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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 685 records · Page 38

Versatile Nuclear Thermal Propulsion (NTP)

A study was initiated to investigate propulsion stage and mission architecture options potentially enabled by fission energy. One initial concept is a versatile Nuclear Thermal Propulsion (NTP) system with a maximum specific impulse of 900 s and a maximum thrust (per engine) of 15 klbf. The system assumes a monopropellant stage (hydrogen), and is designed to also provide 300 lbf of thrust (potentially split between multiple thrusters) at an Isp > 500 s for orbital maneuvering and station keeping. Boost pumps are used to assist with engine decay heat removal and low thrust engine burns, and to compensate for partial tank depressurization during full thrust engine burns. Potential stage assembly orbits that take full advantage of launch vehicle payload mass and volume capabilities are being assessed. The potential for using NTP engines to also generate a small to moderate amount of electrical power is also being evaluated. A first generation versatile NTP stage could enable 8 of 9 upcoming opportunities for short (less than 24 month) round trip human missions to Mars. A second generation versatile NTP is under consideration that could potentially provide a maximum specific impulse of 1800 s at 15 klbf, and enable ambitious missions throughout the solar system. The second generation NTP system under consideration would also allow a choice of volatiles to be used as propellant. This would potentially allow in-situ resources such as water, ammonia, methane, or other compounds to be used directly as propellant by the second generation engine.

Houts, Michael G.↗

Versatile Nuclear Thermal Propulsion (NTP)

A study was initiated to investigate propulsion stage and mission architecture options potentially enabled by fission energy. One initial concept is a versatile Nuclear Thermal Propulsion (NTP) system with a maximum specific impulse of 900 s and a maximum thrust (per engine) of 15 klbf. The system assumes a monopropellant stage (hydrogen), and is designed to also provide 300 lbf of thrust (potentially split between multiple thrusters) at an Isp > 500 s for orbital maneuvering and station keeping. Boost pumps are used to assist with engine decay heat removal and low thrust engine burns, and to compensate for partial tank depressurization during full thrust engine burns. Potential stage assembly orbits that take full advantage of launch vehicle payload mass and volume capabilities are being assessed. The potential for using NTP engines to also generate a small to moderate amount of electrical power is also being evaluated. A first generation versatile NTP stage could enable 8 of 9 upcoming opportunities for short (less than 24 month) round trip human missions to Mars. A second generation versatile NTP is under consideration that could potentially provide a maximum specific impulse of 1800 s at 15 klbf, and enable ambitious missions throughout the solar system. The second generation NTP system under consideration would also allow a choice of volatiles to be used as propellant. This would potentially allow in-situ resources such as water, ammonia, methane, or other compounds to be used directly as propellant by the second generation engine.

Houts, Mike↗

Cost Breakeven Analysis of Lunar ISRU for Human Lunar Surface Architectures

The return of humans to the lunar surface encompasses a range of possible architectures from brief Apollo-like sorties to long-term sustainment of human presence. Any architecture in this span requires propellant for the crew’s ascent from the lunar surface, as well as consumables to support their presence on the Moon. Oxygen and hydrogen are candidates for the propellant for the ascent vehicle due to their high specific impulse and potential for production from lunar resources and also constitute important consumables for the crew. Thus, the production of oxygen and/or hydrogen from lunar resources could significantly reduce the mass that must be sent from Earth to enable future human lunar missions. To assess the merits of using lunar resources, the costs associated with developing, producing, launching, operating, and maintaining those systems must be considered relative to the costs of delivering the needed resources from Earth. The demand for those resources depends upon the nature of the lunar mission, while the costs of both Earth-derived and lunar-derived resources depend on the performance requirements and technology capabilities associated with each approach. Thus, determining which approach is more cost efficient requires modeling the performance and cost of the associated systems as well as the range of possible architectures over which such a determination might apply. This research proposes a model that parametrically captures the factors influencing the relevant costs of providing propellant and crew consumables on the lunar surface from Earth and from the Moon. Two ISRU system models are assessed relative to propellant delivery from Earth. In this model, lunar ISRU breaks even with propellant delivery from Earth at high propellant demands and mission durations with multi-year ISRU system lifetimes; however, the costs of developing the necessary technologies to support a highly reliable and autonomous lunar ISRU system were not included.

ISRU↗

Science of the Moon

Science of the Moon discusses the present state of knowledge of the Moon, as well as the scientific questions remaining about the Moon's history and current attributes. This chapter covers events in lunar history, the geology of the Moon, properties and modification of the lunar regolith, the effects of radiation on the lunar surface, volatiles including those in the lunar Permanently Shadowed Regions, as well as the lunar seismic environment and what it indicates about the lunar interior. The chapter also lists instruments that, when deployed on the Moon or utilized in a lunar sample analysis facility in a lunar base, contribute to knowledge of the Moon. Presented within the chapter are unanswered questions regarding cratering on the lunar surface, the transition from bedrock to regolith, lunar tectonism, the crustal structure and composition of the Moon, reserve potential for in-situ resources, and the nature of the volatiles on the Moon.

Lunar science, Moon, geology, geophysics↗

Cold Season Performance of the NU-WRF Regional Climate Model in the Great Lakes Region

As Earth’s largest collection of freshwater, the Laurentian Great Lakes have enormous ecological and socio-economic value. Their basin has become a regional hotspot of climatic and limnological change, potentially threatening its vital natural resources. Consequentially, there is a need to assess the current state of climate models regarding their performance across the Great Lakes region and develop the next generation of high-resolution regional climate models to address complex limnological processes and lake-atmosphere interactions. In response to this need, the current paper focuses on the generation and analysis of a 20-member ensemble of 3-km National Aeronautics and Space Administration (NASA)-Unified Weather Research and Forecasting (NU-WRF) simulations for the 2014-2015 cold season. The study aims to identify the model’s strengths and weaknesses; optimal configuration for the region; and the impacts of different physics parameterizations, coupling to a 1D lake model, time-variant lake-surface temperatures, and spectral nudging. Several key biases are identified in the cold-season simulations for the Great Lakes region, including an atmospheric cold bias that is amplified by coupling to a 1D lake model but diminished by applying the Community Atmosphere Model radiation scheme and Morrison microphysics scheme; an excess precipitation bias; anomalously early initiation of fall lake turnover and subsequent cold lake bias; excessive and overly persistent lake ice cover; and insufficient evaporation over Lakes Superior and Huron. The research team is currently addressing these key limitations by coupling NU-WRF to a 3D lake model in support of the next generation of regional climate models for the critical Great Lakes Basin.

Michael Notaro↗

Compact Electric Bi-Directional Pulley Actuator

While significant work has been dedicated to the study of potential uses of in situ resources once mined, the methods to mine the raw materials has not been fully explored. This paper presents the first attempt at producing a drop in replacement for hydraulic cylinders on heavy construction equipment with an electromechanical actuator utilizing pulleys for the conversion of a single motor’s rotational motion to bidirectional linear motion. By utilizing a twin block and tackle arrangement and paired spools, the system can generate bidirectional motion nearly identical to a hydraulic cylinder. More importantly, the use of rope builds in shock resistance to the system which is often a weak point for screw style actuators. Significant work remains to refine the concept into flight hardware, but the concept shows promise. The produced actuator can be applied or scaled for near direct replacement of hydraulic cylinders on terrestrial mining and construction equipment for faster development of off Earth use.

Kevin Peterson↗

Forecasting with the GEOS-CF System and Other NASA Resources to Support Air Quality Management

Air quality (AQ) is a major and growing concern for public health around the world. Economic development, population growth, and climate change are all expected to exacerbate already poor AQ in many regions. Furthermore, AQ is often only sparsely monitored with reference-grade in-situ instruments. NASA resources and products have the potential to help in addressing this AQ data gap. The GEOS-CF (Goddard Earth Observing System – Composition Forecasting) global atmospheric composition modeling system is run each day at a global scale to provide recent estimates and five-day forecasts at hourly temporal resolution of atmospheric constituents relevant to AQ. NASA satellite missions (along with those of other space agencies) provide remotely-sensed estimates of atmospheric composition relevant to AQ. This paper gives a brief overview of these capabilities, and outlines the efforts underway to combine model forecasts, satellite retrievals, and surface-based measurements to provide more comprehensive and accurate estimates and forecasts of local AQ which will be broadly applicable and accessible globally.

GEOS-CF↗

Forecasting with the GESO-CF System and Other NASA Resources to Support Air Quality Management

Air quality (AQ) is a major and growing concern for public health around the world. Economic development, population growth, and climate change are all expected to exacerbate already poor AQ in many regions. Further-more, AQ is often only sparsely monitored with reference-grade in-situ instruments. NASA resources and products have the potential to help in addressing this AQ data gap. The GEOS-CF (Goddard Earth Observing System –Composition Forecasting) global atmospheric composition modeling system is run each day at a global scale to provide recent estimates and five-day forecasts at hourly temporal resolution of atmospheric constituents relevant to AQ. NASA satellite missions (along with those of other space agencies) provide remotely-sensed estimates of atmospheric composition relevant to AQ. This paper gives a brief over-view of these capabilities, and outlines the efforts underway to combine model forecasts, satellite retrievals, and surface-based measurements to provide more comprehensive and accurate estimates and forecasts of local AQ which will be broadly applicable and accessible globally.

Forecasting↗

GeoBridge: Connecting Communities to Geothermal Information and Opportunities: Preprint

The geothermal community is well established with long-standing events, organizations, and tools that are known across the geothermal community. But many of these tools and resources are located behind pay walls, require memberships, or are otherwise difficult to find, especially for people looking to join the geothermal community. These barriers to access can prevent outsiders from discovering valuable geothermal resources, limiting the geothermal community's potential for collaboration with other communities, such as clean energy entrepreneurs looking to expand into geothermal energy. The Department of Energy's (DOE) GeoBridge serves to bring these communities together by acting as a single, publicly accessible, searchable portal that facilitates easy access to available geothermal knowledge and information. It works to expand and diversify the pool of geothermal stakeholders by providing in-roads to geothermal information and community resources. It helps build a stronger geothermal community; one inclusive of individuals and groups from a variety of different backgrounds, including potential investors and start-up companies looking to accelerate innovation in geothermal technologies. By linking communities to geothermal information, analysis and expertise, GeoBridge serves as a launch point, directing interested parties to existing data and tools, events, educational resources, STEM programs, permitting and regulatory information, and other resources that can be used to evaluate, promote, and discover geothermal opportunities.

access↗

GeoBridge: Connecting Communities to Geothermal Information and Opportunities

The geothermal community is well established with long-standing events, organizations, and tools that are known across the geothermal community. But many of these tools and resources are located behind pay walls, require memberships, or are otherwise difficult to find, especially for people looking to join the geothermal community. These barriers to access can prevent outsiders from discovering valuable geothermal resources, limiting the geothermal community's potential for collaboration with other communities, such as clean energy entrepreneurs looking to expand into geothermal energy. The Department of Energy's (DOE) GeoBridge serves to bring these communities together by acting as a single, publicly accessible, searchable portal that facilitates easy access to available geothermal knowledge and information. It works to expand and diversify the pool of geothermal stakeholders by providing in-roads to geothermal information and community resources. It helps build a stronger geothermal community; one inclusive of individuals and groups from a variety of different backgrounds, including potential investors and start-up companies looking to accelerate innovation in geothermal technologies. By linking communities to geothermal information, analysis and expertise, GeoBridge serves as a launch point, directing interested parties to existing data and tools, events, educational resources, STEM programs, permitting and regulatory information, and other resources that can be used to evaluate, promote, and discover geothermal opportunities.

access↗

Addressing Regulatory Challenges to Tribal Solar Deployment: Key Findings

Tribal land in the United States represents approximately 2% of the country's total landmass and holds more than 5% of solar photovoltaic potential (Doris, Lopez, and Beckley 2013). This resource is largely untapped. Many Tribes note that regulatory challenges often are roadblocks to taking advantage of solar potential. This report serves as a summary of a larger project, Addressing Regulatory Challenges to Tribal Solar Deployment. The project seeks to unlock some of this potential by bringing Tribal, regulatory, utility, and other stakeholders together to articulate key barriers to Tribal solar adoption and develop replicable solutions. By increasing institutional capacity and developing frameworks, trainings, and a technical document repository for regulatory bodies, utilities, and Tribes, this project can help expand an emerging market.

14 SOLAR ENERGY↗

FORCE Development Status Update: Vertical Integration and Benchmarking of System Dynamics

Recent efforts to establish effective models for grid energy analysis, especially given the increase in variable renewable energy (VRE) sources and the economic challenges faced by traditional nuclear energy, have generated new technological considerations. One effort to improve the economic viability of nuclear power involves investigating integrated energy systems (IES) which include secondary energy systems that introduce flexibility and secondary market possibilities to existing and perceived future nuclear energy generation technologies. To analyze the technical and economic potential of IES, the Framework for Optimization of Resources and Economics (FORCE) tool suite was developed through a collaboration among national laboratories. Within the FORCE tool suite, the Holistic Energy Resource Optimization Network (HERON) provides algorithms for analyzing the long-term viability of potential IES technologies, while HYBRID provides algorithms and models to achieve high-resolution analysis of coupling physics over a short time period. Continued maturing of the FORCE tool suite requires further interconnections between the various tools in the suite in order to ensure consistent analysis. Analyses performed by applying HYBRID to transient process modeling should be easily harvestable as inputs to HERON analyses. The first item in this status update is a demonstration of an automated data pipeline for loading data from HYBRID into HERON analyses. Application of HYBRID results to HERON, as part of using the FORCE tool suite, relies on robust modeling assumptions for the various models included in HYBRID. The second result of this status update is the benchmarking and validation of cost and operational data, with a particular focus on natural gas energy generators. These generators are benchmarked with a focus on contrasting them with proposed thermal energy storage (TES) technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The primary goals of this project are identifying hidden geothermal resources in the USA and designing profitable enhanced geothermal systems (EGS). Many non-obvious processes and parameters could characterize geothermal resources and could control the ultimate energy potential of geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize geothermal resources, but this data is sparse and multi-scale that has hindered attempts to leverage the datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) give promise to overcome these issues. Modern ML methods and tools can (1) analyze large datasets, (2) assimilate model ensembles that include a multitude of inputs and outputs, (3) process sparse datasets, (4) perform transfer learning between sites with different data quality, (5) extract hidden geothermal signatures from field and simulation data, (6) label geothermal resources and processes, (7) identify highvalue data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies.

58 GEOSCIENCES↗

Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The primary goals of this project are identifying hidden geothermal resources in the USA and designing profitable enhanced geothermal systems (EGS). Many non-obvious processes and parameters could characterize geothermal resources and could control the ultimate energy potential of geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize geothermal resources, but this data is sparse and multi-scale. This has hindered attempts to leverage the datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) give promise to overcome these issues. Modern ML methods and tools can (1) analyze large datasets, (2) assimilate model ensembles that include a multitude of inputs and outputs, (3) process sparse datasets, (4) perform transfer learning between sites with different data quality, (5) extract hidden geothermal signatures from field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. In this work, we implement ML-based geothermal exploration and an enhanced geothermal systems (EGS) design tool to achieve the above goals. Our exploration tool is GeoThermalCloud (GTC) EGS design tool is GeoDT-ML. GTC (github.com/SmartTensors/GeoThermalCloud.jl) utilizes a LANL unsupervised ML platform called SmartTensors (https://tensors.lanl.gov/) to automate data analyses and interpretations by extracting hidden signatures to identify geothermal prospects. It enables the identification of critical measurements needed to identify geothermal resource signatures. GeoDT-ML (github.com/SmartTensors/GeoThermalCloud.jl/tree/master/) adds coupling to GeoDT (https://github.com/GeoDesignTool/GeoDT.git) for stochastic EGS design optimization and performance prediction. GeoDT-ML leverages recent advances in deep learning and high-performance computing. Contributors to this effort include LANL, PNNL, Google, Stanford, and Julia Computing.

15 GEOTHERMAL ENERGY↗

Balancing Water Sustainability and Productivity Objectives in Microalgae Cultivation: Siting Open Ponds by Considering Seasonal Water-Stress Impact Using AWARE-US

Microalgae have great potential as an energy crop. Scaling-up algal biofuel production in the United States (US) should be done with careful attention to water stress. This study evaluates the regional and seasonal water-stress impact of potential algae-pond deployments in the US. Three site-selection strategies focusing on biomass yield, water-use efficiency (WUE), and water-stress impact, respectively, are applied and compared to meet a US algae biomass production target of 30 million metric tons/yr ash-free dry weight, which converts to 20.8 billion L renewable diesel, via hydrothermal liquefaction. Ranking algae ponds based on biomass yield leads to freshwater consumption of 2.66 km3/yr, resulting in the highest water-stress impact (39.1 US equivalent km3). Under the WUE scenario, water consumption is reduced by 81%, but biomass yield is reduced by 12%. In contrast, adding a water-stress constraint to the biomass-yield ranking reduces water consumption by 50% and water-stress impact by 97%, with a small yield reduction (1.7%). Results show that pond location has a significant effect on water stress and that water stress is not proportional to water consumption or yield. Furthermore, capturing seasonal water patterns is critical for planning because sites in water-abundant regions can have short-term but significant water-stress impacts.

algae, Biofuel, water scarcity footprint, hydrothe↗

LiDAR Measurements to Investigate Farm-to-Farm Interactions at the AWAKEN Experiment

The exponential growth of wind energy and the need to exploit wind resources over areas with higher energy potential have led to the construction of neighboring wind turbines and farms with relatively small separation distances. As a result, for specific wind and atmospheric conditions, the wakes generated by an upstream wind farm may affect wind resources available for a downstream wind farm resulting in detrimental impacts on energy harvesting and structural loads for the downwind wind turbines. Distances between neighboring wind farms are typically larger than those associated with intra-wind-farm wake interactions, generating cumulative wakes whose characteristics might differ from those predicted through classical engineering wake models. These phenomena are referred to as farm-to-farm interactions. A better understanding and characterization of farm-to-farm interactions is one of the science goals tackled by the ongoing American WAKE experimeNt (AWAKEN). The site under investigation for this field campaign comprises two large wind farms in northern Oklahoma, USA, which are spaced roughly 5km apart along the prevailing South-North wind direction. To investigate possible interactions between these two wind farms, the WindFluX mobile LiDAR station has been deployed mainly to perform volumetric scans over their gap region. In this paper, preliminary results from these LiDAR volumetric scans will be discussed, specifically for a case with multiple wind turbine wakes evolving during the occurrence of a low-level jet.

17 WIND ENERGY↗

Ground data systems resource allocation process

The Ground Data Systems Resource Allocation Process at the Jet Propulsion Laboratory provides medium- and long-range planning for the use of Deep Space Network and Mission Control and Computing Center resources in support of NASA's deep space missions and Earth-based science. Resources consist of radio antenna complexes and associated data processing and control computer networks. A semi-automated system was developed that allows operations personnel to interactively generate, edit, and revise allocation plans spanning periods of up to ten years (as opposed to only two or three weeks under the manual system) based on the relative merit of mission events. It also enhances scientific data return. A software system known as the Resource Allocation and Planning Helper (RALPH) merges the conventional methods of operations research, rule-based knowledge engineering, and advanced data base structures. RALPH employs a generic, highly modular architecture capable of solving a wide variety of scheduling and resource sequencing problems. The rule-based RALPH system has saved significant labor in resource allocation. Its successful use affirms the importance of establishing and applying event priorities based on scientific merit, and the benefit of continuity in planning provided by knowledge-based engineering. The RALPH system exhibits a strong potential for minimizing development cycles of resource and payload planning systems throughout NASA and the private sector.

Berner, Carol A.↗

Addressing Regulatory Challenges to Tribal Solar Deployment: Preprint

Although Tribal land represents more than 5% of the solar photovoltaic technical potential in the United States, this resource is largely untapped due to a range of barriers, including complex project economics, Tribal technical and human resource capacity, project funding and financing obstacles, and regulatory challenges. To identify and better understand the regulatory barriers, the National Renewable Energy Laboratory (NREL) and the Midwest Tribal Energy Resources Association (MTERA) engaged Tribes, utilities, and regulators. Funded by the U.S. Department of Energy, the 3-year effort seeks to address regulatory challenges or barriers that affect Tribal solar projects differently - specifically or disproportionately because they are located on Tribal lands. This paper, largely excerpted from a comprehensive (draft) guidebook released by NREL and MTERA, provides an overview of 13 key regulatory barriers identified through this research, as well as potential short- and long-term solutions. In addition, the paper points to potential pathways for addressing key barriers through case studies highlighting successful Tribal solar projects along with considerations for stakeholders working with Tribes. These resources can support stakeholders in creating meaningful relationships and pursuing workable solar projects.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗