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NASA NTRS2021

Modeling the Radiative Effect on Microphysics in Cirrus Clouds Against Satellite Observations

The radiative effect on microphysics (REM) plays an important role in the dew/frost formation near the surface. How REM impacts cirrus clouds is investigated in this study, using bin microphysical model simulations and coincident data of the CloudSat and Global Precipitation Measurement (GPM) satellites. REM affects ice crystal spectrum with two types: radiative cooling and warming. Radiative cooling, as predicted by the bin-model simulations, favors the formation of horizontally oriented ice crystals (HOICs), but radiative warming does not. Hence, a test of REM can be transformed to a test of HOICs, because HOICs can be measured by the microwave polarization observations of the GPM Microwave Imager (GMI) at 166 GHz. To analyze the GMI data for their HOIC distribution, clouds are sorted into four groups with different optical depth and altitude, based on the radiative cooling/warming ratio (or eta) computed with satellite-retrieved ice water content. Their HOIC distributions (e.g., the midlevel thick clouds have more HOICs than the high-level ones) agree well with those predicted by the bin-model simulations. The general agreement between the GMI observations and bin-model simulations suggests that REM is common in cirrus clouds and impacts cirrus clouds significantly.

clouds↗
NASA NTRSDate not supplied

Enabling Single Cell Research in Hollow Hydrogel Microparticles

Studying biology at the single cell level enables novel discoveries through ultra-high throughput identification and isolation of rare cells and interesting subpopulations. Encapsulation of single cells in hollow hydrogel microparticles, or PicoShells, enables easy visualization, manipulation, and assaying of single cells. The PicoShell’s porous hydrogel shell allows diffusion of nutrients and wastes into and out of the hollow liquid core, allowing uninhibited cell growth. The porous shell also allows diffusion of assay reagents, enabling solution changes, and multi-step assays. Finally, single cells and their progeny can be tracked through time, for example to measure single cell growth rates. However, PicoShells are fabricated using microfluidic techniques, which require specialized expertise, equipment, and facilities. This limits PicoShell’s widespread utility for single cell biology. For Saccharomyces cerevisiae and other desiccation-tolerant microbes, desiccating PicoShells containing cells of interest offers a solution, enabling those without microfluidic capabilities to obtain dried, shelf-stable PicoShells containing their cells of interest from a specialized microfluidics facility. Researchers could then rehydrate the PicoShells and perform their single cell assays, bypassing the microfluidic steps. Desiccated PicoShells could also be flown in space, where desiccation is already a common practice for microbes (i.e. BioSentinel and BioNutrients), bringing single cell analysis capabilities to space. In this work, we develop a method to desiccate PicoShells containing S. cerevisiae while maintaining characteristics similar to fresh, non-desiccated PicoShells. We show good microparticle morphology and hydrogel pore size as well as high yeast viability in line with previous studies. We also demonstrate sorting of a fast-growing yeast population using size-based filtration, as S. cerevisiae in PicoShells are able to physically stretch the microparticle as they grow, increasing the PicoShell diameter. These efforts contribute to the feasibility of leveraging microparticle PicoShells for single cell space biology research on Earth and in space.

Simon Ng↗
NASA NTRSDate not supplied

Constraints on the Origin of Mercury’s Large Core from Core-Mantle Differentiation Models

Mercury’s core is notoriously large when compared to other planets of our solar system. The origin of this large core is still uncertain. Available data on the surface composition and internal structure of Mercury from the past MESSENGER mission and future data collected by BepiColombo will continue to provide clues to Mercury’s formation. Here, we present results combining experimental data on elemental distribution between core and mantle with spacecraft data, to estimate bulk Mercury composition. We applied this strategy to major elements (Fe, Si, Mg, Al and O), as well as minor elements (Cr and Ti), and compared derived compositions to chondritic data and the chemical compositions of the other terrestrial planets. Our results show that Mercury has a chemical composition significantly different from all known materials of the solar system. In addition, numerous scenarios were proposed to explain Mercury’s structure, including “chaotic models” such as giant impacts and “orderly models” such as aerodynamic sorting. Here, we tested whether Mercury’s composition can be explained by mantle stripping by impacts. We will show how such a scenario reconciles several features of Mercury’s geochemistry with chondritic data. We will also discuss the outlook of additional constraints from supplementary data potentially collected by BepiColombo.

Mercury↗
NASA NTRSDate not supplied

Habitable Working and Living Spaces in the Deep Space Science Vessel

The Deep Space Science Vessel (DSSV) is a conceptual design of a very large spacecraft intended as a mobile microgravity science platform. It represents an effort to conceptualize the systems and internal architectures needed to support a forty-eight-person crew for multi-year missions throughout the inner solar system and potentially beyond. The general arrangement of the DSSV is a modular spacecraft. Considering only the pressurized, habitable elements, the DSSV includes two large pressurized modules (Hab and Lab) docked together along with eight smaller node modules completing the habitable configuration. The Hab and Lab modules are docked side by side, with the longitudinal axes parallel to each other and a single docking port connecting them. A node module is docked to each dome on the Hab and Lab modules, such that the two small node modules on each end of the large Hab and Lab domes are docked both to each other and to the Hab and Lab. This creates a “racetrack” translation path on the interior. The other four node modules are docked at the center of the Hab and Lab modules, two on each side, creating another “racetrack” translation path perpendicular to the first one. The DSSV has a generally vertical orientation. Within the Hab and Lab modules the decks are perpendicular to the longitudinal axis. The node modules are oriented with their longitudinal axes perpendicular to those of the Hab and Lab modules, so the nodes have a horizontal internal orientation. Decks are numbered one through nine, with decks two and eight representing the “top” and “bottom” domes of the Hab and Lab modules. The Hab Module decks encompass the ship’s galley, crew quarters, waste, hygiene, portions of crew exercise, and group recreation. The Lab Module contains food production facilities, the life science lab, the ship’s infirmary, the physical science lab, and the maintenance and fabrication workshop. The Node Modules serve a number of different functions. The two Exercise Nodes are docked to deck five of both the Hab and Lab modules and contain most of the aerobic and resistive exercise devices. Also docked to deck five but on the opposite side of the Hab and Lab modules are the Observation Deck and Space Café. These two node modules provide social gathering space for small numbers of crew. The Mission Operations Node is on deck nine directly above the Galley and contains spacecraft monitoring and commanding capabilities. Docked to it is the EVA Operations Node, which contains suit maintenance and storage. (The airlock is a separate, external element docked to the EVA Operations Node.) The Subsystems Node is on deck one beneath the maintenance and fabrication workshop. Docked to it is the Stowage Node. This node does not house DSSV primary stowage, but is a staging point where stowage brought in from logistics modules can be sorted, unpacked, or repacked as needed prior to distribution to the appropriate sections of the spacecraft.

Deep Space Habitat↗
NASA NTRSDate not supplied

Soyuz Landing Risk Characterization

INTRODUCTION United States On-orbit Segment (USOS) astronauts have been returning to Earth from the International Space Station (ISS) aboard the Russian Soyuz vehicle since 2003. The energetics associated with Soyuz landings are comparable to our next generation of US space vehicles (Orion, Crew Dragon, and Starliner). Soyuz also lands crew in a similar state of spaceflight deconditioning that is anticipated using the future vehicles. A number of injuries have now been observed during these Soyuz landings. Currently it is unknown how Soyuz landing accelerations and the numbers and types of associated injuries relate to the new occupant protection requirements levied upon future space vehicles. Understanding this relationship will allow better quantification of the risk of injury for future spacecraft designs. METHODS An estimate of the occurrences of injury during Soyuz landings has been determined using data contained in NASA flight medicine databases and supplemented with data collected from crewmembers and flight surgeons. At the time of this abstract, 96 USOS astronauts have returned to Earth in the Soyuz (59 US, 31 International Partner, and 6 spaceflight participants). Of that total, data from 80 individual crew landings has been collected through this study. Injuries are classified as either contusions/abrasions, Class I (minor, no medical follow-up), Class II (moderate, medical follow-up necessary), Class III (severe), and Class IV (life threatening). Current NASA occupant protection standards are primarily based on the Multi-axial Dynamic Response Index (MDRI), which is a simple lumped-parameter spring, mass, damper model tuned to human impact responses in three orthogonal axes. RESULTS Using what is known about Soyuz landing dynamics from airborne and drop test data, the MDRI predicts essentially no Class IV or III injuries, < 1% Class II injuries, and < 5% Class I injuries. Approximately one-third of all USOS crewmembers for whom data has been gathered have suffered some sort of injury related to landing in the Soyuz vehicle. Most of these injuries fall into the contusion/abrasion category (21.3 %). Class I injuries have been sustained by 5.0% of all crew, and Class II injuries have been observed in 3.8%. No Class III or IV injuries have been sustained to date. Forty-three injuries have been documented, with some crewmembers sustaining more than one injury in a single landing. The knee was the most likely area of injury (n=9), followed by the back (n=8), and then the arm (n=7). CONCLUSION Soyuz landing dynamics are the most comparable analog environment for the anticipated loads associated with Orion and commercial crew vehicle landings. The MDRI under predicts the percentage of Class II injuries experienced during Soyuz landings. The MDRI is better at predicting Class I injury occurrences. However, if contusions/abrasions are included in the minor injury Class I category, then the MDRI also vastly under predicts those injuries as well. Given this data, it will be important to re-evaluate the expected injury rates for future vehicles, and work toward improving the predictive tools for spaceflight use. Spaceflight deconditioning may account for some of the under prediction, and work is ongoing to assess the relationship between landing injuries and impact tolerance changes due to spaceflight deconditioning.

N Newby↗
NASA NTRSDate not supplied

Voxel Based Three-Dimensional Topology Optimization of Heat Exchanger Fins

Increasing interest in novel aircraft propulsion systems and potential for unwanted heat generation, or capture and reuse of waste heat, may require increasingly lightweight and high performing heat exchangers. Advances in manufacturing technologies have shown potential to create complex designs, but design tools need more flexibility. This study utilizes genetic algorithm-driven topology optimization to develop high performance heat exchanger fins for critical applications such as aerospace. The solid domain is generated using voxel representation where a voxel value of 1 indicates the solid domain and a voxel value of 0 refers to the fluid domain. The use of voxel representation somewhat matches the digitization of a model that is required to fabricate using additive manufacturing, and also allows for a highly unconstrained geometry. To test the topology optimization approach, a three-dimensional(3D)baseline offset strip fin geometry in steady laminar flow(Reynolds number = 215)with conjugate heat transfer(simultaneous solution of solid and fluid temperature fields)is optimized. New designs are generated using the genetic algorithm (GA) and sent to evaluation by the CFD software OpenFOAM; then the GA sorts and selects the reproduction pool for the following generation. This process is repeated for 60 generations. The study also investigates the effect off in material on the performance of the GA and the resulting designs. The results show that the optimal designs have overall performance improvement of 18% relative to the baseline. Additionally, a fin constructed of a lower conductivity material (such as an Inconel super alloy that might be necessary for waste heat recovery applications)results in lower overall performance improvement (11%)and optimal designs with higher pressure drop relative to their baseline, and relative to optimal designs produced using higher conductivity materials.

3D Optimization↗
NASA NTRSDate not supplied

Demonstration of Capability to Simulate Particle Irregular Shape and Poly-Disperse Mixtures Within Lunar Lander Plume-Surface Interaction

Plume-Surface Interaction (PSI) between lander engine plumes and regolith soil creates hazards in obscuration and contamination by particle clouds, high-energy ejecta streams, and landing area cratering damage. The MSFC Fluid Dynamics Branch is developing simulation tools to offer a predictive PSI capability to NASA customers such as the Human Lander System (HLS) and Commercial Lunar Payload Services (CLPS). The Gas-Granular Flow Solver (GGFS) is the main application tool for coupled gas-particle two-phase flow simulations to predict the range of PSI effects from onset of surface erosion to deep crater formation. GGFS features an Eulerian-Eulerian modeling approach, treating both gas and granular material as interacting continuum phases. Modeling the lunar regolith granular material fluidic characteristics poses special challenges due to complex particle shapes and mixture composition. The lunar regolith is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking jagged particle shapes. Eulerian granular material flow modeling requires closure formulations for the granular material constitutive models (stress, friction, collisional and kinetic energy dissipation, drag, etc.). While closure models for spherical particles are available from particle kinetic theory, closure models for realistic non-spherical particles must be extracted from unit physics Discrete Element Model (DEM) particle interaction simulations and provided in the form of tabular datasets. The effects of particle irregular shape (non-spherical shape factors, angular particle surface roughness, and interlocking features) are simulated by approximating the particle features in the form of grouped elemental spheres to form composite particles in the DEM simulations. The effects of the wide range of regolith mixture particle sizes and the strong effects of the presence of the small particle sizes results in high cohesion and low porosity of the regolith mixture. The range of particle sizes is simulated by binning the particle sizes into an appropriate finite number of particle-size species and solving the problem as a species mixture. Combining these two modeling approaches enables simulations to capture both, the contributions of the irregular particle shape and the particle size distribution. The integration and maturation of the DEM-based constitutive model database generation process and poly-disperse mixture binning approach into the GGFS simulation framework are proceeding under funding by the NASA Game Changing Development program. The status of current capabilities will be presented in comparisons of crater characteristics resulting for spherical and irregular shape particles, and for mono-, bi-, and tri-disperse mixture simulations of Apollo LM plume-surface interaction. The computational results confirm the significance of including the particle shape and mixture effects. Going forward plans for the full implementation of the general poly-disperse regolith modeling capability and maturation towards NASA project application readiness under the GCD program will be presented.

Peter A Liever↗
NASA NTRS2021

Machine Learning Based Path Planning for Improved Rover Navigation

Enhanced AutoNav (ENav), the baseline surface navigation software for NASA’s Perseverance rover, sorts a list of candidate paths for the rover to traverse, then uses the Approximate Clearance Evaluation (ACE) algorithm to evaluate whether the most highly ranked paths are safe. ACE is crucial for maintaining the safety of the rover, but is computationally expensive. If the most promising candidates in the list of paths are all found to be infeasible, ENav must continue to search the list and run time-consuming ACE evaluations until a feasible path is found. In this paper, we present two heuristics that, given a terrain heightmap around the rover, produce cost estimates that more effectively rank the candidate paths before ACE evaluation. The first heuristic uses Sobel operators and convolution to incorporate the cost of traversing high-gradient terrain. The second heuristic uses a machine learning (ML) model to predict areas that will be deemed untraversable by ACE. We used physics simulations to collect training data for the ML model and to run Monte Carlo trials to quantify navigation performance across a variety of terrains with various slopes and rock distributions. Compared to ENav's baseline performance, integrating the heuristics can lead to a significant reduction in ACE evaluations and average computation time per planning cycle, increase path efficiency, and maintain or improve the rate of successful traverses. This strategy of targeting specific bottlenecks with ML while maintaining the original ACE safety checks provides an example of how ML can be infused into planetary science missions and other safety-critical software.

Yue, Yisong↗
NASA NTRSDate not supplied

Demonstration of Capability to Simulate Particle Irregular Shape and Poly-Disperse Mixtures Within Lunar Lander Plume-Surface Interaction

Plume-Surface Interaction (PSI) between lander engine plumes and regolith soil creates hazards in obscuration and contamination by particle clouds, high-energy ejecta streams, and landing area cratering damage. The MSFC Fluid Dynamics Branch is developing simulation tools to offer a predictive PSI capability to NASA customers such as the Human Lander System (HLS) and Commercial Lunar Payload Services (CLPS). The Gas-Granular Flow Solver (GGFS) is the main application tool for coupled gas-particle two-phase flow simulations to predict the range of PSI effects from onset of surface erosion to deep crater formation. GGFS features an Eulerian-Eulerian modeling approach, treating both gas and granular material as interacting continuum phases. Modeling the lunar regolith granular material fluidic characteristics poses special challenges due to complex particle shapes and mixture composition. The lunar regolith is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking jagged particle shapes. Eulerian granular material flow modeling requires closure formulations for the granular material constitutive models (stress, friction, collisional and kinetic energy dissipation, drag, etc.). While closure models for spherical particles are available from particle kinetic theory, closure models for realistic non-spherical particles must be extracted from unit physics Discrete Element Model (DEM) particle interaction simulations and provided in the form of tabular datasets. The effects of particle irregular shape (non-spherical shape factors, angular particle surface roughness, and interlocking features) are simulated by approximating the particle features in the form of grouped elemental spheres to form composite particles in the DEM simulations. The effects of the wide range of regolith mixture particle sizes and the strong effects of the presence of the small particle sizes results in high cohesion and low porosity of the regolith mixture. The range of particle sizes is simulated by binning the particle sizes into an appropriate finite number of particle-size species and solving the problem as a species mixture. Combining these two modeling approaches enables simulations to capture both, the contributions of the irregular particle shape and the particle size distribution. The integration and maturation of the DEM-based constitutive model database generation process and poly-disperse mixture binning approach into the GGFS simulation framework are proceeding under funding by the NASA Game Changing Development program. The status of current capabilities will be presented in comparisons of crater characteristics resulting for spherical and irregular shape particles, and for mono-, bi-, and tri-disperse mixture simulations of Apollo LM plume-surface interaction. The computational results confirm the significance of including the particle shape and mixture effects. Going forward plans for the full implementation of the general poly-disperse regolith modeling capability and maturation towards NASA project application readiness under the GCD program will be presented.

Peter A. Liever↗
NASA NTRSDate not supplied

An Overview of NASA Research into Urban Air Mobility Noise

NASA is conducting research into the noise of future Urban Air Mobility (UAM) concepts. This work is wide ranging and incorporates efforts to measure, characterize, and predict the possible noise impacts on people and communities. A part of this effort is focused on laboratory psychoacoustic testing. The sorts of tests generate data that can be used to make predictive models that may be used to guide future design, operation and regulation practices. Another component of this work, and one that people outside NASA can engage in, is the NASA-led UAM Noise Working Group (UnWG).

UAM↗
NASA NTRS2022

ThermoBase: A Database of the Phylogeny and Physiology of Thermophilic and Hyperthermophilic Organisms

Thermophiles and hyperthermophiles are those organisms which grow at high temperature (> 40°C). The unusual properties of these organisms have received interest in multiple fields of biological research, and have found applications in biotechnology, especially in industrial processes. However, there are few listings of thermophilic and hyperthermophilic organisms and their relevant environmental and physiological data. Such repositories can be used to standardize definitions of thermophile and hyperthermophile limits and tolerances and would mitigate the need for extracting organism data from diverse literature sources across multiple, sometimes loosely related, research fields. Therefore, we have developed ThermoBase, a web-based and freely available database which currently houses comprehensive descriptions for 1238 thermophilic or hyperthermophilic organisms. ThermoBase reports taxonomic, metabolic, environmental, experimental, and physiological information in addition to literature resources. This includes parameters such as coupling ions for chemiosmosis, optimal pH and range, optimal temperature and range, optimal pressure, and optimal salinity. The database interface allows for search features and sorting of parameters. As such, it is the goal of ThermoBase to facilitate and expedite hypothesis generation, literature research, and understanding relating to thermophiles and hyperthermophiles within the scientific community in an accessible and centralized repository. ThermoBase is freely available online at the Astrobiology Habitable Environments Database (AHED; https://ahed.nasa.gov), at the Database Center for Life Science (TogoDB; http://togodb.org/db/thermobase), and in the S1 File.

Thermophiles↗
NASA NTRSDate not supplied

Overview of NASA ISRU Plans, Priorites, and Activities

Introduction:The National Aeronautics andSpace Administration (NASA) of the United States ofAmerica (US) has initiated the Artemis Moon to Marsprogram to send astronauts (the first woman andperson of color) back to the lunar surface, create asustainable human lunar exploration program, andlead the first human exploration mission to the Marssurface in the 2030’s [1]. A major objective of thisprogram is to characterize the resources that exist onthe Moon and Mars, and learn how to utilize them forsustained and affordable exploration. Commonlyknown as In Situ Resource Utilization (ISRU), thesearch for, acquisition, and processing of resources inspace has the potential to greatly reduce thedependency on transporting mission consumables andinfrastructure from Earth, thereby reducing missioncosts, risks, and dependency on Earth.ISRU is Enabling: Through the extraction andprocessing of resources into mission commoditiessuch as rocket propellants, life support consumables,and fuel cell reactants, ISRU enhances and evolvesthe cis-lunar, lander, and surface transportationsystems required for human exploration; expandingand enhancing HOW humans can explore and returnfrom the Moon. Through the extraction andprocessing of resources into metals, silicon, and othermanufacturing and construction feedstock, ISRUenhances and allows for the expansion of criticalinfrastructure using in situ manufacturing andconstruction capabilities that influence WHAT humanscan do on the Moon and in cis-lunar space. Becauseof this, ISRU supports and enables commercialinvolvement beyond NASA and governmentalagencies by both lowering the cost of sustainedtransportation to/from/on the Moon as well assupporting the market required for needing thesetransportation systems. Strategic Framework:To achieve this vision,NASA’s Space Technology Mission Directorate(STMD) ensures the coordinated development ofISRU and other critical space and surfaceinfrastructure elements such as propulsion, power,manufacturing, construction, and robotics through theStrategic Technology Architecture Roundtable(STAR) process. Through STAR, an integratedframework and process has been created allowing forcapabilities and technologies to be linked andassessed, gaps to be identified, specifications andmetrics to be established, and provide a means toprioritize and implement technology development andmissions. A critical part of the STAR effort has beenthe establishment of the Strategic Framework thatorganizes all work under four major Thrusts (Go,Land, Live, and Explore) and identifies the drivingOutcomes for each of these Thrusts. From the Thrustsand Outcomes, all work can be categorized and linkedbetween Capability Areas, and Technology Gaps canbe identified and addressed (Figure 1.)Figure 1. Strategic Framework and STAR FrameworkISRU Envisioned Future: To drive thedevelopment of technologies and capabilities, theSTAR process starts with establishing a ‘grand vision’of where each Outcome and Capability is aiming tobe considered complete. For ISRU, the EnvisionedFuture is “Scalable ISRU production/utilizationcapabilities including sustainable commodities on thelunar and Mars Surface”. This involves starting with10’s of metric tons of products, but evolves into 100’sto 1000’s of metric tons of water, oxygen, propellants,construction and manufacturing feedstock, andcommodities for habitat and food production andoperations. For ISRU, the ‘Prospect to Product’philosophy starts with Destination Reconnaissance &Resource Assessment, followed by ResourceAcquisition, Isolation, and Preparation, leading intoResource Processing (which is further subdivided intomission consumables and feedstocks for constructionand manufacturing). The ISRU Envisioned Futurealso considers what resources are available andattempts to address what and when these resourceswill be evaluated and harnessed, as well asconsidering which products/commodities can beobtained for early use and which ones require moretime and/or users of refined products.It Takes an Architecture: ISRU does not existon its own. By definition, it requires customers/users SHORT TITLE HERE: A. B. Author and C. D. Authorto use the products/commodities produced by ISRUsystems. Also, for an ISRU capability to exist, itmust obtain products and services from other systemsand infrastructure. An important aspect of the STARprocess and the ISRU Envisioned Futures Prioritiesstrategy is to identify and link all of these systems andcapabilities to achieve the desired end state (Figure2).Figure 2. ISRU as Part of a Larger ArchitectureISRU Capability Drivers: The guidingprinciples for NASA’s Space TechnologyDevelopment for Artemis are to develop criticaltechnologies and capabilities that enable (i) asustainable Lunar surface presence, (ii) the future goalof sending humans to Mars, and (iii) promotingcritical technologies to enable future science andcommercial missions. It is a major goal of theArtemis campaign to establish some sort of base campat the lunar South Pole by approximately the end ofthe decade. The ISRU Envisioned Futures Prioritiesstrategy is aligned with the Artemis campaign todevelop and demonstrate ISRU capabilities in thistimeframe that could lead to sustained surfaceoperations, infrastructure growth, and commercialoperations in the next decade (Figure 3).Figure 3. ISRU Dual Path to Full Implementation and CommercializationState of the Art and Gaps: To achieve theenvisioned future, an extensive effort was performedto understand the State of the Art (SOA) for ISRUgoing back decades, and to assess the SOA against thenear and long-term goals and objectives of the ISRUStrategic Outcome objectives. While the releasedISRU Envisioned Futures Priorities only includes atop-level definition of both the SOA and Gaps, furtherinformation on these for ISRU can be found in theISRU Gap Assessment Study performed for theInternational Space Exploration Coordination Group(ISECG) [2]. To provide further guidance to industryand academia, a top level assessment was performedand provide that divides critical areas of ISRUcapabilities and technologies into 3 categories:Significant Funding, Partially Covered/MoreRequired, and Limited/No Funded Activities.Envisioned Future Priorities- Next Steps forISRU: While a significant amount of work over abroad range of technology areas has been performedover the last several years for lunar ISRU, to reach theenvisioned future for ISRU, a lot more work isrequired at the technology level leading to bothsystems and technology demonstrations in the nearfuture. To guide investments within NASA, industry,and academia, 5 specific areas of high priority wereidentified. These are:1.Complete development of the Water and Oxygen Mining Paths and close technology gaps, with emphasis on oxygen extraction from Highland regolith and parallel paths for polar water mining.2.Expand development of metal extraction and feedstock for manufacturing and construction, with emphasis on aluminum and initial/easy to obtain/make construction feedstocks leading to more refined metals and other regolith resources. Also, evaluate biologically inspired/derived technologies in bio-mining, bio-plastic, and other feedstock commodities.3.Ensure the resource assessment needed for future ISRU commercial operations is coordinated with both near/long-term science objectives as well as Artemis mission locations of interest.4.Initiate NASA and industry-led system-level analyses, integration, and testing activities for ISRU capabilities. While significant work has been performed at the technology and subsystemlevel, it is now important to understand how these technology investments can be leveraged and utilized in actual systems and applications5.Initiate lunar ISRU technology flight demonstrations leading to initial ‘Pilot Plant’ end-to-end production capability demonstrations, led by industry

ISRU↗
NASA NTRSDate not supplied

“Are We There Yet?” Can We Biomap the Solar System with Low-Cost Solar Sail Missions?

Abstract: So much of our effort in space exploration has been devoted to one-off missions with major investments in each. This is a great strategy for early investigations of clearly significant planetary and small body destinations, but we have an entire Solar System to interrogate and the pace has definitely been slow to date. We are in the dawning era of much smaller spacecraft, and the potential to gather data from multiple destinations over longer time spans with a heightened cadence of missions to allow us to conduct survey-style investigations of the vast number of objects that attend our particular star. If we think of solar systems as belonging to one of two classes, i.e. life-bearing or not life-bearing, then the presence of some sort of biological or prebiological phenomenon on any individual body in a system places that system in the first category. The emergence of life can then be considered as a solar system-wide property and the entire suite of ingredients and processes that go into kindling of life anywhere within that system is of interest. This ranges from bodies with prebiotic chemistry through to full-blown biospheres. Thus, all bodies in a solar system are part of the milieu within which life occurs. Can the idea of low-cost solar sail-propelled spacecraft deployed en masse be useful for something as hard to investigate as life-like phenomena and their precursors? Perhaps, the answer is yes, and we must give serious attention to the possibilities.

Penelope J Boston↗
NASA NTRSDate not supplied

Are We Shaking Too Much? An Inquiry into Environmental Random Vibration Testing Margins

Problem Statement: The conventional, MIL-STD-810 approach to vibration environment derivation is perhaps too conservative, leading to unnecessary failures during acceptance & qualification vibration testing of Armstrong’s one-off flight equipment. Objective: This presentation explores some alternative understandings of the distributions of vibration severity in nonstationary environments. Proposed methods of sorting and adding appropriate margin are explored.

Scott L. Stebbins↗
NASA NTRSDate not supplied

Soyuz Landing Risk Characterization

INTRODUCTION United States On-orbit Segment (USOS) astronauts have been returning to Earth from the International Space Station (ISS) aboard the Russian Soyuz vehicle since 2003. The energetics associated with Soyuz landings are comparable to our next generation of US space vehicles (Orion, Crew Dragon, and Starliner). Soyuz also lands crew in a similar state of spaceflight deconditioning that is anticipated using the future vehicles. A number of injuries have now been observed during these Soyuz landings. Currently it is unknown how Soyuz landing accelerations and the numbers and types of associated injuries relate to the new occupant protection requirements levied upon future space vehicles. Understanding this relationship will allow better quantification of the risk of injury for future spacecraft designs. METHODS An estimate of injury occurrence during Soyuz landings has been determined using data contained in NASA flight medicine databases and supplemented with data collected from crewmembers and flight surgeons. At the time of this abstract, 96 USOS astronauts have returned to Earth in the Soyuz (59 US, 31 International Partner, and 6 spaceflight participants). Of that total, data from 80 individual crew landings has been collected through this study as of 2021. Injuries are classified either as contusions/abrasions, Class I (minor, no medical follow-up), Class II (moderate, medical follow-up necessary), Class III (severe), or Class IV (life threatening). Current NASA occupant protection standards are primarily based on the Multi-axial Dynamic Response Index (MDRI), which is a simple lumped-parameter spring, mass, damper model tuned to human impact responses in three orthogonal axes. RESULTS Using what is known about Soyuz landing dynamics from airborne and drop test data, the MDRI predicts essentially no Class IV or III injuries, < 1% Class II injuries, and < 5% Class I injuries. Approximately one-third of all USOS crewmembers for whom data has been gathered have suffered some sort of injury related to landing in the Soyuz vehicle. Most of these injuries fall into the contusion/abrasion category (21.3 %) (n.b. This is the percent for whom contusion/abrasion was the worst injury. Those with class I or II injuries typically also received contusions/abrasions). Class I injuries have been sustained by 5.0% of all crew, and Class II injuries have been observed in 3.8%. No Class III or IV injuries have been sustained to date. Forty-three injuries have been documented, with some crewmembers sustaining more than one injury in a single landing. The knee was the most likely area of injury (n=9), followed by the back (n=8), then the arm (n=7). CONCLUSION Soyuz landing dynamics are the most comparable analog environment for the anticipated loads associated with Orion and commercial crew vehicle landings. The MDRI under predicts the percentage of Class II injuries experienced during Soyuz landings, but it is better at predicting Class I injury occurrences. However, if contusions/abrasions are included in the minor injury Class I category, then the MDRI vastly under predicts those injuries as well. Given this data, it is important to re-evaluate the expected injury rates for future vehicles and work toward improving the predictive tools for spaceflight use. Spaceflight deconditioning may account for some of the under prediction, and work is ongoing to assess the relationship between landing injuries and impact tolerance changes due to spaceflight deconditioning. Future work includes expanding this study to involve private space missions on new vehicles to better characterize the effects of time in flight, suit and seat design, and vehicle dynamics.

N Newby↗
NASA NTRS2022

Decadal and Annual Variations in Meteoric Flux from Ulysses, Wind, and SOFIE Observations

Our solar system is filled with meteoric particles, or cosmic dust, which is either interplanetary or interstellar in origin. Interstellar dust (ISD) enters the heliosphere due to the relative motion of the sun and the interstellar flow. Interplanetary dust (IPD) comes primarily from asteroid collisions or comet sublimation, and comprises the bulk of material entering Earth’s atmosphere. This study examines variations in ISD and the IPD flux at Earth using observations from three different satellite techniques. First are size-resolved in situ meteoroid detections by the Ulysses spacecraft, and second are in situ indirect dust observations by Wind. Third are measurements of meteoric smoke in the mesosphere by the Solar Occultation For Ice Experiment (SOFIE). Wind and Ulysses observations are sorted into the interstellar and interplanetary components. Wind ISD show the anticipated correlation to the 22-yr. solar magnetic cycle, and are consistent with model predictions of ISD. Because Wind does not discriminate particle size, the IPD measurements were interpreted using meteoric mass distributions from Ulysses observations and from different models. Wind observations during 2007-2020 indicate a total meteoric influx at Earth of 22 metric tons per day (t d(exp -1)), in reasonable agreement with long-term averages from SOFIE (25 t d(exp -1)) and Ulysses (32 t d(exp -1)). The SOFIE and Wind influx time series both show an unexpected correlation to the 22-yr. solar cycle. This relationship could be an artifact, or may indicate that IPD responds to changes in the solar magnetic field.

Meteoric influx↗
NASA NTRS2022

Mapping Phyllosilicates on the Asteroid Bennu Using Thermal Emission Spectra and Machine Learning Model Applications

Bennu, the target of the OSIRIS-REx mission, is an asteroid with compositions analogous to low petrologic type CI, CM, CR, and/or ungrouped carbonaceous chondrites. Asteroids like Bennu provide information about the building blocks of the early Solar System. Analysis of the mid-infrared remote sensing data informs mineral quantification. We apply a phyllosilicate specific model, developed by Breitenfeld et al. (2021) that distinguishes between Mg and Fe serpentines, to Baseball Diamond 1 (BBD1), Equatorial Station 3 (EQ3), and Touch-And-Go OSIRIS-REx Thermal Emission Spectrometer data. The average total phyllosilicate predictions are 73 (BBD1) and 72 vol% (EQ3). We observe higher Fe-cronstedtite and lower Mg-rich serpentine content in the equatorial region of Bennu than average. Mid-infrared spectral variability may be explained by sorting effects through mass movement.

Bennu↗
NASA NTRSDate not supplied

Developing a Spectral Correlation based Method for mitigating Angular Mismatch Effects in Intercalibration Using a Benchmark Hyperspectral Sensor

The CLARREO Pathfinder (CPF) mission will implement a state-of-the-art intercalibration method for transferring CPF’s in-orbit Système Internationale (SI)-traceable reference to the shortwave channel of the Clouds and the Earth’s Radiance Energy System (CERES) and the reflective solar bands of the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the NOAA-20 satellite platform with a targeted intercalibration methodology uncertainty of 0.3% (k=1). In order to achieve such a high intercalibration accuracy, the CPF intercalibration measurements to be scheduled need to closely match those from CERES and VIIRS in time, space, angles, and wavelength. Despite’s CPF’s two-axis pointing capability to match its boresight line of sight to that of a target sensor, there will be finite residual differences in angular samplings of the two instruments. The potential angular mismatch between CPF and the target sensors can introduce systematic errors in the intercalibration results, and therefore needs to be corrected using a rigorously designed algorithm. The CPF intercalibration team has been developing a correction method for mitigating the impact of these angular anisotropic effects in the CPF-VIIRS and CPF-CERES intercalibration. The method explores the spectral correlation relationship between the reflected solar radiances from the same surface target that would be measured by CPF at two adjacent angles. Our studies have shown that the spectral information based on CPF measurements can be used to accurately predict the spectral radiance or reflectance difference due to a given mismatch in the viewing and solar geometry. The hyper-spectral information can also be used to provide scene stratification without using any auxiliary data, which is critical to reduce the angular correction uncertainty. The angular correction relationship can be well established using simulated CPF-like top-of-atmosphere spectral radiances observed at all sorts of viewing geometry and solar angles and for different scenes. Intensive radiative transfer simulations have been completed using a state-of-art radiative transfer model developed by the CPF team members. The implementation of the algorithm on high-fidelity event simulation data and the characterization for the angular adjustment uncertainty will be presented.

Wan Wu↗