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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Expressing Functionality Using Design Patterns, A Real-World Example

Digital Engineering is a transformative strategy that leverages an integrated model-based approach to improve communication, decision making, design understanding, and acquisition efficiency of system development. As modern systems are derived from pre-existing systems, harvesting tacit knowledge from existing systems in a useful, model-based way will reduce the experiential learning and cognition required for new system development, contributing to a Digital Engineering transformation. This study enables such a technique by demonstrating the use of architectural theory in expressing tacit knowledge from existing systems and presenting that knowledge according to the model-based view offered by the Functional Architecture of Systems methodology. By validating the functional information expressed by the design pattern, this work solidifies design patterns as a critical component of a technical architecture and proposes a functional architecture viewpoint for describing mined knowledge in a usable, model-based, way suitable for archival in a modern knowledge management system.

Systems Engineering↗
NASA NTRSDate not supplied

Examination of Lunar Regolith Simulants By SEM-EDS and Imaging Raman Spectroscopy

The Artemis series lunar missions will include sample returns from the lunar south pole. Lunar regolith simulants (RS) generated in the lab provide opportunities to compare two surface science techniques: scanning electron microscopy (SEM-EDS) and Raman induced surface spectroscopy. The results will also be applicable for supporting future commercial lunar payload services (CLPS) and Artemis surface. Surface characterization contributes to continued development of lunar regolith studies and adds to various regolith databases. In characterizing various lunar regolith simulants, part of the aim should be to standardize techniques and utilize anticipated methods available for astromaterials studied during, or returned from, upcoming missions, particularly samples collected from the Moon’s south pole and permanently shadowed regions (PSRs).. An initial survey of available simulants has been started with Raman scanning process for particle counting the results of which will enrich the NASA-JSC Simulant Development Lab (SDL) simulant properties database and the Colorado School of Mines Planetary Simulant Data Base. An SEM-EDS dataset of raw regolith simulant materials are collected.

Raman Microscopy↗
NASA NTRS1978

Possible environmental effects of increased coal use in California

If coal is to be utilized in California it must be made compatible with the state's drive toward restoring environmental quality. The impacts resulting from coal's mining and transportation, or from water consumption, water quality degradation and electric transmission line routing can probably be adequately mitigated through strong and early planning efforts, the use of improved control and process technologies, and sincere utility commitment. The socioeconomic impacts may prove somewhat more difficult to satisfactorily mitigate. Of greatest concern is adequate control of generated air pollutants and disposal of solid and liquid wastes since acceptable technologies or handling techniques have yet to be conclusively demonstrated.

Carey, D. L.↗
NASA NTRS1981

Geologic applications of thermal-inertia mapping from satellite

In the Powder River Basin, Wyo., narrow geologic units having thermal inertias which contrast with their surroundings can be discriminated in optimal images. A few subtle thermal inertia anomalies coincide with areas of helium leakage believed to be associated with deep oil and gas concentrations. The most important results involved delineation of tectonic framework elements some of which were not previously recognized. Thermal and thermal inertia images also permit mapping of geomorphic textural domains. A thermal lineament appears to reveal a basement discontinuity which involves the Homestake Mine in the Black Hill, a zone of Tertiary igneous activity and facies control in oil producing horizons. Applications of these data to the Cabeza Prieta, Ariz., area illustrate their potential for igneous rock type discrimination. Extension to Yellowstone National Park resulted in the detection of additional structural information but surface hydrothermal features could not be distinguished with any confidence. A thermal inertia mapping algorithm, a fast and accurate image registration technique, and an efficient topographic slope and elevation correction method were developed.

Offield, T. W.↗
NASA NTRS1974

Geologic evaluation and applications of ERTS-1 imagery over Georgia

Satellite imagery and other remote sensing tools and techniques have provided a powerful tool to assist geologic research; significantly increased the mapping efficiency of field geologists; shown new lineaments associated with known shear and fault zones; delineated new structural features; provided a tool to reevaluate tectonic history; helped to locate potential ground-water sources and areas of aquifer recharge; defined areas of geologic hazards; shown areas of heavy siltation in major reservoirs; and, by close interval repetition, aided in monitoring surface mine reclamation activities and the environmental protection of the intricate marshland system. The Georgia Geological Survey has been engaged in regional mapping for the new state geologic map. ERTS-1 images enlarged to compatible mapping scales have increased field geologic mapping efficiency by at least 25%. There are a number of areas where data from ERTS-1 imagery has allowed a notably higher level of precision than has been available with any amount of field work on the ground.

Pickering, S. M.↗
NASA NTRS1979

Analysis and evaluation in the production process and equipment area of the low-cost solar array project

Analyses of slicing processes and junction formation processes are presented. A simple method for evaluation of the relative economic merits of competing process options with respect to the cost of energy produced by the system is described. An energy consumption analysis was developed and applied to determine the energy consumption in the solar module fabrication process sequence, from the mining of the SiO2 to shipping. The analysis shows that, in current technology practice, inordinate energy use in the purification step, and large wastage of the invested energy through losses, particularly poor conversion in slicing, as well as inadequate yields throughout. The cell process energy expenditures already show a downward trend based on increased throughput rates. The large improvement, however, depends on the introduction of a more efficient purification process and of acceptable ribbon growing techniques.

Goldman, H.↗
NASA NTRS1979

Processing of multispectral thermal IR data for geologic applications

Multispectral thermal IR data were acquired with a 24-channel scanner flown in an aircraft over the E. Tintic Utah mining district. These digital image data required extensive computer processing in order to put the information into a format useful for a geologic photointerpreter. Simple enhancement procedures were not sufficient to reveal the total information content because the data were highly correlated in all channels. The data were shown to be dominated by temperature variations across the scene, while the much more subtle spectral variations between the different rock types were of interest. The image processing techniques employed to analyze these data are described.

Kahle, A. B.↗
NASA NTRS1975

Utilizing Skylab data in on-going resources management programs in the state of Ohio

The author has identified the following significant results. The use of Skylab imagery for total area woodland surveys was found to be more accurate and cheaper than conventional surveys using aerial photo-plot techniques. Machine-aided (primarily density slicing) analyses of Skylab 190A and 190B color and infrared color photography demonstrated the feasibility of using such data for differentiating major timber classes including pines, hardwoods, mixed, cut, and brushland providing such analyses are made at scales of 1:24,000 and larger. Manual and machine-assisted image analysis indicated that spectral and spatial capabilities of Skylab EREP photography are adequate to distinguish most parameters of current, coal surface mining concern associated with: (1) active mining, (2) orphan lands, (3) reclaimed lands, and (4) active reclamation. Excellent results were achieved when comparing Skylab and aerial photographic interpretations of detailed surface mining features. Skylab photographs when combined with other data bases (e.g., census, agricultural land productivity, and transportation networks), provide a comprehensive, meaningful, and integrated view of major elements involved in the urbanization/encroachment process.

Baldridge, P. E.↗
NASA NTRS2023

Machine Intelligence for Radiation Science: Summary of the Radiation Research Society 67th Annual Meeting Symposium

The era of high-throughput techniques created big data in the medical field and research disciplines. Machine intelligence (MI) approaches can overcome critical limitations on how those large-scale data sets are processed, analyzed, and interpreted. The 67 th Annual Meeting of the Radiation Research Society featured a symposium on MI approaches to highlight recent advancements in the radiation sciences and their clinical applications. This article summarizes three of those presentations regarding recent developments for metadata processing and ontological formalization, data mining for radiation outcomes in pediatric oncology, and imaging in lung cancer.

radiation↗
NASA NTRS1981

An unsupervised classification approach for analysis of Landsat data to monitor land reclamation in Belmont county, Ohio

Two unsupervised classification procedures for analyzing Landsat data used to monitor land reclamation in a surface mining area in east central Ohio are compared for agreement with data collected from the corresponding locations on the ground. One procedure is based on a traditional unsupervised-clustering/maximum-likelihood algorithm sequence that assumes spectral groupings in the Landsat data in n-dimensional space; the other is based on a nontraditional unsupervised-clustering/canonical-transformation/clustering algorithm sequence that not only assumes spectral groupings in n-dimensional space but also includes an additional feature-extraction technique. It is found that the nontraditional procedure provides an appreciable improvement in spectral groupings and apparently increases the level of accuracy in the classification of land cover categories.

Brumfield, J. O.↗
NASA NTRS2003

Fractals and Spatial Methods for Mining Remote Sensing Imagery

The rapid increase in digital remote sensing and GIS data raises a critical problem -- how can such an enormous amount of data be handled and analyzed so that useful information can be derived quickly? Efficient handling and analysis of large spatial data sets is central to environmental research, particularly in global change studies that employ time series. Advances in large-scale environmental monitoring and modeling require not only high-quality data, but also reliable tools to analyze the various types of data. A major difficulty facing geographers and environmental scientists in environmental assessment and monitoring is that spatial analytical tools are not easily accessible. Although many spatial techniques have been described recently in the literature, they are typically presented in an analytical form and are difficult to transform to a numerical algorithm. Moreover, these spatial techniques are not necessarily designed for remote sensing and GIS applications, and research must be conducted to examine their applicability and effectiveness in different types of environmental applications. This poses a chicken-and-egg problem: on one hand we need more research to examine the usability of the newer techniques and tools, yet on the other hand, this type of research is difficult to conduct if the tools to be explored are not accessible. Another problem that is fundamental to environmental research are issues related to spatial scale. The scale issue is especially acute in the context of global change studies because of the need to integrate remote-sensing and other spatial data that are collected at different scales and resolutions. Extrapolation of results across broad spatial scales remains the most difficult problem in global environmental research. There is a need for basic characterization of the effects of scale on image data, and the techniques used to measure these effects must be developed and implemented to allow for a multiple scale assessment of the data before any useful process-oriented modeling involving scale-dependent data can be conducted. Through the support of research grants from NASA, we have developed a software module called ICAMS (Image Characterization And Modeling System) to address the need to develop innovative spatial techniques and make them available to the broader scientific communities. ICAMS provides new spatial techniques, such as fractal analysis, geostatistical functions, and multiscale analysis that are not easily available in commercial GIS/image processing software. By bundling newer spatial methods in a user-friendly software module, researchers can begin to test and experiment with the new spatial analysis methods and they can gauge scale effects using a variety of remote sensing imagery. In the following, we describe briefly the development of ICAMS and present application examples.

Lam, Nina↗
NASA NTRS2023

Orbital Workshop Concept

This is a concept for a system that can perform certain aspects of recycling/manufacturing/integration/servicing in zero-g & low-g space environments. The system consists of a slowly rotating inflatable tube that surrounds a system being worked on. This design captures debris by generating artificial gravity, thereby allowing “dirty” manufacturing/ recycling/ integration/ servicing techniques and enables loading/unloading of large systems. The system encapsulates the piece being worked on and uses an internal robotic arm with appropriate tools. This system is designed to complement the abilities of the Orbital Collector (see NTR 1660756036).

manufacturing↗
NASA NTRS1974

Geological evaluation and applications of ERTS-1 imagery over Georgia

ERTS-1 70mm and 9 x 9 film negatives are being used by conventional and color enhancement methods as a tool for geologic investigation. Geologic mapping and mineral exploration by conventional methods is very difficult in Georgia. Thick soil cover and heavy vegetation cause outcrops of bed rock to be small, rare and obscure. ERTS imagery, and remote sensing in general have helped delineate: (1) major tectonic boundaries; (2) lithologic contacts; (3) foliation trends; (4) topographic lineaments; and (5) faults. The ERTS-1 MSS imagery yields the greatest amount of geologic information on the Piedomont, Blue Ridge, and Valley and Ridge Provinces of Georgia where topography is strongly controlled by the bedrock geology. ERTS imagery, and general remote sensing techniques, have provided us with a powerful tool to assist geologic research; have significantly increased the mapping efficiency of our field geologists; have shown new lineaments associated with known shear and fault zones; have delineated new structural features; have provided a tool to re-evaluate our tectonic history; have helped to locate potential ground water sources and areas of aquifer recharge; have defined areas of geologic hazards; have shown areas of heavy siltation in major reservoirs; and by its close interval repetition, have aided in monitoring surface mine reclamation activities and the environmental protection of our intricate marshland system.

Pickering, S. M.↗
NASA NTRS1990

Genetic algorithm based fuzzy control of spacecraft autonomous rendezvous

The U.S. Bureau of Mines is currently investigating ways to combine the control capabilities of fuzzy logic with the learning capabilities of genetic algorithms. Fuzzy logic allows for the uncertainty inherent in most control problems to be incorporated into conventional expert systems. Although fuzzy logic based expert systems have been used successfully for controlling a number of physical systems, the selection of acceptable fuzzy membership functions has generally been a subjective decision. High performance fuzzy membership functions for a fuzzy logic controller that manipulates a mathematical model simulating the autonomous rendezvous of spacecraft are learned using a genetic algorithm, a search technique based on the mechanics of natural genetics. The membership functions learned by the genetic algorithm provide for a more efficient fuzzy logic controller than membership functions selected by the authors for the rendezvous problem. Thus, genetic algorithms are potentially an effective and structured approach for learning fuzzy membership functions.

Karr, C. L.↗
NASA NTRSDate not supplied

ICE-RASSOR: Intelligent Capabilities Enhanced Regolith Advanced Surface Systems Operations Robot

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU)processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from a reduced sensor payload. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We apply supervised learning using real data to estimate the soil mass collected without the need for mass flow rate monitors or other explicate sensing techniques. We also create a reduced-order simulation environment to develop autonomous trenching controllers via reinforcement learning and prototype state estimation architectures. Our initial results suggest that excavated regolith mass can be inferred within 2.9% RMS error of full scale, and reinforcement learning for autonomous operations has learned viable trenching strategies and helped identify desirable sensing capabilities, arrangements, and considerations. Future work includes regolith mass estimation during dynamic operation, expanding our simulation to more complex environments, and transfer learning from simulation to hardware.

machine learning↗
NASA NTRSDate not supplied

ICE-RASSOR: Intelligent Capabilities Enhanced Regolith Advanced Surface Systems Operations Robot

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU) processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from on-board sensory. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We apply supervised learning using real data to estimate the soil mass collected without the need for mass flow rate monitors or other explicate sensing techniques. We also create a reduced-order simulation environment to develop autonomous trenching controllers via reinforcement learning and proto-type state estimation architectures. Our initial results suggest that excavated regolith mass can be inferred within 2.9% RMS error of full scale, and reinforcement learning for autonomous operations has learned viable trenching strategies and helped identify desirable sensing capabilities, arrangements, and considerations. Future work includes regolith mass estimation during dynamic operation, expanding our simulation to more complex environments, and transfer learning from simulation to hardware.

machine learning↗
NASA NTRS2006

Software Development Cost Estimation Executive Summary

Identify simple fully validated cost models that provide estimation uncertainty with cost estimate. Based on COCOMO variable set. Use machine learning techniques to determine: a) Minimum number of cost drivers required for NASA domain based cost models; b) Minimum number of data records required and c) Estimation Uncertainty. Build a repository of software cost estimation information. Coordinating tool development and data collection with: a) Tasks funded by PA&E Cost Analysis; b) IV&V Effort Estimation Task and c) NASA SEPG activities.

data mining↗
NASA NTRSDate not supplied

Characterization of Fluorescence Signals in Synthetic Anorthite

In-situ resource utilization (ISRU) is a key capability to enable a long term presence on the Moon and other planetary bodies. For example, efforts have been underway to develop processes to utilize the lunar regolith to produce building materials and extract useful resources. In processes that utilize the regolith directly to produce construction materials, such as in various sintering methods, characterizing the composition of the regolith is important as the composition can affect the optimal process parame-ters. In processes that involve extracting resources such as iron, oxygen, hydrogen, etc., identifying areas with higher abundance of a particular resource will be critical since different regions of the Moon exhibit differing regolith composition. To this end, Ra-man is one technique that can rapidly characterize the mineralogy of rock samples. This technique has al-ready been deployed on Mars to detect various miner-als including olivine, carbonates, phosphates, etc. Besides characterizing the mineralogy, Raman spectra often contain unwanted fluorescence signals that can mask Raman peaks. In some cases, the fluorescence signals are narrow enough to aid in the identification of specific elements in soils. In this work, we explore fluorescence peaks in a synthetic anorthite sample, which are at the same position as Ruby fluorescence peaks attributed to chromium. These fluorescence peaks, as well as similar fluorescence peaks attributed to other elements, could have important implications for ISRU and the mining of critical resources as has been previously described.

Raman Spectroscopy↗