SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Development plan for design, development, and production of solid state Mars probe radar altimeter
The collocation of a National Weather Service (NWS) Forecast Office with atmospheric scientists from NASA/Marshall Space Flight Center (MSFC) in Huntsville, Alabama has afforded a unique opportunity for science sharing and technology transfer. Specifically, the NWS office in Huntsville has interacted closely with research scientists within the SPORT (Short-term Prediction and Research and Transition) Center at MSFC. One significant technology transfer that has reaped dividends is the transition of unique NASA EOS polar orbiting datasets into NWS field operations. NWS forecasters primarily rely on the AWIPS (Advanced Weather Information and Processing System) decision support system for their day to day forecast and warning decision making. Unfortunately, the transition of data from operational polar orbiters or low inclination orbiting satellites into AWIPS has been relatively slow due to a variety of reasons. The ability to integrate these high resolution NASA datasets into operations has yielded several benefits. The MODIS (MODerate-resolution Imaging Spectrometer ) instrument flying on the Aqua and Terra satellites provides a broad spectrum of multispectral observations at resolutions as fine as 250m. Forecasters routinely utilize these datasets to locate fine lines, boundaries, smoke plumes, locations of fog or haze fields, and other mesoscale features. In addition, these important datasets have been transitioned to other WFOs for a variety of local uses. For instance, WFO Great Falls Montana utilizes the MODIS snow cover product for hydrologic planning purposes while several coastal offices utilize the output from the MODIS and AMSR-E instruments to supplement observations in the data sparse regions of the Gulf of Mexico and western Atlantic. In the short term, these datasets have benefited local WFOs in a variety of ways. In the longer term, the process by which these unique datasets were successfully transitioned to operations will benefit the planning and implementation of products and datasets derived from both NPP and NPOESS. This presentation will provide a brief overview of current WFO usage of satellite data, the transition of datasets between SPORT and the N W S , and lessons learned for future transition efforts.
The 67 Management Plans represent recommended study approaches for resolving 108 of the 305 Issues which were identified. Each study Management Plan is prepared in three formats: Management Plan Overview (lists the subsumed Issues, study background, and related overview information); Study Plan (details the study approach by tasks, lists special needs, and describes expected study products); Schedule-Task Flow (provides a time-lined schedule for the study tasks and resource requirements). The Management Relationships Matrix, included in this volume, shows the data input-output relationships among all recommended studies. A listing is also included which cross-references the unresolved requirements to Issues to management plans. A glossary of all abbreviations utilized is provided.
As part of an ongoing effort to validate satellite remote sensing snow products for the recentlydeveloped U.S. Air Force Weather Agency (AFWA) - NASA blended snow product, Satellite and in-situ data for snow extent and snow water equivalent (SWE) are evaluated in Finland for the 2006-2007 snow season Finnish Meteorological Institute (FMI) daily weather station data and Finnish Environment Institute (SYKE) bi-monthly snow course data are used as ground truth. Initial comparison results display positive agreement between the AFWA NASA Snow Algorithm (ANSA) snow extent and SWE maps and in situ data, with discrepancies in accordance with known AMSR-E and MODIS snow mapping limitations. Future ANSA product improvement plans include additional validation and inclusion of fractional snow cover in the ANSA data product. Furthermore, the AMSR-E 19 GHz (horizontal channel) with the difference between ascending and descending satellite passes (Diurnal Amplitude Variations, DAV) will be used to detect the onset of melt, and QuikSCAT scatterometer data (14 GHz) will be used to map areas of actively melting snow.
This document (Volume I) provides an executive summary of the lessons learned from the Constellation Program. A companion Volume II provides more detailed analyses for those seeking further insight and information. In this volume, Section 1.0 introduces the approach in preparing and organizing the content to enable rapid assimilation of the lessons. Section 2.0 describes the contextual framework in which the Constellation Program was formulated and functioned that is necessary to understand most of the lessons. Context of a former program may seem irrelevant in the heady days of new program formulation. However, readers should take some time to understand the context. Many of the lessons would be different in a different context, so the reader should reflect on the similarities and differences in his or her current circumstances. Section 3.0 summarizes key findings developed from the significant lessons learned at the program level that appear in Section 4.0. Readers can use the key findings in Section 3.0 to peruse for particular topics, and will find more supporting detail and analyses in Section 4.0 in a topical format. Appendix A contains a white paper describing the Constellation Program formulation that may be of use to readers wanting more context or background information. The reader will no doubt recognize some very similar themes from previous lessons learned, blue-ribbon committee reviews, National Academy reviews, and advisory panel reviews for this and other large-scale human spaceflight programs; including Apollo, Space Shuttle, Shuttle/Mir, and the ISS. This could represent an inability to learn lessons from previous generations; however, it is more likely that similar challenges persist in the Agency structure and approach to program formulation, budget advocacy, and management. Perhaps the greatest value of these Constellation lessons learned can be found in viewing them in context with these previous efforts to guide and advise the Agency and its stakeholders.
Vehicles and systems in the field of aerospace have two major requirements: a high demand for a large quantity and an expectation to perform for their lifetime with little to no failures. Thus, there is a need for a fast production rate of aerospace products with high quality. Improvements to production rate have many benefits, including a reduction in energy consumption per unit manufactured. This would be from factory energy usage, which is required to build and verify a product. Manufacturing process specifications require inspection of parts to determine if any flaws are present. Depending on factory planning and product quality, especially at higher rates, the evaluation process can pose a production rate bottleneck. This project was comprised of using artificial intelligence and machine learning (AI/ML) methods on inspection evaluations with the objective of reducing the required time to produce an aerospace structure or product and without reducing the final quality.
This paper and exhibit describes the on-going research activities, plans and products of the Autonomy Technology program at NASA Jet Propulsion Laboratory. In this paper, we briefly describe the areas of Mission Planning and Execution, Distributed Autonomous Systems, Science Data Understanding, and Autonomous Guidance and Control.
Two issues regarding primary productivity, as it pertains to the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Program and the National Aeronautics and Space Administration (NASA) Mission to Planet Earth (MTPE) are presented in this volume. Chapter 1 describes the development of a science plan for deriving primary production for the world ocean using satellite measurements, by the Ocean Primary Productivity Working Group (OPPWG). Chapter 2 presents discussions by the same group, of algorithm classification, algorithm parameterization and data availability, algorithm testing and validation, and the benefits of a consensus primary productivity algorithm.
A dual spin stabilized TDR spacecraft design is presented for low data rate (LDR) and medium data rate (MDR) user spacecraft telecommunication relay service. The relay satellite provides command and data return channels for unmanned users together with duplex voice and data communication channels for manned user spacecraft. TDRS/ground links are in the Ku band. Command links are provided at UHF for LDR users and S band for MDR users. Voice communication channels are provided at UHF/VHF for LDR users and at S band for MDR users. The spacecraft is designed for launch on the Delta 2914 with system deployment planned for 1978. This volume contains a description of the overall TDR spacecraft configuration, a detailed description of the spacecraft subsystems, a reliability analysis, and a product effectiveness plan.
Hughes Aircrafts 13-year productivity study clearly identifies management as the key link in the entire productivity chain. This fact led to the establishment of a long-term series of seminars on personal, managerial, organizational, and operational productivity for all levels and sectors of line and staff management. To inspire the work force to higher levels of productivity and creativity management, itself, must first be inspired. In turn they have to clearly understand the productive and creative processes, fashion an effective productivity improvement plan with sound strategy and implementation, create an optimal environmental chemistry, and provide the outstanding leadership necessary to propel their organizations to achieve full potential. The primary goals of the seminars are to (1) ignite that spark of inspiration, enabling productive action to follow, (2) provide participants a credible roadmap and effective tools for implementation, and (3) develop a dedicated commitment to leadership and productivity throughout the management team.
There are two important aspects of the Moon and its materials which must be addressed in preparation for a manned return to the Moon and establishment of a lunar base. These involve its geologic science and resource utilization. Knowledge of the Moon forms the basis for interpretations of the planetary science of the terrestrial planets and their satellites; and there are numerous exciting explorations into the geologic science of the Moon to be conducted using orbiter and lander missions. In addition, the rocks and minerals and soils of the Moon will be the basic raw materials for a lunar outpost; and the In-Situ Resource Utilization (ISRU) of lunar materials must be considered in detail before any manned return to the Moon. Both of these fields -- planetary science and resource assessment -- will necessitate the collection of considerable amounts of new data, only obtainable from lunar-orbit remote sensing and robotic landers. For over fifteen years, there have been a considerable number of workshops, meetings, etc. with their subsequent 'white papers' which have detailed plans for a return to the Moon. The Lunar Observer mission, although grandiose, seems to have been too expensive for the austere budgets of the last several years. However, the tens of thousands of man-hours that have gone into 'brainstorming' and production of plans and reports have provided the precursor material for today's missions. It has been only since last year (1991) that realistic optimism for lunar orbiters and soft landers has come forth. Plans are for 1995 and 1996 'Early Robotic Missions' to the Moon, with the collection of data necessary for answering several of the major problems in lunar science, as well as for resource and site evaluation, in preparation for soft landers and a manned-presence on the Moon.
The purpose of preliminary examination of the Genesis sample collectors is to provide information on the condition and availability of collector materials to the science community as a basis for allocation requests. Similarly, the information will be used by the Genesis Sample Allocation sub-committee of CAPTEM to determine the optimum allocation scheme, and by the Genesis Curator to determine the processing sequence for allocation production. The plan includes a decision process and detailed examination and documentation protocol for whole arrays and individual collectors (wafers, concentrator targets, bulk metallic glass, gold foil, and polished aluminum). It also includes a plan for communicating the information obtained to the scientific community. The plan does not include a detailed plan for preliminary examination of the SRC lid foil collectors, the process for removal of individual collectors from their frames, or for the subsequent subdivision of collector materials for allocation.
The need for a more flexible and efficient data file management system for mission planning in the Mission Operations Laboratory (EO) at MSFC has spawned the development of Silvabase. Silvabase is a new data file structure based on a B+ tree data structure. This data organization allows for efficient forward and backward sequential reads, random searches, and appends to existing data. It also provides random insertions and deletions with reasonable efficiency, utilization of storage space well but not at the expense of speed, and performance of these functions on a large volume of data. Mission planners required that some data be keyed and manipulated in ways not found in a commercial product. Mission planning software is currently being converted to use Silvabase in the Spacelab and Space Station Mission Planning Systems. Silvabase runs on a Digital Equipment Corporation's popular VAX/VMS computers in VAX Fortran. Silvabase has unique features involving time histories and intervals such as in operations research. Because of its flexibility and unique capabilities, Silvabase could be used in almost any government or commercial application that requires efficient reads, searches, and appends in medium to large amounts of almost any kind of data.
The author has identified the following significant results. The wide variety of geological and geophysical phenomena which can be observed in Iceland, and particularly their very direct relation to the management of the country's natural resources, has provided great impetus to the use of ERTS-1 imagery to measure and map the dynamic natural phenomena in Iceland. MSS imagery is being used to study a large variety of geological and geophysical eruptive products, geologic structure, volcanic geomorphology, hydrologic, oceanographic, and agricultural phenomena of Iceland. Some of the preliminary results from this research projects are: (1) a large number of geological and volcanic features can be studied from ERTS-1 imagery, particularly imagery acquired at low sun angle, which had not previously been recognized; (2) under optimum conditions the ERTS-1 satellite can discern geothermal areas by their snow melt pattern or warm spring discharge into frozen lakes; (3) various maps at scales of 1:1 million and 1:500,000 can be updated and made more accurate with ERTS-1 imagery; (4) the correlation of water reserves with snowcover can improve the basis for planning electrical production in the management of water resources; (5) false-color composites (MSS) permitted the mapping of four types of vegetation: forested; grasslands, reclaimed, and cultivated areas, and the seasonal change of the vegetation, all of high value to rangeland management.
The STX mass storage system design is intended for environments requiring high speed access to large volumes of data (terabyte and greater). Prior to commitment to a product design plan, STX conducted an exhaustive study of the commercially available off-the-shelf hardware and software. STX also conducted research into the area of emerging technologies in networks and storage media so that the design could easily accommodate new interfaces and peripherals as they came on the market. All the selected system elements were brought together in a demo suite sponsored jointly by STX and ALLIANT where the system elements were evaluated based on actual operation using a client-server mirror image configuration. Testing was conducted to assess the various component overheads and results were compared against vendor data claims. The resultant system, while adequate to meet our capacity requirements, fell short of transfer speed expectations. A product team lead by STX was assembled and chartered with solving the bottleneck issues. Optimization efforts yielded a 60 percent improvement in throughput performance. The ALLIANT computer platform provided the I/O flexibility needed to accommodate a multitude of peripheral interfaces including the following: up to twelve 25MB/s VME I/O channels; up to five HiPPI I/O full duplex channels; IPI-s, SCSI, SMD, and RAID disk array support; standard networking software support for TCP/IP, NFS, and FTP; open architecture based on standard RISC processors; and V.4/POSIX-based operating system (Concentrix). All components including the software are modular in design and can be reconfigured as needs and system uses change. Users can begin with a small system and add modules as needed in the field. Most add-ons can be accomplished seamlessly without revision, recompilation or re-linking of software.
The measurement of both SO2 and NO2 gases are recognized as an essential component of atmospheric composition missions. We describe current capabilities and limitations of the operational Aura/OMI NO2 and SO2 data that have been used by a large number of researchers. Analyses of the data and validation studies have brought to light a number of areas in which these products can be expanded and improved. Major improvements for new NASA standard (SP) NO2 product include more accurate tropospheric and stratospheric column amounts, along with much improved error estimates and diagnostics. Our approach uses a monthly NO2 climatology based on the NASA Global Modeling Initiative (GMI) chemistry-transport model and takes advantage of OMI data from cloudy scenes to find clean areas where the contribution from the trap NO2 column is relatively small. We then use a new filtering, interpolation and smoothing techniques for separating the stratospheric and tropospheric components of NO2, minimizing the influence of a priori information. The new algorithm greatly improves the structure of stratospheric features relative to the original SP. For the next-generation OMI SO2 product we plan to implement operationally the offline iterative spectral fitting (ISF) algorithm and re-process the OMI Level-2 SO2 dataset using a priori SO2 and aerosol profiles, clouds, and surface reflectivity appropriate for observation conditions. This will improve the ability to detect and quantify weak tropospheric SO2 loadings. The new algorithm is validated using aircraft in-situ data during field campaigns in China (2005 and 2008) and in Maryland (Frostburg, 2010 and DISCOVER-AQ in July 2011). The height of the SO2 plumes will also be estimated for high SO2 loading cases (e.g., volcanic eruptions). The same SO2 algorithm will be applied to the data from OMPS sensor to be launched on NPP satellite later this year. The next-generation NO2 and SO2 products will provide critical information (e.g., averaging kernels) for evaluation of chemistry-transport models, for data assimilation, and to impose top-down constraints on the SO2 and NO2 emission sources.
The planned Soil Moisture Active Passive (SMAP) mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council's Decadal Survey, Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond [1]. Scheduled to launch late in 2014, the proposed SMAP mission would provide high resolution and frequent revisit global mapping of soil moisture and freeze/thaw state, utilizing enhanced Radio Frequency Interference (RFI) mitigation approaches to collect new measurements of the hydrological condition of the Earth's surface. The SMAP instrument design incorporates an L-band radar (3 km) and an L band radiometer (40 km) sharing a single 6-meter rotating mesh antenna to provide measurements of soil moisture and landscape freeze/thaw state [2]. These observations would (1) improve our understanding of linkages between the Earth's water, energy, and carbon cycles, (2) benefit many application areas including numerical weather and climate prediction, flood and drought monitoring, agricultural productivity, human health, and national security, (3) help to address priority questions on climate change, and (4) potentially provide continuity with brightness temperature and soil moisture measurements from ESA's SMOS (Soil Moisture Ocean Salinity) and NASA's Aquarius missions. In the planned SMAP mission prelaunch time frame, baseline algorithms are being developed for generating (1) soil moisture products both from radiometer measurements on a 36 km grid and from combined radar/radiometer measurements on a 9 km grid, and (2) freeze/thaw products from radar measurements on a 3 km grid. These retrieval algorithms need a variety of global ancillary data, both static and dynamic, to run the retrieval models, constrain the retrievals, and provide flags for indicating retrieval quality. The choice of which ancillary dataset to use for a particular SMAP product would be based on a number of factors, including its availability and ease of use, its inherent error and resulting impact on the overall soil moisture or freeze/thaw retrieval accuracy, and its compatibility with similar choices made by the SMOS mission. All decisions regarding SMAP ancillary data sources would be fully documented by the SMAP Project and made available to the user community.
A description of plans for verifying LSST's Calibration Data Products. This document covers our approach to verification element LVV-57, addressing requirement DMS-REQ-0130.