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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3

The detection of interstellar methylcyanoacetylene

A new interstellar molecule, methylcyanoacetylene (CH3C3N), has been detected in the molecular cloud TMC-1. The J = 8 to 7, J = 7 to 6, J = 6 to 5, and J = 5 to 4 transitions have been observed. For the first three of these, both the K = 0 and K = 1 components are present, while for J = 5 to 4, only the K = 0 line has been detected. The observed frequencies were calculated by assuming a value of radial velocity V(LSR) = 5.8 km/s for TMC-1, typical of other molecules in the cloud. All observed frequencies are within 10 kHz of the calculated frequencies, which are based on the 1982 laboratory constants of Moises et al. (1982), so the identification is secure. The lines are broadened by hyperfine splitting, and the J = 5 to 4, K = 0 transition shows incipient resolution into three hyperfine components. The rotational temperature determined from these observations is quite low, with T(rot) in the range from 2.7 to 4 K. The total column density is approximately 5 x 10 to the 12th per sq cm.

Broten, N. W.↗

Names Don't Fly: Smart Filters for Profanity Detection and Classification in User-Generated Content

Generally, names associate with a person’s identity. But what if in the pretext of a legitimate name and given the opportunity, users of software provide names to online web forms that carry along offensive language, slurs, and other profanity that is then sent to Mars ? The answer is simple: they don’t fly. In this paper,we perform model explorations to detect and classify inappropriate content in the names submitted from people across the world to ‘Send Your Names to MARS’ public engagement campaign.We propose a novel pipeline approach, that can effectively overcome the issues of lack of negative samples, noisy labels by gathering expert knowledge over time with human(s) in the loop and data augmentation, and achieve high accuracy in classifying inappropriate names with very little or no context. We describe cloud-based infrastructure to deploy our application and run predictions on large-scale data through our pipeline and achieve significant speedup over offline processes, with enhanced reliability and security.

Soderstrom, Tomas↗

Meteorological conditions during the formation of ice on aircraft

These are the results of a number of records recently secured from autographic meteorological instruments mounted on airplanes at times when ice formed. Ice is found to collect on an airplane only when the airplane is in some form of visible moisture, such as cloud, fog, mist, rain. etc., and the air temperature is within certain critical limits. Described here are the characteristics of clear ice and rime ice and the specific types of hazards they present to airplanes and lighter than air vehicles. The weather records are classified according to the two general types of formation (clear ice and rime) together with the respective temperatures, relative humidities, clouds, and elevations above ground at which formations occurred. This classification includes 108 cases where rime formed, 43 cases in which clear ice formed, and 4 cases when both rime and clear ice formed during the same flight. It is evident from the above figures that there was a preponderance of rime by the ratio of 2.5 to 1, while in only a few cases both types of ice formation occurred during the same flight.

Samuels, L T↗

DRF: A Software Architecture for a Data Marketplace to Support Advanced Air Mobility

Advanced Air Mobility is a new aviation vision, where unmanned aerial systems will trans- port passengers and cargo across urban and rural areas. Critical to the realization of this vision is the development of a digital marketplace, which allows service providers and consumers operating in the airspace ecosystem to securely exchange data and reasoning insights. In this paper, we present the architecture of a decentralized data marketplace that connects data and reasoning service providers to vehicles and other service consumers along the cloud-to-edge continuum. We also present two example use cases to demonstrate the value of our approach.

Autonomy↗

The AgMIP GRIDded Crop Modeling Initiative (AgGRID) and the Global Gridded Crop Model Intercomparison (GGCMI)

Climate change is a significant risk for agricultural production. Even under optimistic scenarios for climate mitigation action, present-day agricultural areas are likely to face significant increases in temperatures in the coming decades, in addition to changes in precipitation, cloud cover, and the frequency and duration of extreme heat, drought, and flood events (IPCC, 2013). These factors will affect the agricultural system at the global scale by impacting cultivation regimes, prices, trade, and food security (Nelson et al., 2014a). Global-scale evaluation of crop productivity is a major challenge for climate impact and adaptation assessment. Rigorous global assessments that are able to inform planning and policy will benefit from consistent use of models, input data, and assumptions across regions and time that use mutually agreed protocols designed by the modeling community. To ensure this consistency, large-scale assessments are typically performed on uniform spatial grids, with spatial resolution of typically 10 to 50 km, over specified time-periods. Many distinct crop models and model types have been applied on the global scale to assess productivity and climate impacts, often with very different results (Rosenzweig et al., 2014). These models are based to a large extent on field-scale crop process or ecosystems models and they typically require resolved data on weather, environmental, and farm management conditions that are lacking in many regions (Bondeau et al., 2007; Drewniak et al., 2013; Elliott et al., 2014b; Gueneau et al., 2012; Jones et al., 2003; Liu et al., 2007; M¨uller and Robertson, 2014; Van den Hoof et al., 2011;Waha et al., 2012; Xiong et al., 2014). Due to data limitations, the requirements of consistency, and the computational and practical limitations of running models on a large scale, a variety of simplifying assumptions must generally be made regarding prevailing management strategies on the grid scale in both the baseline and future periods. Implementation differences in these and other modeling choices contribute to significant variation among global-scale crop model assessments in addition to differences in crop model implementations that also cause large differences in site-specific crop modeling (Asseng et al., 2013; Bassu et al., 2014).

climate↗

Hyperspectral Detail Meets Radiometric Accuracy: A Foundational Reflected Solar Capability for the Coming Decade

Hyperspectral Earth-reflected solar measurements contain rich, detailed information about clouds, aerosols, and the atmosphere. This information compounds when paired with high, SI-traceable radiometric accuracy. Unlike spectral resolution, which can be resampled to coarser spectral resolutions, radiometric accuracy cannot be recovered once a measurement is made, making the choice to invest in this capability now a decision with lasting consequences for the climate record. CLARREO Pathfinder is demonstrating that this combination of hyperspectral sampling and benchmark-quality accuracy is achievable today, but no follow-on mission is currently planned within NASA's Earth Science Division portfolio, and the recent cancellation of the European Space Agency TRUTHS mission has heightened the urgency of sustaining this capability. We recommend prioritizing investment in a follow-on to CLARREO Pathfinder, along with dedicated support for the science community to fully exploit these measurements. This capability would reduce long-standing uncertainties in cloud feedback, aerosol forcing, and global energy imbalance, while providing a degradation-resistant, gap-resilient calibration foundation for the broader Earth observing system. Building on flight-proven technology and an engaged science community, this is a near-term, fiscally realistic opportunity to secure a foundational Earth observation capability for the coming decade.

satellite↗

Abundances of interstellar atoms from ultaviolet absorption lines

The equivalent widths of interstellar absorption lines of Mg II, P II, Cl I and II, Mn II, Fe II, Cu II, and Ni II, obtained in a Copernicus survey of Bohlin et al (1983) have been analyzed to yield column densities along the lines of sight. The measured depletions are clearly correlated with n sub H, the mean hydrogen column density along the line of sight. Depletions also seem to be weakly correlated with various ratios of hydrogen to extinction by dust grains and also variations of extinction with wavelength, although part of these effects are a secondary result of the correlation with n sub H. The apparent coupling of depletion to the mean density are interpreted in terms of an idealized model due to Spitzer (1985), where each element has one value of depletion in the low-density, warm, neutral gas and an enhanced, different value in cold clouds. The difference of apparent depletions for Mg, P, Cl, Mn, and Fe between warm and cold clouds averages 0.44 + or - 0.12 (rms) dex, and, after an allowance for observational errors is made, the scatter of individual depletions from the overall trend predicted by method is only about 0.10 dex. The identification of the observed apparent depletions with actual ones, while very likely, is not entirely secure, because of the possible presence of highly saturated compoents with very narrow profiles and the possible contamination of the results by H II regions.

Jenkins, E. B.↗

The influence of man in space observations

The paper evaluates the Skylab missions from the viewpoint of to what extent the presence of men may have been a detriment to scientific observations, either through their movements or through contamination of the spacecraft and instruments. The stability of the instrument canister within the Apollo Telescope Mount was secured by the Experiment Pointing Control System. Angular stability was specified to be within plus or minus 2.5 arc seconds, and was found to be less than 2 arc seconds during normal crew activity. No astronomical observations were reported as being degraded by crew movements. Instrumentation was installed to measure rates of contaminant particle deposition on optical surfaces. Clouds were formed from particles originating in outgassing from vehicle surface materials and from vent apertures. The Coronograph Contamination Measurement Instrument was used to measure the brightness of the induced cloud surrounding Skylab. Preliminary analysis shows no significant degradation of photographic data attributable to contamination.

Hanes, T. E.↗

Abundant Ammonia and Nitrogen-Rich Soluble Organic Matter in Samples From Asteroid (101955) Bennu

Organic matter in meteorites reveals clues about early Solar System chemistry and the origin of molecules important to life, but terrestrial exposure complicates interpretation. Samples returned from the B-type asteroid Bennu by the Origins, Spectral Interpretation, Resource Identifcation, and Security–Regolith Explorer mission enabled us to study pristine carbonaceous astromaterial without uncontrolled exposure to Earth’s biosphere. Here we show that Bennu samples are volatile rich, with more carbon, nitrogen and ammonia than samples from asteroid Ryugu and most meteorites. Nitrogen-15 isotopic enrichments indicate that ammonia and other N-containing soluble molecules formed in a cold molecular cloud or the outer protoplanetary disk. We detected amino acids (including 14 of the 20 used in terrestrial biology), amines, formaldehyde, carboxylic acids, polycyclic aromatic hydrocarbons and N-heterocycles (including all fve nucleobases found in DNA and RNA), along with ~10,000 N-bearing chemical species. All chiral non-protein amino acids were racemic or nearly so, implying that terrestrial life’s left-handed chirality may not be due to bias in prebiotic molecules delivered by impacts. The relative abundances of amino acids and other soluble organics suggest formation and alteration by low-temperature reactions, possibly in NH3-rich fuids. Bennu’s parent asteroid developed in or accreted ices from a reservoir in the outer Solar System where ammonia ice was stable.

Daniel P Glavin↗

Coordinated Analysis of Isotopically Anomalous Nanoglobules and Insoluble Organic Matter in Quick-Look Samples From Asteroid Bennu

Spectral characterization of B-type asteroid Bennu by the Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) spacecraft indicated abundant organic matter with similarities to insoluble organic matter (IOM) in meteorites. IOM in chondritic samples occurs in multiple forms, including a fluffy morphology and submicron-sized rounded nanoglobules. Isotopic anomalies in H, C, and N have been observed in both morphologies and are postulated to result from low-temperature chemical reactions in the molecular cloud or outer protoplanetary disk [e.g., 2,3]. We tested the hypothesis that Bennu also contains such isotopically anomalous organic matter by conducting coordinated in situ analysis of “quick-look” samples collected from the avionics deck of the OSIRIS-REx sample canister. This study expands our understanding of the fundamental nature of Bennu and its pre-accretionary environment by investigating the morphologies and isotopic distribution of presolar organic matter in Bennu.

A N Nguyen↗

Controlling Infrastructure Costs: Right-Sizing the Mission Control Facility

Johnson Space Center's Mission Control Center is a space vehicle, space program agnostic facility. The current operational design is essentially identical to the original facility architecture that was developed and deployed in the mid-90's. In an effort to streamline the support costs of the mission critical facility, the Mission Operations Division (MOD) of Johnson Space Center (JSC) has sponsored an exploratory project to evaluate and inject current state-of-the-practice Information Technology (IT) tools, processes and technology into legacy operations. The general push in the IT industry has been trending towards a data-centric computer infrastructure for the past several years. Organizations facing challenges with facility operations costs are turning to creative solutions combining hardware consolidation, virtualization and remote access to meet and exceed performance, security, and availability requirements. The Operations Technology Facility (OTF) organization at the Johnson Space Center has been chartered to build and evaluate a parallel Mission Control infrastructure, replacing the existing, thick-client distributed computing model and network architecture with a data center model utilizing virtualization to provide the MCC Infrastructure as a Service. The OTF will design a replacement architecture for the Mission Control Facility, leveraging hardware consolidation through the use of blade servers, increasing utilization rates for compute platforms through virtualization while expanding connectivity options through the deployment of secure remote access. The architecture demonstrates the maturity of the technologies generally available in industry today and the ability to successfully abstract the tightly coupled relationship between thick-client software and legacy hardware into a hardware agnostic "Infrastructure as a Service" capability that can scale to meet future requirements of new space programs and spacecraft. This paper discusses the benefits and difficulties that a migration to cloud-based computing philosophies has uncovered when compared to the legacy Mission Control Center architecture. The team consists of system and software engineers with extensive experience with the MCC infrastructure and software currently used to support the International Space Station (ISS) and Space Shuttle program (SSP).

Martin, Keith↗

NASA's Photon-Counting SLR2000 Satellite Laser Ranging System: Progress and Applications

NASA's new unmanned SLR2000 system is designed to track, with millimeter precision and using single photon returns, a constellation of roughly 24 retroreflector-equipped satellites, which range in altitude from about 300 km to 20,000 km. Totally autonomous operation and a common engineering configuration are expected to greatly reduce station operations costs relative to NASA's current manned systems. The system has also been designed with a goal of significantly lowering replication costs. All of the prototype components and subsystems have been completed and tested and have substantially met the original specifications. The prototype system is presently undergoing final integration and testing in a dedicated shelter with an azimuth tracking dome synchronized to the optical tracking mount. The facility also features a number of security features such as security cameras and sensors designed to detect power or thermal control problems or entry by unauthorized personnel. Field tests are in progress. The present paper provides an overview of the various subsystems and test results to date. The meteorological subsystem, which has operated successfully in the field for almost three years, consists of several sensors which measure: (1) pressure, temperature, and relative humidity; (2) wind speed and direction; (3) ground visibility and precipitation; and (4) local cloud cover as a function of station azimuth and elevation (day and night). A "pseudo-operator" software program interprets the sensor readings and modifies satellite tracking priorities based on local meteorological conditions.

Degnan, John J.↗

The XMM-Newton Survey of the Small Magellanic Cloud

Context. Although numerous archival XMM-Newton observations existed towards the Small Magellanic Cloud (SMC) before 2009, only a fraction of the whole galaxy had been covered. Aims. Between May 2009 and March 2010, we carried out an XMM-Newton survey of the SMC, to ensure a complete coverage of both its bar and wing. Thirty-three observations of 30 different fields with a total exposure of about one Ms filled the previously missing parts. Methods. We systematically processed all available SMC data from the European Photon Imaging Camera. After rejecting observations with very high background, we included 53 archival and the 33 survey observations. We produced images in five different energy bands. We applied astrometric boresight corrections using secure identifications of X-ray sources and combined all the images to produce a mosaic covering the main body of the SMC. Results. We present an overview of the XMM-Newton observations, describe their analysis, and summarize our first results, which will be presented in detail in follow-up papers. Here, we mainly focus on extended X-ray sources, such as supernova remnants (SNRs) and clusters of galaxies, that are seen in our X-ray images. Conclusions. Our XMM-Newton survey represents the deepest complete survey of the SMC in the 0.15−12.0 keV X-ray band. We propose three new SNRs that have low surface brightnesses of a few 10−14 erg cm−2 s−1 arcmin−2 and large extents. In addition, several known remnants appear larger than previously measured at either X-rays or other wavelengths extending the size distribution of SMC SNRs to larger values.

global↗

The Mars 2020 Ground Data System Architecture

The Mars 2020 Mission’s primary objective is to collect 20 geographically unique samples during its prime mission of one and a quarter Martian years, or just over 2 Earth years. Mission planners determined the project needed to develop a system that would enable the operations team to analyze engineering and science data, make science decisions, select viable rover targets at a millimeter resolution and validate an uplink bundle for a car sized rover with more complex science instruments than any previous Mars surface mission. All this had to be done within a five hour time frame. Doing this with a small team would be a challenge, but this had to be accomplished by a large team of engineers and scientists located across North America and Europe. Achieving this level of operational efficiency was unheard of in the prime mission. In addition, the mission had another set of requirements that had nothing to do with surface operations; the Mars 2020 Ground Data System (GDS) was also expected to comply with a new set of security requirements to keep up with the ever changing cybersecurity landscape. The Mars 2020 Ground Data System (GDS) is a re-architected version of the Mars Science Laboratory GDS. The primary goal was to integrate the lessons learned from previous Mars surface missions, accommodate a set of new requirements and capabilities required to ensure mission success, and comply with a new set of cybersecurity controls. The new architecture includes several unique qualities including a data lake, language-agnostic system-wide event-based operations, containerization, automated deployment, network segmentation, infrastructure-as-code, API-driven interfaces, and the first Mars surface GDS to operate primarily in the cloud. The new architecture enabled greater access to the system’s data, tighter integration with the operations team, and a higher level of traceability. The availability of the data also enabled a new set of capabilities previously not possible on surface missions. These new capabilities include an autonomous data to information, pipeline for downlink analysis, horizontal scaling of science data processing capabilities, autonomous round trip data tracking of science and engineering data, integration of flight system state into the tactical planning cycle, high fidelity targeting utilizing kinematic data, and hierarchical image and 3d meshes data representations. This paper will introduce the requirements for the Mars 2020 Mission, the heritage architecture, and the rationale for the changes to achieve the new architecture. The paper will continue to describe the fundamental changes made to the GDS architecture, how these changes enabled a more tightly integrated GDS, and the new capabilities that were enabled by the new architecture. The paper will conclude with the lessons learned from the process of rearchitecting a heritage GDS system and from the first 200 days of operations supporting over 800 users from around the world.

Lopez-Roig, Reynaldo↗

Nominal 30-M Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine

A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must for food and water security analysis. Precise and accurate global cropland extent maps, indicating cropland and non-cropland areas, is a starting point to develop high-level products such as crop watering methods (irrigated or rainfed), cropping intensities (e.g., single, double, or continuous cropping), crop types, cropland fallows, as well as assessment of cropland productivity (productivity per unit of land), and crop water productivity (productivity per unit of water). Uncertainties associated with the cropland extent map have cascading effects on all higher-level cropland products. However, precise and accurate cropland extent maps at high spatial resolution over large areas (e.g., continents or the globe) are challenging to produce due to the small-holder dominant agricultural systems like those found in most of Africa and Asia. Cloud-based Geospatial computing platforms and multi-date, multi-sensor satellite image inventories on Google Earth Engine offer opportunities for mapping croplands with precision and accuracy over large areas that satisfy the requirements of broad range of applications. Such maps are expected to provide highly significant improvements compared to existing products, which tend to be coarser in resolution, and often fail to capture fragmented small-holder farms especially in regions with high dynamic change within and across years. To overcome these limitations, in this research we present an approach for cropland extent mapping at high spatial resolution (30-m or better) using the 10-day, 10 to 20-m, Sentinel-2 data in combination with 16-day, 30-m, Landsat-8 data on Google Earth Engine (GEE). First, nominal 30-m resolution satellite imagery composites were created from 36,924 scenes of Sentinel-2 and Landsat-8 images for the entire African continent in 2015-2016. These composites were generated using a median-mosaic of five bands (blue, green, red, near-infrared, NDVI) during each of the two periods (period 1: January-June 2016 and period 2: July-December 2015) plus a 30-m slope layer derived from the Shuttle Radar Topographic Mission (SRTM) elevation dataset. Second, we selected Cropland/Non-cropland training samples (sample size 9791) from various sources in GEE to create pixel-based classifications. As supervised classification algorithm, Random Forest (RF) was used as the primary classifier because of its efficiency, and when over-fitting issues of RF happened due to the noise of input training data, Support Vector Machine (SVM) was applied to compensate for such defects in specific areas. Third, the Recursive Hierarchical Segmentation (RHSeg) algorithm was employed to generate an object-oriented segmentation layer based on spectral and spatial properties from the same input data. This layer was merged with the pixel-based classification to improve segmentation accuracy. Accuracies of the merged 30-m crop extent product were computed using an error matrix approach in which 1754 independent validation samples were used. In addition, a comparison was performed with other available cropland maps as well as with LULC maps to show spatial similarity. Finally, the cropland area results derived from the map were compared with UN FAO statistics. The independent accuracy assessment showed a weighted overall accuracy of 94, with a producers accuracy of 85.9 (or omission error of 14.1), and users accuracy of 68.5 (commission error of 31.5) for the cropland class. The total net cropland area (TNCA) of Africa was estimated as 313 Mha for the nominal year 2015.

Cropland mapping; cropland areas; 30-m; Landsat-8;↗

Near Real-Time Flood Monitoring and Impact Assessment Systems

Floods are the costliest natural disaster, causing approximately 6.8 million deaths in the twentieth century alone. Worldwide economic flood damage estimates in 2012 exceed $19 Billion USD. Extended duration floods also pose longer term threats to food security, water, sanitation, hygiene, and community livelihoods, particularly in developing countries. Projections by the Intergovernmental Panel on Climate Change (IPCC) suggest that precipitation extremes, rainfall intensity, storm intensity, and variability are increasing due to climate change. Increasing hydrologic uncertainty will likely lead to unprecedented extreme flood events. As such, there is a vital need to enhance and further develop traditional techniques used to rapidly assess flooding and extend analytical methods to estimate impacted population and infrastructure. Measuring flood extent in situ is generally impractical, time consuming, and can be inaccurate. Remotely sensed imagery acquired from space-borne and airborne sensors provides a viable platform for consistent and rapid wall-to-wall monitoring of large flood events through time. Terabytes of freely available satellite imagery are made available online each day by NASA, ESA, and other international space research institutions. Advances in cloud computing and data storage technologies allow researchers to leverage these satellite data and apply analytical methods at scale. Repeat-survey earth observations help provide insight about how natural phenomena change through time, including the progression and recession of floodwaters. In recent years, cloud-penetrating radar remote sensing techniques (e.g., Synthetic Aperture Radar) and high temporal resolution imagery platforms (e.g., MODIS and its 1-day return period), along with high performance computing infrastructure, have enabled significant advances in software systems that provide flood warning, assessments, and hazard reduction potential. By incorporating social and economic data, researchers can develop systems that automatically quantify the socioeconomic impacts resulting from flood disaster events.

Ahamed, Aakash↗

Physical Processes Governing Atmospheric Trace Constituents Measured from an Aircraft on PEM-Tropics

Before the mission, the PI (principal investigator) was instrumental in securing real-time use of the new 51-level ECMWF (European Centre for Medium Range Weather Forecasts) meteorological data. During the mission, he provided flight planning and execution guidance as meteorologist for the P-3B. Mr. Yong Zhu computed and plotted meteorological forecast maps using the ECMWF data and transmitted them to the field from MIT (Massachusetts Institute of Technology). Dr. John Cho was in the field for the Christmas Island portion to extract data from the on-site NOAA (National Oceanic and Atmospheric Administration) radars for local wind profiles that were used at the flight planning meetings. When the power supply for the VHF radar failed, he assisted the NOAA engineer in its repair. After the mission, Mr. Zhu produced meteorological data memos, which were made available to the PEM (Pacific Exploratory Mission)-Tropics B science team on request. An undergraduate student, Ms. Danielle Morse, wrote memos annotating the cloud conditions seen on the aircraft external monitor video tapes. Dr. Cho and the PI circulated a memo regarding the status (and associated problems) of the meteorological measurement systems on the DC-8 and P-3B to the relevant people on the science team. Several papers by members of our project were completed and accepted by JGR (Journal of Geophysical Research) for the first special section on PEM-Tropics B. These papers included coverage of the following topics: 1) examination of boundary layer data; 2) water vapor transport; 3) tropospheric trace constituent layers; 4) summarizations of the meteorological background and events during PEM-Tropics B; 5) concomitant lidar measurements of ozone, water vapor, and aerosol.

Newell, Reginald E.↗

HEASARC - The High Energy Astrophysics Science Archive Research Center

The High Energy Astrophysics Science Archive Research Center (HEASARC) is NASA's archive for high-energy astrophysics and cosmic microwave background (CMB) data, supporting the broad science goals of NASA's Physics of the Cosmos theme. It provides vital scientific infrastructure to the community by standardizing science data formats and analysis programs, providing open access to NASA resources, and implementing powerful archive interfaces. Over the next five years the HEASARC will ingest observations from up to 12 operating missions, while serving data from these and over 30 archival missions to the community. The HEASARC archive presently contains over 37 TB of data, and will contain over 60 TB by the end of 2014. The HEASARC continues to secure major cost savings for NASA missions, providing a reusable mission-independent framework for reducing, analyzing, and archiving data. This approach was recognized in the NRC Portals to the Universe report (2007) as one of the HEASARC's great strengths. This poster describes the past and current activities of the HEASARC and our anticipated developments in coming years. These include preparations to support upcoming high energy missions (NuSTAR, Astro-H, GEMS) and ground-based and sub-orbital CMB experiments, as well as continued support of missions currently operating (Chandra, Fermi, RXTE, Suzaku, Swift, XMM-Newton and INTEGRAL). In 2012 the HEASARC (which now includes LAMBDA) will support the final nine-year WMAP data release. The HEASARC is also upgrading its archive querying and retrieval software with the new Xamin system in early release - and building on opportunities afforded by the growth of the Virtual Observatory and recent developments in virtual environments and cloud computing.

Smale, Alan P.↗