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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 1,783 records · Page 99
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Autonomous Telemetry Collection for Single-Processor Small Satellites

For the Space Technology 5 mission, which is being developed under NASA's New Millennium Program, a single spacecraft processor will be required to do on-board real-time computations and operations associated with attitude control, up-link and down-link communications, science data processing, solid-state recorder management, power switching and battery charge management, experiment data collection, health and status data collection, etc. Much of the health and status information is in analog form, and each of the analog signals must be routed to the input of an analog-to-digital converter, converted to digital form, and then stored in memory. If the micro-operations of the analog data collection process are implemented in software, the processor may use up a lot of time either waiting for the analog signal to settle, waiting for the analog-to-digital conversion to complete, or servicing a large number of high frequency interrupts. In order to off-load a very busy processor, the collection and digitization of all analog spacecraft health and status data will be done autonomously by a field-programmable gate array that can configure the analog signal chain, control the analog-to-digital converter, and store the converted data in memory.

Speer, Dave↗
NASA NTRS1973

Discrimination techniques employing both reflective and thermal multispectral signals

Recent improvements in remote sensor technology carry implications for data processing. Multispectral line scanners now exist that can collect data simultaneously and in registration in multiple channels at both reflective and thermal (emissive) wavelengths. Progress in dealing with two resultant recognition processing problems is discussed: (1) More channels mean higher processing costs; to combat these costs, a new and faster procedure for selecting subsets of channels has been developed. (2) Differences between thermal and reflective characteristics influence recognition processing; to illustrate the magnitude of these differences, some explanatory calculations are presented. Also introduced, is a different way to process multispectral scanner data, namely, radiation balance mapping and related procedures. Techniques and potentials are discussed and examples presented.

Malila, W. A.↗
DOE OSTI2022

Multi phenomena melt pool sensor data fusion for enhanced process monitoring of laser powder bed fusion additive manufacturing

Finding actionable trends in laser-based metal additive manufacturing process monitoring data is challenging owing to the diversity and complexity of the underlying physical interactions. A single monitoring solution that captures a particular process phenomenon, such as a photodiode that tracks melt pool intensity, is not alone capable of evaluating process stability or detecting flaw formation with sufficient precision for routine application in industry. In this work, to improve flaw detection performance, we adopted a data fusion approach that captures multiple process phenomena. To demonstrate this, we acquired data from laser powder bed fusion (LPBF) builds of cylindrical specimens produced with different laser spot sizes, emulating defocusing due to process faults such as thermal lensing. The resulting specimens had porosity of varying types and severity, quantified by post-build non-destructive X-ray computed tomography, Archimedes density measurements, and destructive metallographic characterization. During the build, the melt pool state was monitored with two coaxial high-speed video cameras and a temperature field imaging system. Physically intuitive low-level melt pool signatures, such as melt pool temperature, shape and size, and spatter intensity were extracted from this high-dimensional, image-based sensor data. These process signatures were subsequently used as input features in relatively simple machine learning models, such as a support vector machine, which were trained to detect laser defocusing, and in addition, predict porosity type and severity. The results show that the data fusion approach significantly enhanced system performance by reducing the overall false positive rate from ~ 0.1 to ~ 0.001 without sacrificing the true positive rate (~0.90). These results were at par with a black-box, deep machine learning approach (convolutional neural network).

36 MATERIALS SCIENCE↗
NASA NTRS2011

Dealing with Processing Chapter 10 Files from Multiple Vendors

This presentation discusses the experiences of the NASA Dryden Flight Research Center's (DFRC) Western Aeronautical Test Range (WATR) in dealing with the problems encountered while performing post flight data processing using the WATR's data collection/processing system on Chapter 10 files from different Chapter 10 recorders. The transition to Chapter 10 recorders has brought Vvith it an assortment of issues that must be addressed: the ambiguities of language in the Chapter 10 standard, the unrealistic near-term expectations of the Chapter 10 standard, the incompatibility of data products generated from Chapter 10 recorders, and the unavailability of mature Chapter 10 applications. Some of these issues properly belong to the users of Chapter 10 recorders, some to the manufacturers, and some to the flight test community at large. The goal of this presentation is to share the WATR's lesson learned in processing data products from various Chapter 10 recorder vendors. The WATR could benefit greatly in the open forum Vvith lessons learned discussions with other members of the flight test community.

Knudtson, Kevin Mark↗
NASA NTRS2016

Kepler: A Search for Terrestrial Planets - Kepler Data Characterization Handbook

The Kepler Data Characteristics Handbook (KDCH) provides a description of all phenomena identified in the Kepler data throughout the mission, and an explanation for how these characteristics are handled by the final version of the Kepler Data Processing Pipeline (SOC 9.3).The KDCH complements the Kepler Data Release Notes (KDRNs), which document phenomena and processing unique to a data release. The original motivation for this separation into static, explanatory text and a more journalistic set of figures and tables in the KDRN was for the user to become familiar with the Data Characteristics Handbook, then peruse the short Notes for a new quarter, referring back to the Handbook when necessary. With the completion of the Kepler mission and the final Data Release 25, both the KDCH and the DRN encompass the entire Kepler mission, so the distinction between them is in the level of exposition, not the extent of the time interval discussed.

Kepler↗
DOE OSTI2019

Methods of resolving artifacts in Hadamard-transformed data

Apparatus and methods are disclosed for processing data transformed according to an invertible transform (e.g., using a Hadamard transform) multiplexing scheme. In one example of the disclosed technology, a computer-implemented method includes generating transformed data by applying a Hadamard transform to intensity data generated by modulating input of analytes into a mass spectrometer according to a pseudorandom sequence (PRS). The exemplary method further includes identifying at least one pair of symmetric intensity peaks in the transformed data based on the PRS and removing data associated with the pair of symmetric peaks from the transformed data to produce modified data, which can be used to identify, characterize, and/or quantify the composition of the sample. In some examples, the exemplary method further includes validating peaks in the transformed data based on comparing the location of peaks in the untransformed intensity data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1999

The Utility and Validity of Kinematic GPS Positioning for the Geosar Airborne Terrain Mapping Radar System

GeoSAR is an airborne, interferometric Synthetic Aperture Radar (IFSAR) system for terrain mapping, currently under development by a consortium including NASA's Jet Propulsion Laboratory (JPL), Calgis, Inc., a California mapping sciences company, and the California Department of Conservation (CaIDOC), with funding provided by the U.S. Army Corps of Engineers Topographic Engineering Center (TEC) and the U.S. Defense Advanced Research Projects Agency (DARPA). IFSAR data processing requires high-accuracy platform position and attitude knowledge. On 9 GeoSAR, these are provided by one or two Honeywell Embedded GPS Inertial Navigation Units (EGI) and an Ashtech Z12 GPS receiver. The EGIs provide real-time high-accuracy attitude and moderate-accuracy position data, while the Ashtech data, post-processed differentially with data from a nearby ground station using Ashtech PNAV software, provide high-accuracy differential GPS positions. These data are optimally combined using a Kalman filter within the GeoSAR motion measurement software, and the resultant position and orientation information are used to process the dual frequency (X-band and P-band) radar data to generate high-accuracy, high -resolution terrain imagery and digital elevation models (DEMs). GeoSAR requirements specify sub-meter level planimetric and vertical accuracies for the resultant DEMS. To achieve this, platform positioning errors well below one meter are needed. The goal of GeoSAR is to obtain 25 cm or better 3-D positions from the GPS systems on board the aircraft. By imaging a set of known point target corner-cube reflectors, the GeoSAR system can be calibrated. This calibration process yields the true position of the aircraft with an uncertainty of 20- 50 cm. This process thus allows an independent assessment of the accuracy of our GPS-based positioning systems. We will present an overview of the GeoSAR motion measurement system, focusing on the use of GPS and the blending of position data from the various systems. We will present the results of our calibration studies that relate to the accuracy the GPS positioning. We will discuss the effects these positioning, errors have on the resultant DEM products and imagery.

Freedman, Adam↗
NASA NTRS2010

RF Device for Acquiring Images of the Human Body

A safe, non-invasive method for forming images through clothing of large groups of people, in order to search for concealed weapons either made of metal or not, has been developed. A millimeter wavelength scanner designed in a unique, ring-shaped configuration can obtain a full 360 image of the body with a resolution of less than a millimeter in only a few seconds. Millimeter waves readily penetrate normal clothing, but are highly reflected by the human body and concealed objects. Millimeter wave signals are nonionizing and are harmless to human tissues when used at low power levels. The imager (see figure) consists of a thin base that supports a small-diameter vertical post about 7 ft (=2.13 m) tall. Attached to the post is a square-shaped ring 2 in. (=5 cm) wide and 3 ft (=91 cm) on a side. The ring is oriented horizontally, and is supported halfway along one side by a connection to a linear bearing on the vertical post. A planar RF circuit board is mounted to the inside of each side of the ring. Each circuit board contains an array of 30 receivers, one transmitter, and digitization electronics. Each array element has a printed-circuit patch antenna coupled to a pair of mixers by a 90 coupler. The mixers receive a reference local oscillator signal to a subharmonic of the transmitter frequency. A single local oscillator line feeds all 30 receivers on the board. The resulting MHz IF signals are amplified and carried to the edge of the board where they are demodulated and digitized. The transmitted signal is derived from the local oscillator at a frequency offset determined by a crystal oscillator. One antenna centrally located on each side of the square ring provides the source illumination power. The total transmitted power is less than 100 mW, resulting in an exposure level that is completely safe to humans. The output signals from all four circuit boards are fed via serial connection to a data processing computer. The computer processes the approximately 1-MB data set into a three-dimensional image in a matter of seconds. The innovation is to configure the receiver array in a ring topology surrounding the scanned object. The ring is then scanned vertically to cover the necessary two-dimensional surface. This fabrication of the ring is made possible by using planar antenna and circuit technology. A planar circuit board serves as a medium for both antennas and signal processing components. Using this technique, parts counts are kept low, and the cost per element is a small fraction of a waveguide-based system.

Gaier, Todd C.↗
NASA NTRS2022

The Mars 2020 Ground Data System Architecture

The Mars 2020 Mission’s primary objective is to collect 20 geographically unique samples during its prime mission of one and a quarter Martian years, or just over 2 Earth years. Mission planners determined the project needed to develop a system that would enable the operations team to analyze engineering and science data, make science decisions, select viable rover targets at a millimeter resolution and validate an uplink bundle for a car sized rover with more complex science instruments than any previous Mars surface mission. All this had to be done within a five hour time frame. Doing this with a small team would be a challenge, but this had to be accomplished by a large team of engineers and scientists located across North America and Europe. Achieving this level of operational efficiency was unheard of in the prime mission. In addition, the mission had another set of requirements that had nothing to do with surface operations; the Mars 2020 Ground Data System (GDS) was also expected to comply with a new set of security requirements to keep up with the ever changing cybersecurity landscape. The Mars 2020 Ground Data System (GDS) is a re-architected version of the Mars Science Laboratory GDS. The primary goal was to integrate the lessons learned from previous Mars surface missions, accommodate a set of new requirements and capabilities required to ensure mission success, and comply with a new set of cybersecurity controls. The new architecture includes several unique qualities including a data lake, language-agnostic system-wide event-based operations, containerization, automated deployment, network segmentation, infrastructure-as-code, API-driven interfaces, and the first Mars surface GDS to operate primarily in the cloud. The new architecture enabled greater access to the system’s data, tighter integration with the operations team, and a higher level of traceability. The availability of the data also enabled a new set of capabilities previously not possible on surface missions. These new capabilities include an autonomous data to information, pipeline for downlink analysis, horizontal scaling of science data processing capabilities, autonomous round trip data tracking of science and engineering data, integration of flight system state into the tactical planning cycle, high fidelity targeting utilizing kinematic data, and hierarchical image and 3d meshes data representations. This paper will introduce the requirements for the Mars 2020 Mission, the heritage architecture, and the rationale for the changes to achieve the new architecture. The paper will continue to describe the fundamental changes made to the GDS architecture, how these changes enabled a more tightly integrated GDS, and the new capabilities that were enabled by the new architecture. The paper will conclude with the lessons learned from the process of rearchitecting a heritage GDS system and from the first 200 days of operations supporting over 800 users from around the world.

Lopez-Roig, Reynaldo↗
NASA NTRS2017

A Overview of New Technologies Driving Innovation in the Airborne Science Community

Following a more than a century of scientific aircraft and ballooning there is a sense that a renaissance of sorts is at hand in the aviation industry. The advent of incredibly miniaturized autopilots, inertial navigation systems, GPS antennae, and payloads has sparked a revolution in manned and unmanned aircraft. Improved SATCOM and onboard computing has enabled realtime data processing and improved transfer of data on and off the aircraft, making flight planning and data collection more efficient and effective. Electric propulsion systems are scaling up to larger and larger vehicles as evidenced by the NASA GL-10, which is leading to a new X-plane and is leading to renewed interest in personal air vehicles. There is also significant private and government investments in the development of High Altitude, Long Endurance (HALE) aircraft. This presentation will explore how such developments are likely to improve our ability to observe earth systems processes from aircraft by providing an overview of current NASA Airborne Science capabilities, followed by a brief discussion of new technologies being applied to Airborne Science missions, and then conclude with an overview of new capabilities on the horizon that are likely to be of interest to the Earth Science community.

airborne science↗
NASA NTRS2017

An Overview of New Technologies Driving Innovation in the Airborne Science Community

Following a more than a century of scientific aircraft and ballooning there is a sense that a renaissance of sorts is at hand in the aviation industry. The advent of incredibly miniaturized autopilots, inertial navigation systems, GPS antennae, and payloads has sparked a revolution in manned and unmanned aircraft. Improved SATCOM and onboard computing has enabled realtime data processing and improved transfer of data on and off the aircraft, making flight planning and data collection more efficient and effective. Electric propulsion systems are scaling up to larger and larger vehicles as evidenced by the NASA GL-10, which is leading to a new X-plane and is leading to renewed interest in personal air vehicles. There is also significant private and government investments in the development of High Altitude, Long Endurance (HALE) aircraft. This presentation will explore how such developments are likely to improve our ability to observe earth systems processes from aircraft by providing an overview of current NASA Airborne Science capabilities, followed by a brief discussion of new technologies being applied to Airborne Science missions, and then conclude with an overview of new capabilities on the horizon that are likely to be of interest to the Earth Science community.

airborne science↗
NASA NTRS2019

GeneLab: A Systems Biology Platform for Omics Analysis

NASA GeneLab is an open-access repository for omics datasets generated by biological experiments conducted in space or experiments relevant to spaceflight (e.g. simulated cosmic radiation, simulated microgravity, bed rest studies). The GeneLab Data Systems (GLDS) version 4.0 will be available on October 1st 2019, and will provide the latest in terms of professional state-of-the-art bioinformatics platform for the space biology and radiation community to upload their data into an omics data commons, to process their data with vetted standard workflows and to compare to existing analyses. Started in 2015 as a repository designed to archive omics data from space experiments, GeneLab has expanded its scope to all ionizing radiation omics experiments conducted on the ground and has put considerable effort in providing carefully characterized radiation metadata on all dataset. GeneLab is also providing processed data derived from the raw data covering a large spectrum of omics (genome, epigenome, transcriptome, epitranscriptome, proteome, metabolome) to help users explore important questions: 1) Which genes or proteins are expressed differently in space for various living organisms? 2) What specific DNA mutations or epigenetic changes happen in space or after exposure to ionizing radiation? and 3) How does genetics affect these responses? Processed data available on GeneLab are derived by standard data analysis workflows vetted by hundreds of scientists who volunteered to join one of the four GeneLab Analysis Working Groups (Animal AWG, Plant AWG, Microbe AWG, Multi-Omics AWG). In this presentation, we will discuss how to bridge the gap between irradiation studies performed on earth and biological experiments conducted in space since the early 1990's. We will discuss how radiation dosimetry was estimated for datasets derived from samples collected during the Space Shuttle era or on the International Space Station. Finally, we will address future strategies regarding dose monitoring in future missions into space, inter-agency efforts to unify data under one umbrella, and knowledge dissemination across the radiation research community and the space biology community.

open-science↗
NASA NTRS2019

NASA GeneLab Space Omics Database: Expanding from Space to Ionizing Radiation Data on the Ground

NASA GeneLab is an open-access repository for omics datasets generated by biological experiments conducted in space or ground experiments relevant to spaceflight (e.g. simulated cosmic radiation, simulated microgravity, bed rest studies). The GeneLab Data Systems (GLDS) version 4.0 will be available on October 1st 2019, and will provide a state-of-the-art bioinformatics platform for the space biology and radiation communities to upload their data into an omics data commons, to process their data with vetted standard workflows and to compare with existing analyses. Started in 2015 as a repository designed to archive omics data from space experiments, GeneLab has expanded its scope to all ionizing radiation omics experiments conducted on the ground and has put considerable effort in providing carefully characterized radiation metadata on all datasets. GeneLab is also providing processed data derived from the raw data covering a large spectrum of omics (genome, epigenome, transcriptome, epitranscriptome, proteome, metabolome) to help users explore important questions: 1) Which genes or proteins are expressed differently in space for various living organisms? 2) What specific DNA mutations or epigenetic changes happen in space or after exposure to ionizing radiation? and 3) How does genetics affect these responses? Processed data available on GeneLab are derived by standard data analysis workflows vetted by hundreds of scientists who volunteered to join one of the four GeneLab Analysis Working Groups (Animal AWG, Plant AWG, Microbe AWG, Multi-Omics AWG). In this presentation, we will discuss how to bridge the gap between irradiation studies performed on earth and biological experiments conducted in space since the early 1990's. We will discuss how radiation dosimetry was estimated for datasets derived from samples collected during the Space Shuttle era on the International Space Station and on other orbiting platforms. Finally, we will address future strategies regarding dose monitoring in future missions into space, inter-agency efforts to unify data under one umbrella, and knowledge dissemination across the radiation research community and the space biology community.

open-science↗
NASA NTRS2018

An Integrated Platform for Mission Performance: Goddard Space Flight Center's Meta Information System

Successful management of NASA Goddard Space Flight Centers portfolio of mission projects (i.e. spacecraft, spacecraft instruments / subsystems, and ground systems) depends upon numerous processes, data and information resources coming together throughout the life-cycle of the projects to enable sound decision-making, risk reduction, conformance with requirements and continual improvement. In the summer of 2012, GSFC SMA management recognized that the set of legacy data systems used to support the SMA mission and responsibilities at GSFC were not effective, integrated nor on par with best practices. Accordingly, GSFC SMA management launched a project to transform the GSFC electronic management system to create and deploy an integrated, state-of-the-market information system for process performance, data management and analytics that is currently operating in support of GSFC overall mission performance. The information system, known as Meta, provides controlled, process-based applications, integrated data management, and analytics for a robust set of integrated applications. Since the inception of the project, a lean, award-winning SMA project team has thus far designed, configured and managed the system to serve as an integrated platform for 18 applications that support key processes for GSFC and the Science Mission Directorate at NASA headquarters, such as internal Management System assessments, Supplier Assessments, Supplier Research & Analysis, Problem Reporting for in-house mission projects, On-orbit Anomaly Reporting for GSFC-operated spacecraft, GSFC Project Life-Cycle Reviews, Risk Management and Reporting, and SMA Project Team Reporting. The system has experienced steady growth in utilization with 1,917 users (NASA employees and support contractor personnel) and 44 gigabytes of data and related files managed by the system as of the end of April 2018. Overall, Meta has achieved increasing levels of process management and real-time data / information integration to enable improved process performance, richer analytics and informed decision-making. This paper will present and examine the need, goals, approach and design driving the management and operation of the Meta information system and its ongoing growth as an integrated platform for advancing NASA mission performance.

Integration↗
DOE OSTI2020

Frost Table Elevation across a Low-Centered and a High-Centered Polygon, Mapped using Ground Penetrating Radar, Utqiagvik (Barrow), Alaska, 2015

Ground Penetrating Radar, active layer thickness point measurements, and ground elevation surveys were conducted on a low-centered and a high-centered polygon in Utqiagvik (Barrow), AK (on October 2nd, 2015) to map frost table topography and evaluate its influence on hydrological flow. Data were collected to improve our understanding of the topography of the permafrost table across polygons which may have a major influence on hydrology. This dataset includes 2 zip files containing the raw data, 2 csv files of processed data, and a pdf user guide.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1982

An experimental search for near-wall boundary conditions for large eddy simulation

Instantaneous wall shear stress and streamwise velocities have been measured simultaneously in a flat plate, turbulent boundary layer at moderate Reynolds number in an effort to provide experimental support for large eddy simulations. Data were obtained by using a buried-wire wall shear gage and a hot-wire rake positioned in the log region of the flow. All data processing was accomplished with digital data analysis techniques on a minicomputer. Fluctuations of the instantaneous U plus versus Y plus profiles about a mean law of the wall are shown to be significant and complex. Peak cross-correlation values between wall shear stress and the velocities are high and reflect the passage of a large structure inclined at a small angle to the wall. Estimates of this angle are consistent with those made by other investigators. Conditional sampling techniques were used to detect the passage of various sizes and types of flow disturbances (events) and to estimate their mean frequency of occurrence. Events characterized by large and sudden streamwise accelerations were found to be highly coherent throughout the log region and were strongly correlated with large fluctuations in wall shear-stress. Phase randomness between the near-wall quantities and the outer velocities was small. The results suggest that the flow events detected by conditional sampling applied to velocities in the log region may be related to the bursting process.

Robinson, S. K.↗
DOE OSTI2023

Secure Data Logging and Processing with Blockchain and Machine Learning (Final Report)

Secure Data Logging and Processing with Blockchain and Machine Learning (ML) research is focused on the development of a platform to securely log and process sensor data in fossil power plants. The platform integrates two emerging technologies, blockchain and ML, and incorporates several innovative mechanisms to ensure the integrity, reliability, and resiliency of power systems. The goal is to protect the power plant from various cyberattacks such as false data injection and denial of service attacks using these technologies. The research goal was enabled by the following Research Project Objectives: 1) Secure authentication and identity verification of sensor nodes, actuators, and other equipment within a network. 2) Development of mechanisms that ensure only data sent by legitimate sensors are accepted and stored in the data repository. 3) Development of data aggregation methodologies using ML / Deep Learning (DL) algorithms to minimize noise / faulty data. 4) Implementation of the blockchain technologies to provide data security using secured IOTA framework & nodes.

20 FOSSIL-FUELED POWER PLANTS↗