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While planning for the space shuttle, Bendix Corporation with the help of Johnson Space Center expanded the anthropometric data base for aerospace and nonaerospace use in clothing, workplace, etc. The result was the Anthropometric Source Book which was later utilized by the U.S. Bureau of Mines in designing advanced mining systems. The book was particularly valuable in the design of a remote cab used in mining.
In the emerging industry of deep-sea mining for minerals and deposits (e.g. polymetallic nodules for nickel, cobalt, copper, and manganese), more data is required to understand the effects of sediment plume generation and predict the distribution of disturbed sediment. There are two main sources of plume generation, the first being at the active mining site where the “collector” directly removes the top layer of the sea floor. The other is the “midwater plume” consisting of unwanted sediment that was collected during extraction that is pumped back into the aphotic zone. The vast majority of plume generation is caused by the collector, causing detrimental and long-lasting impacts on seafloor ecosystems due to the lack of wave activity or strong currents at the sea floor. Therefore, it is crucial to invest in the infrastructure to support the study and constant monitoring over a large area of the sea floor where plume generation is present. Due to the limited number of usable channels and power requirements, current subsea wireless communications technologies are not well suited to instrumenting the large areas of the sea floor needed to monitor plume migration. The scope of this effort is to transition experimental demonstrations of high-bandwidth, full-duplex scalable underwater laser communications to the seafloor in an open ocean environment. Specifically tackling challenges associated with the dynamic nature of the subsea world, including but not limited to, deployment logistics, sustainability, and range. The goal is to enable the internet of underwater things for deep sea industries by broadening the capabilities of subsea communications. By using high-precision laser transmitters, many of the challenges current subsea optical systems face can be circumvented, such as power consumption, interference, and bandwidth limitations. This approach lends itself to wireless interlinking multi-node networks, in series or parallel, facilitating the implementation of a wide array of sensor types. This interlinking allows all the data gathered from the network to be processed through a single hardline uplink to the surface, lowering the complexity required for near real-time data processing. Additionally, the laser control systems produce metadata that can be used to help characterize the water column between the nodes. Combining data from various sensors such as turbidity, temperature, current velocity with metadata such as beam attenuation and deflection can produce a high-resolution model of sea floor conditions around an active mining zone. The resulting near real-time model can be used to optimize location and flow rate of the mining operation to minimize and quantify the environmental impact.
Diagnostic ERTS imagery has been used to pinpoint surface conditions associated with known mining districts. These include enhancements which depict hitherto unrecognized surface alteration and allow analysis of ore-controlling fractures distribution in a regional context. ERTS has likewise provided observational data containing previously unrecognized surface anomalies in large oil-producing basins which correlate closely with known oil fields. These observational data offer promise of providing new and powerful techniques for oil exploration, especially if further work using more sophisticated enhancement-processing proves capable of emphasizing the anomalies. ERTS is showing a better-than-anticipated potential for producing accurate small-scale (large-area) geologic maps, often containing details that were previously not recorded on similar regional maps. The maps produced from ERTS imagery can be prepared more effectively than previously possible, mainly because of the synoptic, multispectral, and repetitive character of ERTS data. ERTS has also provided extensive information on possible geologic hazards. Many new fractures have been identified in several regions of the Pacific Coast seismic belt that have histories of recent earthquakes. This has obvious implications for engineering projects such as dams, aqueducts, and transportation routes. In the mid-continent area, ERTS data have been used to predict zones of rooffall danger in a working coal mine from newly discovered lineations (probably fractures) used as indicators of hazards.
Increased biomedical risks and challenges associated with deep space missions require knowledge discovery, health countermeasures, and biomedical support capabilities. Maximally open-access and reusable data is needed by developers, scientists, and engineers to develop these systems. The NASA Open Science Data Repository (OSDR) is a maximally open access and FAIR database (ie., findable, accessible, interoperable, and reusable), and meets various scientific, technical, and operational needs. It offers users and submitters the ability to upload, download, search, share, analyze, cite, and visualize data across ‘omics, physiological, phenotypic, payload, hardware, behavioral, bioimaging, video, and environmental monitoring telemetry datasets. OSDR is an expanded database, based upon the successes of NASA GeneLab. OSDR has >460 studies with datasets covering model organisms to non-NASA human astronauts. There are ~12 datasets from the Inspiration 4 (I4) mission, spanning metagenomics, comprehensive metabolic panels, clonal hematopoiesis, spatial transcriptomics, proteomics, and cytokine panels. In the interest of data privacy, two I4 datasets with raw files relating to the epitranscriptome, and a new request feature is live in OSDR (with a backend review process established) developed from industry norms. OSDR is collecting and curating biomedical human data from a new sub-orbital research flight and is open to more space life science/biomedical submissions from the international and commercial sectors. OSDR also recently began a collaboration with the European Space Agency (ESA) to collect and curate >200 terabytes of human and model organism data. The OSDR submission portal is designed to ingest and curate ~25 ‘omics and ~50 physiological-phenotypic-imaging assay data types. Tools available for OSDR users include: 1) an Environmental Data Application to compare radiation, CO2, relative humidity, temperature, and other telemetry across missions and subjects, 2) the RadLab database, a collaboration between NASA, ESA, the German and Italian Space Agencies, and the Bulgarian Academy of Sciences, and 3) a Multi-study visualization tool which enables users to look across and combine ‘omics datasets. There are ~600 volunteer OSDR Analysis Working Group (AWG) members providing feedback on scientific data/metadata standards and collaborating to mine-reuse OSDR in research. OSDR/GeneLab has enabled ~60 publications reusing data as of October 2023.
The cost of mining coal using a room pillar mining method with continuous miner and a longwall mining system was calculated. Costs were calculated for the years 1975 and 2000 time periods and are to be used as economic standards against which advanced mining concepts and systems will be compared. Some assumptions were changed and some internal model stored data was altered from the original calculations procedure chosen, to obtain a result that more closely represented what was considered to be a standard mine. Coal seam thicknesses were varied from one and one-half feet to eight feet to obtain the cost of mining coal over a wide range. Geologic conditions were selected that had a minimum impact on the mining productivity.
Data-reduction methods using general-purpose analog computer equipment and compatible testing techniques for determining the frequency response of linear physical systems are examined. The techniques considered may be classed as steady state or transient depending on the method of excitation. The relative merits of periodic, slow sweep, and transient (rapid sweep) forcing functions are discussed and applications are given that relate to dynamic-response tests of aeroelastic systems. Two frequency-sweep-input methods are considered in detail. one case the sweep rate is sufficiently slow that the response is approximately the same as that for steady-state conditions. With this input the frequency response can be evaluated and displayed in real time while the test is in progress. Errors due to treating sweep data as steady state can be eliminated, when desired, by reanalyzing tape-recorded time histories of the input and output as transient rather than as periodic data. In the second method the frequency-response function is deter- mined from the system's transient response to a very rapid sweep input. The purpose of frequency sweep in this case is to provide sufficient harmonic content in the input to overcome noise while keeping the test time as short as possible. tests and limited flight-test data presented herein, it appears that a transient-type rapid-sweep forcing function offers a considerable saving in test time while preserving the accuracy possible with steady-state sinusoidal inputs.
In this article, we explore simplifying mechanisms in materials economics for conceptionally organizing the flows of chemical elements into society. We use the concept of rank, which plays a crucial role in information theory where power laws are involved, and is a useful measure for seeking extremal principles. Borrowing from an analogy to Zipf’s law leads to a power-law relationship between abundance and rank that—pressing the Zipf’s law analogy further—may suggest that the price paid for elemental materials optimizes efficient utilization. Factors such as weight, volume, and moles in the earth's crust or in global mining production of elements are used in our analysis. For this research, 42 elements with price and production data for the year 2010 (a relatively typical year) were considered. We observe that the role of the volume from global mining production dominates in materials economics and indicate that elements such as Te and He should be sold at prices at leas ~ 100–1000 times more than their present price for efficient utilization.
This paper represents an integration of several Landsat TM image processing techniques with other data to discriminate the lithologies and associated areas of hydrothermal alteration in the vicinity of the Paradise Peak gold mine in west central Nevada. A microprocessor-based image processing system and an IDIMS system were used to analyze data from a 512 X 512 window of a Landsat-5 TM scene collected on June 30, 1984. Image processing techniques included simple band composites, band ratio composites, principal components composites, and baseline-based composites. These techniques were chosen based on their ability to discriminate the spectral characteristics of the products of hydrothermal alteration as well as of the associated regional lithologies. The simple band composite, ratio composite, two principal components composites, and the baseline-based composites separately can define the principal areas of alteration. Combined, they provide a very powerful exploration tool.
Previous JPL ground systems have been designed with the Ground Data System (GDS) engineer in mind. The focus on these systems has been on packaging and delivery of low level information (frames, packets, telemetry values) to the end user. It was not that long ago when project teams would be huddled over a workstation, examining crude displays of telemetry bits organized in various ways, trying to determine the status of a spacecraft. Understanding the data often required additional levels of GDS expertise, or worse, transformation of the raw data into alternative formats followed by ingestion into other tools so that the data became meaningful. The primary focus was often to answer these types of questions: "Why did this particular frame fail Reed-Solomon decode? Why did this packet get marked as invalid? Why am I missing a block of telemetry from my query?" -- which are completely valid questions to ask from a GDS Engineer's point of view, and large families of tools have been designed to help answer these questions. But these are not the questions that most users care about - which are more like: "Why is the battery state of charge trending down? Show me a summary image report for the last traverse to the target. Show me a data accountability summary for the last DSN pass." Answers to these questions, which are what users are looking for, requires a higher level of abstraction and supporting tools than mining through ones and zeros. JPL has created a next generation capability called the Mission Data Processing and Control System (MPCS) which is designed to support this higher level of abstraction by providing customizable views of the ground system combining collections of lower level information into more meaningful ways. Instead of examining frames, packets, and individual telemetry data points -- MPCS is capable of providing comprehensive summary reports, product status, overall flight/ground event status, as well as payload health summaries. Based on these higher level views, end users can make tactical or strategic decisions, or drop into detailed analysis as needed. System designers need to continue building systems that support low level GDS troubleshooting - but the basic design of a GDS should be geared towards what end users actually need to see. This paper will describe the capabilities of MPCS that directly support these higher levels of abstraction, and which are being used today in missions such as the Mars Science Laboratory and other NASA missions.
The number of scientific publications reporting cutting-edge third-generation photovoltaic devices is increasing rapidly, owing to the pressing need to develop renewable-energy technologies that address the climate-change crisis. Consequently, the field could benefit from a central repository where photovoltaic-performance metrics, such as the power-conversion efficiency (η) are recorded. We present two automatically generated databases that contain photovoltaic properties and device material data for dye-sensitized solar cells (DSCs) and perovskite solar cells (PSCs), totalling 660,881 data entries representing 57,678 photovoltaic devices. The databases were generated by applying the text-mining toolkit ChemDataExtractor on a corpus of 25,720 articles. A multi-faceted evaluation, incorporating manual and automatic methods, was applied to ensure that the data contained therein were of the highest quality, with precision metrics ranging from 73.1% to 95.8%. The DSC database contains 475,045 entries representing 41,680 devices, and the PSC database contains 185,836 entries representing 15,818 devices. The databases are available in MongoDB and JSON formats, which can be queried in Python, R, Java and MATLAB for data-driven photovoltaic materials discovery.
ERTS imagery is of unique value for mapping of certain fractures that are not identifiable on aircraft imagery. Because color infrared and ERTS imagery complement each other both sources of data were used to map fractures in western Indiana and eastern Illinois. In the Kings Station Mine, Gibson County, Indiana, most roof falls reported had occurred in areas where mapped fractures were closely spaced and intersecting. Using this information as a basis for extrapolation, roof fall hazard maps were prepared for other mine sites. Various coal resources programs related to energy and environment also were conducted.
Anthropogenic sulfate loading into otherwise low-sulfate freshwater systems can cause significant ecological consequences as a biogeochemical stressor. To address this challenge, in situ bioremediation technologies have been developed to leverage naturally occurring microorganisms that transform sulfate into sulfide rather than implementing resource-intensive physio-chemical processes. However, bioremediation technologies often require the supply of electron donors to facilitate biological sulfate reduction. Bioelectrochemical systems (BES) can be an alternative approach for supplying molecular hydrogen as an electron donor for sulfate-reducing bacteria through water electrolysis. Although the fundamental mechanisms behind BESs have been studied, limited research has evaluated the design and operational parameters of treatment systems when developing BESs on a scale relevant to environmental systems. Further, this study aimed to develop an application-based mathematical model to evaluate the performance of BESs across a range of reactor configurations and operational modes. The model was based on sulfate transformation by hydrogenotrophic sulfate-reducing bacteria coupled with the recovery of solid iron sulfide species formed by the oxidative dissolution of dissolved ferrous iron from a stainless steel anode. Sulfate removal closely corresponded to the rate of electrolytic hydrogen production and hydraulic residence time but was less sensitive to specific microbial rate constants. The mathematical model results were compared to experimental data from a pilot-scale BES tested with nonacidic mine drainage as a case study. The close agreement between the mathematical model and the pilot-scale BES experiment highlights the efficacy of using a mathematical model as a tool to develop a conceptual design of a scaled-up treatment system.
The cuprates exhibit a prominent charge-density-wave (CDW) instability with a wave vector along [100], i.e., the Cu-O bond direction. Whereas CDW order is most prominent at moderate doping and low temperature, there exists increasing evidence for dynamic charge correlations throughout a large portion of the temperature-doping phase diagram. In particular, the signatures of incipient charge order have been observed as phonon softening and/or broadening near the CDW wave vector approximately halfway through the Brillouin zone. Most of this work is focused on moderately doped cuprates, for which the CDW order is robust, or on optimally doped samples, for which the superconducting transition temperature (T c ) attains its maximum. Here we present a time-of-flight neutron scattering study of phonons in simple-tetragonal HgBa 2 CuO 4+δ (T c = 55 K) at a low doping level where prior work showed the CDW order to be weak. We employ and showcase a new software-based technique that mines a large number of measured Brillouin zones for useful data in order to improve accuracy and counting statistics. Density-functional theory has not provided an accurate description of phonons in HgBa2CuO4+δ, yet we find the right set of parameters to qualitatively reproduce the data. The notable exception is a dispersion minimum in the longitudinal Cu-O bond-stretching branch along [100]. Here, this discrepancy suggests that, while CDW order is weak, there exist significant dynamic charge correlations in the optic phonon range at low doping, near the edge of the superconducting dome.
In his remarkable memoir Runway to Orbit, Dr. Kenneth W. Iliff - the recently retired Chief Scientist of the NASA Dryden Flight Research Center- tells a highly personal, yet a highly persuasive account of the last forty years of American aeronautical research. His interpretation of events commands respect, because over these years he has played pivotal roles in many of the most important American aeronautics and spaceflight endeavors. Moreover, his narrative covers much of the second half of the first 100 years of flight, a centennial anniversary being celebrated this year. aerospace knowledge. He arrived at the then NASA Flight Research Center in 1962 as a young aeronautical engineer and quickly became involved in two of the seminal projects of modern flight, the X-15 and the lifting bodies. In the process, he pioneered (with Lawrence Taylor) the application of digital computing to the reduction of flight data, arriving at a method known as parameter estimation, now applied the world over. Parameter estimation not only enabled researchers to acquire stability and control derivatives from limited flight data, but in time allowed them to obtain a wide range of aerodynamic effects. Although subsequently involved in dozens of important projects, Dr. Iliff devoted much of his time and energy to hypersonic flight, embodied in the Shuttle orbiter (or as he refers to it, the world s fastest airplane). To him, each Shuttle flight, instrumented to obtain a variety of data, represents a research treasure trove, one that he has mined for years. This book, then, represents the story of Dr. Ken Iliff s passion for flight, his work, and his long and astoundingly productive career. It can be read with profit not just by scientists and engineers, but equally by policy makers, historians, and journalists wishing to better comprehend advancements in flight during the second half of the twentieth century. Dr. Iliff's story is one of immense contributions to the nation s repository of
The author has identified the following significant results. The Hayden Pass (Orient mine area) includes 60 sq miles of the northern Sangre de Cristo Mountains and San Luis Valley in south-central Colorado. Based on interpretation of the remote sensor data, a geologic map was prepared and compared with a second geologic map, prepared from interpretation of both remote sensor data and field data. Comparison of the two maps gives an indication of the usefulness and reliability of the remote sensor data. The relative utility of color and color infrared photography was tested. The photography was used successfully to locate 75% of all faults in a portion of the geologically complex Bonanza volcanic center and to map and correctly identify 93% of all quaternary deposits and 62% of all areas of tertiary volcanic outcrop. Using a filter wheel photometer, more than 8,600 measurements of band reflectance of several sedimentary rocks were performed. The following conclusions were drawn: (1) the typical spectral reflectance curve shows a gradual increase with increasing wavelength; (2) the average band reflectance is about 0.20; and (3) within a formation, the minimum natural variation is about 0.04, or about 20% of the mean band reflectance.
The ability of Landsat multispectral digital data to differentiate among 62 combinations of rock and alteration types at the Goldfield mining district of Western Nevada was investigated by using statistical techniques of cluster and discriminant analysis. Multivariate discriminant analysis was not effective in classifying each of the 62 groups, with classification results essentially the same whether data of four channels alone or combined with six ratios of channels were used. Bivariate plots of group means revealed a cluster of three groups including mill tailings, basalt and all other rock and alteration types. Automatic hierarchical clustering based on the fourth dimensional Mahalanobis distance between group means of 30 groups having five or more samples was performed. The results of the cluster analysis revealed hierarchies of mill tailings vs. natural materials, basalt vs. non-basalt, highly reflectant rocks vs. other rocks and exclusively unaltered rocks vs. predominantly altered rocks. The hierarchies were used to determine the order in which sets of multiple discriminant analyses were to be performed and the resulting discriminant functions were used to produce a map of geology and alteration which has an overall accuracy of 70 percent for discriminating exclusively altered rocks from predominantly altered rocks.
The ability of Landsat multispectral digital data to differentiate among 62 combinations of rock and alteration types at the Goldfield mining district of Western Nevada was investigated by using statistical techniques of cluster and discriminant analysis. Multivariate discriminant analysis was not effective in classifying each of the 62 groups, with classification results essentially the same whether data of four channels alone or combined with six ratios of channels were used. Bivariate plots of group means revealed a cluster of three groups including mill tailings, basalt and all other rock and alteration types. Automatic hierarchical clustering based on the fourth dimensional Mahalanobis distance between group means of 30 groups having five or more samples was performed using Johnson's HICLUS program. The results of the cluster analysis revealed hierarchies of mill tailings vs. natural materials, basalt vs. non-basalt, highly reflectant rocks vs. other rocks and exclusively unaltered rocks vs. predominantly altered rocks. The hierarchies were used to determine the order in which sets of multiple discriminant analyses were to be performed and the resulting discriminant functions were used to produce a map of geology and alteration which has an overall accuracy of 70 percent for discriminating exclusively altered rocks from predominantly altered rocks.
Citizen science (or crowdsourcing) has drawn much high-level recent and ongoing interest and support. It is poised to be applied, beyond the by-now fairly familiar use of, e.g., Twitter for natural hazards monitoring, to science research, such as augmenting the validation of NASA earth science mission data. This interest and support is seen in the 2014 National Plan for Civil Earth Observations, the 2015 White House forum on citizen science and crowdsourcing, the ongoing Senate Bill 2013 (Crowdsourcing and Citizen Science Act of 2015), the recent (August 2016) Open Geospatial Consortium (OGC) call for public participation in its newly-established Citizen Science Domain Working Group, and NASA's initiation of a new Citizen Science for Earth Systems Program (along with its first citizen science-focused solicitation for proposals). Over the past several years, we have been exploring the feasibility of extracting from the Twitter data stream useful information for application to NASA precipitation research, with both "passive" and "active" participation by the twitterers. The Twitter database, which recently passed its tenth anniversary, is potentially a rich source of real-time and historical global information for science applications. The time-varying set of "precipitation" tweets can be thought of as an organic network of rain gauges, potentially providing a widespread view of precipitation occurrence. The validation of satellite precipitation estimates is challenging, because many regions lack data or access to data, especially outside of the U.S. and in remote and developing areas. Mining the Twitter stream could augment these validation programs and, potentially, help tune existing algorithms. Our ongoing work, though exploratory, has resulted in key components for processing and managing tweets, including the capabilities to filter the Twitter stream in real time, to extract location information, to filter for exact phrases, and to plot tweet distributions. The key step is to process the "precipitation" tweets to be compatible with satellite-retrieved precipitation data. These key components for processing and managing "precipitation" tweets (and additional ones to be developed) are not limited to precipitation, nor are they limited to the Twitter social medium. Indeed, to maximize the value of our work for NASA earth science programs, these components should be generalized and be part of an overall framework for processing citizen science data for science research. In this paper, we outline such a framework.