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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Spatiotemporal Automatic Calibration of Infrastructure Lidar, Radar, and Camera with a Global Navigation Satellite System: Preprint

Robust and accurate perception is important for modern intelligent transportation systems (ITS), which use sensors of various modalities for data fusion to create a digital twin of an intersection. Sensor calibration is an important process that creates a unified coordinate frame for the sensor output data so that it can be used for data fusion. Classical approaches for sensor calibration are time-consuming, require an overlapping field of view for feature matching, and are not feasible for ITS application as they cause disruptions in the flow of traffic. In this paper, we present a spatiotemporal automatic calibration approach to calibrate multiple infrastructure lidar, radar, and cameras installed at a traffic intersection. The approach uses global navigation satellite system (GNSS) positioning information shared by connected vehicles, and when the vehicle is detected by the sensor, we match the sensor detections with the GNSS coordinates. The proposed algorithm is evaluated with a real-world dataset utilizing detections from two radars, cameras, and lidars with a test vehicle instrumented with a post-processing kinematic (PPK)-corrected GNSS driving past the sensors installed at a four-way traffic intersection. The experimental results show that the proposed automatic calibration approach can achieve the transformation with a root mean squared error of less than 0.5 for radar and lidar and less than 2 for camera detections. The ability to rapidly calibrate sensors not only benefits initial installations, but can also be used for system health monitoring, while utilizing available connected vehicle data to test the real-time sensor fidelity and operational status.

ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1976

Digital image correlation techniques applied to LANDSAT multispectral imagery

The author has identified the following significant results. Automatic image registration and resampling techniques applied to LANDSAT data achieved accuracies, resulting in mean radial displacement errors of less than 0.2 pixel. The process method utilized recursive computational techniques and line-by-line updating on the basis of feedback error signals. Goodness of local feature matching was evaluated through the implementation of a correlation algorithm. An automatic restart allowed the system to derive control point coordinates over a portion of the image and to restart the process, utilizing this new control point information as initial estimates.

Bonrud, L. O.↗
DOE OSTI2022

Corresponding Standard Reference Material Data used in Partial Least Squares Regression Models for Sugar Composition Estimates in Biomass in: Economic Impact of Yield and Composition Variation in Bioenergy Crops: Populus trichocarpa

Corresponding Standard Reference Material Data used in Partial Least Squares Regression Models for Sugar Composition Estimates in Biomass in: Economic Impact of Yield and Composition Variation in Bioenergy Crops: Populus trichocarpa (for corresponding manuscript: DOI: 10.1002/bbb.2148) PDF Files: Images of 1H NMR spectra for neutralized 2-stage acid hydrolysates of 4 NIST Standard Reference Material biomass samples (Monterey Pine 8493, Sugarcane Bagasse 8491, Wheat Straw 8494, and Eastern Cottonwood/Poplar 8492) and 2 Center for Bioenergy Innovation reference biomass samples (Poplar - Populus trichocarpa and Switchgrass - Panicum Virgatum). Suppression of the water peak was achieved using a NOESY-1D with presaturation, a recycle delay of 5 s, and a total of 64 scans. Spectra were acquired at 298 K and processed with automatic phase correction, baseline correction, and chemical shift referencing to TSP-d4. Images show all 1H data from 10 to 1ppm with inset spectra of region of interest (4.0 to 3.1 ppm). Text Files: Spectra for neutralized 2-stage acid hydrolysates of 4 NIST Standard Reference Material biomass samples (Monterey Pine 8493, Sugarcane Bagasse 8491, Wheat Straw 8494, and Eastern Cottonwood/Poplar 8492) and 2 Center for Bioenergy Innovation reference biomass samples (Poplar - Populus trichocarpa and Switchgrass - Panicum Virgatum) were converted into text files for plotting. Files contain 8192 points of raw spectral data from 12.23 to -2.78 ppm. The text file contains 4 columns of data and includes: Point number, Intensity, Hz, and ppm. Xcel Spreadsheet: HPLC measured monomeric sugar concentrations and bucketed 1H NMR data used to build monomeric sugar composition prediction models. Sugar composition in biomass determined from HPLC analyses are given in mg sugar/mg of biomass. Spectral bucketing was performed using Bruker’s AMIX software. Spectra were divided into 0.005 ppm buckets in the region of 3.10– 4.15 ppm for a total of 210 buckets. Headers for the bucketed data are the chemical shift in ppm of the center of the bucket. Bucketed data was used to build partial least squares models for subsequent predictions in The Unscrambler v. 10.5(CAMO A/S, Trondheim, Norway). The formation of methanol during hydrolysis interferes with the quantitative NMR analysis of sugars, so the methanol peak centered at 3.37 ppm and spanning four buckets (3.2925 – 3.2775 ppm) was set to zero for all spectra.

09 BIOMASS FUELS↗
DOE OSTI2014

A scalable approach to solving dense linear algebra problems on hybrid CPU-GPU systems

Aiming to fully exploit the computing power of all CPUs and all graphics processing units (GPUs) on hybrid CPU-GPU systems to solve dense linear algebra problems, in this paper we design a class of heterogeneous tile algorithms to maximize the degree of parallelism, to minimize the communication volume, and to accommodate the heterogeneity between CPUs and GPUs. The new heterogeneous tile algorithms are executed upon our decentralized dynamic scheduling runtime system, which schedules a task graph dynamically and transfers data between compute nodes automatically. The runtime system uses a new distributed task assignment protocol to solve data dependencies between tasks without any coordination between processing units. By overlapping computation and communication through dynamic scheduling, we are able to attain scalable performance for the double-precision Cholesky factorization and QR factorization. Finally, our approach demonstrates a performance comparable to Intel MKL on shared-memory multicore systems and better performance than both vendor (e.g., Intel MKL) and open source libraries (e.g., StarPU) in the following three environments: heterogeneous clusters with GPUs, conventional clusters without GPUs, and shared-memory systems with multiple GPUs.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2001

Aeroelastic Deformation Measurements of Flap, Gap, and Overhang on a Semispan Model

Single-camera, single-view videogrammetry has been used for the first time to determine static aeroelastic deformation of a slotted flap configuration on a semispan model at the National Transonic Facility (NTF). Deformation was determined by comparing wind-off to wind-on spatial data from targets placed on the main element, shroud, and flap of the model. Digitized video images from a camera were recorded and processed to automatically determine target image plane locations that were then corrected for sensor, lens, and frame grabber spatial errors. The videogrammetric technique used for the measurements presented here has been established at NASA facilities as the technique of choice when high-volume static aeroelastic data with minimum impact on data taking is required. However, the primary measurement at the NTF with this technique in the past has been the measurement of the static aeroelastic wing twist of the main wing element on full span models rather than for the measurement of component deformation. Considerations for using the videogrammetric technique for semispan component deformation measurements as well as representative results are presented.

Burner, A. W.↗
NASA NTRS2008

Facilitating Analysis of Multiple Partial Data Streams

Robotic Operations Automation: Mechanisms, Imaging, Navigation report Generation (ROAMING) is a set of computer programs that facilitates and accelerates both tactical and strategic analysis of time-sampled data especially the disparate and often incomplete streams of Mars Explorer Rover (MER) telemetry data described in the immediately preceding article. As used here, tactical refers to the activities over a relatively short time (one Martian day in the original MER application) and strategic refers to a longer time (the entire multi-year MER missions in the original application). Prior to installation, ROAMING must be configured with the types of data of interest, and parsers must be modified to understand the format of the input data (many example parsers are provided, including for general CSV files). Thereafter, new data from multiple disparate sources are automatically resampled into a single common annotated spreadsheet stored in a readable space-separated format, and these data can be processed or plotted at any time scale. Such processing or plotting makes it possible to study not only the details of a particular activity spanning only a few seconds, but also longer-term trends. ROAMING makes it possible to generate mission-wide plots of multiple engineering quantities [e.g., vehicle tilt as in Figure 1(a), motor current, numbers of images] that, heretofore could be found only in thousands of separate files. ROAMING also supports automatic annotation of both images and graphs. In the MER application, labels given to terrain features by rover scientists and engineers are automatically plotted in all received images based on their associated camera models (see Figure 2), times measured in seconds are mapped to Mars local time, and command names or arbitrary time-labeled events can be used to label engineering plots, as in Figure 1(b).

Maimone, Mark W.↗
DOE OSTI2023

Automatic Point Cloud Building Envelope Segmentation (AutoCuBES)

The Auto-CuBES algorithm is based on unsupervised machine learning that automatically labels 3D point cloud data and reduces the time spent in manual segmentation. The algorithm can process high-resolution point clouds and generate a wire-frame building envelope model with a small set of calibration parameters. The algorithm inputs a 3D point cloud generated by commonly available surveying equipment and outputs a wire-frame model of the building envelope. Unsupervised machine learning methods were used to identify facades, windows, and doors while minimizing the number of calibration parameters.

Puente, BryanMaldonado↗
NASA NTRS1970

Computerized spectrum analysis

Automatic spectral data reduction and analysis system consisting of densitometer, analog-digital converter and IBM 1800 process computer with magnetic disk memory

Kylstra, C. D.↗
NASA NTRS1972

Some new techniques for processing remotely obtained images by self-generated spectral masks.

An extension of a new technique that makes possible parallel, simultaneous processing of remotely obtained images is presented. The technique holds out promise for automatic onboard classification of data. The central feature involves the generation of binary masks, directly from the image, based on object reflectance data, that group objects into equivalence classes. These masks, called equivalence class masks, can be used in various logical combinations to isolate classes of objects with a priori known reflectance or radiance signatures. Experimental verification of the technique is furnished for simple scenes. A computational scheme, based on a sequence of integrated irradiance measurements on the image, that makes it possible to identify objects within an equivalence class is suggested.

Stark, H.↗
NASA NTRS1986

Application of laser-velocimetry to the study of the flow around a two-dimensional airfoil

The experimental techniques employed by NASA researchers to obtain a high volume throughput of data in a study of high-lift multielement airfoils using a laser velocimeter (LV) are detailed. The two-dimensional LV system recorded mean velocity, turbulence intensities, Re shear stresses, skewness and kurtosis of the flow. A computer-controlled positioning mount for the LV allowed automated surveys of the flows with a 0.001 in. positioning accuracy. The flow was seeded with oil droplets and additional refinement of the wind tunnel controls permitted rapid speedup at selected areas of the flowfield over specific regions of the airfoil. Surface pressure taps furnished data for selecting regions for more detailed investigation. The data processing capabilities processed 30-40 samples every 10 min in an automated mode. Profiles of the data were computed automatically to furnish graphical displays on demand. Numerous samples of the data displays generated are provided.

Braden, J. A.↗
NASA NTRS1993

Automatic detection of mass-resolved ion conics

A processing algorithm to automatically detect a specific type of ion distribution (called the ion conic distribution) in data obtained from a space-based mass spectrometer has been devised. Automation of this task is necessary due to the sparseness of conic events within the very large databases typical of space plasma instruments. This paper reports on the algorithm used to perform this automated analysis, along with a description of the methods used to verify the algorithm and a summary of initial results on the characterization of the near-earth space plasma.

Doherty, Mark F.↗
NASA NTRS1992

Interactive explorations of hierarchical segmentations

The authors report on the implementation of an interactive tool, called HSEGEXP, to interactively explore the hierarchical segmentation produced by the iterative parallel region growing (IPRG) algorithm to select the best segmentation result. This combination of the HSEGEXP tool with the IPRG algorithm amounts to a computer-assisted image segmentation system guided by human interaction. The initial application of the HSEGEXP tool is in the refinement of ground reference data based on the IPRG/HSEGEXP segmentation of the corresponding remotely sensed image data. The HSEGEXP tool is being used to help evaluate the effectiveness of an automatic 'best' segmentation process under development.

Tilton, James C.↗
NASA NTRS2007

A Web 2.0 and OGC Standards Enabled Sensor Web Architecture for Global Earth Observing System of Systems

This paper will describe the progress of a 3 year research award from the NASA Earth Science Technology Office (ESTO) that began October 1, 2006, in response to a NASA Announcement of Research Opportunity on the topic of sensor webs. The key goal of this research is to prototype an interoperable sensor architecture that will enable interoperability between a heterogeneous set of space-based, Unmanned Aerial System (UAS)-based and ground based sensors. Among the key capabilities being pursued is the ability to automatically discover and task the sensors via the Internet and to automatically discover and assemble the necessary science processing algorithms into workflows in order to transform the sensor data into valuable science products. Our first set of sensor web demonstrations will prototype science products useful in managing wildfires and will use such assets as the Earth Observing 1 spacecraft, managed out of NASA/GSFC, a UASbased instrument, managed out of Ames and some automated ground weather stations, managed by the Forest Service. Also, we are collaborating with some of the other ESTO awardees to expand this demonstration and create synergy between our research efforts. Finally, we are making use of Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) suite of standards and some Web 2.0 capabilities to Beverage emerging technologies and standards. This research will demonstrate and validate a path for rapid, low cost sensor integration, which is not tied to a particular system, and thus be able to absorb new assets in an easily evolvable, coordinated manner. This in turn will help to facilitate the United States contribution to the Global Earth Observation System of Systems (GEOSS), as agreed by the U.S. and 60 other countries at the third Earth Observation Summit held in February of 2005.

Mandl, Daniel↗
NASA NTRS2011

Orthographic Stereo Correlator on the Terrain Model for Apollo Metric Images

A stereo correlation method on the object domain is proposed to generate the accurate and dense Digital Elevation Models (DEMs) from lunar orbital imagery. The NASA Ames Intelligent Robotics Group (IRG) aims to produce high-quality terrain reconstructions of the Moon from Apollo Metric Camera (AMC) data. In particular, IRG makes use of a stereo vision process, the Ames Stereo Pipeline (ASP), to automatically generate DEMs from consecutive AMC image pairs. Given camera parameters of an image pair from bundle adjustment in ASP, a correlation window is defined on the terrain with the predefined surface normal of a post rather than image domain. The squared error of back-projected images on the local terrain is minimized with respect to the post elevation. This single dimensional optimization is solved efficiently and improves the accuracy of the elevation estimate.

Terrain Model↗
NASA NTRS2014

Virtualization - A Key Cost Saver in NASA Multi-Mission Ground System Architecture

With science team budgets being slashed, and a lack of adequate facilities for science payload teams to operate their instruments, there is a strong need for innovative new ground systems that are able to provide necessary levels of capability processing power, system availability and redundancy while maintaining a small footprint in terms of physical space, power utilization and cooling.The ground system architecture being presented is based off of heritage from several other projects currently in development or operations at Goddard, but was designed and built specifically to meet the needs of the Science and Planetary Operations Control Center (SPOCC) as a low-cost payload command, control, planning and analysis operations center. However, this SPOCC architecture was designed to be generic enough to be re-used partially or in whole by other labs and missions (since its inception that has already happened in several cases!)The SPOCC architecture leverages a highly available VMware-based virtualization cluster with shared SAS Direct-Attached Storage (DAS) to provide an extremely high-performing, low-power-utilization and small-footprint compute environment that provides Virtual Machine resources shared among the various tenant missions in the SPOCC. The storage is also expandable, allowing future missions to chain up to 7 additional 2U chassis of storage at an extremely competitive cost if they require additional archive or virtual machine storage space.The software architecture provides a fully-redundant GMSEC-based message bus architecture based on the ActiveMQ middleware to track all health and safety status within the SPOCC ground system. All virtual machines utilize the GMSEC system agents to report system host health over the GMSEC bus, and spacecraft payload health is monitored using the Hammers Integrated Test and Operations System (ITOS) Galaxy Telemetry and Command (TC) system, which performs near-real-time limit checking and data processing on the downlinked data stream and injects messages into the GMSEC bus that are monitored to automatically page the on-call operator or Systems Administrator (SA) when an off-nominal condition is detected. This architecture, like the LTSP thin clients, are shared across all tenant missions.Other required IT security controls are implemented at the ground system level, including physical access controls, logical system-level authentication authorization management, auditing and reporting, network management and a NIST 800-53 FISMA-Moderate IT Security plan Risk Assessment Contingency Plan, helping multiple missions share the cost of compliance with agency-mandated directives.The SPOCC architecture provides science payload control centers and backup mission operations centers with a cost-effective, standardized approach to virtualizing and monitoring resources that were traditionally multiple racks full of physical machines. The increased agility in deploying new virtual systems and thin client workstations can provide significant savings in personnel costs for maintaining the ground system. The cost savings in procurement, power, rack footprint and cooling as well as the shared multi-mission design greatly reduces upfront cost for missions moving into the facility. Overall, the authors hope that this architecture will become a model for how future NASA operations centers are constructed!

Ground System Architecture↗
NASA NTRS2022

Automating Surface Attitude Positioning and Pointing Operations for Mars 2020

The Surface Attitude Positioning and Pointing (SAPP) subsystem of the Mars Perseverance rover keeps track of the rover’s position and attitude on the surface of Mars. The SAPP Downlink Engineering Operations team members receive data from the rover on a daily basis. They must interpret the data to make sure the rover is staying safe and to support uplink planning. The SAPP team keeps track of the error growth in the rover’s attitude estimate due to noise in the Rover Inertial Measurement Unit’s (RIMU) gyroscopes used to propagate that attitude estimate whenever the rover is moving. Whenever this error grows to a particular threshold, SAPP is responsible for updating the onboard attitude knowledge using the RIMU’s accelerometers to estimate rover roll and pitch and sun imaging to estimate rover yaw, thereby reducing this attitude estimation error. Accurate attitude estimation is required so that the rover can successfully point its High Gain Antenna (HGA) to receive information from Earth and as a backup to the Mars orbiters used for sending data from the rover to Earth, point instruments on its Remote Sensing Mast (RSM), and support safe movement and placement of instruments by the rover’s ARM relative to the Martian surface. The Mars 2020 Engineering Operations team has been working to increase the operational efficiency of the mission and eventually move to a five-hour timeline for daily operations. In pursuit of this goal, the SAPP Engineering Operations team has automated their downlink process by developing a centralized Jupyter notebook to analyze the data received daily from the rover. The SAPP downlink Jupyter notebook automatically collects the data relevant to the SAPP subsystem and visualizes this information in plots and tables that can be easily read by downlink operators to aid them in assessing the status of the subsystem. Various Application Programming Interfaces (APIs) have been incorporated into the downlink daily notebook to automate the collection and posting of data, such as gathering and posting data products to the cloud. The SAPP team has also developed a SAPP downlink software library that includes functions to aid the notebook in processing data. In addition to assessing the SAPP subsystem on a daily basis, operators need to assess the long-term trending behavior of the subsystem over time. An automated trending process has been developed to collect information from the daily notebooks in order to plot and analyze that data in a centralized place. These daily and trending processes have expedited the SAPP downlink assessment and laid the groundwork to completely automate the SAPP downlink process so that SAPP operators are unnecessary unless something unexpected occurs. This paper will provide an overview of the functions that the SAPP subsystem carries out on a daily basis, and will then dive into the automations that have been developed for daily and trending downlink assessment. An assessment of the downlink efficiency will be provided, along with a summary of lessons learned and work to go. Finally, the authors will discuss how these types of automated spacecraft health assessments could be more broadly used within mission operations.

Zarifian, Anais↗
NASA NTRS1973

Digital processing of radiographic images

Some techniques are presented and the software documentation for the digital enhancement of radiographs. Both image handling and image processing operations are considered. The image handling operations dealt with are: (1) conversion of format of data from packed to unpacked and vice versa; (2) automatic extraction of image data arrays; (3) transposition and 90 deg rotations of large data arrays; (4) translation of data arrays for registration; and (5) reduction of the dimensions of data arrays by integral factors. Both the frequency and the spatial domain approaches are presented for the design and implementation of the image processing operation. It is shown that spatial domain recursive implementation of filters is much faster than nonrecursive implementations using fast fourier transforms (FFT) for the cases of interest in this work. The recursive implementation of a class of matched filters for enhancing image signal to noise ratio is described. Test patterns are used to illustrate the filtering operations. The application of the techniques to radiographic images of metallic structures is demonstrated through several examples.

Bond, A. D.↗
DOE OSTI2020

Automated Data Review of Analytical Laboratory Results at Los Alamos National Laboratory - 20299

Newport News Nuclear BWXT-Los Alamos, LLC (N3B) collects samples in support of the U.S. Department of Energy's (DOE) Office of Environmental Management (EM) Los Alamos Legacy Cleanup Contract (LLCC). N3B receives and reviews over 1.6 million sample data points annually in support of various ongoing environmental monitoring and remediation projects of the LLCC. N3B must demonstrate and document that reported external analytical laboratory data produced for the LLCC are of sufficient quality to fulfill their intended purpose and to support defensible decision making as described in EPA QA/G4 Guidance for the Data Quality Objectives Process 1994. In 2018, N3B assumed management of the LLCC along with the Environmental Information Management (EIM) database that contains all historical and current environmental data associated with the LLCC. The entire EIM database is shared between N3B, Triad National Security, LLC (Triad), and New Mexico Environment Department (NMED). These three parties jointly manage the database, its configuration, and changes / updates. All environmental data that are entered into EIM are updated and available, on a daily basis, in the linked public database Intellus New Mexico (Intellus). The quality and defensibility of the environmental data generated from sampling activities is a key component of an effective remediation process. Providing quality data is accomplished through a data assessment process that includes examination, verification, and validation. Examination is the assessment of completeness of the deliverables, identification of any reporting errors, and determining the usability of the data based on the laboratory's evaluation of its data as described in the case narrative received with the data. Verification consists of an evaluation of the Electronic Data Deliverables (EDD) data report to determine the extent to which the external analytical laboratories met method and contract-specific quality control and reporting requirements. Validation consists of determining the data quality and the extent to which the external analytical laboratories accurately and completely reported all sample and quality control results and satisfied all contract requirements. EIM contains an automatic Data Validation Module which performs automated data review (DVM ADR). DVM ADR is a tool to assist in the validation process. When DVM ADR is used in conjunction with manual examination of sample data packages, the combination of the two will meet and exceed the requirements of verification. N3B recognized an opportunity for process improvement, focusing on DVM ADR configuration and enhancements in EIM. Testing EIM's configuration provided proof of the DVM ADR's capabilities and flexibility to accurately perform routine data checks based on analytical methods and regulatory requirements. In addition, the DVM ADR module was improved through enhancements for all analytes, particularly upgrades for radiochemistry data. Extensive testing of the DVM ADR module occurred using EDDs from actual laboratory analyses on the EIM testing site. During this process, N3B manipulated EDD information to verify that the actual outcomes matched the expected outcomes. The results of this testing were shared with the database architects, and configuration improvements were identified to address these results. During this process, N3B identified that the radiochemical DVM ADR capabilities were underutilized, and so enhanced the DVM ADR functionality with respect to radioanalytical assessment. N3B environmental data uploads to Intellus on a daily basis from EIM, once the analytical data undergoes examination and verification. As such, it is important to have a high level of confidence in the quality and defensibility of the data. The process of manual examination, along with the DVM ADR, in conjunction with full validation of a percentage the data specified through the Data Quality Objectives greatly increases efficiency of data review and confidence level of the quality of the data, and gives the project managers, governmental offices, and the public expedited access to high-quality data. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗