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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Gamma ray astronomy

The Burst and Transient Source Experiment (BATSE) is one of four instruments on the Compton observatory which was launched by the space shuttle Atlantis on April 5, 1991. As of mid-March, 1994, BATSE detected more than 925 cosmic gamma-ray bursts and more than 725 solar flares. Pulsed gamma rays have been detected from at least 16 sources and emission from at least 28 sources (including most of the pulsed sources) has been detected by the earth occultation technique. UAH participation in BATSE is extensive but can be divided into two main areas, operations and data analysis. The daily BATSE operations tasks represent a substantial level of effort and involve a large team composed of MSFC personnel as well as contractors such as UAH. The scientific data reduction and analysis of BATSE data is also a substantial level of effort in which UAH personnel have made significant contributions.

Paciesas, William S.↗
NASA NTRS1996

The Telecommunications and Data Acquisition Report

This quarterly publication provides archival reports on developments in programs managed by JPL's Telecommunications and Mission Operations Directorate (TMOD), which now includes the former Telecommunications and Data Acquisition (TDA) Office. In space communications, radio navigation, radio science, and ground-based radio and radar astronomy, it reports on activities of the Deep Space Network (DSN) in planning, supporting research and technology, implementation, and operations. Also included are standards activity at JPL for space data and information systems and reimbursable DSN work performed for other space agencies through NASA. The preceding work is all performed for NASA's Office of Space Communications (OSC). TMOD also performs work funded by other NASA program offices through and with the cooperation of OSC. The first of these is the Orbital Debris Radar Program funded by the Office of Space Systems Development. It exists at Goldstone only and makes use of the planetary radar capability when the antennas are configured as science instruments making direct observations of the planets, their satellites, and asteroids of our solar system. The Office of Space Sciences funds the data reduction and science analyses of data obtained by the Goldstone Solar System Radar. The antennas at all three complexes are also configured for radio astronomy research and, as such, conduct experiments funded by the National Science Foundation in the U.S. and other agencies at the overseas complexes. These experiments are either in microwave spectroscopy or very long baseline interferometry. Finally, tasks funded under the JPL Director's Discretionary Fund and the Caltech President's Fund that involve TMOD are included. This and each succeeding issue of 'The Telecommunications and Data Acquisition Progress Report' will present material in some, but not necessarily all, of the aforementioned programs.

Yuen, Joseph H.↗
NASA NTRS2002

Formation of Brown Dwarfs LTSA 2001

The goals of the work funded by this grant are: (1) The measurement of the mass function and minimum mass of free-floating brown dwarfs down to the mass of Jupiter; (2) The measurement of the frequency of wide brown dwarf and planetary companions down to the mass of Jupiter as function of primary mass (0.02-2 Msun), age (1-10 Myr), and environment (clusters vs. dispersed regions). For the first objective, we have completed the design of guaranteed SIRTF observations of nearby star-forming regions and now await the launch of the mission in April 2003. In support of these upcoming observations, in the fall of 2002 we obtained optical spectroscopy at the MMT and the 1.5-meter telescope at Fred Lawrence Whipple Observatory for candidate young low-mass stars and brown dwarfs in the IC348 and Taurus star-forming regions. Two papers that include these data in new measurements of the mass functions in these regions are near completion and will be submitted for publication to the Astrophysical Journal in January. We have also proposed deep optical and near-IR imaging of the SIRTF fields in the IC348, Chamaeleon, and Ophiuchus star-forming regions with the MMT, Magellan, and Gemini North telescopes in early 2003. For the second objective, we have used deep HST WFPC2 images to search for young giant planets and brown dwarfs around approximately 100 low-mass stars and brown dwarfs in the nearby cluster IC 348. We have completed all data reduction and have checked these data for candidate companions. We are in the process of writing a paper that describes these candidate companions and presents the companion detection limits that were achieved with HST. We will attempt followup spectroscopy of the most promising candidate companions to confirm their nature as cool companions rather than background field stars during the commissioning of the facility adaptive optics system for the Gemini North telescope early in 2003. In addition, in SIRTF guaranteed time observations we plan to search for wide substellar companions (greater than 10 inches) around the youngest nearby field stars (ages of 30-100 Myr, d less than 30 pc). We have proposed to use Keck adaptive optics imaging to search these same stars for close-in planets and brown dwarfs at 0.1-l0 inches, which will perfectly complement our SIRTF observations.

Luhman, Kevin L.↗
NASA NTRS2002

Participation in the Mars Orbiting Laser Altimeter Experiment

This NASA Grant, 5-4434, has covered the active participation of the Principal Investigator, Prof. Gordon Pettengill, and his Co-Investigator, Peter Ford, in the Mars Orbiting Laser Altimeter (MOLA) Experiment, over a period of five years. This participation has included attending team meetings, planning observing operations, developing data-reduction software algorithms, and processing data, as well as presenting a number of oral reports at scientific meetings and published papers in refereed journals. This research has concentrated on the various types of Martian clouds that were detected by the laser altimeter.

Pettengill, Gordon H.↗
NASA NTRS2003

Formation of Brown Dwarfs LTSA 2001

The goals of the work funded by this grant are: 1) The measurement of the mass function and minimum mass of free-floating brown dwarfs down to the mass of Jupiter; 2) The measurement of the frequency of wide brown dwarf and planetary companions down to the mass of Jupiter as function of primary mass (0.02-2 Msun), age (1-10 Myr), and environment (clusters vs. dispersed regions). For the first objective, we have completed the design of guaranteed SIRTF observations of nearby star-forming regions. With the successful launch of the SIRTF mission in August of 2003, we now await the execution of these observations, which should begin in early 2004. In support of these upcoming observations, in the fall of 2002 and spring of 2003 we obtained optical spectroscopy at the MMT, the 1.5 meter telescope at Fred Lawrence Whipple Observatory, and Magellan Observatory for several hundred candidate young low-mass stars and brown dwarfs in the IC348, Taurus, and Chamaeleon star-forming regions. All of these data have been published in three papers in The Astrophysical Journal. We also recently used the MMT to obtain deep near-IR images of IC348 to accompany the SIRTF images and have time in the next month at the IRTF and Keck for spectroscopy of candidate brown dwarfs in IC348 and Taurus. We have submitted proposals for deep optical and near-IR imaging of the SIRTF fields in Chamaeleon and Ophiuchus for spring 2004 with Magellan and the AAT. Results from this research have been presented in invited talks at UU Symposium 221 (July 2003) and at the SIRTF Galactic Science Workshop (August 2003). For the second objective, we have used deep HST WFPC2 images to search for young giant planets and brown dwarfs around approx. 100 low-mass stars and brown dwarfs in the nearby cluster IC348. We have completed all data reduction and have checked these data for candidate companions. We expect to submit the paper describing these observations to The Astrophysical Journal by the end of the year. In addition, in SIRTF guaranteed time observations we plan to search for wide substellar companions (>10 sec) around the youngest nearby field stars (ages of 30-100 Myr, d<30 pc). We have submitted a proposal to use Keck adaptive optics imaging to search these same stars for close-in planets and brown dwarfs at 0.1-10 sec, which will perfectly complement our SIRTF observations.

Luhman, Kevin L.↗
NASA NTRS2012

Demystifying Kepler Data: A Primer for Systematic Artifact Mitigation

The Kepler spacecraft has collected data of high photometric precision and cadence almost continuously since operations began on 2009 May 2. Primarily designed to detect planetary transits and asteroseismological signals from solar-like stars, Kepler has provided high quality data for many areas of investigation. Unconditioned simple aperture time-series photometry are however affected by systematic structure. Examples of these systematics are differential velocity aberration, thermal gradients across the spacecraft, and pointing variations. While exhibiting some impact on Kepler's primary science, these systematics can critically handicap potentially ground-breaking scientific gains in other astrophysical areas, especially over long timescales greater than 10 days. As the data archive grows to provide light curves for 10(exp 5) stars of many years in length, Kepler will only fulfill its broad potential for stellar astrophysics if these systematics are understood and mitigated. Post-launch developments in the Kepler archive, data reduction pipeline and open source data analysis software have occurred to remove or reduce systematic artifacts. This paper provides a conceptual primer for users of the Kepler data archive to understand and recognize systematic artifacts within light curves and some methods for their removal. Specific examples of artifact mitigation are provided using data available within the archive. Through the methods defined here, the Kepler community will find a road map to maximizing the quality and employment of the Kepler legacy archive.

Kinemuchi, K.↗
NASA NTRS2015

Spacecube: A Family of Reconfigurable Hybrid On-Board Science Data Processors

SpaceCube is a family of Field Programmable Gate Array (FPGA) based on-board science data processing systems developed at the NASA Goddard Space Flight Center (GSFC). The goal of the SpaceCube program is to provide 10x to 100x improvements in on-board computing power while lowering relative power consumption and cost. SpaceCube is based on the Xilinx Virtex family of FPGAs, which include processor, FPGA logic and digital signal processing (DSP) resources. These processing elements are leveraged to produce a hybrid science data processing platform that accelerates the execution of algorithms by distributing computational functions to the most suitable elements. This approach enables the implementation of complex on-board functions that were previously limited to ground based systems, such as on-board product generation, data reduction, calibration, classification, eventfeature detection, data mining and real-time autonomous operations. The system is fully reconfigurable in flight, including data parameters, software and FPGA logic, through either ground commanding or autonomously in response to detected eventsfeatures in the instrument data stream.

reconfigurable computing↗
NASA NTRS2018

Imaging for Hypersonic Experimental Aeroheating Testing (IHEAT) Version 4.0: User Manual

The IHEAT v4.0 software is a data reduction code for global thermography data acquired in the NASA Langley Aerothermodynamics Laboratory (LAL) hypersonic wind tunnels. IHEAT uses red and green color-intensity data from two-dimensional images of wind tunnel models to compute temperatures and heat-transfer rates using a semi-infinite, one-dimensional heat transfer approximation at each image pixel. Multiple automated tools in IHEAT v4.0 decrease the time required to reduce the data from a phosphor thermography wind tunnel run. Data at one or all of the image pixel locations can be exported to computer files for further analysis. The prior version of IHEAT, v3.2, was written in PV-WAVE® (now owned by Rogue Wave® Software) in 1994 and was limited in functionality to fit within the memory constraints of the available computers at the time. IHEAT v4.0 is written in MATLAB® by MathWorks® and contains several new features that leverage the increase in available memory of the current computers. A Piecewise tool permits the user to extract data along a segmented line cut that can follow interesting features in the image better than the single, straight line cuts that were possible with the legacy Length and Profile tools. The new Load Run and Batch tools facilitate batch processing by loading in all of the input files and images for a run at the same time. Load Run permits the user to process the available run images manually, while Batch automatically saves heat transfer data from all of the images based on the analysis previously performed on a single frame. IHEAT v4.0 also can automatically calculate the temporal collapse of reference line cuts from the time history heating data for a run to indicate the appropriate frame to reduce for each run. The IHEAT v4.0 source code was compiled into a standalone executable file that can be accessed remotely from several computers with different operating systems, simultaneously. The software is run through the MATLAB® Compiler Runtime engine, and therefore, IHEAT does not require a software license to run. Any software commands executed in the IHEAT v4.0 code will not affect other similar applications running on the same machine. Similarly, changes to the parent software do not affect a compiled code. These features of IHEAT v4.0 are improvements over the legacy v3.2 code, which required regular maintenance to avoid losing functionality as the PVWAVE ® programming language was upgraded.

Mason, Michelle L.↗
DOE OSTI2022

Maintaining Trust in Reduction: Preserving the Accuracy of Quantities of Interest for Lossy Compression

As the growth of data sizes continues to outpace computational resources, there is a pressing need for data reduction techniques that can significantly reduce the amount of data and quantify the error incurred in compression. Compressing scientific data presents many challenges for reduction techniques since it is often on non-uniform or unstructured meshes, is from a high-dimensional space, and has many Quantities of Interests (QoIs) that need to be preserved. To illustrate these challenges, we focus on data from a large scale fusion code, XGC. XGC uses a Particle-In-Cell (PIC) technique which generates hundreds of PetaBytes (PBs) of data a day, from thousands of timesteps. XGC uses an unstructured mesh, and needs to compute many QoIs from the raw data, f.One critical aspect of the reduction is that we need to ensure that QoIs derived from the data (density, temperature, flux surface averaged momentums, etc.) maintain a relative high accuracy. We show that by compressing XGC data on the high-dimensional, nonuniform grid on which the data is defined, and adaptively quantizing the decomposed coefficients based on the characteristics of the QoIs, the compression ratios at various error tolerances obtained using a multilevel compressor (MGARD) increases more than ten times. We then present how to mathematically guarantee that the accuracy of the QoIs computed from the reduced f is preserved during the compression. We show that the error in the XGC density can be kept under a user-specified tolerance over 1000 timesteps of simulation using the mathematical QoI error control theory of MGARD, whereas traditional error control on the data to be reduced does not guarantee the accuracy of the QoIs.

Gong, Qian↗
DOE OSTI2025

Final report- UFL - RAPIDS2: A SciDAC Institute for Computer Science, Data, and Artificial Intelligence

The research initiatives supported by the U.S. Department of Energy (DOE) Grant DE-SC0022265 are fundamentally aimed at pioneering advanced machine learning (ML) techniques for scientific data compression within high-performance computing (HPC) environments. This comprehensive body of work addresses the critical challenge posed by the exponential growth of data generated by scientific simulations in domains such as fusion energy, climate modeling, and computational fluid dynamics (CFD). A core objective is to develop compression algorithms that achieve substantial data reduction—often by orders of magnitude—while rigorously ensuring the fidelity of both the primary data (PD) and scientifically crucial derived quantities of interest (QoI). The methodologies deployed under this grant integrate sophisticated deep learning architectures, prominently featuring autoencoders, advanced generative models like conditional diffusion, and hybrid learning techniques. Key innovations include the development of Guaranteed Autoencoders (GAE) and the Guaranteed Conditional Diffusion with Tensor Correction (GCDTC) framework, which provide explicit, instance-level error bounds on reconstructed data. Furthermore, specialized strategies such as nonlinear constraint satisfaction are employed to preserve the integrity of QoI, a vital requirement for the trustworthiness of downstream scientific analyses. This research also focuses on the design and implementation of scalable, GPU-accelerated software pipelines that seamlessly integrate into existing HPC workflows, ensuring both computational efficiency and practical applicability. The CAESAR framework, for example, unifies foundation and generative models to create an adaptive and efficient compression solution for spatio-temporal scientific data. Collectively, these efforts represent a significant advancement in mitigating the scientific data deluge, enabling more effective data management, accelerated scientific discovery, and optimized utilization of HPC resources.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1994

Mean sea surface and geoid gradient comparisons with TOPEX altimeter data

Cycles 4 to 54 of TOPEX data have been analyzed through comparisons with the mean sea surface given on the disturbed geophysical data record (GDR). Two inverted barometer correction procedures were considered for the data reduction. One used a constant atmospheric pressure for all data while the one adopted for use, for most computations, introduced a cycle average pressure. The maximum difference between the two estimates was 3.0 cm with a clear annual signal. With the modified correction the TOPEX sea surface was compared to The Ohio State University (OSU) mean sea surface, given on the GDR, to estimate three translations ( delta x = -2.3 cm; delta y = 25.0 cm; delta z = -0.3 cm) and a bias (43.3 cm) between the two surfaces. The only significant translation is delta y which indicates the reference frame of the TOPEX system differs from that used in the OSU mean sea surface system. The bias between the TOPEX mean sea surface and the OSU mean sea surface was used to estimate an equatorial radius of 6,378,136.55 m based on an 18-cm biased estimate of the TOPEX altimeter. Examination of the average difference, by cycle, between the TOPEX sea surface and the OSU mean sea surface suggested a bias change of 3.1 +/- 2.2 mm/yr with a positive sign indicating the average ocean surface is rising or the altimeter measured distance is decreasing. Models were implemented that solved directly for a bias, bias rate annual/semiannual, and tide correction terms. The computations indicated that a simultaneous solution for this bias, bias rate, and annual/semiannual terms gave the most accurate results. Nonsimultaneous solutions led to slightly different bias rate values. The root mean square difference between the TOPEX sea surface and OSU sea surface, after translation and bias correction, was +/- 17 cm for a typical cycle. Some locations were indentified where the difference could reach 2.3 cm and were repeated over several cycles indicating errors in the mean sea surface. Most of the large differences occur in regions lacking altimeter data prior to the TOPEX/POSEIDON mission and/or areas of significant bathymetric signature. Geoid gradients are needed for the reduction of individual track data to a reference track. The accuracy of the determination of such gradients was determined through the comparison of predicted along-track gradients to the observed gradients. Among four mean sea surfaces tested the best agreement was found with the OSU mean sea surface placed on the TOPEX geophysical data record.

Rapp, Richard H.↗
NASA NTRS2024

The CapiSorb Visible System (CVS) Demonstrations on ISS

Falling liquid film amine sorbent reactors have been successfully employed to scrub CO 2 aboard submarines for decades. However, applying such proven methods aboard orbiting and coast spacecraft is significantly challenged by the nearly weightless environment, where liquid sprays and films do not fall, and vapor bubbles and gases do not rise. The Capillary Sorbent (CapiSorb) Visible System (CVS) is a technology demonstration experiment performed aboard the ISS April 18 – 21, 2023. The system establishes stable steady thin liquid film flows in Contactor (absorber) and Degasser (desorber/stripper) replacing the passive role of gravity with the combined passive roles of surface tension, wetting, and system geometry. A TOX-0 fructose ersatz liquid sorbent is employed enabling ‘transparent’ experiments performed and filmed by the crew safely in the open cabin of the ISS. Completed objectives include demonstrations of stable passive ‘massively’ parallel planar thin film capillary flows across atmospheric pressure Contactor and sealed heated Degasser. The impacts of varying flow rate, flow direction, heat input, viscosity, positive and negative Degasser pressures, condensate collection and return, fluid distribution, interfacial stability, and others are reported. At least 49 diagnostics are recorded for digitization and subsequent thermal-fluids model validation by a single HD video downlink during the nearly 22 hours of operations. An overview of the flight hardware including description of the components, diagnostics, crew procedures, flight operations, and summary of accomplishments is reported in Ref. 1. Further details of the diagnostics, tests performed, and data reduction is reported in Ref. 2. This report collects both1,2 into a single report adding methods of data digitization, reduction, and archive along with analyses and discussions of technology impacts.

microgravity↗
NASA NTRS1977

Orbit determination accuracies using satellite-to-satellite tracking

The uncertainty in relay satellite sate is a significant error source which cannot be ignored in the reduction of satellite-to-satellite tracking data. Based on simulations and real data reductions, it is numerically impractical to use simultaneous unconstrained solutions to determine both relay and user satellite epoch states. A Bayesian or least squares estimation technique with an a priori procedure is presented which permits the adjustment of relay satellite epoch state in the reduction of satellite-to-satellite tracking data without the numerical difficulties introduced by an ill-conditioned normal matrix.

Vonbun, F. O.↗
NASA NTRS1984

Crossed hot-wire data acquisition and reduction system

The report describes a system for rapid computerized calibration acquisition, and processing of data from a crossed hot-wire anemometer is described. Advantages of the system are its speed, minimal use of analog electronics, and improved accuracy of the resulting data. Two components of mean velocity and turbulence statistics up to third order are provided by the data reduction. Details of the hardware, calibration procedures, response equations, software, and sample results from measurements in a turbulent plane mixing layer are presented.

Westphal, R. V.↗
DOE OSTI2025

LCLS Big Data Handling – How I Learned to Stop Worrying and Love the Data Deluge

Advanced data and computing systems are vital to Linac Coherent Light Source (LCLS) operations, data interpretation and overall scientific productivity. The transition to MHz-era operation marks a fundamental change in scale that requires new infrastructure and architectures to link LCLS to the required scale of computing needed for scientific interpretation. The LCLS-II Data System meets big data challenges by implementing configurable data reduction that can adapt to multiple science areas, real-time analysis frameworks to provide visualization and fast feedback, and the ability to transfer data to local and remote computational facilities for near real time analysis at the appropriate scale. Feature extracted information generated in the data analysis pipeline - at the edge, local compute, or remote High-Performance Computing (HPC) resources - can be used to steer experiments and inform user decisions during beam time. Artificial Intelligence and Machine Learning (AI/ML) techniques present new opportunities to rapidly analyse large datasets and direct experiments, but create new challenges in scaling, adaptability, complexity, and trustworthiness. We describe how the LCLS-II Data System architecture addresses its data-driven challenges in the areas of data acquisition, data processing, data management, and workflow orchestration to decrease the overall time-to-science and provide a vision for future developments.

artificial intelligence↗