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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 271 records · Page 15

Spacecraft Charging as an Asset to Interplanetary Small Spacecraft

Small spacecraft operate on a far more limited power budget than their larger counterparts, a problem compounded for interplanetary spacecraft in the outer solar system. The reduced solar flux beyond Earth’s orbit makes solar panels less effective for spacecraft exploring the gas giants and they are susceptible to damage by intense radiation belts. Radioisotope thermoelectric generators are expensive and bulky compared to their power output. Interplanetary small satellite missions benefit from both alternative energy sources and low-power electronics to power their buses and scientific payloads. Traditionally, spacecraft engineers treat the space environment as a hazard, but it nevertheless offers a potential solution. Currents from space plasmas charge spacecraft to high potentials and can cause electrical arcing to occur between differentially charged surfaces. The spacecraft can harvest a small amount of power —<10 mW/m2at Jupiter — from the electric field between these surfaces to do useful work, either by charging a battery or directly powering an instrument or actuator. While using the energy directly has limited use due to the low electron density and temperature of most space plasmas, it can nevertheless be used in situations where solar panels are not desirable, such as high radiation environments. Two applications — a Langmuir probe and an attitude control actuator — exploit the disparate current-voltage characteristics between surfaces with different material properties and require minimal input power to operate.

spacecraft charging↗

Solving The Space Weather Problem: A 15+ Year Roadmap to Revolutionize Space Weather Research, Protect NASA Space Assets, and Enable Robust Operations

The White Paper (WP) describes a roadmap to address the Space Weather (SpWx) problem. It presents a strategic vision of how a community-wide effort could be organized and implemented to enable transformative advancement in SpWx research and ultimately, in applications. We envision a ‘system-of-systems’—an integrated web of SpWx stations and state-ofthe-art modeling facilities to enable a transformative advance in SpWx nowcasting and forecasting (Figure 1). The Space Weather Aggregated Network of Systems (SWANS) will enable space situational awareness for end-users invested in spaceflight operations, infrastructure risk mitigation, and future human endeavors in space exploration while profoundly transforming Heliophysics research.

A Vourrlidas↗

Power Beaming From Lunar Orbit to Small Lunar Science Assets

Long lunar nights limit science lander lifetimes to only two weeks in most global locations unless they carry large batteries or radioisotopes. An orbiting beamed power spacecraft is another option to provide this energy, thus removing the energy storage burden on the lander while still giving it years of science operations.

Lunar↗

Flight Test Exploration of Integrated Wildfire Response Operations with Crewed and Uncrewed Air Assets

Since 2016, Japan Aerospace Exploration Agency (JAXA) and NASA have partnered to investigate the safe and efficient integration of uncrewed aircraft systems (UAS) in disaster relief operations. Current disaster response operations would benefit from the use of UAS but are limited by the need for safe airspace integration technologies and enabling regulations. The work presented in this paper focuses on the safe integration of UAS and helicopters in active wildfire disaster response operations. The authors propose the use of mission planning and traffic management technologies, including onboard pilot situation awareness support technologies, to coordinate airspace operations between crewed and uncrewed aircraft (e.g., UAS). A representative wildfire scenario including a helicopter and UAS was developed. The helicopter mission included a flight path that mimicked the siphoning of water from a natural water reservoir (lake) and a subsequent water drop over vegetation along the progressing edge of a fire perimeter. Simulated UAS were assumed to conduct aerial ignition flights in the vicinity as part of a controlled burn of the vegetation ahead of the fire front to create a natural barrier between the fire and a nearby populated area. A situation awareness tool was developed and used to support the helicopter pilots’ task to stay clear of the volume of airspace where the UAS was conducting its operation while efficiently conducting the fire suppression mission. A flight test using JAXA’s experimental helicopter was conducted in August 2022 to validate the developed technology. The advantages of the developed technology were demonstrated, and pilot feedback confirmed that real-time awareness of the UAS operation airspace helped the flight planning and execution of a safe mission that minimized the flight time loss due to the potential interference with the UAS. Post-flight interviews with the pilots indicated no sufficient increase in the pilots’ workload and provided ideas for future technology development. Future research will provide recommendations to standards development organizations to support considerations for crewed-uncrewed interactions in disaster-response operations.

disaster response↗

Flight Test Exploration of Integrated Wildfire Response Operations with Crewed and Uncrewed Air Assets

Since 2016, JAXA and NASA have partnered to investigate the safe and efficient integration of unmanned aircraft systems (UAS) in disaster response operations. Through the collaboration, supporting systems from the respective agencies have been successfully integrated and demonstrated in multiple activities ranging from localized simulations and flight tests to large-scale national disaster drills. This paper describes findings from the most recent flight test by JAXA using a crewed helicopter conducting wildfire response operations in proximity to an area in which simulated small UAS, supported by UTM services, were conducting prescribed burn operations.

disaster response↗

Determining Optimal Asset Location for Rapid and Efficient Wildfire Suppression: A Simulation-Based Approach

The impact of wildfire incidents has been growing in recent years, posing a serious threat to communities at the urban-wildland interface. To address this problem, there have been growing calls to use UAVs to increase the capacity of responsible agencies to quickly and effectively suppress fires and to reduce risks associated with firefighting. One of the opportunities associated with UAVs is the ability to rapidly and autonomously operate from limited-access air bases where fires are expected to burn. This study provides an approach to determine where these air bases should be placed in order to most rapidly extinguish fires, given provided fuel distributions. This approach uses an integrated simulation of fire propagation and UAV-based suppression actions to determine how much of a given environment was burned over a range of scenarios. It then uses an optimization method to explore the space and determine the location with the least burned area. Results show the approach to efficiently and effectively provide optimal bases for single-base placements over a range of scenarios, though future work is required to adequately calibrate the model and study how it can be used in multiple-base placement problems.

Daniel Hulse↗

Determining Optimal Asset Location for Rapid and Efficient Wildfire Suppression: A Simulation-Based Approach

The impact of wildfire incidents has been growing in recent years, posing a serious threat to communities at the urban-wildland interface. To address this problem, there have been growing calls to use UAVs to increase the capacity of responsible agencies to quickly and effectively suppress fires and to reduce risks associated with firefighting. One of the opportunities associated with UAVs is the ability to rapidly and autonomously operate from limited-access air bases where fires are expected to burn. This study provides an approach to determine where these air bases should be placed in order to most rapidly extinguish fires, given provided fuel distributions. This approach uses an integrated simulation of fire propagation and UAV-based suppression actions to determine how much of a given environment was burned over a range of scenarios. It then uses an optimization method to explore the space and determine the location with the least burned area. Results show the approach to efficiently and effectively provide optimal bases for single-base placements over a range of scenarios, though future work is required to adequately calibrate the model and study how it can be used in multiple-base placement problems.

Daniel Hulse↗

Machine Learning and Economic Models to Enable Risk-Informed Condition Based Maintenance of a Nuclear Plant Asset

The primary objective of this research is to address challenges in the implementation of risk-informed, condition-based predictive maintenance (PdM), which reduces operating costs while still maintaining the safety and reliability of commercial nuclear power plants (NPPs). To achieve the objective, risk models are being developed by taking advantage of advancements in data analytics, deep learning, machine learning (ML), and artificial intelligence (AI). The notable outcomes presented in the report include ? Development of a ML models using heterogeneous plant process and vibration data collected at different spatial and temporal resolutions from the Salem?s CWS to diagnose a circulating water pump (CWP) failure based on salient fault signatures. The developed diagnostic models are extendable to other faults associated with CWPs and CWP motors given associated fault signatures. ? Development of a natural language processing (NLP) technique to automatically classify the WO data into different categories. The developed NLP technique was validated on independent WO data. This automates the tedious and time-consuming activity of mining and classifying WOs by subject matter experts. ? Estimation of mean time between downtime (i.e., time duration between time instances when 1 or more CWPs are not available) and developed an approach to establish reliability of CWS components using unstructured WO data along with CWS plant process data. ? Formulation of economic model based on Markov chain models. The parameters of associated with the transition rate between different states of Markov chain models were estimated using WO data. The economic model formulation and discussion captures both time-independent and time-dependent parameter variation, leading to risk-informed decision-making.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗