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NASA NTRS2011

Crosscutting Development- EVA Tools and Geology Sample Acquisition

Exploration to all destinations has at one time or another involved the acquisition and return of samples and context data. Gathered at the summit of the highest mountain, the floor of the deepest sea, or the ice of a polar surface, samples and their value (both scientific and symbolic) have been a mainstay of Earthly exploration. In manned spaceflight exploration, the gathering of samples and their contextual information has continued. With the extension of collecting activities to spaceflight destinations comes the need for geology tools and equipment uniquely designed for use by suited crew members in radically different environments from conventional field geology. Beginning with the first Apollo Lunar Surface Extravehicular Activity (EVA), EVA Geology Tools were successfully used to enable the exploration and scientific sample gathering objectives of the lunar crew members. These early designs were a step in the evolution of Field Geology equipment, and the evolution continues today. Contemporary efforts seek to build upon and extend the knowledge gained in not only the Apollo program but a wealth of terrestrial field geology methods and hardware that have continued to evolve since the last lunar surface EVA. This paper is presented with intentional focus on documenting the continuing evolution and growing body of knowledge for both engineering and science team members seeking to further the development of EVA Geology. Recent engineering development and field testing efforts of EVA Geology equipment for surface EVA applications are presented, including the 2010 Desert Research and Technology Studies (Desert RATs) field trial. An executive summary of findings will also be presented, detailing efforts recommended for exotic sample acquisition and pre-return curation development regardless of planetary or microgravity destination.

Source record↗

NASA NTRS2021

An Innovative Approach to Modeling VIPER Rover Software Life Cycle Cost

NASA’s “Volatiles Investigating Polar Exploration Rover” (VIPER) will be the first robotic mission to prospect for water ice near the south pole of the Moon in late 2023 on a 100-Earth-day mission. The information that the VIPER rover provides will help improve understanding of the composition, distribution, and accessibility of Lunar polar volatiles and will help determine how the Moon’s resources can support future human space exploration. VIPER, however, represents a radical departure from the way that NASA has traditionally developed planetary robotic missions. A key consequence of these differences is that estimating the cost of VIPER’s rover software is challenging and complex.For example, VIPER is being developed using management procedures typically applied to NASA research and technology projects, rather than space flight programs. In addition, key portions of the rover’s software are being designed as ground software to run on mission control computers (rather than on-board the rover as flight software as with prior planetary missions) taking advantage of continuous, interactive data communications between the Moon and Earth and higher performance computing available on the ground. Moreover, the rover’s software is being engineered using Agile software development practices and incorporates a significant amount of open-source, rather than following traditional (spiral, waterfall, etc.) development methods and in-house code. In this paper, we present an innovative process to estimate the life cycle cost of VIPER’s rover software. We first describe how we modeled the architecture and code counts for three software elements: Rover Flight Software (RFSW), Rover Ground Software (RGSW), and Rover Simulation Software (RSIM). We then discuss key challenges and unique aspects of our approach, such as the lack of Lunar rover analogies, the need to integrate and test large open source software, and the strategies developed to account for use of non-space flight management practices and the impact of the COVID-19 pandemic. We conclude with a summary of our results, including cumulative distribution, nearest neighbors and cluster analysis, as well as heuristics used to confirm the reasonableness of the cost estimate.

Utz, Hans↗

NASA NTRSDate not supplied

Global 3D Data Visualization and Analysis Platform with Advanced Machine Learning Capabilities in Support of Lunar Exploration

Introduction: The science goals for NASA’s Artemis program include: a) Understanding the character and origin of lunar polar volatiles, b) Conducting experimental science in the lunar environment and c) Investigating and mitigating exploration risks. The permanently shadowed regions (PSRs) on the Lunar south pole are expected to host large quantities of water-ice and volatiles that are important for sustainable Lunar exploration. There are several missions such as onboard Korea Pathfinder Lunar Orbiter (KPLO: Korean name Danuri) with onboard ShadowCam camera, Astrobotic Peregrine Mission One [4], and other efforts underway to obtain high resolution topographic, minerals, volatiles and other information on the moon. We envision a need in immediate future for platforms to integrate these data sets, provide rendering and visualization capabilities in the context of a 3D Lunar globe for easier information access and analysis. NASA's Celestial Mapping System (CMS) is developed to address the need for 3D tools for planetary science investigations, mission planning, in-situ operations, in a 3D-first design constructed around a unified view of a planetary globe. At present CMS provides many critical functionalities that include: 1) equipment planning and optimized placement on Lunar surface 2) line-of-sight (LOS) analysis 3) powerful measurement tools based on 3D terrain with realistic 3D models to represent rovers, astronauts and equipment 4) visualization of derived mapping products (e.g. resource maps), and 5) a data engine for hosting new observations that are not available in other contemporary lunar data tools. Planetary Data Ingestion: CMS can consume and analyze data from locally hosted and external third party sources. It is compatible with Open Geospatial Consortium (OGC) data and file standards and currently integrates datasets from the Astrogeology Science Center of USGS. This includes global and local data acquired from NASA (LRO, Clementine, Lunar Orbiter) and JAXA (SELENE/Kaguya), with capability of integrating more datasets. In addition, users can specify other WMS-hosted data endpoints, which CMS can then query and stream data from automatically. To set-up an automated process for ingestion and accurate rendering, visualization and analysis of external 3rd party planetary datasets within CMS, we initiated the process of ingesting unique dataset of super-enhanced images of the permanently shadowed regions (PSRs) at the lunar poles which were produced by the Hyper-effective nOise Removal U-net Software (HORUS) tool. This tool was developed to enhance the extremely low-light images of the interior of PSRs and provide the ability to see within these regions at and discern surface features (i.e. boulders and craters) down to 3 meters in size. We focused on the Nobile region on the Lunar south pole, selected site for VIPER mission and stitched several images to create a high-resolution map within one of the PSR of Nobile crater. Figure 1 shows the dark PSR zone form the original NAC layer of LRO as the base layer (left image) and the illuminated areas within that crater (center) which was created by ingesting and merging several of HORUS generated images. At present we employ a semi-automated process to ensure spatial accuracy and merger of several overlapping zones. However, we are in the process of completely automating this process by employing AI based techniques that would rank, sort, and stack the images based on their information density. The georectification of the images would employ selected features. Analysis on Ingested Planetary Datasets: Once an external planetary data-set is successfully ingested, georectified and merged seamlessly as a data-layer; CMS’ numerous analysis tools can be used on this data. A Line of Sight (LOS) tool has been developed for CMS which analyzes terrain profiles and obstructions to determine visibility for remote observers. Figure 1 (right image) shows the viewshed analysis on the same PSR in the Nobile region. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. The Measurements tool allows the user to take area and distance measurements of features on the terrain using various shapes. Measurement type can be specified in a number of ways: Line, Path, Polygon, Circle, Ellipse, Square, Rectangle or Freehand. Once the shape is specified, elevation information can then be extracted along each of these shapes. Figure 2 (left) shows the measurements performed on a crater n illuminated PSR in Nobile region. The equipment placement tool allows the user to place a 3D equipment model at a desired location and analyze its coverage area. The equipment placement tool is coupled with LOS to determine the coverage. Figure 2 (right) shows an equipment placed on the Lunar terrain and it’s coverage area. The red rays are blocked sight lines and the green rays are non-obstructed sight lines with the cyan lines showing the point of intersection with the terrain. More details are provided in the video demonstrations in Reference 5. Overcoming Polar Distortions: 3D geospatial applications exhibit significant distortions in polar imagery due to several reasons: 1) distortions in the source imagery, 2) incompatible tessellation algorithms at the poles, and 3) map projections. We are leveraging new tessellation algorithms and reprojecting data using projections that are better suited for Lunar poles. The goal is to seamlessly switch to polar projections while maintaining 3D view and navigation.

Maps↗

NASA NTRSDate not supplied

Unlocking the Mysteries of the Moon’s Shadowed Regions

The Moon poles host large quantities of water-ice deposits in the permanently shadowed regions (PSRs), which are vital for enabling sustainable human space exploration, making these regions high-priority targets for upcoming Artemis missions [1]. Unfortunately, today, the best available orbital lunar imagery [2, 3] lacks the meter-scale resolution and signal needed to understand the geomorphology and trafficability of PSRs, complicating the planning and execution of future missions seeking to explore PSRs. We have developed an image enhancement tool called HORUS (Hyper-effective nOise Removal Unet Software) [4, 5], designed to enhance LRO Narrow-Angle Camera (NAC) optical low-light imagery of permanently shadowed regions by effectively removing the CCD-related, photon, and other residual noises that corrupt the images. The tool is composed of two deep learning neural networks trained on environmental metadata and real and synthetic imagery, the latter generated by a physical noise model (LROC). We demonstrated that HORUS effectively produces low-noise, high-resolution images (~1.5m/px), achieving a 5 to 10x improvement over existing long-exposure images of PSRs. HORUS allows scientists and engineers to identify geomorphic features (e.g., craters and boulders) in shadowed regions as small as 3 meters across as well as to peek inside of small shadowed regions, for the first time. The tool was deployed and thoroughly validated for NASA's VIPER mission [6], where it was applied to 20 candidate target regions across the lunar South Pole. Additionally, we conducted different approaches to validate the resulting HORUS-processed images. With HORUS denoised images, VIPER scientists can increase their confidence on what surface features (previously unseen) exist in the shadowed regions, helping them plan rover traverses more safely and efficiently (e.g., Fig. 1) In this manuscript, we will describe how VIPER scientists are utilizing HORUS denoised images to extract new information from the terrain and increase their confidence in what surface features exist in the shadowed regions. In combination with other high-resolution images and digital elevation maps, HORUS images are helping the team analyze potential lading and science sites, as well as planning traverses more safely and efficiently (e.g., Fig. 1). Additionally, we will describe how HORUS tool unlocks a broad range of scientific and exploration applications to other Artemis and CPLS missions to the lunar poles, including (but not limited to) geomorphic analysis, change detection, surface hazard detection, and terrain relative navigation.

artificial intelligence↗

NASA NTRS2006

Overview of Mars Science Laboratory (MSL) Environmental Program

This viewgraph presentation is an overview of the Mars Science Laboratory (MSL) program. The engineering objectives of the program are to create a Mobile Science Laboratory capable of one Mars Year surface operational lifetime (670 Martian sols = 687 Earth days). It will be able to land and operation over wide range of latitudes, altitudes and seasons It must have controlled propulsive landing and demonstrate improved landing precision via guided entry The general science objectives are to perform science that will focus on Mars habitability, perform next generation analytical laboratory science investigations, perform remote sensing/contact investigations and carry a suite of environmental monitoring instruments. Specific scientific objectives of the MSL are: (1) Characterization of geological features, contributing to deciphering geological history and the processes that have modified rocks and regolith, including the role of water. (2) Determination of the mineralogy and chemical composition (including an inventory of elements such as C, H, N, O, P, S, etc. known to be building blocks for life) of surface and near-surface materials. (3) Determination of energy sources that could be used to sustain biological processes. (4) Characterization of organic compounds and potential biomarkers in representative regolith, rocks, and ices. (5) Determination the stable isotopic and noble gas composition of the present-day bulk atmosphere. (6) Identification potential bio-signatures (chemical, textural, isotopic) in rocks and regolith. (7) Characterization of the broad spectrum of surface radiation, including galactic cosmic radiation, solar proton events, and secondary neutrons. (8) Characterization of the local environment, including basic meteorology, the state and cycling of water and C02, and the near-surface distribution of hydrogen. Several views of the planned MSL and the rover are shown. The MSL environmental program is to: (1) Ensure the flight hardware design is capable of surviving all the environments throughout its mission life time, including ground, transportation, launch, cruise, entry decent and landing (EDL) and surface operation environments. (2) Verify environmental testing and analysis have adequately validated the flight hardware's ability to withstand all natural, self-induced, and mission-activity-induced environments. The planned tests to ascertain the capability of the MSL to perform as desired are reviewed.

spacecraft↗

NASA NTRSDate not supplied

Science, Exploration and the Human Experience.

Dr. Darlene S. Lim is a research scientist at NASA's Ames Research Center in California's Silicon Valley, and the Deputy Project Scientist and Science Operations Lead for NASA's Volatiles Investigating Polar Exploration Rover (VIPER) Lunar Mission. The VIPER lunar rover mission is a mobile robot that will go to the South Pole of the Moon to get a close-up view of the location and concentration of water ice that could eventually be harvested to sustain human exploration on the Moon, Mars — and beyond. VIPER represents the first resource mapping mission on another celestial body and presents a unique operational paradigm within the history of robotic spaceflight. Throughout her career, Darlene has led several NASA-funded programs that have been focused on blending field science research with the development of capabilities and concepts for future human-robotic spaceflight to the Moon and Mars. These research activities have taken her around the world, from pole to pole, land to sea, and to many lakes in between, where she has studied life in extreme environments, the way people conduct science, and how they need to be supported in their work of discovery and exploration. At the center of each of these endeavors is the human - the person who must interact with others, with technology, and with the environment of interest, to apply the scientific method towards the accrual and expansion of knowledge about the planet that we live on and beyond. Darlene has been working with teams of scientists and engineers from a variety of disciplines to hone her understanding of the process by which their interactions and research needs can be supported and enabled under intense operational conditions such as those associated with Moon and Mars exploration. Darlene’s presentation will take the audience through the arc of her research over the past two decades culminating in her on-going work with the NASA VIPER lunar rover mission.

Darlene Sze Shien Lim↗

NASA NTRSDate not supplied

Global 3D Data Visualization and Analysis Platform With Advanced Machine Learning Capabilities in Support of Lunar Exploration

Introduction: The science goals for NASA’s Artemis program include: a) Understanding the character and origin of lunar polar volatiles, b) Conducting experimental science in the lunar environment and c) Investigating and mitigating exploration risks [1]. The permanently shadowed regions (PSRs) on the Lunar south pole are expected to host large quantities of water-ice and volatiles that are important for sustainable Lunar exploration [2]. There are several missions such as onboard Korea Pathfinder Lunar Orbiter (KPLO: Korean name Danuri) with onboard ShadowCam camera [3], Astrobotic Peregrine Mission One [4], and other efforts underway to obtain high resolution topographic, minerals, volatiles and other information on the moon. We envision a need in immediate future for platforms to integrate these data sets, provide rendering and visualization capabilities in the context of a 3D Lunar globe for easier information access and analysis. NASA's Celestial Mapping System (CMS) [5] is developed to address the need for 3D tools for planetary science investigations, mission planning, in-situ operations, in a 3D-first design constructed around a unified view of a planetary globe. At present CMS provides many critical functionalities that include: 1) equipment planning and optimized placement on Lunar surface 2) line-of-sight (LOS) analysis 3) powerful measurement tools based on 3D terrain with realistic 3D models to represent rovers, astronauts and equipment 4) visualization of derived mapping products (e.g. resource maps), and 5) a data engine for hosting new observations that are not available in other contemporary lunar data tools [5, 7]. Planetary Data Ingestion: CMS can consume and analyze data from locally hosted and external third party sources. It is compatible with Open Geospatial Consortium (OGC) data and file standards and currently integrates datasets from the Astrogeology Science Center of USGS. This includes global and local data acquired from NASA (LRO, Clementine, Lunar Orbiter) and JAXA (SELENE/Kaguya), with capability of integrating more datasets. In addition, users can specify other WMS-hosted data endpoints, which CMS can then query and stream data from automatically. To set-up an automated process for ingestion and accurate rendering, visualization and analysis of external 3rd party planetary datasets within CMS, we initiated the process of ingesting unique dataset of super-enhanced images of the permanently shadowed regions (PSRs) at the lunar poles which were produced by the Hyper-effective nOise Removal U-net Software (HORUS) tool [8]. This tool was developed to enhance the extremely low-light images of the interior of PSRs and provide the ability to see within these regions at and discern surface features (i.e. boulders and craters) down to 3 meters in size. We focused on the Nobile region on the Lunar south pole, selected site for VIPER mission and stitched several images to create a high-resolution map within one of the PSR of Nobile crater. Figure 1 shows the dark PSR zone form the original NAC layer of LRO as the base layer (left image) and the illuminated areas within that crater (center) which was created by ingesting and merging several of HORUS generated images. At present we employ a semi-automated process to ensure spatial accuracy and merger of several overlapping zones. However, we are in the process of completely automating this process by employing AI based techniques that would rank, sort, and stack the images based on their information density. The georectification of the images would employ selected features. Analysis on Ingested Planetary Datasets: Once an external planetary data-set is successfully ingested, georectified and merged seamlessly as a data-layer; CMS’ numerous analysis tools can be used on this data. A Line of Sight (LOS) tool has been developed for CMS which analyzes terrain profiles and obstructions to determine visibility for remote observers [5,6]. Figure 1 (right image) shows the viewshed analysis on the same PSR in the Nobile region. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. The Measurements tool allows the user to take area and distance measurements of features on the terrain using various shapes. Measurement type can be specified in a number of ways: Line, Path, Polygon, Circle, Ellipse, Square, Rectangle or Freehand. Once the shape is specified, elevation information can then be extracted along each of these shapes. Figure 2 (left) shows the measurements performed on a crater n illuminated PSR in Nobile region. The equipment placement tool allows the user to place a 3D equipment model at a desired location and analyze its coverage area. The equipment placement tool is coupled with LOS to determine the coverage. Figure 2 (right) shows an equipment placed on the Lunar terrain and it’s coverage area. The red rays are blocked sight lines and the green rays are non-obstructed sight lines with the cyan lines showing the point of intersection with the terrain. More details are provided in the video demonstrations in Reference 5. Overcoming Polar Distortions: 3D geospatial applications exhibit significant distortions in polar imagery due to several reasons: 1) distortions in the source imagery, 2) incompatible tessellation algorithms at the poles, and 3) map projections. We are leveraging new tessellation algorithms and reprojecting data using projections that are better suited for Lunar poles. The goal is to seamlessly switch to polar projections while maintaining 3D view and navigation.

Maps↗

NASA NTRS2018

Impact of Gaps in the NASA-ISRO SAR Mission Swath

The NASA-ISRO Synthetic Aperture Radar (NISAR) mission will carry L-band and S-band SAR instruments, each with a 240 km swath width. The L-band instrument has the capability to map the entire Earth’s land and ice covered surfaces from both ascending and descending orbit positions, continuously in an exact 12 day repeating cycle, given temporally dense (better than 6-day on average) sampling of Earth over the life of the mission. To achieve this swath coverage without loss of resolution or polarimetric capability, NISAR uses a reflector-feed based antenna system with scan-on-receive (“SweepSAR”) capability. One of the characteristics of SweepSAR is that the pulse repetition interval of the radar is shorter than the echo receive window for the 240 km swath. Therefore, transmit events occur during the receive window and the receivers must be blanked periodically, creating gaps in the coverage. For fixed pulse rate operations, these gaps are persistent strips of blanked ranges. NISAR is being designed to allow variation of the pulse rate in order to spread out these gaps throughout the synthetic aperture, but processing these variably-acquired data is more challenging and can lead to compromises in image quality. At the highest level NISAR places requirements on science measurements rather than image quality, so there is often a debate among science and engineering team members as to whether to operate with fixed pulse rates – leading to range strips consistently blank from cycle to cycle but with optimal image quality – or to vary the pulse rate, fill in the gaps, and live with degraded image quality. NISAR’s performance team has shown that science requirements can be met with the gaps. However, scientists are eager for maximum and coverage within a swath. A companion paper (Villano et al.) describes image quality for NISAR using a variable PRF approach, but does not go further to science requirements. This paper explores the issues when gaps are present in the swath due to fixed PRF operations.

Veeramachaneni, Chandini↗

NASA NTRS2022

Going to Extremes: Architecting Holographic Microscopes for Extreme Environments

Bacterial life exists on earth in extreme environments. These are environments described by large temperature excur- sions, large pressure excursions, and large radiation excursions from the nominal conditions near sea level which are largely populated by humans. These extreme locales represent such places as the ocean ice, the briny pools of Death Valley and deep mines, the acidic hot springs of the High Sierra or Yellowstone, or even the clouds of our upper atmosphere. The preponderance of bacterial life in these extreme environments here on earth suggests that bacterial life might likely exist in the extreme environments of our own solar system, such as the icy moons of Europa or Enceladus. Thus, architecting instruments for detect- ing life in these extreme environments on earth builds confidence that we can architect such instruments for flight missions. In this paper, we discuss our experience with designing digital holo- graphic microscope instruments to enable detection of bacteria in several extreme environments. In particular we discuss three different instruments. The first is our field instrument which is a small, portable instrument for examination of remote sites. The second is submersible instrument which enables exploration of deep aquatic environments and is deployed on a ocean-going drone. The third is a balloon-borne instrument to examine the bacterial content of the upper atmosphere. We will provide a review of each instrument and discuss aspects of instrument engineering for each particular application.

Ramirez, Alex↗

NASA NTRS2017

Lunar Advanced Volatile Analysis Subsystem: Pressure Transducer Trade Study

In Situ Resource Utilization (ISRU) is a key factor in paving the way for the future of human space exploration. The ability to harvest resources on foreign astronomical objects to produce consumables and propellant offers potential reduction in mission cost and risk. Through previous missions, the existence of water ice at the poles of the moon has been identified, however the feasibility of water extraction for resources remains unanswered. The Resource Prospector (RP) mission is currently in development to provide ground truth, and will enable us to characterize the distribution of water at one of the lunar poles. Regolith & Environment Science and Oxygen & Lunar Volatile Extraction (RESOLVE) is the primary payload on RP that will be used in conjunction with a rover. RESOLVE contains multiple instruments for systematically identifying the presence of water. The main process involves the use of two systems within RESOLVE: the Oxygen Volatile Extraction Node (OVEN) and Lunar Advanced Volatile Analysis (LAVA). Within the LAVA subsystem, there are multiple calculations that depend on accurate pressure readings. One of the most important instances where pressure transducers (PT) are used is for calculating the number of moles in a gas transfer from the OVEN subsystem. As a critical component of the main process, a mixture of custom and commercial off the shelf (COTS) PTs are currently being tested in the expected operating environment to eventually down select an option for integrated testing in the LAVA engineering test unit (ETU).

Kang, Edward Shinuk↗

NASA NTRS2018

Synergistic and Collaborative Development Strategies for FV3 Powered Next Generation Unified Global Modeling System

The GFDL (Geophysical Fluid Dynamics Laboratory, NOAA - National Oceanic and Atmospheric Administration) Finite-Volume Cubed-Sphere Dynamical Core (FV3) is a scalable and flexible dynamical core capable of both hydrostatic and non-hydrostatic atmospheric simulations. FV3 has been chosen as the dynamical core for the Next Generation Global Prediction System project (NGGPS), designed to upgrade the current NCEP (National Centers for Environmental Prediction, NOAA) operational Global Forecast System (GFS) to run as a unified, fully-coupled system in NOAA's Environmental Modeling System infrastructure. FV3 dynamic core has a long history of serving as the main engine for global atmospheric models at various Government and Academic Research Laboratories including NOAA: GFDL Climate Modeling Suite (AM4 (Atmosphere Modeling 4), CM4 (Climate Model 4) ESM4 (Earth System Model 4), Hiram (HIgh Resolution Atmospheric Model)); NASA: GMAO (Global Modeling and Assimilation Office) Goddard Earth Observing System Model (GEOS); and NCAR (National Center for Atmospheric Research) Community Earth System Model (CESM). The three primary stakeholders in FV3 (GFDL, GMAO, EMC (Environmental Modeling Center - NOAA)) have embarked on synergistic and collaborative strategies with focus on the advancement of non-hydrostratic dynamic core, physics, chemistry, and data assimilation efforts, leveraging collective strengths of each of the partnering agencies. This talk presents the ongoing plans for model advancements at GFDL, GMAO and EMC, with special emphasis on contributions towards developing community based unified global modeling system for operational and research applications at respective organizations. Future plans include extending the collaborations to the development of earth system components including GMAO's aerosol chemistry models (GOCART/MAM (Goddard Chemistry Aerosol Radiation and Transport / Modal Aerosol Model)), Land Information System (LIS), and advanced data assimilation techniques; and GFDL's Modular Ocean Model (MOM) and Sea Ice Simulator (SIS) for transition to operations at NCEP.

Putman, William↗

NASA NTRSDate not supplied

CONTAMINATION CONTROL FOR ULTRA-SENSITIVE LIFE DETECTION SCIENCE MISSIONS

"This study report summarizes technological developments in science-required contamination control for cost-capped, life-detection missions in the Solar System. Technology advances focus on developing implementable strategies to restrict contamination of the spacecraft and instruments by the launch vehicle hardware. Secondary bake out operations during cruise further reduce molecular contaminants down to femtomolar levels in the sample path. The study validated a full-spacecraft, deployable barrier design as an effective strategy to isolate the spacecraft from the pre-launch processing and launch environment (e.g., fairing acoustic materials). It accommodates late mounting of RTGs and other required prelaunch activities. A new, high-fidelity physics, contamination-transport model for particles (including cells and their parts) and science-relevant molecules (e.g., possible biomolecules) was developed to validate the barrier concept. Importantly, this model takes into account the physics of extremely clean surfaces achieved by the best traditional contamination engineering. The ability to deal with very low levels of particulate and molecular contamination makes this model unique among standard contamination modeling approaches. Modeling also demonstrated that a high-temperature bake out during interplanetary cruise of the sample collector that comprises the largest surface area in the sample path for an Enceladus orbiter reference mission, was extremely effective. This study included the evaluation of other details necessary for an effective contamination control strategy for life detection missions including feasibility of achieving parts per trillion level cleanliness for semi-volatile hydrocarbons in nitrogen purge gas, identification of launch vehicle services required for the baseline contamination control, and defining additional contamination control measures to be taken during launch operations. Key results of the study are: • New spacecraft barrier design that accommodates RTGs is readily cleanable and repairable. Deployment of a 1/3 scale model was successfully demonstrated. • The barrier reduces particle contamination (likely biological) from fairing to spacecraft by 1e-2 to 1e-3. • On-cruise bake-out of critical surfaces significantly reduced molecular contamination (by as much as 1e-12). Subsequently, the probability of a surface contamination particle being transported to an instrument by an ice particle is less than 5.1e-5 (for microbes specifically, 4.39e-10). The report concludes that a full-spacecraft barrier designed specifically for life-detection missions that require stringent control of particulate and molecular contaminates is an effective means of mitigating risks of false positive and negative results for life signature investigations. Further, secondary cleaning steps for critical sections of the sample path can be highly effective at reducing molecular contaminants to low femtomolar levels."

Contamination↗

NASA NTRSDate not supplied

Contamination Control for Ultra-Sensitive Life-Detection Missions

contamination, life detection, barrier, modeling↗

NASA NTRS2006

NASA Tech Briefs, September 2006

Topics covered include: Improving Thermomechanical Properties of SiC/SiC Composites; Aerogel/Particle Composites for Thermoelectric Devices; Patches for Repairing Ceramics and Ceramic- Matrix Composites; Lower-Conductivity Ceramic Materials for Thermal-Barrier Coatings; An Alternative for Emergency Preemption of Traffic Lights; Vehicle Transponder for Preemption of Traffic Lights; Automated Announcements of Approaching Emergency Vehicles; Intersection Monitor for Traffic-Light-Preemption System; Full-Duplex Digital Communication on a Single Laser Beam; Stabilizing Microwave Frequency of a Photonic Oscillator; Microwave Oscillators Based on Nonlinear WGM Resonators; Pointing Reference Scheme for Free-Space Optical Communications Systems; High-Level Performance Modeling of SAR Systems; Spectral Analysis Tool 6.2 for Windows; Multi-Platform Avionics Simulator; Silicon-Based Optical Modulator with Ferroelectric Layer; Multiplexing Transducers Based on Tunnel-Diode Oscillators; Scheduling with Automated Resolution of Conflicts; Symbolic Constraint Maintenance Grid; Discerning Trends in Performance Across Multiple Events; Magnetic Field Solver; Computing for Aiming a Spaceborne Bistatic- Radar Transmitter; 4-Vinyl-1,3-Dioxolane-2-One as an Additive for Li-Ion Cells; Probabilistic Prediction of Lifetimes of Ceramic Parts; STRANAL-PMC Version 2.0; Micromechanics and Piezo Enhancements of HyperSizer; Single-Phase Rare-Earth Oxide/Aluminum Oxide Glasses; Tilt/Tip/Piston Manipulator with Base-Mounted Actuators; Measurement of Model Noise in a Hard-Wall Wind Tunnel; Loci-STREAM Version 0.9; The Synergistic Engineering Environment; Reconfigurable Software for Controlling Formation Flying; More About the Tetrahedral Unstructured Software System; Computing Flows Using Chimera and Unstructured Grids; Avoiding Obstructions in Aiming a High-Gain Antenna; Analyzing Aeroelastic Stability of a Tilt-Rotor Aircraft; Tracking Positions and Attitudes of Mars Rovers; Stochastic Evolutionary Algorithms for Planning Robot Paths; Compressible Flow Toolbox; Rapid Aeroelastic Analysis of Blade Flutter in Turbomachines; General Flow-Solver Code for Turbomachinery Applications; Code for Multiblock CFD and Heat-Transfer Computations; Rotating-Pump Design Code; Covering a Crucible with Metal Containing Channels; Repairing Fractured Bones by Use of Bioabsorbable Composites; Kalman Filter for Calibrating a Telescope Focal Plane; Electronic Absolute Cartesian Autocollimator; Fiber-Optic Gratings for Lidar Measurements of Water Vapor; Simulating Responses of Gravitational-Wave Instrumentation; SOFTC: A Software Correlator for VLBI; Progress in Computational Simulation of Earthquakes; Database of Properties of Meteors; Computing Spacecraft Solar-Cell Damage by Charged Particles; Thermal Model of a Current-Carrying Wire in a Vacuum; Program for Analyzing Flows in a Complex Network; Program Predicts Performance of Optical Parametric Oscillators; Processing TES Level-1B Data; Automated Camera Calibration; Tracking the Martian CO2 Polar Ice Caps in Infrared Images; Processing TES Level-2 Data; SmaggIce Version 1.8; Solving the Swath Segment Selection Problem; The Spatial Standard Observer; Less-Complex Method of Classifying MPSK; Improvement in Recursive Hierarchical Segmentation of Data; Using Heaps in Recursive Hierarchical Segmentation of Data; Tool for Statistical Analysis and Display of Landing Sites; Automated Assignment of Proposals to Reviewers; Array-Pattern-Match Compiler for Opportunistic Data Analysis; Pre-Processor for Compression of Multispectral Image Data; Compressing Image Data While Limiting the Effects of Data Losses; Flight Operations Analysis Tool; Improvement in Visual Target Tracking for a Mobile Robot; Software for Simulating Air Traffic; Automated Vectorization of Decision-Based Algorithms; Grayscale Optical Correlator Workbench; "One-Stop Shopping" for Ocean Remote-Sensing and Model Data; State Analysis Database Tool; Generating CAHV and CAHVOmages with Shadows in ROAMS; Improving UDP/IP Transmission Without Increasing Congestion; FORTRAN Versions of Reformulated HFGMC Codes; Program for Editing Spacecraft Command Sequences; Flight-Tested Prototype of BEAM Software; Mission Scenario Development Workbench; Marsviewer; Tool for Analysis and Reduction of Scientific Data; ASPEN Version 3.0; Secure Display of Space-Exploration Images; Digital Front End for Wide-Band VLBI Science Receiver; Multifunctional Tanks for Spacecraft; Lightweight, Segmented, Mostly Silicon Telescope Mirror; Assistant for Analyzing Tropical-Rain-Mapping Radar Data; and Anion-Intercalating Cathodes for High-Energy- Density Cells.

Source record↗

NASA NTRS2022

VIPRE: A Tool Aiding the Design for Entry Probe Missions

Exploring planetary atmospheres uncovers important information for how our solar system formed and evolved. While remote sensing is extensively used, some crucial observations require in-situ measurements by an atmospheric probe. Given their scientific importance, probe missions to Saturn, Uranus and Neptune are considered for the coming decades. In anticipation of future probe missions, the software tool VIPRE was developed as proof-of-concept to facilitate selection of probe entry locations. Currently, there is no analytical way to identify which interplanetary trajectory from thousands of feasible launch opportunities is optimal for a considered mission concept. The search and decision process for that solution is complex and relies on the intuition of mission designers, who focus on a subset of trajectories to make the trade space manageable. The idea of VIPRE is to (1) generate a multi-dimensional data cube showing relevant engineering and science parameters simultaneously for thousands of trajectories, and (2) visualize the data for all entry sites over the body's envelope. VIPRE lays the foundation to make the data available for browsing in a 3-D visualization to identify the best family of solutions for a given mission. The paper introduces the validated and verified core algorithms of VIPRE, published on GitHub. VIPRE serves as a basic framework to be used and extended for different purposes. The paper presents the motivation for the development and algorithms. It explains the computation and data visualization strategy, and gives a list of suggested functionalities to extend and further develop VIPRE to fully leverage its potential.

Ice Giants↗

NASA NTRS2004

Extraction of Oxygen from the Martian Atmosphere

A mechanical process was designed for direct extraction of molecular oxygen from the martian atmosphere based on liquefaction of the majority component, CO2, followed by separation of the lower-boiling components. The atmospheric gases are compressed from about 0.007 bar to 13 bar and then cooled to liquefy most of the CO2. The uncondensed gases are further compressed to 30 bar or more, and then cooled again to recover water as ice and to remove much of the remaining CO2. The final gaseous products consisting mostly of nitrogen, oxygen, and carbon monoxide are liquefied and purified by cryogenic distillation. The liquefied CO2 is expanded back to the low-pressure atmosphere with the addition of heat to recover a majority of the compression energy and to produce the needed mechanical work. Energy for the process is needed primarily as heat to drive the CO2-based expansion power system. When properly configured, the extraction process can be a net producer of electricity. The conceptual design, termed 'MARRS' for Mars Atmosphere Resource Recovery System, was based on the NASA/JSC Mars Reference Mission (MRM) requirement for oxygen. This mission requires both liquid oxygen for propellant, and gaseous oxygen as a component of air for the mission crew. With single redundancy both for propellant and crew air, the oxygen requirement for the MRM is estimated at 5.8 kg/hr. The process thermal power needed is about 120 kW, which can be provided at 300-500 C. A lower-cost nuclear reactor made largely of stainless steel could serve as the heat source. The chief development needed for MARRS is an efficient atmospheric compression technology, all other steps being derived from conventional chemical engineering separations. The conceptual design describes an exceptionally low-mass compression system that can be made from ultra-lightweight and deployable structures. This system adapts to the rapidly changing martian environment to supply the atmospheric resource to MARRS at constant conditions.

England, C.↗

NASA NTRS2012

Drilling, Coring and Sampling Using Piezoelectric Actuated Mechanisms: From the USDC to a Piezo-Rotary-Hammer Drill

NASA exploration missions are increasingly including sampling tasks but with the growth in engineering experience (particularly, Phoenix Scout and MSL) it is now very much recognized that planetary drilling poses many challenges. The difficulties grow significantly with the hardness of sampled material, the depth of drilling and the harshness of the environmental conditions. To address the requirements for samplers that could be operated at the conditions of the various bodies in the solar system, a number of piezoelectric actuated drills and corers were developed by the Advanced Technologies Group of JPL. The basic configuration that was conceived in 1998 is known as the Ultrasonic/Sonic Driller/Corer (USDC), and it operates as a percussive mechanism. This drill requires as low preload as 10N (important for operation at low gravity) allowing to operate with as low-mass device as 400g, use an average power as low as 2- 3W and drill rocks as hard as basalt. A key feature of this drilling mechanism is the use of a free-mass to convert the ultrasonic vibrations generated by piezoelectric stack to sonic impacts on the bit. Using the versatile capabilities f the USDC led to the development of many configurations and device sizes. Significant improvement of the penetration rate was achieved by augmenting the hammering action by rotation and use of a fluted bit to remove cuttings. To reach meters deep in ice a wireline drill was developed called the Ultrasonic/Sonic Gopher and it was demonstrated in 2005 to penetrate about 2-m deep at Antarctica. Jointly with Honeybee Robotics, this mechanism is currently being modified to incorporate rotation and inchworm operation forming Auto-Gopher to reach meters deep in rocks. To take advantage of the ability of piezoelectric actuators to operate over a wide temperatures range, piezoelectric actuated drills were developed and demonstrated to operate at as cold as -200oC and as hot as 500oC. In this paper, the developed mechanisms will be reviewed and discussed including the configurations, capabilities, and challenges.

ultrasonic/Sonic Driller/ Corer (USDC)↗

DOE OSTI2025

On the Role of Airborne Ice Nucleating Particles in Primary and Secondary Ice Formation Processes in Convective Midlatitude Clouds

Abstract Formation of ice in mixed-phase clouds may proceed via primary nucleation and secondary ice production (SIP). Primary nucleation involves the presence of ice nucleating particles (INPs), while SIP follows primary nucleation, resulting in ice crystal number concentrations N ice exceeding the number of INPs. The ice formation pathways in young congestus clouds are not well understood nor are the environmental conditions favorable for the onset of SIP. Coincident airborne measurements of INPs and N ice collected during the Secondary Production of Ice in Cumulus Experiment (SPICULE) campaign over the U.S. central Great Plains are reported for young congestus clouds. Number concentrations of INPs and N ice at temperatures between −10° and −20°C were used to categorize whether SIP was active in each analyzed cloud pass. Observational data suggested that fragmentation of freezing droplets (FFDs) was occurring and the most likely SIP mechanism for ice enhancement during the early stages of the sampled clouds, where higher cloud-base temperatures and stronger updrafts produced conditions favorable for the onset of FFD. Simple model simulations of a congestus cloud were used to compare predictions of N ice from newly implemented SIP mechanisms (including FFD) alongside those from the existing Hallett–Mossop (HM) mechanism. Although predicted N ice , when all SIP mechanisms were active, was in good agreement with observations, the dominant SIP mechanism in the model was predicted to be HM. The rate of heterogeneous freezing in raindrops was likely inhibiting realistic FFD rates in the simulated cloud. These discrepancies between the observations and simulations underscore the need for extended laboratory studies to formulate improved model representations of SIP in convective clouds.

Patnaude, Ryan J. [Department of Atmospheric Scien↗