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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 NTRS2023

NASA's Center Innovation Fund (CIF) Internal Research and Development (IRAD) Handling Qualities Study on the Mikrolar Motion Platform Test Report

In order to support the National Aeronautics and Space Administration’s (NASA) Extravehicular Activity and Surface Mobility Program (EHP), system engineers, designers, and researchers embarked on a yearlong challenge to develop a new lunar rover-based motion table simulator to study handling qualities of lunar rovers in the lunar South Pole region, support development research for any lunar rover vendor, and provide a lunar training capability for future lunar/planetary astronauts. In 1989, the United Kingdom’s Royal Air Force Institute of Aviation Medicine (RAF-IAM) stated that motion platforms are the only simulation devices capable of fully stimulating the body motion sensors. They confirmed that motion platforms can impart accelerations to the whole body and therefore exercise the automatic motion feedback-loop that operators are used to. With both visual and motion cues handling the vehicle becomes more realistic. Strachan (2019) con-firms motion cueing from a well set-up motion platform has been found to be important especially in conditions such as night or reduced visibility where motion cues may be more relied upon

Motion Table↗
NASA NTRS2016

The Mass Index and Total Mass of the Geminid Meteoroid Stream as Found with Radar, Optical, and Lunar Impact Data

The Geminid meteor shower was observed in 2015 using the Western Meteor Physics Group’s Canadian Meteor Orbit Radar (CMOR), Marshall Space Flight Center’s (MSFC) eight wide-field optical cameras, and MSFC’s lunar impact monitoring. These observations allowed Geminid fluxes to be calculated in three unique mass-ranges, from 1.8 (exponent -4) grams to 30 grams. From these fluxes, a mass index of 1.68 plus or minus 0.04 is found, which is in excellent agreement with past Geminid mass indices such as 1.69 found by Blaauw et al using only radar data and 1.7 found by Arlt and Rendtel using visual data. This mass index, however, is found over five orders of magnitude of mass, which allows a higher level of confidence that this mass index holds over a large portion of the stream. Mass indices are an important quantity to be accurately measured for a shower, indicating the distribution of mass in a well-studied stream in which we know the parent body (3200 Phaethon), improving forecasts of the shower activity, and allow fluxes to be scaled to high and low masses. The quantities derived here, along with a profile of the Geminid meteor shower activity in 2015 from CMOR, permit the total Geminid mass the Earth encountered in 2015 to be found, along with a minimum total mass of the Geminid meteoroid stream. Attempts have been made in the past to measure the mass of meteoroid streams using Zenithal Hourly Rate (ZHR) profiles, but here this new and improved treatment uses empirically derived fluxes and measured mass indices for the 2015 encounter with the meteoroid stream. This is to be compared with other meteoroid stream mass estimates including that of the Perseids, caused by comet Swift Tuttle.

Blaauw, R.↗
NASA NTRS2018

Overview of the Digitization Workflow Post Image Acquisition of Apollo Lunar and Antarctic Meteorite Samples Using Agisoft Photoscan for the NASA 3D Astromaterials Virtual Samples Collection

The 3D Virtual Astromaterials Samples (3DVAS) collection is a multi-year funded project to create a digital database of sixty Apollo Lunar and Antarctic Meteorite samples following non-destructive documentation conservation protocols. After initial image processing, the photos are evaluated and processed using unique structure-from-motion photogrammetric techniques in a high performance modelling software designed to create a 3D model from 2D images: Agisoft Photoscan Pro. Agisoft Photoscan Pro uses image processing algorithms and techniques originating in computer vision to resolve 3D models for accurate and detailed visualization of a subject. The software provides a stepwise process that is tailored per model based on spatial and specular reflectance properties, for example. The process includes: photo alignment, creation of a dense point cloud, mesh, and finally texture. Photo alignment is dependent on model properties. The 3DVAS process requires a special rotation platform with calibrated photogrammetric targets, specific distance rotation protocols, and a contrasting background for alignment and scale accuracy. As a result of the photographic process, alignment will complete with two mirrored hemispheres that, in a sense, represent the 2D images overlapping to create a 3D model. Each dense point cloud is analyzed with provided statistical measures in a gradual selection process to eliminate outliers. The point cloud is reduced to include only data valuable to the final model. When a precise dense point cloud is achieved, a mesh and texture are applied. Each model is scaled with scale bar accuracies within 100 microns. Each sample has its own intimate process for modelling; there is no standard for the parameters required in the final creation of a high resolution model. By processing multiple samples, a skill is gained in practice to allow a close definition of the original sample and will result in the most detailed version of the sample shell. This process completes one-fifth of the 3DVAS protocol for providing accurate digital documentation. Each model shell is merged with X-ray Computed Tomography data to create a full volumetric sample. All 3DVAS data will be served on NASA's Astromaterials Acquisition and Curation website with an early subset of data available in 2019 and the 3D Virtual Astromaterials Samples Collection launch in 2020.

Thomas, Andi B.↗
NASA NTRS2009

Developments to Increase the Performance, Operational Versatility and Automation of a Lunar Surface Manipulation System

The objective of this paper is to describe and summarize the results of the development efforts for the Lunar Surface Manipulation System (LSMS) with respect to increasing the performance, operational versatility, and automation. Three primary areas of development are covered, including; the expansion of the operational envelope and versatility of the current LSMS test-bed, the design of a second generation LSMS, and the development of automation and remote control capability. The first generation LSMS, which has been designed, built, and tested both in lab and field settings, is shown to have increased range of motion and operational versatility. Features such as fork lift mode, side grappling of payloads, digging and positioning of lunar regolith, and a variety of special end effectors are described. LSMS operational viability depends on bei nagble to reposition its base from an initial position on the lander to a mobility chassis or fixed locations around the lunar outpost. Preliminary concepts are presented for the second generation LSMS design, which will perform this self-offload capability. Incorporating design improvements, the second generation will have longer reach and three times the payload capability, yet it will have approximately equivalent mass to the first generation. Lastly, this paper covers improvements being made to the control system of the LSMS test-bed, which is currently operated using joint velocity control with visual cues. These improvements include joint angle sensors, inverse kinematics, and automated controls.

Dorsey, John T.↗
NASA NTRS2012

NASA Tech Briefs, April 2012

Topics include: Computational Ghost Imaging for Remote Sensing; Digital Architecture for a Trace Gas Sensor Platform; Dispersed Fringe Sensing Analysis - DFSA; Indium Tin Oxide Resistor-Based Nitric Oxide Microsensors; Gas Composition Sensing Using Carbon Nanotube Arrays; Sensor for Boundary Shear Stress in Fluid Flow; Model-Based Method for Sensor Validation; Qualification of Engineering Camera for Long-Duration Deep Space Missions; Remotely Powered Reconfigurable Receiver for Extreme Environment Sensing Platforms; Bump Bonding Using Metal-Coated Carbon Nanotubes; In Situ Mosaic Brightness Correction; Simplex GPS and InSAR Inversion Software; Virtual Machine Language 2.1; Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction; Pandora Operation and Analysis Software; Fabrication of a Cryogenic Bias Filter for Ultrasensitive Focal Plane; Processing of Nanosensors Using a Sacrificial Template Approach; High-Temperature Shape Memory Polymers; Modular Flooring System; Non-Toxic, Low-Freezing, Drop-In Replacement Heat Transfer Fluids; Materials That Enhance Efficiency and Radiation Resistance of Solar Cells; Low-Cost, Rugged High-Vacuum System; Static Gas-Charging Plug; Floating Oil-Spill Containment Device; Stemless Ball Valve; Improving Balance Function Using Low Levels of Electrical Stimulation of the Balance Organs; Oxygen-Methane Thruster; Lunar Navigation Determination System - LaNDS; Launch Method for Kites in Low-Wind or No-Wind Conditions; Supercritical CO2 Cleaning System for Planetary Protection and Contamination Control Applications; Design and Performance of a Wideband Radio Telescope; Finite Element Models for Electron Beam Freeform Fabrication Process Autonomous Information Unit for Fine-Grain Data Access Control and Information Protection in a Net-Centric System; Vehicle Detection for RCTA/ANS (Autonomous Navigation System); Image Mapping and Visual Attention on the Sensory Ego-Sphere; HyDE Framework for Stochastic and Hybrid Model-Based Diagnosis; and IMAGESEER - IMAGEs for Education and Research.

Source record↗
NASA NTRSDate not supplied

GeneLab: Current and Future Omics Data Integration Between Space Biology and HRP

For the past five years, the Biological and Physical Sciences Division has pioneered Open Science in Space Biology by funding the NASA GeneLab project. Along with the Ames Life Sciences Data Archive, GeneLab has quickly become the world leader in archiving and scientifically curating spaceflight and spaceflight relevant multi-omics data. Specifically, the GeneLab Data System has become a full enterprise solution providing advanced mining capabilities, several application programming interfaces for data federation and machine learning approaches, and delivering to the world an analytical and visualization platform which has enabled collaboration within the scientific community. Over the past three years, large meta-analysis and modeling studies have been published by the GeneLab Analysis Working Groups (AWGs), which are comprised of ~200 volunteer scientists. One natural extension of GeneLab data reuse has recently turned towards linking animal data with human data, which is the next necessary step to further validate animal models for inferring biological risks to humans conducting LEO, lunar or Martian missions. As such, data from the Human Research Program are an essential component of GeneLab and ALSDA. At the moment, simulated space radiation experiments conducted at Brookhaven National Laboratory make the most of HRP GeneLab data, and the scientific community has been eager to also link their animal spaceflight results to actual Astronaut data and human analog data. We will discuss further the current status of knowledge and future approaches to accelerate our basics understanding of the impact of space stressors on humans using latest omics technology.

omics↗
NASA NTRSDate not supplied

Results of the Field Test and Defining Sensormotor Fitness for Duty Standards

The primary goals of the Field Test were (1) to determine functional abilities associated with long-duration space flight crews beginning as soon after landing as possible (< 2 hours), and (2) to characterize the time course of recovery with additional follow-up measurement sessions within 24 hours after landing. The NASA and Russian teams have collected data on a total of 39 different United States Orbital Segment (USOS) and Russian crewmembers, with 9 Russian crewmembers being tested twice (total of 48 tests). Eighteen subjects (7 Russian, 11 USOS) completed a reduced Field Test (pilot) protocol and 30 subjects (19 Russian and 11 USOS) participated in the full Field Test. This presentation will focus on a subset of the measures that will be used in the upcoming ground study to determine sensorimotor fitness for duty standards, namely: tandem walk, obstacle walk, eye-hand coordination task, finger-to-nose task, and Computerized Dynamic Posturography (CDP). Exploration-class missions including Artemis, Gateway, and beyond will require a new level of autonomy around periods of gravitational transition, where sensorimotor disturbances increase. The operational support that is available upon return to Earth including rescue teams, medical interventions, and the ability to rest as needed will not be available after landing on the lunar or Martian surface. Because of this, there is a need to define fitness for duty standards that will help inform crew capabilities during and soon after gravitational transitions. Due to the new requirements of the exploration environment, we must utilize a set of exploration field measures, for which no previous spaceflight data exists to define fitness for duty standards. A Sensorimotor Adaptation Analog (SAA) that can provide different levels of acute disorientation through combined vestibular, visual, and proprioceptive disruptions will be used to increase the range of performance in exploration field measures, simulating the moderate-to-severe performance decrements observed in spaceflight. The levels of SAA will be titrated and validated by comparison to gold standard measures that have a wealth of spaceflight data at different time points during recovery. These data will be pulled directly from the results of Field Test and help ensure the range of performance while being exposed to SAA mimics the range of performance from pre-flight to immediately postflight in Field Test subjects. Specifically, we will be using the tandem walk, obstacle walk, eye-hand coordination task, finger-to-nose task, and CDP as the gold standard measures. Referencing this Field Test data in the form of gold standard measures will also help us characterize and contextualize how each magnitude of SAA disorientation compares to recovery from long-term microgravity exposure.

M J F Rosenberg↗
NASA NTRS2017

A New Architecture for Visualization: Open Mission Control Technologies

Open Mission Control Technologies (MCT) is a new architecture for visualisation of mission data. Driven by requirements for new mission capabilities, including distributed mission operations, access to data anywhere, customization by users, synthesis of multiple data sources, and flexibility for multi-mission adaptation, Open MCT provides users with an integrated customizable environment. Developed at NASAs Ames Research Center (ARC), in collaboration with NASAs Advanced Multimission Operations System (AMMOS) and NASAs Jet Propulsion Laboratory (JPL), Open MCT is getting its first mission use on the Jason 3 Mission, and is also available in the testbed for the Mars 2020 Rover and for development use for NASAs Resource Prospector Lunar Rover. The open source nature of the project provides for use outside of space missions, including open source contributions from a community of users. The defining features of Open MCT for mission users are data integration, end user composition and multiple views. Data integration provides access to mission data across domains in one place, making data such as activities, timelines, telemetry, imagery, event timers and procedures available in one place, without application switching. End user composition provides users with layouts, which act as a canvas to assemble visualisations. Multiple views provide the capability to view the same data in different ways, with live switching of data views in place. Open MCT is browser based, and works on the desktop as well as tablets and phones, providing access to data anywhere. An early use case for mobile data access took place on the Resource Prospector (RP) Mission Distributed Operations Test, in which rover engineers in the field were able to view telemetry on their phones. We envision this capability providing decision support to on console operators from off duty personnel. The plug-in architecture also allows for adaptation for different mission capabilities. Different data types and capabilities may be added or removed using plugins. An API provides a means to write new capabilities and to create data adaptors. Data plugins exist for mission data sources for NASA missions. Adaptors have been written by international and commercial users. Open MCT is open source. Open source enables collaborative development across organizations and also makes the product available outside of the space community, providing a potential source of usage and ideas to drive product design and development. The combination of open source with an Apache 2 license, and distribution on GitHub, has enabled an active community of users and contributors. The spectrum of users for Open MCT is, to our knowledge, unprecedented for mission software. In addition to our NASA users, we have, through open source, had users and inquires on projects ranging from Internet of Things, to radio hobbyists, to farming projects. We have an active community of contributors, enabling a flow of ideas inside and outside of the space community.

Trimble, Jay↗
NASA NTRS2015

Attitude Design for the LADEE Mission

The Lunar Atmosphere and Dust Environment Explorer (LADEE) satellite successfully completed its 148-day science investigation in a low-altitude, near-equatorial lunar orbit on April 18, 2014. The LADEE spacecraft was built, managed and operated by NASA's Ames Research Center (ARC). The Mission Operations Center (MOC) was located at Ames and was responsible for activity planning, command sequencing, trajectory and attitude design, orbit determination, and spacecraft operations. The Science Operations Center (SOC) was located at Goddard Space Flight Center and was responsible for science planning, data archiving and distribution. This paper details attitude design and operations support for the LADEE mission. LADEE's attitude design was shaped by a wide range of instrument pointing requirements that necessitated regular excursions from the baseline one revolution per orbit "Ram" attitude. Such attitude excursions were constrained by a number of flight rules levied to protect instruments from the Sun, avoid geometries that would result in simultaneous occlusion of LADEE's two star tracker heads, and maintain the spacecraft within its thermal and power operating limits. To satisfy LADEE's many attitude requirements and constraints, a set of rules and conventions was adopted to manage the complexity of this design challenge and facilitate the automation of ground software that generated pointing commands spanning multiple days of operations at a time. The resulting LADEE Flight Dynamics System (FDS) that was developed used Visual Basic scripts that generated instructions to AGI's Satellite Tool Kit (STK) in order to derive quaternion commands at regular intervals that satisfied LADEE's pointing requirements. These scripts relied heavily on the powerful "align and constrain" capability of STK's attitude module to construct LADEE's attitude profiles and the slews to get there. A description of the scripts and the attitude modeling they embodied is provided. One particular challenge analysts faced was in the design of LADEE maneuver attitudes. A flight rule requiring pre-maneuver verification of in-flight maneuver conditions by ground operators prior to burn execution resulted in the need to accommodate long periods in the maneuver attitude. This in turn complicated efforts to satisfy star tracker interference and communication constraints in lunar orbit. In response to this challenge, a graphical method was developed and used to survey candidate rotation angles about the thrust vector. This survey method is described and an example of its use on a particular LADEE maneuver is discussed. Finally, the software and methodology used to satisfy LADEE's attitude requirements are also discussed in the context of LADEE's overall activity planning effort. In particular, the way in which strategic schedules of instrument and engineering activities were translated into actual attitude profiles at the tactical level, then converted into precise quaternion commands to achieve those pointing goals is explained. In order to reduce the risk of time-consuming re-planning efforts, this process included the generation of long-term projections of constraint violation predictions for individual attitude profiles that could be used to establish keep-out time-frames for particular attitude profiles. The challenges experienced and overall efficacy of both the overall LADEE ground system and the attitude components of the Flight Dynamics System in meeting LADEE's varied pointing requirements are discussed.

LADEE↗
NASA NTRS2009

Lunar Landing Trajectory Design for Onboard Hazard Detection and Avoidance

The Autonomous Landing and Hazard Avoidance Technology (ALHAT) Project is developing the software and hardware technology needed to support a safe and precise landing for the next generation of lunar missions. ALHAT provides this capability through terrain-relative navigation measurements to enhance global-scale precision, an onboard hazard detection system to select safe landing locations, and an Autonomous Guidance, Navigation, and Control (AGNC) capability to process these measurements and safely direct the vehicle to a landing location. This paper focuses on the key trajectory design issues relevant to providing an onboard Hazard Detection and Avoidance (HDA) capability for the lander. Hazard detection can be accomplished by the crew visually scanning the terrain through a window, a sensor system imaging the terrain, or some combination of both. For ALHAT, this hazard detection activity is provided by a sensor system, which either augments the crew s perception or entirely replaces the crew in the case of a robotic landing. Detecting hazards influences the trajectory design by requiring the proper perspective, range to the landing site, and sufficient time to view the terrain. Following this, the trajectory design must provide additional time to process this information and make a decision about where to safely land. During the final part of the HDA process, the trajectory design must provide sufficient margin to enable a hazard avoidance maneuver. In order to demonstrate the effects of these constraints on the landing trajectory, a tradespace of trajectory designs was created for the initial ALHAT Design Analysis Cycle (ALDAC-1) and each case evaluated with these HDA constraints active. The ALHAT analysis process, described in this paper, narrows down this tradespace and subsequently better defines the trajectory design needed to support onboard HDA. Future ALDACs will enhance this trajectory design by balancing these issues and others in an overall system design process.

Paschall, Steve↗
NASA NTRS2008

Cammp Team

The International Space Station (ISS) Configuration Analysis Modeling and Mass Properties (CAMMP) Team is presenting a demo of certain CAMMP capabilities at a Booz Allen Hamilton conference in San Antonio. The team will be showing pictures of low fidelity, simplified ISS models, but no dimensions or technical data. The presentation will include a brief description of the contract and task, description and picture of the Topology, description of Generic Ground Rules and Constraints (GGR&C), description of Stage Analysis with constraints applied, and wrap up with description of other tasks such as Special Studies, Cable Routing, etc. The models include conceptual Crew Exploration Vehicle (CEV) and Lunar Lander images and animations created for promotional purposes, which are based entirely on public domain conceptual images from public NASA web sites and publicly available magazine articles and are not based on any actual designs, measurements, or 3D models. Conceptual Mars rover and lander are completely conceptual and are not based on any NASA designs or data. The demonstration includes High Fidelity Computer Aided Design (CAD) models of ISS provided by the ISS 3D CAD Team which will be used in a visual display to demonstrate the capabilities of the Teamcenter Visualization software. The demonstration will include 3D views of the CAD models including random measurements that will be taken to demonstrate the measurement tool. A 3D PDF file will be demonstrated of the Blue Book fidelity assembly complete model with no vehicles attached. The 3D zoom and rotation will be displayed as well as random measurements from the measurement tool. The External Configuration Analysis and Tracking Tool (ExCATT) Microsoft Access Database will be demonstrated to show its capabilities to organize and track hardware on ISS. The data included will be part numbers, serial numbers, historical, current, and future locations, of external hardware components on station. It includes dates of all external ISS events and flights and the associated hardware changes for each event. The hardware location information does not always reveal the exact location of the hardware, only the general location. In some cases the location is a module or carrier, in other cases it is a WIF socket, handrail, or attach point. Only small portions of the data will be displayed for demonstration purposes.

Evertt, Shonn F.↗
NASA NTRSDate not supplied

ISRU Pilot Excavator - Development of Autonomous Excavation Algorithms

The ISRU Pilot Excavator (IPEx) is a Space Technology Mission Directorate (STMD) Game Changing Development (GCD) project to develop a robotic excavator to demonstrate excavation of up to 10 metric tons of lunar regolith. IPEx is based on the Regolith Advanced Surface Systems Operations Robot (RASSOR) excavator developed at NASA Kennedy Space Center (KSC) and utilizes a counter rotating bucket drum concept to balance excavation forces for use on reduced gravity planetary bodies. To take advantage of the counter rotating bucket drum mechanism, work is being done to develop new autonomous excavation strategies and algorithms. Referred to as “Auto-dig”, these algorithms will allow IPEx to excavate, drive, and deliver its target mass of 10 metric tons of lunar regolith during an 11-day mission semi-autonomously. Due to bandwidth and latency constraints teleoperation will be kept to a minimum, with operators periodically confirming and verifying the excavator’s high-level tasks and operations. While the work to develop optimized autodig solutions is ongoing at KSC, early tests have yielded interesting results that have led to the discovery of additional risks that need to be mitigated in autonomous excavation. Testing has also encouraged the development of new software and visualization tools that provide real-time insight into excavation loads during operation, allowing faster development and helping build better intuition to the excavation process. These tools will help in the pursuit to develop fully optimized digging algorithms that are robust enough to handle hazards such as rocks or irregular terrain.

B. C. Buckles↗
NASA NTRS2016

Solar System Exploration Research Virtual Institute: Year Three Annual Report 2016

NASA's Solar System Exploration Research Virtual Institute (SSERVI) is pleased to present the 2016 Annual Report. Each year brings new scientific discoveries, technological breakthroughs, and collaborations. The integration of basic research and development, industry and academic partnerships, plus the leveraging of existing technologies, has further opened a scientific window into human exploration. SSERVI sponsorship by the NASA Science Mission Directorate (SMD) and Human Exploration and Operations Mission Directorate (HEOMD) continues to enable the exchange of insights between the human exploration and space science communities, paving a clearer path for future space exploration. SSERVI provides a unique environment for scientists and engineers to interact within multidisciplinary research teams. As a virtual institute, the best teaming arrangements can be made irrespective of the geographical location of individuals or laboratory facilities. The interdisciplinary science that ensues from virtual and in-person interactions, both within the teams and across team lines, provides answers to questions that many times cannot be foreseen. Much of this research would not be accomplished except for the catalyzing, collaborative environment enabled by SSERVI. The SSERVI Central Office, located at NASA Ames Research Center in Silicon Valley, California, provides the leadership, guidance and technical support that steers the virtual institute. At the start of 2016, our institute had nine U.S. teams, each mid-way through their five-year funding cycle, plus nine international partnerships. However, by the end of the year we were well into the selection of four new domestic teams, selected through NASA's Cooperative Agreement Notice (CAN) process, and a new international partnership. Understanding that human and robotic exploration is most successful as an international endeavor, international partnerships collaborate with SSERVI domestic teams on a no-exchange of funds basis, but they bring a richness to the institute that is priceless. The international partner teams interact with the domestic teams in a number of ways, including sharing students, scientific insights, and access to facilities. We are proud to introduce our newest partnership with the Astrophysics and Planetology Research Institute (IRAP) in Toulouse, France. In 2016, Principal Investigator Dr. Patrick Pinet assembled a group of French researchers who will contribute scientific and technological expertise related to SSERVI research. SSERVI's domestic teams compete for five-year funding opportunities through proposals to a NASA CAN every few years. Having overlapping proposal selection cycles allows SSERVI to be more responsive to any change in direction NASA might experience, while providing operational continuity for the institute. Allowing new teams to blend with the more seasoned teams preserves corporate memory and expands the realm of collaborative possibilities. A key component of SSERVI's mission is to grow and maintain an integrated research community focused on questions related to the Moon, Near-Earth asteroids, and the moons of Mars. The strong community response to CAN-2 demonstrated the health of that effort. NASA Headquarters conducted the peer-review of 22 proposals early in 2017 and, based on recommendations from the SSERVI Central Office and NASA SSERVI program officers, the NASA selecting officials determined the new teams in the spring of 2017. We are pleased to welcome the CAN-2 teams into the institute, and look forward to the collaborations that will develop with the current teams. The new teams are: The Network for Exploration and Space Science (NESS) team (Principal Investigator (PI) Prof. Jack Burns/U. Colorado); the Exploration Science Pathfinder Research for Enhancing Solar System Observations (ESPRESSO) team (PI Dr. Alex Parker/Southwest Research Institute); the Toolbox for Research and Exploration (TREX) team (PI Dr. Amanda Hendrix/ Planetary Science Institute); and the Radiation Effects on Volatiles and Exploration of Asteroids & Lunar Surfaces (REVEALS) team (PI Prof. Thomas Orlando/ Georgia Institute of Technology). In this report, you will find an overview of the 2016 leadership activities of the SSERVI Central Office, reports prepared by the U.S. teams from CAN-1, and achievements from several of the SSERVI international partners. Reflecting on the past year's discoveries and advancements serves as a potent reminder that there is still a great deal to learn about NASA's target destinations. Innovation in the way we access, sample, measure, visualize, and assess our target destinations is needed for further discovery. At the same time, let us celebrate how far we have come, and strongly encourage a new generation that will make the most of future opportunities.

Pendleton, Yvonne↗
NASA NTRSDate not supplied

Biological Data for Deep Space Mission Support

Increased biomedical risks and challenges associated with deep space missions (cis-Lunar, Mars transit, Mars surface) require new knowledge discovery and development of novel ecosystem and biomedical support capabilities. This paradigm shift supporting distant and long-duration missions requires biological data to be findable, accessible, interoperable, reusable (FAIR), and maximally open-access (i.e., there is a data governance continuum from closed to mediated to embargoed to open). The NASA “Open Science Data Repositories” (OSDR) aims to meet scientific, technical, and operational spaceflight needs, and offers the ability to upload, download, search, share, analyze, and visualize data across physiological, behavioral, ‘omics, and environmental monitoring telemetry datasets. OSDR includes NASA GeneLab, NASA Ames Life Sciences Data Archive (ALSDA), and NASA Biological Institutional Scientific Collection (NBISC). In the past year, ALSDA has undergone a transformation in its data collection, curation, and architecture methods. Standardizing non-genomic (phenotypic) datasets was, and will continue to be, a challenge because of their diverse nature (e.g., molecular, cellular, tissue, whole organism behavior; micro-computed tomography, intraocular pressure, fluorescence microscopy, western blot, ultrasonography; tabular, images, video). This year ALSDA, alongside GeneLab, introduced the Biological Data Management Environment (BDME) with the purpose to accept submission of data from space relevant experiments including spaceflight, radiation, simulated gravity, gravitropism, isolation and confinement, hostile closed environments and/or distance from Earth. In addition to bringing together omics, phenotypic, physiological, bioimaging, and behavioral data into one repository. By integrating with GeneLab a multi-project submission portal aims to reduce the burden on PIs submitting data and enabling the discovery of both omics and phenotypic data. The purpose of ALSDA is to collect, curate, and make all non-human space-relevant biological data maximally findable, accessible, interoperable, and reusable (FAIR). These scope of ALSDA data collected and submitted by PIs include study design metadata, subject metadata, assay metadata (parameters), raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). In 2021, a community of researchers rallied to form the ALSDA Analysis Working Group (AWG) and provided scientific consensus on dataset sample and assay metadata. The community and excitement around the ALSDA/OSDR system has already led to several data reuse studies, demonstrating value using machine learning (ML), knowledge graphs, and meta-analysis approaches.

space biology↗
NASA NTRSDate not supplied

Biological Data for Deep Space Mission Support

Increased biomedical risks and challenges associated with deep space missions (cis-Lunar, Mars transit, Mars surface) require new knowledge discovery and development of novel ecosystem and biomedical support capabilities. This paradigm shift supporting distant and long-duration missions requires biological data to be findable, accessible, interoperable, reusable (FAIR), and maximally open-access (i.e., there is a data governance continuum from closed to mediated to embargoed to open). The NASA “Open Science Data Repositories” (OSDR) aims to meet scientific, technical, and operational spaceflight needs, and offers the ability to upload, download, search, share, analyze, and visualize data across physiological, behavioral, ‘omics, and environmental monitoring telemetry datasets. OSDR includes NASA GeneLab, NASA Ames Life Sciences Data Archive (ALSDA), and NASA Biological Institutional Scientific Collection (NBISC). In the past year, ALSDA has undergone a transformation in its data collection, curation, and architecture methods. Standardizing non-genomic (phenotypic) datasets was, and will continue to be, a challenge because of their diverse nature (e.g., molecular, cellular, tissue, whole organism, behavior; micro-computed tomography, intraocular pressure, fluorescence microscopy, western blot, ultrasonography; tabular, images, video). This year ALSDA, alongside GeneLab, introduced the Biological Data Management Environment (BDME) with the purpose to accept submission of data from space relevant experiments including spaceflight, radiation, simulated gravity, gravitropism, isolation and confinement, hostile closed environments and/or distance from Earth. In addition to bringing together omics, phenotypic, physiological, bioimaging, and behavioral data into one repository. By integrating with GeneLab a multi-project submission portal aims to reduce the burden on PIs submitting data and enabling the discovery of both omics and phenotypic data. The purpose of ALSDA is to collect, curate, and make all non-human space-relevant biological data maximally findable, accessible, interoperable, and reusable (FAIR). These scope of ALSDA data collected and submitted by PIs include study design metadata, subject metadata, assay metadata (parameters), raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). In 2021, a community of researchers rallied to form the ALSDA Analysis Working Group (AWG) and provided scientific consensus on dataset sample and assay metadata. The community and excitement around the ALSDA/OSDR system has already led to several data reuse studies, demonstrating value using machine learning (ML), knowledge graphs, and meta-analysis approaches.

space biology↗
NASA NTRS1978

Visual and radiometric photometry of 1580 Betulia

Broadband visual and 10.6-micron photometry of 1580 Betulia was obtained during its close approach to earth in May 1976. The photometry was analyzed by using the 'radiometric method' to derive the radius (2.10 + or - 0.40 km) and albedo (0.108 + or - 0.012) of Betulia. Radar and polarimetric results indicate a radius greater than 3.0 km and a geometric albedo of about 0.05. To be compatible with these results, Betulia was also modeled as having a surface with the thermal characteristics of bare rock rather than those of the 'lunar' regolith model used for previous analysis of radiometry of other asteroids. A 3.7-km radius and a geometric albedo of about 0.04 are compatible with all available observations. Betulia is the first Mars-crossing asteroid found to have such a low albedo, which may be indicative of carbonaceous surface material.

Lebofsky, L. A.↗
NASA NTRS2011

Benefit of "Push-pull" Locomotion for Planetary Rover Mobility

As NASAs exploration missions on planetary terrains become more aggressive, a focus on alternative modes of locomotion for rovers is necessary. In addition to climbing steep slopes, the terrain in these extreme environments is often unknown and can be extremely hard to traverse, increasing the likelihood of a vehicle or robot becoming damaged or immobilized. The conventional driving mode in which all wheels are either driven or free-rolling is very efficient on flat hard ground, but does not always provide enough traction to propel the vehicle through soft or steep terrain. This paper presents an alternative mode of travel and investigates the fundamental differences between these locomotion modes. The methods of push-pull locomotion discussed can be used with articulated wheeled vehicles and are identified as walking or inchinginch-worming. In both cases, the braked non-rolling wheels provide increased thrust. An in-depth study of how soil reacts under a rolling wheel vs. a braked wheel was performed by visually observing the motion of particles beneath the surface. This novel technique consists of driving or dragging a wheel in a soil bin against a transparent wall while high resolution, high-rate photographs are taken. Optical flow software was then used to determine shearing patterns in the soil. Different failure modes were observed for the rolling and braked wheel cases. A quantitative comparison of inching vs. conventional driving was also performed on a full-scale vehicle through a series of drawbar pull tests in the Lunar terrain strength simulant, GRC-1. The effect of tire stiffness was also compared; typically compliant tires provide better traction when driving in soft soil, however its been observed that rigid wheels may provide better thrust when non-rolling. Initial tests indicate up to a possible 40 increase in pull force capability at high slip when inching vs. rolling.

robotics↗
NASA NTRSDate not supplied

Overview of Plume-Surface Interaction Data from Subscale Inert Gas Testing at NASA MSFC Test Stand 300 Vacuum Facilities

Maturation and validation of predictive modeling capabilities for plume-surface interaction, and the effects caused by the impingement of rocket engine exhaust on surface regolith, require relevant, highly characterized ground test data. The multi-phase nature of this problem poses challenges to ground testing across physical scaling, test environments and techniques, and diagnostics. NASA has developed a Physics Focused Ground Test (PFGT) of plume-surface interaction to address this need. The PFGT is a subscale, inert-gas experiment at Mars- and Lunar-relevant ambient pressure conditions that will provide critical data for model validation of cratering, ejecta, and plume physics. In this test, the ambient pressure in a vacuum chamber will be varied, along with the height of a supersonic nozzle above a surface, and the mass flow rate through the nozzle. Testing will be performed on a range of regolith simulants of varying composition and will also include instrumented impingement plate tests in place of regolith simulant to characterize gas-only plume physics. Novel high-speed visual diagnostics will capture temporal data on crater formation and ejecta dynamics, and planar laser-induced fluorescence diagnostics will capture plume structure and behavior. This paper will present an overview of the data collected during this test – for both the cratering and ejecta testing and the gas-only plume physics testing. Emphasis will be placed on trends, effects, and interactions observed in the data across the test parameter space.

Chad J. Eberhart↗