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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 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
NASA NTRS2026

Simulating the Lunar Thermal Environment for the Surface-Deployed LEMS Artemis III TVAC Test

The Lunar Environment Monitoring Station (LEMS) is an autonomous, survive-the lunar-night seismic suite to be deployed on the Lunar surface by the Artemis III crew and designed to operate continuously for two years. It will see the extremes of the Lunar south pole thermal environment where surface temperatures range from -200°C to +20°C and where nighttime duration is at least 354 hours. Given power and mass constraints, the thermal system is limited to 2.5 Watts of heat during the lunar night. Presented is the system thermal vacuum test plan and configuration to validate the thermal control system performance in a flight-like environment. The test will measure the nighttime heat leaks for the bus and 18 seismometers to ensure lunar night survival and operability.

Thermal↗
NASA NTRSDate not supplied

Harness Thermal Heat Loss Measurement for a Lunar Surface-Deployed LEMS Artemis III Payload

The Lunar Environment Monitoring Station (LEMS) is an autonomous, survive-the-lunar-night seismic suite to be deployed on the Lunar surface by the Artemis III crew and designed to operate continuously for two years. It will see the extremes of the Lunar south pole thermal environment where surface temperatures range from -200°C to +20°C and where nighttime duration is at least 354 hours. Given power and mass constraints, the thermal system is limited to 2.5 Watts of heat during the lunar night. The electrical harnessing named the Signal and Power Passthrough (SAPP) was designed to minimize heat loss while meeting power and signal integrity requirements. To mitigate risk due to uncertainty associated with the harnessing materials, routing, and tie-downs, a flight-like thermal conductance test was performed to measure the heat loss. The test methodology, results, and model correlation are presented.

TVAC↗
NASA NTRS2026

Simulating the Lunar Thermal Environment for the Surface-Deployed LEMS Artemis III TVAC Test

The Lunar Environment Monitoring Station (LEMS) is an autonomous, survive-the lunar-night seismic suite to be deployed on the Lunar surface by the Artemis III crew and designed to operate continuously for two years. It will see the extremes of the Lunar south pole thermal environment where surface temperatures range from -200°C to +20°C and where nighttime duration is at least 354 hours. Given power and mass constraints, the thermal system is limited to 2.5 Watts of heat during the lunar night. Presented is the system thermal vacuum test plan and configuration to validate the thermal control system performance in a flight-like environment. The test will measure the nighttime heat leaks for the bus and 18 seismometers to ensure lunar night survival and operability.

Thermal↗
NASA NTRSDate not supplied

Harness Thermal Heat Loss Measurement for A Lunar Surface-Deployed LEMS Artemis III Payload

The Lunar Environment Monitoring Station (LEMS) is an autonomous, survive-the-lunar-night seismic suite to be deployed on the Lunar surface by the Artemis III crew and designed to operate continuously for two years. It will see the extremes of the Lunar south pole thermal environment where surface temperatures range from -200°C to +20°C and where nighttime duration is at least 354 hours. Given power and mass constraints, the thermal system is limited to 2.5 Watts of heat during the lunar night. The electrical harnessing named the Signal and Power Passthrough (SAPP) was designed to minimize heat loss while meeting power and signal integrity requirements. To mitigate risk due to uncertainty associated with the harnessing materials, routing, and tie-downs, a flight-like thermal conductance test was performed to measure the heat loss. The test methodology, results, and model correlation are presented.

Thermal↗
NASA NTRSDate not supplied

Harness Thermal Heat Loss Measurement for A Lunar Surface-Deployed LEMS Artemis III Payload

The Lunar Environment Monitoring Station (LEMS) is an autonomous, survive-the-lunar-night seismic suite to be deployed on the Lunar surface by the Artemis III crew and designed to operate continuously for two years. It will see the extremes of the Lunar south pole thermal environment where surface temperatures range from -200°C to +20°C and where nighttime duration is at least 354 hours. Given power and mass constraints, the thermal system is limited to 2.5 Watts of heat during the lunar night. The electrical harnessing named the Signal and Power Passthrough (SAPP) was designed to minimize heat loss while meeting power and signal integrity requirements. To mitigate risk due to uncertainty associated with the harnessing materials, routing, and tie-downs, a flight-like thermal conductance test was performed to measure the heat loss. The test methodology, results, and model correlation are presented.

TVAC↗
NASA NTRS2026

Simulating the Lunar Thermal Environment for the Surface-Deployed LEMS Artemis III TVAC Test

The Lunar Environment Monitoring Station (LEMS) is an autonomous, survive-the lunar-night seismic suite to be deployed on the Lunar surface by the Artemis III crew and designed to operate continuously for two years. It will see the extremes of the Lunar south pole thermal environment where surface temperatures range from -200°C to +20°C and where nighttime duration is at least 354 hours. Given power and mass constraints, the thermal system is limited to 2.5 Watts of heat during the lunar night. Presented is the system thermal vacuum test plan and configuration to validate the thermal control system performance in a flight-like environment. The test will measure the nighttime heat leaks for the bus and 18 seismometers to ensure lunar night survival and operability.

TVAC↗
DOE OSTI2020

Fission Batteries: Definition, Key Attributes and Research and Development Needs

The term battery was first introduced by the American scientist and inventor Benjamin Franklin in 1749, followed by invention of the first true battery in 1800 by Alessandro Volta. Today, batteries are a ubiquitous source of portable electric power across different applications. Batteries are widely used across a range of scales from consumer products to grid-scale energy storage. There are different types of batteries, but they can be broadly classified as chemical or electric batteries [1], atomic batteries, nuclear batteries, tritium batteries or radioisotope generators [2, 3]. Atomic batteries, nuclear batteries, tritium batteries, and radioisotope generators have gained significant attention for applications requi-ing long-term power supply and high-power density, including the space power reactor [4]. While a number of reactor systems, particularly micro-reactors, are referred to as fission batteries, this paper defines key attributes required for a fission reactor to achieve capabilities comparable with the characteristics of batteries that enable their wide-spread use. Achieving this full vision of a fission battery will enable broad deployment of fission reactors that function like batteries. The research and development (R&D) activities needed to achieve the desired fission battery attributes are discussed below.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2025

Ensuring Safe, Effective, and Reliable Use of Artificial Intelligence-Based Applications for Nuclear Electricity Generation through a Systems Approach

There is a significant potential to reduce operating and maintenance cost at nuclear power plants using artificial intelligence (AI) and machine learning (ML). For instance, AI/ML has the potential to significant improve work management processes, condition reporting, and plant surveillance activities. However, the nuclear industry has been slow in adopting AI/ML due to several multifaceted barriers discussed in this paper. This work presents such multidisciplinary approach intended to 1) accelerate industry adoption of AI/ML-based applications at nuclear power plants and 2) ensure their safe, reliable, and effective use. This approach is discussed further in this work and will be used to address overarching challenges associated with AI deployment at scale to provide industry guidance that support accelerated adoption of AI/ML technologies throughout the industry.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Modeling a fast spectrum molten salt reactor in a systems dynamics fuel cycles code

Molten salt reactor (MSR) concepts are being actively developed by several private companies, with some touting the fuel cycle benefits of this technology. Simulating the deployment of MSRs and their effect on fuel cycle transitions is the role of a system dynamics fuel cycles tool. However, many current fuel cycles tools have difficulty modeling MSR isotopic variations because they were designed for modeling existing reactors based on discrete fuel elements with batch fueling schemes (i.e., charge and discharge). This work presents ORION fuel cycle modeling results using a specific high power density fast spectrum MSR design. For code verification, a single-stage MSR fuel cycle was set up in ORION and results were compared with the results from the SCALE-based reactor physics model (ChemTriton). A transition scenario was set up in ORION from the current light water reactor fleet to a future fleet of MSRs to study the characteristics of an MSR that affect its performance during transition. Several transition scenarios were set with holds and delays in place that are representative of a sodium fast reactor as modeled in Evaluation Group 23 for the Fuel Cycle Options Campaign Evaluation and Screening Study. Several MSR characteristics lend to its high performance and ease in transition from the current fuel cycle: fissile material is only loaded at initial startup; all fissile material is available as it is bred due to online fuel processing; and fissile material recirculating through the core is briefly held in tanks for processing and has very minimal out-of-core time (on the order of a minutes to a few days). These characteristics are in contrast to a solid-fueled reactor, which requires discharge, cooling, and fabrication of fuel all of which could take a few months to a few years and repeated loading of fresh fuel assemblies. In conclusion, a solid-fueled reactor only discharges a fraction of a core every year.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Demonstration of Essential Reliability Services by a 300-MW Solar Photovoltaic Power Plant

The California Independent System Operator (CAISO), First Solar, and the National Renewable Energy Laboratory (NREL) conducted a demonstration project on a large utility-scale photovoltaic (PV) power plant in California to test its ability to provide essential ancillary services to the electric grid. With increasing shares of solar- and wind-generated energy on the electric grid, traditional generation resources equipped with automatic governor control (AGC) and automatic voltage regulation controls -- specifically, fossil thermal -- are being displaced. The deployment of utility-scale, grid-friendly PV power plants that incorporate advanced capabilities to support grid stability and reliability is essential for the large-scale integration of PV generation into the electric power grid, among other technical requirements. A typical PV power plant consists of multiple power electronic inverters and can contribute to grid stability and reliability through sophisticated 'grid-friendly' controls. In this way, PV power plants can be used to mitigate the impact of variability on the grid, a role typically reserved for conventional generators. In August 2016, testing was completed on First Solar's 300-MW PV power plant, and a large amount of test data was produced and analyzed that demonstrates the ability of PV power plants to use grid-friendly controls to provide essential reliability services. These data showed how the development of advanced power controls can enable PV to become a provider of a wide range of grid services, including spinning reserves, load following, voltage support, ramping, frequency response, variability smoothing, and frequency regulation to power quality. Specifically, the tests conducted included various forms of active power control such as AGC and frequency regulation; droop response; and reactive power, voltage, and power factor controls. This project demonstrated that advanced power electronics and solar generation can be controlled to contribute to system-wide reliability. It was shown that the First Solar plant can provide essential reliability services related to different forms of active and reactive power controls, including plant participation in AGC, primary frequency control, ramp rate control, and voltage regulation. For AGC participation in particular, by comparing the PV plant testing results to the typical performance of individual conventional technologies, we showed that regulation accuracy by the PV plant is 24-30 points better than fast gas turbine technologies. The plant's ability to provide volt-ampere reactive control during periods of extremely low power generation was demonstrated as well. The project team developed a pioneering demonstration concept and test plan to show how various types of active and reactive power controls can leverage PV generation's value from being a simple variable energy resource to a resource that provides a wide range of ancillary services. With this project's approach to a holistic demonstration on an actual, large, utility-scale, operational PV power plant and dissemination of the obtained results, the team sought to close some gaps in perspectives that exist among various stakeholders in California and nationwide by providing real test data.

14 SOLAR ENERGY↗
DOE OSTI2023

Modeling Systems’ Disruption and Social Acceptance—A Proof-of-Concept Leveraging Reinforcement Learning

As the need for a just and equitable energy transition accelerates, disruptive clean energy technologies are becoming more visible to the public. Clean energy technologies, such as solar photovoltaics and wind power, can substantially contribute to a more sustainable world and have been around for decades. However, the fast pace at which they are projected to be deployed in the United States (US) and the world poses numerous technical and nontechnical challenges, such as in terms of their integration into the electricity grid, public opposition and competition for land use. For instance, as more land-based wind turbines are built across the US, contention risks may become more acute. This article presents a methodology based on reinforcement learning (RL) that minimizes contention risks and maximizes renewable energy production during siting decisions. As a proof-of-concept, the methodology is tested on a case study of wind turbine siting in Illinois during the 2022–2035 period. Results show that using RL halves potential delays due to contention compared to a random decision process. This approach could be further developed to study the acceptance of offshore wind projects or other clean energy technologies.

17 WIND ENERGY↗
NASA NTRS1990

Space segment configuration of the Canadian mobile satellite system

The performance requirements, the main parameters, and the configuration of the MSAT spacecraft are reviewed. The major features of the communications subsystem are discussed in some detail. Key technology items include the L-band Radio Frequency (RF) power amplifier which must operate with a high DC to RF power efficiency and generate low intermodulation when loaded with multi-carrier signals; and the large diameter deployable L-band antenna. The development status and expected performance of these spacecraft components is examined.

Bertenyi, Elemer↗
DOE OSTI2024

Measuring the robustness of predictive probability for early stopping in two-group comparisons

We report physical experiments are often expensive and time-consuming. Test engineers must certify the compatibility of aircraft and their weapon systems before they can be deployed in the field, but the testing required is time consuming, expensive, and resource limited. Adopting Bayesian adaptive designs is a promising way to borrow from the successes seen in the clinical trials domain. The use of predictive probability (PP) to stop testing early and make faster decisions is particularly appealing given the aforementioned constraints. Given the high-consequence nature of the tests performed in the national security space, a strong understanding of new methods is required before being deployed. Although PP has been thoroughly studied for binary data, there is less work with continuous data, where many reliability studies are interested in certifying the specification limits of components. A simulation study evaluating the robustness of this approach indicates early stopping based on PP is reasonably robust to minor assumption violations, especially when only a few interim analyses are conducted. The simulation study also compares PP to conditional power, showing its relative strengths and weaknesses. A post-hoc analysis exploring whether release requirements of a weapon system from an aircraft are within specification with desired reliability resulted in stopping the experiment early and saving 33% of the experimental runs.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2019

The Dragonfly Entry and Descent System

Dragonfly is a proposed New Frontiers class mission that will send a nuclear powered octocopter to the surface of Titan for an extended science mission. This presentation will provide an overview of the Entry and Descent system that is under development to ensure the save delivery of this unique "relocatable lander" to Titan. Titan's dense atmosphere, large atmospheric scale height, and low gravity allows for a slow-paced entry and descent sequence that lasts more than 100 minutes, as opposed to the "7 minutes of terror" that is charac-teristic of landed Mars missions. This slow pace al-lows for sufficient temporal separation between critical events of the EDL sequence to minimize overall risk.The Dragonfly entry and descent system is composed of high-heritage components, minimizing overall risk. The aeroshell will be a scaled Genesis Sample Return capsule with a diameter of 3.75 meters, built by Lock-heed Martin. The thermal protection system (TPS) is made up of Phenolic Impregnated Carbon Ablator-Domestic (PICA-D) on the heatshield, SLA-561V on the backshell, and SLA-220M on the aft cover and low gain antenna. Each material has extensive heritage for the chosen application. The spacecraft will enter Titan at a velocity of 7.3 km/s, resulting in a predicted fully margined stagnation point heating environment of 254 W/cm2 heat rate and 13 kJ/cm2 heat load, well within the tested limits of the chosen materials. The aeroheat-ing environments, including the significant contribu-tion of shock layer radiation from CN on both the heatshield and backshell, are evaluated using state of the art models and codes that have been validated with appropriate ground testing.Once the deceleration pulse is complete, a disk-gap-band (DGB) drogue parachute will be deployed at ap-proximately Mach 1.5 to stabilize and further deceler-ate the spacecraft. Due to the dense atmosphere, the spacecraft will spend more than 80 minutes on this parachute, until reaching an appropriate altitude to de-ploy the subsonic main parachute. The lander is re-leased after approximately 17 minutes on the main chute before releasing and transitioning to powered flight in order to navigate to its first landing site. The release of the lander from the backshell effectively ends the entry and descent portion of the mission.The full presentation will provide additional details about the design of the EDL system hardware, engi-neering design, and overall con-ops. Preliminary aero-thermal and TPS sizing analyses will be presented, and the parachute system will be described in greater detail. In addition, the Dragonfly spacecraft will carry an En-gineering Science Investigation (ESI) package designed to obtain engineering data during EDL that will be used to validate the design methodology for future missions. An overview of the proposed ESI package will also be presented.

EDL↗
NASA NTRS2016

Transitioning Autonomous Systems Technology Research to a Flight Software Environment

NASA has developed methods and algorithms for autonomous spacecraft operations,including automated planning and scheduling, fault diagnostics and impact determination,procedure management and display. Making the transition from technology research tooperational flight software requires overcoming significant technical, programmatic andcultural challenges. Technology research is aimed at developing methods that performspecific functions correctly, but the resulting software may not be designed for flightprocessors with limited CPU, memory and network resources, and may not be easilyintegrated into spacecraft flight software. Our objective in the Autonomous Systems andOperations Project is to make significant strides toward the transformation from technologyto operational use. Our focus was twofold: maturing research grade autonomy software intoa flight software environment using broadly accepted languages and tools; and integratingautonomy applications with each other and with representative systems and their data andcommand interfaces. For a target flight software environment, we chose Core FlightSoftware, developed by Goddard Space Flight Center as a common operating systemindependent framework. Our hardware integration environment was provided by theIntegrated Power and Avionics Systems (iPAS) Lab at Johnson Space Center, in whichvarious subsystem development has been conducted to address engineering challenges forthe vehicles and systems required for long-duration missions into the solar system. The iPASand its network of connected facilities provides realistic subsystem hardware or simulationsof spacecraft power, life support, guidance, navigation and control, and command and datahandling subsystems. Interfaces between autonomy applications and the subsystems beingassessed and controlled were developed, assessed and refined. The hardware and softwareenvironment using CFS and the iPAS facility has proven to be a highly flexible and realisticenvironment in which to rapidly integrate applications in an iterative, low cost setting. Usingthe integration environment we have developed, we will turn our focus to performance andsizing analysis to determine the computational requirements for full-scale deployment ofautonomy technology. Scalability of reasoners and the spacecraft models upon which theyoperate, and robustness across the full range of spacecraft conditions and environments willbe explored and improved. We are making significant contributions to the future programsthat will build the spacecraft that will take humans beyond the Earth-Moon system, in whichprogram Systems Engineers will be able to accurately and confidently design in accurate,robust and mature autonomous operations systems.

Flight Software↗
DOE OSTI2021

A Cyber-Physical System for Freeway Ramp Meter Signal Control Using Deep Reinforcement Learning in a Connected Environment

Freeway bottlenecks such as on-ramp merging areas account for about 40% of recurring freeway congestion. It is generally agreed that building more roads and adding more lanes to existing infrastructure does not solve the congestion problem, and so dynamic traffic control measures offer a more cost-effective alternative. Ramp meters, traffic signal devices that regulate traffic flow entering freeways, are among the most effective measures to mitigate congestion at on-ramp merging areas on freeways. The confluence of deep reinforcement learning (RL) and connectivity provides a possible solution to advance ramp meter signal control. Deep RL is a group of machine-learning methods that enables an agent learning from the environment to improve its performance. In this study, three deep RL methods-proximal policy optimization (PPO), Ape-X deep Q-network (DQN), and asynchronous advantage actor-critic agents (A3C)-are explored for ramp meter signal control to maximize vehicle speed and traffic throughput, as well as to minimize energy consumption and emissions at freeway on-ramp merging areas in a connected environment. The low computational requirement and scalability of deep RL for deployment make it a powerful optimization tool for time-sensitive applications such as ramp meter signal control. The results of this study show that deep RL methods yield superior performance to both a fixed-time controller and ALINE A, a state-of-the-art feedback controller.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗
DOE OSTI2025

Lessons Learned: Summary of Insights From the HERO WEC and Waves to Water Deployments Between 2022 and 2024

In 2020, a team from the National Renewable Energy Laboratory (NREL) partnered with the East Carolina University Coastal Studies Institute to develop a small, modular, wave-powered point absorber desalination prototype. That prototype, known as the hydraulic and electric reverse osmosis wave energy converter (HERO WEC), was intended to de-risk the installation activities planned for the Waves to Water Prize sponsored by the Water Power Technologies Office. The NREL team was given approximately 18 months to design, build, bench test, and deploy the HERO WEC prototype. Since the initial HERO WEC development, it has been used for two in-lab test programs and three ocean deployments. The first in-lab test program focused on ensuring that the overall operation of the device occurred as expected and on validating the operation of safety systems such as pressure relief valves or electrical breakers for load mitigation. The second in-lab test program was the first time the NREL team leveraged NREL’s large-amplitude motion platform to characterize the performance of the HERO WEC. Of the three in-water deployments, the first deployment was effectively an installation and recovery practice with no meaningful wave activity during the time that it was installed. The second deployment was a 2-week effort that enabled both the electric and hydraulic configurations of the device to be in the water for approximately 5 days each. This deployment was also the first time that the team had the opportunity to perform a drivetrain swap on the Coastal Studies Institute research vessel. The third deployment had to be split into two separate installations due to minor damage incurred from the WEC spinning during the initial installation. This report summarizes the deployments, the challenges encountered with each deployment, and the lessons learned for future work.

16 TIDAL AND WAVE POWER↗
NASA NTRS2016

International Space Station Lithium-Ion Battery

The International Space Station (ISS) primary Electric Power System (EPS) currently uses Nickel-Hydrogen (Ni-H2) batteries to store electrical energy. The electricity for the space station is generated by its solar arrays, which charge batteries during insolation for subsequent discharge during eclipse. The Ni-H2 batteries are designed to operate at a 35 depth of discharge (DOD) maximum during normal operation in a Low Earth Orbit. Since the oldest of the 48 Ni-H2 battery Orbital Replacement Units (ORUs) has been cycling since September 2006, these batteries are now approaching their end of useful life. In 2010, the ISS Program began the development of Lithium-Ion (Li-Ion) batteries to replace the Ni-H2 batteries and concurrently funded a Li-Ion ORU and cell life testing project. When deployed, they will be the largest Li-Ion batteries ever utilized for a human-rated spacecraft. This paper will include an overview of the ISS Li-Ion battery system architecture, the Li-Ion battery design and development, controls to limit potential hazards from the batteries, and the status of the Li-Ion cell and ORU life cycle testing.

battery↗