Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “network baseline”

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.

At least 541 records · Page 30

Error analysis for a spaceborne laser ranging system

The dependence (or independence) of baseline accuracies, obtained from a typical mission of a spaceborne ranging system, on several factors is investigated. The emphasis is placed on a priori station information, but factors such as the elevation cut-off angle, the geometry of the network, the mean orbital height, and to a limited extent geopotential modeling are also examined. The results are obtained through simulations, but some theoretical justification is also given. Guidelines for freeing the results from these dependencies are suggested for most of the factors.

Pavlis, E. C.↗

Global and regional kinematics with VLBI

Since a VLBI station cannot operate in isolation and since simultaneous operation of the entire VLBI network is impractical, it is necessary to design observing programs with periodic observing sessions using networks of 3-7 stations that, when treated together, will have the necessary interstation data and network overlaps to determine the desired rates of change. Thus, there has been a mix of global, intercontinental, transcontinental, and regional networks to make measurements ranging from plate motions to deformation over a few hundred km. Over time, even networks focusing on regional deformation using mobile VLBI included large stations removed by several thousand km to increase sensitivity, determine EOP more accurately, and provide better ties to the terrestrial reference frame (TRF). Analysis products have also evolved, beginning with baseline components, and then to full three-dimensional site velocities in a global TRF.

Ma, Chopo↗

Integrating Enhanced Grace Terrestrial Water Storage Data Into the U.S. and North American Drought Monitors

NASA's Gravity Recovery and Climate Experiment (GRACE) satellites measure time variations nf the Earth's gravity field enabling reliable detection of spatio-temporal variations in total terrestrial water storage (TWS), including ground water. The U.S. and North American Drought Monitors are two of the premier drought monitoring products available to decision-makers for assessing and minimizing drought impacts, but they rely heavily on precipitation indices and do not currently incorporate systematic observations of deep soil moisture and groundwater storage conditions. Thus GRACE has great potential to improve the Drought Monitors hy filling this observational gap. Horizontal, vertical and temporal disaggregation of the coarse-resolution GRACE TWS data has been accomplished by assimilating GRACE TWS anomalies into the Catchment Land Surface Model using ensemble Kalman smoother. The Drought Monitors combine several short-term and long-term drought indices and indicators expressed in percentiles as a reference to their historical frequency of occurrence for the location and time of year in question. To be consistent, we are in the process of generating a climatology of estimated soil moisture and ground water based on m 60-year Catchment model simulation which will subsequently be used to convert seven years of GRACE assimilated fields into soil moisture and groundwater percentiles. for systematic incorporation into the objective blends that constitute Drought Monitor baselines. At this stage we provide a preliminary evaluation of GRACE assimilated Catchment model output against independent datasets including soil moisture observations from Aqua AMSR-E and groundwater level observations from the U.S. Geological Survey's Groundwater Climate Response Network.

Housborg, Rasmus↗

Cognitive Assessment During Long-Duration Space Flight

The Space Flight Cognitive Assessment Tool for Windows (WinSCAT) is a computer-based, self-administered battery of five cognitive assessment tests developed for medical operations at NASA's Johnson Space Center in Houston, Texas. WinSCAT is a medical requirement for U.S. long-duration astronauts and has been implemented with U.S. astronauts from one NASA/Mir mission (NASA-7 mission) and all expeditions to date on the International Space Station (ISS). Its purpose is to provide ISS crew surgeons with an objective clinical tool after an unexpected traumatic event, a medical condition, or the cumulative effects of space flight that could negatively affect an astronaut's cognitive status and threaten mission success. WinSCAT was recently updated to add network capability to support a 6-person crew on the station support computers. Additionally, WinSCAT Version 2.0.28 has increased difficulty of items in Mathematics, increased number of items in Match-to-Sample, incorporates a moving rather than a fixed baseline, and implements stricter interpretation rules. ISS performance data were assessed to compare initial to modified interpretation rules for detecting potential changes in cognitive functioning during space flight. WinSCAT tests are routinely taken monthly during an ISS mission. Performance data from these ISS missions do not indicate significant cognitive decrements due to microgravity/space flight alone but have shown decrements. Applying the newly derived rules to ISS data results in a number of off-nominal performances at various times during and after flight.. Correlation to actual events is needed, but possible explanations for off-nominal performances could include actual physical factors such as toxic exposure, medication effects, or fatigue; emotional factors including stress from the mission or life events; or failure to exert adequate effort on the tests.

Seaton, Kimberly↗

Link monitor and control operator assistant: A prototype demonstrating semiautomated monitor and control

This article describes the approach, results, and lessons learned from an applied research project demonstrating how artificial intelligence (AI) technology can be used to improve Deep Space Network operations. Configuring antenna and associated equipment necessary to support a communications link is a time-consuming process. The time spent configuring the equipment is essentially overhead and results in reduced time for actual mission support operations. The NASA Office of Space Communications (Code O) and the NASA Office of Advanced Concepts and Technology (Code C) jointly funded an applied research project to investigate technologies which can be used to reduce configuration time. This resulted in the development and application of AI-based automated operations technology in a prototype system, the Link Monitor and Control Operator Assistant (LMC OA). The LMC OA was tested over the course of three months in a parallel experimental mode on very long baseline interferometry (VLBI) operations at the Goldstone Deep Space Communications Center. The tests demonstrated a 44 percent reduction in pre-calibration time for a VLBI pass on the 70-m antenna. Currently, this technology is being developed further under Research and Technology Operating Plan (RTOP)-72 to demonstrate the applicability of the technology to operations in the entire Deep Space Network.

Lee, L. F.↗

The development and operation of the international solar-terrestrial physics central data handling facility

The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) International Solar-Terrestrial Physics (ISTP) Program is committed to the development of a comprehensive, multi-mission ground data system which will support a variety of national and international scientific missions in an effort to study the flow of energy from the sun through the Earth-space environment, known as the geospace. A major component of the ISTP ground data system is an ISTP-dedicated Central Data Handling Facility (CDHF). Acquisition, development, and operation of the ISTP CDHF were delegated by the ISTP Project Office within the Flight Projects Directorate to the Information Processing Division (IPD) within the Mission Operations and Data Systems Directorate (MO&DSD). The ISTP CDHF supports the receipt, storage, and electronic access of the full complement of ISTP Level-zero science data; serves as the linchpin for the centralized processing and long-term storage of all key parameters generated either by the ISTP CDHF itself or received from external, ISTP Program approved sources; and provides the required networking and 'science-friendly' interfaces for the ISTP investigators. Once connected to the ISTP CDHF, the online catalog of key parameters can be browsed from their remote processing facilities for the immediate electronic receipt of selected key parameters using the NASA Science Internet (NSI), managed by NASA's Ames Research Center. The purpose of this paper is twofold: (1) to describe how the ISTP CDHF was successfully implemented and operated to support initially the Japanese Geomagnetic Tail (GEOTAIL) mission and correlative science investigations, and (2) to describe how the ISTP CDHF has been enhanced to support ongoing as well as future ISTP missions. Emphasis will be placed on how various project management approaches were undertaken that proved to be highly effective in delivering an operational ISTP CDHF to the Project on schedule and within budget. Examples to be discussed include: the development of superior teams; the use of Defect Causal Analysis (DCA) concepts to improve the software development process in a pilot Total Quality Management (TQM) initiative; and the implementation of a robust architecture that will be able to support the anticipated growth in the ISTP Program science requirements with only incremental upgrades to the baseline system. Further examples include the use of automated data management software and the implementation of Government and/or industry standards, whenever possible, into the hardware and software development life-cycle. Finally, the paper will also report on several new technologies (for example, the installation of a Fiber Data Distribution Interface network) that were successfully employed.

Lehtonen, Kenneth↗

SUBTASK 1.6 – BASIN ELECTRIC CARBON STORAGE RESEARCH PROJECT: NOVEL MONITORING TECHNIQUES

The Energy & Environmental Research Center (EERC) conducted baseline activities associated with an applied research project at Basin Electric Power Cooperative’s (Basin’s) carbon capture and storage (CCS) site in Beulah, North Dakota, to establish novel carbon storage-monitoring techniques as commercial methods under Cooperative Agreement No. DE-FE0024233, Subtask 1.6. The following report summarizes the baseline activities performed and briefly describes the subsequent (operational monitoring) activities that have been proposed to the U.S. Department of Energy (DOE) as part of the overall project to develop and demonstrate novel monitoring techniques at North America’s largest permitted CCS operation. Dakota Gasification Company (DGC), a wholly owned subsidiary of Basin, owns and operates the Great Plains Synfuels Plant (GPSP) approximately 5 miles northwest of the town of Beulah, North Dakota (Figure 1). In 2023, DGC received approval from the North Dakota Industrial Commission (NDIC) to develop a storage facility on-site for injecting a stream of carbon dioxide (CO2) captured from GPSP. DGC will transport the captured CO2 stream with approximately 6.8 miles of transmission lines that extend north of GPSP and inject >1 million tonnes (MMt) of CO2 annually (>1 MMt/yr) over a 12-year period with up to six underground injection control (UIC) Class VI-compliant injection wells completed in the Broom Creek Formation, a predominantly sandstone reservoir and saline aquifer underlying GPSP. The Broom Creek Formation lies approximately 5900 feet (ft) below ground surface (bgs) at GPSP. The commercial scale (i.e., >1 MMt/yr) of DGC’s permitted carbon storage project is ideal for developing and testing the novel monitoring techniques included within Subtask 1.6. The goals of this project are to demonstrate 1) the cost-effectiveness of novel monitoring technologies included as part of this research, 2) technology capability for tracking the CO2 plume and/or associated pressure response in the subsurface and monitoring out-of-zone migration, and 3) compliance with UIC Class VI program requirements. The research activities proposed for the overall project include 1) design of an automated, integrated, modular (AIM) monitoring station; 2) time-lapse electromagnetic (EM) field surveys; 3) drone-based surveillance studies; 4) time-lapse monitoring with seismic methods; 5) advanced wellbore-monitoring methods; 6) deployment of an AIM monitoring network; 7) EM monitoring of CO2 with real-time data processing; 8) continued seasonal drone-based surveillance studies; 9) seismic monitoring with passive and active surveys; and 10) wellbore monitoring with nuclear magnetic resonance (NMR) for near-surface characterization. Completion of Activities 1.0–5.0 (baseline activities) are described in this report. Upon authorization of funding by DOE, the EERC will initiate Activities 6.0– 10.0 (operational monitoring activities). Current state-of-the-art (SOA) carbon storage-monitoring techniques require countless labor hours dedicated to the acquisition of data. Once data are gathered, these SOA techniques often rely on commercial facilities to process raw data from the field. However, it is anticipated that next-generation monitoring techniques, such as those being demonstrated, will lower acquisition footprints, be less operationally intensive, and improve data acquisition efficiencies. These new techniques are more conducive to the application of machine learning, artificial intelligence, and automation, thus providing a pathway for integration into active control systems, informing site operability, and improving the integration of data for future CCS projects across the United States. Additionally, reclaimed and active mining lands are present within the project site, creating a unique opportunity to demonstrate the effectiveness of remote sensing and surface-based geophysics monitoring techniques at similar project sites that may include disturbed, unconsolidated, or actively excavated near-surface environments. The efforts included in the overall project will produce necessary designs, learnings, and data acquired during the baseline and operational monitoring periods that are necessary for time-lapse demonstration and validation of the described monitoring techniques. In addition, it is anticipated that the monitoring technologies included in this study will be compliant with UIC Class VI requirements to enable the potential for implementation at other CCS sites across the United States.

42 ENGINEERING↗

Definition, analysis and development of an optical data distribution network for integrated avionics and control systems

The potential and functional requirements of fiber optic bus designs for next generation aircraft are assessed. State-of-the-art component evaluations and projections were used in the system study. Complex networks were decomposed into dedicated structures, star buses, and serial buses for detailed analysis. Comparisons of dedicated links, star buses, and serial buses with and without full duplex operation and with considerations for terminal to terminal communication requirements were obtained. This baseline was then used to consider potential extensions of busing methods to include wavelength multiplexing and optical switches. Example buses were illustrated for various areas of the aircraft as potential starting points for more detail analysis as the platform becomes definitized.

Burns, R. R.↗

Secure Large-Scale Airport Simulations Using Distributed Computational Resources

To fully conduct research that will support the far-term concepts, technologies and methods required to improve the safety of Air Transportation a simulation environment of the requisite degree of fidelity must first be in place. The Virtual National Airspace Simulation (VNAS) will provide the underlying infrastructure necessary for such a simulation system. Aerospace-specific knowledge management services such as intelligent data-integration middleware will support the management of information associated with this complex and critically important operational environment. This simulation environment, in conjunction with a distributed network of supercomputers, and high-speed network connections to aircraft, and to Federal Aviation Administration (FAA), airline and other data-sources will provide the capability to continuously monitor and measure operational performance against expected performance. The VNAS will also provide the tools to use this performance baseline to obtain a perspective of what is happening today and of the potential impact of proposed changes before they are introduced into the system.

McDermott, William J.↗

Using Neural Networks to Explore Air Traffic Controller Workload

When a new system, concept, or tool is proposed in the aviation domain, one concern is the impact that this will have on operator workload. As an experience, workload is difficult to measure in a way that will allow comparison of proposed systems with those already in existence. Chatterji and Sridhar (2001) suggested a method by which airspace parameters can be translated into workload ratings, using a neural network. This approach was employed, and modified to accept input from a non-real time airspace simulation model. The following sections describe the preparations and testing work that will enable comparison of a future airspace concept with a current day baseline in terms of workload levels.

Martin, Lynne↗

Self port scanning tool : providing a more secure computing Environment through the use of proactive port scanning

Secure computing is a necessity in the hostile environment that the internet has become. Protection from nefarious individuals and organizations requires a solution that is more a methodology than a one time fix. One aspect of this methodology is having the knowledge of which network ports a computer has open to the world, These network ports are essentially the doorways from the internet into the computer. An assessment method which uses the nmap software to scan ports has been developed to aid System Administrators (SAs) with analysis of open ports on their system(s). Additionally, baselines for several operating systems have been developed so that SAs can compare their open ports to a baseline for a given operating system. Further, the tool is deployed on a website where SAs and Users can request a port scan of their computer. The results are then emailed to the requestor. This tool aids Users, SAs, and security professionals by providing an overall picture of what services are running, what ports are open, potential trojan programs or backdoors, and what ports can be closed.

nMap↗

Iris Deep-Space Transponder for SLS EM-1 CubeSat Missions

Several key design upgrades have been recently made to the Iris Deep-Space Transponder baselined to be used on secondary payload missions of the upcoming Space Launch System Exploration Mission One (SLS EM-1). The Iris Transponder is a reconfigurable software-defined radio (SDR) designed for missions requiring interoperability with NASA's Deep Space Network (DSN) on X-band frequencies (7.2 GHz uplink, 8.4 GHz downlink). The transponder provides radiometric tracking support with the DSN to provide navigational products for precise orbit determination while performing standard uplink and downlink communications in a CubeSat/SmallSat-applicable package size. The recent hardware changes include a volume reduction of 30% from previous models, with the main transponder unit weighing less than 1.0 kg, while maintaining total ionizing dose (TID) radiation tolerance of >23 krads (Si) for deep-space missions. Lab tests indicate maximum downlink rates of up to 6.25 Msps can be supported by the transponder in conventional BPSK modulation, but most SLS EM-1 CubeSat missions are link-performance limited to less than 256 kbps. A prototype unit of the flight production units has been assembled and various performance and characterization tests are underway. This talk discusses the key design aspects and specifications of the Iris Transponder and presents preliminary results from early testing of the assembled transponder.

Kobayashi, M. Michael↗

Anticipating Technical Expertise and Capability Evolution in Research Communities Using Dynamic Graph Transformers

The ability to anticipate global technical expertise and capability evolution trends is essential for national and global security, especially in safety-critical domains such as nuclear nonproliferation (NN) and rapidly emerging fields like artificial intelligence (AI). Here, in this work, we extend traditional statistical relational learning approaches (e.g., link prediction in collaboration networks) and formulate a problem of anticipating technical expertise and capability evolution using dynamic heterogeneous graph representations. We develop novel capabilities to forecast collaboration patterns, authorship behavior, and technical capability evolution at different granularities (e.g., scientist and institution levels) in two distinct research fields. We implement a dynamic graph transformer (DGT) neural architecture, which pushes the state-of-the-art graph neural network models by: 1) forecasting heterogeneous (rather than homogeneous) nodes and edges; and 2) relying on both discrete- and continuous-time inputs. We demonstrate that our DGT models predict collaboration, partnership, and expertise patterns with 0.26, 0.73, and 0.53 mean reciprocal rank values for AI and 0.48, 0.93, and 0.22 for NN domains. DGT model performance exceeds the best-performing static graph baseline models by 30%–80% across AI and NN domains. Our findings demonstrate that DGT models boost inductive task performance when previously unseen nodes appear in the test data for the domains with emerging collaboration patterns (e.g., AI). Specifically, models accurately predict which established scientists will collaborate with early career scientists and vice versa in the AI domain.

97 MATHEMATICS AND COMPUTING↗

Physical Insights From the Multidecadal Prediction of North Atlantic Sea Surface Temperature Variability Using Explainable Neural Networks

Abstract North Atlantic sea surface temperatures (NASST), particularly in the subpolar region, are among the most predictable in the world's oceans. However, the relative importance of atmospheric and oceanic controls on their variability at multidecadal timescales remain uncertain. Neural networks (NNs) are trained to examine the relative importance of oceanic and atmospheric predictors in predicting the NASST state in the Community Earth System Model 1 (CESM1). In the presence of external forcings, oceanic predictors outperform atmospheric predictors, persistence, and random chance baselines out to 25‐year leadtimes. Layer‐wise relevance propagation is used to unveil the sources of predictability, and reveal that NNs consistently rely upon the Gulf Stream‐North Atlantic Current region for accurate predictions. Additionally, CESM1‐trained NNs successfully predict the phasing of multidecadal variability in an observational data set, suggesting consistency in physical processes driving NASST variability between CESM1 and observations.

Geology↗

InversionNet3D: Efficient and Scalable Learning for 3-D Full-Waveform Inversion

Seismic full-waveform inversion (FWI) techniques aim to find a high-resolution subsurface geophysical model provided with waveform data. Some recent effort in data-driven FWI has shown some encouraging results in obtaining 2-D velocity maps. However, due to high computational complexity and large memory consumption, the reconstruction of 3-D high-resolution velocity maps via deep networks is still a great challenge. Here, in this article, we present InversionNet3D (InvNet3D), an efficient and scalable encoder–decoder network for 3-D FWI. The proposed method employs group convolution in the encoder to establish an effective hierarchy for learning information from multiple sources while cutting down unnecessary parameters and operations at the same time. The introduction of invertible layers further reduces the memory consumption of intermediate features during training and, thus, enables the development of deeper networks with more layers and higher capacity as required by different application scenarios. Experiments on the 3-D Kimberlina dataset demonstrate that InvNet3D achieves state-of-the-art reconstruction performance with lower computational cost and lower memory footprint compared to the baseline.

58 GEOSCIENCES↗

Influence of Process Parameters and Alloy Composition on Crack Mitigation in Selective Laser Melting

Microcracking and residual stresses are key limitations of laser powder bed fusion (LPBF), an additive manufacturing (AM) technique that uses a high power laser to consolidate successive layers of metal powder. For tungsten, these microcracks find their origin in the combination of a ductile-to-brittle transition (DBT) between 200°C and 400°C and high residual stresses. This work utilized in situ high speed video to capture the cracking mechanisms, and combined the experimental results with thermomechanical modeling to unveil correlations between crack network morphology and process parameter-related variables, such as the local temperature and residual stress distributions. Consequently, preheating and alloying with rare earth oxides were adopted as possible crack mitigation strategies, the efficacy of which was tested against the initial fundamental baseline results. Preheating temperatures above 500°C eliminated all cracking, though this threshold is expected to be higher when tungsten powder (higher oxygen content) is introduced. Alloying can serve as an active oxygen getter in the system, but the rare earth oxides in this work were too large to have significant contributions to crack-mitigation.

36 MATERIALS SCIENCE↗

Millimeter wave satellite concepts, volume 1

The identification of technologies necessary for development of millimeter spectrum communication satellites was examined from a system point of view. Development of methodology based on the technical requirements of potential services that might be assigned to millimeter wave bands for identifying the viable and appropriate technologies for future NASA millimeter research and development programs, and testing of this methodology with selected user applications and services were the goals of the program. The entire communications network, both ground and space subsystems was studied. Cost, weight, and performance models for the subsystems, conceptual design for point-to-point and broadcast communications satellites, and analytic relationships between subsystem parameters and an overall link performance are discussed along with baseline conceptual systems, sensitivity studies, model adjustment analyses, identification of critical technologies and their risks, and brief research and development program scenarios for the technologies judged to be moderate or extensive risks. Identification of technologies for millimeter satellite communication systems, and assessment of the relative risks of these technologies, was accomplished through subsystem modeling and link optimization for both point-to-point and broadcast applications.

Hilsen, N. B.↗

Millimeter wave satellite concepts. Volume 1: Executive summary

The objectives of the program were: (1) development of methodology based on the technical requirements of potential services that might be assigned to millimeter wave bands for identifying the viable and appropriate technologies for future NASA millimeter research and development programs, and (2) testing of this methodology with user applications and services. The scope of the program included the entire communications network, both ground and space subsystems. The reports include: (1) cost, weight, and performance models for the subsystems, (2) conceptual design for point-to-point and broadcast communications satellites, (3) analytic relationships between subsystem parameters and an overall link performance, (4) baseline conceptual systems, (5) sensitivity studies, (6) model adjustment analyses, (7) identification of critical technologies and their risks, (8) brief R&D program scenarios for the technologies judged to be moderate or extensive risks.

Hilsen, N. B.↗