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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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This dataset is from WFIP3 BLOC site WindCube v1 Profiling Lidar / Raw Data from CU Boulder. Please note that the .sta files are in human-readable text, while the .rtd files require some processing software that is not easily automated. We plan to process the .rtd data following the campaign, but if you wish to try it sooner, we can make it available upon request.
The Ohio State University has been requested by the National Aeronautics and Space Administration to conduct a multi-year study and analysis of data from satellites launched specifically for geodetic purposes and from other satellites useful in geodetic studies. The program includes analysis of positions derived from photographic observations of both reflecting and emitting satellites, from range observations and from any other suitable but similar types of data. The final result is supposed to be a geocentric-geodetic datum for the whole earth with connections to all major datums and NASA supported stations.
The networking demands of Ames Research Center are dramatically increasing. More and more workstations are requested to run video and audio applications on the network. These applications require a much greater bandwidth than data applications. The existing ARCLAN 2000 network bandwidth is insufficient, due to the use of FDDI as its backbone, for accommodating video applications. Operating at a maximum of 100 Mbps, FDDI can handle only a few workstations running multimedia applications. The ideal solution is to replace the current ARCLAN 2000 FDDI backbone with an ATM backbone. ATM has the capability to handle the increasing traffic loads on the ARCLAN 2000 that results from these new applications. As it can be seen from Figure 1, ARCLAN 2000 have a total of 32 routers (5 being core routers) each connected to the FDDI backbone via a 100 Mbps link. This network serves 34 different locations by using 34 hubs that are connected to secondary routers. End users are connected to the secondary routers with 10 Mbps links.
While most of the work on this program has been completed, as previously reported, the portion of the program dealing with the sub topic of ISO LWS data analysis and reduction for the LWS Extragalactic Science Team and its leader, Dr. Howard Smith, is still active. This program in fact continues to generate results, and newly available computer modeling has extended the value of the datasets, As a result the team has requested and been granted an obtained a no-cost extension to this program, through December 31, 2003. The essence of the proposal is to perform ISO spectroscopic studies, including data analysis and modeling, of star formation regions using an ensemble of archival space-based data from the Infrared Space Observatory's Long Wavelength Spectrometer and Short Wavelength Spectrometer, but including as well some other spectroscopic data bases. Four kinds of regions are considered in the studies: (1) disks around more evolved objects; (2) young, low or high mass pre-main sequence stars in star formation regions; (3) star formation in external, bright IR galaxies; and (4) the galactic center. One prime focus of the program is the OH lines in the far infrared. The program has the following goals: (1) refine the data analysis of ISO observations, to obtain deeper and better SNR results on selected sources. The ISO data itself underwent "pipeline 10" reductions in early 2001, and additional "hands-on data reduction packages" were supplied by the ISO teams in 2001. The Fabry-Perot database in particularly sensitive to noise can slight calibration errors. (2) model the atomic and molecular line shapes, in particular the OH lines, using revised Monte-Carlo techniques developed by the SWAS team at the Center for Astrophysics; (3) attend scientific meetings and workshops; (4) do E&PO activities related to infrared astrophysics and/or spectroscopy.
Electric power system automation for Space Station Freedom is intended to operate in a loop. Data from the power system is used for diagnosis and security analysis to generate Operations Management System (OMS) requests, which are sent to an arbiter, which sends a plan to a commander generator connected to the electric power system. This viewgraph presentation profiles automation software for diagnosis, scheduling, and constraint interfaces, and simulation to support automation development. The automation development process is diagrammed, and the process of creating Ada and ART versions of the automation software is described.
Global climate change is a topic that has become very controversial despite strong support within the scientific community. It is common for agencies releasing information about climate change to be served with Freedom of Information Act (FOIA) requests for everything that led to that conclusion. Capturing and presenting the provenance, linking to the research papers, data sets, models, analyses, observation instruments and satellites, etc. supporting key findings has the potential to mitigate skepticism in this domain. The U.S. Global Change Research Program (USGCRP) is now coordinating the production of a National Climate Assessment (NCA) that presents our best understanding of global change. We are now developing a Global Change Information System (GCIS) that will present the content of that report and its provenance, including the scientific support for the findings of the assessment. We are using an approach that will present this information both through a human accessible web site as well as a machine readable interface for automated mining of the provenance graph. We plan to use the developing W3C PROV Data Model and Ontology for this system.
Trust in Autonomous Systems is largely about humans trusting the decisions made by autonomous systems. This trust can be increased through learning from domain experts. In particular, autonomous systems can learn offline from past mission operations before conducting any operations of its own. Additionally, autonomous systems can learn online by obtaining human feedback during operations. We will discuss several classes of machine learning methods and our application of them to autonomous systems. The first class of methods is anomaly detection, which uses operations data to identify examples of anomalous operations. The second class of methods is inverse reinforcement learning, also known as apprenticeship learning, that takes past operations data as input and yields a controller that is able to duplicate the operations described by the data. The third class is active learning, which identifies examples on which the model is most uncertain and requests domain expert feedback.
NASA's Earth Observing System Data and Information System (EOSDIS) has been in operation since August 1994, managing most of NASA's Earth science data from satellites, airborne sensors, filed campaigns and other activities. Having been designated by the Federal Government as a project responsible for production, archiving and distribution of these data through its Distributed Active Archive Centers (DAACs), the Earth Science Data and Information System Project (ESDIS) is responsible for EOSDIS, and is legally bound by the Office of Management and Budgets circular A-130, the Federal Records Act. It must follow the regulations of the National Institute of Standards and Technologies (NIST) and National Archive and Records Administration (NARA). It must also follow the NASA Procedural Requirement 7120.5 (NASA Space Flight Program and Project Management). All these ensure that the data centers managed by ESDIS are trustworthy from the point of view of efficient and effective operations as well as preservation of valuable data from NASA's missions. Additional factors contributing to this trust are an extensive set of internal and external reviews throughout the history of EOSDIS starting in the early 1990s. Many of these reviews have involved external groups of scientific and technological experts. Also, independent annual surveys of user satisfaction that measure and publish the American Customer Satisfaction Index (ACSI), where EOSDIS has scored consistently high marks since 2004, provide an additional measure of trustworthiness. In addition, through an effort initiated in 2012 at the request of NASA HQ, the ESDIS Project and 10 of 12 DAACs have been certified by the International Council for Science (ICSU) World Data System (WDS) and are members of the ICSUWDS. This presentation addresses questions such as pros and cons of the certification process, key outcomes and next steps regarding certification. Recently, the ICSUWDS and Data Seal of Approval (DSA) organizations merged their Core Trustworthy Data Repositories Requirements and require that members be recertified every three years. Given the rigor with which NASA manages the ESDIS Project and the DAACs, the recertification through WDSDSA, while involving some additional work, is a relatively simple process.
The results of two questionnaires sent to engineering experts are statistically analyzed and compared with objective data from Saturn V design and testing. Engineers were asked how likely it was for structural failure to occur at load increments above and below analysts' stress limit predictions. They were requested to estimate the relative probabilities of different failure causes, and of failure at each load increment given a specific cause. Three mathematical models are constructed based on the experts' assessment of causes. The experts' overall assessment of prediction strength fits the Saturn V data better than the models do, but a model test option (T-3) based on the overall assessment gives more design change likelihood to overstrength structures than does an older standard test option. T-3 compares unfavorably with the standard option in a cost optimum structural design problem. The report reflects a need for subjective data when objective data are unavailable.
In a frequency-division/demand-assigned multiple-access (FD/DAMA) architecture, each mobile subscriber must make a connection request to the Network Management Center before transmission for either open-end or closed-end services. Open-end services are for voice calls and long file transfer and are processed on a blocked-call-cleared basis. Closed-end services are for transmitting burst data and are processed on a first-come first-served basis. This paper presents the signalling design and architecture for non-voice services of an FD/DAMA mobile satellite network. The connection requests are made through the recently proposed multiple channel collision resolution scheme which provides a significantly higher throughput than the traditional slotted ALOHA scheme. For non-voice services, it is well known that retransmissions are necessary to ensure the delivery of a message in its entirety from the source to destination. Retransmission protocols for open-end and closed-end data transfer are investigated. The signal structure for the proposed network is derived from X-25 standards with appropriate modifications. The packet types and their usages are described in this paper.
With the recent explosion of the Internet and the enormous business opportunities available to communication system providers, great interest has developed in improving the efficiency of data transfer using the Transmission Control Protocol (TCP) of the Internet Protocol (IP) suite. The satellite system providers are interested in solving TCP efficiency problems associated with long delays and error-prone links. Similarly, the terrestrial community is interested in solving TCP problems over high-bandwidth links. Whereas the wireless community is interested in improving TCP performance over bandwidth constrained, error-prone links. NASA realized that solutions had already been proposed for most of the problems associated with efficient data transfer over large bandwidth-delay links (which include satellite links). The solutions are detailed in various Internet Engineering Task Force (IETF) Request for Comments (RFCs). Unfortunately, most of these solutions had not been tested at high-speed (155+ Mbps). Therefore, the NASA's ACTS experiments program initiated a series of TCP experiments to demonstrate scalability of TCP/IP and determine how far the protocol can be optimized over a 622 Mbps satellite link. These experiments were known as the 118i and 118j experiments. During the 118i and 118j experiments, NASA worked closely with SUN Microsystems and FORE Systems to improve the operating system, TCP stacks. and network interface cards and drivers. We were able to obtain instantaneous data throughput rates of greater than 520 Mbps and average throughput rates of 470 Mbps using TCP over Asynchronous Transfer Mode (ATM) over a 622 Mbps Synchronous Optical Network (SONET) OC12 link. Following the success of these experiments and the successful government/industry collaboration, a new series of experiments. the 118x experiments. were developed.
At the request of the Bureau of Aeronautics, Department of the Navy, an investigation at transonic and low supersonic speeds of the drag and longitudinal trim characteristics of the Douglas XF4D-1 airplane is being conducted by the Langley Pilotless Aircraft Research Division. The Douglas XF4D-1 is a jet-propelled, low-aspect-ratio, swept-wing, tailless, interceptor-type airplane designed to fly at low supersonic speeds. As a part of this investigation, flight tests were made using rocket- propelled 1/10- scale models to determine the effect of the addition of 10 external stores and rocket packets on the drag at low lift coefficients. In addition to these data, some qualitative values of the directional stability parameter C(sub n beta) and duct total-pressure recovery are also presented.
Mars Pathfinder, the first low-cost, quick Discovery class mission to be completed, successfully landed on the surface of Mars on July 4, 1997, deployed and navigated a small rover, and collected data from 3 science instruments and 10 technology experiments. The mission operated on Mars for 3 months and returned 2.3 Gbits of new data, including over 16,500 lander and 550 rover images, 16 chemical analyses of rocks and soil, and 8.5 million individual temperature, pressure and wind measurements. The rover traversed 100 m clockwise around the lander, exploring about 200 square meters of the surface. The mission captured the imagination of the public, and garnered front page headlines during the first week. A total of about 566 million internet "hits" were registered during the first month of the mission, with 47 million "hits" on July 8th alone, making the Pathfinder landing by far the largest internet event in history at the time. Pathfinder was the first mission to deploy a rover on Mars. It carried a chemical analysis instrument, to characterize the rocks and soils in a landing area over hundreds of square meters on Mars, which provided a calibration point or "ground truth" for orbital remote sensing observations. The combination of spectral imaging of the landing area by the lander camera, chemical analyses aboard the rover, and close-up imaging of colors, textures and fabrics with the rover cameras offered the potential of identifying rocks (petrology and mineralogy). With this payload, a landing site in Ares Vallis was selected because it appeared acceptably safe and offered the prospect of analyzing a variety of rock types expected to be deposited by catastrophic floods, which enabled addressing first-order scientific questions such as differentiation of the crust, the development of weathering products, and the nature of the early Martian environment and its subsequent evolution. The 3 instruments and rover allowed seven areas of scientific investigation: the geology and geomorphology of the surface, mineralogy and geochemistry of rocks and soils, physical properties of surface materials, magnetic properties of airborne dust, atmospheric science including aerosols, and rotational and orbital dynamics of Mars. Scientists were assembled into 7 Science Operations Groups that were responsible for requesting measurements by the 3 instruments, rover and engineering subsystems for carrying out their scientific investigations and for analyzing the data and reporting on their findings. The spacecraft was launched on December 4, 1996 and had a 7 month cruise to Mars, with four trajectory correction maneuvers. The vehicle entered the atmosphere directly following cruise stage separation. Parachute deployment, heatshield and lander separation, radar ground acquisition, airbag inflation and rocket ignition all occurred before landing at 2:58 AM true local solar time (9:56:55 AM PDT). The lander bounced at least 15 times up to 12 in high without airbag rupture, demonstrating the robustness of this landing system. Reconstruction of the final landing sequence indicates that the parachute/backshel1/1ander was tilted due to a northwest directed wind and wind shear, which resulted in the lander bouncing about I km to the northwest and initially downhill about 20 m from where the solid rockets fired. Two anomalously bright spots located in the lander scene are likely the heatshield, which continued in a ballistic trajectory about 2 km downrange (west southwest), and the backshell/parachute, which stayed nearer to where the rockets fired. Unconnected disturbed soil patches in the scene indicate that the final few bounces of the lander were from the east-southeast and were followed by a gentle roll to the west before coming to rest on the base petal. The location of the lander away from where the solid rockets fired and considerations of the exhaust products used to inflate the airbags and their fate, indicate that the Pathfinder landing system is one of the cleanest designed leaving the local area essentially contaminant free. The radio signal from the low-=gain antenna was received at 11:34 AM PDT indicating a successful landing.
An Interactive Cluster Analysis Procedure (ICAP) was developed to derive classifier training statistics from remotely sensed data. The algorithm interfaces the rapid numerical processing capacity of a computer with the human ability to integrate qualitative information. Control of the clustering process alternates between the algorithm, which creates new centroids and forms clusters and the analyst, who evaluate and elect to modify the cluster structure. Clusters can be deleted or lumped pairwise, or new centroids can be added. A summary of the cluster statistics can be requested to facilitate cluster manipulation. The ICAP was implemented in APL (A Programming Language), an interactive computer language. The flexibility of the algorithm was evaluated using data from different LANDSAT scenes to simulate two situations: one in which the analyst is assumed to have no prior knowledge about the data and wishes to have the clusters formed more or less automatically; and the other in which the analyst is assumed to have some knowledge about the data structure and wishes to use that information to closely supervise the clustering process. For comparison, an existing clustering method was also applied to the two data sets.
The domestic nuclear power plant fleet has relied on labor-intensive and time-consuming preventive maintenance programs, thus driving up operation and maintenance costs to achieve high-capacity factors. Artificial intelligence and machine learning can help simplify complex problems, such as diagnosing equipment degradation, to enable more effective decision-making. Benefits will be felt not only within existing analog and digital instrumentation and control, but also work processes, the integration of people with technology, and most importantly, the business case. Together, these hold promise to make nuclear power more efficient and reduce costs associated with operation and maintenance. While the artificial intelligence and machine learning technologies hold significant promise in the nuclear industry, there are challenges or barriers to their adoption. This report outlines the those different machine learning adoption barriers (categorized as historical, technical, economic, regulatory, and user) that the industry must overcome to realize the full benefits of artificial intelligence and machine learning capabilities for long-term economic sustainability. This report also provides solutions for some of these barriers by focusing on improving the explainability of machine learning to encourage trust from the end-user. Trust and explainability are essential to machine learning adoption. This report focuses on research-developed solutions to some of these barriers while analyzing a non-safety-related system, namely the circulating water system. This system frequently experiences waterbox fouling which our models preemptively diagnoses then explains to the operator how those conclusions were reached. This report presents and discusses the inherent trade-off between machine learning performance (in terms of accuracy) and explainability, where highly accurate machine learning methods (such as deep-learning) are the least explainable, and the most explainable methods (such as decision trees) are the least accurate. In addition, explainability of artificial intelligence techniques in terms of transparency and post-hoc metrics are discussed. This report outlines the importance of data novelty and value of new information in evaluating both the explainability and trustworthiness. Novelty detection helps to establish consistency or inconsistency of the new data with respect to the training data. On the other hand, value of information could be a part of the user-centric visualization recommendation system that request additional information to be collected, thereby strengthening the machine learning outcomes. During this project, a copyrighted user-centric visualization that aligns with a human-in-the-loop approach was developed. The user-centric visualization presents different levels of information and can be tailored as per user credentials to gain user confidence. One of the salient features of the user-centric visualization is it presents machine learning methods with explainability metrics. A simplified version of the user-centric visualization was presented to 32 users with varying levels of machine learning expertise. Feedback was solicited to test the hypothesis that the app contained sufficient explainability and that the users would trust the algorithm. Overall, the app was positively received, and the hypothesis was supported. This report discusses the trust-but-verify framework – a potential approach to build user trust artificial intelligence. The framework discusses trust from the human level to artificial intelligence level. The fundamental premise of the trust but verify framework is derived from an observation of nuclear safety culture (i.e., nuclear power plant personnel do not rely on a singular source of data to make a decision). This also ties back to the user-centric visualization that presents different levels of information to achieve both explainability and trustworthiness of artificial intelligence. Even so, the adoption of artificial intelligence and machine learning in the nuclear industry faces additional barriers, namely regulatory and stakeholder readiness. To overcome these challenges, new solutions must gain regulatory approval and cater to stakeholder needs. The Nuclear Regulatory Committee has a 5-year strategic plan which prepares them for reviewing artificial intelligence technologies in licensee submissions. Early and frequent engagement with the regulator is encouraged. Additionally, artificial intelligence solutions should incorporate human-in-the-loop considerations and offer explainability. Stakeholders must prepare by hiring or training staff to adapt to advancing technology in everyday plant tasks.
Trying to get your experiment aboard ISS? You likely will need power. Many enditem providers do. ISS Plug-In Plan (IPiP) supports power and data for science, Payloads (or Utilization), vehicle systems, and daily operations through the Electrical Power System (EPS) Secondary Power/Data Subsystem. Yet limited resources and increasing requirements continue to influence decisions on deployment of ISS end items. Given the fluid launch schedule and the rapidly- increasing number of end item providers requiring power support, the focus of the Plug-In Plan has evolved from a simple FIFO recommendation to provide power to end item users, to anticipating future requirements by judicious development and delivery of support equipment (cables, power supplies, power strips, and alternating current (AC) power inverters), employing innovative deployment strategies, and collaborating on end item development. This paper describes the evolution of the ISS Program Office, Engineering Directorate, Flight Operations Directorate (FOD), International Partners and the end item provider relationship and how collaboration successfully leverages unique requirements with limited on- board equipment and resources, tools and processes which result in more agile integration, and describes the process designed for the new ISS end item provider to assure that their power requirements will be met.
An approach is described that provides a distributed directory structure within a storage of an information handling system (a local node). A request is received with the request corresponding to a shared virtual address. The shared virtual address that is shared amongst a number of nodes that includes the local node and some remote nodes. A Global Address Space Directory (GASD) is retrieved that corresponds to a global virtual address space. The GASD is stored in a Coordination Namespace that is stored in a memory that is distributed amongst the nodes. A mapping that is included in the GASD is used to determine the node where the shared virtual address currently resides. The shared virtual address is then accessed from the node where it currently resides.
Abstract The US National Library of Medicine regularly collects summary data on direct use of Unified Medical Language System (UMLS) resources. The summary data sources include UMLS user registration data, required annual reports submitted by registered users, and statistics on downloads and application programming interface calls. In 2019, the National Library of Medicine analyzed the summary data on 2018 UMLS use. The library also conducted a scoping review of the literature to provide additional intelligence about the research uses of UMLS as input to a planned 2020 review of UMLS production methods and priorities. 5043 direct users of UMLS data and tools downloaded 4402 copies of the UMLS resources and issued 66 130 951 UMLS application programming interface requests in 2018. The annual reports and the scoping review results agree that the primary UMLS uses are to process and interpret text and facilitate mapping or linking between terminologies. These uses align with the original stated purpose of the UMLS.