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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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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

In-Situ Resource Utilization (ISRU) Living off the Land on the Moon and Mars

In-Situ Resource Utilization (ISRU) is the concept of using local resources at various destinations to provide products and services for robotic and human explorers. This idea of 'living off the land' has the potential of reducing reliance on earth to supply mission consumables such as propellants and life support consumables. Local resources include: water, oxygen, and metals within the surface soil material (regolith), atmospheric gases (eg CO2 on Mars), and the regolith material itself. ISRU systems involve physically and chemically extracting these resources and converting them into desired products.

In-situ resource utilization↗
NASA NTRS2015

Mars Soil-Based Resource Processing and Planetary Protection

The ability to extract and process resources at the site of exploration into products and services, commonly referred to as In Situ Resource Utilization (ISRU), can have significant benefits for robotic and human exploration missions. In particular, the ability to use in situ resources to make propellants, fuel cell reactants, and life support consumables has been shown in studies to significantly reduce mission mass, cost, and risk, while enhancing or enabling missions not possible without the incorporation of ISRU. In December 2007, NASA completed the Mars Human Design Reference Architecture (DRA) 5.0 study. For the first time in a large scale Mars architecture study, water from Mars soil was considered as a potential resource. At the time of the study, knowledge of water resources (their form, concentration, and distribution) was extremely limited. Also, due to lack of understanding of how to apply planetary protection rules and requirements to ISRU soil-based excavation and processing, an extremely conservative approach was incorporated where only the top several centimeters of ultraviolet (UV) radiated soil could be processed (assumed to be 3% water by mass). While results of the Mars DRA 5.0 study showed that combining atmosphere processing to make oxygen and methane with soil processing to extract water provided the lowest mission mass, atmosphere processing to convert carbon dioxide (CO2) into oxygen was baselined for the mission since it was the lowest power and risk option. With increased knowledge and further clarification of Mars planetary protection rules, and the recent release of the Mars Exploration Program Analysis Group (MEPAG) report on "Special Regions and the Human Exploration of Mars", it is time to reexamine potential water resources on Mars, options for soil processing to extract water, and the implications with respect to planetary protection and Special Regions on Mars.

Sanders, G. B.↗
NASA NTRS2017

Lunar Advanced Volatile Analysis Subsystem: Pressure Transducer Trade Study

In Situ Resource Utilization (ISRU) is a key factor in paving the way for the future of human space exploration. The ability to harvest resources on foreign astronomical objects to produce consumables and propellant offers potential reduction in mission cost and risk. Through previous missions, the existence of water ice at the poles of the moon has been identified, however the feasibility of water extraction for resources remains unanswered. The Resource Prospector (RP) mission is currently in development to provide ground truth, and will enable us to characterize the distribution of water at one of the lunar poles. Regolith & Environment Science and Oxygen & Lunar Volatile Extraction (RESOLVE) is the primary payload on RP that will be used in conjunction with a rover. RESOLVE contains multiple instruments for systematically identifying the presence of water. The main process involves the use of two systems within RESOLVE: the Oxygen Volatile Extraction Node (OVEN) and Lunar Advanced Volatile Analysis (LAVA). Within the LAVA subsystem, there are multiple calculations that depend on accurate pressure readings. One of the most important instances where pressure transducers (PT) are used is for calculating the number of moles in a gas transfer from the OVEN subsystem. As a critical component of the main process, a mixture of custom and commercial off the shelf (COTS) PTs are currently being tested in the expected operating environment to eventually down select an option for integrated testing in the LAVA engineering test unit (ETU).

Kang, Edward Shinuk↗
DOE OSTI2023

DQ Admittance Extraction for Inverter-Based Resources

The power grid industry is pushing for electromagnetic transient (EMT)-based studies for generation interconnection and planning process due to high penetrations of inverter-based resource (IBRs). Vendor-specific and site-specific black-box IBR models are preferred in those simulation studies. For small-signal analysis, measurement-based admittance models are necessary. In this paper, we demonstrate the extraction of frequency-domain dq frame IBR models. These linear models are specific to operating conditions. We demonstrate two extraction methods: frequency scan and a step response-based method. The latter relies on converting time-domain responses to Laplace-domain expressions via eigensystem realization analysis (ERA). Both can lead to dq admittance representation and the latter is time saving.

admittance model↗
DOE OSTI2023

DQ Admittance Extraction for Inverter-Based Resources: Preprint

The power grid industry is pushing for electro-magnetic transient (EMT)-based studies for generation interconnection and planning process due to high penetrations of inverter-based resource (IBRs). Vendor-specific and site-specific black-box IBR models are preferred in those simulation studies. For small-signal analysis, measurement-based admittance models are necessary. In this paper, we demonstrate the extraction of frequency-domain dq frame IBR models. These linear models are specific to operating conditions. We demonstrate two extraction methods: frequency scan and a step response-based method. The latter relies on converting time-domain responses to Laplace-domain expressions via eigensystem realization analysis (ERA). Both can lead to dq admittance representation and the latter is time saving.

admittance model↗
DOE OSTI2025

Leveraging Large Language Models for Real-World Data Evidence: A Framework for Automated Treatment Extraction and Data Harmonization

Background: The ability to comprehensively collect treatment information from cancer patient medical records would enable studies to evaluate real-world benefits and risks tied to specific treatments. Currently, it is difficult to system- atically collect high-quality treatment information because it is often stored in unstructured text. Manually extracting and standardizing drug and regimen data is time-intensive. Recent advances in large language models (LLMs) offer a potential solution for automated extraction of structured treatment information from clinical text. Objective: This study systematically evaluates the utility of four LLMs from the Llama family for automated extraction of oncology treatment information from clinical text. This information can guide researchers using cancer registry data to provide insights into cancer care and outcomes beyond clinical trials. Methods: Four instruction-tuned Llama models with varying parameter counts (1B, 3B, 8B, and 70B) were evaluated for their ability to extract treatment information from clinical documents. A unified oncology knowledge base integrating seven major public data sources was developed to standardize and normalize extracted entities—a critical step for harmonizing data from diverse sources. Extracted treatment data were compared against expert-annotated ground truth. Model performance was assessed using accuracy metrics (Precision, Recall, F1-Score) and opera- tional feasibility metrics, including processing speed and structural compliance of the output. Results: A strong positive correlation was observed between model size and extraction accuracy. F1-score improved from 0.609 for the 1B model to 0.710 (3B), 0.807 (8B), and 0.828 (70B). While larger models demonstrated superior accuracy and compliance, they incurred higher computational costs. The modest performance difference between 8B and 70B suggests diminishing returns with increasing model size. Conclusions: LLMs represent a viable technology for automating oncology treatment extraction. The 8B-parameter model emerged as a highly effective option, balancing high accuracy and computational efficiency. Selecting an appropriate LLM for deployment in cancer registries involves a trade-off between desired accuracy and available operational resources. Harmonizing extracted entities with the oncology knowledge base facilitates standardized integration into common data models, enhancing data quality for real-world evidence analyses.

artificial intelligence↗
NASA NTRS2020

Implementation Concept of Operation for a Multi-Purpose Cassegrain Solar Concentrator, Micro-Spectrometers, and Electrostatic Neutralizers to Enable In Situ Construction Activities plus Lunar, Planetary, and Deep Space Science Exploration on the Moon

The ability to utilize regolith would support human missions to the Moon and Mars by both stabilizing the surface as well as the use of indigenous resources. Precision landing requirements include surface stabilization to prevent damage or contamination due to regolith projectiles as a result of plume interaction with regolith. The use of indigenous resources rather than hauling materials from Earth appears to be economically a palatable option by converting indigenous resources to usable products. However, such activities have new technical challenges to overcome the issues related to lunar environmental conditions, a wide range of temperature fluctuation, extremely high vacuum, and electrostatically charged fine regolith dusts. For both the regolith sintering and extraction of resources onsite, a Cassegrain solar concentrator was studied for not only sintering lunar regolith into a hardened stabilized surface, but also other multiple applications. This report illustrates a Cassegrain solar concentrator that has multi-functional capabilities for space missions. Proper design and implementation of high-performance lightweight composite materials for the primary mirror of the Cassegrain concentrator can offer multiple capabilities to be performed on the Moon. The multiple applications studied with Cassegrain concentrators are (1) Solar sintering for landing pad and habitats, (2) Harvest of volatiles: H2O, O2, H2, and He-3, (3) Space antenna for telemetry and telecommunication, and (4) Space telescope with 20-meter aperture that exceeds the space telescopes to date in terms of the State-of-Art (SOA) in resolution and aperture diameter. In this study, a key emphasis was placed on the NASA Langley-developed boron nitride nanotube (BNNT) nanocomposite technology which is ideal for the segmented primary mirror structure of the Cassegrain system because it promises a very low coefficient of thermal expansion (CTE) and negligible Poisson ratio. Also, BNNT nanocomposites offer several noticeable benefits, such as light weight, radiation shielding capability, and mechanical strength for structural applications. Additionally, the NASA Langley-developed bullet-like micro-spectrometer and electrostatic power generator were reviewed for mineral mapping applications and electrostatic power generation and dust mitigation from electrostatically charged regolith.

landing pad↗
NASA NTRS1975

Earth resources shuttle imaging radar

A report is presented on a preliminary design of a Synthetic Array Radar (SAR) intended for experimental use with the space shuttle program. The radar is called Earth Resources Shuttle Imaging Radar (ERSIR). Its primary purpose is to determine the usefulness of SAR in monitoring and managing earth resources. The design of the ERSIR, along with tradeoffs made during its evolution is discussed. The ERSIR consists of a flight sensor for collecting the raw radar data and a ground sensor used both for reducing these radar data to images and for extracting earth resources information from the data. The flight sensor consists of two high powered coherent, pulse radars, one that operates at L and the other at X-band. Radar data, recorded on tape can be either transmitted via a digital data link to a ground terminal or the tape can be delivered to the ground station after the shuttle lands. A description of data processing equipment and display devices is given.

Source record↗
DOE OSTI2017

Basic Research Needs for Energy and Water (Brochure)

Water is precious. This unique, indispensable resource is essential not only for life, but also for practically all forms of economic activity. The food we eat, the clothes we wear, the goods we use, and the electricity we consume all require water. Cooling in power plants, refining petroleum, producing fuel, and extracting energy resources from the earth make up a significant fraction of water use. Conversely, water treatment, distribution, and use are large consumers of energy.

Source record↗
NASA NTRS2005

In Situ Resource Utilization (ISRU) Experiments for Mars Exploration

In situ resource utilization can best be described as living off the land. In our case the land is the planet Mars. ISRU is based on the idea that some fraction of the consumables, life support and propellant materials do not have to be flown from earth. Rather, they can be manufactured or extracted from resources already present on Mars. The primary resources on Mars are the atmosphere, polar caps and regolith. The atmosphere of Mars is mostly carbon dioxide as shown in the table below. The proportion of oxygen on the other hand is quite small. Still, there is quite a bit of oxygen in the Martian atmosphere, but it is unfortunately tied up with carbon. Thus, one of the goals of ISRU is the separation of breathable oxygen from the carbon dioxide. Several means of separation have been proposed. We have begun experiments on another approach for production of oxygen with carbon monoxide as a useful by product. Our work on a CO2 separator is described later in this report. Regolith melting is another means of obtaining materials. Two materials of interest are iron and silicon. Iron oxide is plentiful on Mars and is of obvious importance for structural components. Silicon is the foundation of solid state devices. Power generation on Mars may be accomplished using silicon solar cells. There is discussion of the feasibility of in situ production of solar cells. This would require a means of extracting silicon from the regolith. We have conducted several experiments concerning melting and glassification of the Mars soil simulant. Other summer faculty fellows have tried various means of processing the stimulant material. These include furnace melting, microwave melting and laser ablation. We have conducted several furnace melting experiments in both air and carbon dioxide environments. We have also carried out experiments to test spark melting in a carbon dioxide atmosphere. These experiments suggest the possibility of using arc melting in a reducing atmosphere. It is important to keep in mind that we are working with a soil stimulant. Any simulant, no matter how chemically similar it is to Martian regolith, may differ in mineralogy. The underlying assumption in this work is that once a glass is formed, any differences between simulant and regolith are unimportant. The exact means of forming the glass do, however, depend on the mineralogy of the regolith. A sample return mission is required to help answer these questions.

Marone, Matt↗
DOE OSTI2017

Vehicle's lightweight design vs. electrification from life cycle assessment perspective

Lightwiegh materials and vehicles' electrification are among the most viable and economic solutions to improve fuel ecocnmoy of vehicles and reduce environmental impacts in the operational phase of typical vehicle's life cycle span. This study aims to shed more light on the combined effect of lightweighing and electrification by assessing different lightweight designs and electric powetrians from the environmental perspective using a life cycle analysis coupled with an emphasis on energy expenditures and carbon dioxide emissions. This article discusses the life cycle assessment for several advanced powertrains namely; plug-in hybrid electric vehicles (PHEV), battery electric vehicles (BEV) and hybrid electric vehicles (HEV) relative to the conventional gasoline operated internal combustion engine based power train vehicles. The main focus will be on the energy greenhouse gas emissions (GHG) in the material extraction and resources phase, manufacturing phase and use phase (operation and maintenance). While most of the current studies focus on the use phase that does not reflect the correct environmental impacts associated with advanced powertrains, thus the presented text applies a holistic LCA approach that covers pre-manufacturing, manufacturing, operational and end-of-life phases, plus another indirect phase to account for fuel extraction, refining and transportation to the end-users or customers. Based on the LCA emissions results, one may infer that environmental policies that reduce emissions rates from the electricity sector can mitigate this effect without completely eliminating it. Interestingly, the analysis show that lightweight vehicles with internal combustion engines have less impacts on the environment as a direct result of upstream emissions associated with electricity generation in United States. This scenario can differ in other countries with higher renewable and sustainable energy generated electric powers.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

Constellation: A science graph network for scalable data and knowledge discovery in extreme-scale scientific collaborations

Constellation's overarching goal is the federation of information from resources within an extreme-scale scientific collaboration to enable the scalable discovery of data and new knowledge pathways. The resource fabric is comprised of petascale supercomputers and storage systems, users, jobs, datasets and lifecycle artifacts. For an extreme-scale supercomputing center, normal operations can generate hundreds of millions of data products and metadata entries describing the resource fabric. Constellation federates the information extracted from the resources using a custom, transformative science graph network; constructs rich metadata indexes and higher-order derived metadata from the extracted information; and conducts scalable graph analytics to unravel hidden data pathways. Our implementation and deployment for a production, supercomputing facility shows that the graph can scale to more than 750 million vertices, its domain agnostic indexing can answer interesting science queries, and its analytics can aid in structural, topological and temporal analysis to identify usage hotspots.

Vazhkudai, Sudharshan S.↗
DOE OSTI2022

Sampling and Characterization of Coal Basins as an Alternative Rare-Earth Element Resource

Conference presentation at TechConnect World Innovation Conference & Expo, Washington, D.C., June 13–15, 2022. The University of North Dakota (UND) through the Energy & Environmental Research Center (EERC) and the Institute for Energy Studies teamed with the University of Kentucky Center for Applied Energy Research, Microbeam Technologies Inc., the Kentucky Geological Survey (KGS), the North Dakota Geological Survey (NDGS), and the mining industry to execute a contract with the U.S. Department of Energy National Energy Technology Laboratory (NETL) to obtain and characterize samples of U.S. domestic precombustion coal and coal-related materials with a minimum concentration of 300 parts per million (ppm) total rare-earth elements (TREEs) as the material is removed from the ground, with no processing other than drying.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2018

Marine partially protected areas: drivers of ecological effectiveness

The number of marine protected areas ( MPA s) has grown exponentially worldwide over the past decade in order to meet international targets. Most of these protected areas allow extraction of resources and are therefore designated as “partially protected areas” ( PPA s). However, the effectiveness of PPA s remains unclear due to the high variability of use types permitted. Here, we carried out what we believe to be the first global meta‐analysis of PPA s using a regulation‐based classification system for MPA s to assess their ecological effectiveness. This novel classification allows for unambiguous differentiation between areas according to allowed use, which is the key feature determining PPA performance. Highly and moderately regulated areas exhibited higher biomass and abundance of commercial fish species, whereas fish abundance and biomass in weakly regulated areas differed little from unprotected areas. Notably, the effectiveness of moderately regulated areas can be enhanced by the presence of an adjacent fully protected area. We concluded that limited and well‐regulated uses in PPA s and the presence of an adjacent fully protected area confer ecological benefits, from which socioeconomic advantages are derived.

Zupan, Mirta↗
DOE OSTI2021

Machine-learning predictions of the shale wells’ performance

The ultra-low permeability nature of shale reservoirs leads to an extended linear flow and necessitates horizontal wells with multi-stage engineered fractures to efficiently extract hydrocarbons resources. These artificially-generated and naturally-occurring fractures form complex networks that create complex flow regimes which control oil production. These fractures are neither identical nor equally-spaced, which leads to a production profile with a masked onset of the boundary-dominated flow. The combination of the extended linear flow with the indeterminate onset of the boundary-dominated flow challenges the current deterministic analytic approaches to forecast the estimated ultimate recovery (EUR). In this work, we propose a novel machine-learning approach which overcomes these challenges and provides reliable EUR estimates based on field-wide analyses. We implement a novel unsupervised machine learning (ML) methodology, which allows for automatic identification of the optimal number of features (signals) present in the data based on non-negative matrix/tensor factorization coupled with k-means clustering incorporating regularization and physics constraints. In the presented analyses, the input data to the ML algorithm is the available (public) production history from the field collected at existing unconventional reservoirs. We validate our approach through hindcasting of the production data, where we achieved an excellent agreement. In addition, our approach is able to identify the poorly-performing wells, which could benefit from early refracing. Our approach provides fast and accurate estimations of the well performance without presumptions about the state of the well or the flow regime.

03 NATURAL GAS↗
DOE OSTI2012

Temperature dependence of cation exchange in geothermal applications

Geothermal energy is heat energy stored by the earth, and is currently being explored as a renewable energy resource. To extract energy efficiently from a geothermal reservoir it must be hot, close to the surface, and have good permeability. If a reservoir is lacking any of these it can be enhanced by creating fractures in the rock. These fractures increase surface area available for heat transfer, and allow water to flow more efficiently increasing energy output. In this study we determine if the effectiveness of the enhancement can be determined by the chemical indicator lithium (Li). We preformed simulations to study the amount of Li that absorbs onto the rock at different temperatures. From this data we determined the absorption of Li onto the rock does not change significantly with change in temperature and therefore can be used to determine change in surface area after enhancement.

Earth Sciences↗
DOE OSTI2024

Reverse Osmosis Simulation Data

This dataset consists of computational fluid dynamics (CFD) output for various spacer configurations in a feed-water channel in reverse osmosis (RO) applications. Feed-water channels transport brine solution to the RO membrane surfaces. The spacers embedded in the channels help improve membrane performance by disrupting the concentration boundary layer growth on membrane surfaces. Refer to the "Related Work" resource below for more details. This dataset considers a feed-water channel of length 150mm. The inlet brine velocity and concentration are fixed at 0.1m/s and 100kg/m3 respectively. The diameter of the cylindrical spacers is fixed as 0.3mm and six varying inter-spacer distances of 0.75mm, 1mm, 1.5mm, 2mm, 2.5mm, and 3mm are simulated. The dataset comprising the steady, spatial fields of solute concentration, velocity, and density near each spacer is placed in the folder corresponding to the spacer configuration considered. We run two sets of CFD simulations and include the outputs from both sets for each configuration: (1) with a coarser mesh, producing low-resolution (LR) data of spatial resolution 20x20, and (2) with a finer mesh, producing high-resolution (HR) data of spatial resolution 100x100. These data points can be treated as images with the quantities of interest as their channels and can be used to train machine learning models to learn a mapping from the LR images as inputs to the HR images as outputs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗