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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

NASA’s Pandora SmallSat Mission: Simulated Modeling and Retrieval of Near-infrared Exoplanet Transmission Spectra

Pandora is a SmallSat mission dedicated to understanding exoplanets and their host stars by disentangling the impact of stellar heterogeneity on exoplanet transmission spectra. Selected as a NASA Astrophysics Pioneers mission in 2021, Pandora will provide simultaneous long-term visible photometric monitoring (0.4–0.7 μm) and low-resolution near-infrared (NIR) spectroscopy (0.9–1.6 μm) of transiting systems for the purposes of monitoring host star variability and characterizing exoplanetary atmospheres. Pandora’s year-long prime mission from 2026 to 2027 coincides with the middle of a decade defined by targeted efforts for atmospheric characterization of exoplanets, offering a key opportunity to leverage this new resource to maximize science with JWST and other observatories. Here we investigate Pandora’s anticipated performance for the general exoplanet population accessible to transit spectroscopy, from hot Jupiters to temperate sub-Neptunes. By modeling the atmospheres of five test cases broadly consistent with the bulk properties of HD 209458b, HD 189733b, WASP-80 b, HAT-P-18 b, and K2-18 b, we find that Pandora may provide abundance constraints as precise as ∼1.0 dex for main atmospheric absorbers such as H 2 O and CH 4 . Then, we explore the synergies between Pandora and JWST. Our results suggest that targets with JWST data in the NIR can benefit from the addition of Pandora observations and result in more reliable abundance estimates than with JWST data alone. Moreover, Pandora can serve the community by providing precursory observations of targets of interest for JWST atmospheric characterization. We conclude by outlining strategies for the use of Pandora as a standalone observatory and in synergy with JWST.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Estimates of Lake Nitrogen, Phosphorus, and Chlorophyll‐ a Concentrations to Characterize Harmful Algal Bloom Risk Across the United States

Abstract Excess nutrient pollution contributes to the formation of harmful algal blooms (HABs) that compromise fisheries and recreation and that can directly endanger human and animal health via cyanotoxins. Efforts to quantify the occurrence, drivers, and severity of HABs across large areas is difficult due to the resource intensive nature of field monitoring of lake nutrient and chlorophyll‐aconcentrations. To better characterize how nutrients interact with other environmental factors to produce algal blooms in freshwater systems, we used spatially explicit and temporally matched climate, landscape, in‐lake characteristic, and nutrient inventory data sets to predict nutrients and chlorophyll‐aacross the conterminous US (CONUS). Using a nested modeling approach, three random forest (RF) models were trained to explain the spatiotemporal variation in total nitrogen (TN), total phosphorus (TP), and chlorophyll‐aconcentrations across US EPA's National Lakes Assessment (n = 2,062). Concentrations of TN and TP were the most important predictors and, with other variables, the RF model accounted for 68% of variation in chlorophyll‐a. We then used these RF models to extrapolate lake TN and TP predictions to lakes without nutrient observations and predict chlorophyll‐afor ∼112,000 lakes across the CONUS. Risk for high chlorophyll‐aconcentrations is highest in the agriculturally dominated Midwest, but other areas of risk emerge in nutrient pollution hot spots across the country. These catchment and lake‐specific results can help managers identify potential nutrient pollution and chlorophyll‐ahot spots that may fuel blooms, prioritize at‐risk lakes for additional monitoring, and optimize management to protect human health and other environmental end goals.

Environmental Sciences & Ecology↗
DOE OSTI2019

A New Study on Characterization and Properties of Natural Fibers Obtained from Olive Tree (Olea europaea L.) Residues

Nowadays, fibers extracted from natural resources have a wide range of promising applications, including the prospect to be used as reinforcing material in polymer composites. In this context, the purpose of this study has been to extract fibers from different parts of the olive tree (leaves, small and large branches) and characterize their physico-chemical, thermal, and morphological properties using advanced equipment. Olive leaf (OL) fiber showed asymmetrical size distribution, as compared to those extracted from small olive branches (OSS), and big olive branches (OBS). The OL fiber exhibited 64.1% crystallinity, which is lower than that of the OSS fiber—with 65.4% crystallinity. Thermal analysis revealed that the OBS and OSS fibers are more thermally stable, compared to the OL fibers. The obtained results concluded that olive tree fibers can be suitable for being used as reinforcement material to develop polymer composites for various lightweight applications.

36 MATERIALS SCIENCE↗
NASA NTRS2014

Characterizing the Physical and Thermal Properties of Planetary Regolith at Low Temperatures

The success or failure of in-situ resource utilization for planetary surface exploration-whether for science, colonization, or commercialization-relies heavily on the design and implementation of systems that can effectively process planetary regolith and exploit its potential benefits. In most cases, this challenge necessarily includes the characterization of regolith properties at low temperatures (cryogenic). None of the nearby solar system destinations of interest, such as the moon, Mars and asteroids, possess a sufficient atmosphere to sustain the consistently "high" surface temperatures found on Earth. Therefore, they can experience permanent cryogenic temperatures or dramatic cyclical changes in surface temperature. Characterization of physical properties (e.g., specific heat, thermal and electrical conductivity) over the entire temperature profile is important when planning a mission to a planetary surface; however, the impact on mechanical properties due to the introduction of icy deposits must also be explored in order to devise effective and robust excavation technologies. The Granular Mechanics and Regolith Operations Laboratory and the Cryogenics Test Laboratory at NASA Kennedy Space Center are developing technologies and experimental methods to address these challenges and to aid in the characterization of the physical and mechanical properties of regolith at cryogenic temperatures. This paper will review the current state of knowledge concerning planetary regolith at low temperature, including that of icy regolith, and describe efforts to manipulate icy regolith through novel penetration and excavation techniques.

Characterizing the Physical and Thermal Properties↗
DOE OSTI2023

Geospatial Characterization of Low-Temperature Heating and Cooling Demand in the United States: Preprint

Geothermal resources at temperatures below 150 degrees C have great potential as energy sources for various direct-use applications including heating and cooling in residential and commercial buildings. This study geospatially quantifies U.S. heating and cooling demand in residential, commercial, and manufacturing sectors; heating demand in the agricultural sector; and cooling demand in data centers at the county level through end-use energy consumption, expenditure, and commissioned power analyses. Heating and cooling demand in the residential sector was estimated using energy consumption data obtained from the U.S. Energy Information Administration accounting for different U.S. climate zones. For commercial sector analysis, the end-use major fuel energy intensity at the census division level was disaggregated to the county level with respect to principal building activities. Heating and cooling demand analysis for the manufacturing sector was based on end-use energy consumption for direct-use total process categorized by the North America Industry Classification System. Fuel expenditures in the U.S. Department of Agriculture Farm Production Expenditures were examined for heating demand analysis in the agricultural sector, particularly for the greenhouse, nursery, and floriculture production category. Lastly, commissioned power for data centers in the United States were explored for cooling demand analysis. Results indicated a significant fraction of U.S. primary energy consumption is used for low-temperature heating and cooling applications. Heating and cooling demand in residential and commercial sectors is significantly affected by the number of housing units and climate zone designations, while heating and cooling demand in manufacturing and agricultural sectors and data centers are mainly dependent on the number of facilities and their locations. Maps were generated visualizing where heating and cooling demand is high and, overlain with geothermal resource maps, can indicate locations where geothermal energy can supply this heating and cooling demand.

cooling demand↗
NASA NTRS1975

CARETS: A prototype regional environmental information system. Volume 2, parts A and B: Norfolk and environs; a land use perspective

The author has identified the following significant results. The Norfolk-Portsmouth metropolitan statistical area in southeastern Virginia was the site of intensive testing of a number of land resources assessment methods. Land use and land cover data at three levels of detail were derived by manual image interpretation from both aircraft and satellite sources and used to characterize the 1,766 sq km (682 sq mi) area from the perspective of its various resource-related activities and problems. Measurements at level 1 from 1:100, 000 scale maps revealed 42 percent of the test area (excluding bays and estuaries) to be forest, 28 percent agriculture, 23 percent urban and built-up, 4 percent nonforested wetlands, and 2 percent water. At the same scale and level of detail, 10 percent of the area underwent change from one land use category to another in the period 1959-70, 62 percent of which involved the relatively irreversible change from forest or agriculture to urban uses.

Norfolk-Portsmouth SHSA↗
DOE OSTI2020

Model Exploration of an Information-Based Healthcare Intervention Using Parallelization and Active Learning

This paper describes the application of a large-scale active learning method to characterize the parameter space of a computational agent-based model developed to investigate the impact of CommunityRx, a clinical information-based health intervention that provides patients with personalized information about local community resources to meet basic and self-care needs. Additionally, the diffusion of information about community resources and their use is modeled via networked interactions and their subsequent effect on agents' use of community resources across an urban population. A random forest model is iteratively fitted to model evaluations to characterize the model parameter space with respect to observed empirical data. We demonstrate the feasibility of using high-performance computing and active learning model exploration techniques to characterize large parameter spaces; by partitioning the parameter space into potentially viable and non-viable regions, we rule out regions of space where simulation output is implausible to observed empirical data. We argue that such methods are necessary to enable model exploration in complex computational models that incorporate increasingly available micro-level behavior data. We provide public access to the model and high-performance computing experimentation code.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2022

Balancing Predictive and Reactive Science Planning for Mars 2020 Perseverance

The design of the science planning process for a space science mission needs to find a balance between operational and resource constraints and scientific decision-making. Science planning has previously been characterized as either predictive or reactive. Predictive science planning is needed when constraints drive science activities to be planned far in advance. For example, a combination of long one-way light time plus high-stakes science decisions drove the Cassini-Huygens mission to Saturn to have an extremely predictive planning process. On the other extreme, reactive science planning is needed when constraints drive science activities to be planned based on the results of the previous plan. For example, the Mars Exploration Rover mission interacted with the surface of Mars, and so the planning team needed to know the state of the rover at the end of each planning cycle before starting the next cycle. Operational and resource constraints that require management on intermediate timescales has led to the development of a science planning process between these two extremes. For example, the Mars Science Laboratory is a technically complex rover and has a parallel predictive process that allows the operations team to manage engineering constraints several days in advance while maintaining the reactive tactical planning process similar to that of MER. The Mars 2020 Perseverance rover is a technically complex rover in the MSL style, but has an added layer of science complexity: it is tasked with collecting a returnable cache of scientifically valuable samples of Mars within prime mission. Thus, the science planning process also needs to accommodate high-stakes longer-term science decisions in the style of Cassini. In order to balance the push-pull of these constraints, we have developed a science campaign-focused operational paradigm for Mars 2020 Perseverance that allows for both predictive planning to accommodate technological complexity and high-stakes science decisions as well as reactive planning to accommodate the realities of interacting with the martian surface. This paradigm influenced the design of operational processes and operational tools.

Spanovich, Nicole↗
DOE OSTI2021

Discovering Hidden Geothermal Signatures using Unsupervised Machine Learning

Discovering hidden geothermal resources is a very challenging task. It requires the mining of large datasets, including various diverse data attributes representing subsurface hydrogeological and geothermal conditions. The commonly used Play Fairway Analysis (PFA) typically relies on subject-matter expertise to analyze site or regional data to estimate geothermal conditions and prospectivity. Here, we demonstrate an alternative approach based on machine learning (ML) to process a geothermal dataset of Southwest New Mexico (SWNM). The study region includes low- and medium-temperature hydrothermal systems. However, most of these systems are poorly characterized because of insufficient existing data and limited past explorative studies. This study aims to discover hidden patterns and relationships in the SWNM geothermal dataset to better understand regional hydrothermal conditions. This is achieved by applying an unsupervised machine learning algorithm based on non-negative matrix factorization coupled with customized k-means clustering (NMFk). NMFk can automatically identify (1) hidden (latent) signatures characterizing datasets, (2) the optimal number of these signatures, (3) dominant data attributes associated with each signature, and (4) spatial distribution of the extracted signatures. Here, NMFk is applied to analyze 18 geological, geophysical, hydrogeological, geothermal attributes at 44 locations in SWNM. NMFk successfully finds data patterns and identifies the spatial associations of hydrothermal signatures with the four physiographic provinces in SWNM (Colorado Plateau, Volcanic Field, Basin and Range, and the Rio Grande rift). The algorithm identified up to 5 hydrothermal signatures in the SWNM datasets that differentiate between low- and medium-temperature hydrothermal systems in different provinces. Also, the algorithm identifies two medium-temperature hydrothermal systems in SWNM that require further exploration for geothermal resource development. Based on our analyses, 12 of the attributes are important to identify medium-temperature hydrothermal systems, and the remaining six attributes are critical to characterize low-temperature hydrothermal systems. Based on the obtained results, we identify potential physiographic provinces for further exploration to characterize them as geothermal resources. The resulting NMFk model can be applied to predict geothermal conditions and their uncertainties at new SWNM locations based on limited data from unexplored areas.

58 GEOSCIENCES↗
DOE OSTI2025

Low-Cost Screening of Algae for Extreme Tolerance to pH, Temperature, Salinity, and Light

AbstractBioprospecting algae strains with tolerance to extreme conditions such as pH, temperature, salinity, and light is crucial for advancing biotechnology and environmental applications. However, traditional screening methods often involve significant costs and labor, restricting their accessibility and practical use. In this study, we developed and validated low-cost, high-throughput screening techniques, predominantly employing agar plates and liquid culture assays, to effectively differentiate tolerance levels among various algae strains. The methodologies were optimized using the model microalgaChlamydomonas reinhardtiiand its closely related speciesChlamydomonas incertaand the recently discovered extremophilicChlamydomonas pacifica. We systematically evaluated the algae for tolerance to extremes by establishing precise gradients of pH (acidic to alkaline conditions), salinity (0 to 5 M NaCl), temperature (34–42°C), and light intensity (40 to 2977 μE·m⁻²·s⁻¹). Our results demonstrated that these cost-effective, agar plate-based methods effectively distinguished algae strains exhibiting superior tolerance to extreme environmental conditions. These screening techniques not only provided clear differentiation among the closely related strains but also delivered reproducible outcomes suitable for scaling up to larger bioprospecting efforts. Furthermore, the affordability and simplicity of these methods facilitate their implementation in resource-limited laboratories, thereby broadening participation in algae bioprospecting endeavors. This study highlights the potential of low-cost, accessible screening techniques to significantly enhance the discovery and characterization of algal strains with extreme traits. Ultimately, these methods support the development of robust algae-based resources, driving innovation in diverse industrial processes and environmental solutions.Graphical Abstract

Saucedo, Barbara (ORCID:0009000008860839)↗
DOE OSTI2019

Wildlife Management Plan for the Oak Ridge Reservation

This document outlines a plan for management of the wildlife resources on the US Department of Energy’s (DOE’s) Oak Ridge Reservation. Management includes wildlife population control through restoration of wildlife species; preservation, management, and enhancement of wildlife habitats; coordination of wildlife studies and characterization of areas, hunting, trapping, removal, and habitat manipulation; wildlife damage control; and law enforcement. Wildlife resources are divided into several categories, each with a specific set of objectives and procedures to attain the goals. These objectives are management of (1) wildlife habitats to ensure that all resident wildlife species exist on the Reservation in viable numbers; (2) focal species to promote healthy populations on designated land units; (3) game species for research, education, recreation, and public safety; (4) the Three Bend Scenic and Wildlife Management Refuge Area; (5) nuisance wildlife, including nonnative species, to achieve adequate population control for the maintenance of health and safety on the Reservation; (6) sensitive species (i.e., state or federally listed as Endangered, Threatened, Of Special Concern, or In Need of Management) through preservation and protection of both the species and habitats critical to the survival of those species; and (7) wildlife disease. Achievement of the objectives is a joint effort between Oak Ridge National Laboratory and the Tennessee Wildlife Resources Agency (TWRA) through agreements between DOE and the University of Tennessee (UT)-Battelle LLC, between TWRA and DOE, and between Tennessee Department of Environment and Conservation (TDEC) and DOE. Implementation of objectives is to be informed by leading-edge research and a strong collaborative approach between UT-Battelle and TWRA.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Dielectric Constant Measurements on Lunar Soils and Terrestrial Minerals

The return to the Moon has ignited the need to characterize the lunar regolith using in situ methods. An examination of the lunar regolith samples collected by the Apollo astronauts indicates that only a few minerals (silicates and oxides) need be considered for in situ resource utilization (ISRU). This simplifies the measurement requirements and allows a detailed analysis using simple methods. Characterizing the physical properties of the rocks and soils is difficult because of many complex parameters such as soil temperature, mineral type, grain size, porosity, and soil conductivity. In this presentation, we will show that the dielectric constant measurement can provide simple detection for oxides such as TiO2, FeO, and water. Their presence is manifest by an unusually large imaginary permittivity.

Anderson, R. C.↗
DOE OSTI2020

Modular performance prediction for scientific workflows using Machine Learning

Scientific workflows provide an opportunity for declarative computational experiment design in an intuitive and efficient way. A distributed workflow is typically executed on a variety of resources, and it uses a variety of computational algorithms or tools to achieve the desired outcomes. Such a variety imposes additional complexity in scheduling these workflows on large scale computers. As computation becomes more distributed, insights into expected workload that a workflow presents become critical for effective resource allocation. In this paper, we present a modular framework that leverages Machine Learning for creating precise performance predictions of a workflow. The central idea is to partition a workflow in such a way that makes the task of forecasting each atomic unit manageable and gives us a way to combine the individual predictions efficiently. We recognize a combination of an executable and a specific physical resource as a single module. This gives us a handle to characterize workload and machine power as a single unit of prediction. Overall, our modular technique of creating atomic modules and deployment of longest-path approach to estimate workflow performance, allows the framework to adapt to highly complex nested directed acyclic workflows and scale to new scenarios, since it does not make assumptions of underlying workflow structure. We present performance estimation results of independent workflow modules executed on the XSEDE SDSC Comet cluster using various Machine Learning algorithms. The results provide insights into the behavior and effectiveness of different algorithms in the context of scientific workflow performance prediction.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

Ground-based observation of near-Earth asteroids

An increased ground-based observation program is an essential component of any serious attempt to assess the resource potential of near-Earth asteroids. A vigorous search and characterization program could lead to the discovery and description of about 400 to 500 near-Earth asteroids in the next 20 years. This program, in conjunction with meteorite studies, would provide the data base to ensure that the results of a small number of asteroid-rendezvous and sample-return missions could be extrapolated with confidence into a geological base map of the Aten, Apollo, and Amor asteroids. Ground-based spectral studies of nearly 30 members of the Aten/Apollo/Amor population provide good evidence that this class includes bodies composed of silicates, metal-silicates, and carbonaceous assemblages similar to those found in meteorites. The instruments that are being used or could be used to search for near-Earth asteroids are listed. Techniques useful in characterizing asteroids and the types of information obtainable using these techniques are listed.

Gaffey, Michael J.↗
NASA NTRS1993

First Lunar Outpost support study

The First Lunar Outpost (FLO) is the first manned step in the accomplishment of the Space Exploration Initiative, the Vice President's directive to NASA on the 20th anniversary of the Apollo moon landing. FLO's broad objectives are the establishment of a permanent human presence on the moon, supporting the utilization of extraterrestrial resources in a long-term, sustained program. The primary objective is to emplace and validate the first elements of a man tended outpost on the lunar surface to provide the basis for: (1) establishing, maintaining and expanding human activities and influence across the surface; (2) establishing, maintaining and enhancing human safety and productivity; (3) accommodating space transportation operations to and from the surface; (4) accommodating production of scientific information; (5) exploiting in-situ resources. Secondary objectives are: (1) to conduct local, small scale science (including life science); (2) In-situ resource utilization (ISRU) demonstrations; (3) engineering and operations tests; (4) to characterize the local environment; and (5) to explore locally. The current work is part of ongoing research at the Sasakawa International Center for Space Architecture supporting NASA's First Lunar Outpost initiative. Research at SICSA supporting the First Lunar Outpost initiative has been funded through the Space Exploration Initiatives office at Johnson Space Center. The objectives of the current study are to further develop a module concept from an evaluation of volumetric and programmatic requirements, and pursue a high fidelity design of this concept, with the intention of providing a high fidelity design mockup to research planetary design issues and evaluate future design concepts.

Bartz, Christopher↗
NASA NTRS2012

The Osiris-Rex Mission - Sample Acquisitions Strategy and Evidence for the Nature of Regolith on Asteroid (101955) 1999 RQ36

NASA selected the OSIRIS-REx Asteroid Sample Return Mission as the third New Frontiers mission in May 2011 [I]. The mission name is an acronym that captures the scientific objectives: Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer. OSIRIS-REx will characterize near-Earth asteroid (101955) 1999 RQ36, which is both the most accessible carbonaceous asteroid [2,3] and one of the most potentially hazardous asteroids known [4]. The primary objective of the mission is to return a pristine sample from this bod, to advance our understanding of the generation, evolution, and maturation of regolith on small bodies.

Lauretta, D. S.↗
NASA NTRS2015

Options for Staging Orbits in Cis-Lunar Space

NASA has been studying options to conduct missions beyond Low Earth Orbit, but within the Earth-Moon system, in preparation for deep space exploration including human missions to Mars. Referred to as the Proving Ground, this arena of exploration activities will enable the development of human spaceflight systems and operations to satisfy future exploration objectives beyond the cis-lunar environment. One option being considered includes the deployment of a habitable element or elements, which could be used as a central location for aggregation of supplies and resources for human missions in cis-lunar space and beyond. Characterizing candidate orbit locations for this asset and the impacts on system design and mission operations is important in the overall assessment of the options being considered. The orbits described in this paper were initially selected by taking advantage of previous studies conducted by NASA and the work of other authors. In this paper orbits are assessed for their relative attractiveness based on various factors. First, a set of constraints related to the capability of the combined Orion and SLS system to deliver humans and cargo to and from the orbit are evaluated. Second, the ability to support potential lunar surface activities is considered. Finally, deployed assets intended to spend multiple years in the Proving Ground would ideally require minimal station keeping costs to reduce the mass budget allocated to this function. Additional mission design drivers include potential for uninterrupted communication with deployed assets, thermal, communications, and other operational implications. The results of the characterization and evaluation of the selected orbits indicate a Near Rectilinear Orbit (NRO) is an attractive candidate as an aggregation point or staging location for operations. In this paper, the NRO is further described in terms which balance a number of key attributes that favor a variety of mission classes to meet multiple, sometimes competing, constraints.

Whitley, Ryan↗
NASA NTRSDate not supplied

GRX-810: NASA High Temperature Alloy Development for Additive Manufacturing

High-entropy alloys, and by extension, medium entropy alloys are an exciting new class of materials due to their impressive mechanical properties, especially at cryogenic and elevated temperatures. In this study, a novel oxide dispersion strengthened (ODS) NiCoCr-based alloy is presented which exhibits exceptional high temperature properties compared to conventional wrought superalloys. This new ODS alloy, GRX-810, leverages additive manufacturing to disperse nanoscale Y2O3 particles throughout the microstructure without the use of resource intensive processing steps, such as mechanical alloying. Microstructural and mechanical characterization confirms the successful incorporation and dispersion of nano-scale oxides throughout the build volume. As a result, this recently discovered processing route presents a new alloy design and production path that is synergistic between additive manufacturing and dispersion strengthening, possibly enabling a new generation of high-performance alloys.

Tim Smith↗