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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Toward Hall MHD Power Generation and Drag Augmentation Using a Coaxial-Electrode Configuration During Hypersonic Entry

Planetary EDL requires that a spacecraft must reduce its relative velocity from multiple km/s to zero for safe landing. The entry phase requires slowing down through an intense hypersonic flight regime (Mach 25 to Mach 5). Magnetohydrodynamics (MHD) is a next-generation concept with a wide untapped set of technologies that can expand planetary exploration capabilities and create more robust entry vehicles by utilizing in-situ resources, increasing control authority, and reducing heat flux. There is therefore a need for an experimentally validated simulation tool for MHD technologies in hypersonic entry.

MHD drag↗
NASA NTRS2024

GCAS Visualization Codebase Augmentation Migration to Modern Standards and Feature Enhancements

The Glenn Research Center Communication Analysis Suite (GCAS) includes many analysis tools that can be used to support a wide range of scenarios. It includes a visualization tool that implements the three.js graphics library to display a three-dimensional (3D) representation of its results. This software will enable researchers, engineers, and mission planners to interact intuitively with and understand the results of their analyses, which might not be apparent from raw data. With NASA’s efforts to return humans to the Moon as a part of the Artemis missions, the GCAS has been used extensively for lunar terrain and landing system development analysis, which is vital to ensuring mission achievability and safety. This has created the need to add several significant features to the visualization tool, such as the ability to display the terrain of the lunar surface accurately and to provide information demonstrating how a given region might impact mission objectives. Many of the changes made to the visualization tool can be separated into one of three general advancements: code restructuring to adhere to modern coding standards and practices, new user camera controls for first-person and third-person perspective views, and a terrain generation feature to enable rendering highly accurate terrains based on any celestial body’s digital elevation model (DEM) in GeoTIFF format. These improvements notably elevate the visualization tool's functionality, accuracy, and user interaction while providing a robust foundation for future development.

Visualization↗
NASA NTRS2023

Public Health Data Applications Using the CDC Tracking Network: Augmenting Environmental Hazard Information with Lower-latency NASA Data

Exposure to environmental hazards is an important determinant of health, and the frequency and severity of exposures is expected to be impacted by climate change. Through a partnership with the U.S. National Aeronautics and Space Administration, the U.S. Centers for Disease Control and Prevention’s National Environmental Public Health Tracking Network is integrating timely observations and model data of priority environmental hazards into its publicly accessible Data Explorer (https://ephtracking.cdc.gov/DataExplorer/). Newly integrated datasets over the contiguous U.S. (CONUS) include: daily 5-day forecasts of air quality based on the Goddard Earth Observing System Composition Forecast (GEOS-CF), daily historical (1980-present) concentrations of speciated PM2.5 based on the Modern Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), and Moderate Resolution Imaging Spectroradiometer (MODIS) daily near real-time maps of flooding (MCDWD). Data integrated into the CDC Tracking Network are broadly intended to improve community health through action by informing both research and early warning activities, including (1) describing temporal and spatial trends in disease and potential environmental exposures, (2) identifying populations most affected, (3) generating hypotheses about associations between health and environmental exposures, and (4) developing, guiding, and assessing environmental public health policies and interventions aimed at reducing or eliminating health outcomes associated with environmental factors.

air quality↗
NASA NTRSDate not supplied

COBRA-DDP: Trajectory Generation and Collision Avoidance Augmentations for eVTOL Vehicles

This paper presents a receding horizon model predictive control variation of the combined Bernstein polynomial optimal reciprocal collision avoidance (ORCA) differential dynamic programming (COBRA-DDP) algorithm for AAM vehicles. Collision avoidance in combination with effective trajectory replanning are expected to be core components of AAM vehicles operating within a crowded airspace. This environment necessitates the use of real-time trajectory planning algorithms that are capable of planning around large amounts of stationary and moving obstacles. Previous work on COBRA-DDP demonstrated the capability of the algorithm to produce dynamically feasible trajectories for AAM vehicles and general collision avoidance. This paper improves upon the previous work by increasing the number of stationary and moving obstacles, implementing a variation of COBRA-DDP that lends itself to real-time application. These advancements are demonstrated on a vertical takeoff and landing (VTOL) vehicle simulation with highly nonlinear vehicle dynamics.

COBRA-DDP↗
NASA NTRSDate not supplied

Optimization of Airport Runway Configuration with Forecast-Augmented Offline Reinforcement Learning

Runway configuration Management (RCM) governs the optimal utilization of runways based on variables such as traffic and meteorological conditions, making it a daunting task in air traffic management due to its dependency on volatile operational and environmental factors. This paper improves upon our previous work [1] on using offline model-free reinforcement learning for creating a Runway Configuration Assistance (RCA) decision-support tool. A novel integration of forecast data from LAMP (Localized Aviation Model Output Statistics Program) and TAF (Terminal Area Forecast) is introduced, enhancing the tool’s accuracy and also its adaptability to quick wind changes. The performance is evaluated using two major US airports, Charlotte Douglas International Airport (CLT) and Denver International Airport (DEN). To counter scalability issues presented by the addition of discrete forecast variables, we transitioned to a continuous state space model, ensuring scalability and inclusion of longer forecast data. The results of our experiments reflect significant improvements in the RCA tool’s prediction accuracy.

Sumanth Nethi↗
NASA NTRSDate not supplied

COBRA-DDP: Trajectory Generation and Collision Avoidance Augmentations for eVTOL Vehicles

This paper presents a receding horizon model predictive control variation of the combined Bernstein polynomial optimal reciprocal collision avoidance (ORCA) differential dynamic programming (COBRA-DDP) algorithm for AAM vehicles. Collision avoidance in combination with effective trajectory replanning are expected to be core components of AAM vehicles operating within a crowded airspace. This environment necessitates the use of real-time trajectory planning algorithms that are capable of planning around large amounts of stationary and moving obstacles. Previous work on COBRA-DDP demonstrated the capability of the algorithm to produce dynamically feasible trajectories for AAM vehicles and general collision avoidance. This paper improves upon the previous work by increasing the number of stationary and moving obstacles, implementing a variation of COBRA-DDP that lends itself to real-time application. These advancements are demonstrated on a vertical takeoff and landing (VTOL) vehicle simulation with highly nonlinear vehicle dynamics.

COBRA-DDP↗
NASA NTRS2024

Augmentation of Seed Film Technology With Probiotics in Support of Space Crop Production

This project set out to establish a method for introducing Plant Growth Promoting Microbes to seed film for use in a flight-based crop production system. The inoculation method, demonstrated in this paper, succeeded in this introduction while simultaneously avoiding disrupting the integrity of the seed film material. Future research should continue to explore the idea of growth production and crop protection via intentional introduction of an exophytic microbiome including the verification of effects of varying inoculum concentrations on mature plants. Positive effects are more likely to be noted when multiple organisms are introduced simultaneously. Additional benefit is likely to be seen on an experimental basis when crops are challenged via the introduction of both biotic and abiotic stressors.

Aubrie E Orourke↗
NASA NTRS2024

Augmenting RANS Turbulence Models Guided by Field Inversion and Machine Learning

This report investigates the use of a data-driven approach, viz., Field Inversion and Machine Learning (FIML), to improve conventional RANS turbulence models like the Spalart-Allmaras model and the Menter SST k-ω model. One of the crucial aspects of using an ML-based approach with limited training data to produce corrections that are generalizable to a large range of flow configurations is to design appropriate “features” (inputs to the ML model). A model, based on guidance from the FIML methodology, is presented in analytical form. An additional list of potential features is provided. Although these were not used in the present correction, they were considered in the course of its development, and are included to fully document the complete process employed in the present work.

turbulence modeling↗