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At least 685 records · Page 38

Thermal Analysis of the X3 Hall Thruster

Electric propulsion has generated significant interest recently as a mass efficient thrust option for deep space missions. This increased interest has drawn a renewed focus on improving the efficiency of electric propulsion thrusters, specifically Hall thrusters. Hall thrusters are a specific subset of ion engines that accelerate charged particles using a Hall current. Recent research into the 12.5 kW HERMeS (Hall Effect Rocket with Magnetic Shielding) for use on the proposed Asteroid Redirect Robotic Mission (ARRM) has shown the desire to use these devices on flight missions outside of earth orbit. This paper will focus on another Hall thruster, the X3. The X3 is a 100 kW class Hall effect thruster used for laboratory technology development. What makes the X3 unique, relative to more contemporary Hall thrusters beyond the order of magnitude increase in discharge power, is that the X3 is a 3 channel, nested Hall thruster. Common Hall thrusters typically have one annular channel where the plasma is constrained and used to charge the fuel and accelerated. The X3’s 3 channels are nested in a concentric format, with each channel fitting in a single plane. This presents very unique thermal modeling challenges with respect to quantifying the impact of plasma thermal loading and cross talk between the power dissipating components for each channel. This work will discuss the development of the X3 thermal model and the efforts to validate it with experimental data. Furthermore, some of the unique challenges that appear when trying to model high power components will be discussed. The X3 represents a challenging and interesting example of the issues affecting thermal modeling of high power electric propulsion thrusters which will become more prevalent as their use becomes more common. II

Hofer, Richard Jr.↗

Open Science for Life in Space: Data Sharing and Tools for Knowledge Discovery

The next era in human space exploration is rapidly approaching and will require the use of countermeasures to deep space health hazards. The development of countermeasures (or, the re-purposing of existing agents) will be highly dependent on our understanding of basic biological responses to space stressors (e.g. ionizing radiation, altered gravitational fields, altered day-night cycles, confinement, isolation, hostile-closed environments, distance-duration from Earth, exposure to celestial regolith, etc.). The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, imaging, whole organism and behavior). We will discuss here several strategies that NASA’s Biological and Physical Science Division has put in place to maximize the return on investment for spaceflight bioscience data. Open Science, as a scientific philosophy, is the concept that the more people who have access to the data, the more knowledge will be gained from it. This guiding principle led NASA to develop GeneLab in 2015. GeneLab houses spaceflight and relevant ground-based multi-omics data, and has grown to ~400 transcriptomic, proteomic, metabolomic and epigenomic datasets from plant, rodent, small animal, and microbial space experiments. GeneLab provides users with various tools for data analysis and a visualization portal that allows users to interact with gene expression data from space-related ‘omics experiments. Open Science is also about building scientific communities, and with this spirit in mind, GeneLab has spawned several Analysis Working Groups (AWGs), comprised of more than 200 volunteer scientists. The AWGs initially provided feedback on the processing pipeline and metadata ‘omics standards for GeneLab. Over the last few years, they have become a community-driven science enterprise, engaging in large meta-analysis of GeneLab datasets, resulting in 10 publications (beyond the originally submitted research). Overall, the Open Science nature of GeneLab has resulted in a high degree of data re-use, resulting in 38 additional publications derived from the original 67 publication over the past four years. The enormous success and knowledge gained from GeneLab has led to a collection of sister NASA “Open Science Data Repositories (OSDR)” and research support groups. These include the NASA Ames Life Sciences Data Archive (ALSDA), the NASA Biological Institutional Scientific Collection (NBISC), and the Biospecimen Sharing Program (BSP). All are adopting the GeneLab data architecture system to maximize open-access, find-ability, accessibility, interoperability, and reusability (FAIR). ALSDA collects and curates phenotypic-physiological bioimaging-behavioral data from space and space-relevant non-human experiments, oftentimes coming from the same omics-associated experimental datasets found in GeneLab. Since 2021, a community of ~100 researchers have rallied around ALSDA, to provide feedback in a new ALSDA AWG focused on phenotypic-physiological investigation-sample-assay metadata standards (e.g., Micro-Computed Tomography, Light/Fluorescence Microscopy, Western Blot, Flow Cytometry, Novel Object Recognition, Elevated Plus Maze, etc. of ~50 assays collected). These standards are part of a new single point-of-entry data submission portal for all non-human Space Biology and Human Research Program principal investigators, to submit, curate, and share their research data. With open-access space biological data now collected and curated together with rich metadata, and with the potential for linkage to “big data” from the international biological and medical communities (NIH, EBI, etc.), the artificial intelligence and machine learning (AI/ML) era has started for Space Biology. Several other talks will cover these topics in this conference.

life sciences↗

Open Science for Life in Space: Data Sharing and Tools for Knowledge Discovery

The next era in human space exploration is rapidly approaching and will require the use of countermeasures to deep space health hazards. The development of countermeasures (or, there-purposing of existing agents) will be highly dependent on our understanding of basic biological responses to space stressors (e.g. ionizing radiation, altered gravitational fields, altered day-night cycles, confinement, isolation, hostile-closed environments, distance-duration from Earth, exposure to celestial regolith, etc.). The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, imaging, whole organism and behavior). We will discuss here several strategies that NASA's Biological and Physical Science Division has put in place to maximize the return on investment for spaceflight bioscience data. Open Science, as a scientific philosophy, is the concept that the more people who have access to the data, the more knowledge will be gained from it. This guiding principle led NASA to develop GeneLab in 2015. GeneLab houses spaceflight and relevant ground-based multi-omics data, and has grown to ~400 transcriptomatic, proteomic, metabolomic and epigenomic datasets from plant, rodent, small animal, and microbial space experiments. GeneLab provides users with various tools for data analysis and a visualization portal that allows users to interact with gene expression data from space-related 'omics experiments. Open Science is also about building scientific communities, and with this spirit in mind, GeneLab has spawned several Analysis Working Groups (AWGs), comprised of more than 200 volunteer scientists. The AWGs initially provided feedback on the processing pipeline and metadata 'omics standards for GeneLab. Over the last few years, they have become a community-driven science enterprise, engaging in large meta-analysis of GeneLab datasets, resulting in 10 publications (beyond the originally submitted research). Overall, the Open Science nature of GeneLab has resulted in a high degree of data-use, resulting in 40 enabled publications by open data. The enormous success and knowledge gained from GeneLab has led to a collection of sister NASA "Open Science Data Repositories (OSDR)" and research support groups. These include the NASA Ames Life Sciences Data Archive (ALSDA), the NASA Biological Institutional Scientific Collection (NBISC), and the Biospecimen Sharing Program (BSP). All are adopting the GeneLab data architecture system to maximize open-access, find-ability, accessibility, interoperability, and reusability (FAIR). ALSDA collects and curates phenotypic-physiological bioimaging-behavioral data from space and space-relevant non-human experiments, oftentimes coming from the same omics-associated experimental datasets found in GeneLab. Since 2021, a community of ~100 researchers have rallied around ALSDA, to provide feedback in a new ALSDA AWG focused on phenotypic-physiological investigation-sample-assay metadata standards (e.g., Micro-Computed Tomography, Light/Flourescence Microscopy, Western Blot, Flow Cytometry, Novel Object Recognition, Elevated Plus Maze, etc. of ~50 assays collected). These standards are part of a new single point-of-entry data submission portal for all non-human Space Biology and Human Research Program principal investigators, to submit, curate, and share their research data. With open-access space biological data now collected and curated together with rich metadata, and with the potential for linkage to "big data" from the international biological and medical communities (NIH, EBI, etc.), the artificial intelligence and machine learning (AI/ML) era has started for Space Biology.

omics↗

A Web-based Collaborative Tool for Mars Analog Data Exploration

Solving today's complex research and modeling challenges are dependent on our ability to discover, access, integrate, and share information from multiple sources. The planetary sciences community is no exception'; over the last few years, the need for data mining and exploration tools that can expedite comparative studies between Martian and terrestrial analogs sites and aid the interpretation of Mars data sets has become evident. Data sharing maximizes scientific return from studies and data sets.

Necsoiu, M.↗

High-Resolution Gridded Level 3 Aerosol Optical Depth Data from MODIS

The state-of-art satellite observations of atmospheric aerosols over the last two decades from NASA's MODIS instruments have been extensively utilized in climate change and air quality research and applications. The operational algorithms now produce level 2 aerosol data at varying spatial resolutions (1, 3, and 10 km) and level 3 data at 1 degree. The local and global applications have been benefited from the coarse resolution gridded data sets (i.e., level 3, 1 degree), as it is easier to use since data volume is low and, several online and offline tools are readily available to access and analyze the data with minimal computing resources. At the same time, researchers who require data at much finer spatial scales have to go through a challenging process of obtaining, processing, and analyzing larger volumes of data sets that require high-end computing resources and coding skills. Therefore, we have created a high spatial resolution (HRG, 0.1x0.1 degree) daily and monthly aerosol optical depth (AOD) product by combining two MODIS operational algorithms, namely Deep Blue (DB) and Dark Target (DT). The new HRG AODs meets the accuracy requirements of level 2 AOD data and provide either the same or more spatial coverage on daily and monthly scales. The data sets are provided in daily and monthly files through open Ftp server with python scripts to read and map the data. The reduced data volume with an easy to use format and tools to access the data will encourage more users to utilize the data for research and applications.

aerosol↗

The NASA Open Science Data Repository: Biomedical Data, Analysis Tools, and Informatic Collaborations

Increased biomedical risks and challenges associated with deep space missions require knowledge discovery, health countermeasures, and biomedical support capabilities. Maximally open-access and reusable data is needed by developers, scientists, and engineers to develop these systems. The NASA Open Science Data Repository (OSDR) is a maximally open access and FAIR database (ie., findable, accessible, interoperable, and reusable), and meets various scientific, technical, and operational needs. It offers users and submitters the ability to upload, download, search, share, analyze, cite, and visualize data across ‘omics, physiological, phenotypic, payload, hardware, behavioral, bioimaging, video, and environmental monitoring telemetry datasets. OSDR is an expanded database, based upon the successes of NASA GeneLab. OSDR has >460 studies with datasets covering model organisms to non-NASA human astronauts. There are ~12 datasets from the Inspiration 4 (I4) mission, spanning metagenomics, comprehensive metabolic panels, clonal hematopoiesis, spatial transcriptomics, proteomics, and cytokine panels. In the interest of data privacy, two I4 datasets with raw files relating to the epitranscriptome, and a new request feature is live in OSDR (with a backend review process established) developed from industry norms. OSDR is collecting and curating biomedical human data from a new sub-orbital research flight and is open to more space life science/biomedical submissions from the international and commercial sectors. OSDR also recently began a collaboration with the European Space Agency (ESA) to collect and curate >200 terabytes of human and model organism data. The OSDR submission portal is designed to ingest and curate ~25 ‘omics and ~50 physiological-phenotypic-imaging assay data types. Tools available for OSDR users include: 1) an Environmental Data Application to compare radiation, CO2, relative humidity, temperature, and other telemetry across missions and subjects, 2) the RadLab database, a collaboration between NASA, ESA, the German and Italian Space Agencies, and the Bulgarian Academy of Sciences, and 3) a Multi-study visualization tool which enables users to look across and combine ‘omics datasets. There are ~600 volunteer OSDR Analysis Working Group (AWG) members providing feedback on scientific data/metadata standards and collaborating to mine-reuse OSDR in research. OSDR/GeneLab has enabled ~60 publications reusing data as of October 2023.

space biology↗

Airborne for All Engaging the ESIP Community to Explore Findings from a Recent Airborne and Field Data Workshop and Identify Synergies Across Organizations

The highly diverse, heterogeneous, and cross-disciplinary nature of airborne Earth observation provides unique challenges for those who want to use the data for scientific research and applications. NASA recently held its first Airborne and Field data workshop as a collaborative, open forum for users and producers of airborne Earth observations to discuss their experiences and concerns. During the two day event, NASA collected feedback from attendees about what NASA is doing well and what needs are still unmet in order to determine how NASA can better help the community make use of airborne and field data. In this session, we will report on the workshop findings. We will discuss the needs discovered from the workshop and we look for community feedback about how NASA can best address community concerns and work with other organizations that collect airborne data.

Sara Lubkin↗

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↗

Development of a Consistent MODIS and VIIRS Cloud Detection Approach for CERES

A consistent cloud fraction record across various satellite platforms is essential for maintaining a long-term and stable climate data record of Earth's energy budget. With the Aqua satellite nearing the end of its operational lifetime, the continuation of this record relies on utilizing VIIRS observations from NOAA20 for cloud detection in NASA’s Clouds and Earth’s Radiant Energy System (CERES) project. However, integrating data from VIIRS and MODIS instruments poses challenges due to their distinct characteristics, such as varying spatial resolutions and different spectral channels. As a result, deriving consistent cloud properties from these two sensors without introducing artificial discontinuities in the time series remains a complex and challenging task. This paper will present progress toward developing a unified MODIS and VIIRS cloud mask using common channels to produce consistent cloud properties for CERES next edition (Ed5) Earth radiation budget data products. The fundamental approach taken in the CERES cloud mask is to compare the observed radiances to the expected background clear sky radiances. Therefore, one vital step is to compute clear sky radiances with a radiative transfer model that accurately accounts for satellite-specific, spectrally dependent surface reflectance, surface emission, and atmospheric absorption. Refined radiative transfer models and updated ancillary data inputs including surface emissivity maps, IGBP, snow and ice maps are incorporated into the processing framework to improve cloud detection consistency and accuracy. Pixel level cloud mask results and monthly global cloud fraction comparisons between MODIS and VIIRS will be presented to evaluate their consistency. Remaining challenges will be discussed. It is expected that this work will contribute consistent cloud properties for CERES that adequately bridges the MODIS and VIIRS imager data records.

CERES↗

Optical data processing for aerospace applications

Optical data processing has a significant potential in future aerospace systems. In this paper, potential system applications are identified. One of the more important applications is the determination of errors of large antennas or reflector surfaces and the active control or compensation of the surface. Technological challenges to the application of optical data processing technology to aerospace systems are identified, and current NASA research efforts are discussed.

Stermer, R. L.↗

Creating an Interface to view Multi-Spacecraft Swarm Telemetry

Distributed Spacecraft Systems are a type of multi-spacecraft mission architecture that can not only provide improved resolution, coverage, and availability of existing missions, but also enable missions that would be previously infeasible using traditional approaches. Distributed Spacecraft Autonomy (DSA) is a project developed by the National Aeronautics and Space Administration that enables distributed spacecraft systems. In previous science swarm missions, the spacecraft involved have not been able to communicate with each other without utilizing a ground station. Now that the spacecraft can perform inter-satellite communication, the spacecraft can be treated as a collective. Swarm autonomy is critical for a growing number of satellites which means novel ways of displaying swarm data needs to be implemented. Such systems introduce unique challenges to traditional approaches for command and control of these spacecraft, due to the large number of spacecraft and the complexity of the interactions between them. The ground data system for DSA addresses these challenges through the creation of a custom user interface that allows a single operator to orchestrate a multi-spacecraft swarm in a scalable way. This plenary describes the details of the autonomy demonstration being performed, the requirements of those using the interface to analyze the spacecraft telemetry to assess demonstration success, and the approach taken by the ground systems team to create an interface that satisfies these requirements. This approach involves the creation of several distinct components that correspond to the level of detail presented to the user. These components are based on conventional user roles in human-robot interaction, including supervisor, operator, and mechanic, extended to accommodate the additional overhead of coordinating actions between agents. One main feature of the interface is the listenability matrix component which will represent inter-satellite communications in a heat mapped matrix. The above work described will enable users to command and interact with the spacecraft as a collective.

human-swarm interaction↗

Planning/scheduling techniques for VQ-based image compression

The enormous size of the data holding and the complexity of the information system resulting from the EOS system pose several challenges to computer scientists, one of which is data archival and dissemination. More than ninety percent of the data holdings of NASA is in the form of images which will be accessed by users across the computer networks. Accessing the image data in its full resolution creates data traffic problems. Image browsing using a lossy compression reduces this data traffic, as well as storage by factor of 30-40. Of the several image compression techniques, VQ is most appropriate for this application since the decompression of the VQ compressed images is a table lookup process which makes minimal additional demands on the user's computational resources. Lossy compression of image data needs expert level knowledge in general and is not straightforward to use. This is especially true in the case of VQ. It involves the selection of appropriate codebooks for a given data set and vector dimensions for each compression ratio, etc. A planning and scheduling system is described for using the VQ compression technique in the data access and ingest of raw satellite data.

Short, Nicholas M., Jr.↗

Heat Transfer Measurements of NASA Liquid Kerosene/Oxygen Rotating Detonation Rocket Engine

The RDRE has been identified as a viable high performance propulsion system with numerous advantages over the state-of-the-art (SOA) liquid rocket engine. NASA has been investigating this combustion device for applications ranging from lander, upper stage, thruster, and hypersonics. All of the activities funded to date have been focused on closing major technology gaps preventing the RDRE from being used more broadly by industry. One of those gaps include the prediction and management of heat transfer to the walls from the extreme combustion environment. This work overviews the heat transfer measurements made using new and existing hardware. A liquid oxygen / liquid RP-1 RDRE was tested utilizing a calorimeter outer body and outer body nozzle extension. An actively cooled inner body with axial running cooling channels was also used. A bimetallic GRCop-42 / Monel K500 injector was developed and demonstrated to be a viable technology for RDRE environments. Trends in bulk heat loads are discussed along with a direct comparison to constant pressure theory predictions of wall heat transfer. The experimental data obtained in this investigation showed similar heat fluxes to constant pressure theory indicating deflagration may have dominated the flow field. Only a single detonation wave was observed in all tests which imparted a significant dynamic load (vibration) on the test article making measurement of combustor performances extremely challenging. Both accelerometer and load cell data corroborate the extreme G-forces measured. The single wave mode yielded relatively low performances compared with other hot fire test data sets available. This leads to the conclusion that a single detonation wave in this geometry is not sufficient for high performance. Wave multiplicity, or rather, a specific number of waves may yield higher performances.

Thomas Teasley↗

High Data Rate Architecture (HiDRA)

One of the greatest challenges in developing new space technology is in navigating the transition from ground based laboratory demonstration at Technology Readiness Level 6 (TRL-6) to conducting a prototype demonstration in space (TRL-7). This challenge is com- pounded by the relatively low availability of new spacecraft missions when compared with aeronautical craft to bridge this gap, leading to the general adoption of a low-risk stance by mission management to accept new, unproven technologies into the system. Also in consideration of risk, the limited selection and availability of proven space-grade components imparts a severe limitation on achieving high performance systems by current terrestrial technology standards. Finally from a space communications point of view the long duration characteristic of most missions imparts a major constraint on the entire space and ground network architecture, since any new technologies introduced into the system would have to be compliant with the duration of the currently deployed operational technologies, and in some cases may be limited by surrounding legacy capabilities. Beyond ensuring that the new technology is verified to function correctly and validated to meet the needs of the end users the formidable challenge then grows to additionally include: carefully timing the maturity path of the new technology to coincide with a feasible and accepting future mission so it flies before its relevancy has passed, utilizing a limited catalog of available components to their maximum potential to create meaningful and unprecedented new capabilities, designing and ensuring interoperability with aging space and ground infrastructures while simultaneously providing a growth path to the future. The International Space Station (ISS) is approaching 20 years of age. To keep the ISS relevant, technology upgrades are continuously taking place. Regarding communications, the state-of-the-art communication system upgrades underway include high-rate laser terminals. These must interface with the existing, aging data infrastructure. The High Data Rate Architecture (HiDRA) project is designed to provide networked store, carry, and forward capability to optimize data flow through both the existing radio frequency (RF) and new laser communications terminal. The networking capability is realized through the Delay Tolerant Networking (DTN) protocol, and is used for scheduling data movement as well as optimizing the performance of existing RF channels. HiDRA is realized as a distributed FPGA memory and interface controller that is itself controlled by a local computer running DTN software. Thus HiDRA is applicable to other arenas seeking to employ next-generation communications technologies, e.g. deep space. In this paper, we describe HiDRA and its far-reaching research implications.

DTN↗

Ejection time by ear densitogram and its derivative - Clinical and physiologic applications.

Ear densitographic ejection times (EDET) and first derivative ear densitogram ejection times (dEDET) were studied to determine whether their reliability and validity justify their substitution for ejection times derived from the far less stable carotid pulse tracing. Inter- and intra-subject comparisons were made on thirty individuals under a wide variety of disease and challenge states. Statistical analysis of the data - which had been obtained through a blinded procedure - showed an overall correlation (r) of .98 for carotid vs EDET and .99 for carotid vs dEDET. The t-test demonstrated no significant differences among ejection times derived from the three methods. Moreover, the close tracking at rest and during challenges of ejection times derived from these curves with those from the carotid indicate that either method may be substituted for standard carotid curves without sacrificing reliability or validity of the measure.

Quarry-Pigott, V.↗

Development of three-way ranging for the Voyager Neptune encounter

Range data will be used to help navigate Voyager 2 to Neptune and the most distant planetary encounter ever attempted. In preparation for this challenging August 1989 planetary encounter, a new data type, known as 'three-way range', has been developed. With three-way ranging, a ranging signal generated at a ground station, received at the spacecraft and transponded to Earth is then received coherently at a second tracking station, which can be distant from the transmitting station. This paper contains analytic and operational descriptions of three-way range. Hardware modifications and design necessary for implementing this new data type are discussed. Preliminary assessments of three-way ranging performance are given and accuracies are discussed.

Roth, D. C.↗

The role of the World Data Centers in handling ocean climate data

The World Data Center System, set up for the International Geophysical Year in 1957, is an international network of data centers that links data contributors to data users in the geosciences. It includes means for the synthesis, analysis, and preparation of data products. It was set up in response to the needs of the international scientific community, and is still overseen by non-governmental scientific organizations. Because it is freely available to researchers in all countries, the World Data Center System has a special role to play in support of ocean climate research and monitoring programs. The World Data Centers face a number of challenges today. Apathy is probably the greatest, since many scientists take the system for granted. There is need to improve access and exploit new technology. The system must establish new links to assure continuity in a world with political changes. The multidisciplinary needs of global change research will demand capabilities for data and information management that go beyond the traditional emphasis on geophysics.

Webster, Ferris↗