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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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NASA NTRS2001

NASA Tech Briefs, February 2001

The topics include: 1) Application Briefs; 2) National Design Engineering Show Preview; 3) Marketing Inventions to Increase Income; 4) A Personal-Computer-Based Physiological Training System; 5) Reconfigurable Arrays of Transistors for Evolvable Hardware; 6) Active Tactile Display Device for Reading by a Blind Person; 7) Program Automates Management of IBM VM Computer Systems; 8) System for Monitoring the Environment of a Spacecraft Launch; 9) Measurement of Stresses and Strains in Muscles and Tendons; 10) Optical Measurement of Temperatures in Muscles and Tendons; 11) Small Low-Temperature Thermometer With Nanokelvin Resolution; 12) Heterodyne Interferometer With Phase-Modulated Carrier; 13) Rechargeable Batteries Based on Intercalation in Graphite; 14) Signal Processor for Doppler Measurements in Icing Research; 15) Model Optimizes Drying of Wet Sheets; 16) High-Performance POSS-Modified Polymeric Composites; 17) Model Simulates Semi-Solid Material Processing; 18) Modular Cryogenic Insulation; 19) Passive Venting for Alleviating Helicopter Tail-Boom Loads; 20) Computer Program Predicts Rocket Noise; 21) Process for Polishing Bare Aluminum to High Optical Quality; 22) External Adhesive Pressure-Wall Patch; 23) Java Implementation of Information-Sharing Protocol; 24) Electronic Bulletin Board Publishes Schedules in Real Time; 25) Apparatus Would Extract Water From the Martian Atmosphere; 26) Review of Research on Supercritical vs Subcritical Fluids; 27) Hybrid Regenerative Water-Recycling System; 28) Study of Fusion-Driven Plasma Thruster With Magnetic Nozzle; 29) Liquid/Vapor-Hydrazine Thruster Would Produce Small Impulses; and 30) Thruster Based on Sublimation of Solid Hydrazine

Source record↗
NASA NTRS2004

Optoelectronic Sensor System for Guidance in Docking

The Video Guidance Sensor (VGS) system is an optoelectronic sensor that provides automated guidance between two vehicles. In the original intended application, the two vehicles would be spacecraft docking together, but the basic principles of design and operation of the sensor are applicable to aircraft, robots, vehicles, or other objects that may be required to be aligned for docking, assembly, resupply, or precise separation. The system includes a sensor head containing a monochrome charge-coupled- device video camera and pulsed laser diodes mounted on the tracking vehicle, and passive reflective targets on the tracked vehicle. The lasers illuminate the targets, and the resulting video images of the targets are digitized. Then, from the positions of the digitized target images and known geometric relationships among the targets, the relative position and orientation of the vehicles are computed. As described thus far, the VGS system is based on the same principles as those of the system described in "Improved Video Sensor System for Guidance in Docking" (MFS-31150), NASA Tech Briefs, Vol. 21, No. 4 (April 1997), page 9a. However, the two systems differ in the details of design and operation. The VGS system is designed to operate with the target completely visible within a relative-azimuth range of +/-10.5deg and a relative-elevation range of +/-8deg. The VGS acquires and tracks the target within that field of view at any distance from 1.0 to 110 m and at any relative roll, pitch, and/or yaw angle within +/-10deg. The VGS produces sets of distance and relative-orientation data at a repetition rate of 5 Hz. The software of this system also accommodates the simultaneous operation of two sensors for redundancy

Howard, Richard T.↗
NASA NTRSDate not supplied

BioSentinel: NASA’s First Deep Space Biological Mission

Since Apollo 17 in 1972, NASA has sent no humans or other biological organisms outside of Earth’s protective magnetosphere. NASA’s current Artemis program plans to put astronauts back on the Moon and eventually land human missions on Mars. One of the major challenges to long-duration crewed travel and habitation in deep space is an in-depth understanding of the biological effects of space radiation, often convoluted by the impact of reduced gravity. Such missions will require significant countermeasures, likely both technological and biomedical, to protect organisms from chronic radiation exposure. Small satellite missions like CubeSats can inform these countermeasures by investigating model organisms in relevant space environments. The BioSentinel mission is comprised of four segments developed at NASA Ames Research Center: a 6U CubeSat (1U = 10-cm cube), an ISS payload launched in December 2021 and two ground units, one for the mission’s CubeSat and one for the ISS payload. The last three segments have been operational since January 2022 and serve as experimental controls. BioSentinel’s 6U CubeSat is planned to launch as a secondary payload on the Artemis-1 rocket. It will be deployed on a lunar fly-by trajectory and into a heliocentric orbit. BioSentinel will be the first interplanetary satellite to study the biological response to space radiation outside Low Earth Orbit (LEO) in almost 50 years. BioSentinel is a complete, autonomous spacecraft capable of conducting experiments in deep space. Its 4U BioSensor payload is a fully automated and adaptable platform that can perform biological measurements with a range of microorganisms in multiple space environments, including the ISS, free flyers, and other platforms like the Lunar Gateway and lander vehicles. Once it reaches its orbit, BioSentinel’s CubeSat will measure the DNA damage response to ambient radiation in a model organism, the budding yeast Saccharomyces cerevisiae, which will be compared to information provided by an onboard radiation sensor and to data obtained in LEO (on ISS) and on Earth. Once in interplanetary space, fluidic cards containing desiccated yeast will be activated by growth medium addition at different time points throughout the mission. Growth and metabolic activity will be tracked continuously via optical measurements. This paper describes BioSentinel’s objectives, science, data management, and preliminary results from the ISS and ISS ground control segments.

BioSentinel↗
NASA NTRSDate not supplied

BioSentinel: NASA’s First Deep Space Biological Mission

Since Apollo 17 in 1972, NASA has sent no humans or other biological organisms outside of Earth’s protective magnetosphere. NASA’s current Artemis program plans to put astronauts back on the Moon and eventually land human missions on Mars. One of the major challenges to long-duration crewed travel and habitation in deep space is an in-depth understanding of the biological effects of space radiation, often convoluted by the impact of reduced gravity. Such missions will require significant countermeasures, likely both technological and biomedical, to protect organisms from chronic radiation exposure. Small satellite missions like CubeSats can inform these countermeasures by investigating model organisms in relevant space environments. The BioSentinel mission is comprised of four segments developed at NASA Ames Research Center: a 6U CubeSat (1U = 10-cm cube), an ISS payload launched in December 2021 and two ground units, one for the mission’s CubeSat and one for the ISS payload. The last three segments have been operational since January 2022 and serve as experimental controls. BioSentinel’s 6U CubeSat is planned to launch as a secondary payload on the Artemis-1 rocket. It will be deployed on a lunar fly-by trajectory and into a heliocentric orbit. BioSentinel will be the first interplanetary satellite to study the biological response to space radiation outside Low Earth Orbit (LEO) in almost 50 years. BioSentinel is a complete, autonomous spacecraft capable of conducting experiments in deep space. Its 4U BioSensor payload is a fully automated and adaptable platform that can perform biological measurements with a range of microorganisms in multiple space environments, including the ISS, free flyers, and other platforms like the Lunar Gateway and lander vehicles. Once it reaches its orbit, BioSentinel’s CubeSat will measure the DNA damage response to ambient radiation in a model organism, the budding yeast Saccharomyces cerevisiae, which will be compared to information provided by an onboard radiation sensor and to data obtained in LEO (on ISS) and on Earth. Once in interplanetary space, fluidic cards containing desiccated yeast will be activated by growth medium addition at different time points throughout the mission. Growth and metabolic activity will be tracked continuously via optical measurements. This paper describes BioSentinel’s objectives, science, data management, and preliminary results from the ISS segment.

BioSentinel↗
NASA NTRS2022

Evolution of Biological Satellites: From Low Earth Orbit to NASA’s BioSentinel Deep Space Mission

NASA has set its sights on human exploration in deep space with the Artemis missions, with an ambitious plan to put astronauts back on the Moon and to eventually land human missions on Mars. Such missions will require significant countermeasures, likely both technological and biomedical, to protect biology from chronic radiation exposure. Small satellites like CubeSats can inform these countermeasures by querying relevant space environments with model organisms over relevant durations. NASA has launched five biological CubeSats into low Earth orbit (LEO) from GeneSat in 2006 to EcAMSat in 2017. Each one of these missions increased our understanding of the effects of spaceflight, while refining technologies and imparting valuable lessons to the next generation of CubeSats. The Artemis I rocket will carry ten CubeSats, each of them with its own objective. One in particular, BioSentinel, will conduct the first study of the biological response to interplanetary space radiation beyond LEO since Apollo 17. Once it reaches its heliocentric orbit – after a short lunar fly-by – BioSentinel will measure the DNA damage response to ambient radiation in a model organism, the budding yeast Saccharomyces cerevisiae, which will be compared to information provided by an onboard radiation sensor and to data obtained in LEO (on ISS) and on Earth. Once in interplanetary space, fluidic cards containing desiccated yeast cells will be activated by growth medium addition at different time points throughout the mission. Growth and metabolic activity will be tracked continuously via optical density. BioSentinel is a complete, autonomous spacecraft capable of conducting experiments in deep space. Its 4U BioSensor payload is a fully automated and adaptable platform that can perform biological measurements with a range of microorganisms in multiple space environments, including the ISS, free flyers, and other platforms like the Lunar Gateway and lander vehicles.

Sergio R Santa Maria↗
NASA NTRS1972

Advanced dosimetry systems for the space transport and space station

Advanced dosimetry system concepts are described that will provide automated and instantaneous measurement of dose and particle spectra. Systems are proposed for measuring dose rate from cosmic radiation background to greater than 3600 rads/hr. Charged particle spectrometers, both internal and external to the spacecraft, are described for determining mixed field energy spectra and particle fluxes for both real time onboard and ground-based computer evaluation of the radiation hazard. Automated passive dosimetry systems consisting of thermoluminescent dosimeters and activation techniques are proposed for recording the dose levels for twelve or more crew members. This system will allow automatic onboard readout and data storage of the accumulated dose and can be transmitted to ground after readout or data records recovered with each crew rotation.

Wailly, L. F.↗
NASA NTRS2006

Conflict-Aware Scheduling Algorithm

conflict-aware scheduling algorithm is being developed to help automate the allocation of NASA s Deep Space Network (DSN) antennas and equipment that are used to communicate with interplanetary scientific spacecraft. The current approach for scheduling DSN ground resources seeks to provide an equitable distribution of tracking services among the multiple scientific missions and is very labor intensive. Due to the large (and increasing) number of mission requests for DSN services, combined with technical and geometric constraints, the DSN is highly oversubscribed. To help automate the process, and reduce the DSN and spaceflight project labor effort required for initiating, maintaining, and negotiating schedules, a new scheduling algorithm is being developed. The scheduling algorithm generates a "conflict-aware" schedule, where all requests are scheduled based on a dynamic priority scheme. The conflict-aware scheduling algorithm allocates all requests for DSN tracking services while identifying and maintaining the conflicts to facilitate collaboration and negotiation between spaceflight missions. These contrast with traditional "conflict-free" scheduling algorithms that assign tracks that are not in conflict and mark the remainder as unscheduled. In the case where full schedule automation is desired (based on mission/event priorities, fairness, allocation rules, geometric constraints, and ground system capabilities/ constraints), a conflict-free schedule can easily be created from the conflict-aware schedule by removing lower priority items that are in conflict.

Wang, Yeou-Fang↗
NASA NTRS1991

A strongly goal-directed close-range vision system for spacecraft docking

In this presentation, we will propose a strongly goal-oriented stereo vision system to establish proper docking approach motions for automated rendezvous and capture (AR&C). From an input sequence of stereo video image pairs, the system produces a current best estimate of: contact position; contact vector; contact velocity; and contact orientation. The processing demands imposed by this particular problem and its environment dictate a special case solution; such a system should necessarily be, in some sense, minimalist. By this we mean the system should construct a scene description just sufficiently rich to solve the problem at hand and should do no more processing than is absolutely necessary. In addition, the imaging resolution should be just sufficient. Extracting additional information and constructing higher level scene representations wastes energy and computational resources and injects an unnecessary degree of complexity, increasing the likelihood of malfunction. We therefore take a departure from most prior stereopsis work, including our own, and propose a system based on associative memory. The purpose of the memory is to immediately associate a set of motor commands with a set of input visual patterns in the two cameras. That is, rather than explicitly computing point correspondences and object positions in world coordinates and trying to reason forward from this information to a plan of action, we are trying to capture the essence of reflex behavior through the action of associative memory. The explicit construction of point correspondences and 3D scene descriptions, followed by online velocity and point of impact calculations, is prohibitively expensive from a computational point of view for the problem at hand. Learned patterns on the four image planes, left and right at two discrete but closely spaced instants in time, will be bused directly to infer the spacecraft reaction. This will be a continuing online process as the docking collar approaches.

Boyer, Kim L.↗
NASA NTRS2004

Automated Rendezvous and Capture System Development and Simulation for NASA

The United States does not have an Automated Rendezvous and Capture Docking (AR&C) capability and is reliant on manned control for rendezvous and docking of orbiting spacecraft. T h i s reliance on the labor intensive manned interface for control of rendezvous and docking vehicles has a significant impact on the cost of the operation of the International Space Station (ISS) and precludes the use of any U.S. expendable launch capabilities for Space Station resupply. The Marshall Space Flight Center (MSFC) has conducted pioneering research in the development of an automated rendezvous and capture (or docking) (AR&C) system for U.S. space vehicles. This A M C system was tested extensively using hardware-in-the-loop simulations in the Flight Robotics Laboratory, and a rendezvous sensor, the Video Guidance Sensor was developed and successfully flown on the Space Shuttle on flights STS-87 and STS-95, proving the concept of a video- based sensor. Further developments in sensor technology and vehicle and target configuration have lead to continued improvements and changes in AR&C system development and simulation. A new Advanced Video Guidance Sensor (AVGS) with target will be utilized as the primary navigation sensor on the Demonstration of Autonomous Rendezvous Technologies (DART) flight experiment in 2004. Realtime closed-loop simulations will be performed to validate the improved AR&C systems prior to flight.

Roe, Fred D.↗
NASA NTRS2004

Automated Rendezvous and Capture System Development and Simulation for NASA

The United States does not have an Automated Rendezvous and Capture/Docking (AR and C) capability and is reliant on manned control for rendezvous and docking of orbiting spacecraft. This reliance on the labor intensive manned interface for control of rendezvous and docking vehicles has a significant impact on the cost of the operation of the International Space Station (ISS) and precludes the use of any U.S. expendable launch capabilities for Space Station resupply. The Soviets have the capability to autonomously dock in space, but their system produces a hard docking with excessive force and contact velocity. Automated Rendezvous and Capture/Docking has been identified as a key enabling technology for the Space Launch Initiative (SLI) Program, DARPA Orbital Express and other DOD Programs. The development and implementation of an AR&C capability can significantly enhance system flexibility, improve safety, and lower the cost of maintaining, supplying, and operating the International Space Station. The Marshall Space Flight Center (MSFC) has conducted pioneering research in the development of an automated rendezvous and capture (or docking) (AR and C) system for U.S. space vehicles. This AR&C system was tested extensively using hardware-in-the-loop simulations in the Flight Robotics Laboratory, and a rendezvous sensor, the Video Guidance Sensor was developed and successfully flown on the Space Shuttle on flights STS-87 and STS-95, proving the concept of a video- based sensor. Further developments in sensor technology and vehicle and target configuration have lead to continued improvements and changes in AR&C system development and simulation. A new Advanced Video Guidance Sensor (AVGS) with target will be utilized on the Demonstration of Autonomous Rendezvous Technologies (DART) flight experiment in 2004.

Roe, Fred D.↗
NASA NTRS2008

Automated Generation and Assessment of Autonomous Systems Test Cases

This slide presentation reviews some of the issues concerning verification and validation testing of autonomous spacecraft routinely culminates in the exploration of anomalous or faulted mission-like scenarios using the work involved during the Dawn mission's tests as examples. Prioritizing which scenarios to develop usually comes down to focusing on the most vulnerable areas and ensuring the best return on investment of test time. Rules-of-thumb strategies often come into play, such as injecting applicable anomalies prior to, during, and after system state changes; or, creating cases that ensure good safety-net algorithm coverage. Although experience and judgment in test selection can lead to high levels of confidence about the majority of a system's autonomy, it's likely that important test cases are overlooked. One method to fill in potential test coverage gaps is to automatically generate and execute test cases using algorithms that ensure desirable properties about the coverage. For example, generate cases for all possible fault monitors, and across all state change boundaries. Of course, the scope of coverage is determined by the test environment capabilities, where a faster-than-real-time, high-fidelity, software-only simulation would allow the broadest coverage. Even real-time systems that can be replicated and run in parallel, and that have reliable set-up and operations features provide an excellent resource for automated testing. Making detailed predictions for the outcome of such tests can be difficult, and when algorithmic means are employed to produce hundreds or even thousands of cases, generating predicts individually is impractical, and generating predicts with tools requires executable models of the design and environment that themselves require a complete test program. Therefore, evaluating the results of large number of mission scenario tests poses special challenges. A good approach to address this problem is to automatically score the results based on a range of metrics. Although the specific means of scoring depends highly on the application, the use of formal scoring - metrics has high value in identifying and prioritizing anomalies, and in presenting an overall picture of the state of the test program. In this paper we present a case study based on automatic generation and assessment of faulted test runs for the Dawn mission, and discuss its role in optimizing the allocation of resources for completing the test program.

Testing challenges↗
NASA NTRS1994

Production and quality assurance automation in the Goddard Space Flight Center Flight Dynamics Facility

The Flight Dynamics Facility (FDF) at the NASA Goddard Space Flight Center (GSFC) generates numerous products for NASA-supported spacecraft, including the Tracking and Data Relay Satellites (TDRS's), the Hubble Space Telescope (HST), the Extreme Ultraviolet Explorer (EUVE), and the space shuttle. These products include orbit determination data, acquisition data, event scheduling data, and attitude data. In most cases, product generation involves repetitive execution of many programs. The increasing number of missions supported by the FDF has necessitated the use of automated systems to schedule, execute, and quality assure these products. This automation allows the delivery of accurate products in a timely and cost-efficient manner. To be effective, these systems must automate as many repetitive operations as possible and must be flexible enough to meet changing support requirements. The FDF Orbit Determination Task (ODT) has implemented several systems that automate product generation and quality assurance (QA). These systems include the Orbit Production Automation System (OPAS), the New Enhanced Operations Log (NEOLOG), and the Quality Assurance Automation Software (QA Tool). Implementation of these systems has resulted in a significant reduction in required manpower, elimination of shift work and most weekend support, and improved support quality, while incurring minimal development cost. This paper will present an overview of the concepts used and experiences gained from the implementation of these automation systems.

Chapman, K. B.↗
NASA NTRS1994

An operations and command systems for the extreme ultraviolet explorer

About 40% of the budget of a scientific spacecraft mission is usually consumed by Mission Operations & Data Analysis (MO&DA) with MO driving these costs. In the current practice, MO is separated from spacecraft design and comes in focus relatively late in the mission life cycle. As a result, spacecraft may be designed that are very difficult to operate. NASA centers have extensive MO expertise but often lessons learned in one mission are not exploited for other parallel or future missions. A significant reduction of MO costs is essential to ensure a continuing and growing access to space for the scientific community. We are addressing some of these issues with a highly automated payload operations and command system for an existing mission, the Extreme Ultraviolet Explorer (EUVE). EUVE is currently operated jointly by the Goddard Space Flight Center (GSFC), responsible for spacecraft operations, and the Center for Extreme Ultraviolet Astrophysics (CEA) of the University of California, Berkeley, which controls the telescopes and scientific instruments aboard the satellite. The new automated system is being developed by a team including personnel from the NASA Ames Research Center (ARC), the Jet Propulsion Laboratory (JPL) and the Center for EUV Astrophysics (CEA). An important goal of the project is to provide AI-based technology that can be easily operated by nonspecialists in AI. Another important goal is the reusability of the techniques for other missions. Models of the EUVE spacecraft need to be built both for planning/scheduling and for monitoring. In both cases, our modeling tools allow the assembly of a spacecraft model from separate sub-models of the various spacecraft subsystems. These sub-models are reusable; therefore, building mission operations systems for another small satellite mission will require choosing pre-existing modules, reparametrizing them with respect to the actual satellite telemetry information, and reassembling them in a new model. We briefly describe the EUVE mission and indicate why it is particularly suitable for the task. Then we briefly outline our current work in mission planning/scheduling and spacecraft and instrument health monitoring.

Muscettola, Nicola↗
NASA NTRS2019

Simulation-to-Flight 1 (STF-1): Automating the Planning, Scheduling, Assessment and Data Processing/Reduction for a Small Satellite

On December 16, 2019, a 3-U CubeSat named STF-1 launched as West Virginia's first spacecraft. This event marked the culmination of a run-up to launch involving the production of the spacecraft, creation/configuration of command and control infrastructure, and the evolution of its co-creation, the NASA Operational Simulator for Small Satellites (NOS3). This event also marked the beginning of a new phase: operations. While plans, procedures, and infrastructure were already in place or started for operations, many lessons were learned during the operations phase, especially during early operations (first month/commissioning phase). Additional plans, procedures, and infrastructure, especially related to communication planning and automated data processing, were created and developed to fill needs for the operation of the STF-1 mission.This paper and presentation will overview the STF-1 operations team's solutions to addressing the many needs of operating a low-earth orbiting CubeSat mission with a single ground antenna that is shared and scheduled with several other missions. The STF-1 operations team deployed a combination of virtualization technologies, ground station technology solutions, collaboration software, custom planning software solutions, and existing ground antenna scheduling solutions to create an effective and efficient CubeSat operations environment. The end-solution satisfied the operations stakeholders, which include NASA, its industry partner TMC Technologies, and four independent professor-student teams at West Virginia University.

CubeSat↗
NASA NTRS2019

STF-1 Ground Operations - Automating the Planning, Scheduling, Assessment and Data Processing/Reduction for a Small Satellite

On December 16, 2018, a 3-U CubeSat named STF-1 launched as West Virginia's first spacecraft. This event marked the culmination of a run-up to launch involving the production of the spacecraft, creation/configuration of command and control infrastructure, and the evolution of its co-creation, the NASA Operational Simulator for Small Satellites (NOS3). This event also marked the beginning of a new phase: operations. While plans, procedures, and infrastructure were already in place or started for operations, many lessons were learned during the operations phase, especially during early operations (first month/commissioning phase). Additional plans, procedures, and infrastructure, especially related to communication planning and automated data processing, were created and developed to fill needs for the operation of the STF-1 mission.This paper and presentation will overview the STF-1 operations team's solutions to addressing the many needs of operating a low-earth orbiting CubeSat mission with a single ground antenna that is shared and scheduled with several other missions. The STF-1 operations team deployed a combination of virtualization technologies, ground station technology solutions, collaboration software, custom planning software solutions, and existing ground antenna scheduling solutions to create an effective and efficient CubeSat operations environment. The end-solution satisfied the operations stakeholders, which include NASA, its industry partner TMC2 Technologies, and four independent professor-student teams at West Virginia University.

Suder, Mark↗
NASA NTRS1991

Augmentation of the space station module power management and distribution breadboard

The space station module power management and distribution (SSM/PMAD) breadboard models power distribution and management, including scheduling, load prioritization, and a fault detection, identification, and recovery (FDIR) system within a Space Station Freedom habitation or laboratory module. This 120 VDC system is capable of distributing up to 30 kW of power among more than 25 loads. In addition to the power distribution hardware, the system includes computer control through a hierarchy of processes. The lowest level consists of fast, simple (from a computing standpoint) switchgear that is capable of quickly safing the system. At the next level are local load center processors, (LLP's) which execute load scheduling, perform redundant switching, and shed loads which use more than scheduled power. Above the LLP's are three cooperating artificial intelligence (AI) systems which manage load prioritizations, load scheduling, load shedding, and fault recovery and management. Recent upgrades to hardware and modifications to software at both the LLP and AI system levels promise a drastic increase in speed, a significant increase in functionality and reliability, and potential for further examination of advanced automation techniques. The background, SSM/PMAD, interface to the Lewis Research Center test bed, the large autonomous spacecraft electrical power system, and future plans are discussed.

Walls, Bryan↗