SEARCH · Engineering Papers
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.
The architecture of NASA's Earth Observation System Data Information System (EOSDIS) is described. The role of the EOSDIS Core System (ECS) is described, showing how each ECS functional category (flight operations functions, science data processing functions, and communications and system management functions) supports the five EOSDIS goals and objectives. The baseline configuration of ECS is presented and discussed.
A large portion of Earth Science investigations is phenomenon- or event-based, such as the studies of Rossby waves, mesoscale convective systems, and tropical cyclones. However, except for a few high-impact phenomena, e.g. tropical cyclones, comprehensive records are absent for the occurrences or events of these phenomena. Phenomenon-based studies therefore often focus on a few prominent cases while the lesser ones are overlooked. Without an automated means to gather the events, comprehensive investigation of a phenomenon is at least time-consuming if not impossible. An Earth Science event (ES event) is defined here as an episode of an Earth Science phenomenon. A cumulus cloud, a thunderstorm shower, a rogue wave, a tornado, an earthquake, a tsunami, a hurricane, or an EI Nino, is each an episode of a named ES phenomenon," and, from the small and insignificant to the large and potent, all are examples of ES events. An ES event has a finite duration and an associated geolocation as a function of time; its therefore an entity in four-dimensional . (4D) spatiotemporal space. The interests of Earth scientists typically rivet on Earth Science phenomena with potential to cause massive economic disruption or loss of life, but broader scientific curiosity also drives the study of phenomena that pose no immediate danger. We generally gain understanding of a given phenomenon by observing and studying individual events - usually beginning by identifying the occurrences of these events. Once representative events are identified or found, we must locate associated observed or simulated data prior to commencing analysis and concerted studies of the phenomenon. Knowledge concerning the phenomenon can accumulate only after analysis has started. However, except for a few high-impact phenomena. such as tropical cyclones and tornadoes, finding events and locating associated data currently may take a prohibitive amount of time and effort on the part of an individual investigator. And even for these high-impact phenomena, the availability of comprehensive records is still only a recent development. A major reason for the lack of comprehensive ,records for the majority of the ES phenomena is the perception that they do not pose immediate and/or severe threat to life and property and are thus not consistently tracked. monitored, and catalogued. Many phenomena even lack commonly accepted criteria for definitions. However. the lack of comprehensive records is also due to the increasingly prohibitive volume of observations and model data that must be examined. NASA Earth Observing System Data Information System (EOSDIS) alone archives several petabytes (PB) of satellite remote sensing data and steadily increases. All of these factors contribute to the difficulty of methodically identifying events corresponding to a given phenomenon and significantly impede systematic investigations. In the following we present a couple motivating scenarios, demonstrating the issues faced by Earth scientists studying ES phenomena.
A significant portion of Earth Science investigations is phenomenon- (or event-) based, such as the studies of Rossby waves, volcano eruptions, tsunamis, mesoscale convective systems, and tropical cyclones. However, except for a few high-impact phenomena, e.g. tropical cyclones, comprehensive records are absent for the occurrences or events of these phenomena. Phenomenon-based studies therefore often focus on a few prominent cases while the lesser ones are overlooked. Without an automated means to gather the events, comprehensive investigation of a phenomenon is at least time-consuming if not impossible. We have constructed a prototype Automated Event Service (AES) system that is used to methodically mine custom-defined events in the reanalysis data sets of atmospheric general circulation models. Our AES will enable researchers to specify their custom, numeric event criteria using a user-friendly web interface to search the reanalysis data sets. Moreover, we have included a social component to enable dynamic formation of collaboration groups for researchers to cooperate on event definitions of common interest and for the analysis of these events. An Earth Science event (ES event) is defined here as an episode of an Earth Science phenomenon (ES phenomenon). A cumulus cloud, a thunderstorm shower, a rogue wave, a tornado, an earthquake, a tsunami, a hurricane, or an El Nino, is each an episode of a named ES phenomenon, and, from the small and insignificant to the large and potent, all are examples of ES events. An ES event has a duration (often finite) and an associated geo-location as a function of time; it's therefore an entity embedded in four-dimensional (4D) spatiotemporal space. Earth Science phenomena with the potential to cause massive economic disruption or loss of life often rivet the attention of researchers. But, broader scientific curiosity also drives the study of phenomena that pose no immediate danger, such as land/sea breezes. Due to Earth System's intricate dynamics, we are continuously discovering novel ES phenomena. We generally gain understanding of a given phenomenon by observing and studying individual events. This process usually begins by identifying the occurrences of these events. Once representative events are identified or found, we must locate associated observed or simulated data prior to commencing analysis and concerted studies of the phenomenon. Knowledge concerning the phenomenon can accumulate only after analysis has started. However, as mentioned previously, comprehensive records only exist for a very limited set of high-impact phenomena; aside from these, finding events and locating associated data currently may take a prohibitive amount of time and effort on the part of an individual investigator. The reason for the lack of comprehensive records for most of the ES phenomena is mainly due to the perception that they do not pose immediate and/or severe threat to life and property. Thus they are not consistently tracked, monitored, and catalogued. Many phenomena even lack precise and/or commonly accepted criteria for definitions. Moreover, various Earth Science observations and data have accumulated to a previously unfathomable volume; NASA Earth Observing System Data Information System (EOSDIS) alone archives several petabytes (PB) of satellite remote sensing data, which are steadily increasing. All of these factors contribute to the difficulty of methodically identifying events corresponding to a given phenomenon and significantly impede systematic investigations. We have not only envisioned AES as an environment for identifying customdefined events but also aspired for it to be an interactive environment with quick turnaround time for revisions of query criteria and results, as well as a collaborative environment where geographically distributed experts may work together on the same phenomena. A Big Data technology is thus required for the realization of such a system. In the following, we first introduce the technology selected for AES in the next section. We then demonstrate the utility of AES using a use case, Blizzard, before we conclude.
STEM (Science, Technology, Engineering, Mathematics) learning is most effective when students are encouraged to see the connections between science, technology and real world problems. Helping to make these connections has become an increasingly important aspect of Earth Science data research. The Global Hydrology Resource Center (GHRC), one of NASA's 12 EOSDIS (Earth Observing System Data Information System) data centers, has developed a new type of documentation called the micro article to facilitate making connections between data and Earth science research problems.
NASAs Earth Observing System Data Information System (EOSDIS) manages Earth Observation satellites and the Distributed Active Archive Centers (DAACs), where the data is stored and processed. The challenge is that Earth Observation data is complicated. There is plenty of data available, however, the science teams have had a top-down approach: define what it is you are trying to study -select a set of satellite(s) and sensor(s), and drill down for the data.Our alternative is to take a bottom-up approach using eight environmental fields of interest as defined by the Group on Earth Observations (GEO) called Societal Benefit Areas (SBAs): Disaster Resilience (DR) Public Health Surveillance (PHS) Energy and Mineral Resource Management (EMRM) Water Resources Management (WRM) Infrastructure and Transport Management (ITM) Sustainable Urban Development (SUD) Food Security and Sustainable Agriculture (FSSA) Biodiversity and Ecosystems Sustainability (BES).
This presentation summarizes the current status of NASA/Earth Observing System Data & Information System (EOSDIS) Digital Object Identifiers (DOIs) which provide Persistent Identifiers for citing NASA data sets.
The Exploration Extravehicular Mobility Unit (xEMU) project was the culimation of over a decade of spacesuit development that was performed in-house at the NASA Johnson Space Center. This project reached a level where almost fully completed development fidelity spacesuits had been designed, assembled and tested in an integrated configuration. The xEMU Development-Verification-Test (DVT) hardware was assembled into two different xEMU test articles and underwent a series of thermal-vacuum tests at the Johnson Space Center’s Chamber B. These tests not only gathered data on thermal performance, but also exercised the life support system, communication system, suit information systems, and suit avionics. This complex test has and will continue to produce many meaningful reports ranging from component level test results (for example on spacesuit boots), test design of heater cages to simulate thermal environments for a spacesuit test article, and higher level thermal performance of subsystems (such as the Portable Life Support System) or the entire assembly. This paper provides an overview of the test configuration and also top level results from this highly successful integrated test of the xEMU.
The Exploration Extravehicular Mobility Unit (xEMU) project was the culimation of over a decade of spacesuit development that was performed in-house at the NASA Johnson Space Center. This project reached a level where almost fully completed development fidelity spacesuits had been designed, assembled and tested in an integrated configuration. The xEMU Development-Verification-Test (DVT) hardware was assembled into two different xEMU test articles and underwent a series of thermal-vacuum tests at the Johnson Space Center’s Chamber B. These tests not only gathered data on thermal performance, but also exercised the life support system, communication system, suit information systems, and suit avionics. This complex test has and will continue to produce many meaningful reports ranging from component level test results (for example on spacesuit boots), test design of heater cages to simulate thermal environments for a spacesuit test article, and higher level thermal performance of subsystems (such as the Portable Life Support System) or the entire assembly. This paper provides an overview of the test configuration and also top level results from this highly successful integrated test of the xEMU.
Development work on system design information for amine type carbon dioxide sorber is reported. Amberlite IR-45, an aminated styrene divinyl benzene matrix, was investigated to determine the influence of design parameters of sorber particle size, process flow rate, CO2 partial pressure, total pressure, and bed designs. CO2 capacity and energy requirements for a 4-man size system were related mathematically to important operational parameters. Some fundamental studies in CO2 sorber capacity, energy requirements, and process operation were also performed.
Information is given in viewgraph form on the modeling of nonlinear damping in distributed parameter systems.
This viewgraph presentation lists questions regarding the implementation of System Wide Information Management (SWIM). Some of the questions concern policy issues and strategies, technology issues and strategies, or transition issues and strategies.
The main goal is to prepare the space station technical and managerial structure for likely changes in the creation, capture, transfer, and utilization of knowledge. By anticipating advances, the design of Space Station Project (SSP) information systems can be tailored to facilitate a progression of increasingly sophisticated strategies as the space station evolves. Future generations of advanced information systems will use increases in power to deliver environmentally meaningful, contextually targeted, interconnected data (knowledge). The concept of a Knowledge Base Management System is emerging when the problem is focused on how information systems can perform such a conversion of raw data. Such a system would include traditional management functions for large space databases. Added artificial intelligence features might encompass co-existing knowledge representation schemes; effective control structures for deductive, plausible, and inductive reasoning; means for knowledge acquisition, refinement, and validation; explanation facilities; and dynamic human intervention. The major areas covered include: alternative knowledge representation approaches; advanced user interface capabilities; computer-supported cooperative work; the evolution of information system hardware; standardization, compatibility, and connectivity; and organizational impacts of information intensive environments.
NASAs Earth Observing System Data and Information System (EOSDIS) contains a rich set of datasets and related services throughout its many elements. As a result, locating all the EOSDIS data and related resources relevant to particular science theme can be daunting. This is largely because EOSDIS data's organizing principle is affected more by the way they are produced than around the expected end use. Virtual collections oriented around science themes can overcome this by presenting collections of data and related resources that are organized around the user's interest, not around the way the data were produced. Virtual collections consist of annotated web addresses (URLs) that point to data and related resource addresses, thus avoiding the need to copy all of the relevant data to a single place. These URL addresses can be consumed by a variety of clients, ranging from basic URL downloaders (wget, curl) and web browsers to sophisticated data analysis programs such as the Integrated Data Viewer.
The NASA representative to the Unidata Strategic Committee presented a semiannual update on NASAs work with and use of Unidata technologies. The talk covered the program of cloud computing prototypes being undertaken for the Earth Observing System Data and Information System (EOSDIS). Also discussed were dataset interoperability recommendations ratified via the EOSDIS Standards Office and the HDF Product Designer tool with respect to its possible applicability to data in network Common Data Form (NetCDF) version 4.
The NASA representative to the Unidata Strategic Committee presented a semiannual update on NASAs work with and use of Unidata technologies. The talk updated Unidata on the program of cloud computing prototypes underway for the Earth Observing System Data and Information System (EOSDIS). Also discussed was a trade study on the use of the Open source Project for a Network Data Access Protocol (OPeNDAP) with Web Object Storage in the cloud.
For NASA's Advanced Information Systems Technology (AIST) Program, an Earth System Digital Twin (ESDT) is defined as an interactive and integrated multidomain, multiscale, digital replica of the state and temporal evolution of Earth systems. It dynamically integrates: relevant Earth system models and simulations; other relevant models (e.g., related to the world's infrastructure); continuous and timely (including near real time and direct readout) observations (e.g., space, air, ground, over/underwater, Internet of Things (IoT), socioeconomic); long-time records; as well as analytics and artificial intelligence tools. Effective ESDTs enable users to run hypothetical scenarios to improve the understanding, prediction of and mitigation/response to Earth system processes, natural phenomena and human activities as well as their many interactions. An ESDT is a type of integrated information system that, for example, enables continuous assessment of impact from naturally occurring and/or human activities on physical and natural environments. AIST ESDT strategic goals are to: 1. Develop information system frameworks to provide continuous and accurate representations of systems as they change over time; 2. Mirror various Earth Science systems and utilize the combination of Data Analytics, Artificial Intelligence, Digital Thread, and state-of-the-art models to help predict the Earth’s response to various phenomena; 3. Provide the tools to conduct "what if" investigations that can result in actionable predictions. The AIST ESDT thrust is developing capabilities toward the development of future digital twins of the Earth or of subcomponents of the Earth. This will enable the development of an overarching framework that will integrate New Observing Strategies (NOS) to enable new observation measurements, i.e., multi-source, coordinated, dynamic and responsive to needs and requests defined by Analytic Collaborative Frameworks (ACF) that enable agile science investigations fusing and analyzing very large amounts of diverse data. NOS and ACF capabilities along with open access to various science, infrastructure and human data, interconnected modeling, data assimilation, simulations, surrogate modeling, high-performance computing and advanced visualization, will define a powerful framework that could be utilized for local, regional or global and/or thematic digital twins. This presentation will describe a general overview of the AIST ESDT vision including prior work done in the areas of NOS and ACF as well as current and upcoming ESDT projects.
Information is provided on the development, qualification and acceptance verification of commercial solar heating and hot water systems and components. The verification includes the performances, the efficiences and the various methods used, such as similarity, analysis, inspection, test, etc., that are applicable to satisfying the verification requirements.
This document presents the user's guide, system description, and mathematical specifications for the Langley Atmospheric Information Retrieval System (LAIRS). It also includes a description of an optimal procedure for operational use of LAIRS. The primary objective of the LAIRS Program is to make it possible to obtain accurate estimates of atmospheric pressure, density, temperature, and winds along Shuttle reentry trajectories for use in postflight data reduction.