SEARCH · Engineering Papers
Results for “FUSION”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
A Historic Review: Nuclear Fusion Space Propulsion Research, Experimentation, Theory Development, and Systems Analysis Efforts Led by the NASA Glenn Research Center (1994-2004)
Explore the source record for details and available documents.
SLS Aerodynamics: Progress Toward Fusion of CFD and Wind Tunnel Data
Explore the source record for details and available documents.
Adaptive Multi-Sensor Localization Information Fusion for Autonomous Urban Air Mobility Operations
An adaptive method is developed to iteratively fuse the information provided by multiple sensors to enable autonomous urban air mobility type operations. First, noisy and bias corrupted IMU readings are processed as soon as they arrive using kinematic equations represented in the vehicle's body frame. To correct the systems drift resulting from the integration, an information content measure is introduced to decide on the environment. For the cluttered environment the information provided by environmental sensors is counted as reliable and the drift correction as accurate. For the open space, the GPS data is counted as reliable, and the drift correction is done based on the GPS readings. The measurement noise effects are minimize using Iterated Extended Kalman Filter framework. The algorithm is implemented in the in-house developed FlightDeckz simulation environment using an IMU model, simulated video recorded from a camera mounted on the vehicle (for the purpose of this study, outside scenery was generated with XPlane), which flies in an urban environment, and GPS data generated from the environment's digital map.
Adaptive Multi-Sensor Localization Information Fusion For Autonomous Urban Air Mobility Operations
Explore the source record for details and available documents.
Fusion of SAR and TM Data for Quantitative Estimation of Forest Variables Over an Extended Range of Validity
Near-simultaneous AIRSAR and Landsat TM data are used, along with radar scattering models and optical regression-based models, to estimate vegetation variables for a mixed old-growth dense forest in the US Pacific Northwest.
Bayesian Fusion of Color and Texture Segmentations
A common method for texture representation is to use the marginal probability densities over the outputs of a set of multi-orientation, multi-scale filters as a description of the texture.
Bayesian Fusion of TRMM Passive and Active Measurements
A Beyasian method was adopted to combine the instantaneous measurements of the Tropical Rainfall Measureing Mission (TRMM)'s rada and radiometer ([4]).
CIF Report - Information Fusion and Data Analytics for Human Lunar Exploration
This project leverages the Concept Exploration Laboratory (CEL) to collect, warehouse, and augment data relevant to human lunar exploration as a platform for NA (S&MA) to develop operational data integration techniques. The project capitalizes on 16+ years of CEL experience applied to NASA, DoD, the City of Houston, the State of Texas, and private industry. The integrated data will be utilized in the two scenarios described in a definition of concept for development of a full scale data analysis suite and storage solution, useful to all JSC organizations engaged in real time operations and safety tasks, and may be useful as pathfinders for the Digital Transformation Program.
Information Fusion & Analytics for Human Lunar Exploration
Explore the source record for details and available documents.
Graphical User Interfaces for Laser Powder Bed Fusion Additive Manufacturing
Explore the source record for details and available documents.
Graphical User Interfaces for Laser Powder Bed Fusion Additive Manufacturing
Explore the source record for details and available documents.
Scaleup of Microwave Powder Bed Fusion for Lunar Infrastructure Construction
NASA and its partners are seeking to establish a sustainable and permanent presence on the Moon. Like explorers on Earth, making use of natural resources upon arrival at the destination will be paramount. In-situ resource utilization of the lunar regolith will enable efficient construction of lunar infrastructure. Transforming the granular regolith into a solid can be achieved in many ways. One method is to use microwave energy to sinter the regolith into various structures. The lunar regolith has a low thermal conductivity, but microwaves can volumetrically heat it to bind the granular particles together in an energy efficient manner. One concept that is being developed and evaluated to sinter the regolith into infrastructure uses the Moon’s surface as a powder bed. Regolith would be added to the sintered lunar structure to build up layers to create structures such as landing pads, blast shields, roads, etc. Microwave systems, concept of operations, and sintering protocols are being developed to create a sub-element structure targeted for a lunar demonstration mission.
Influence of High-Intensity Ultrasound on Ti-6Al-4V Microstructure During Laser Powder Bed Fusion Solidification Conditions
Explore the source record for details and available documents.
Molten Salt Lattice Confinement Fusion (LCF) Fast Fission Reactor for Lunar and Planetary Surface Power
Explore the source record for details and available documents.
NASA Satellites and Data Fusion: A Case Study with Coral Reefs
As the world is experiencing a significant rise in both AI, Climate, and Space start-up companies, we are in a new wave of limitless innovation. NASA's statutory responsibility is to "provide for the widest practicable and appropriate dissemination of information concerning its activities and the results thereof." (51 U.S.C. § 20112) In particular, through machine learning, the public data drawn from NASA’s space assets can provide insights for addressing climate-related problems here on Earth. And many climate start-up companies can benefit from leveraging this data, either for proof of concepts or their own missions. In the Fall of 2021, several scientists from NASA and Coral Vita led a Practicum with the Georgia Institute of Technology Masters in Data Analytics program. The Practicum saw two teams of students develop and implement machine learning models to infer, from CALIPSO satellite imagery, vitality properties upon satellite pass. This kind of capability can lead to real-time mapping of coral health around the world, giving organization an understanding of where to prioritize reef reconstitution.. In this presentation, we will highlight this use case and discuss other concrete applications in which space data is used to solve problems here on Earth.
Multi-Path Fusion: A Hierarchical Machine Learning Approach for Combining Diverse Data Sets for A Forest Monitoring New Observing System
Explore the source record for details and available documents.