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At least 667 records · Page 37

New Initiatives for the NASA Cosmic Dust Collections

The NASA Cosmic Dust Collections (CDC) have steadily grown over its forty-one-year residence at Johnson Space Center. CDC features an active acquisition program which collects new material and accessions new collections within NASA’s purview. An overview of current initiatives is described here.

M Fries↗

Petrologic Sub-types, Sub-groups, and Pairing for CV Chondrites in the US Antarctic Meteorite Collection

Carbonaceous chondrites of the Vigarano group (CV) are primitive meteorites that provide a wealth of information about the early solar system, including constraints on chondrule formation, origin of calcium-aluminum inclusions, stability of organic compounds, and redox conditions. The US Antarctic meteorite collection contains 119 CV samples from 15 dense collection areas (DCAs) from the Trans-Antarctic Mountains. These samples have been assigned a preliminary classification as CVs, but have not been assigned to the subgroups Oxidized A, Oxidized B, and Reduced. Additionally, variation in petrologic grade can be determined non-destructively using Raman spectroscopy. In order to update classification of both subgroups and petrologic types in the collection, we have acquired magnetic susceptibility, metal and sulfide compositions, and Raman spectra, for as many samples as possible. We use the recent assessment and delineation of CV sub-groups of as a guide.

solar nebula↗

Nomenclature for the OSIRIS-REx Returned Sample Collection to be Curated at NASA Johnson Space Center

The Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) space-craft collected material from the asteroid Bennu on October 20, 2020. The OSIRIS-REx Sample Return Capsule (SRC) is planned to return to Earth on September 24, 2023. The OSIRIS-REx returned sample collection to be curated at NASA Johnson Space Center (JSC) will include both the asteroid material and the flight hardware. We expect most of the asteroid material to be inside the head of the Touch-and-Go Sample Acquisition Mechanism (TAGSAM), and that this material will include a broad range of particles sizes from as large as a few centimeters to less than a micrometer across in their longest dimension. In addition, asteroid material may have been returned along with the flight hardware: intentionally by the contact pads or screens on the witness plates, or serendipitously wedged into or adhering to hardware items. The nomenclature for this new astromaterials collection must accommodate the different types of samples it comprises.

asteroid↗

Developing a Tool to Collect Microbiological Samples in Space

We developed and tested a tool to collect aseptic samples during extravehicular activity or space walks. This tool can withstand the extreme temperature (-92 – 90 ˚C) and pressure variations without compromising the sterility of the collection device or the integrity of the sample. Results from ground testing the tool demonstrate that external surfaces of space suits are not sterile and that a wide variety of human associated bacteria and some fungi can survive at least seven hours of exposure to vacuum. These bacteria include non-spore forming organisms like Staphylococcus that are not normally considered extremophiles We plan to use this tool to characterize the exterior of the International Space Station. We expect the results of this work to guide the planetary protection requirements and contamination control strategy for crewed missions to Mars. This tool could also be used to monitor contamination associated with the Artemis missions to the moon or collect aseptic samples robotically in environments that are not suitable for human exploration.

A B Regberg↗

A Remote Vehicle Operations Center’s Role in Collecting Human Factors Data

The National Aeronautics and Space Administration is supporting research to develop a prototype remote vehicle operations center at Langley Research Center to explore current and future advanced air mobility operations using small unmanned aerial systems vehicles as surrogates for future, larger-scale passenger carrying vehicles. Data collected within the Remote Operations for Autonomous Missions (ROAM) Unmanned Aerial Systems (UAS) Operations Center will be used to explore different roles and responsibilities of remote operators managing multiple autonomous vehicles, with the goal of exploring human-autonomy teaming concepts that enable m:N operations (i.e., m operators managing N vehicles). ROAM has developed into a world-class research, development, and technology (RD&T) environment that can support both the collection of human factors data and the command and control of remote vehicles in beyond visual line of sight conditions. Presented in this paper is an overview of ROAM, with a focus on the design components that support human factors data collection and a review of initial usability results of the facility.

Human factors↗

A Remote Vehicle Operations Center’s Role in Collecting Human Factors Data

The National Aeronautics and Space Administration is supporting research to develop a prototype remote vehicle operations center at Langley Research Center to explore current and future advanced air mobility operations using small unmanned aerial systems vehicles as surrogates for future, larger-scale passenger carrying vehicles. Data collected within the Remote Operations for Autonomous Missions (ROAM) Unmanned Aerial Systems (UAS) Operations Center will be used to explore different roles and responsibilities of remote operators managing multiple autonomous vehicles, with the goal of exploring human-autonomy teaming concepts that enable m:N operations (i.e., m operators managing N vehicles). ROAM has developed into a world-class research, development, and technology (RD&T) environment that can support both the collection of human factors data and the command and control of remote vehicles in beyond visual line of sight conditions. Presented in this paper is an overview of ROAM, with a focus on the design components that support human factors data collection and a review of initial usability results of the facility.

Human factors↗

Model Evaluation and Intercomparison Using Data Collected by the Langley Mobile Ozone Lidar in Hampton, Virginia

Throughout the year 2022, the Langley Mobile Ozone Lidar (LMOL) has been frequently collecting ozone and aerosol measurements in the lower troposphere. The lidar is located in the parking lot behind the Atmospheric Sciences building at NASA Langley in Hampton, Virginia, approximately 37.095 N, -76.389 W. The data was collected during a range of several distinct atmospheric conditions, including stratospheric intrusions, surface frontal passages, and long-range transported wildfire smoke plumes. We use this data to evaluate and intercompare the forecast accuracy of two atmospheric chemistry models: the GEOS Composition Forecasting model (GEOS-CF) and the Weather Research and Forecasting model with Chemistry (WRF-Chem). Both models make daily three-dimensional forecasts of many trace gases and species for the contiguous United States. Over a range of ten distinct collection events, each spanning 36 hours to nearly seven days, the forecast models predict tropospheric ozone at NASA Langley with reasonable accuracy. The models best predict the timing and shape of the observed stratospheric intrusions in the middle troposphere but often vary in the magnitude of the ozone mixing ratios. For other atmospheric conditions, there is more variability in the model accuracy. Here, we summarize the accuracy of the models for all events and investigate reasons for differences between the models and the lidar.

Daniel B. Phoenix↗

Automated Collection of Scientific Publications Linked to NASA Earth Science Datasets

NASA's Earth Observing System Data and Information System (EOSDIS) began dataset Digital Object Identifier (DOI) registration in 2012. The number of dataset DOIs registered as of January of 2023 exceeds 11,000. As the research community becomes aware of the importance of sharing data through Open Science and optimizing data reuse through Findability, Accessibility, Interoperability, and Reuse (FAIR) data management principles, datasets are increasingly being cited in scientific publications. When datasets are cited explicitly by DOI within published works, automated methods can be developed for collecting these published works from a variety of bibliometric sources. The coverage of the sources varies, so each source can collect citations that are only available within it. Using major citation databases such as Scopus and Web of Science, the Google Scholar search engine, the CrossRef Open Citation Index, and the dataset DOI registry DataCite, we present an automated workflow for dataset citation collection. By harvesting citations automatically, a citation library is created explicitly linking EOSDIS datasets to publications that cite them. Using Zotero, a free and open-source citation manager, we demonstrate how to access and browse this library by the tags indicating bibliometric sources, dataset DOI, and the dataset archive center. We also demonstrate temporary trends in the number of publications harvested from bibliometric sources.

Infometrics↗

ISS External Microorganisms: Tools and Techniques for Collecting Planetary Protection Samples During Extravehicular Activity

We have designed, built, and tested a sampling kit (Fig. 1) to aseptically collect microbiological samples from exterior surfaces on the ISS (International Space Station). The kit was flown to ISS as part of the NG-19 commercial cargo mission in August of 2023. Astronauts will use the kit to collect samples from six exterior surfaces on ISS. These samples will be frozen at -80°C after collection and returned to the ground for next generation DNA sequencing. The results of this experiment will help inform planetary protection requirements for crewed missions. We hypothesize that there are detectable microbial communities outside ISS and that these communities originate from inside ISS. Current life support systems do not include any components for reducing microbial leakage. Gases are vented from inside ISS without filtration and there are currently no protocols in place to minimize bioburden on space suit exteriors prior to use. It is important to quantify the bioburden on current vehicles so that achievable limits can be set for crewed missions to astrobiologically relevant locations like Mars.

Planetary Protection↗

Data communications for a collective operation in a parallel active messaging interface of a parallel computer

Algorithm selection for data communications in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI composed of data communications endpoints, each endpoint including specifications of a client, a context, and a task, endpoints coupled for data communications through the PAMI, including associating in the PAMI data communications algorithms and bit masks; receiving in an origin endpoint of the PAMI a collective instruction, the instruction specifying transmission of a data communications message from the origin endpoint to a target endpoint; constructing a bit mask for the received collective instruction; selecting, from among the associated algorithms and bit masks, a data communications algorithm in dependence upon the constructed bit mask; and executing the collective instruction, transmitting, according to the selected data communications algorithm from the origin endpoint to the target endpoint, the data communications message.

97 MATHEMATICS AND COMPUTING↗

Implementing asyncronous collective operations in a multi-node processing system

A method, system, and computer program product are disclosed for implementing an asynchronous collective operation in a multi-node data processing system. In one embodiment, the method comprises sending data to a plurality of nodes in the data processing system, broadcasting a remote get to the plurality of nodes, and using this remote get to implement asynchronous collective operations on the data by the plurality of nodes. In one embodiment, each of the nodes performs only one task in the asynchronous operations, and each nodes sets up a base address table with an entry for a base address of a memory buffer associated with said each node. In another embodiment, each of the nodes performs a plurality of tasks in said collective operations, and each task of each node sets up a base address table with an entry for a base address of a memory buffer associated with the task.

97 MATHEMATICS AND COMPUTING↗

Impact of Collection Equipment on Ash Variability of Baled Corn Stover Biomass for Bioenergy

Cost-effective conversion of agricultural residues for renewable energy hinges not only on the material’s quality but also the biorefinery’s ability to reliably measure quality specifications. The ash content of biomass is one such specification, influencing pretreatment and disposal costs for the conversion facility and the overall value of a delivered lot of biomass. The biomass harvest process represents a primary pathway for accumulation of soil-derived ash within baled material. In this work, the influence of five collection techniques on the total ash content and variability of ash content within baled corn stover in southwest Kansas is discussed. The equipment tested included a mower for cutting the corn stover stubble, a basket rake, wheel rake, or shred flail to gather the stover, and a mixed or uniform in-feed baler for final collection. The results showed mean ash content to range from 11.5 to 28.2 % depending on operational choice. Resulting impacts on feedstock costs for a biochemical conversion process range from $5.38 to $22.30 Mg-1 based on the loss of convertible dry matter and ash disposal costs. Collection techniques that minimized soil contact (shred flail or nonmowed stubble) were shown to prevent excessive ash contamination, whereas more aggressive techniques (mowing and use of a wheel rake) caused greater soil disturbance and entrainment within the final baled material. Material sampling and testing were shown to become more difficult as within-bale ash variability increased, creating uncertainty around feedstock quality and the associated costs of ash mitigation.

09 BIOMASS FUELS↗

Data communications for a collective operation in a parallel active messaging interface of a parallel computer

Algorithm selection for data communications in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI composed of data communications endpoints, each endpoint including specifications of a client, a context, and a task, endpoints coupled for data communications through the PAMI, including associating in the PAMI data communications algorithms and bit masks; receiving in an origin endpoint of the PAMI a collective instruction, the instruction specifying transmission of a data communications message from the origin endpoint to a target endpoint; constructing a bit mask for the received collective instruction; selecting, from among the associated algorithms and bit masks, a data communications algorithm in dependence upon the constructed bit mask; and executing the collective instruction, transmitting, according to the selected data communications algorithm from the origin endpoint to the target endpoint, the data communications message.

97 MATHEMATICS AND COMPUTING↗

Smisc - A collection of miscellaneous functions

A collection of functions for statistical computing and data manipulation. These include routines for rapidly aggregating heterogeneous matrices, manipulating file names, loading R objects, sourcing multiple R files, formatting datetimes, multi-core parallel computing, stream editing, specialized plotting, etc. Smisc-package A collection of miscellaneous functions allMissing Identifies missing rows or columns in a data frame or matrix as.numericSilent Silent wrapper for coercing a vector to numeric comboList Produces all possible combinations of a set of linear model predictors cumMax Computes the maximum of the vector up to the current index cumsumNA Computes the cummulative sum of a vector without propogating NAs d2binom Probability functions for the sum of two independent binomials dataIn A flexible way to import data into R. dbb The Beta-Binomial Distribution df2list Row-wise conversion of a data frame to a list dfplapply Parallelized single row processing of a data frame dframeEquiv Examines the equivalence of two dataframes or matrices dkbinom Probability functions for the sum of k independent binomials factor2character Converts all factor variables in a dataframe to character variables findDepMat Identify linearly dependent rows or columns in a matrix formatDT Converts date or datetime strings into alternate formats getExtension Filename manipulations: remove the extension or path, extract the extension or path getPath Filename manipulations: remove the extension or path, extract the extension or path grabLast Filename manipulations: remove the extension or path, extract the extension or path ifelse1 Non-vectorized version of ifelse integ Simple numerical integration routine interactionPlot Two-way Interaction Plot with Error Bar linearMap Linear mapping of a numerical vector or scalar list2df Convert a list to a data frame loadObject Loads and returns the object(s) in an ".Rdata" file more Display the contents of a file to the R terminal movAvg2 Calculate the moving average using a 2-sided window openDevice Opens a graphics device based on the filename extension p2binom Probability functions for the sum of two independent binomials padZero Pad a vector of numbers with zeros parseJob Parses a collection of elements into (almost) equal sized groups pbb The Beta-Binomial Distribution pcbinom A continuous version of the binomial cdf pkbinom Probability functions for the sum of k independent binomials plapply Simple parallelization of lapply plotFun Plot one or more functions on a single plot PowerData An example of power data pvar Prints the name and value of one or more objects qbb The Beta-Binomial Distribution rbb And numerous others (space limits reporting).

Landon Sego, PNNL↗

Establishing a group of endpoints to support collective operations without specifying unique identifiers for any endpoints

A parallel computer executes a number of tasks, each task includes a number of endpoints and the endpoints are configured to support collective operations. In such a parallel computer, establishing a group of endpoints receiving a user specification of a set of endpoints included in a global collection of endpoints, where the user specification defines the set in accordance with a predefined virtual representation of the endpoints, the predefined virtual representation is a data structure setting forth an organization of tasks and endpoints included in the global collection of endpoints and the user specification defines the set of endpoints without a user specification of a particular endpoint; and defining a group of endpoints in dependence upon the predefined virtual representation of the endpoints and the user specification.

97 MATHEMATICS AND COMPUTING↗

Device and method for enhanced collection and assay of chemicals with high surface area ceramic

A method and device for enhanced capture of target analytes is disclosed. This invention relates to collection of chemicals for separations and analysis. More specifically, this invention relates to a solid phase microextraction (SPME) device having better capability for chemical collection and analysis. This includes better physical stability, capacity for chemical collection, flexible surface chemistry and high affinity for target analyte.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Copper Defects and Charge Collection in Cadmium Telluride Photovoltaic Devices

In CdTe photovoltaic devices, the CdTe layer must be doped with Cu to reduce its resistivity, increase carrier lifetime, and improve hole transport. However, the Cu concentration is typically very low around the interfaces and within the CdTe layer, making it difficult to determine the influence Cu has on charge transport at the nanoscale; Cu concentrations are difficult to detect due to low ionization probability of Cu atoms [1]. Here, we use synchrotron X-ray microscopy to probe the nanoscale distribution of Cu and correlate it to local charge collection in CdTe photovoltaic devices. We demonstrate Cu segregation around grain boundaries, and, using cross-section charge collection measurements and transport modelling, show recombination center concentration in the CdTe layer dictates the interface at which charge collection occurs. The work gives insights on how Cu distributes in CdTe photovoltaic systems, and an understanding of how these distributions affect charge transport.

Walker, Trumann↗

Oxidation of Glycolate in the Defense Waste Processing Facility (DWPF) Recycle Collection Tank - 20305

The Savannah River Site's Defense Waste Processing Facility (DWPF) operations are being upgraded with the introduction of the Nitric-Glycolic Flowsheet. Glycolic acid has been shown superior to formic acid as the reducing acid used during chemical processing. The new flowsheet improves or maintains necessary parameters such as 1) reduction of mercury, 2) adjustment of feed rheology and 3) adjustment of melter oxidation/reduction potential. Further, the potential for catalytic hydrogen generation in DWPF processing is virtually eliminated. DWPF process condensates are collected and returned to the SRS Concentration, Storage and Transfer Facilities (CSTF). The Recycle Collection Tank (RCT) collects off-gas condensate during chemical processing, vitrification, and other unit operations performed in DWPF and is the singular return vessel delivering recycle effluent back to CSTF. Each batch of recycle may contain a small amount of glycolate from chemical processing and melter off-gas condensates. To avoid potential flammability issues due to thermolysis of glycolate in the CSTF, chemical oxidation within the RCT has been investigated as an option for mitigating the transfer of glycolate. Sodium permanganate has been down-selected as the best option for oxidation of glycolate. Testing was performed using both 2-L and 22-L reactors (16,800:1 and 1,530:1 scale by volume) with non-radioactive waste simulants to approximate the expected RCT compositions. RCT simulants were evaluated at various process pH and temperature conditions. Also, RCT operations, namely the sequence of addition of corrosion inhibitors (NaOH and NaNO{sub 2}) versus a permanganate strike, were evaluated. Glycolate was introduced via a sludge simulant to mimic both expected entrainment and abnormal process foam-over conditions - the range being between 68 and 5100 mg/kg glycolate. Glycolate destruction was monitored by ion chromatography (IC). The corresponding manganese behavior was monitored in real-time using in situ ultraviolet-visible (UV-Vis) spectroscopy. RCT glycolate content can be reduced to below the IC detection limit within 90 minutes for all concentrations investigated. Ion Chromatography analysis revealed that under alkaline conditions, glycolate is primarily oxidized to oxalate with no significant formation of CO{sub 2} or carbonate, and nitrite is not oxidized to nitrate. Initially, complete oxidation of organics species and nitrite was assumed. Determination of the mechanistic chemical reaction has allowed the required amount of permanganate to be more accurately predicted and the total addition to be significantly reduced. UV-Vis measurements reveal that permanganate (Mn{sup 7+}) is reduced to manganate (Mn{sup 6+}) in the RCT. The oxidant stoichiometry is defined by using the initial permanganate to glycolate (P/G) molar ratio. At low initial glycolate concentration (68 and 140 mg/kg), the minimum required initial permanganate to glycolate (P/G) molar ratio was found to be 5-6. With high initial glycolate concentrations (5100 mg/kg) a lower (P/G) molar ratio of ∼2.5 was needed. The final portion of this effort supporting the nitric/glycolic flowsheet will be to test actual (fully radioactive) RCT samples as per the above simulant tests. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗