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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Supramolecular Assembly of Lanthanide-Binding Tag Peptides for Aqueous Separation of Rare Earth Elements

Selective and eco-friendly separation and purification methods for rare earth elements (REEs) are necessary to meet the increasing demand for these valuable metals, which are extensively used in modern electronics and clean energy technologies. Mining feedstocks consist of REE mixtures as stable trivalent cations (Ln 3+ ) that are difficult to separate due to their identical charge and similar size. Lanthanide-binding tags (LBTs), peptide chelates that coordinate Ln 3+ in binding pockets, show promise as selective, high-affinity extractants. We demonstrate that the LBT variant LBTLLA 5– , designed for high selectivity for Tb 3+ , is an effective extractant, forming complexes with REEs in solution that subsequently organize into self-assembling structures rich in Ln 3+ . These structures condense into aggregates that can be separated, enabling an efficient, all-aqueous, eco-friendly separation process. The self-assembled structures are studied using dynamic light scattering, ζ-potential measurements, transmission electron microscopy, anomalous small-angle X-ray scattering, inductively coupled plasma optical emission spectroscopy, and ultraviolet–visible absorption spectroscopy, which confirm LBTLLA 5– peptide-REE ion binding and the further assembly of micron-scale structures rich in REEs. Molecular dynamics simulations reveal the interactions promoting aggregation as well as the integrity of the binding pocket upon self-assembly. We find that LBTLLA 5– :Ln 3+ complexes recruit excess cations within the macrostructures, and we demonstrate that aggregation and selective separation can be controlled by manipulating the metal-peptide ratio in solution. Furthermore, we demonstrate separation from equimolar mixtures of REE pairs Tb 3+ -Lu 3+ and Tb 3+ -La 3+ , supporting the application of LBT peptides as a platform for the selective separation of REEs.

LBT peptides↗
NASA NTRS2018

NASA Earth eXchange (NEX) App Store

NASA Earth Exchange (NEX), and her public cloud version OpenNEX, have become platforms supporting scientific collaboration, knowledge sharing and research for the entire Earth science community. To date, a number of custom tools and capabilities have been integrated into the platforms. However, such integration has to undergo a case-by-case manual process thus lacks scalability. This timely project builds an App Store onto OpenNEX as a building block. Climate data analytics tools/programs can be easily uploaded, shared, organized, searched, and recommended like photos and videos on the YouTube. The foundation of our App Store is a provenance server, which not only records metadata but also execution history of climate data analytics apps including the input data and parameters, output data and products, who runs the app for which purpose, and how apps may be chained into workflows. Researchers can thus understand, reproduce, and repurpose existing apps and workflows. Machine learning approaches are applied to mine provenance to provide recommend-as-you-go services for Earth scientists, such as to recommend suitable apps and workflow snippets. A browser-based workflow tool is also provided for researchers to explore the provenance server and design value-added workflows. Scalability, sustainability, extensibility, usability, adaptability, security and privacy are considered in the App Store.

eXchange↗
NASA NTRSDate not supplied

Enabling Model Organism and Commercial Astronaut Data Access Through the NASA Open Science Data Repository

NASA’s Open Science Data Repository (OSDR) brings together omics data from NASA’s GeneLab project and non-omics data, including physiological, phenotypic, imaging, and behavioral data from NASA’s Ames Life Sciences Data Archive (ALSDA) collected from decades of space biology research, providing open and FAIR (findable, accessible, interoperable, and reusable) access of these precious data to scientists world-wide. This rich source of meticulously curated metadata and data from spaceflight and analog studies has been mined by the scientific community resulting in dozens of high impact scientific publications that reveals a complex network of molecular and physiological effects of spaceflight across living systems, from microbes to plants, to mammals. Understanding how these effects translate to the human condition is critical as we move deeper into the era of commercial space travel. However, the integration of data, specifically omics data, from astronauts is particularly challenging due to their sensitive nature. OSDR has risen to this challenge by developing a mechanism to control access to identifiable levels of omics data, such as raw sequence data, while enabling public access to processed, unidentifiable, data and associated metadata that will allow the scientific community to interrogate human astronaut data alongside data from model organisms to begin answering these critical questions. The 2021 SpaceX Inspiration4 (I4) mission collected a comprehensive atlas of biological measurements from four civilian astronauts, providing a wealth of data to characterize the effects of spaceflight on the human body. These data include both non-omics and omics assays such as direct RNA sequencing (RNA-seq), single nuclei ATAC-seq and RNA-seq, metagenomics, proteomics, and comprehensive metabolic and cytokine panels, all of which have been integrated into the OSDR system across no less than 9 studies. Each study has been carefully curated using community-backed OSDR standards for sample and assay level metadata ensuring these data are findable and accessible. In addition to hosting both raw and processed data from the principal investigator team for each assay type, the GeneLab team plans to re-process the I4 omics data using GeneLab’s standard processing pipelines. The GeneLab processed data outputs will allow for comparisons across studies on OSDR and enable visualization of these data through the OSDR data visualization platform thereby enabling data reusability and interoperability. Here we describe the robust privacy and security protocols implemented by OSDR to safeguard sensitive health data from astronauts while facilitating metadata and processed data sharing for research purposes. We further provide a road map for navigating the vast amount of data provided for each I4 study on the OSDR, including experimental design, associated experiments, payloads, and missions, data generation and analysis protocols, and associated scientific articles. Additionally, we illustrate how to interrogate the standardized metadata provided in the sample and assay tables as well as various means to download and access the data including programmatically through the GeneLab Open API (GLOpenAPI). The open access of datasets in NASA’s OSDR provides a unique opportunity for the scientific community, as well as citizen scientists and students, to continue using OSDR resources to further unlock profound insights into the consequences of space travel on the human body. Through implementation of security measures to protect sensitive human data, the OSDR seeks to strengthen the science exchange between the Biological and Physical Sciences Program and the Human Research Program, per recommendation 4-1 of the 2023-2032 Decadal Survey, and encourage further sharing and dissemination of astronaut data to provide the scientific community with the resources needed to lay the groundwork for developing targeted mitigation strategies to help withstand the rigors of long-duration spaceflight.

Amanda Marie Saravia-butler↗
NASA NTRSDate not supplied

Enabling Model Organism and Commercial Astronaut Data Access Through the NASA Open Science Data Repository

NASA’s Open Science Data Repository (OSDR) brings together omics data from NASA’s GeneLab project and non-omics data, including physiological, phenotypic, imaging, and behavioral data from NASA’s Ames Life Sciences Data Archive (ALSDA) collected from decades of space biology research, providing open and FAIR (findable, accessible, interoperable, and reusable) access of these precious data to scientists world-wide. This rich source of meticulously curated metadata and data from spaceflight and analog studies has been mined by the scientific community resulting in dozens of high impact scientific publications that reveals a complex network of molecular and physiological effects of spaceflight across living systems, from microbes to plants, to mammals. Understanding how these effects translate to the human condition is critical as we move deeper into the era of commercial space travel. However, the integration of data, specifically omics data, from astronauts is particularly challenging due to their sensitive nature. OSDR has risen to this challenge by developing a mechanism to control access to identifiable levels of omics data, such as raw sequence data, while enabling public access to processed, unidentifiable, data and associated metadata that will allow the scientific community to interrogate human astronaut data alongside data from model organisms to begin answering these critical questions. The 2021 SpaceX Inspiration4 (I4) mission collected a comprehensive atlas of biological measurements from four civilian astronauts, providing a wealth of data to characterize the effects of spaceflight on the human body. These data include both non-omics and omics assays such as direct RNA sequencing (RNA-seq), single nuclei ATAC-seq and RNA-seq, metagenomics, proteomics, and comprehensive metabolic and cytokine panels, all of which have been integrated into the OSDR system across no less than 9 studies. Each study has been carefully curated using community-backed OSDR standards for sample and assay level metadata ensuring these data are findable and accessible. In addition to hosting both raw and processed data from the principal investigator team for each assay type, the GeneLab team plans to re-process the I4 omics data using GeneLab’s standard processing pipelines. The GeneLab processed data outputs will allow for comparisons across studies on OSDR and enable visualization of these data through the OSDR data visualization platform thereby enabling data reusability and interoperability. Here we describe the robust privacy and security protocols implemented by OSDR to safeguard sensitive health data from astronauts while facilitating metadata and processed data sharing for research purposes. We further provide a road map for navigating the vast amount of data provided for each I4 study on the OSDR, including experimental design, associated experiments, payloads, and missions, data generation and analysis protocols, and associated scientific articles. Additionally, we illustrate how to interrogate the standardized metadata provided in the sample and assay tables as well as instructions for how to download and access the data. The I4 datasets described here re present the first ever comprehensive collection of commercial astronaut data.

Amanda M Saravia-Butler↗
DOE OSTI2021

Strategic Petroleum Reserve Cavern Leaching Monitoring CY20

The U.S. Strategic Petroleum Reserve is a crude oil storage system run by the U.S. Department of Energy. The reserve consists of 60 active storage caverns spread across four sites in Louisiana and Texas, near the Gulf of Mexico. Beginning in 2016, the SPR began executing U.S. congressionally mandated oil sales. The configuration of the reserve, with a total capacity of greater than 700 MMB, requires raw water to be used instead of saturated brine for oil withdrawals such as for sales. All sales will produce leaching within the caverns used for oil delivery. Twenty-five caverns had a combined total of over 39 MMB of water injected in CY 20 as part of the Exchange for Storage program; oil was withdrawn in the same manner as for congressionally mandated sales. Leaching effects were monitored in these caverns to understand how the oil withdrawals may impact the long-term integrity of the caverns. While frequent sonars are the best way to monitor changes in cavern shape, they can be resource intensive for the number of caverns involved in sales and exchanges. An intermediate option is to model the leaching effects and see if any concerning features develop. The leaching effects were modeled here using the Sandia Solution Mining Code (SANSMIC) . The results indicate that leaching induced features are not of concern in the majority of the caverns, 19 of 25. Six caverns, BH-107, BH-113, BH-114, BM-4, BM-106, and WH-114 have features that may grow with additional leaching and should be monitored as leaching continues in those caverns. Ten caverns had post sale sonars that were compared with SANSMIC results. SANSMIC was able to capture the leaching well , particularly the formation of shelves and flares. A deviation in the SANSMIC and sonar cavern shapes was observed near the cavern floor in caverns with significant floor rise, a process not captured by SANSMIC. These results suggest SANSMIC is a useful tool for monitoring changes in cavern shape due to leaching effects related to sales and exchanges.

02 PETROLEUM↗
DOE OSTI2019

Visual Detection with Context for Document Layout Analysis

We present 1) a work in progress method to visually segment key regions of scientific articles using an object detection technique augmented with contextual features, and 2) a novel dataset of region-labeled articles. A continuing challenge in scientific literature mining is the difficulty of consistently extracting high-quality text from formatted PDFs. To address this, we adapt the object-detection technique Faster R-CNN for document layout detection, and incorporate contextual information that leverages the inherently localized nature of article contents to improve the region detection performance. Due to the limited availability of region-labels for scientific articles, we also contribute a novel dataset of region annotations, the first version of which covers 9 region classes and 822 article pages. Initial experimental results demonstrate a 23.9% absolute improvement in mean average precision over the baseline by incorporating contextual features, and a processing speed 14x faster than a text-based technique. Ongoing work on further improvements is also discussed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Machine learning in nuclear materials research

Nuclear materials are often demanded to function for extended time in extreme environments, including high radiation fluxes with associated transmutations, high temperature and temperature gradients, mechanical stresses, and corrosive coolants. They also have a wide range of microstructural and chemical makeups, resulting in multifaceted and often out-of-equilibrium interactions. Machine learning (ML) is increasingly being used to tackle these complex time-dependent interactions and aid researchers in developing models and making predictions, sometimes with better accuracy than traditional modeling that focuses on one or two parameters at a time. Conventional practices of acquiring new experimental data in nuclear materials research are often slow and expensive, limiting the opportunity for data-centric ML, but new methods are changing that paradigm. Here we review high-throughput computational and experimental data approaches, especially robotic experimentation and active learning that is based on Gaussian process and Bayesian optimization. We show ML examples in structural materials (e.g., reactor pressure vessel (RPV) alloys and radiation detecting scintillating materials) and highlight new techniques of high-throughput sample preparation and characterizations, and automated radiation/environmental exposures and real-time online diagnostics. Herein, this review suggests that ML models of material constitutive relations in plasticity, damage, and even electronic and optical responses to radiation are likely to become powerful tools as they develop. Finally, we speculate on how the recent trends of using natural language processing (NLP) to aid the collection and analysis of literature data, interpretable artificial intelligence (AI), and the use of streamlined scripting, database, workflow management, and cloud computing platforms that will soon make the utilization of ML techniques as commonplace as the spreadsheet curve-fitting practices of today.

36 MATERIALS SCIENCE↗
NASA NTRS1975

Interdisciplinary applications and interpretations of ERTS data within the Susquehanna River basin

The author has identified the following significant results. The full potential of high quality data is achieved only with the application of efficient and effective interpretation techniques. An excellent operating system for handling, processing, and interpreting ERTS-1 and other MSS data was achieved. Programs for processing digital data are implemented on a large nondedicated general purpose computer. Significant results were attained in mapping land use, agricultural croplands, forest resources, and vegetative cover. Categories of land use classified and mapped depend upon the geographic location, the detail required, and the types of lands use of interest. Physiographic and structural provinces are spectacularly displayed on ERTS-1 MSS image mosaics. Geologic bedrock structures show up well and formation contacts can sometimes be traced for hundreds of kilometers. Large circular structures and regional features, previously obscured by the detail of higher resolution data, can be seen. Environmental monitoring was performed in three areas: coal strip mining, coal refuse problems, and damage to vegetation caused by insects and pollution.

Mcmurtry, G. J.↗
NASA NTRS2012

Aircraft Anomaly Detection Using Performance Models Trained on Fleet Data

This paper describes an application of data mining technology called Distributed Fleet Monitoring (DFM) to Flight Operational Quality Assurance (FOQA) data collected from a fleet of commercial aircraft. DFM transforms the data into aircraft performance models, flight-to-flight trends, and individual flight anomalies by fitting a multi-level regression model to the data. The model represents aircraft flight performance and takes into account fixed effects: flight-to-flight and vehicle-to-vehicle variability. The regression parameters include aerodynamic coefficients and other aircraft performance parameters that are usually identified by aircraft manufacturers in flight tests. Using DFM, the multi-terabyte FOQA data set with half-million flights was processed in a few hours. The anomalies found include wrong values of competed variables, (e.g., aircraft weight), sensor failures and baises, failures, biases, and trends in flight actuators. These anomalies were missed by the existing airline monitoring of FOQA data exceedances.

Gorinevsky, Dimitry↗
NASA NTRS1992

Energy for lunar resource exploitation

Humanity stands at the threshold of exploiting the known lunar resources that have opened up with the access to space. America's role in the future exploitation of space, and specifically of lunar resources, may well determine the level of achievement in technology development and global economic competition. Space activities during the coming decades will significantly influence the events on Earth. The 'shifting of history's tectonic plates' is a process that will be hastened by the increasingly insistent demands for higher living standards of the exponentially growing global population. Key to the achievement of a peaceful world in the 21st century, will be the development of a mix of energy resources at a societally acceptable and affordable cost within a realistic planning horizon. This must be the theme for the globally applicable energy sources that are compatible with the Earth's ecology. It is in this context that lunar resources development should be a primary goal for science missions to the Moon, and for establishing an expanding human presence. The economic viability and commercial business potential of mining, extracting, manufacturing, and transporting lunar resource based materials to Earth, Earth orbits, and to undertake macroengineering projects on the Moon remains to be demonstrated. These extensive activities will be supportive of the realization of the potential of space energy sources for use on Earth. These may include generating electricity for use on Earth based on beaming power from Earth orbits and from the Moon to the Earth, and for the production of helium 3 as a fuel for advanced fusion reactors.

Glaser, Peter E.↗
DOE OSTI2019

Heat‐Generating Nuclear Waste in Salt: Field Testing and Simulation

Core Ideas A field‐scale experiment and numerical simulations confirm salt backfill behavior. Simulations closely match temperature around and under the piled salt backfill. Results indicate limited dissolution–precipitation reactions around the heat source. Alteration of backfill is unlikely if the drift is allowed to dry before emplacement. Investigations relating to in‐drift disposal of heat‐generating nuclear waste in salt have raised questions about heat–brine interactions in the unsaturated run‐of‐mine (RoM) salt pile used as backfill. These interactions have the potential to change the structure of the RoM salt surrounding the canister, possibly altering long‐term containment of the source. An experiment is in progress at the Waste Isolation Pilot Plant (WIPP), New Mexico, in which a heated canister was placed on the floor of an open drift, covered in a pile of RoM salt, and energized with 1000 W. Temperature in the RoM salt pile had stabilized after about 15 d, allowing evaluation of the heat‐up period of the ongoing experiment. Using a multiphase porous flow simulator that has been modified to handle salt‐specific coupled processes, we examined coupled thermal–hydrological–chemical behavior in the RoM salt pile. Our simulations suggest that for the relatively dry cases examined, porosity changes within RoM salt in a generic salt repository are likely to be minor in the period between waste emplacement and plastic closure of the drift. The primary sensitivity for porosity change is to the early moisture content of the RoM salt used to cover the canister. Secondary influences include moisture availability from the disturbed rock zone (DRZ) surrounding the drift and the capillary pressure ratio between the DRZ and the RoM salt. Early changes in porosity and permeability may be affected by moisture content, but this was not observed in the test. Such changes would be most likely to occur when using damp RoM salt or if waste is emplaced in a drift immediately following opening of the drift before evaporative dewatering of the drift walls occurs.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2012

Appropriate Simulants are a Requirement for Mars Surface Systems Technology Development

To date, there are two simulants for martian regolith: JSC Mars-1A, produced from palagonitic (weathered) basaltic tephra mined from the Pu'u Nene cinder cone in Hawaii [1] by commercial company Orbitec, and Mojave Mars Simulant (MMS), produced from Saddleback Basalt in the western Mojave desert by the Jet Propulsion Laboratory [2]. Until numerous recent orbiters, rovers, and landers were sent to Mars, weathered basalt was surmised to cover every inch of the martian landscape. All missions since Viking have disproven that the entire martian surface is weathered basalt. In fact, the outcrops, features, and surfaces that are significantly different from weathered basalt are too numerous to realistically count. There are gullies, evaporites, sand dunes, lake deposits, hydrothermal deposits, alluvium, etc. that indicate sedimentary and chemical processes. There is no one size fits all simulant. Each unique area requires its own simulant in order to test technologies and hardware, thereby reducing risk.

Edmunson, Jennifer E.↗
NASA NTRS2003

Reference Material Kydex(registered trademark)-100 Test Data Message for Flammability Testing

The Marshall Space Flight Center (MSFC) Materials and Processes Technical Information System (MAPTIS) database contains, as an engineering resource, a large amount of material test data carefully obtained and recorded over a number of years. Flammability test data obtained using Test 1 of NASA-STD-6001 is a significant component of this database. NASA-STD-6001 recommends that Kydex 100 be used as a reference material for testing certification and for comparison between test facilities in the round-robin certification testing that occurs every 2 years. As a result of these regular activities, a large volume of test data is recorded within the MAPTIS database. The activity described in this technical report was undertaken to mine the database, recover flammability (Test 1) Kydex 100 data, and review the lessons learned from analysis of these data.

Engel, Carl D.↗
DOE OSTI2021

Case Study: Hybrid Carbon Conversion Using Low-Carbon Energy Sources in Coal-Producing States

The demand for more carbon efficient power sources and a decrease in natural gas prices has decreased the desire for coal power. This decrease in demand has led to massive job losses in coal mining regions over the past decade. The purpose of this project is to develop a hybrid energy system utilizing both a coal power plant and advanced reactor, which is competitive with natural gas by improving on profitability and decreasing carbon emissions. This report details the problem with a summary of the impact on the coal industry and the availability of renewable energy sources in the Appalachian region. Because of the geography of the region, variable renewable energy sources are not available without significant size and siting restrictions. However, biomass in the form of wood waste is abundant and can be used as a carbon neutral energy source. Combining biomass and coal processing, in addition to thermal power plants, can increase system profits and efficiency by providing peaking power and conversion opportunities for secondary markets. The electric load is based on publicly available demand data from Appalachian Power, which services the western Virginia and southern West Virginia in the Appalachian region. The demand information is combined by service, normalized, and scaled to an average demand of 1000 kW, which will be the basis for sizing the hybrid energy system. A traditional screening curve analysis for a coal plant and advanced reactor shows that the least cost design varies significantly based on the assumed discount rate and capital recovery period. An optimization program to size the design in TEAL based on the load curve gives 10 optimal designs, all with a negative resulting net present value (NPV) and a coal plant capacity of less than 15%. Including profits from selling captured carbon at a flat rate results in a positive NPV; however, the coal capacity factor only increases to about 40%. There are limitations with this optimization as well since the price of CO2 is likely to decrease as more is sold to the conversion market. The suggested design will combine coal power, an advanced reactor, and coal and biomass coprocessing to produce a variety of products that can be sold to the conversion market while increasing system efficiency. The analysis of conversion pathways for coal and biomass reveals that multiple options will need to be included in the analysis to produce the optimal system design. Three systems will be optimized and compared to determine the best design based on the figures of merit of total NPV and cost of carbon avoided. The first system will include a coal power plant and an advanced reactor that will sell electricity to the grid to meet demand and sell captured carbon to the conversion market. The second system adds a high-temperature steam electrolysis plant, which will utilize electricity during times of low demand to produce hydrogen and sell it to the conversion market. The third system adds biomass and coal processing with options for hydrocarbon oils, syngas to be produced for the conversion market, and electricity generation to power components within the system or provide peaking power. This analysis will be based on a new approach that combines traditional screening curve methods with a dispatch algorithm that optimizes the system based on the opportunity cost of different production options. The resulting optimization algorithm should provide results with less processing time than HERON’s decision tree method. The results from this analysis will determine an optimal design and reinforce the benefits of coal power when used in a hybrid energy system. The initial results show that the addition of a secondary market for carbon sales could result in a positive NPV and increases the capacity factor of the coal plant as compared to a design with only sales to the electricity market. The addition of more markets and additional coal consumption from biomass coprocessing could increase NPV further, replace carbon in other markets through the sale of biomass-derived hydrocarbons, and demonstrate the value of coal power technology.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Biomanufacturing and bioprocessing of lunar regolith

Microbial biomanufacturing is important to accelerate lunar construction because it can leverage lunar material and waste streams as feedstocks to create a circular production system. In-space bio-mining and biomanufacturing using moon and asteroidal source material will enable the creation of infrastructure, produce industrial fuels and lubricants, and enable recovery of actinides and rare-earth elements (REEs) present in trace concentrations. Moreover, biomanufacturing in closed-loop systems (recycling and reuse of resources toward the establishment of a circular economy) will enable long-term lunar activities by recycling waste (CO 2 , gray water) and producing oxygen and biomaterials. Our response focuses on the use of lunar regolith and waste streams as feedstocks for protein and microbial-enabled biomining and bioprocessing to extract actinides and REEs, and to create biocomposites for lunar infrastructure. We envision an enclosed process that initiates with (1a) extracting actinides and REEs from lunar regolith using immobilized proteins, followed by (1b) creating biocomposites from the post-extracted lunar regolith for infrastructure, and (1c) cultivating diatoms and other microalgae on waste streams to harvest silica shells for incorporating into biocomposites and to generate O 2 for human respiration and/or producing refinable feedstocks. LLNL has significant expertise in all three processes and provides facilities, personnel, and expertise at the intersection of metal (lanthanide, actinide, transition) separations, purifications, biohydrometallurgy, radiobiochemistry, synthetic and systems biology, and materials science and engineering. Importantly, all three processes are relatively well-studied for Earth-based workflows and can be derisked for demonstration on the lunar surface by 2029.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1991

Water resources and hydrology of Mars

The surface of Mars has been extensively modified by a large variety of water erosional and depositional processes. Although liquid water is presently unstable on the planet's surface, in its cold, hyperarid climate, there is abundant geomorphological evidence of past fluvial valley development multiple episodes of catastrophic flooding, periglacial landforms, ice-related permafrost, lake deposits, eroded impact craters and possible glacial landforms throughout much of Mars' geological history. The amount of water required to form such features is estimated to be equivalent to a planet-wide layer approximately 50 meters deep. Some of this water undoubtedly was removed from the planet by atmospheric escape processes, but much probably remains in the subsurface of Mars. Jakosky summarized the present partitioning of water on Mars, expressed as an average global depth, as follows: in the polar caps, 30 meters; in the megaregolith, 500 to 1000 meters; structurally bound in clays, 10 meters; and in high latitude regolith, a few meters. However, most of this water is probably in the form of ice, except in anomalous areas of possible near surface liquid water, and in regions where hydrothermal systems are still active. The best locations for prospecting are those areas where water or ice is sufficiently concentrated at shallow enough depths to make it feasible to pump out or mine.

Baker, V. R.↗
NASA NTRS2003

Use of Computed Tomography for Characterizing Materials Grown Terrestrially and in Microgravity

Computed Tomography (CT) has advanced considerably since being responsible for such dramatic advances in diagnostics within the medical field. It has become a major tool in non destructive evaluation (NDE), and is used in many fields as diverse as coal-mining to metal solidification to examination of rock cores. A review of industrial applications has been written by Dennis. It is only recently that the technique has been seriously used to determine composition through precise measurement of density. While such applications are restricted to cases when there is no ambiguity in the relationship of composition to density. Thus alloy solid solutions lend themselves to compositional analysis provided there is a large change in density with composition. The technique is most useful when rapid non-destructive evaluation is needed. Such cases will occur with samples returning from the International Space Station (ISS) when knowledge of the results could affect future strategies for processing of on-board samples. Experiments from those Principal Investigators (PI) that are most likely to benefit from early CT scanning are discussed. With a dearth of samples, the major emphasis in the first part of this project has been on preparing suitable standards, optimizing the CT technique for these applications, and using the CT system to determine density variations with temperature. An interesting application of CT has been in the examination of meteorites, which can be classified as space-grown materials and will certainly have solidified in a low gravity environment.

Gillies, Donald C.↗
NASA NTRS2017

Mass and Reliability Source (MaRS) Database

The Mass and Reliability Source (MaRS) Database consolidates components mass and reliability data for all Oribital Replacement Units (ORU) on the International Space Station (ISS) into a single database. It was created to help engineers develop a parametric model that relates hardware mass and reliability. MaRS supplies relevant failure data at the lowest possible component level while providing support for risk, reliability, and logistics analysis. Random-failure data is usually linked to the ORU assembly. MaRS uses this data to identify and display the lowest possible component failure level. As seen in Figure 1, the failure point is identified to the lowest level: Component 2.1. This is useful for efficient planning of spare supplies, supporting long duration crewed missions, allowing quicker trade studies, and streamlining diagnostic processes. MaRS is composed of information from various databases: MADS (operating hours), VMDB (indentured part lists), and ISS PART (failure data). This information is organized in Microsoft Excel and accessed through a program made in Microsoft Access (Figure 2). The focus of the Fall 2017 internship tour was to identify the components that were the root cause of failure from the given random-failure data, develop a taxonomy for the database, and attach material headings to the component list. Secondary objectives included verifying the integrity of the data in MaRS, eliminating any part discrepancies, and generating documentation for future reference. Due to the nature of the random-failure data, data mining had to be done manually without the assistance of an automated program to ensure positive identification.

Valdenegro, Wladimir↗