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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Lunar base siting

As with any planetary body, the lunar surface is quite heterogeneous. There are widely dispersed sites of particular interest for known and potential resource availability, selenology, and lunar observatories. Discriminating characteristics include solar illumination, view of earth, local topography, engineering properties of the regolith and certain geological features, and local mineralogy and petrology. Space vehicle arrival and departure trajectories constitute a minor consideration. Over time, a variety of base sites will be developed serving different purposes. Resource-driven sites may see the fastest growth during the first decades of lunar development, but selection of the most favorable sites is likely to be driven by suitability for a combination of activities. As on earth, later development may be driven by geographical advantages of surface transportation routes. With the availability of near-constant sunlight for power generation, as well as permanently shadowed areas at cryogenic temperatures, polar sites are attractive because they require substantially less earth-launched mass and lower equipment complexity for an initial permanent base. Discovery of accessible volatiles reservoirs, either in the form of polar permafrost or gas reservoirs at other locations, would dramatically increase the attractiveness of any site from a logistical support and selenological point of view. Amid such speculation, no reliable evidence of such volatiles exist. More reliable evidence exists for areas of certain mineral concentrations, such as ilmenite, which could form a feedstock for some proposed resource extraction schemes. While tentative selections of advantageous base sites are made, new data from lunar polar orbiters and the Galileo polar flybys would be very helpful.

Staehle, Robert L.↗
NASA NTRS1997

Using Common Graphics Paradigms Implemented in a Java Applet to Represent Complex Scheduling Requirements

The experiments planned for the International Space Station promise to be complex, lengthy and diverse. The scarcity of the space station resources will cause significant competition for resources between experiments. The scheduling job facing the Space Station mission planning software requires a concise and comprehensive description of the experiments' requirements (to ensure a valid schedule) and a good description of the experiments' flexibility (to effectively utilize available resources). In addition, the continuous operation of the station, the wide geographic dispersion of station users, and the budgetary pressure to reduce operations manpower make a low-cost solution mandatory. A graphical representation of the scheduling requirements for station payloads implemented via an Internet-based application promises to be an elegant solution that addresses all of these issues. The graphical representation of experiment requirements permits a station user to describe his experiment by defining "activities" and "sequences of activities". Activities define the resource requirements (with alternatives) and other quantitative constraints of tasks to be performed. Activities definitions use an "outline" graphics paradigm. Sequences define the time relationships between activities. Sequences may also define time relationships with activities of other payloads or space station systems. Sequences of activities are described by a "network" graphics paradigm. The bulk of this paper will describe the graphical approach to representing requirements and provide examples that show the ease and clarity with which complex requirements can be represented. A Java applet, to run in a web browser, is being developed to support the graphical representation of payload scheduling requirements. Implementing the entry and editing of requirements via the web solves the problems introduced by the geographic dispersion of users. Reducing manpower is accomplished by developing a concise representation which eliminates the misunderstanding possible with verbose representations and which captures the complete requirements and flexibility of the experiments.

Jaap, John↗
NASA NTRS2010

Creating Methane from Plastic: Recycling at a Lunar Outpost

The high cost of re-supply from Earth demands resources to be utilized to the fullest extent for exploration missions. The ability to refuel on the lunar surface would reduce the vehicle mass during launch and provide excess payload capability. Recycling is a key technology that maximizes the available resources by converting waste products into useful commodities. One example of this is to convert crew member waste such as plastic packaging, food scraps, and human waste into fuel. This process thermally degrades plastic in the presence of oxygen producing CO2 and CO. The CO2 and CO are then reacted with hydrogen over catalyst (Sabatier reaction) producing methane. An end-to-end laboratory-scale system has been designed and built to produce methane from plastic, in this case polyethylene. This first generation system yields 12-16% CH4 by weight of plastic used.

Santiago-Maldonado, Edgardo↗
DOE OSTI2016

Leveraging Federal Renewable Energy Tax Credits

State and local governments have a limited window of opportunity to leverage recently-extended federal tax credits to accelerate the deployment of clean, renewable energy. Federal tax credits have played an important role in the rapid growth of the U.S. renewable energy industry. This DOE guide outlines the wide array of resources available to state and local governments interested in leveraging federal tax credits to accelerate the deployment of clean, renewable energy.

Modeling Tools, Financing, Clean Energy Planning, ↗
DOE OSTI2023

Multi-Agent Reinforcement Learning for Distribution System Critical Load Restoration

Grid resilience has become a critical topic recently because of the increasing occurrence of extreme events and the growing integration of intermittent renewable energy sources. To build a resilient distribution system, this paper develops a multiagent reinforcement learning-based (MARL) method to coordinate distribution energy resources (DERs) dispatch, load pickup, and network reconfiguration for load restoration after a system outage. With the help of two types of control agents, namely critical load restoration (CLR) and coordination (COR) agents, system loads can be restored efficiently, given available resources. The effectiveness and superiority of the proposed algorithm are demonstrated through simulations and comparative studies on a real distribution feeder in Western Colorado.

distribution system↗
DOE OSTI2026

Impacts of Regional Coordination on Transmission Needs for Power System Resource Adequacy [Slides]

Resource adequacy (RA) is an important component of bulk power system reliability that addresses whether there are sufficient resources available to meet electricity demand at all times. RA analysis is used to assess whether the planned power system will provide reliable electricity to consumers while accounting for equipment outages, weather variability, and load uncertainty. Coordination between regions can enable resource sharing to meet RA needs if sufficient transmission capacity exists. Transmission's role in RA coordination can be particularly pronounced for large power systems like the U.S. electricity grid which contains geographically diverse demand and weather-dependent resources. Depending on the level of coordination desired, existing inter-regional transmission capacity may not be sufficient. This study is designed to assess optimal pathways for the development of inter-regional transmission in the U.S. under varying levels of RA coordination. Results can inform long-term grid infrastructure planning and provide insights into potential benefits of greater coordination for generation and transmission planning between regional U.S. power systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Multi-Agent Reinforcement Learning for Distribution System Critical Load Restoration: Preprint

Grid resilience has become a critical topic recently because of the increasing occurrence of extreme events and the growing integration of intermittent renewable energy sources. To build a resilient distribution system, this paper develops a multi-agent reinforcement learning-based (MARL) method to coordinate distribution energy resources (DERs) dispatch, load pickup, and network reconfiguration for load restoration after a system outage. With the help of two types of control agents, namely critical load restoration (CLR) and coordination (COR) agents, system loads can be restored efficiently, given available resources. The effectiveness and superiority of the proposed algorithm are demonstrated through simulations and comparative studies on a real distribution feeder in Western Colorado.

distribution system↗
DOE OSTI2015

EERE Resources for Graduate Students

The Office of Energy Efficiency and Renewable Energy (EERE) at the U.S. Department of Energy (DOE) has a number of resources available for graduate students, including research positions, internships, and career-planning information to help you navigate the education-to-employment pathway in energy.

Graduate, Energy, Resources, Education, Teaching, ↗
DOE OSTI2017

SFCOMPO-2.0: An OECD NEA database of spent nuclear fuel isotopic assays, reactor design specifications, and operating data

SFCOMPO-2.0 is the new release of the Organisation for Economic Co-operation and Development (OECD) Nuclear Energy Agency (NEA) database of experimental assay measurements. These measurements are isotopic concentrations from destructive radiochemical analyses of spent nuclear fuel (SNF) samples. We supplement the measurements with design information for the fuel assembly and fuel rod from which each sample was taken, as well as with relevant information on operating conditions and characteristics of the host reactors. These data are necessary for modeling and simulation of the isotopic evolution of the fuel during irradiation. SFCOMPO-2.0 has been developed and is maintained by the OECD NEA under the guidance of the Expert Group on Assay Data of Spent Nuclear Fuel (EGADSNF), which is part of the NEA Working Party on Nuclear Criticality Safety (WPNCS). Significant efforts aimed at establishing a thorough, reliable, publicly available resource for code validation and safety applications have led to the capture and standardization of experimental data from 750 SNF samples from more than 40 reactors. These efforts have resulted in the creation of the SFCOMPO-2.0 database, which is publicly available from the NEA Data Bank. Our paper describes the new database, and applications of SFCOMPO-2.0 for computer code validation, integral nuclear data benchmarking, and uncertainty analysis in nuclear waste package analysis are briefly illustrated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Mission Analysis for Marine Renewable Energy to Provide Power for Marine Carbon Dioxide Removal

The mission of this project was to provide a preliminary feasibility assessment of powering different marine carbon dioxide removal (mCDR), marine carbon capture, and marine carbon sequestration strategies with marine energy. In this report, carbon capture refers to methods that can separate or capture carbon dioxide (CO 2 ) from the air or ocean; carbon sequestration refers to methods that store CO 2 obtained by capture methods out of the atmosphere for long periods of time; and carbon dioxide removal (CDR) refers to methods that do both. The project found that mCDR powered by marine energy and offshore wind energy available in the United States could meet global CDR scales needed by 2040 and 2050 to limit warming to 1.5 degrees C by 2100. Note that this preliminary estimate assumes that it is possible to harvest all the marine and offshore wind resources available in the United States with existing technology options, and it does not account for the power needed for monitoring these methods, as these power needs are not yet well defined and require further research. Additionally, these CDR scales will still require emissions reductions.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

A cross-dimensional analysis of data-driven short-term load forecasting methods with large-scale smart meter data

Electricity load forecasting is essential to utility operation and power grid stability. A wide spectrum of data-driven methods, ranging from linear regression models to more recent deep learning models have been adopted to forecast electric load over the years. However, there still lacks a holistic evaluation of the applicability of conventional statistical and machine learning based algorithms with respect to different temporal and spatial scopes, computational requirements, and sensitivity of model-tuning. Enabled by a large-scale electricity load profile dataset of over 40,000 residential customers in a utility region, we conducted a cross-dimensional analysis of data-driven load forecasting methods. Three regression-based and seven deep learning algorithms with different model configurations were evaluated in terms of their overall and peak load prediction accuracy, and training burdens, across spatial aggregation levels ranging from the transformer, feeder, substation, to neighborhood. We found, first, the load forecasting accuracy is constrained by a predictability boundary, influenced by the forecasting horizon and spatial aggregation level. Specifically, RandomForest, XGBoost, TFT, TSMixer, and TiDE models achieved less than 10 % prediction error for up to 96-h ahead forecasting for district, substation, and feeder levels, while other models struggle at long-horizon predictions; Second, for winter and summer peak load dates, most models were able to predict the peak demand timing within ± 1 h, but the prediction percentage error varied by models, with TFT and TiDE models being the top performers; Third, models with similar prediction accuracy can differ in training burden by an order of magnitude. Therefore, choosing model configurations that balance prediction performance and computational resource is an important practical consideration for large-scale deployment of the machine learning based load forecasting. The outcome of this study can guide researchers and practitioners to choose the proper load forecasting algorithms based on their problem scope, required accuracy, and available resources. The predictability boundary can serve as a benchmark for electricity load forecasting problems with new algorithms and datasets.

Li, Han↗
DOE OSTI2018

Tiered Approach to Resilience Assessment

Regulatory agencies have long adopted a three-tier structure for risk assessment and risk management. We build on this structure to propose a tiered approach for resilience assessment that can be integrated in the existing regulatory processes. Comprehensive approaches to assessing resilience at appropriate and operational scales, reconciling analytical complexity as needed with stakeholder needs and resources available, and ultimately creating actionable recommendations to enhance resilience is still lacking. Our proposed structure consists of tiers by which analysts can scale a resilience assessment and associated management actions relative to the scope and urgency of the risk and the capacity of resource managers to improve system resilience. We use an application of water allocation decisions in the Platte River Basin, Nebraska, USA to illustrate this approach.

Sustainability, natural resources management, disa↗
DOE OSTI2022

ADROC: An Emulation Experimentation Platform for Advancing Resilience of Control Systems

Cyberattacks against industrial control systems have increased over the last decade, making it more critical than ever for system owners to have the tools necessary to understand the cyber resilience of their systems. However, existing tools are often qualitative, subject matter expertise-driven, or highly generic, making thorough, data-driven cyber resilience analysis challenging. The ADROC project proposed to develop a platform to enable efficient, repeatable, data-driven cyber resilience analysis for cyber-physical systems. The approach consists of two phases of modeling: computationally efficient math modeling and high-fidelity emulations. The first phase allows for scenarios of low concern to be quickly filtered out, conserving resources available for analysis. The second phase supports more detailed scenario analysis, which is more predictive of real-world systems. Data extracted from experiments is used to calculate cyber resilience metrics. ADROC then ranks scenarios based on these metrics, enabling prioritization of system resources to improve cyber resilience.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2006

Technology Assessment in Support of the Presidential Vision for Space Exploration

This paper discusses the process and results of technology assessment in support of the United States Vision for Space Exploration of the Moon, Mars and Beyond. The paper begins by reviewing the Presidential Vision: a major endeavor in building systems of systems. It discusses why we wish to return to the Moon, and the exploration architecture for getting there safely, sustaining a presence, and safely returning. Next, a methodology for optimal technology investment is proposed with discussion of inputs including a capability hierarchy, mission importance weightings, available resource profiles as a function of time, likelihoods of development success, and an objective function. A temporal optimization formulation is offered, and the investment recommendations presented along with sensitivity analyses. Key questions addressed are sensitivity of budget allocations to cost uncertainties, reduction in available budget levels, and shifting funding within constraints imposed by mission timeline.

technology↗
DOE OSTI2019

Impact of Atmospheric Rivers on Surface Hydrological Processes in Western U.S. Watersheds

Atmospheric rivers (ARs) can significantly modulate surface hydrological processes through the extreme precipitation they produce. Previously, studies have investigated the impact of ARs on individual hydrological processes, but a comprehensive evaluation of ARs’ impact on surface hydrology is lacking. This study used a high-resolution regional climate simulation to quantify the impact of ARs on surface hydrological processes across the western U.S. watersheds. The model performance is evaluated through extensive comparison against observations. Our analysis indicates that ARs produce heavy precipitation but suppress evapotranspiration. Snowpack ablates more during ARs, which is mainly driven by warmer air temperature and increased downward longwave radiation. At the 0oC to 10oC temperature range, ARs increase the probability of snow ablation from 0.33 to 0.57. Soil moisture responds similarly to AR and non-AR precipitation events. The runoff-to-precipitation ratio almost doubles due to modulation by heavy precipitation in the southwestern watersheds or intensification of snow ablation in the northwestern watersheds during AR events compared to non-AR events. From analysis of the relationship between the hydrological responses and different meteorological factors, precipitation, temperature and radiation were identified as the key drivers that distinguish the hydrologic responses between AR and non-AR events. Lastly, analysis of ARs and total runoff at annual scale and April 1st snowpack and winter precipitation shows that ARs explain 30% to 60% of the interannual variance and sharpen the seasonality of water resources availability in the west coast mountain watersheds.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Open Vehicle Sketch Pad Aircraft Modeling Strategies

Geometric modeling of aircraft during the Conceptual design phase is very different from that needed for the Preliminary or Detailed design phases. The Conceptual design phase is characterized by the rapid, multi-disciplinary analysis of many design variables by a small engineering team. The designer must walk a line between fidelity and productivity, picking tools and methods with the appropriate balance of characteristics to achieve the goals of the study, while staying within the available resources. Identifying geometric details that are important, and those that are not, is critical to making modeling and methodology choices. This is true for both the low-order analysis methods traditionally used in Conceptual design as well as the highest-order analyses available. This paper will highlight some of Conceptual design's characteristics that drive the designer s choices as well as modeling examples for several aircraft configurations using the open source version of the Vehicle Sketch Pad (Open VSP) aircraft Conceptual design geometry modeler.

Hahn, Andrew S.↗
DOE OSTI2020

Facility Location Optimization Model for COVID-19 Resources

In response to anticipated resource shortfalls related to the treatment and testing of COVID-19, many communities are planning to build additional facilities to increase capacity. These facilities include field hospitals, testing centers, mobile manufacturing units, and distribution centers. In many cases, these facilities are intended to be temporary and are designed to meet an immediate need. When deciding where to place new facilities many factors need to be considered, including the feasibility of potential locations, existing resource availability, anticipated demand, and accessibility between patients and the new facility. In this project, a facility location optimization model was developed to integrate these key pieces of information to help decision makers identify the best place, or places, to build a facility to meet anticipated resource demands. The facility location optimization model uses the location of existing resources and the anticipated resource demand at each location to minimize the distance a patient must travel to get to the resource they need. The optimization formulation is presented below. The model was designed to operate at the county scale, where patients are grouped per county. This assumption can be modified to integrate other scales or include individual patients.

60 APPLIED LIFE SCIENCES↗