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

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At least 973 records · Page 54

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Visual Brick model authoring tool for building metadata standardization

In this study, the Brick ontology is a unified semantic metadata standard for building assets and their relationships, serving as a key enabler for effective interoperability and automation of building systems and analytics. However, creating a Brick model, in other words, standard semantic metadata based on the Brick ontology for a building dataset, can be a complex task. This paper presents two case studies of the creation of Brick models for real-world residential and commercial building datasets, highlighting the challenges during the Brick model creation process. Additionally, the paper introduces VizBrick, an interactive authoring tool for creating semantic building metadata. VizBrick facilitates the creation of Brick models by providing an intuitive visual interface and interactive capabilities, such as keyword search, automatic mapping suggestions, and recommendations. The use of VizBrick is shown to significantly reduce the time and effort required during the Brick model creation process.

42 ENGINEERING↗

DOE OSTI2024

GlideinBenchmark: collecting resource information to optimize provisioning

Choosing the right resource can speedup jobs completion, better utilize the available hardware and visibly reduce costs, especially when renting computers on the cloud. This was demonstrated in earlier studies on HEPCloud. But the benchmarking of the resources proved to be a laborious and time-consuming process. This paper presents GlideinBenchmark, a new Web application leveraging the pilot infrastructure of GlideinWMS to benchmark resources, and shows how to use the data collected and published by GlideinBenchmark to automate the optimal selection of resources. An experiment can select the benchmark or the set of benchmarks that most closely evaluate the performance of its workflows. With GlideinBenchmark and the help of the GldieinWMS Factory it controls the benchmark execution. Finally, a scheduler like HEPCloud’s Decision Engine can use the results to optimize resource provisioning.

Mambelli, Marco↗

DOE OSTI2025

ARMing the Edge: Demonstration of Edge Computing Field Campaign Report

Edge computing enables “next-to-instrument” control and intelligent data volume reduction and the potential for autonomous, adaptive measurement strategies such as for automated control of scan strategies for Doppler lidar (DL). Instruments with narrow bandwidth connections (e.g., ship and remote sites) can do scene determination and save phenomenon-appropriate data. For example, Doppler spectrum can be saved when clouds are detected by the instrument or automatic moment detection can take place in camera images and only preserve spectrum when non-monomodal spectra are detected. Automated control at the edge involves changing the sampling (temporal or scanning strategy) of an instrument to suit the phenomena both present and being studied (Jackson et al. 2020). Both data processing and instrument control introduces the possibility of a software-defined instrument.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1976

OAST Space Theme Workshop. Volume 3: Working group summary. 2: Data handling, communications (E-2). A. Statement. B. Technology needs (form 1). C. Priority assessment (form 2)

Technologies required to support the stated OAST thrust to increase information return by X1000, while reducing costs by a factor of 10 are identified. The most significant driver is the need for an overall end-to-end data system management technology. Maximum use of LSI component technology and trade-offs between hardware and software are manifest in most all considerations of technology needs. By far, the greatest need for data handling technology was identified for the space Exploration and Global Services themes. Major advances are needed in NASA's ability to provide cost effective mass reduction of space data, and automated assessment of earth looking imagery, with a concomitant reduction in cost per useful bit. A combined approach embodying end-to-end system analysis, with onboard data set selection, onboard data processing, highly parallel image processing (both ground and space), low cost, high capacity memories, and low cost user data distribution systems would be necessary.

Source record↗

NASA NTRS1978

Monitoring gypsy moth defoliation by applying change detection techniques to Landsat imagery

The overall objective of a research effort at NASA's Goddard Space Flight Center is to develop and evaluate digital image processing techniques that will facilitate the assessment of the intensity and spatial distribution of forest insect damage in Northeastern U.S. forests using remotely sensed data from Landsats 1, 2 and C. Automated change detection techniques are presently being investigated as a method of isolating the areas of change in the forest canopy resulting from pest outbreaks. In order to follow the change detection approach, Landsat scene correction and overlay capabilities are utilized to provide multispectral/multitemporal image files of 'defoliation' and 'nondefoliation' forest stand conditions.

Williams, D. L.↗

NASA NTRS1979

Methodology for error analysis and simulation of lidar aerosol measurements

A methodology is presented for objective and automated determination of the uncertainty in lidar aerosol measurements. This methodology is based on standard error-propagation procedures, a large data base on atmospheric behavior, and long experience in lidar data processing. Algebraic expressions for probable error are derived as a function of the relevant parameters. The validity of these expressions is then tested by making simulated measurements and analyses in which random errors of appropriate size are injected at proper steps of the measurement and analysis process. An illustrative example is given where the methodology is applied to a new lidar system now being used for airborne measurements of the stratospheric aerosol.

Russell, P. B.↗

NASA NTRS1983

Satellite freeze forecast system: Executive summary

A satellite-based temperature monitoring and prediction system consisting of a computer controlled acquisition, processing, and display system and the ten automated weather stations called by that computer was developed and transferred to the national weather service. This satellite freeze forecasting system (SFFS) acquires satellite data from either one of two sources, surface data from 10 sites, displays the observed data in the form of color-coded thermal maps and in tables of automated weather station temperatures, computes predicted thermal maps when requested and displays such maps either automatically or manually, archives the data acquired, and makes comparisons with historical data. Except for the last function, SFFS handles these tasks in a highly automated fashion if the user so directs. The predicted thermal maps are the result of two models, one a physical energy budget of the soil and atmosphere interface and the other a statistical relationship between the sites at which the physical model predicts temperatures and each of the pixels of the satellite thermal map.

Martsolf, J. D.↗

NASA NTRS1985

The star system: A production engineering approach to STS

A fundamental change to the way Space Transportation System flight preparation is done is documented. It involves (1) systematic restructuring the Space Transportation System flight preparation task, to minimize its R&D content; (2) development of the Space Transportation Automated Reconfiguration (STAR) system to structure and support the remaining work flow. STAR is an integrated software system providing automation and quality control mechanisms necessary to create a production-like process. This approach was implemented using tools and methodology developed by IBM under NASA contract, to produce payload flight data requirements. It offers increased product quality, reduced cost per flight, and greater responsiveness to change.

Angier, R. C.↗

NASA NTRS1986

Transportability, distributability and rehosting experience with a kernel operating system interface set

For the past two years, PRC has been transporting and installing a software engineering environment framework, the Automated Product control Environment (APCE), at a number of PRC and government sites on a variety of different hardware. The APCE was designed using a layered architecture which is based on a standardized set of interfaces to host system services. This interface set called the APCE Interface Set (AIS), was designed to support many of the same goals as the Common Ada Programming Support Environment (APSE) Interface Set (CAIS). The APCE was developed to provide support for the full software lifecycle. Specific requirements of the APCE design included: automation of labor intensive administrative and logistical tasks: freedom for project team members to use existing tools: maximum transportability for APCE programs, interoperability of APCE database data, and distributability of both processes and data: and maximum performance on a wide variety of operating systems. A brief description is given of the APCE and AIS, a comparison of the AIS and CAIS both in terms of functionality and of philosophy and approach and a presentation of PRC's experience in rehosting AIS and transporting APCE programs and project data. Conclusions are drawn from this experience with respect to both the CAIS efforts and Space Station plans.

Blumberg, F. C.↗

NASA NTRS1993

Optimization of knowledge-based systems and expert system building tools

The objectives of the NASA-AMES Cooperative Agreement were to investigate, develop, and evaluate, via test cases, the system parameters and processing algorithms that constrain the overall performance of the Information Sciences Division's Artificial Intelligence Research Facility. Written reports covering various aspects of the grant were submitted to the co-investigators for the grant. Research studies concentrated on the field of artificial intelligence knowledge-based systems technology. Activities included the following areas: (1) AI training classes; (2) merging optical and digital processing; (3) science experiment remote coaching; (4) SSF data management system tests; (5) computer integrated documentation project; (6) conservation of design knowledge project; (7) project management calendar and reporting system; (8) automation and robotics technology assessment; (9) advanced computer architectures and operating systems; and (10) honors program.

Yasuda, Phyllis↗

NASA NTRS2005

The Optimization of Trained and Untrained Image Classification Algorithms for Use on Large Spatial Datasets

The HARVIST project seeks to automatically provide an accurate, interactive interface to predict crop yield over the entire United States. In order to accomplish this goal, large images must be quickly and automatically classified by crop type. Current trained and untrained classification algorithms, while accurate, are highly inefficient when operating on large datasets. This project sought to develop new variants of two standard trained and untrained classification algorithms that are optimized to take advantage of the spatial nature of image data. The first algorithm, harvist-cluster, utilizes divide-and-conquer techniques to precluster an image in the hopes of increasing overall clustering speed. The second algorithm, harvistSVM, utilizes support vector machines (SVMs), a type of trained classifier. It seeks to increase classification speed by applying a "meta-SVM" to a quick (but inaccurate) SVM to approximate a slower, yet more accurate, SVM. Speedups were achieved by tuning the algorithm to quickly identify when the quick SVM was incorrect, and then reclassifying low-confidence pixels as necessary. Comparing the classification speeds of both algorithms to known baselines showed a slight speedup for large values of k (the number of clusters) for harvist-cluster, and a significant speedup for harvistSVM. Future work aims to automate the parameter tuning process required for harvistSVM, and further improve classification accuracy and speed. Additionally, this research will move documents created in Canvas into ArcGIS. The launch of the Mars Reconnaissance Orbiter (MRO) will provide a wealth of image data such as global maps of Martian weather and high resolution global images of Mars. The ability to store this new data in a georeferenced format will support future Mars missions by providing data for landing site selection and the search for water on Mars.

Kocurek, Michael J.↗

NASA NTRS2016

Digital Image Correlation for Performance Monitoring

Evaluating the health of a mechanism requires more than just a binary evaluation of whether an operation was completed. It requires analyzing more comprehensive, full-field data. Health monitoring is a process of non-destructively identifying characteristics that indicate the fitness of an engineered component. In order to monitor unit health in a production setting, an automated test system must be created to capture the motion of mechanism parts in a real-time and non-intrusive manner. One way to accomplish this is by using high-speed video and Digital Image Correlation (DIC). In this approach, individual frames of the video are analyzed to track the motion of mechanism components. The derived performance metrics allow for state-of-health monitoring and improved fidelity of mechanism modeling. The results are in-situ state-of-health identification and performance prediction. This paper introduces basic concepts of this test method, and discusses two main themes: the use of laser marking to add fiducial patterns to mechanism components, and new software developed to track objects with complex shapes, even as they move behind obstructions. Finally, the implementation of these tests into an automated tester is discussed.

Palaviccini, Miguel↗

DOE OSTI2023

Label Assist: Personalized Travel Models for Longitudinal Data Collection

Understanding travel behavior is crucial to transportation decarbonization. OpenPATH is an open-source mobility platform which collects and analyzes human travel behavior at the individual level. The mobile application passively senses trips and prompts users to label them. However, users find the labeling process burdensome; less than half the trips are typically labeled, making much of the data unusable in aggregate analyses of mobility patterns. Prior work has addressed the response fatigue challenge through automated mode inference using sensor data, but sensors cannot capture all aspects of travel behavior. We explore an alternative approach in which we leverage prior user input to predict travel choices in novel trips. We first explore trip clustering methods and develop a novel two-step pipeline using DBSCAN and SVMs to extract realistic geospatial clusters. We then propose two strategies to predict trip labels: (i) clustering trips and extrapolating labels for similar trips, and (ii) random forest classification. The random forest approach is able to achieve - $70-80% accuracy (purpose: 72%, mode: 79%, replaced mode: 81%). These novel approaches to trip classification allow us to increase the rate of user labeling by suggesting predicted labels to be verified by the user. Unlabeled trips can also contribute to aggregate analyses, using label predictions and their associated confidences as a substitute. While there exist other travel survey apps with the ability to infer travel choices, to our knowledge, this is the first paper to describe such a supervised system and rigorously evaluate it.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

NASA NTRS1988

Engineering planetary lasers for interstellar communication

Transmitting large amounts of data efficiently among neighboring stars will vitally support any eventual contact with extrasolar intelligence, whether alien or human. Laser carriers are particularly suitable for high-quality, targeted links. Space laser transmitter systems designed by this work, based on both demonstrated and imminent advanced space technology, could achieve reliable data transfer rates as high as 1 kb/s to matched receivers as far away as 25 pc, a distance including over 700 approximately solar-type stars. The centerpiece of this demonstration study is a fleet of automated spacecraft incorporating adaptive neural-net optical processing active structures, nuclear electric power plants, annular momentum control devices, and ion propulsion. Together the craft sustain, condition, modulate, and direct to stellar targets an infrared laser beam extracted from the natural mesospheric, solar-pumped, stimulated CO2 emission recently discovered at Venus. For a culture already supported by mature interplanetary industry, the cost of building planetary or high-power space laser systems for interstellar communication would be marginal, making such projects relevant for the next human century. Links using high-power lasers might support data transfer rates as high as optical frequencies could ever allow. A nanotechnological society such as we might become would inevitably use 10 to the 20th power b/yr transmission to promote its own evolutionary expansion out of the galaxy.

Sherwood, Brent↗

DOE OSTI2022

Automated detection of mild cognitive impairment and dementia from voice recordings: A natural language processing approach

Automated computational assessment of neuropsychological tests would enable widespread, cost-effective screening for dementia. A novel natural language processing approach is developed and validated to identify different stages of dementia based on automated transcription of digital voice recordings of subjects’ neuropsychological tests conducted by the Framingham Heart Study (n = 1084). Transcribed sentences from the test were encoded into quantitative data and several models were trained and tested using these data and the participants’ demographic characteristics. Average area under the curve (AUC) on the held-out test data reached 92.6%, 88.0%, and 74.4% for differentiating Normal cognition from Dementia, Normal or Mild Cognitive Impairment (MCI) from Dementia, and Normal from MCI, respectively. The proposed approach offers a fully automated identification of MCI and dementia based on a recorded neuropsychological test, providing an opportunity to develop a remote screening tool that could be adapted easily to any language.

neuropsychological↗

NASA NTRS1994

Split mandrel versus split sleeve coldworking: Dual methods for extending the fatigue life of metal structures

It is common practice to use split sleeve coldworking of fastener holes as a means of extending the fatigue life of metal structures. In search of lower manufacturing costs, the aerospace industry is examining the split mandrel (sleeveless) coldworking process as an alternative method of coldworking fastener holes in metal structures. The split mandrel process (SpM) significantly extends the fatigue life of metal structures through the introduction of a residual compressive stress in a manner that is very similar to the split sleeve system (SpSl). Since the split mandrel process is significantly less expensive than the split sleeve process and more adaptable to robotic automation, it will have a notable influence upon other new manufacture of metal structures which require coldworking a significant number of holes, provided the aerospace community recognizes that the resulting residual stress distributions and fatigue life improvement are the same for both processes. Considerable testing has validated the correctness of that conclusion. The findings presented in this paper represent the results of an extensive research and development program, comprising data collected from over 400 specimens fabricated from 2024-T3 and 7075-T651 aluminum alloys in varied configurations, which quantify the benefits (fatigue enhancement and cost savings) of automating a sleeveless coldworking system.

Rodman, Geoffrey A.↗

NASA NTRS2017

Medical Data Architecture Project Status

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically-relevant information to support medical operations during exploration missions. This gap identifies that the current International Space Station (ISS) medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable an increasingly autonomous crew than the current ISS paradigm. The MDA will develop capabilities that support automated data collection, and the necessary functionality and challenges in executing a self-contained medical system that approaches crew health care delivery without assistance from ground support.To attain this goal, the first year of the MDA project focused on reducing technical risk, developing documentation and instituting iterative development processes that established the basis for the first version of MDA software (or Test Bed 1). Test Bed 1 is based on a nominal operations scenario authored by the ExMC Element Scientist. This narrative was decomposed into a Concept of Operations that formed the basis for Test Bed 1 requirements. These requirements were successfully vetted through the MDA Test Bed 1 System Requirements Review, which permitted the MDA project to begin software code development and component integration. This paper highlights the MDA objectives, development processes, and accomplishments, and identifies the fiscal year 2017 milestones and deliverables in the upcoming year.

Exploration medical system↗

DOE OSTI2020

Automated Identification of Molecular Crystals’ Packing Motifs

Packing motifs—patterns in how molecules orient relative to one another in a crystal structure—are an important concept in many subdisciplines of materials science because of correlations observed between specific packing motifs and properties of interest. That said, packing motif data sets have remained small and noisy due to intensive manual labeling processes and insufficient labeling schemes. The most prominent labeling algorithms calculate relative interplanar angles of nearest neighbor molecules to determine the packing motif of a molecular crystal, but this simple approach can fail when neighbors are naively sampled isotropically around the crystal structure. To remedy this issue, here we propose an optimization algorithm, which rotates the molecular crystal structure to find representative molecules that inform the packing motif. We package this algorithm into an automated framework—Autopack—which both optimally rotates the crystal structure and labels the packing motif based on the appropriate neighboring molecules. In this work, we detail the Autopack framework and its performance, which shows improvements compared to previous state-of-the-art labeling methods, providing the first quantitative point of comparison for packing motif labeling algorithms. Furthermore, using Autopack (available at https://ipo.llnl.gov/technologies/software/autopack), we perform the first large-scale study of potential relationships between chemicals’ compositions and packing motifs, which shows that these relationships are more complex than previously hypothesized from studies that used only tens of polycyclic aromatic hydrocarbon molecules. Autopack’s capabilities help pose next steps for crystal engineering research focusing not only on a molecule’s adoption of a specific packing motif but also on new structure–property relationships.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗