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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

How Well Do Satellite AOD Observations Represent the Spatial and Temporal Variability of PM2.5 Concentration for the United States?

Due to their extensive spatial coverage, satellite Aerosol Optical Depth (AOD) observations have been widely used to estimate and predict surface PM2.5 concentrations. While most previous studies have focused on establishing relationships between collocated, hourly or daily AOD and PM2.5 measurements, in this study, we instead focus on the comparison of the large-scale spatial and temporal variability between satellite AOD and PM2.5 using monthly mean measurements. A newly developed spectral analysis technique e Combined Maximum Covariance Analysis (CMCA) is applied to Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging Spectroradiometer (MISR), Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Ozone Monitoring Instrument (OMI) AOD datasets and Environmental Protection Agency (EPA) PM2.5 data, in order to extract and compare the dominant modes of variability. Results indicate that AOD and PM2.5 agree well in terms of interannual variability. An overall decrease is found in both AOD and PM2.5 across the United States, with the strongest signal over the eastern US. With respect to seasonality, good agreement is found only for Eastern US, while for Central and Western US, AOD and PM2.5 seasonal cycles are largely different or even reversed. These results are verified using Aerosol Robotic Network (AERONET) AOD observations and differences between satellite and AERONET are also examined. MODIS and MISR appear to have the best agreement with AERONET. In order to explain the disagreement between AOD and PM2.5 seasonality, we further use Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) extinction profile data to investigate the effect of two possible contributing factors, namely aerosol vertical distribution and cloud-free sampling. We find that seasonal changes in aerosol vertical distribution, due to the seasonally varying mixing height, is the primary cause for the AOD and PM2.5 seasonal discrepancy, in particular, the low AOD but high PM2.5 observed during the winter season for Central and Western US. In addition, cloud-free sampling by passive sensors also induces some bias in AOD seasonality, especially for the Western US, where the largest seasonal change in cloud fraction is found. The seasonal agreement between low level (below 500 m AGL), all sky CALIOP AOD and PM2.5 is significantly better than column AOD from MODIS, MISR, SeaWiFS and OMI. In particular, the correlation between low level, all sky AOD and PM2.5 seasonal cycles increases to above 0.7 for Central and Western US, as opposed to near zero or negative correlation for column, clear sky AOD. This result highlights the importance of accounting for the seasonally varying aerosol profiles and cloud-free sampling bias when using column AOD measurements to infer surface PM2.5 concentrations.

MODIS (radiometry)↗
NASA NTRSDate not supplied

Challenges of Operations in a Dynamic Environment: A Three-Year Perspective of SAGE III

The Stratospheric Aerosol and Gas Experiment~III on the International Space Station (SAGE III/ISS) was delivered to the International Space Station (ISS) on 23 February 2017. The SAGE III/ISS payload was robotically installed external to the ISS and began acquiring science measurements on 17 March 2017. The SAGE III/ISS instrument retrieves vertical profiles of atmospheric ozone, multi-wavelength aerosol extinctions, and other gaseous species. This paper will focus on the improvements made to the operations of the SAGE III/ISS payload. A key focus of the operations team following commissioning was to create robust tools that aide in the operations of the payload. A close collaboration with the SAGE III/ISS ground systems team allowed for the development of web-based tools to continuously monitor the health of the instrument. The mission operations team also worked with the SAGE III/ISS science team to gain a better sense of how the instrument works to maximize the quality and quantity of the science data collected. Another unique aspect of the SAGE III/ISS payload, that will be discussed, is the challenges of operating a hosted payload on the ISS; an active platform that has frequent attitude maneuvers, dockings, and EVA's. This active environment increases the need for the SAGE III/ISS operations team command the payload. Through coordination and teamwork, SAGE III/ISS mission has developed an operations team that has successfully managed the instrument around ISS activities and recovered from multiple instrument upsets. This has led the SAGE III/ISS payload to successfully surpass the acquisition metrics set forth prior to launch, allowing for the continued contribution to studying the atmospheric composition of the stratosphere and how it plays a role in earth’s climate.

SAGE III↗
NASA NTRSDate not supplied

Operations Challenges in a Dynamic Environment: A Three-Year Perspective of SAGE III

The Stratospheric Aerosol and Gas Experiment III on the International Space Station (SAGE III/ISS) was delivered to the International Space Station (ISS) on 23 February 2017. The SAGE III/ISS payload was robotically installed external to the ISS and began acquiring science measurements on 17 March 2017. The SAGE III/ISS instrument retrieves vertical profiles of atmospheric ozone, multi-wavelength aerosol extinctions, and other gaseous species. This paper will focus on the improvements made to the operations of the SAGE III/ISS payload. A key focus of the operations team following commissioning was to create robust tools that aid in the operations of the payload. A close collaboration with the SAGE III/ISS ground systems team allowed for the development of web-based tools to continuously monitor the health of the payload. The mission operations team also worked with the SAGE III/ISS science team to gain a better sense of how the instrument works to maximize the quality and quantity of the science data collected. Another unique aspect of the SAGE III/ISS payload, that will be discussed, is the challenges of operating a hosted payload on the ISS; an active platform that has frequent attitude maneuvers, dockings, and EVAs. This active environment increases the need for the SAGE III/ISS operations team command to the payload. Through coordination and teamwork, SAGE III/ISS mission has developed an operations team, tool, and procedures that have successfully managed the payload around ISS activities and recovered from multiple instrument upsets. This has led the SAGE III/ISS payload to successfully surpass the acquisition metrics set forth prior to launch, allowing for the continued contribution to studying the atmospheric composition of the stratosphere and how it plays a role in Earth’s climate.

SAGE III↗
NASA NTRS1999

Park Smart

The Parking Garage Automation System (PGAS) is based on a technology developed by a NASA-sponsored project called Robot sensorSkin(TM). Merritt Systems, Inc., of Orlando, Florida, teamed up with NASA to improve robots working with critical flight hardware at Kennedy Space Center in Florida. The system, containing smart sensor modules and flexible printed circuit board skin, help robots to steer clear of obstacles using a proximity sensing system. Advancements in the sensor designs are being applied to various commercial applications, including the PGAS. The system includes a smartSensor(TM) network installed around and within public parking garages to autonomously guide motorists to open facilities, and once within, to free parking spaces. The sensors use non-invasive reflective-ultrasonic technology for high accuracy, high reliability, and low maintenance. The system is remotely programmable: it can be tuned to site-specific requirements, has variable range capability, and allows remote configuration, monitoring, and diagnostics. The sensors are immune to interference from metallic construction materials, such as rebar and steel beams. Inside the garage, smart routing signs mounted overhead or on poles in front of each row of parking spots guide the motorist precisely to free spaces.

Source record↗
NASA NTRS2016

Extreme Mapping: Looking for Water on the Moon

There are many challenges when exploring extreme environments. Gathering accurate data to build maps about places that you cannot go is incredibly complex. NASA supports scientists by remotely operating robotic rovers to explore uncharted territories. One potential upcoming mission is to look for water near a lunar pole (the Resource Prospector mission). Learn about the technical hurdles and research steps that NASA takes before the mission. NASA practices on Earth with Mission Analogs which simulate the proposed mission. This includes going to lunar-type landscapes, building field networks, testing out rovers, instruments and operational procedures. NASA sets up remote science back rooms just as there are for actual missions. NASA develops custom Ground Data Systems software to support scientific mission planning and monitoring over variable time delays, and separate commanding software and infrastructure to operate the rovers.

MOON↗
NASA NTRSDate not supplied

Radar Observations from the Haystack Ultrawideband Satellite Imaging Radar in 2019

The NASA Orbital Debris Program Office (ODPO) conducts radar measurements of the low Earth orbit (LEO) orbital debris environment on a continual basis for monitoring and to enable modeling of the environment over time. Radar observations from the Haystack Ultra-wideband Satellite Imaging Radar (HUSIR) in 2019 are the most recent snapshot of the environment to date that has been both measured and analyzed. HUSIR provides data on orbital debris in LEO down to a NASA size estimation model (SEM) size of approximately 5.5 mm, depending upon altitude and year-to -year variation in the sensitivity of the radar. This is of interest as it is the millimeter-sized orbital debris that drives mission-ending risk to robotic spacecraft in LEO. This paper will explore the results of the 2019 HUSIR radar measurements, including above-average flux measurements at lower LEO altitudes and the evolution of the flux during the time of observations.

James Murray↗
NASA NTRSDate not supplied

How Autonomous Intelligent Systems Can Facilitate Earth-independent Medical Care: Going Beyond Telepresence

During the last decade, teleoperated robotic systems have extended humans’ sensorimotor competence to digitally fly beyond the physical barrier of distance and scale and thus transmit sensorimotor skills of the human through direct communication. Telepresence capabilities have enabled tele-physical remote access at small scales thanks to telerobotic mediums. Although the concept was initially motivated by space applications, such technologies quickly have expanded into the medical domain and resulted in teleoperated medical robots, including telerobotic surgical systems (such as the da Vinci surgical system). Effective telepresence fundamentally depends on an agile, reliable, and secure communication medium that can transmit real-time information between the operator and a remote device. However, direct telepresence may not be achievable for long-duration exploration spaceflight missions. Thus, autonomous systems and local intelligence represent potential solutions to the aforementioned issues. One example solution employs demonstration systems which enable learning from the pre-captured inputs of a skilled human operator. These will be computationally modeled and later probabilistically replicated toward the completion of remote physical tasks when direct telepresence is not viable - such as under communication blackout conditions. In other words, trained autonomous systems (e.g., robots) can perform remote operations that mimic the physical performance of experts during remote operations/training. Beyond learning the physics of the task, autonomous agents can also be used to conduct algorithmic decision-making that mimics the higher-level cognition of the expert. Thus, using an autonomous system, pre-trained cognitive and manipulation-based skills can be leveraged (acquired during pre-mission events) to produce digital twins of an intelligent operator. Such systems can be used for the real-time conduction of intricate tasks in complex and unstructured environments. Such systems will operationalize “cognitive digital twins” and can expand the reach of human cognition and manipulation through the power of data-driven learning from demonstration algorithms. This system category will be discussed as a fully autonomous operation in this talk. In addition to the above, we will also propose and discuss the possibility of partial-automation using remote intelligence and remote sensing. In contrast to full automation, partial automation can close the loop through a local operator equipped with augmented sensory awareness through wearable systems. Such technologies will allow the local operator to conduct delicate tasks while being guided using sensory augmentation and being monitored to gauge her/his level of cognitive focus and performance. The difference with the previous category is that a remote human will conduct the task. Further, rather than making a digital twin of human cognition, we will augment the control inputs of the local human to match those of the skilled expert operator who is not accessible in real-time. Going beyond classic telepresence and thus approaching intelligent telepresence, our vision is that autonomous agents will eventually enable the safe, consistent and efficient delivery of complex, remote and smart medical care during space exploration across operators in an Earth-independent fashion. We will discuss our collective vision from NASA and MERIIT@NYU lab in this talk.

Telepresence↗
NASA NTRS2004

Survey of current situation in radiation belt modeling

The study of Earth's radiation belts is one of the oldest subjects in space physics. Despite the tremendous progress made in the last four decades, we still lack a complete understanding of the radiation belts in terms of their configurations, dynamics, and detailed physical accounts of their sources and sinks. The static nature of early empirical trapped radiation models, for examples, the NASA AP-8 and AE-8 models, renders those models inappropriate for predicting short-term radiation belt behaviors associated with geomagnetic storms and substorms. Due to incomplete data coverage, these models are also inaccurate at low altitudes (e.g., <1000 km) where many robotic and human space flights occur. The availability of radiation data from modern space missions and advancement in physical modeling and data management techniques have now allowed the development of new empirical and physical radiation belt models. In this paper, we will review the status of modern radiation belt modeling. Published by Elsevier Ltd on behalf of COSPAR.

Protons↗
NASA NTRS2010

NASA Tech Briefs, October 2010

Topics covered include: Hybrid Architecture Active Wavefront Sensing and Control; Carbon-Nanotube-Based Chemical Gas Sensor; Aerogel-Positronium Technology for the Detection of Small Quantities of Organic and/or Toxic Materials; Graphene-Based Reversible Nano-Switch/Sensor Schottky Diode; Inductive Non-Contact Position Sensor; High-Temperature Surface-Acoustic-Wave Transducer; Grid-Sphere Electrodes for Contact with Ionospheric Plasma; Enabling IP Header Compression in COTS Routers via Frame Relay on a Simplex Link; Ka-Band SiGe Receiver Front-End MMIC for Transponder Applications; Robust Optimization Design Algorithm for High-Frequency TWTs; Optimal and Local Connectivity Between Neuron and Synapse Array in the Quantum Dot/Silicon Brain; Method and Circuit for In-Situ Health Monitoring of Solar Cells in Space; BGen: A UML Behavior Network Generator Tool; Platform for Post-Processing Waveform-Based NDE; Electrochemical Hydrogen Peroxide Generator; Fabrication of Single, Vertically Aligned Carbon Nanotubes in 3D Nanoscale Architectures; Process to Create High-Fidelity Lunar Dust Simulants; Lithium-Ion Electrolytes Containing Phosphorous-Based, Flame-Retardant Additives; InGaP Heterojunction Barrier Solar Cells; Straight-Pore Microfilter with Efficient Regeneration; Determining Shear Stress Distribution in a Laminate; Self-Adjusting Liquid Injectors for Combustors; Handling Qualities Prediction of an F-16XL-Based Reduced Sonic Boom Aircraft; Tele-Robotic ATHLETE Controller for Kinematics - TRACK; Three-Wheel Brush-Wheel Sampler; Heterodyne Interferometer Angle Metrology; Aligning Astronomical Telescopes via Identification of Stars; Generation of Optical Combs in a WGM Resonator from a Bichromatic Pump; Large-Format AlGaN PIN Photodiode Arrays for UV Images; Fiber-Coupled Planar Light-Wave Circuit for Seed Laser Control in High Spectral Resolution Lidar Systems; On Calculating the Zero-Gravity Surface Figure of a Mirror; Optical Modification of Casimir Forces for Improved Function of Micro- and Nano-Scale Devices; Analysis, Simulation, and Verification of Knowledge-Based, Rule-Based, and Expert Systems; Core and Off-Core Processes in Systems Engineering; Digital Reconstruction Supporting Investigation of Mishaps; and Template Matching Approach to Signal Prediction.

Source record↗
NASA NTRSDate not supplied

ICE-RASSOR: Intelligent Capabilities Enhanced Regolith Advanced Surface Systems Operations Robot

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU)processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from a reduced sensor payload. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We apply supervised learning using real data to estimate the soil mass collected without the need for mass flow rate monitors or other explicate sensing techniques. We also create a reduced-order simulation environment to develop autonomous trenching controllers via reinforcement learning and prototype state estimation architectures. Our initial results suggest that excavated regolith mass can be inferred within 2.9% RMS error of full scale, and reinforcement learning for autonomous operations has learned viable trenching strategies and helped identify desirable sensing capabilities, arrangements, and considerations. Future work includes regolith mass estimation during dynamic operation, expanding our simulation to more complex environments, and transfer learning from simulation to hardware.

machine learning↗
NASA NTRSDate not supplied

ICE-RASSOR: Intelligent Capabilities Enhanced Regolith Advanced Surface Systems Operations Robot

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU) processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from on-board sensory. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We apply supervised learning using real data to estimate the soil mass collected without the need for mass flow rate monitors or other explicate sensing techniques. We also create a reduced-order simulation environment to develop autonomous trenching controllers via reinforcement learning and proto-type state estimation architectures. Our initial results suggest that excavated regolith mass can be inferred within 2.9% RMS error of full scale, and reinforcement learning for autonomous operations has learned viable trenching strategies and helped identify desirable sensing capabilities, arrangements, and considerations. Future work includes regolith mass estimation during dynamic operation, expanding our simulation to more complex environments, and transfer learning from simulation to hardware.

machine learning↗
NASA NTRSDate not supplied

Overview and Performance of the LOFTID Instrumentation Suite

NASA’s Hypersonic Inflatable Aerodynamic Decelerator (HIAD) is an enabling technology that facilitates atmospheric entry of heavy payloads to planets such as Earth and Mars using a deployable aeroshell. The deployable nature of the HIAD technology allows it to overcome the size constraints imposed on current rigid aeroshell entry systems. This enables use of larger aeroshells resulting in increased entry system performance (e.g. higher payload mass and/or volume, higher landing altitude at Mars). On November 10th, 2022 the Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) was launched out of Vandenberg Air Force Base as a secondary payload on an Atlas V rocket. After the primary payload was delivered to its orbit, the LOFTID reentry vehicle was inflated, positioned, and then separated to reenter Earth’s atmosphere at a velocity of 8.1km/s, ultimately splashing down safely in the Pacific Ocean. The flight successfully demonstrated a 6m diameter, 70-deg sphere-cone HIAD on a high-energy orbital reentry. This demonstration has provided invaluable fight data essential to characterize the vehicle performance and support the ongoing effort to further scale the HIAD technology to vehicles of 10m in diameter or greater. Aeroshells of this scale are applicable to near-term commercial applications and future NASA robotic and human exploration missions. LOFTID incorporated an extensive instrumentation suite totaling over 150 science measurements. This included thermocouples, total heat flux sensors, and a radiometer to characterize the aeroheating environment and aeroshell thermal response. An Inertial Measurement Unit (IMU), Global Positioning System (GPS), and flush air data system was included to allow post-flight reconstruction of the vehicle trajectory including a decoupling of the aerodynamics from the atmospheric density. Loadcells were used to measure HIAD structural response during entry, and cameras (both visual-spectrum and infrared) were mounted on the aft segment looking at the aeroshell to monitor structural deflection and surface temperature distribution. Finally, a single up-look camera was included which has provided a surprising amount of science potential from the spectacular footage. In addition to the primary instrumentation suite, a new Fiber Optic Sensing System (FOSS) was used to provide global temperature distributions as a technology demonstration. The system provided over 200 thermal measurements creating a thermal map for the backside of the nose Flexible Thermal Protection System. Another pair of FOSS cables were run along the rigid center structure and measured the temperature response to the vehicle wake environment. The LOFTID instrumentation suite leveraged Agency-wide expertise, with hardware development occurring at Ames Research Center, Langley Research Center, Marshall Space Flight Center, and Armstrong Flight Research Center. This presentation will discuss the instrumentation selected for LOFTID to capture the HIAD performance during the high-energy orbital reentry flight test, provide examples of data products, and snippets of the spectacular reentry video.

G T Swanson↗
NASA NTRSDate not supplied

Overview and Performance of the LOFTID Instrumentation Suite

NASA’s Hypersonic Inflatable Aerodynamic Decelerator (HIAD) is an enabling technology that facilitates atmospheric entry of heavy payloads to planets such as Earth and Mars using a deployable aeroshell. The deployable nature of the HIAD technology allows it to overcome the size constraints imposed on current rigid aeroshell entry systems. This enables use of larger aeroshells resulting in increased entry system performance (e.g. higher payload mass and/or volume, higher landing altitude at Mars). On November 10th, 2022 the Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) was launched out of Vandenberg Air Force Base as a secondary payload on an Atlas V rocket. After the primary payload was delivered to its orbit, the LOFTID reentry vehicle was inflated, positioned, and then separated to reenter Earth’s atmosphere at a velocity of 8.1km/s, ultimately splashing down safely in the Pacific Ocean. The flight successfully demonstrated a 6m diameter, 70-deg sphere-cone HIAD on a high-energy orbital reentry. This demonstration has provided invaluable fight data essential to characterize the vehicle performance and support the ongoing effort to further scale the HIAD technology to vehicles of 10m in diameter or greater. Aeroshells of this scale are applicable to near-term commercial applications and future NASA robotic and human exploration missions. LOFTID incorporated an extensive instrumentation suite totaling over 150 science measurements. This included thermocouples, total heat flux sensors, and a radiometer to characterize the aeroheating environment and aeroshell thermal response. An Inertial Measurement Unit (IMU), Global Positioning System (GPS), and flush air data system was included to allow post-flight reconstruction of the vehicle trajectory including a decoupling of the aerodynamics from the atmospheric density. Loadcells were used to measure HIAD structural response during entry, and cameras (both visual-spectrum and infrared) were mounted on the aft segment looking at the aeroshell to monitor structural deflection and surface temperature distribution. Finally, a single up-look camera was included which has provided a surprising amount of science potential from the spectacular footage. In addition to the primary instrumentation suite, a new Fiber Optic Sensing System (FOSS) was used to provide global temperature distributions as a technology demonstration. The system provided over 200 thermal measurements creating a thermal map for the backside of the nose Flexible Thermal Protection System. Another pair of FOSS cables were run along the rigid center structure and measured the temperature response to the vehicle wake environment. The LOFTID instrumentation suite leveraged Agency-wide expertise, with hardware development occurring at Ames Research Center, Langley Research Center, Marshall Space Flight Center, and Armstrong Flight Research Center. This paper will discuss the instrumentation selected for LOFTID, a summary of sensor in-flight performance, and will provide examples of data products from the post-flight analysis effort.

Gregory T Swanson↗
NASA NTRSDate not supplied

Overview and Performance of the LOFTID Instrumentation Suite

NASA’s Hypersonic Inflatable Aerodynamic Decelerator (HIAD) is an enabling technology that facilitates atmospheric entry of heavy payloads to planets such as Earth and Mars using a deployable aeroshell. The deployable nature of the HIAD technology allows it to overcome the size constraints imposed on current rigid aeroshell entry systems. This enables use of larger aeroshells resulting in increased entry system performance (e.g. higher payload mass and/or volume, higher landing altitude at Mars). On November 10th, 2022 the Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) was launched out of Vandenberg Air Force Base as a secondary payload on an Atlas V rocket. After the primary payload was delivered to its orbit, the LOFTID reentry vehicle was inflated, positioned, and then separated to reenter Earth’s atmosphere at a velocity of 8.1km/s, ultimately splashing down safely in the Pacific Ocean. The flight successfully demonstrated a 6m diameter, 70-deg sphere-cone HIAD on a high-energy orbital reentry. This demonstration has provided invaluable fight data essential to characterize the vehicle performance and support the ongoing effort to further scale the HIAD technology to vehicles of 10m in diameter or greater. Aeroshells of this scale are applicable to near-term commercial applications and future NASA robotic and human exploration missions. LOFTID incorporated an extensive instrumentation suite totaling over 150 science measurements. This included thermocouples, total heat flux sensors, and a radiometer to characterize the aeroheating environment and aeroshell thermal response. An Inertial Measurement Unit (IMU), Global Positioning System (GPS), and flush air data system was included to allow post-flight reconstruction of the vehicle trajectory including a decoupling of the aerodynamics from the atmospheric density. Loadcells were used to measure HIAD structural response during entry, and cameras (both visual-spectrum and infrared) were mounted on the aft segment looking at the aeroshell to monitor structural deflection and surface temperature distribution. Finally, a single up-look camera was included which has provided a surprising amount of science potential from the spectacular footage. In addition to the primary instrumentation suite, a new Fiber Optic Sensing System (FOSS) was used to provide global temperature distributions as a technology demonstration. The system provided over 200 thermal measurements creating a thermal map for the backside of the nose Flexible Thermal Protection System. Another pair of FOSS cables were run along the rigid center structure and measured the temperature response to the vehicle wake environment. The LOFTID instrumentation suite leveraged Agency-wide expertise, with hardware development occurring at Ames Research Center, Langley Research Center, Marshall Space Flight Center, and Armstrong Flight Research Center. This paper will discuss the instrumentation selected for LOFTID, a summary of sensor in-flight performance, and will provide examples of data products from the post-flight analysis effort.

Greg Swanson↗
NASA NTRS1994

Telemetry distribution and processing for the second German Spacelab Mission D-2

For the second German Spacelab Mission D-2 all activities related to operating, monitoring and controlling the experiments on board the Spacelab were conducted from the German Space Operations Control Center (GSOC) operated by the Deutsche Forschungsanstalt fur Luft- und Raumfahrt (DLR) in Oberpfaffenhofen, Germany. The operational requirements imposed new concepts on the transfer of data between Germany and the NASA centers and the processing of data at the GSOC itself. Highlights were the upgrade of the Spacelab Data Processing Facility (SLDPF) to real time data processing, the introduction of packet telemetry and the development of the high-rate data handling front end, data processing and display systems at GSOC. For the first time, a robot on board the Spacelab was to be controlled from the ground in a closed loop environment. A dedicated forward channel was implemented to transfer the robot manipulation commands originating from the robotics experiment ground station to the Spacelab via the Orbiter's text and graphics system interface. The capability to perform telescience from an external user center was implemented. All interfaces proved successful during the course of the D-2 mission and are described in detail in this paper.

Rabenau, E.↗
NASA NTRS2008

Rapid Biochemical Analysis on the International Space Station (ISS): Preparing for Human Exploration of the Moon and Mars

The Lab-on-a-Chip Application Development - Portable Test System, known as LOCAD-PTS, was launched to the International Space Station (ISS) aboard Space Shuttle Discovery (STS-116) on December 9th,2006. Since that time, it has remained onboard ISS and has been operated by the crew on 10 separate occasions LOCAD-PTS is a handheld device for rapid biochemical analysis; it consists of a spectrophotometer, a series of interchangeable cartridges, a pipette and several clean/sterilized swabbing kits to obtain samples from ISS surfaces. Sampling, quantitative analysis and data retrieval is performed onboard, therefore reducing the need to return samples to Earth. Less than 20 minutes are required from sampling to data, significantly faster than existing culture-based methods on ISS, which require 3-5 days. Different cartridges are available for the detection of different target molecules (simply by changing the formulation within each cartridge), thereby maximizing the benefit and applications addressed by a single instrument. Initial tests on ISS have focused on the detection of the bact.erial macromolecule endotoxin, a component of bacterial cell walls. LOCAD-PTS detects endotoxin with a cartridge that contains a formulation known as Limulus Amebocyte Lysate (LAL) assay. LAL is derived from blood of the horseshoe crab, Limulus polyphemus, and detects enodotoxin with an enzyme cascade that triggers generation Of a yellow colored dye, p-nitroanaline. The more p-nitroanaline product, the more endotoxin is in the original sample. To enable quantitative analysis, the absorbance of this color is measured by LOCAD-PTS through a 395 nm filter and compared with an internal calibration curve, to provide a reading on the LED display that ranges from 0.05 Endotoxin Units (EU)/ml to 5 EU/ml. Several surface sites were analyzed within ISS between March 2007 and February 2008, including multiple locations in the US Laboratory Destiny, Node 1 Unity, AMock, and Service Module Zvezda. The goals of this initial study were to i) test the cleanliness of reagents/supplies on orbit, ii) test the crew's ability to collect and process a sample in microgravity without contamination, iii) demonstrate nominal function of the LOCAD-PTS, and iv) provide a general survey of endotoxin within the ISS. The surface sites varied greatly in terms of their frequency-of-use and material texture/composition; from relatively smooth aluminum, to fabric, to the room temperature vulcanizing (RTV) rubber of a Extravehicular Mobility Unit (EMU) spacesuit. Results showed that: i) the swabbing kits and reagents remained clean on orbit, ii) the crew could collect and process a sample without contamination, and iii) the LOCAD-PTS functioned nominally in > 99% of the 55 tests completed. We will present detailed results of the survey of endotoxin on ISS surfaces. These results and technology are important in the near-term - by providing an extra tool in the toolbox for ISS microbial monitoring. They are also important in the longer term as valuable preparation for human exploration of the Moon and Mars. One of the proposed science goals for the human exploration of Mars will be to detect and characterize any indigenous biological molecules that may exist on the Martian surface. To achieve that goal, the crew must have the technology available onboard to differentiate indigenous biology from any terrestrial biological material brought to Mars by the spacecraft and crew (termed 'forward contamination'). The LAL assay is already one of the official methods used by NASA's planetary protection program to certify cleanliness of interplanetary robotic spacecraft prior to launch; and therefore endotoxin is a good marker of forward contamination (as well as other microbial molecules detectable with LOCAD-PTS e.g. box-1, 3-glucan and lipoteichoic acid). Furthermore, the distribution and abundance of these molecules on the ISS provides a good indicator of what to expect on the Crew Exploratioehicle Orion, the lunar lander Antares, and future crewed spacecraft destined for Mars. In addition, technology such as LOCAD-PTS has been proposed to help evaluate forward contamination during lunar surface operations by the crew, as preparation for the human exploration of Mars.

Maule, J.↗
NASA NTRSDate not supplied

ICE-RASSOR: Intelligent Capabilities Enhanced

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU) processing. RAS-SOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar sur-face, RASSOR software and sensory systems need to be robust and maximize the information extracted from on-board sensing. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We apply supervised learning using real data to estimate the soil mass collected without the need for mass flow rate monitors or other explicate sensing techniques. We also create a reduced-order simulation environment to develop autonomous trenching controllers via reinforcement learning and proto-type state estimation architectures. Our initial results suggest that excavated regolith mass can be inferred within 2.9% RMS error of full scale, and reinforcement learning for autonomous operations has learned viable trenching strategies and helped identify desirable sensing capabilities, arrangements, and considerations. Future work includes regolith mass estimation during dynamic operation, expanding our simulation to more complex environments, and transfer learning from simulation to hardware.

machine learning↗
NASA NTRS1999

Information Technology and the Autonomous Control of a Mars In-Situ Propellant Production System

With the rapidly increasing performance of information technology, i.e., computer hardware and software systems, as well as networks and communication systems, a new capability is being developed that holds the clear promise of greatly increased exploration capability, along with dramatically reduced design, development, and operating costs. These new intelligent systems technologies, utilizing knowledge-based software and very high performance computer systems, will provide new design and development tools, scheduling mechanisms, and vehicle and system health monitoring capabilities. In addition, specific technologies such as neural nets will provide a degree of machine intelligence and associated autonomy which has previously been unavailable to the mission and spacecraft designer and to the system operator. One of the most promising applications of these new information technologies is to the area of in situ resource utilization. Useful resources such as oxygen, compressed carbon dioxide, water, methane, and buffer gases can be extracted and/or generated from planetary atmospheres, such as the Martian atmosphere. These products, when used for propulsion and life-support needs can provide significant savings in the launch mass and costs for both robotic and crewed missions. In the longer term the utilization of indigenous resources is an enabling technology that is vital to sustaining long duration human presence on Mars. This paper will present the concepts that are currently under investigation and development for mining the Martian atmosphere, such as temperature-swing adsorption, zirconia electrolysis etc., to create propellants and life-support materials. This description will be followed by an analysis of the information technology and control needs for the reliable and autonomous operation of such processing plants in a fault tolerant manner, as well as the approach being taken for the development of the controlling software. Finally, there will be a brief discussion of the verification and validation process so crucial to the implementation of mission-critical software.

Gross, Anthony R.↗