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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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41 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

A Machine Learning Model for Solar Sail Shape Reconstruction Using Flight Data

Solar sail deformation leads to disturbance torques from solar radiation pressure, driving performance requirements for momentum management systems. For the Solar Cruiser technology demonstrator mission, we have developed a model leveraging neural network-based machine learning to derive sail shape characteristics. The model uses torque and attitude telemetry simulated from a reduced-order tensor model of the deformed sail mesh over a characterization sequence. The machine learning model predicts sail boom deflection with comparable accuracy to that of an onboard context camera. This model can discover sail shape with no additional mass or data downlink requirements, allowing for validation of sail force modeling assumptions using in flight data. The results from the project hold promise for the further implementation of machine learning techniques in solar sail telemetry analysis and control.

solar sail↗
NASA NTRSDate not supplied

A Machine Learning Model for Solar Sail Shape Reconstruction Using Flight Data

Solar sail deformation leads to disturbance torques from solar radiation pressure, driving performance requirements for momentum management systems. For the Solar Cruiser technology demonstrator mission, we have developed a model leveraging neural network-based machine learning to derive sail shape characteristics. The model uses torque and attitude telemetry simulated from a reduced-order tensor model of the deformed sail mesh over a characterization sequence. The machine learning model predicts sail boom deflection with comparable accuracy to that of an onboard context camera. This model can discover sail shape with no additional mass or data downlink requirements, allowing for validation of sail force modeling assumptions using in flight data. The results from the project hold promise for the further implementation of machine learning techniques in solar sail telemetry analysis and control.

solar sail↗
NASA NTRS2021

Design of Solar Sailing Trajectories Resilient to Safe Mode Events

Solar sails are an enabling technology for stand-alone small-satellite deep-space exploration. However, their always-on nature, combined with the time of flight required for deep-space missions, makes them particularly susceptible to safe mode events. Unlike missions using electric propulsion, exclusively solar sail- ing missions cannot carry extra propellant to make up for a safe mode event, and more powerful methods like expected availability cannot be directly applied. This work extends the expected availability and duty cycle approaches to solar sailing. Through an application to NASA’s Solar Cruiser mission, a 46 % increase in tra- jectory resilience is obtained at negligible change in the mission’s time of flight. Additionally, it is shown that when a safe mode event stops the spacecraft from reaching its target orbit, the developed methods reduce the expected final error by approximately an order of magnitude.

Johnson, Les↗
NASA NTRSDate not supplied

Gravity Offloading and Analysis of Long Imperfection-Sensitive Elements (GOALIE)

Use of large-scale deployable structures (e.g., iROSA) can enable space exploration and science missions (e.g., ACS3, Solar Cruiser). Numerical models predicting behavior of deployable structures in microgravity are difficult to validate because ground testing of long, slender, and flexible booms is challenging due to the influence of Earth’s gravity. The GOALIE team is collecting data for model validation through experimental testing to increase confidence in numerical models. Redwire, Inc. provided a subscale (7 m) and a full-scale (30 m) Triangular, Rollable, and Collapsible (TRAC) boom to use for test development. Other boom designs may be tested in the future.

Composites↗