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NASA NTRS · 20210010437

SMD Technology Highlights

Florence Wee Ming Tan
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Abstract

Six technology highlights from the Science Mission Directorate (SMD) Heliophysics, Astrophysics, Earth, and Biological and Physical Sciences divisions. Technologies featured include 1. the 1653 m2 Solar Cruiser Solar Sail Propulsion system to enable missions to reach novel and otherwise difficult or impossible destinations for observing the Sun. 2. Technology sponsored by NASA and developed by MIT Space Nanotechnology Lab is developing high-performance space instrumentation for more powerful future X-ray telescopes that will study the dynamics of the high-energy universe. 3. Active thermal control technology that will help enable large ultra-stable telescopes needed to detect and characterize Earth-like planets around other stars. 4. SMD sponsored high-performance infrared sensors with reduced requirements for cooling onboard satellites and these sensors could potentially be flown on small satellite platforms like CubeSats. 5. A new technology that will utilize electron beams/ultraviolet light to remove dust that could help protect future space assets and astronauts from dangerous effects that arise from Moon/Mars dust exposure. 6. Studies using model organisms on ISS to understand the impact of the spaceflight environment on organisms in preparation for long-duration missions.

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solar sailspace weathersunlight pressurepolyimidescompositesx-ray astronomyx-ray mirrorx-ray diffraction gratingcritical-angle transmission gratingstress-based figure correctionthin-film stressthermal oxideChandraLynxArcusthermal controlspace telescopesexoplanet scienceinfrared radiationfocal plane arraybarrier infrared detectorshigh operating temperaturemetasurfaceflat lensdigital focal planesdust mitigationelectrostatic dust charginglunar surface explorationelectron beamspectrummodel organismsgene expressionfluorescent imagingISS life science research

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Florence Wee Ming Tan. 2021-02-21. SMD Technology Highlights. https://ntrs.nasa.gov/citations/20210010437

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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.

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