Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Discovery”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

STS-114: Discovery L-1 Countdown Status Briefing STS-114/Discovery L-2 Countdown Status Briefing

Bruce Buckingham from NASA Public Affairs introduces Jeff Spaulding, NASA Test Director and Kathy Winters, Shuttle Weather Officer in this L-2 countdown status briefing. Spaulding gives the Space Shuttle launch countdown status before lift-off on July 26th. He expresses that vehicle launch and ground systems are performing well and that there are no significant issues in preparation for the launch. The crew arrival time to the launching pad and the launch window for Discovery is also discussed. He ends his countdown status by expressing that the Discovery Orbiter is the safest Shuttle to date. Kathy Winters gives her weather forecast for the launch day. She presents a satellite picture of tropical storm Franklin and charts showing the STS-114 Tanking Forecast, Launch Forecast, Solid Rocket Booster (SRB) recovery, Continental United States (CONUS) launch, Transoceanic Abort Landing (TAL) launch, 24 and 48 Hour Delay, CONUS 24 and 48 hour delay, and TAL 24 and 48 hr delay. Questions from the news media about the mood of the test engineers as launch day is approached are answered. Jessica Rye from NASA Public Affairs introduces Pete Nikolento, NASA Test Director; Scott Higgenbotham, STS-114 Payload Mission Manager; and Kathy Winters, Space Shuttle Weather Officer in this L-1 Countdown Status Briefing. Nikolento expresses that the completion of the main engine system check-outs and servicing of on-board fuel-cell reactants have been completed. He also talks about pad closeouts and external cryogenic loads prior to launch. Scott Higgenbotham gives the payload status and Kathy Winters talks about her weather forecast for launch. Questions about the ecosensors, TAL sites, weather forecast and thoughts about return to flight are addressed.

Source record↗
NASA NTRS2005

STS-114: Discovery Mission Status Briefing

Phil Engelauf, STS-114 Mission Operations Representative, Mark Ferring, STS-114 Lead ISS Flight Director and Cindy Begley, STS-114 Lead EVA Officer is presented in this STS-114 Discovery mission status briefing. Mark Ferring talks about Control Moment Gyroscopes (CMG), Phil Engelauf discusses repair techniques for the Space Shuttle Discovery and Cindy Begley talks about the EVA's that Steve Robinson and Soichi Noguchi are performing. She also answers questions from the media about the spacewalker's ability to perform these tasks.

Source record↗
NASA NTRS2005

STS-114: Discovery Post Landing Press Briefing

Dean Acosta, NASA Public Affairs Deputy Assistant Administrator hosted this press briefing. Michael Griffin, NASA Administrator; Bill Parsons, Shuttle Program Manager; Michael Leinbach, Shuttle Launch Director; and Bill Ready, Space Operations Associate Administrator were present. The Panel specifically honored the Columbia crew as they praised Commander Eileen Collin's performance in bringing the Discovery and crew safe back to Earth. Re-entry, test flight and next test flight, thermal insulation, heat, vehicle inspection, turn around processing, and ferrying Discovery back to the Kennedy Space Center were topics covered with the News media. Michael Griffin announced the launching of Mars Reconnaissance Orbiter will take place the following morning.

Source record↗
NASA NTRS2005

STS-114: Discovery Post MMT Briefing

Wayne Hale, Space Shuttle Deputy Program Manager, is presented in this STS-114 Discovery Post Mission Management Team (MMT) briefing. He begins by talking about obtaining clearance from the Reinforced Carbon-Carbon (RCC) material. He then describes the supplies such as eleven water containers and the transfer of 50 additional pounds of Oxygen to the International Space Station. Hale presents a video of a billowed thermal blanket next to the commander's window on the port side of the Space Shuttle Discovery that seems to be of some concern. He answers questions from the news media about the dimensions of this blanket, and the dangers of getting close to this blanket during the Extravehicular Activity (EVA) to repair the gap fillers.

Source record↗
NASA NTRS2006

STS-121: Discovery Space Shuttle Safety Improvements Briefing

Steve Poulos, Space Shuttle Orbiter Projects Office Manager, and John Chapman, Space Shuttle External Tank Project Manager is shown in this STS-121 Space Shuttle Discovery safety improvements briefing. A graphic presentation of the gap filler installation is shown. The graphics include: 1) Protruding gap fillers during STS-114 mission; 2) STS-114 gap fillers removed on orbiter; 3) Gap filler installation prior to STS-114; 4) Post-STS-114 installation techniques; 5) Gap filler installation post STS-114; 6) Gap filler priority areas; 7) Discovery gap filler installation table and status for STS-121; 8) Damaged blanket on STS-114; 9) On-orbit photography and post-landing photography on STS-114; and 10) STS-114 insulation tiles. Poulos presents imagery that was obtained on STS-114. The imagery includes: 1) The Enhanced Launch Vehicle Imaging System (ELVIS); 2) Liquid oxygen external tank view; 3) Hand-held imagery of the external tank falling into the ocean; 4) ELVIS on STS-121, short, medium and long range camera configurations; 5) Radar capability on the ground at Kennedy Space Center, and 6) STS-121 aft external tank door tiles. Poulos says that STS-121 will have even more imagery than STS-114. John Chapman presents video animation of the external tank where modifications were made along with the ice frost ramps with extensions. Chapman explains these areas using an external tank model. Questions are then answered from the media.

Source record↗
NASA NTRS2007

Discovery of Non-random Spatial Distribution of Impacts in the Stardust Cometary Collector

We report the discovery that impacts in the Stardust cometary collector are not distributed randomly in the collecting media, but appear to be clustered on scales smaller than 10 cm. We also report the discovery of at least two populations of oblique tracks. We evaluated several hypotheses that could explain the observations. No hypothesis was consistent with all the observations, but the preponderance of evidence points toward at least one impact on the central Whipple shield of the spacecraft as the origin of both clustering and low-angle oblique tracks. High-angle oblique tracks unambiguously originate from a non-cometary impact on the spacecraft bus just forward of the collector.

Horz, Friedrich↗
NASA NTRS2008

Gamma Ray Burst Discoveries by the Swift Mission

With 3 years of on-orbit operations (launched in Nov 2004), Swift has detected over 300 gammaray bursts (GRBs). The unique combination of quick and accurate position determinations by the BAT instrument, fast autonomous spacecraft slewing, and multi-band instrumentation (XRT and UVOT) has allowed Swift to accumulate a long list of discoveries about GRBs. These positions are also available to the ground follow-up community (via TDRSS and GCN) within 15-30 sec. A summary of these discoveries will be given (e.g. long and short GRB host associations, SN associations, flaring and on-going activity in the central engine). The Swift spacecraft and instruments are in fine working order with no signs of performance degradation. With an expected orbital lifetime well past 2020, the overlap with GLAST (launch in mid-2008) will yield greater than 30 GRBs/year with observations by both missions. This will provide an unprecedented wavelength coverage from optical to 100 GeV. The coordination of pointing Swift with GLAST will be described.

Barthelmy, Scott↗
NASA NTRS2007

Automated Knowledge Discovery From Simulators

A computational method, SimLearn, has been devised to facilitate efficient knowledge discovery from simulators. Simulators are complex computer programs used in science and engineering to model diverse phenomena such as fluid flow, gravitational interactions, coupled mechanical systems, and nuclear, chemical, and biological processes. SimLearn uses active-learning techniques to efficiently address the "landscape characterization problem." In particular, SimLearn tries to determine which regions in "input space" lead to a given output from the simulator, where "input space" refers to an abstraction of all the variables going into the simulator, e.g., initial conditions, parameters, and interaction equations. Landscape characterization can be viewed as an attempt to invert the forward mapping of the simulator and recover the inputs that produce a particular output. Given that a single simulation run can take days or weeks to complete even on a large computing cluster, SimLearn attempts to reduce costs by reducing the number of simulations needed to effect discoveries. Unlike conventional data-mining methods that are applied to static predefined datasets, SimLearn involves an iterative process in which a most informative dataset is constructed dynamically by using the simulator as an oracle. On each iteration, the algorithm models the knowledge it has gained through previous simulation trials and then chooses which simulation trials to run next. Running these trials through the simulator produces new data in the form of input-output pairs. The overall process is embodied in an algorithm that combines support vector machines (SVMs) with active learning. SVMs use learning from examples (the examples are the input-output pairs generated by running the simulator) and a principle called maximum margin to derive predictors that generalize well to new inputs. In SimLearn, the SVM plays the role of modeling the knowledge that has been gained through previous simulation trials. Active learning is used to determine which new input points would be most informative if their output were known. The selected input points are run through the simulator to generate new information that can be used to refine the SVM. The process is then repeated. SimLearn carefully balances exploration (semi-randomly searching around the input space) versus exploitation (using the current state of knowledge to conduct a tightly focused search). During each iteration, SimLearn uses not one, but an ensemble of SVMs. Each SVM in the ensemble is characterized by different hyper-parameters that control various aspects of the learned predictor - for example, whether the predictor is constrained to be very smooth (nearby points in input space lead to similar output predictions) or whether the predictor is allowed to be "bumpy." The various SVMs will have different preferences about which input points they would like to run through the simulator next. SimLearn includes a formal mechanism for balancing the ensemble SVM preferences so that a single choice can be made for the next set of trials.

Burl, Michael↗
NASA NTRS2010

How Formal Methods Impels Discovery: A Short History of an Air Traffic Management Project

In this paper we describe a process of algorithmic discovery that was driven by our goal of achieving complete, mechanically verified algorithms that compute conflict prevention bands for use in en route air traffic management. The algorithms were originally defined in the PVS specification language and subsequently have been implemented in Java and C++. We do not present the proofs in this paper: instead, we describe the process of discovery and the key ideas that enabled the final formal proof of correctness

Butler, Ricky W.↗
NASA NTRS2011

Improvements in Space Geodesy Data Discovery at the CDDIS

The Crustal Dynamics Data Information System (CDDIS) supports data archiving and distribution activities for the space geodesy and geodynamics community. The main objectives of the system are to store space geodesy and geodynamics related data products in a central data bank. to maintain information about the archival of these data, and to disseminate these data and information in a timely manner to a global scientific research community. The archive consists of GNSS, laser ranging, VLBI, and DORIS data sets and products derived from these data. The CDDIS is one of NASA's Earth Observing System Data and Information System (EOSDIS) distributed data centers; EOSDIS data centers serve a diverse user community and arc tasked to provide facilities to search and access science data and products. Several activities are currently under development at the CDDIS to aid users in data discovery, both within the current community and beyond. The CDDIS is cooperating in the development of Geodetic Seamless Archive Centers (GSAC) with colleagues at UNAVCO and SIO. TIle activity will provide web services to facilitate data discovery within and across participating archives. In addition, the CDDIS is currently implementing modifications to the metadata extracted from incoming data and product files pushed to its archive. These enhancements will permit information about COOlS archive holdings to be made available through other data portals such as Earth Observing System (EOS) Clearinghouse (ECHO) and integration into the Global Geodetic Observing System (GGOS) portal.

Noll, C.↗
NASA NTRS2011

Easing the Discovery of NASA and International Near-Real-Time Data Using the Global Change Master Directory

The Global Change Master Directory (GCMD) provides an extensive directory of descriptive and spatial information about data sets and data-related services, which are relevant to Earth science research. The directory's data discovery components include controlled keywords, free-text searches, and map/date searches. The GCMD portal for NASA's Land Atmosphere Near-real-time Capability for EOS (LANCE) data products leverages these discovery features by providing users a direct route to NASA's Near-Real-Time (NRT) collections. This portal offers direct access to collection entries by instrument name, informing users of the availability of data. After a relevant collection entry is found through the GCMD's search components, the "Get Data" URL within the entry directs the user to the desired data. http://gcmd.nasa.gov/r/p/gcmd_lance_nrt.

Olsen, Lola↗
NASA NTRS2012

Discovery of an Energetic Pulsar Associated with SNR G76.9+1.0

We report the discovery of PSR J2022-<-3842, a 24 ms radio and X-ray pulsar in the supernova remnant G76.9+i.0, in observations with the Chandra X-ray telescope, the Robert C. Byrd Green Bank Radio Telescope, and the Rossi X-ray Timing Explorer (RXTE). The pulsar's spin-down rate implies a rotation-powered luminosity E = 1.2 X 10(exp 38) erg/s, a surface dipole magnetic field strength B(sub S), = 1.0 X 10(exp 12) G, and a characteristic age of 8.9 kyr. PSR J2022+3842 is thus the second-most energetic Galactic pulsar known, after the Crab, as well as the most rapidly-rotating young, radio-bright pulsar known. The radio pulsations are highly dispersed and broadened by interstellar scattering, and we find that a large (delta f/f approximates 1.9 x 10(exp -6)) spin glitch must have occurred between our discovery and confirmation observations. The X-ray pulses are narrow (0.06 cycles FWHM) and visible up to 20 keV, consistent with magnetospheric emission from a rotation-powered pulsar. The Chandra X-ray image identifies the pulsar with a hard, unresolved source at the midpoint of the double-lobed radio morphology of G76.9+ 1.0 and embedded within faint, compact X-ray nebulosity. The spatial relationship of the X-ray and radio emissions is remarkably similar to extended structure seen around the Vela pulsar. The combined Chandra and RXTE pulsar spectrum is well-fitted by an absorbed power-law model with column density N(sub H) = (1.7 +/- 0.3) x 10(exp 22) / sq cm and photon index Gamma = 1.0 +/- 0.2; it implies that the Chandra point-source flux is virtually 100% pulsed. For a distance of 10 kpc, the X-ray luminosity of PSR J2022+3842 is L(sub x){2-1O keV) = 7.0 x 10(exp 33) erg/s. Despite being extraordinarily energetic, PSR J2022+3842 lacks a bright X-ray wind nebula and has an unusually low conversion efficiency of spin-down power to X-ray luminosity, Lx/E = 5.9 X 10(exp-5).

Arzoumanian, Zaven↗
NASA NTRS2012

Discovery of an Unidentified Fermi Object as a Black Widow-Like Millisecond Pulsar

The Fermi Gamma-ray Space Telescope has revolutionized our knowledge of the gamma-ray pulsar population, leading to the discovery of almost 100 gamma-ray pulsars and dozens of gamma-ray millisecond pulsars (MSPs). Although the outer-gap model predicts different sites of emission for the radio and gamma-ray pulsars, until now all of the known gamma-ray MSPs have been visible in the radio. Here we report the discovery of a radio-quiet" gamma-ray emitting MSP candidate by using Fermi, Chandra, Swift, and optical observations. The X-ray and gamma-ray properties of the source are consistent with known gamma-ray pulsars. We also found a 4.63-hr orbital period in optical and X-ray data. We suggest that the source is a black widow-like MSP with a approx. 0.1 Stellar Mass late-type companion star. Based on the profile of the optical and X-ray light-curves, the companion star is believed to be heated by the pulsar while the X-ray emissions originate from pulsar magnetosphere and/or from intra-binary shock. No radio detection of the source has been reported yet and although no gamma-ray/radio pulsation has been found, we estimated that the spin period of the MSP is approx. 3-5 ms based on the inferred gamma-ray luminosity.

Kong, A. K. H.↗
NASA NTRS2014

SGR J1745-29: Swift Discovery and Monitoring of a New SGR Near Sgr A*

Starting in 2013 February, Swift has been performing short daily monitoring observations of the G2 gas cloud near Sgr A* with the X-Ray Telescope to determine whether the cloud interaction leads to an increase in the flux from the Galactic center. On 2013 April 24 Swift detected an order of magnitude rise in the X-ray flux from the region near Sgr A*. Initially thought to be a flare from Sgr A*, detection of a short hard X-ray burst from the same region by the Burst Alert Telescope suggested that the flare was from an unresolved new Soft Gamma Repeater, SGR J1745-29. Here we present the discovery of SGR J1745-29 by Swift, including analysis of data before, during, and after the burst. We cover the entire light-curve of the SGR outburst so far, from discovery through to the source entering a Swift Sun constraint in November 2013. Thanks to the interest in G2 and its location near the Galactic Center, SGR J1745-29 has become one of the best monitoring SGRs in outburst yet seen.

Kennea, Jamie A.↗
NASA NTRS2015

iPTF14yb: The First Discovery of a Gamma-Ray Burst Afterglow Independent of a High-Energy Trigger

We report here the discovery by the Intermediate Palomar Transient Factory (iPTF) of iPTF14yb, a luminous (Mr >> -27.8 mag), cosmological (redshift 1.9733), rapidly fading optical transient. We demonstrate, based on probabilistic arguments and a comparison with the broader population, that iPTF14yb is the optical afterglow of the long-duration gamma-ray burst GRB 140226A. This marks the first unambiguous discovery of a GRB afterglow prior to (and thus entirely independent of) an associated high-energy trigger. We estimate the rate of iPTF14yb-like sources (i.e., cosmologically distant relativistic explosions) based on iPTF observations, inferring an all-sky value of Rrel = 610/yr (68% confidence interval of 110-2000/yr). Our derived rate is consistent (within the large uncertainty) with the all-sky rate of on-axis GRBs derived by the Swift satellite. Finally, we briefly discuss the implications of the nondetection to date of bona fide "orphan" afterglows (i.e., those lacking detectable high-energy emission) on GRB beaming and the degree of baryon loading in these relativistic jets.

gamma-ray burst: general aEuro" stars: flare aEuro↗
NASA NTRS2016

The Outer Solar System Origins Survey: Design and First-Quarter Discoveries - I.

We report the discovery, tracking, and detection circumstances for 85 trans-Neptunian objects (TNOs) from the first 42 square degrees of the Outer Solar System Origins Survey. This ongoing r-band solar system survey uses the 0.9 square degree field of view MegaPrime camera on the 3.6 meter Canada-France-Hawaii Telescope. Our orbital elements for these TNOs are precise to a fractional semimajor axis uncertainty of less than 0.1 percent. We achieve this precision in just two oppositions, as compared to the normal three to five oppositions, via a dense observing cadence and innovative astrometric technique. These discoveries are free of ephemeris bias, a first for large trans-Neptunian surveys. We also provide the necessary information to enable models of TNO orbital distributions to be tested against our TNO sample. We confirm the existence of a cold "kernel" of objects within the main cold classical Kuiper Belt and infer the existence of an extension of the "stirred" cold classical Kuiper Belt to at least several au beyond the 2:1 mean motion resonance with Neptune. We find that the population model of Petit et al. remains a plausible representation of the Kuiper Belt. The full survey, to be completed in 2017, will provide an exquisitely characterized sample of important resonant TNO populations, ideal for testing models of giant planet migration during the early history of the solar system.

Bannister, Michele T.↗
NASA NTRS2016

OSSOS. IV. Discovery of a Dwarf Planet Candidate in the 9:2 Resonance with Neptune

We report the discovery and orbit of a new dwarf planet candidate, 2015 RR245, by the Outer Solar System Origins Survey (OSSOS). The orbit of 2015 RR245 is eccentric (e 0.586), with a semimajor axis near 82 au, yielding a perihelion distance of 34 au. 2015 RR245 has g - r 0.59 +/- 0.11 and absolute magnitude Hr 3.6 +/- 0.1; for an assumed albedo of pV 12, the object has a diameter of approximately 670 km. Based on astrometric measurements from OSSOS and Pan-STARRS1, we find that 2015 RR245 is securely trapped on ten-megayear timescales in the 9:2 mean-motion resonance with Neptune. It is the first trans-Neptunian object (TNO) identied in this resonance. On hundred-megayear timescales, particles in 2015 RR245-like orbits depart and sometimes return to the resonance, indicating that 2015 RR245 likely forms part of the long-lived metastable population of distant TNOs that drift between resonance sticking and actively scattering via gravitational encounters with Neptune. The discovery of a 9:2 TNO stresses the role of resonances in the long-term evolution of objects in the scattering disk and reinforces the view that distant resonances are heavily populated in the current solar system. This object further motivates detailed modeling of the transient sticking population.

Bannister, Michele T.↗
NASA NTRS2016

The IPAC Image Subtraction and Discovery Pipeline for the Intermediate Palomar Transient Factory

We describe the near real-time transient-source discovery engine for the intermediate Palomar Transient Factory (iPTF), currently in operations at the Infrared Processing and Analysis Center (IPAC), Caltech. We coin this system the IPAC/iPTF Discovery Engine (or IDE). We review the algorithms used for PSF-matching, image subtraction, detection, photometry, and machine-learned (ML) vetting of extracted transient candidates. We also review the performance of our ML classifier. For a limiting signal-to-noise ratio of 4 in relatively unconfused regions, bogus candidates from processing artifacts and imperfect image subtractions outnumber real transients by approximately equal to 10:1. This can be considerably higher for image data with inaccurate astrometric and/or PSF-matching solutions. Despite this occasionally high contamination rate, the ML classifier is able to identify real transients with an efficiency (or completeness) of approximately equal to 97% for a maximum tolerable false-positive rate of 1% when classifying raw candidates. All subtraction-image metrics, source features, ML probability-based real-bogus scores, contextual metadata from other surveys, and possible associations with known Solar System objects are stored in a relational database for retrieval by the various science working groups. We review our efforts in mitigating false-positives and our experience in optimizing the overall system in response to the multitude of science projects underway with iPTF.

methods: analytical – methods: data analysis –↗