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NASA NTRS1993

Low Cost Dewatering of Waste Slurries

The U.S. Bureau of Mines has developed a technique for dewatering mineral waste slurries which utilizes polymer and a static screen. A variety of waste slurries from placer gold mines and crushed stone operations have been successfully treated using the system. Depending on the waste, a number of polymers have been used successfully with polymer costs ranging from $0.05 to $0.15 per 1,000 gal treated. The dewatering is accomplished using screens made from either ordinary window screen or wedge wire. The screens used are 8 ft wide and 8 ft long. The capacity of the screens varies from 3 to 7 gpm/sq. ft. The water produced is acceptable for recycling to the plant or for discharge to the environment. For example, a fine grain dolomite waste slurry produced from a crushed stone operation was dewatered from a nominal 2.5 pct solids to greater than 50 pct solids using $0.10 to $0.15 worth of polymer per 1,000 gal of slurry. The resulting waste water had a turbidity of less than 50 NTU and could be discharged or recycled. The paper describes field tests conducted using the polymer-screen dewatering system.

Peterson, J. B.↗

NASA NTRS2011

Improve Data Mining and Knowledge Discovery Through the Use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(R) (MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykhian, Gholam Ali↗

NASA NTRS2011

Improve Data Mining and Knowledge Discovery through the use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(TradeMark)(MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykahian, Gholan Ali↗

NASA NTRS1994

An electromagnetic noncontacting sensor for thickness measurement in a dispersive medium

This paper describes a general purpose imaging technology developed by the U.S. Bureau of Mines (USBM) that, when fully implemented, will solve the general problem of 'seeing into the earth.' A first-generation radar coal thickness sensor, the RCTS-1, has been developed and field-tested in both underground and highwall mines. The noncontacting electromagnetic technique uses spatial modulation created by moving a simple sensor antenna in a direction along each axis to be measured while the complex reflection coefficient is measured at multiple frequencies over a two-to-one bandwidth. The antenna motion imparts spatial modulation to the data that enables signal processing to solve the problems of media, target, and antenna dispersion. Knowledge of the dielectric constant of the media is not necessary because the electrical properties of the media are determined automatically along with the distance to the target and thickness of each layer of the target. The sensor was developed as a navigation guidance sensor to accurately detect the coal/noncoal interface required for the USBM computer-assisted mining machine program. Other mining applications include the location of rock fractures, water-filled voids, and abandoned gas wells. These hazards can be detected in advance of the mining operation. This initiating technology is being expanded into a full three-dimensional (3-D) imaging system that will have applications in both the underground and surface environment.

Chufo, Robert L.↗

NASA NTRS1973

Study of application of ERTS-A imagery to fracture-related mine safety hazards in the coal mining industry

The author has identified the following significant results. Mined land reclamation analysis procedures developed within the Indiana portion of the Illinois Coal Basin were independently tested in Ohio utilizing 1:80,000 scale enlargements of ERTS-1 image 1029-15361-7 (dated August 21, 1972). An area in Belmont County was selected for analysis due to the extensive surface mining and the different degrees of reclamation occurring in this area. Contour mining in this area provided the opportunity to extend techniques developed for analysis of relatively flat mining areas in Indiana to areas of rolling topography in Ohio. The analysts had no previous experience in the area. Field investigations largely confirmed office analysis results although in a few areas estimates of vegetation percentages were found to be too high. In one area this error approximated 25%. These results suggest that systematic ERTS-1 analysis in combination with selective field sampling can provide reliable vegetation percentage estimates in excess of 25% accuracy with minimum equipment investment and training. The utility of ERTS-1 for practical and reasonably reliable update of mined lands information for groups with budget limitations is suggested. Many states can benefit from low cost updates using ERTS-1 imagery from public sources.

Wier, C. E.↗

NASA NTRS2013

Damage Detection Response Characteristics of Open Circuit Resonant (SansEC) Sensors

The capability to assess the current or future state of the health of an aircraft to improve safety, availability, and reliability while reducing maintenance costs has been a continuous goal for decades. Many companies, commercial entities, and academic institutions have become interested in Integrated Vehicle Health Management (IVHM) and a growing effort of research into "smart" vehicle sensing systems has emerged. Methods to detect damage to aircraft materials and structures have historically relied on visual inspection during pre-flight or post-flight operations by flight and ground crews. More quantitative non-destructive investigations with various instruments and sensors have traditionally been performed when the aircraft is out of operational service during major scheduled maintenance. Through the use of reliable sensors coupled with data monitoring, data mining, and data analysis techniques, the health state of a vehicle can be detected in-situ. NASA Langley Research Center (LaRC) is developing a composite aircraft skin damage detection method and system based on open circuit SansEC (Sans Electric Connection) sensor technology. Composite materials are increasingly used in modern aircraft for reducing weight, improving fuel efficiency, and enhancing the overall design, performance, and manufacturability of airborne vehicles. Materials such as fiberglass reinforced composites (FRC) and carbon-fiber-reinforced polymers (CFRP) are being used to great advantage in airframes, wings, engine nacelles, turbine blades, fairings, fuselage structures, empennage structures, control surfaces and aircraft skins. SansEC sensor technology is a new technical framework for designing, powering, and interrogating sensors to detect various types of damage in composite materials. The source cause of the in-service damage (lightning strike, impact damage, material fatigue, etc.) to the aircraft composite is not relevant. The sensor will detect damage independent of the cause. Damage in composite material is generally associated with a localized change in material permittivity and/or conductivity. These changes are sensed using SansEC. The unique electrical signatures (amplitude, frequency, bandwidth, and phase) are used for damage detection and diagnosis. An operational system and method would incorporate a SansEC sensor array on select areas of the aircraft exterior surfaces to form a "Smart skin" sensing surface. In this paper a new method and system for aircraft in-situ damage detection and diagnosis is presented. Experimental test results on seeded fault damage coupons and computational modeling simulation results are presented. NASA LaRC has demonstrated with individual sensors that SansEC sensors can be effectively used for in-situ composite damage detection of delamination, voids, fractures, and rips. Keywords: Damage Detection, Composites, Integrated Vehicle Health Monitoring (IVHM), Aviation Safety, SansEC Sensors

Dudley, Kenneth L.↗

NASA NTRS2019

Lunar Hydrogen Infrastructure

This presentation uses recent developments and discoveries to provide a high-level technical overview of a hydrogen-based energy infrastructure that supports sustained exploration of the moon. Combining creative orbital mechanics, robotic mining and process automation techniques, humanity can use lunar resources to generate the necessary propellant to support the transportation of cargo and humans between multiple points in the cis-lunar space. Robotic systems could collect water by either directly collecting the water entrained in the lunar regolith or by processing minerals found in the lunar regolith. These robotic systems could then electrolyze the water to generate high quality hydrogen and oxygen propellant and capitalize on the very low temperatures (< 15 Kelvin) in permanently shadowed regions (PSR) to maintain these propellants in a cryogenic state. Uncrewed service vehicles could distribute this lunar-generated resource throughout the cis-lunar space to intermediary waystations, like the Gateway. These platforms enable larger payloads into Low Earth Orbit (LEO) by providing the propellant necessary to travel through the cis-lunar space without requiring launch mass to lift the propellant and supporting tankage into LEO from the Earth's surface. Delivering 1 kg to LEO from the lunar surface reduces the propellant mass of the launch vehicle from Earth by 7 kg to 11.3 kg, depending on the final destination. By leveraging resources among multiple nations and corporations, this exploration infrastructure potentially can be both fiscally self-supporting and enable more organizations to sustain a human presence on the moon.

Lunar Architecture↗

NASA NTRS1982

Remote Sensing Applications to the Pennsylvania Abandoned Mine Reclamation Program

Pennsylvania Abandoned Mine Land Inventory demonstrated the effective use of remote sensing techniques within the context of the Surface Mining Control and Reclamation Act of 1977. The inventory combined data from field work, a literature search, and photointerpretation to fulfill both State and Federal requirements. A primary project objective was to accurately identify and map all surface features and disturbances from abandoned surface and underground mining. Black-and-white aerial photographs were used to record pits, contour benches, highwalls, spoil material, graded and recontoured areas, impounded water, and serious erosion and slide prone areas. In addition, vegetation cover estimates and surrounding land uses were noted. The inventory data base provides Pennsylvania with a valuable resource management tool that should be systematically updated. The utilization of remotely sensed data from SPOT or LANDSAT-D satellites may prove valuable in the anticipated updating and monitoring of the Pennsylvania AML inventory over the next several years.

Clemens, E.↗

NASA NTRS1974

Automated strip-mine and reclamation mapping from ERTS

Using computer processing techniques, it is possible to produce geometrically-corrected maps of the coal strip mines in East-Central Ohio by utilizing ERTS-1 CCTs. Several target categories can be drawn by a computer-controlled pen on film that will accurately overlay a base map of any scale selected by the operator. For each overlay, the computer can generate a table that shows the area of each target category in square kilometers, acres, or percent of total area.

Rogers, R. H.↗

NASA NTRS1977

Integration of remote sensing and surface geophysics in the detection of faults

Remote sensing was included in a comprehensive investigation of the use of geophysical techniques to aid in underground mine placement. The primary objective was to detect faults and slumping, features which, due to structural weakness and excess water, cause construction difficulties and safety hazards in mine construction. Preliminary geologic reconnaissance was performed on a potential site for an underground oil shale mine in the Piceance Creek Basin of Colorado. LANDSAT data, black and white aerial photography and 3 cm radar imagery were obtained. LANDSAT data were primarily used in optical imagery and digital tape forms, both of which were analyzed and enhanced by computer techniques. The aerial photography and radar data offered supplemental information. Surface linears in the test area were located and mapped principally from LANDSAT data. A specific, relatively wide, linear pointed directly toward the test site, but did not extend into it. Density slicing, ratioing, and edge enhancement of the LANDSAT data all indicated the existence of this linear. Radar imagery marginally confirmed the linear, while aerial photography did not confirm it.

Jackson, P. L.↗

NASA NTRS1975

Determine utility of ERTS-1 to detect and monitor area strip mining and reclamation

Rogers, R. H.↗

NASA NTRS1976

Monitoring of environmental effects of coal strip mining from satellite imagery

This paper evaluates satellite imagery as a means of monitoring coal strip mines and their environmental effects. The satellite imagery employed is Skylab EREP S-190A and S-190B from SL-2, SL-3 and SL-4 missions; a large variety of camera/film/filter combinations has been reviewed. The investigation includes determining the applicability of satellite imagery for detection of disturbed acreage in areas of coal surface mining as well as the much more detailed monitoring of specific surface-mining operations, including: active mines, inactive mines, highwalls, ramp roads, pits, water impoundments and their associated acidity, graded areas and types of grading, and reclamed areas. Techniques have been developed to enable mining personnel to utilize this imagery in a practical and economic manner, requiring no previous photo-interpretation background and no purchases of expensive viewing or data-analysis equipment. To corroborate the photo-interpretation results, on-site observations were made in the very active mining area near Madisonville, Kentucky.

Brooks, R. L.↗

NASA NTRS1974

Automatic mapping of strip mine operations from spacecraft data

The author has identified the following significant results. Computer techniques were applied to process ERTS tapes acquired over coal mining operations in southeastern Ohio on 21 August 1972 and 3 September 1973. ERTS products obtained included geometrically-correct map overlays, at scales from 1:24,000 to 1:250,000, showing stripped earth, partially reclaimed earth, water, and natural vegetation. Computer-generated tables listing the area covered by each land-water category in square kilometers were also produced. By comparing these mapping products, the study demonstrates the capability of ERTS to monitor changes in the extent of stripping and reclamation. NASA C-130 photography acquired on 7 September 1973 when compared with the ERTS products generated from the 3 September 1973 tape established the categorization accuracy to be better than 90%. It is estimated that the stripping and reclamation maps and data were produced from the ERTS CCTs at a tenth of the cost of conventional techniques.

Rogers, R. H.↗

NASA NTRS1975

The application of remote sensing technology to the solution of problems in the management of resources in Indiana

The use of satellite remote sensing for resources management was investigated in Indiana. The technique was applied to strip mining and reclamation, highway planning, and the detection of dolomite reefs. A data base was created and used to produce land characteristics and suitability maps for land use planning. In addition, a three dimensional model was developed which provides a cross-sectional profile of the thermal plumes emitted by point sources of thermal pollution into rivers and lakes; this model may be used for the design and site selection of electric power plants.

Landgrebe, D. A.↗

NASA NTRS1981

Coal face measurement system for underground use

A measurement system was developed for the Eickhoff longwall shearer to determine the contour of the coal face as it mines coal. Contour data are obtained by an indirect measurement technique based on evaluating the motion of the shearer during mining. Starting from a known location, points along the coal face are established through a knowledge of the machines' positions and yaw movements as it moves past the coal face. The hardware and system operation procedures are described. The tests of system performance and their results are reported.

Source record↗

NASA NTRS2005

Atmospheric Composition Data and Information Services Center (ACDISC)

NASA's GSFC Earth Sciences (GES) Data and Information and Data Services Center (DISC) manages the archive, distribution and data access for atmospheric composition data from AURA'S OMI, MLS, and hopefully one day, HIRDLS instruments, as well as heritage datasets from TOMS, UARS, MODIS, and AIRS. This data is currently archived in the GES Distributed Active Archive Center (DAAC). The GES DISC has begun the development of a community driven data management system that's sole purpose is to manage and provide value added services to NASA's Atmospheric Composition (AC) Data. This system, called the Atmospheric Composition Data and Information Services Center (ACDISC) will provide access all AC datasets from the above mentioned instruments, as well as AC datasets residing at remote archive sites (e.g, LaRC DAAC) The goals of the ACDISC are to: 1) Provide a data center for Atmospheric Scientists, guided by Atmospheric Scientists; 2) Be absolutely responsive to the data and data service needs of the Atmospheric Composition (AC) community; 3) Provide services (i.e., expertise) that will facilitate the effortless access to and usage of AC data; 4) Collaborate with AC scientists to facilitate the use of data from multiple sensors for long term atmospheric research. The ACDISC is an AC specific, user driven, multi-sensor, on-line, easy access archive and distribution system employing data analysis and visualization, data mining, and other user requested techniques that facilitate science data usage. The purpose of this presentation is to provide the evolution path that the GES DISC in order to better serve AC data, and also to receive continued community feedback and further foster collaboration with AC data users and providers.

Kempler, S.↗

NASA NTRS2005

Goddard Atmospheric Composition Data Center: Aura Data and Services in One Place

The Goddard Atmospheric Composition Data and Information Services Center (AC-DISC) is a portal to the Atmospheric Composition specific, user driven, multi-sensor, on-line, easy access archive and distribution system employing data analysis and visualization, data mining, and other user requested techniques for the better science data usage. It provides convenient access to Atmospheric Composition data and information from various remote-sensing missions, from TOMS, UARS, MODIS, and AIRS, to the most recent data from Aura OMI, MLS, HIRDLS (once these datasets are released to the public), as well as Atmospheric Composition datasets residing at other remote archive site.

Leptoukh, G.↗

NASA NTRS2004

Microwave-Spectral Signatures Would Reveal Concealed Objects

A proposed technique for locating concealed objects (especially small antipersonnel land mines) involves the acquisition and processing of spectral signatures over broad microwave frequency bands. This technique was conceived to overcome the weaknesses of older narrow- band electromagnetic techniques like ground-probing radar and low-frequency electromagnetic induction. Ground-probing radar is susceptible to false detections and/or interference caused by rocks, roots, air pockets, soil inhomogeneities, ice, liquid water, and miscellaneous buried objects other than those sought. Moreover, if the radar frequency happens to be one for which the permittivity of a sought object matches the permittivity of the surrounding soil or there is an unfavorable complex-amplitude addition of the radar reflection at the receiver, then the object is not detected. Low-frequency electromagnetic induction works well for detecting metallic objects, but the amounts of metal in plastic mines are often too small to be detectable. The potential advantage of the proposed technique arises from the fact that wideband spectral signatures generally contain more relevant information than do narrow-band signals. Consequently, spectral signatures could be used to make better decisions regarding whether concealed objects are present and whether they are the ones sought. In some cases, spectral signatures could provide information on the depths, sizes, shapes, and compositions of objects. An apparatus to implement the proposed technique (see Figure 1) could be assembled from equipment already in common use. Typically, such an apparatus would include a radio-frequency (RF) transmitter/receiver, a broad-band microwave antenna, and a fast personal computer loaded with appropriate software. In operation, the counter would be turned on, the antenna would be aimed at the ground or other mass suspected to contain a mine or other sought object, and the operating frequency would be swept over the band of interest.

Arndt, G.↗