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At least 1,513 records · Page 84

A multi-length-scale investigation of the applicability of ductility laws for annealed and work-hardened copper

Small-scale mechanical testing provides unique advantages over conventional testing in investigating the mechanical response of nuclear materials. While small-scale testing enables accelerated materials research, it raises the question of comparability to large-scale properties for engineering design considerations. Among different mechanical properties for structural design considerations such as yield and ultimate tensile stress, ductility is of critical importance with respect to structural component health. The effectiveness of using small-scale mechanical testing for probing these mechanical properties is dictated by understanding how the mechanical responses translate from the microscale to the engineering scale. Therefore, a better understanding of size scaling effects via gathering and analysis of experimental data is required to bridge length-scales. Further, this work builds upon previous reports to provide statistical data on how mechanical response changes as the size of the specimens are reduced from conventional sizes. One hundred twenty mesoscale tensile coupons of oxygen-free high thermal conductivity (OFHC) copper in work-hardened and annealed state have been manufactured using micro-wire electrical discharge machining (EDM) and tested under uniaxial tension. The mesoscale specimens have dimensions dictated by pre-selected geometric ratios (i.e., gauge section length over the square root of the cross-section area) with gauge length dimensions of 3 mm (or less) and sub-millimeter gauge widths and thicknesses. The mesoscale responses were compared to bulkscale properties to reveal the effect of specimen size on the mechanical response as a function of grain size and material state for a single phase face-centered cubic metal.

36 MATERIALS SCIENCE↗

Sampling and Analysis Plan for LSL2 Underground Storage Tank Evaluation of PFAS in Soil: Protection of Groundwater

This SAP gathers all pertinent information relevant to the sampling and analysis of soil at the removal site for a former 10,000-gallon UST and reference sites in the vicinity of the excavation site. Data Quality Objectives establishes the process and steps for the acquisition of data. Data Flow Diagram establishes the decisions and next steps. Quality Assurance Project Plan establishes the quality requirements for data collection, including planning, implementation, and assessment of sampling, field measurements, and laboratory analysis. The work is being completed for DOE-SC Pacific Northwest Site Office.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Massively parallel modeling and inversion of electrical resistivity tomography data using PFLOTRAN

Abstract. Electrical resistivity tomography (ERT) is a broadly accepted geophysical method for subsurface investigations. Interpretation of field ERT data usually requires the application of computationally intensive forward modeling and inversion algorithms. For large-scale ERT data, the efficiency of these algorithms depends on the robustness, accuracy, and scalability on high-performance computing resources. In this regard, we present a robust and highly scalable implementation of forward modeling and inversion algorithms for ERT data. The implementation is publicly available and developed within the framework of PFLOTRAN, an open-source, state-of-the-art massively parallel subsurface flow and transport simulation code. The forward modeling is based on a finite-volume discretization of the governing differential equations, and the inversion uses a Gauss–Newton optimization scheme. To evaluate the accuracy of the forward modeling, two examples are first presented by considering layered (1D) and 3D earth conductivity models. The computed numerical results show good agreement with the analytical solutions for the layered earth model and results from a well-established code for the 3D model. Inversion of ERT data, simulated for a 3D model, is then performed to demonstrate the inversion capability by recovering the conductivity of the model. To demonstrate the parallel performance of PFLOTRAN's ERT process model and inversion capabilities, large-scale scalability tests are performed by using up to 131 072 processes on a leadership class supercomputer. These tests are performed for the two most computationally intensive steps of the ERT inversion: forward modeling and Jacobian computation. For the forward modeling, we consider models with up to 122 ×106 degrees of freedom (DOFs) in the resulting system of linear equations and demonstrate that the code exhibits almost linear scalability on up to 10 000 DOFs per process. On the other hand, the code shows superlinear scalability for the Jacobian computation, mainly because all computations are fairly evenly distributed over each process with no parallel communication.

58 GEOSCIENCES↗

RECOZ data reduction and analysis: Programs and procedures

The RECOZ data reduction programs transform data from the RECOZ photometer to ozone number density and overburden as a function of altitude. Required auxiliary data are the altitude profile versus time and for appropriate corrections to the ozone cross sections and scattering effects, air pressure and temperature profiles. Air temperature and density profiles may also be used to transform the ozone density versus geometric altitude to other units, such as to ozone partial pressure or mixing ratio versus pressure altitude. There are seven programs used to accomplish this: RADAR, LISTRAD, RAW OZONE, EDIT OZONE, MERGE, SMOOTH, and PROFILE.

Reed, E. I.↗

Modeling Powered Aerodynamics for the Orion Launch Abort Vehicle Aerodynamic Database

Modeling the aerodynamics of the Orion Launch Abort Vehicle (LAV) has presented many technical challenges to the developers of the Orion aerodynamic database. During a launch abort event, the aerodynamic environment around the LAV is very complex as multiple solid rocket plumes interact with each other and the vehicle. It is further complicated by vehicle separation events such as between the LAV and the launch vehicle stack or between the launch abort tower and the crew module. The aerodynamic database for the LAV was developed mainly from wind tunnel tests involving powered jet simulations of the rocket exhaust plumes, supported by computational fluid dynamic simulations. However, limitations in both methods have made it difficult to properly capture the aerodynamics of the LAV in experimental and numerical simulations. These limitations have also influenced decisions regarding the modeling and structure of the aerodynamic database for the LAV and led to compromises and creative solutions. Two database modeling approaches are presented in this paper (incremental aerodynamics and total aerodynamics), with examples showing strengths and weaknesses of each approach. In addition, the unique problems presented to the database developers by the large data space required for modeling a launch abort event illustrate the complexities of working with multi-dimensional data.

Chan, David T.↗

Science Data Preservation: Implementation and Why It Is Important

Remote Sensing data generation by NASA to study Earth s geophysical processes was initiated in 1960 with the launch of the first Television Infrared Observation Satellite Program (TIROS), to develop a meteorological satellite information system. What would be deemed as a primitive data set by today s standards, early Earth science missions were the foundation upon which today s remote sensing instruments have built their scientific success, and tomorrow s instruments will yield science not yet imagined. NASA Scientific Data Stewardship requirements have been documented to ensure the long term preservation and usability of remote sensing science data. In recent years, the Federation of Earth Science Information Partners and NASA s Earth Science Data System Working Groups have organized committees that specifically examine standards, processes, and ontologies that can best be employed for the preservation of remote sensing data, supporting documentation, and data provenance information. This presentation describes the activities, issues, and implementations, guided by the NASA Earth Science Data Preservation Content Specification (423-SPEC-001), for preserving instrument characteristics, and data processing and science information generated for 20 Earth science instruments, spanning 40 years of geophysical measurements, at the NASA s Goddard Earth Sciences Data and Information Services Center (GES DISC). In addition, unanticipated preservation/implementation questions and issues in the implementation process are presented.

Kempler, Steven J.↗

TESS Data Release Notes: Sector 59, DR84

TESS Sector 59 observations include physical orbits 125 and 126 of the spacecraft around the Earth. Data collection was paused for a total of 0.63 days to download data. Data were downloaded approximately every seven days, once near apogee of each orbit and once near perigee. Note that the Sector 59 data were briefly made available on 2023 January 18–19 before an issue was identified that required reprocessing. Data have since been reprocessed. The reprocessing has a minimal impact on the final light curves, but resulted in a different set of TCEs than initially released. Users should re-download the data if retrieved before January 19th. In total, there are 25.79 days of science data collected in Sector 59.

TESS↗

Easy, Scalable Subsetting of GEDI Point Clouds

The GEDI Subsetter, a Python tool developed for NASA’s Multi-mission Algorithm and Analysis Platform (MAAP), optimizes the accessibility and visualization of GEDI point clouds by enabling users to efficiently subset data in a convenient, scalable manner. Complex science data often requires users to learn new software skills and handle many large files. Handling and cleaning large data sets is tedious and error-prone. These challenges significantly impede analysis. One of the goals of NASA's MAAP is to provide a platform that lowers the barrier to conducting research and analysis at scale. When a group of MAAP users wanted to conduct above-ground biomass estimation using GEDI data, we found that their existing workflow for leveraging GEDI data suffered from the barriers mentioned above. Furthermore, their workflow did not scale easily beyond a small number of granules. We found that existing tools related to GEDI data retrieval and subsetting were too limiting, so the GEDI Subsetter was written to support MAAP users’ needs. Being able to run many subsetting jobs simultaneously in the MAAP, and parallelizing the code itself, has led to significant speed improvements in obtaining relevant data, reducing subsetting time from hours to minutes. MAAP users can now more quickly and easily obtain only the data relevant to their research, by choosing which GEDI collection they want to work with (L1A, L2A, L2B, or L4A), and how they want to subset it, by specifying an area of interest, a temporal range, and relevant attributes. This has significantly reduced the feedback loop for users, allowing them to much more quickly subset GEDI data and begin their analysis. Although the GEDI Subsetter originally targeted users of the MAAP, it is generalized such that it can also be used outside of the MAAP and includes a command-line interface for convenience. Furthermore, with minor modifications, it should be possible to use it with non-GEDI data as the general pattern should be applicable to other sparse/track-based sensors.

Charles Daniels↗

Transformation of the NASA Life Sciences Portal to a FAIR Data Point

The FAIR principles emphasize optimizing metadata, the vast majority of which are textual in nature, and often organized into attribute name-value pairs. This uniformity has led to the development of guidelines and best practices for providing programmatic access to scientific data through their metadata, yielding the first iteration of the FAIR Data Point Specifications (FDPS). A key feature of the FDPS is its support for automated agents seeking and fetching data without first needing to learn a plethora of different application programming interfaces. These software agents can interrogate metadata catalogs that adhere to FDPS in a uniform manner because each catalog describes itself and its metadata schema consistently. This approach enhances the sustainability of data retrieval support, allowing systems to refine and update their metadata schemas as needed and without requiring data-seeking software agents to change how they interrogate FDPS catalogs. An essential aspect of the FDPS is the standardization of data catalog semantics, which formalizes concepts such as “metadata” and “metadata service” and links them to other concepts specifications including the Data Catalog Vocabulary (DCAT), a W3C standard that is also the basis of NASA-STD-2831 “Metadata Standard for Data Discoverability,” authored by NASA’s Office of the Chief Information Officer. The FDPS references DCAT (version 2) elements which focus on the distribution of datasets and support the goal of stream-lined catalog integration across repositories for improved data discovery. Additionally, the FDPS also prescribe the use of Linked Data Platform elements for data catalog-metadata record containment descriptions, allowing users to ascertain which data and metadata belong to which catalogs. NASA’s Life Sciences Portal is implementing the FDPS while formalizing its metadata schema to support the accelerated synthesis of knowledge from space life sciences investigations.

platform↗

Biological Data for Deep Space Mission Support

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

space biology↗

Biological Data for Deep Space Mission Support

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

space biology↗

Experimental characterization of the effects of pneumatic tubing on unsteady pressure measurements

Advances in aircraft control system designs have, with increasing frequency, required that air data be used as flight control feedback. This condition requires that these data be measured with accuracy and high fidelity. Most air data information is provided by pneumatic pressure measuring sensors. Typically unsteady pressure data provided by pneumatic sensing systems are distorted at high frequencies. The distortion is a result of the pressure being transmitted to the pressure sensor through a length of connective tubing. The pressure is distorted by frictional damping and wave reflection. As a result, air data provided all-flush, pneumatically sensed air data systems may not meet the frequency response requirements necessary for flight control augmentation. Both lab and flight test were performed at NASA-Ames to investigate the effects of this high frequency distortion in remotely located pressure measurement systems. Good qualitative agreement between lab and flight data are demonstrated. Results from these tests are used to describe the effects of pneumatic distortion in terms of a simple parametric model.

Whitmore, Stephen A.↗

Deep space communications, weather effects, and error control

Deep space telemetry is and will remain signal-to-noise limited and vulnerable to interference. A need exists to increase received signal power and decrease noise. This includes going to Ka-band in the mid-1990's to increase directivity. The effects of a wet atmosphere can increase the noise temperature by a factor of 5 or more, even at X-band, but the order of magnitude increase in average data rate obtainable at Ka-band relative to X-band makes the increased uncertainty a good trade. Lowbit error probabilities required by data compression are available both theoretically and practically with coding, at an infinitesimal power penalty rather than the 10 to 15 dB more power required to reduce error probabilities without coding. Advances are coming rapidly in coding, as with the new constraint-length 15 rate 1/4 convolutional code concatenated with the already existing Reed-Solomon code to be demonstrated on Galileo. In addition, high density spacecraft data storage will allow selective retransmissions, even from the edge of the Solar System, to overcome weather effects. In general, deep space communication was able to operate, and will continue to operate, closer to theoretical limits than any other form of communication. These include limits in antenna area and directivity, system noise temperature, coding efficiency, and everything else. The deep space communication links of the mid-90's and beyond will be compatible with new instruments and compression algorithms and represent a sensible investment in an overall end-to-end information system design.

Posner, Edward C.↗

Distributed Real-time Plume Monitoring for Deep Sea Mineral Extraction​

In the emerging industry of deep-sea mining for minerals and deposits (e.g. polymetallic nodules for nickel, cobalt, copper, and manganese), more data is required to understand the effects of sediment plume generation and predict the distribution of disturbed sediment. There are two main sources of plume generation, the first being at the active mining site where the “collector” directly removes the top layer of the sea floor. The other is the “midwater plume” consisting of unwanted sediment that was collected during extraction that is pumped back into the aphotic zone. The vast majority of plume generation is caused by the collector, causing detrimental and long-lasting impacts on seafloor ecosystems due to the lack of wave activity or strong currents at the sea floor. Therefore, it is crucial to invest in the infrastructure to support the study and constant monitoring over a large area of the sea floor where plume generation is present. Due to the limited number of usable channels and power requirements, current subsea wireless communications technologies are not well suited to instrumenting the large areas of the sea floor needed to monitor plume migration. The scope of this effort is to transition experimental demonstrations of high-bandwidth, full-duplex scalable underwater laser communications to the seafloor in an open ocean environment. Specifically tackling challenges associated with the dynamic nature of the subsea world, including but not limited to, deployment logistics, sustainability, and range. The goal is to enable the internet of underwater things for deep sea industries by broadening the capabilities of subsea communications. By using high-precision laser transmitters, many of the challenges current subsea optical systems face can be circumvented, such as power consumption, interference, and bandwidth limitations. This approach lends itself to wireless interlinking multi-node networks, in series or parallel, facilitating the implementation of a wide array of sensor types. This interlinking allows all the data gathered from the network to be processed through a single hardline uplink to the surface, lowering the complexity required for near real-time data processing. Additionally, the laser control systems produce metadata that can be used to help characterize the water column between the nodes. Combining data from various sensors such as turbidity, temperature, current velocity with metadata such as beam attenuation and deflection can produce a high-resolution model of sea floor conditions around an active mining zone. The resulting near real-time model can be used to optimize location and flow rate of the mining operation to minimize and quantify the environmental impact.

Mons, Ishan↗

From Regolith to Living Off the Land: Formulating a Data Model to Catalog Lunar Construction Materials

Artemis Program objectives for sustainable, long-term presence on the Moon and more distant planetary surfaces will require learning to “Live off the Land”, relying on in-situ resource utilization to produce infrastructure and building materials from lunar regolith, icy subsurface deposits, and residual waste materials. Meeting demand for consumables while scaling development with resources found within the landing zone will require detailed data on the geology and environment of the lunar surface. Lunar infrastructure development will generate vast amounts of new engineering data regarding availability of processed feedstocks and their performance in building materials. Lunar engineering data accessible to program partners, research institutions and industry may help situate processes and specifications within the in-situ GIS context. Lunar missions to date have generated geological and ice favorability maps of the lunar surface, and recent technology studies have tested automated construction systems and novel material formulations using regolith simulants and binders. Current discussions focus on identifying key feedstocks, quantities required for nominal mission scenarios and infrastructure plans, and mapping the value chain from regolith to feedstock to consumables and construction materials.

lunar construction↗

From Regolith to Living Off the Land: Formulating a Data Model to Catalog Lunar Construction Materials

Artemis Program objectives for sustainable, long-term presence on the Moon and more distant planetary surfaces will require learning to “Live off the Land”, relying on in-situ resource utilization to produce infrastructure and building materials from lunar regolith, icy subsurface deposits, and residual waste materials. Meeting demand for consumables while scaling development with resources found within the landing zone will require detailed data on the geology and environment of the lunar surface. Lunar infrastructure development will generate vast amounts of new engineering data regarding availability of processed feedstocks and their performance in building materials. Lunar engineering data accessible to program partners, research institutions and industry may help situate processes and specifications within the in-situ GIS context. Lunar missions to date have generated geological and ice favorability maps of the lunar surface, and recent technology studies have tested automated construction systems and novel material formulations using regolith simulants and binders. Current discussions focus on identifying key feedstocks, quantities required for nominal mission scenarios and infrastructure plans, and mapping the value chain from regolith to feedstock to consumables and construction materials.

lunar construction↗

AIRS radiometric calibration validation for climate research

Climate research using data from satellite based radiometers makes extreme demands on the traceability and stability of the radiometric calibration. The selection of a cooled grating array spectrometer for the Atmospheric Infrared Sounder, AIRS, is key, but does not ensured that AIRS data will be of climate quality. Additional design features, plus additional pre-launch testing, and extensive on-orbit calibration subsystem monitoring beyond what would suffice for application of the data to weather forecasting were required to ensure the radiometric data quality required for climate research. Validation that climate data quality are being generated makes use of the sea surface skin temperatures (SST and (obs-calc).

calibration↗