of pressure distributions while the inverse method will still compute the exact blade shape that corresponds to this 'interpolated' input pressure distribution. In other words, the interpolation process is transferred to a smoother problem, namely, finding what pressure distribution would produce the required flow conditions and, once this is done, the inverse method will compute the exact solution for this problem. The use of neural network is, in this context, highly related to the use of proper optimization techniques. The optimization is used essentially as an automation procedure to force the input pressure distributions to achieve the required aero and structural design parameters. A multilayered feed forward network with back-propagation is used to train the system for pattern association and classification.

Sanz, Jose M.↗

NASA NTRS2020

Strategic Deconfliction Performance: Results and Analysis from the NASA UTM Technical Capability Level 4 Demonstration

Unmanned Aircraft System (UAS) Traffic Management (UTM) refers to the service-based, cooperative approach to the management of small UAS in the National Airspace System that is safe, scalable, and fair. UTM provides the means to manage the airspace in a complementary manner that does not burden the current air traffic control workforce or infrastructure but allows the Air Navigation Service Provider to maintain its regulatory and operational authority of the airspace. A key feature of UTM is the ability to provide operators the means to strategically deconflict operations from others in the airspace through the digital exchange of information via supporting services. Through this approach, the four-dimensional operation volumes that encompass the intent of operators in a given area are discoverable and can be used for airspace awareness as well as planning conflict free operations that account for and avoid other operations. In certain cases, it is also possible to negotiate volume intersections for shared airspace use without the need to re-plan. In the NASA UTM concept, strategic deconfliction is the first layer of three in the overall conflict management model. The three layers of the conflict management model, which follow the International Civil Aviation Organization’s scheme [ICAO 2005] are: strategic conflict management, separate provision, and collision avoidance. In UTM, the strategic layer mostly occurs prior to departure, but is applicable to en route operations with sufficient planning horizon. The initial requirements for a strategic deconfliction capability within UTM are defined in a NASA publication [Rios 2018]. Within the concept and implementation of service-provided strategic deconfliction is the notion of priority. It is understood that there are instances in which an operation requires a priority designation within the UTM system and special handling accordingly to provide situation awareness and facilitate appropriate responses from other airspace users. Examples of situations requiring priority designation include: when an operator declares an emergency due to problems with the vehicle or its immediate surroundings; operations that are in support of certain organizations (e.g., public safety and first responders); or special missions that also require priority use of airspace (e.g., emergency medical deliveries). UAS Volume Reservations (UVRs) also relate to the topic of priority in the sense that the airspace that the volume encompasses has a different status or classification in which unassociated operations must vacate if inside, or avoid if outside, through strategic deconfliction with the volume. Operations that are specially permitted to access the UVR area are typically assigned priority status given the nature of their mission and their associated credentials. The ability to perform strategic deconfliction, handle certain operations with a priority distinction, and establish UVRs that are communicated throughout the UTM system, is predicated on an architecture that has been established through an evolutionary process in response to close collaboration with stakeholders from government and industry. Another important and influential aspect of these capabilities and architecture is the live, distributed flight tests that have been conducted across the Technical Capability Levels (TCLs) that culminated with a set of complex tests performed as part of TCL4 [Rios 2020]. The TCL4 flight test involved two FAA-designated UAS test sites building teams to collaborate with NASA’s UTM Project on the execution of several detailed, small UAS scenarios in urban environments.

conflict management↗

NASA NTRS1977

Remote sensing data processing - Two years ago, today, and two years from today

Certain technical problems arising in the recent past (1975) in the field of the processing of remote sensing data are reviewed including approaches to the analysis of Landsat MSS data and technical difficulties which must be overcome to achieve operational data processing. The current status of remote sensing data processing is then examined with emphasis on such current technical issues as training selection and labeling, sampling schemes and classification and mensuration. Hardware projections are made for the near future (1979) relative to the development of remote sensing data processing.

Holmes, Q. A.↗

NASA NTRS1996

Multiresolution and Explicit Methods for Vector Field Analysis and Visualization

We first report on our current progress in the area of explicit methods for tangent curve computation. The basic idea of this method is to decompose the domain into a collection of triangles (or tetrahedra) and assume linear variation of the vector field over each cell. With this assumption, the equations which define a tangent curve become a system of linear, constant coefficient ODE's which can be solved explicitly. There are five different representation of the solution depending on the eigenvalues of the Jacobian. The analysis of these five cases is somewhat similar to the phase plane analysis often associate with critical point classification within the context of topological methods, but it is not exactly the same. There are some critical differences. Moving from one cell to the next as a tangent curve is tracked, requires the computation of the exit point which is an intersection of the solution of the constant coefficient ODE and the edge of a triangle. There are two possible approaches to this root computation problem. We can express the tangent curve into parametric form and substitute into an implicit form for the edge or we can express the edge in parametric form and substitute in an implicit form of the tangent curve. Normally the solution of a system of ODE's is given in parametric form and so the first approach is the most accessible and straightforward. The second approach requires the 'implicitization' of these parametric curves. The implicitization of parametric curves can often be rather difficult, but in this case we have been successful and have been able to develop algorithms and subsequent computer programs for both approaches. We will give these details along with some comparisons in a forthcoming research paper on this topic.

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