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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

First Results of Venus Express Spacecraft Observations with Wettzell

The ESA Venus Express spacecraft was observed at X-band with the Wettzell radio telescope in October-December 2009 in the framework of an assessment study of the possible contribution of the European VLBI Network to the upcoming ESA deep space missions. A major goal of these observations was to develop and test the scheduling, data capture, transfer, processing, and analysis pipeline. Recorded data were transferred from Wettzell to Metsahovi for processing, and the processed data were sent from Mets ahovi to JIVE for analysis. A turnover time of 24 hours from observations to analysis results was achieved. The high dynamic range of the detections allowed us to achieve a milliHz level of spectral resolution accuracy and to extract the phase of the spacecraft signal carrier line. Several physical parameters can be determined from these observational results with more observational data collected. Among other important results, the measured phase fluctuations of the carrier line at different time scales can be used to determine the influence of the solar wind plasma density fluctuations on the accuracy of the astrometric VLBI observations.

Calves, Guifre Molera↗
NASA NTRS2012

Rapid and Reliable Damage Proxy Map from InSAR Coherence

Future radar satellites will visit SoCal within a day after a disaster event. Data acquisition latency in 2015-2020 is 8 to approx. 15 hours. Data transfer latency that often involves human/agency intervention far exceeds the data acquisition latency. Need interagency cooperation to establish automatic pipeline for data transfer. The algorithm is tested with ALOS PALSAR data of Pasadena, California. Quantitative quality assessment is being pursued: Meeting with Pasadena City Hall computer engineers for a complete list of demolition/construction project 1. Estimate the probability of detection and probability of false alarm 2. Estimate the optimal threshold value.

InSAR↗
NASA NTRS2003

Thermal Performance Testing Of Cryogenic Piping Systems

Thermal performance measurement of piping systems under actual field conditions is important for space launch development and commercial industry. Knowledge of the true insulating effectiveness is needed in system design, development, and research activities. A new 18-meter-long test apparatus for cryogenic pipelines has been developed. Three different pipelines, rigid or flexible, can be tested simultaneously. Critical factors in heat leak measurements include eliminating heat transfer at end connections and obtaining proper liquid saturation condition. Effects due to variations in the external ambient conditions like wind, humidity, and solar radiation must be minimized. The static method of liquid nitrogen evaporation has been demonstrated, but the apparatus can be adapted for dynamic testing with cryogens, chilled water, or other working fluids. This technology is suited for the development of an industry standard test apparatus and method. Examples of the heat transfer data from testing commercially available pipelines are given. Prototype pipelines are currently being tested and evaluated at the Cryogenics Test Laboratory of NASA Kennedy Space Center.

Fesmire, J. E.↗
NASA NTRSDate not supplied

Improving Sim-to-Real Transfer in Vision-Based Robot Navigation Via Instance-Level GAN-Based Data Augmentation

Achieving robust vision-based robotic tasks requires large amounts of data, which are often difficult to obtain in real-world scenarios. Simulators and synthetic data offer a cost-effective alternative, but the visual gap between simulation and reality hinders the performance of models when deployed in real-world environments. In this paper, we present a data augmentation pipeline that integrates a foundation model (Segment Anything Model) with an unsupervised image-to-image translation model (CycleGAN) for instance-level domain transfer from simulation to reality. This pipeline enables the generation of realistic labeled data from synthetic images for training supervised machine learning models in vision-based navigation tasks. We evaluate our approach on real-world data for ego-vehicle pose estimation, a critical autonomous navigation task involving the prediction of cross-track position and heading angle relative to road center line markings. The results of our tests show that our GAN-based data augmentation pipeline significantly outperforms models trained solely on simulation data or on data processed with standard image augmentation methods for sim-to-real transfer, enhancing model robustness and generalizability in real-world scenarios. Our method provides a scalable and flexible data augmentation tool for leveraging large synthetic datasets to enhance vision-based robotic navigation tasks.

artificial intelligence↗
NASA NTRS2013

The Hopkins Ultraviolet Telescope: The Final Archive

The Hopkins Ultraviolet Telescope (HUT) was a 0.9 m telescope and moderate-resolution (Delta)lambda equals 3 A) far-ultraviolet (820-1850 Å) spectrograph that flew twice on the space shuttle, in 1990 December (Astro-1, STS-35) and 1995 March (Astro-2, STS-67). The resulting spectra were originally archived in a nonstandard format that lacked important descriptive metadata. To increase their utility, we have modified the original datareduction software to produce a new and more user-friendly data product, a time-tagged photon list similar in format to the Intermediate Data Files (IDFs) produced by the Far Ultraviolet Spectroscopic Explorer calibration pipeline. We have transferred all relevant pointing and instrument-status information from locally-archived science and engineering databases into new FITS header keywords for each data set. Using this new pipeline, we have reprocessed the entire HUT archive from both missions, producing a new set of calibrated spectral products in a modern FITS format that is fully compliant with Virtual Observatory requirements. For each exposure, we have generated quicklook plots of the fully-calibrated spectrum and associated pointing history information. Finally, we have retrieved from our archives HUT TV guider images, which provide information on aperture positioning relative to guide stars, and converted them into FITS-format image files. All of these new data products are available in the new HUT section of the Mikulski Archive for Space Telescopes (MAST), along with historical and reference documents from both missions. In this article, we document the improved data-processing steps applied to the data and show examples of the new data products.

Hopkins↗
NASA NTRS1990

A bit-serial VLSI array processing chip for image processing

An array processing chip integrating 128 bit-serial processing elements (PEs) on a single die is discussed. Each PE has a 16-function logic unit, a single-bit adder, a 32-b variable-length shift register, and 1 kb of local RAM. Logic in each PE provides the capability to mask PEs individually. A modified grid interconnection scheme allows each PE to communicate with each of its eight nearest neighbors. A 32-b bus is used to transfer data to and from the array in a single cycle. Instruction execution is pipelined, enabling all instructions to be executed in a single cycle. The 1-micron CMOS design contains over 1.1 x 10 to the 6th transistors on an 11.0 x 11.7-mm die.

Heaton, Robert↗
NASA NTRS1982

Control structures for high speed processors

A special processor was designed to function as a Reed Solomon decoder with throughput data rate in the Mhz range. This data rate is significantly greater than is possible with conventional digital architectures. To achieve this rate, the processor design includes sequential, pipelined, distributed, and parallel processing. The processor was designed using a high level language register transfer language. The RTL can be used to describe how the different processes are implemented by the hardware. One problem of special interest was the development of dependent processes which are analogous to software subroutines. For greater flexibility, the RTL control structure was implemented in ROM. The special purpose hardware required approximately 1000 SSI and MSI components. The data rate throughput is 2.5 megabits/second. This data rate is achieved through the use of pipelined and distributed processing. This data rate can be compared with 800 kilobits/second in a recently proposed very large scale integration design of a Reed Solomon encoder.

Maki, G. K.↗
NASA NTRS1993

Storage media pipelining: Making good use of fine-grained media

This paper proposes a new high-performance paradigm for accessing removable media such as tapes and especially magneto-optical disks. In high-performance computing the striping of data across multiple devices is a common means of improving data transfer rates. Striping has been used very successfully for fixed magnetic disks improving overall system reliability as well as throughput. It has also been proposed as a solution for providing improved bandwidth for tape and magneto-optical subsystems. However, striping of removable media has shortcomings, particularly in the areas of latency to data and restricted system configurations, and is suitable primarily for very large I/Os. We propose that for fine-grained media, an alternative access method, media pipelining, may be used to provide high bandwidth for large requests while retaining the flexibility to support concurrent small requests and different system configurations. Its principal drawback is high buffering requirements in the host computer or file server. This paper discusses the possible organization of such a system including the hardware conditions under which it may be effective, and the flexibility of configuration. Its expected performance is discussed under varying workloads including large single I/O's and numerous smaller ones. Finally, a specific system incorporating a high-transfer-rate magneto-optical disk drive and autochanger is discussed.

Vanmeter, Rodney↗
NASA NTRS2018

Automated Pneumothorax Diagnosis using Deep Neural Networks

Thoracic ultrasound can provide information leading to rapid diagnosis of pneumothorax with improved accuracy over the standard physical examination and with higher sensitivity than anteroposterior chest radiography. However, the clinical We have Furthermore, remote environments, such as the battlefield or deep-space exploration, may lack expertise for diagnosing developed an automated image interpretation pipeline for the analysis of thoracic ultrasound data and the classification of pneumothorax events to provide decision support in such situations. Our pipeline consists of image preprocessing, data augmentation, and deep learning architectures for medical diagnosis. In this work, we demonstrate that robust, accurate interpretation of chest images and video can be achieved using deep neural networks. A number of novel image processing techniques were employed to achieve this result. Affine transformations were applied for data augmentation. Hyperparameters were optimized for learning rate, dropout regularization, batch size, and epoch iteration by a sequential model-based Bayesian approach. In addition, we utilized pretrained architecturesinterpretation of a patient medical image is highly operator dependent. certain pathologies., applying transfer learning and fine-tuning techniques to fully connected layers. Our pipeline yielded binary classification validation accuracies of 98.3% for M-mode images and 99.8% with B-mode video frames.

US Army collaboration↗
NASA NTRS1988

VLSI high speed packet processor

The Goddard Space Flight Center Mission Operations and Data Systems Directorate has developed a packet processor card utilizing semicustom very large scale integration (VLSI) devices, microprocessors, and programmable gate arrays to support the implementation of multichannel telemetry data capture systems. This card will receive synchronized error corrected telemetry transfer frames and output annotated application packets derived from this data. An adaptable format capability is provided by the programmability of three microprocessors while the throughput capability of the packet processor is achieved by a data pipeline consisting of two separate RAM systems controlled by specially designed semicustom VLSI logic.

Grebowsky, Gerald J.↗
NASA NTRS2005

Northeast Regional Planetary Data Center

In 1980, the Northeast Planetary Data Center (NEPDC) was established with Tim Mutch as its Director. The Center was originally located in the Sciences Library due to space limitations but moved to the Lincoln Field Building in 1983 where it could serve the Planetary Group and outside visitors more effectively. In 1984 Dr. Peter Schultz moved to Brown University and became its Director after serving in a similar capacity at the Lunar and Planetary Institute since 1976. Debbie Glavin has served as the Data Center Coordinator since 1982. Initially the NEPDC was build around Tim Mutch's research collection of Lunar Orbiter and Mariner 9 images with only partial sets of Apollo and Viking materials. Its collection was broadened and deepened as the Director (PHS) searched for materials to fill in gaps. Two important acquisitions included the transfer of a Viking collection from a previous PI in Tucson and the donation of surplused lunar materials (Apollo) from the USGS/Menlo Park prior to its building being torn down. Later additions included the pipeline of distributed materials such as the Viking photomosaic series and certain Magellan products. Not all materials sent to Brown, however, found their way to the Data Center, e.g., Voyager prints and negatives. In addition to the NEPDC, the planetary research collection is separately maintained in conjunction with past and ongoing mission activities. These materials (e.g., Viking, Magellan, Galileo, MGS mission products) are housed elsewhere and maintained independently from the NEPDC. They are unavailable to other researchers, educators, and general public. Consequently, the NEPDC represents the only generally accessible reference collection for use by researchers, students, faculty, educators, and general public in the Northeast corridor.

Schultz, Peter H.↗
NASA NTRSDate not supplied

DEVELOP’s Approach to Experiential Learning

The NASA DEVELOP Program addresses environmental decision making needs and geoscience workforce development through 10-week feasibility studies that apply Earth observations to environmental issues at hand. The program builds capacity to use geospatial information in both its participants (students, recent graduates, early career professionals, and transitioning career professionals) and partner organizations (federal agencies, state & local governments, non-profits, and private industry). This is accomplished through a structured project execution model that provides opportunities for participants to have autonomy, learn “on the job,” and gain new skillsets for working with remote sensing data. A pipeline of leadership positions enhances opportunities for individuals engaged in the program to get hands-on experience conducting data analyses, communicating their work, leading technical projects, and building their knowledge bank of Earth-observing satellite capabilities. These skillsets and knowledge are then transferred to partners through the projects. This panel contribution will introduce the DEVELOP model, highlight experiences of participants, and share the program’s insights into good practices for effective experiential learning.

Capacity Building↗
NASA NTRSDate not supplied

Synthetic Hyperspectral Data for Global Water Quality Algorithm Development

Eutrophication and increasing prevalence of potentially toxic algal blooms (cyanoHABs) among global inland water bodies have become a major ecological concern and require direct attention. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local aquatic processes, to spatially resolved global products. Planned aquatic biogeochemistry remote sensing data products from hyperspectral imagers such as NASA’s Surface Biology and Geology (SBG) mission and relevant aquatic sensor sensitivity precursor airborne imaging spectrometer data provide unprecedented radiometric resolution and sensor sensitivity for characterizing complex aquatic ecosystems. However, scarcity of high-quality freshwater in-situ optical data hinders our capability to develop and validate robust retrieval algorithms. A state-of-the-art synthetic dataset of paired top-of-atmosphere, bottom-of-atmosphere, and optical and biogeophysical data was developed through radiative transfer modeling to simulate natural freshwater ecosystems. A synthetic or precursor dataset for SBG is being used to train robust machine learning models to derive water quality products pertinent to SBG mission objectives. The dataset is also used to show the potential of performing vigorous aquatic sensitivity studies and explored pathways for how best to optimize hyperspectral data for machine learning development. A processing pipeline and resultant global synthetic/precursor dataset for inland waters is presented to establish the innovation for water quality studies of inland waters globally. Optical Society of America Imaging and Applied Optics Congress, Hyperspectral Imaging and Sounding of the Environment (OSA HISE) Meeting, 19-23 July 2021, Virtual Meeting, https://www.osa.org/enus/meetings/osa_meetings/optical_sensors_and_sensing_congress/program/hyperspectral_imaging_and_sounding_of_the_environm/

Synthetic↗
NASA NTRS2011

IONAC-Lite

The Interplanetary Overlay Net - working Protocol Accelerator (IONAC) described previously in The Inter - planetary Overlay Networking Protocol Accelerator (NPO-45584), NASA Tech Briefs, Vol. 32, No. 10, (October 2008) p. 106 (http://www.techbriefs.com/component/ content/article/3317) provides functions that implement the Delay Tolerant Networking (DTN) bundle protocol. New missions that require high-speed downlink-only use of DTN can now be accommodated by the unidirectional IONAC-Lite to support high data rate downlink mission applications. Due to constrained energy resources, a conventional software implementation of the DTN protocol can provide only limited throughput for any given reasonable energy consumption rate. The IONAC-Lite DTN Protocol Accelerator is able to reduce this energy consumption by an order of magnitude and increase the throughput capability by two orders of magnitude. In addition, a conventional DTN implementation requires a bundle database with a considerable storage requirement. In very high downlink datarate missions such as near-Earth radar science missions, the storage space utilization needs to be maximized for science data and minimized for communications protocol-related storage needs. The IONAC-Lite DTN Protocol Accelerator is implemented in a reconfigurable hardware device to accomplish exactly what s needed for high-throughput DTN downlink-only scenarios. The following are salient features of the IONAC-Lite implementation: An implementation of the Bundle Protocol for an environment that requires a very high rate bundle egress data rate. The C&DH (command and data handling) subsystem is also expected to be very constrained so the interaction with the C&DH processor and the temporary storage are minimized. Fully pipelined design so that bundle processing database is not required. Implements a lookup table-based approach to eliminate multi-pass processing requirement imposed by the Bundle Protocol header s length field structure and the SDNV (self-delimiting numeric value) data field formatting. 8-bit parallel datapath to support high data-rate missions. Reduced resource utilization implementation for missions that do not require custody transfer features. There was no known implementation of the DTN protocol in a field programmable gate array (FPGA) device prior to the current implementation. The combination of energy and performance optimization that embodies this design makes the work novel.

Torgerson, Jordan L.↗
NASA NTRS2017

Assessment of lnternational Space Station (ISS) Lithium-ion Battery Thermal Runaway (TR)

This task was developed in the wake of the Boeing 787 Dreamliner lithium-ion battery TR incidents of January 2013 and January 2014. The Electrical Power Technical Discipline Team supported the Dreamliner investigations and has followed up by applying lessons learned to conduct an introspective evaluation of NASA's risk of similar incidents in its own lithium-ion battery deployments. This activity has demonstrated that historically NASA, like Boeing and others in the aerospace industry, has emphasized the prevention of TR in a single cell within the battery (e.g., cell screening) but has not considered TR severity-reducing measures in the event of a single-cell TR event. center dotIn the recent update of the battery safety standard (JSC 20793) to address this paradigm shift, the NASA community included requirements for assessing TR severity and identifying simple, low-cost severity reduction measures. This task will serve as a pathfinder for meeting those requirements and will specifically look at a number of different lithium-ion batteries currently in the design pipeline within the ISS Program batteries that, should they fail in a Dreamliner-like incident, could result in catastrophic consequences. This test is an abuse test to understand the heat transfer properties of the cell and ORU in thermal runaway, with radiant barriers in place in a flight like test in on orbit conditions. This includes studying the heat flow and distribution in the ORU. This data will be used to validate the thermal runaway analysis. This test does not cover the ambient pressure case. center dotThere is no pass/ fail criteria for this test.

Graika, Jason↗
NASA NTRSDate not supplied

Optical Time Transfer for Bistatic SAR Spacecraft

A spacecraft-to-spacecraft optical time-transfer simulation has been developed as a tool for informing NASA’s Surface Deformation and Change (SDC) mission architecture. The SDC mission will combine radar images from multiple spacecraft to improve understanding of the Earth’s sea-level and landscape changes. Spacecraft must be precisely synchronized in order to create sharp radar images. Simulation of multiple spacecraft time-synchronizing via laser communication can inform technology choices of a mission by providing a picosecond-precision level estimate of clock error. This timing and ranging simulation has been combined with a radar system performance analysis pipeline. The simulated timing errors are used to predict performance of bistatic SAR systems in the presence of oscillator noise and time synchronization in accuracy. This analysis includes both analytic approximation equations from existing literature, and a numerical radar simulation to extract key system performance parameters like phase error and signal-to-noise ratio (SNR)degradation. Precision time-transfer techniques facilitate the accurate synchronization of clocks between any combination of terminals. Most time-transfer technology for comparing two clocks at different terminals use radio frequencies (RF) to measure the time delay between the sending and receiving of signals. Laser technology offers the capability to transmit high data rates with systems that are of smaller size and lower power than comparable RF systems. The clocks on independent spacecraft will have some phase and frequency errors between them that result in clock drift. The two clock models that are included in this bi-directional MATLAB simulation are a cesium-based Chip-Scale Atomic Clock (CSAC) and a rubidium-based Miniature Atomic Clock (MAC). The CSAC has flown as hardware for small satellite missions such as the University of Florida’s CHOMPTT mission. A study of example orbits, including that of NASA NASA-ISRO Synthetic Aperture Radar Mission (NISAR) mission, and lasing rates demonstrate the impact of flight configuration parameters on the synchronization error between two spacecraft. The MATLAB timing simulation uses a Runge-Kutta 4th-order method to propagate spacecraft orbits and computes the light-travel time estimate between them. The simulation outputs the estimated range and estimated clock error based on a user-defined spacecraft cluster configuration. The radar simulation and analytic approximations are applied to evaluate a potential future NASA bistatic SAR constellation architecture. In the proposed architecture, satellites follow each other in the same orbit at 800 km altitude, with a 210 km baseline. We also baseline the CSAC as an ultra stable oscillator, and use NASA’s NISAR for baseline radar system parameters to compute a clock-system introduced phase error of 5.6 degrees without synchronization by frequent time transfer. We build on this base case with a sensitivity analysis of radar performance over a proposed range of constellation and radar system parameters. With this analysis pipeline, we comment on which radar parameters should or should not be changed to minimize synchronization requirements. This analysis technique could be extended or modified to evaluate the timing requirements of other geometries for other future multistatic SAR missions, or other interferometric satellite missions.

Surface Deformation and Change↗
NASA NTRSDate not supplied

NASA GeneLab: Open Science for Life in Space

The NASA GeneLab project capitalizes on multi-omic technologies to maximize the return on spaceflight experiments. To do this, GeneLab maintains a publicly accessible database (GLDS) that houses spaceflight and spaceflight relevant multi-omics data and collaborates with NASA principal investigators and projects to generate additional omics data. GeneLab houses more than 350 transcriptomic, proteomic, metabolomic and epigenomic datasets from plant, animal and microbial experiments, with a growing number of these having been produced by the GeneLab Sequencing Lab. The GLDS contains rich metadata about each experiment and has integrated radiation dosimetry data from experiments flown on the Space Shuttle, International Space Station, and Free Flying spacecrafts. With the increasing amount and complexity of omics data being generated, GeneLab utilizes community-defined, common models for metadata and terminology so that omics data and results are discoverable and reliably reproducible. GeneLab uses the ISA-Tab specification and semantic model for organizing and representing omics metadata. In addition to metadata standards, data files must be open-source file or common exchange formats to ensure accessibility and usability by all users. To ease data ingestion and transfer, the web-based submission tool allows PIs a user-friendly user interface to curate, organize, and publish their space relevant omics data. In the more recent years, data curation and submission portal has incorporated the FAIR principles making data findable, accessible, interoperable, and reusable. To increase reusability of data, GeneLab has implemented an effort to present processed data in the GLDS in addition to the raw omics data. The processed data will enable interpretation of the data by a larger group of students, scientists and the general public. Standard pipelines for the transformation of raw data into visualizations were developed by four GeneLab Analysis Working Groups (animals, plants, microbes, multi-omics) comprised of over 200 scientists from NASA, industry, and academia. To explore the data, the GLDS provides users various tools for data analysis, collaborative workspace for file storage and sharing, and a visualization portal. The analysis platform built using the Galaxy toolshed provides access to a broad variety of users including those with limited bioinformatics experience and students to learn how to analyze spaceflight omics data. The visualization portal takes GeneLab one step closer to data democratization by removing all bioinformatics requisites to interpret transcriptomics data hosted in the repository. To train the next generation of scientists, NASA offers training programs such as GeneLab 4 High School (GL4HS) and GeneLab 4 Universities. NLM Curation at a Scale Workshop 2022 | NASA GeneLab (GL4U) to teach students bioinformatics and computational biology methods to analyze omics data. Discoveries made using GeneLab have begun and will continue to deepen our understanding of biology, advance the field of genomics, and help to discover cures for diseases, create better diagnostic tools, and ultimately allow astronauts to better withstand the rigors of long-duration spaceflight.

GeneLab↗
NASA NTRS2010

Rapid Corner Detection Using FPGAs

In order to perform precision landings for space missions, a control system must be accurate to within ten meters. Feature detection applied against images taken during descent and correlated against the provided base image is computationally expensive and requires tens of seconds of processing time to do just one image while the goal is to process multiple images per second. To solve this problem, this algorithm takes that processing load from the central processing unit (CPU) and gives it to a reconfigurable field programmable gate array (FPGA), which is able to compute data in parallel at very high clock speeds. The workload of the processor then becomes simpler; to read an image from a camera, it is transferred into the FPGA, and the results are read back from the FPGA. The Harris Corner Detector uses the determinant and trace to find a corner score, with each step of the computation occurring on independent clock cycles. Essentially, the image is converted into an x and y derivative map. Once three lines of pixel information have been queued up, valid pixel derivatives are clocked into the product and averaging phase of the pipeline. Each x and y derivative is squared against itself, as well as the product of the ix and iy derivative, and each value is stored in a WxN size buffer, where W represents the size of the integration window and N is the width of the image. In this particular case, a window size of 5 was chosen, and the image is 640 480. Over a WxN size window, an equidistance Gaussian is applied (to bring out the stronger corners), and then each value in the entire window is summed and stored. The required components of the equation are in place, and it is just a matter of taking the determinant and trace. It should be noted that the trace is being weighted by a constant k, a value that is found empirically to be within 0.04 to 0.15 (and in this implementation is 0.05). The constant k determines the number of corners available to be compared against a threshold sigma to mark a valid corner. After a fixed delay from when the first pixel is clocked in (to fill the pipeline), a score is achieved after each successive clock. This score corresponds with an (x,y) location within the image. If the score is higher than the predetermined threshold sigma, then a flag is set high and the location is recorded.

Morfopoulos, Arin C.↗