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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Hyperspectral Feature Detection Onboard the Earth Observing One Spacecraft using Superpixel Segmentation and Endmember Extraction

We present a demonstration of onboard hyperspectral image processing with the potential to reduce mission downlink requirements. The system detects spectral endmembers and then uses them to map units of surface material. This summarizes the content of the scene, reveals spectral anomalies warranting fast response, and reduces data volume by two orders of magnitude. We have integrated this system into the Autonomous Science craft Experiment for operational use onboard the Earth Observing One (EO-1) Spacecraft. The system does not require prior knowledge about spectra of interest. We report on a series of trial overflights in which identical spacecraft commands are effective for autonomous spectral discovery and mapping for varied target features, scenes and imaging conditions.

Superpixel Endmember Detection↗
NASA NTRS1994

A perspective on space robotics in Japan

This report summarizes the research and development status and perspective on space robotics in Japan. The R & D status emphasizes the current on-going projects at NASDA including the JEM Remote Manipulator System (JEMRMS) to be used on Space Station Freedom and the robotics experiments on Engineering Satellite 7 (ETS-7). As a future perspective, not only NASDA, but also ISAS and other government institutes have been promoting their own research in space robotics in order to support wide spread space activities in the future. Included in this future research is an autonomous satellite retrieval experiment, a dexterous robot experiment, an on-orbit servicing platform, an IVA robot, and several moon/planetary rovers proposed by NASDA or ISAS and other organizations.

Ohkami, Yoshiaki↗
NASA NTRS2024

Smallsat 2024 - Starling Cubesat Swarm Technology Demonstration Flight Results

The Starling swarm of four 6U CubeSats launched in July 2023 to test four key technologies to enable future swarm missions: 1) Mobile Ad-Hoc Networking (MANET) over a crosslink radio network 2) Autonomous onboard decision-making for operations 3) Optical-based absolute and relative navigation 4) Autonomous maneuver planning and execution The Starling team implemented the Better Approach to Mobile Ad-hoc Networking (B.A.T.M.A.N.) protocol to automatically manage the crosslink network of four satellites. The B.A.T.M.A.N. protocol uses a decentralized approach to managing a multi-hop mesh network of devices, in this case, a satellite swarm. The four satellites were able to successfully establish a network at multiple data rates and demonstrate file transfer and command issuance between spacecraft over the network. Starling incorporated Distributed Spacecraft Autonomy's (DSA) software to demonstrate onboard decision-making. The DSA software takes L1/L2 band GPS measurements and uses them to estimate the relative Total Electron Count (TEC) in the ionosphere. The onboard software then determines if there are any features of interest and provides that information to the other satellites over the crosslink network. The swarm of satellites then reaches a consensus on the optimal TEC observation strategy and adjusts its measurement collection tactics autonomously. The Starling Formation-Flying Optical Experiment (StarFOX), produced by Stanford's Space Rendezvous Laboratory, uses the onboard star trackers to collect images of the other swarm spacecraft and produce angles-only navigation estimates. This system is envisioned to be valuable in applications in which Global Navigation Satellite Systems (GNSS) are not available, such as in cis-lunar or deep space. StarFOX successfully applied its algorithms to multiple simultaneous spacecraft targets using the star tracker imagery. Finally, Starling used Emergent Space's Cluster Flight Application (CFA) software suite for the Reconfiguration and Orbit Maintenance Experiments Onboard (ROMEO) demonstration of autonomously planning and executing propulsive maneuvers. Large swarms will need to be able to maintain formation requirements with minimal operator involvement, especially as the size of the swarm scales up. Results from the ROMEO experiment are presented. Starling is funded by the Small Spacecraft Technology (SST) program out of NASA's Space Technology Mission Directorate (STMD).

distributed systems↗
NASA NTRS1997

On-Orbit Measurement of the Superconductive Transition Temperatures of YBa2Cu3O(7-x) Thick Films

Thick film superconductors were integrated into hybrid circuits and tested in the Materials In Devices As Superconductors (MIDAS) spaceflight experiment which operated autonomously aboard the MIR space station for 90 days. MIDAS was designed to cool the circuits from 300 to 75K, maintain the temperature at 75K for 28 days, and warm the circuits back to 300K. This cycle was performed a total of three times, during which the superconductive transition temperature was measured during each cool-down and warm-up portion of the experiment. All of the thick films used in this experiment exhibited superconductive transition temperatures of approximately 87K, and no significant differences in the resistance versus temperature properties of the materials were observed among the data collected during pre-flight, flight, and post-flight operations.

Hooker, Matthew W.↗
NASA NTRSDate not supplied

Celestial Navigation in Cislunar Space with autoNGC

Celestial navigation (CelNav) is a source of navigation observables where images of known solar system bodies are used to locate a spacecraft, beneficial within the solar system for both cislunar and deep space missions. CelNav provides a variety of design benefits to support and enable current and new autonomous space operations- using only a camera and a processor to produce in-situ measurements for navigation. This technology reduces subscription to ground-based tracking during all phases of a mission, freeing up resources for other operational needs. This also supports secure navigation since it eliminates the need for ground contact. CelNav enables missions where the light time delay between Earth and the spacecraft is too long (or the Earth to spacecraft line of sight is obscured) to support critical operations. It also enables smaller mission classes, where Deep Space Network (DSN)time is cost prohibitive, to reduce its cost by focusing primarily on data downlink. Finally, it enables the NASA Artemis program and other cislunar human space flight by providing redundant navigation to traditional radiometric tracking. In this presentation, we discuss the implementation of a CelNav app in autonomous Navigation, Guidance, and Control (autoNGC), a comprehensive flight software suite for onboard autonomy that is built on the core Flight System (cFS). The presentation also summarizes the results of flight software-in-the-loop (SIL) and processor-in-the-loop (PIL) demonstrations. Both are high-fidelity simulations with the use of a camera emulator hosted on a GPU server that simulates images that would be captured by the camera. The CelNav app leverages the use of cGIANT (cFS Goddard Image Analysis and Navigation Tool).Previously developed for the autoNGC software suite, cGIANT is an onboard autonomous image processing and optical navigation (OpNav) tool that performs limb-based OpNav and Terrain Relative Navigation. The added CelNav capability of cGIANT generates bearing measurements to multiple known celestial bodies (planets, moons, asteroids, comets, etc.) in monocular (2D) images. These observables are then fed to the Goddard Enhanced Onboard Navigation System (GEONS)navigation filter app, enabling us to navigate the spacecraft autonomously. In early 2025, the autoNGC CelNav capability is planned to be flight tested as part of the onboard autonomy experiment on the Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment(CAPSTONE) spacecraft that is currently in a Lunar Near Rectilinear Halo Orbit(NRHO).

celestial navigation↗
NASA NTRS1989

Computed torque control of a free-flying cooperat ing-arm robot

The unified approach to solving free-floating space robot manipulator end-point control problems is presented using a control formulation based on an extension of computed torque. Once the desired end-point accelerations have been specified, the kinematic equations are used with momentum conservation equations to solve for the joint accelerations in any of the robot's possible configurations: fixed base or free-flying with open/closed chain grasp. The joint accelerations can then be used to calculate the arm control torques and internal forces using a recursive order N algorithm. Initial experimental verification of these techniques has been performed using a laboratory model of a two-armed space robot. This fully autonomous spacecraft system experiences the drag-free, zero G characteristics of space in two dimensions through the use of an air cushion support system. Results of these initial experiments are included which validate the correctness of the proposed methodology. The further problem of control in the large where not only the manipulator tip positions but the entire system consisting of base and arms must be controlled is also presented. The availability of a physical testbed has brought a keener insight into the subtleties of the problem at hand.

Koningstein, Ross↗
NASA NTRS1994

Lunar exploration rover program developments

The Robotic All Terrain Lunar Exploration Rover (RATLER) design concept began at Sandia National Laboratories in late 1991 with a series of small, proof-of-principle, working scale models. The models proved the viability of the concept for high mobility through mechanical simplicity, and eventually received internal funding at Sandia National Laboratories for full scale, proof-of-concept prototype development. Whereas the proof-of-principle models demonstrated the mechanical design's capabilities for mobility, the full scale proof-of-concept design currently under development is intended to support field operations for experiments in telerobotics, autonomous robotic operations, telerobotic field geology, and advanced man-machine interface concepts. The development program's current status is described, including an outline of the program's work over the past year, recent accomplishments, and plans for follow-on development work.

Klarer, P. R.↗
NASA NTRS1989

The Subscale Orbital Fluid Transfer Experiment

The Center for Advanced Spacecraft Propulsion (CASP) is a subcontractor to Boeing Aerospace Corporation to provide support for the concept definition and design of a subscale orbital fluid transfer experiment (SOFTE). SOFTE is an experiment that will look at the fluid mechanics of the process of transfer of a saturated fluid between two tanks. The experiment will be placed in two get away special (GAS) can containers; the tanks will be in one container and the power and electronics will be in a second container. Since GAS cans are being used, the experiment will be autonomous. The work during the present year consisted of examining concepts for visual observation of the fluid transfer process, methods for accurately metering the amount of fluid transferred between the two tanks, possible test fluids, and materials for the elastomeric diaphragm.

Meserole, J. S.↗
NASA NTRS2018

EcAMSat: A Small Satellite Flown to Explore the Role a Sigma Factor Plays in E. coli's Response to the Antibiotic Gentamicin

We have successfully flown the EcAMSat (Escherichia coli Antimicrobial Satellite) free-flyer mission. This was a 6U (six unit - CubeSat) small satellite that autonomously conducted an experiment in low Earth orbit to explore the impact of the space environment on antibiotic resistance in uropathogenic E. coli (UPEC) and the role a particular sigma factor plays in the response. After being held in stasis during transport to orbit, two strains - a wildtype UPEC and an isogenic mutant with a deleted gene that encodes a sigma factor - were grown to stationary phase in a fluidic card inside EcAMSat's payload, then incubated with three concentrations of the antibiotic gentamicin. The payload then administered alamarBlue (registered trademark), a redox indicator, into all wells of the fluidic card. The cells were then incubated for 144 hours and metabolic activity was measured optically using the payloads' LED (Light-Emitting Diode) and detector system. Data were then telemetered to the ground and compared to a control experiment conducted in an identical satellite in a lab. The results of this experiment will help us better understand important therapeutic targets for treating bacterial infections on Earth and in space. Such targets are particularly relevant to deep-space and long-duration missions where crew may be more susceptible to infection and treatments for them may work differently.

small satellite↗
NASA NTRS2018

EcAMSat: Small Satellite to Examine E. coli's Response in Microgravity to the Antibiotic Gentamicin

We have successfully flown the EcAMSat (Escherichia coli Antimicrobial Satellite) free-flyer mission. This was a 6U small satellite that autonomously conducted an experiment in low Earth orbit to explore the impact of the space environment on antibiotic resistance in uropathogenic E. coli (UPEC) and the role a particular sigma factor plays in the response. After being held in stasis during transport to orbit, two strains†a wildtype UPEC and an isogenic mutant with a deleted gene that encodes a sigma factor†were grown to stationary phase in a fluidic card inside EcAMSat's payload, then incubated with three concentrations of the antibiotic gentamicin. The payload then administered alamarBlue®, a redox indicator, into all wells of the fluidic card. The cells were then incubated for 144 hours and metabolic activity was measured optically using the payloads' LED and detector system. Data were then telemetered to the ground and compared to a control experiment conducted in an identical satellite in a lab. The results of this experiment will help us better understand important therapeutic targets for treating bacterial infections on Earth and in space. Such targets are particularly relevant to deep-space and long-duration missions where crew may be more susceptible to infection and treatments for them may work differently.

antibiotic↗
NASA NTRSDate not supplied

Yeast strain development to test in-space bioproduction in the Lunar Explorer Instrument for space biology Applications (LEIA) mission

The Lunar Explorer Instrument for space biology Applications (LEIA) is investigating the effects of lunar radiation and gravity on yeast viability, growth, and metabolism. LEIA is part of the CP-22 Commercial Lunar Payload Services (CLPS) surface mission to the south polar region of the Moon. The biological payload will test genetic factors that are likely to influence the tolerance of yeast for deep space and lunar surface radiation. LEIA is also investigating in-space production of β-carotene in bioengineered yeast. This carotenoid is both an antioxidant and pro-vitamin A- an essential human micronutrient. We report progress on engineering carotenoid-expressing strains to test the impacts of strain background and specific genetic variants on growth and production of β-carotene. To test for enhanced sensitivity to the LEIA mission environment, we generated gene knockouts for the RAD51 DNA damage repair locus as well as the SOD1, SOD2, and TSA1 reactive oxygen species (ROS) defense enzymes. We are also generating strains expected to increase tolerance to abiotic stressors and ROS. To be included in the biology payload, each strain needs to satisfy a series of requirements to be compatible with the mission concept of operations. The LEIA mission will conduct experiments using an autonomous light emitting diode optical detection system and microfluidics incubator to quantify growth, metabolism, and carotenoid production. Strains must produce sufficient carotenoids for bioproduction to be detectable with this optical system. Cells will be loaded into microfluidics cards, desiccated, and stored for 8-12 months prior to the initiation of lunar surface operations. The CLPS lander will operate for one lunar day, and strains will need to grow to stationary phase within 96 hours to ensure that telemetry of LEIA data to Earth can be completed. Genetic variants also need to display expected phenotypes within these optical detection, storage, and growth cycle constraints.

Yeast Engineering↗
DOE OSTI2026

Intelligent Experiments Through Real-time AI: Fast Data Processing and Autonomous Detector Control for sPHENIX and Future EIC Detectors (Final Report)

The overall vision of this project was to integrate real-time artificial intelligence (AI) directly into the data acquisition and detector-control systems of nuclear physics experiments, including both fast online event selection and an autonomous detector-control feedback loop. The work carried out under the award focused on the fast online event-selection half of that vision: the efficient recording of low-momentum heavy-flavor (HF) hadron decays in proton-proton collisions at the sPHENIX experiment at the Relativistic Heavy Ion Collider (RHIC)—an observable that requires fast tracking and topological trigger selection not previously demonstrated at RHIC, and that is essential for QCD studies at future facilities such as the Electron-Ion Collider (EIC). The autonomous detector-control (GPU-based feedback) component named in the project title remained a design concept and was not implemented under this award. The Massachusetts Institute of Technology (MIT) group led the offline simulation and data processing needed to train the machine-learning (ML) models, the translation of trained models to Field-Programmable Gate Array (FPGA) firmware using the hls4ml framework, and the physics validation of heavy-flavor reconstruction. Over the award period, the team developed and hardware-tested the principal components of an AI-based heavy-flavor trigger on simulated and recorded sPHENIX tracker data: a software Bipartite Graph Attention Network (BiGAT) trigger model reaching > 95% signal efficiency at 99% background rejection; an FPGA-native hit clusterizer matching the offline clustering; smaller networks synthesized to FPGA within the required sub-10 µs latency; and an assembled decoder–clusterizer–inference firmware chain exercised on the FELIX readout board. A complete, fully integrated hardware demonstrator was not finished within the award period. This report documents the project goals, the MIT group’s contributions, the technical accomplishments, and the outlook toward applications at the future EIC ePIC detector.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Agentic artificial intelligence for multistage physics experiments at a large-scale user facility particle accelerator

We present a language-model-driven agentic artificial intelligence (AI) system to autonomously execute multistage physics experiments on a production synchrotron light source. Implemented at the Advanced Light Source particle accelerator, the system translates natural language user prompts into structured execution plans that combine archive data retrieval, control-system channel resolution, automated script generation, controlled machine interaction, and analysis. In a representative machine physics task, we show that preparation time was reduced by 2 orders of magnitude relative to manual scripting even for a system expert, while operator-standard safety constraints were strictly upheld. Core architectural features, plan-first orchestration, bounded tool access, and dynamic capability selection, enable transparent, auditable execution with fully reproducible artifacts. These results establish a blueprint for the safe integration of agentic AI into accelerator experiments and demanding machine physics studies, as well as routine operations, with direct portability across accelerators worldwide and, more broadly, to other large-scale scientific infrastructures.

Accelerator/storage ring control systems↗
DOE OSTI2026

Intelligent experiments through real-time AI: Fast Data Processing and Autonomous Detector Control for sPHENIX and future EIC detectors (Phase-I)

With an ever increasing demand for high precision data from modern detectors for discovery science and precision measurements, all major high energy nuclear and particle experiments, current and future, are facing the challenge on how to deal with the large volume of raw data generated from sophisticated state-of-the-art detectors in high rate collisions. These goals need to be balanced with available hardware and cost limits on DAQ (Data AcQuisition system) bandwidth and offline computing resources to capture, store and process the signal events. Two prototypical examples are the upcoming sPHENIX experiment, the DOE next generation heavy ion physics experiment at the Relativistic Heavy Ion Collider at BNL, and the future EIC experiments that are planned to be online circa 2030.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗