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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Preliminary Target Selection for the DESI Luminous Red Galaxy (LRG) Sample

The DESI survey will observe more than 8 million candidate luminous red galaxies (LRGs) in the redshift range 0.3 < z < 1.0. In this work, we present a preliminary version of the DESI LRG target section developed using Legacy Surveys Data Release 8 g, r, z and W1 photometry. This selection yields a sample with a uniform surface density of ~600 deg –2 and very low predicted stellar contamination and redshift failure rates. During DESI Survey Validation, updated versions of this selection will be tested and optimized.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Preliminary Target Selection for the DESI Milky Way Survey (MWS)

The DESI Milky Way Survey (MWS) will observe ≥8 million stars between 16 < r < 19 mag, supplemented by observations of brighter targets under poor observing conditions. The survey will permit an accurate determination of stellar kinematics and population gradients, characterize diffuse substructure in the thick disk and stellar halo, enable the discovery of extremely metal-poor stars and other rare stellar types, and improve constraints on the Galaxy's 3D dark matter distribution from halo star kinematics. MWS will also enable a detailed characterization of the stellar populations within 100 pc of the Sun, including a complete census of white dwarfs.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1975

A two-level trajectory decomposition algorithm featuring optimal intermediate target selection

A decomposition algorithm is presented that optimizes complex missions by partitioning the trajectory into natural segments such as ascent or entry. Each segment defines a full-rank targeting subproblem. These are solved sequentially using the Newton-Raphson algorithm. The master problem, representing the complete mission, is to determine subproblem targets and master-problem controls that optimize the mission objective subject to intersegment constraints. The gradient projection algorithm solves this problem using derivatives obtained analytically from finite-difference subproblem sensitivities. Thus, the mission is optimized by coordinating the solution of tractible subproblems. Computational results for a synchronous equatorial mission are included.

Petersen, F. M.↗
NASA NTRS1977

A two-level trajectory decomposition algorithm featuring optimal intermediate target selection

A decomposition algorithm is presented which optimizes complex missions by partitioning the trajectory into natural segments such as ascent or entry. Each segment defines a full-rank targeting subproblem. These are solved sequentially using the Newton-Raphson algorithm. The master problem, representing the complete mission, is to determine subproblem targets and master-problem controls that optimize the mission objective subject to intersegment constraints. The gradient projection algorithm solves this problem using derivatives obtained analytically from finite-difference subproblem sensitivities. Thus, the mission is optimized by coordinating the solution of tractible subproblems. Computational results for a synchronous equatorial mission are included.

Petersen, F. M.↗
DOE OSTI2023

Target Selection and Validation of DESI Luminous Red Galaxies

The Dark Energy Spectroscopic Instrument (DESI) is carrying out a five-year survey that aims to measure the redshifts of tens of millions of galaxies and quasars, including 8 million luminous red galaxies (LRGs) in the redshift range 0.4 < z ≲ 1.0. Here we present the selection of the DESI LRG sample and assess its spectroscopic performance using data from Survey Validation (SV) and the first two months of the Main Survey. The DESI LRG sample, selected using g, r, z, and W1 photometry from the DESI Legacy Imaging Surveys, is highly robust against imaging systematics. The sample has a target density of 605 deg -2 and a comoving number density of 5 × 10 -4 h 3 Mpc -3 in 0.4 < z < 0.8; this is a significantly higher density than previous LRG surveys (such as SDSS, BOSS, and eBOSS) while also extending to z ~ 1. After applying a bright star veto mask developed for the sample, 98.9% of the observed LRG targets yield confident redshifts (with a catastrophic failure rate of 0.2% in the confident redshifts), and only 0.5% of the LRG targets are stellar contamination. The LRG redshift efficiency varies with source brightness and effective exposure time, and we present a simple model that accurately characterizes this dependence. In the appendices, we describe the extended LRG samples observed during SV.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2013

Effects of Type and Strength of Force Feedback on Movement Time in a Target Selection Task

Future cockpits will likely include new onboard technologies, such as cockpit displays of traffic information, to help support future flight deck roles and responsibilities. These new technologies may benefit from multimodal feedback to aid pilot information processing. The current study investigated the effects of multiple levels of force feedback on operator performance in an aviation task. Participants were presented with two different types of force feedback (gravitational and spring force feedback) for a discrete targeting task, with multiple levels of gain examined for each force feedback type. Approach time and time in target were recorded. Results suggested that the two highest levels of gravitational force significantly reduced approach times relative to the lowest level of gravitational force. Spring force level only affected time in target. Implications of these findings for the design of future cockpit displays will be discussed.

CDTI↗
DOE OSTI2020

Preliminary Target Selection for the DESI Quasar (QSO) Sample

The DESI survey will measure large-scale structure using quasars as direct tracers of dark matter in the redshift range 0.9 < z < 2.1 and using quasar Lyα forests at z > 2.1. In this work, we present two methods to select candidate quasars for DESI based on imaging in three optical (g, r, z) and two infrared (W1, W2) bands. The first method uses traditional color cuts and the second utilizes a machine-learning algorithm.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1971

Infrared spectrometry studies. Phase 4: Emittance spectra of selected targets from mission 108 airborne data

Infrared radiance measurements from geological materials were studied. These involved laboratory and field spectroscopic measurements, both on the ground and airborne. A proven, feasible system is presented for airborne use over terrains with minimal vegetation. It has been shown that the spectral emittance concepts can be utilized in emittance ratio imagery which depicts the silicate composition of the terrain.

Lyon, R. J. P.↗
NASA NTRS2006

Ground-Based Localization of Mars Rovers

The document discusses a procedure for localizing the Mars rovers in site frame, a locally defined reference frame on the Martian surface. MER onboard position within a site frame is estimated onboard and is based on wheel odometry. Odometry estimation of rover position is only reliable over relatively short distances assuming no wheel slip, sinkage, etc. As the rover traverses, its onboard estimate of position in the current site frame accumulates errors and will need to be corrected on occasions via relocalization on the ground (mission operations). The procedure provides a systematic process for ground operators to localize the rover. The method focuses on analysis of acquired images used to declare a site frame and images acquired post-drive. Target selection is performed using two main steps. In the first step, the user identifies features of interest from the images used to declare the current site. Each of the selected target s position in site frame is recorded. In the second step, post-traverse measurements of the selected features positions are recorded again, this time in rover frame, using images acquired post-traverse. In the third step, we transform the post-traverse target s positions to local level frame. In the fourth step, we compute the delta differences in the pre- and post-traverse target s position. In the fifth step, we analyze the delta differences with techniques that compute their statistics to determine the rover s position in the site frame.

Trebi-Ollennu, Ashitey↗
NASA NTRS2020

Results From the First Four Years of Aegis Autonomous Target-ing for Chemcam on Mars Science Laboratory and New Capability Planned for Supercam on Mars 2020 Rover

Autonomous Exploration for Gathering Increased Science (AEGIS) was uploaded on the NASA Mars Science Laboratory (MSL) Curiosity rover in 2015 for autonomous target selection. This paper presents results from the first four years of its regular opera-tion on Mars for autonomously selecting targets for the ChemCam remote geochemical spectrometer with a focus on the most recent findings. Results show that AEGIS has targeted the most desired material greater than 93% of the time vs 24% without onboard intelligent targeting. There has also been a notable increase in the rate of ChemCam observations. AE-GIS is also part of surface flight software for the NASA Mars 2020 Perseverance rover. This paper describes new AEGIS capabilities that will be availa-ble for autonomously targeting the SuperCam in-strument after the planned 18 February 2021 landing in Jezero crater on Mars.

Castano, R↗
DOE OSTI2025

FluxRETAP: a REaction TArget Prioritization genome-scale modeling technique for selecting genetic targets

MOTIVATION: Metabolic engineering is rapidly evolving as a result of new advances in synthetic biology tools and automation platforms that enable high throughput strain construction, as well as the development of machine learning tools (ML) for biology. However, selecting genetic engineering targets that effectively guide the metabolic engineering process is still challenging. ML can provide predictive power for synthetic biology, but current technical limitations prevent the independent use of ML approaches without previous biological knowledge. RESULTS: Here, we present FluxRETAP, a simple and computationally inexpensive method that leverages the prior mechanistic knowledge embedded in genome-scale models for suggesting targets for genetic overexpression, downregulation or deletion, with the final goal of increasing the production of a desired metabolite. This method can provide a list of desirable engineering targets that can be combined with current ML pipelines. FluxRETAP captured 100% of reaction targets experimentally verified to improve Escherichia coli isoprenol production, 50% of targets that experimentally improved taxadiene production in E. coli and ∼60% of genetic targets from a verified minimal constrained cut-set in Pseudomonas putida, while providing additional high priority targets that could be tested. Overall, FluxRETAP is an efficient algorithm for identifying a prioritized list of testable genetic and reaction targets. AVAILABILITY AND IMPLEMENTATION: FluxRETAP is implemented in python and released under the creative commons license. The implementation and code are freely available at: https://github.com/JBEI/FluxRETAP.

Czajka, Jeffrey J↗
DOE OSTI2023

The metallicity distribution in the core of the Sagittarius dwarf spheroidal: Minimising the metallicity biases

We present the metallicity and radial velocity for 450 bona fide members of the Sagittarius dwarf spheroidal (Sgr dSph) galaxy, measured from high-resolution spectra (R ≃ 18 000) obtained with FLAMES at the VLT. The targets were carefully selected (a) to sample the core of the main body of Sgr dSph while avoiding contamination from the central stellar nucleus, and (b) to prevent any bias on the metallicity distribution by selecting targets based on their Gaia parallax and proper motions. All the targets selected in this way were confirmed as radial velocity members. We used this sample to derive the first metallicity distribution of the core of Sgr dSph, which is virtually unaffected by metallicity biases. The observed distribution ranges from [Fe/H] ≃ -2.3 to [Fe/H] ≃ 0.0, with a strong, symmetric, and relatively narrow peak around [Fe/H] ≃ -0.5 and a weak and extended metal-poor tail, in which only 13.8 ± 1.9% of the stars have [Fe/H] < -1.0. We confirm previous evidence of correlations between chemical and kinematical properties of stars in the core of Sgr. In our sample, stars with [Fe/H] ≥ -0.6 display a lower velocity dispersion and a higher rotation amplitude than those with [Fe/H] < - 0.6, confirming previous suggestions of disk/halo structure for the progenitor of the system.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2008

Controlling the Growth of Future LEO Debris Populations with Active Debris Removal

Active debris removal (ADR) was suggested as a potential means to remediate the low Earth orbit (LEO) debris environment as early as the 1980s. The reasons ADR has not become practical are due to its technical difficulties and the high cost associated with the approach. However, as the LEO debris populations continue to increase, ADR may be the only option to preserve the near-Earth environment for future generations. An initial study was completed in 2007 to demonstrate that a simple ADR target selection criterion could be developed to reduce the future debris population growth. The present paper summarizes a comprehensive study based on more realistic simulation scenarios, including fragments generated from the 2007 Fengyun-1C event, mitigation measures, and other target selection options. The simulations were based on the NASA long-term orbital debris projection model, LEGEND. A scenario, where at the end of mission lifetimes, spacecraft and upper stages were moved to 25-year decay orbits, was adopted as the baseline environment for comparison. Different annual removal rates and different ADR target selection criteria were tested, and the resulting 200-year future environment projections were compared with the baseline scenario. Results of this parametric study indicate that (1) an effective removal strategy can be developed based on the mass and collision probability of each object as the selection criterion, and (2) the LEO environment can be stabilized in the next 200 years with an ADR removal rate of five objects per year.

Liou, J.-C.↗
NASA NTRS2012

Target Search & Selection for the DI/EPOXI Spacecraft

Upon completion of the Hartley 2 flyby in November 2010, the Deep Impact (DI) spacecraft resided in a solar orbit without possibility for gravity assist with any large body. Conservative estimates of remaining fuel were enough to provide only an 18 m/s impulse on the spacecraft. We present our method and results of our systematic scan of potential small body encounters for DI, and our criteria to narrow the selection to the asteroid 2002 GT as the target flyby body. The mission profile has two deterministic maneuvers to achieve the encounter, the first of which executed on November 25, 2011.

Grebow, Daniel J.↗