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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Lunabotics Mining Competition: Inspiration through Accomplishment

Space Mining for resources such as water ice, and regolith, which contain many elements in the form of metals, minerals, volatiles and other compounds, is a necessary step in Space Resource Utilization. One of the primary goals is to extract propellants from the regolith such as oxygen and hydrogen which could then be used for in-space transportation. In addition, the space mining system can be used for various construction tasks that can benefit human and robotic exploration as well as scientific investigations based on the exposed topography. The National Aeronautics & Space Administration (NASA) Lunabotics Mining Competition is a university-level competition designed to engage and retain students in science, technology, engineering and mathematics (STEM). NASA will directly benefit from the competition by encouraging the development of innovative lunar excavation concepts from universities which may result in clever ideas and solutions which could be applied to an actual lunar excavation device or payload. The challenge is for students to design and build a remote controlled or autonomous excavator, called a lunabot, that can collect and deposit a minimum of 10 kilograms of lunar simulant within 15 minutes. The complexities of the challenge include the abrasive characteristics of the lunar simulant, the weight and size limitations of the lunabot, and the ability to control the lunabot from a remote control center or operate autonomously. This paper will present an update of the results and lessons learned during the first and second annual Lunabotics Mining Competitions held in May 2010 and May 2011. It will also preview the 2012 competition with a review of the revised rules. In 2010,22 United States (US) universities competed, and in May 2011 the competition was opened to international participation. In 2011, 36 teams actually competed from 26 USA states and 4 foreign countries (India, Bangladesh, Colombia and Canada). This combined total directly inspired an estimated 653 university students. In 2012 more students and the public will be engaged via internet broadcasting and social networking media. The various designs will be cataloged and categorized to provide information to future Lunabotics mining robot designers and competitors. It is also expected to be of value for actual future space missions, as knowledge is gained from testing many innovative prototypes in simulated lunar regolith.

Mueller, Robert P.↗
NASA NTRS2013

Introduction to Space Resource Mining

There are vast amounts of resources in the solar system that will be useful to humans in space and possibly on Earth. None of these resources can be exploited without the first necessary step of extra-terrestrial mining. The necessary technologies for tele-robotic and autonomous mining have not matured sufficiently yet. The current state of technology was assessed for terrestrial and extraterrestrial mining and a taxonomy of robotic space mining mechanisms was presented which was based on current existing prototypes. Terrestrial and extra-terrestrial mining methods and technologies are on the cusp of massive changes towards automation and autonomy for economic and safety reasons. It is highly likely that these industries will benefit from mutual cooperation and technology transfer.

Mueller, Robert P.↗
NASA NTRS2020

Machine Learning For Planetary Mining Applications

Robotic mining could prove to be an efficient method of mining resources for extended missions on the Moon or Mars. One component of robotic mining is scouting an area for resources to be mined by other robotic systems. Writing controllers for scouting can be difficult due to the need for fault tolerance, inter-agent cooperation, and agent problem solving. Reinforcement learning could solve these problems by enabling the scouts to learn to improve their performance over time. This work is divided into two sections, with each section addressing the use of machine learning in this domain. The first contribution of this work focuses on the application of reinforcement learning to mining mission analysis. Various mission parameters were modified and control policies were learned. Then agent performance was used to assess the effect of the mission parameters on the performance of the mission. The second contribution of this work explores the potential use of reinforcement learning to learn a controller for the scouts. Through learning, these scouts would improve their ability to map their surroundings over time.

Cook, Joshua↗
NASA NTRSDate not supplied

NASA Lunabotics Robotic Mining Competition 10th Anniversary (2010-2019): Taxonomy and Technology Review

Space Mining for resources such as water ice, and regolith, which contain many elements in the form of metals, minerals, volatiles and other compounds, is a necessary step for In-Situ Space Resource Utilization (ISRU). One of the primary goals is to extract propellants from the regolith and water ice, such as oxygen and hydrogen which could then be used for in-space transportation. In addition, the space mining system can be used for various construction tasks that can benefit human and robotic exploration as well as scientific investigations based on excavated exposed topography, such as the side walls of trenches. The National Aeronautics & Space Administration (NASA) "Lunabotics" Robotic Mining Competition (RMC) is a university-level competition designed to engage and retain students in science, technology, engineering and mathematics (STEM). NASA has directly benefited from the competition by encouraging the development of innovative lunar excavation concepts from universities which has resulted in clever ideas and solutions which could be applied to an actual lunar excavation device or payload. The challenge is for students to design and build a remote controlled or autonomous excavator, called a "lunabot", which can collect and deposit a minimum of 10 kilograms of lunar simulant within 15 minutes. In recent years the goal has been changed to excavate a minimum of 1 kg of simulated icy regolith which is found under an overburden of regolith simulant. The complexities of the challenge include the abrasive characteristics of the lunar regolith simulant, the weight and size limitations of the lunabot, and the ability to control the lunabot from a remote-control center or operate it autonomously. This paper will present the results of the ten Lunabotics Robotic Mining Competitions held between May 2010 and May 2019. Each year over 50 university teams have attended, resulting in over 500 lunabot designs and subsequent prototypes. Over 6,000 university students have been part of the on-site competition at KSC. Even more students and the public were engaged via internet broadcasting and social networking media. The various designs have been cataloged and categorized here to provide information to future Lunabotics RMC mining robot designers and competitors. Categories will focus on both the mechanical design as well as the autonomy architecture/design. It is also expected to be of value for actual future space missions, as knowledge is gained from testing many innovative prototypes in simulated lunar regolith. A taxonomy of robotic excavator designs has been presented. In addition, the paper will discuss changes in learning paradigms occurring in the current generation of students, and how this competition leverages those changes to challenge students to develop skills in graduate level concepts and apply them. Examples of how this translates to hiring opportunities for commercial sponsors has also been discussed.

Robert P Mueller↗
NASA NTRS2019

Atmospheric Mining in the Outer Solar System: Outer Planet Resource Processing, Moon Base Propulsion,and Vehicle Design Issues

Atmospheric mining in the outer solar system has been investigated as a means of fuel production for high energy propulsion and power. Fusion fuels such as Helium 3 (3He) and deuterium can be wrested from the atmospheres of Uranus and Neptune and either returned to Earth or used in-situ for energy production. Helium 3 and deuterium were the primary gases of interest with hydrogen being the primary propellant for nuclear thermal solid core and gas core rocket-based atmospheric flight. A series of analyses were undertaken to investigate resource capturing aspects of atmospheric mining in the outer solar system. This included the gas capturing rate, storage options, and different methods of direct use of the captured gases. While capturing 3He, large amounts of hydrogen and 4He are produced. Analyses of orbital transfer vehicles (OTVs), landers, and in-situ resource utilization (ISRU) mining factories are included. Preliminary observations are presented on near-optimal selections of moon base orbital locations, OTV power levels, and OTV and lander rendezvous points. Based on earlier propulsion investigations, the analyses of round trip OTV flights from Uranus and Neptune to their major moons with a 10- Megawatt electric (MWe) OTV power level and a 200 metric ton (MT) lander payload were selected. The OTV power level was based on delivering a relatively short OTV trip time and minimization of the number of lander flights. Moon base sites at Uranus and Neptune and the OTV requirements to support them will also be addressed. These analyses will include all of the major moons of Uranus and Neptune. In addition, the total masses and mass delivery schedules needed for atmospheric mining are presented.

nuclear propulsion↗
DOE OSTI2026

A Physics-Informed Reinforcement Learning Framework for Economic-Thermal Co-Optimization of Crypto Mining Data Centers: Preprint

The rapid expansion of cryptocurrency mining has created a new class of high-density data centers characterized by extreme thermal flux and high sensitivity to volatile economic markets. Traditional thermal management strategies, typically reliant on rule-based control, maintain static setpoints that fail to account for fluctuating electricity prices and cryptocurrency values - factors critical to mining profitability. To address this, we present a physics-informed reinforcement learning (PIRL) framework for economic-thermal co-optimization in crypto mining data centers. This framework consists of a proximal policy optimization (PPO) agent, a virtual testbed powered by high-fidelity physics-based models, and an interactive frontend dashboard. The PPO agent is trained using the virtual testbed and strict hardware safety limits. This physics-informed approach allows the agent to learn a stochastic policy that dynamically balances mining revenue against operational costs by co-optimizing HVAC cooling setpoints and IT computational hashrate. The simulation results demonstrate that the integrated framework achieved an 8.62% increase in net operational profit compared to traditional baseline strategies while strictly adhering to safety-critical temperature constraints (coolant supply temperature < 32 degrees C). This work provides a scalable template for the deployment of reinforcement learning in mission critical facilities where economic volatility and physical safety must be managed simultaneously.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2013

Data Mining for Understanding and Impriving Decision-Making Affecting Ground Delay Programs

The continuous growth in the demand for air transportation results in an imbalance between airspace capacity and traffic demand. The airspace capacity of a region depends on the ability of the system to maintain safe separation between aircraft in the region. In addition to growing demand, the airspace capacity is severely limited by convective weather. During such conditions, traffic managers at the FAA's Air Traffic Control System Command Center (ATCSCC) and dispatchers at various Airlines' Operations Center (AOC) collaborate to mitigate the demand-capacity imbalance caused by weather. The end result is the implementation of a set of Traffic Flow Management (TFM) initiatives such as ground delay programs, reroute advisories, flow metering, and ground stops. Data Mining is the automated process of analyzing large sets of data and then extracting patterns in the data. Data mining tools are capable of predicting behaviors and future trends, allowing an organization to benefit from past experience in making knowledge-driven decisions. The work reported in this paper is focused on ground delay programs. Data mining algorithms have the potential to develop associations between weather patterns and the corresponding ground delay program responses. If successful, they can be used to improve and standardize TFM decision resulting in better predictability of traffic flows on days with reliable weather forecasts. The approach here seeks to develop a set of data mining and machine learning models and apply them to historical archives of weather observations and forecasts and TFM initiatives to determine the extent to which the theory can predict and explain the observed traffic flow behaviors.

data mining↗
NASA NTRS2017

Mars Molniya Orbit Atmospheric Resource Mining

This NASA Innovative Advanced Concepts (NIAC) Phase I study examined the revolutionary concept of performing resource collection and utilization during Mars orbital operations in order to enable the landing of large payloads. An exploration architecture was developed, out of which several mission alternatives were developed. Concepts of operations were then developed for each mission alternative, followed by concepts for spacecraft systems, which were traded to assess their feasibility. A novel architecture using Mars Molniya Orbit Atmospheric Resource Mining is feasible to enable an Earth-independent and pioneering, permanent human presence on Mars by providing a reusable, single-stage-to-orbit transportation system. This will allow cargo and crew to be routinely delivered to and from Mars without transporting propellants from Earth.In Phase I, our study explored how electrical energy could be harnessed from the kinetic energy of the incoming spacecraft and then be used to produce the oxygen necessary for landing. This concept of operations is revolutionary in that its focus is on using in situ resources in complementary and varied forms: the upper atmosphere of Mars is used for aerocapture, which is followed by aerobraking, the kinetic energy of the spacecraft is transformed into usable electrical energy during aerobraking, and the atmospheric composition is the source of oxidizer for a landing under supersonic retropropulsion. This NASA Innovative Advanced Concepts (NIAC) Phase I study explores a novel mission architecture to establish routine, Earth-independent transfer of large mass payloads between Earth and the Mars surface and back to Mars orbit. The first stage of routine mission operations involves an atmospheric resource mining aerobraking campaign following aerocapture into a highly elliptical Mars orbit. During each pass through the atmosphere, the vehicle ingests the atmospheric oxidizer and stores it onboard, using solid oxide electrolysis to convert the primarily CO2 atmosphere into usable O2 for propellant. Power is made available through the use of magnetohydrodynamic energy generation, which converts the motion of the plasma in the shock later into usable electrical energy. Upon termination of the aerobraking sequence, the descent vehicle detaches from the orbit stack, deorbits, and executes the entry, descent, and landing sequence. Hypersonic deceleration is achieved via a deployable heat shield to lower the vehicle ballistic coefficient, and supersonic and subsonic deceleration are achieved via retropropulsion. Mars surface operations involve resource mining of the Martian regolith to produce CH4 and O2 propellant to be used for the subsequent MDAV ascent back to high Mars orbit (HMO) providing an apoapsis raise maneuver to initialize the aerobraking sequence, in addition to providing fuel from the Mars surface for EDL propulsive descent. The Resource Collector Vehicle (RCV), which is used for the orbital mining operations, is raised back to HMO via onboard deployable augmented solar electric propulsion. Concepts of operations were developed for each mission alternative, to evaluate between them and assess feasibility.

Mining↗
NASA NTRSDate not supplied

Lunabotics Robotic Mining Competition for Universities

Space Mining for resources such as water ice, and regolith, which contain many elements in the form of metals, minerals, volatiles and other compounds, is a necessary step for In-Situ Space Resource Utilization (ISRU). One of the primary goals is to extract propellants from the regolith and water ice, such as oxygen and hydrogen which could then be used for in-space transportation. In addition, the space mining system can be used for various construction tasks that can benefit human and robotic exploration as well as scientific investigations based on excavated exposed topography, such as the side walls of trenches. The National Aeronautics & Space Administration (NASA) “Lunabotics” Robotic Mining Competition (RMC) is a university-level competition designed to engage and retain students in science, technology, engineering and mathematics (STEM). NASA has directly benefited from the competition by encouraging the development of innovative lunar excavation concepts from universities which has resulted in clever ideas and solutions which could be applied to an actual lunar excavation device or payload. The challenge is for students to design and build a remote controlled or autonomous 80 kg mass lightweight excavator, called a “lunabot”, which can collect and deposit a minimum of 10 kilograms of lunar simulant within 15 minutes. In recent years the goal has been changed to excavate a minimum of 1 kg of simulated icy regolith which is found under an overburden of regolith simulant. The complexities of the challenge include the abrasive characteristics of the lunar regolith simulant, the weight and size limitations of the lunabot, and the ability to control the lunabot from a remote mission control center or operate it autonomously. This presentation will summarize the results of the Lunabotics Robotic Mining Competitions held in May 2022. Each year, since 2010, over 50 university teams have attended, resulting in over 500 lunabot designs and subsequent prototypes. Over 6,000 university students have been part of the on-site competition at KSC, and many are employed in the space sector today with thriving careers. Even more students and the public were engaged via internet broadcasting and social networking media. Examples of how this translates to hiring opportunities for commercial sponsors will also be discussed. Overall, this competition has proven to be popular with multi-disciplinary university senior design classes and a valuable tool for NASA and academia in educating and inspiring the next generation of space engineers.

Lunabotics↗
DOE OSTI2025

Factors influencing water quality in surface water and alluvial groundwaters downgradient of a reclaimed surface coal mine in the Powder River Basin of southeastern Montana, USA

Abstract Coal mining and reclamation can have a profound influence on hydrogeologic systems, with clear consequences for groundwater quality, yet their long-term influence on downgradient water quality over time following reclamation is less well documented. Geochemical trends were evaluated in water quality downgradient of a fully reclaimed landscape at the former Big Sky Mine in the Rosebud Creek watershed (southeastern Montana, USA), over a 3-year period (2020–2022), including bond release in 2022. Within 6 km downgradient from the reclaimed area, sulfate concentrations decreased from approximately 3500 to 1800 mg l −1 within the Miller Coulee alluvial aquifer. Major ions, δ 34 S SO4 values, and residence time tracers suggest that the observed decreases in sulfate concentration result from a combination of dilution by mixed-age inflows and incomplete transit of the high salinity plume from the mine boundary. Both bedrock and alluvial aquifers of the Rosebud Creek corridor contained contributions of millennia-old regional groundwater, which may serve to mitigate mine-derived high salinity waters. Rosebud Creek, which traverses the outflow zone of Miller Coulee in the study area, exhibited high sulfate concentrations during low flows and consistent downgradient increases in sulfate concentration. The possibility of plume dynamics in Miller Coulee suggests that the greatest water quality impacts may not yet have reached Rosebud Creek.

Keeshin, Skye I. (ORCID:0009000986449872)↗
DOE OSTI2025

MINE: a new way to design genetics experiments for discovery

Abstract The Maximally Informative Next Experiment or MINE is a new experimental design approach for experiments, such as those in omics, in which the number of effects or parameters p greatly exceeds the number of samples n (p > n). Classical experimental design presumes n > p for inference about parameters and its application to p > n can lead to over-fitting. To overcome p > n, MINE is an ensemble method, which makes predictions about future experiments from an existing ensemble of models consistent with available data in order to select the most informative next experiment. Its advantages are in exploration of the data for new relationships with n < p and being able to integrate smaller and more tractable experiments to replace adaptively one large classic experiment as discoveries are made. Thus, using MINE is model-guided and adaptive over time in a large omics study. Here, MINE is illustrated in two distinct multiyear experiments, one involving genetic networks in Neurospora crassa and a second one involving a genome-wide association study in Sorghum bicolor as a comparison to classic experimental design in an agricultural setting.

Biochemistry & Molecular Biology↗
DOE OSTI2025

Addressing Critical Challenges of Coal Mines for Underground Pumped Storage Hydropower Using Numerical Calculations

Using existing coal mines to build underground pumped storage hydropower (UPSH) power plants could help reduce the costs associated with starting a new PSH operation. This innovative approach can leverage the existing infrastructure of coal mine facilities available in many regions of the United States. However, technical challenges associated with water quality, mineral chemistry and integrity of subsurface topologies have thus far prevented any of these facilities from going online. Rye Development is investigating the feasibility of UPSH at existing coal mine facilities. In this project, Rye Development received the technical assistance from Oak Ridge National Laboratory to investigate the impacts of minerals, metal particles, and chemical substances in water flow on hydraulic equipment and assess the overall structural integrity of hydraulic equipment in former coal mines.

13 HYDRO ENERGY↗
NASA NTRS1973

Growth and decline of vegetation on mine dumps

The author has identified the following significant results. The main objective is to determine the extent to which can be used to differentiate between mine dumps having varying degrees of vegetative cover. At this stage it is clear that the various mine dumps can be located and identified. Differences in vegetative cover can be seen and measured. Patterns of vegetative growth, some characteristic to particular dumps, can also be seen. It is therefore tentatively concluded that mine dumps can be differentiated with respect to their vegetative cover on the imagery received to date, and this is reported as a significant result. Subsequent imagery showing seasonal variations should facilitate this program. In addition to work on the mine dumps, a photogeological project has been initiated on geotectonics of South Africa. Studies of ERTS-1 images has indicated that major structures (faults, folds, and linear features) associated with the three geotectonic environments can be identified. In addition, major as well as relatively minor stratigraphic subdivisions can be recognized by their color tones. Results obtained warrant continuation of this study using color composite prints enlarged to a scale of 1:500,000.

Gilbertson, B. P.↗
NASA NTRS1973

Ecological effects of strip mining in Ohio

The author has identified the following significant results. ERTS-1 imagery has identified when reclamation has proved successful, when little lateral extension has occurred in the strip mine, when water has filled an impoundment (4 - 5 acres), and detected narrow contour mines. It has been proven that the CCT contains more information than the imagery received from NASA. A stream is visible in the band 7 digital printout that is not visible in the imagery. Also narrow bodies of water between the high wall and spoils bank and small impoundments (2 - 3 acres) are observed in the digital printout and not in the imagery. Disruption maps (water and bare earth within the mined area) can be made by statistically processing the CCT (decision imagery) or mapping the digital printout with a Bendix digitizer. Reclamation maps will be produced in the near future through decision imagery. There seems little doubt that the mapping of present stripping and the monitoring of the strip mine cycle for changes are practical. Disruption mapping is now an operational capability.

Chase, P. E.↗
NASA NTRS1973

ERTS-1 investigation of ecological effects of strip mining in eastern Ohio

Evidence is presented of ERTS capability to detect, map and monitor the effects of strip mining. Both enlarge ERTS imagery and statistically processed outline maps and imagery of stripped earth and standing water are compared to aerial photos of a strip mine near Coshocton, Ohio. The outline maps and decision imagery are at present limited to forming a disruption map of recently mined and unreclaimed earth and the resultant standing water within the mined area. It is planned to prepare a map of the reclaimed areas (reclamation map) within the stripped area and to detect and identify ecological effects such as vegetation kills and stream sedimentation external to the stripped areas.

Chase, P. E.↗
NASA NTRS1974

Automated strip mine and reclamation mapping from ERTS

In response to the urgent need for a faster and more economical means of generating strip mine and reclamation maps, a study was conducted to evaluate the suitability of using ERTS computer compatible tape for automatic mapping. The procedure uses computer target spectral recognition techniques as a basis for classification. The area encompassed by this investigation includes five counties in eastern Ohio that comprise nearly 7,500 square kilometers (3,000 square miles). The counties have been disrupted by coal mining since the early 1800's, and strip mining has been practiced in all of them. The environmental effects of strip mining are also discussed.

Pettyjohn, W. A.↗
NASA NTRS1975

LANDSAT inventory of surface-mined areas using extendible digital techniques

Multispectral analysis of LANDSAT imagery provides a rapid and accurate means of identification, classification, and measurement of strip-mined surfaces in Western Maryland. Four band analysis allows distinction of a variety of strip-mine associated classes, but has limited extendibility. A method for surface area measurement of strip mines, which is both geographically and temporally extendible, was developed using band-ratioed LANDSAT reflectance data. The accuracy of area measurement by this method, averaged over three LANDSAT scenes taken between September 1972 and July 1974, is greater than 93%. Total affected acreage of large (50 hectare/120 acre) mines can be measured to within 1.0%.

Anderson, A. T.↗
NASA NTRS1975

LANDSAT inventory of surface-mined areas using extendible digital techniques

Multispectral LANDSAT imagery was analyzed to provide a rapid and accurate means of identification, classification, and measurement of strip-mined surfaces in Western Maryland. Four band analysis allows distinction of a variety of strip-mine associated classes, but has limited extendibility. A method for surface area measurements of strip mines, which is both geographically and temporally extendible, has been developed using band-ratioed LANDSAT reflectance data. The accuracy of area measurement by this method, averaged over three LANDSAT scenes taken between September 1972 and July 1974, is greater than 93%. Total affected acreage of large (50 hectare/124 acre) mines can be measured to within 1.0%.

Anderson, A. T.↗