Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “target detection”

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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Rapid Electrochemical Detection and Identification of Microbiological and Chemical Contaminants for Manned Spaceflight Project

Microbial control in the spacecraft environment is a daunting task, especially in the presence of human crew members. Currently, assessing the potential crew health risk associated with a microbial contamination event requires return of representative environmental samples that are analyzed in a ground-based laboratory. It is therefore not currently possible to quickly identify microbes during spaceflight. This project addresses the unmet need for spaceflight-compatible microbial identification technology. The electrochemical detection and identification platform is expected to provide a sensitive, specific, and rapid sample-to-answer capability for in-flight microbial monitoring that can distinguish between related microorganisms (pathogens and non-pathogens) as well as chemical contaminants. This will dramatically enhance our ability to monitor the spacecraft environment and the health risk to the crew. Further, the project is expected to eliminate the need for sample return while significantly reducing crew time required for detection of multiple targets. Initial work will focus on the optimization of bacterial detection and identification. The platform is designed to release nucleic acids (DNA and RNA) from microorganisms without the use of harmful chemicals. Bacterial DNA or RNA is captured by bacteria-specific probe molecules that are bound to a microelectrode, and that capture event can generate a small change in the electrical current (Lam, et al. 2012. Anal. Chem. 84(1): 21-5.). This current is measured, and a determination is made whether a given microbe is present in the sample analyzed. Chemical detection can be accomplished by directly applying a sample to the microelectrode and measuring the resulting current change. This rapid microbial and chemical detection device is designed to be a low-cost, low-power platform anticipated to be operated independently of an external power source, characteristics optimal for manned spaceflight and areas where power and computing resources are scarce.

Pierson, Duane↗
NASA NTRS2003

Search for X-Ray Emission in the Nearest Known Brown Dwarf

The XMM observation were obtained on 2001 January 07-08 for 51767 s. The Optical Monitor (OM) was used with the V filter for 4 exposures of 5000 s each in imaging mode. We used the data given by the OM to confirm the presence of the source in the field of view. The European Photon Imaging Camera (EPIC) MOS 1 and MOS2 were used 48724 s each in prime full window mode with 2.5 s time resolution. The EPIC PN was used 46618 s in prime full window mode with 73.4 ms time resolution. The X-ray source closest to the expected position of our target is offset by delta R.A=2.5 arcsec and delta Dec=-28.37 arcsec. This offset is high in comparison with the 0.4 arcsec observed with the optical data. So at this point we already knew that the target was not detected. To confirm that conclusion, we performed the identification of all X-ray sources in the field of view by comparing source to source our image with the one obtained by Rutledge et al. with Chandra. This allowed us to identify all the X-ray sources in our field of view in an area of 20 arcsec times 10 arcsec centered on the expected coordinates of LP944-20. We were then able to conclude that the target was not detected during this observation. This result allowed us to determine a new and better 3 sigma upper limit of X-Ray emission for this object. We have also derived duty cycles for X-ray flares as a function of X-ray luminosity by comparing the XMM data with Chandra and ROSAT data. One student has been supported with the grant during four months (Herve Bouy). A Sun workstation was purchased for him.

Martin, Eduardo↗
DOE OSTI2020

An Intelligent Adaptable Monitoring Package. Final Report

The “Intelligent Adaptable Monitoring Package” project was a four-year effort that demonstrated the feasibility of integrated sensing packages at tidal and wave energy sites. Such integration is generally required by the breadth of sensors required to understand environmental effects at marine energy sites and the operational difficulty of deploying, maintaining, and recovering such sensors. Over the course of the project, the Adaptable Monitoring Package (AMP) was deployed in multiple settings, each corresponding to a project budget period: - Budget Period 1: Demonstration of cabled deployment at Pacific Northwest National Laboratory’s Marine Science Laboratory. The deployment highlighted AMP hardware endurance over a 4-month deployment in a tidally-dominated environment and laid the groundwork for machine learning algorithms to detect and classify targets present in active sonar data. - Budget Period 2: Demonstration of an autonomous deployment at PacWave South off the coast of Newport, Oregon. The deployment highlighted the stability of AMP hardware and software, with the autonomous package collecting data on a duty cycle over a 1.5-month deployment. - Budget Period 3: Demonstration of an autonomous deployment powered by a wave energy converter at the U.S. Navy’s Wave Energy Test Site. The deployment highlighted the potential of wave energy to power ocean observatories and led to the development of machine learning algorithms to detect and classify targets in optical camera data. In aggregate, this project’s greatest success was demonstrating the AMP’s flexibility in a range of deployment scenarios. Each budget period represented a “first of a kind” demonstration of integrated instrumentation – cabled AMP, autonomous AMP, wave-energy powered AMP – and each deployment helped to identify and set goals for the next. Further, despite the exploratory nature of these deployments, each one achieved high system up-time and proved that flexible integration of multiple sensors in a single package represents a viable strategy for marine energy environmental monitoring. The key lessons learned from the project are: - Without continuous power, either from a shore cable or in situ source, many of the benefits of integration are lost (If continuous power is not available, the ability to detect rare events is lost, as is the ability to minimize the risk of behavioral changes through adaptive sensing. However, even on a duty cycle, there is still value in being able to acquire synchronous data from multiple sensors.); and - Observations from a moving platform present substantially greater data processing challenges than those from stationary platforms. Finally, these deployments also demonstrate an important truth: successful integration alone does not guarantee that relevant data are collected. To grow the knowledge base about environmental interactions with marine energy converters, integrated systems, like the AMP, need to include the right sensor mix and connect the data pipelines to effective processing algorithms. These deployments establish a strong foundation for future collaborations with the environmental research community: not only to understand the environmental effects of marine energy, but also to improve our general ability to study life in the sea.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Confirmation and Quantification of Gas Flow into Capsules

Inertial confinement fusion experiments require a fuel filled target. At the National Ignition Facility (NIF), these targets are filled through a capsule fill tube assembly (CFTA). While fabricating these assemblies, it is possible to plug the fill tube with glue, which would render the CFTA and eventual target unusable. Historically, this plugging was first detectable in a finished target after considerable resources had been expended. Herein, this paper presents a method for not only detecting a plug in the fill tube before the CFTA is assembled into a target, but also characterizing gas flow through the fill tube, which can help NIF operations prepare to expend each target.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1992

Closed-loop autonomous docking system

An autonomous docking system is provided which produces commands for the steering and propulsion system of a chase vehicle used in the docking of that chase vehicle with a target vehicle. The docking system comprises a passive optical target affixed to the target vehicle and comprising three reflective areas including a central area mounted on a short post, and tracking sensor and process controller apparatus carried by the chase vehicle. The latter apparatus comprises a laser diode array for illuminating the target so as to cause light to be reflected from the reflective areas of the target; a sensor for detecting the light reflected from the target and for producing an electrical output signal in accordance with an image of the reflected light; a signal processor for processing the electrical output signal in accordance with an image of the reflected light; a signal processor for processing the electrical output signal and for producing, based thereon, output signals relating to the relative range, roll, pitch, yaw, azimuth, and elevation of the chase and target vehicles; and a docking process controller, responsive to the output signals produced by the signal processor, for producing command signals for controlling the steering and propulsion system of the chase vehicle.

Dabney, Richard W.↗
DOE OSTI2020

Detection of active and latent infections with microfluidic devices and systems thereof

The present invention relates to methods of detecting one or more targets of interest in a sample. In one instance, the target can be correlated to an active infection (e.g., by a virus and/or a bacterium). Methods can include treating the sample with a dissociation agent, thereby releasing the target of interest for more accurate detection (e.g., by use of a sedimentation-based centrifugal microfluidic devices). Also described herein are microfluidic devices and systems for use with a dissociation agent.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2011

The WIRED Survey: Infrared Excesses in the SDSS DR7 White Dwarf Catalog - 2

With the launch of the Wide-field Infrar.ed Survey Explorer (WISE), a new era of detecting planetary debris and brown dwarfs (BDs) around white dwarfs (WDs) has begun with the WISE InfraRed Excesses around Degenerates (WIRED) Survey. The WIRED Survey is sensitive to substellar objects and dusty debris around WDs out to distances exceeding 100 pc, well beyond the completeness level of local WDs. In this paper, we present a cross-correlation of the preliminary Sloan Digital Sky Survey (SDSS) Data Release 7 (DR7) WD catalog between the WISE, Two-Micron All Sky Survey (2MASS), UKIRT Infrared Deep Sky Survey (UKIDSS), and SDSS DR7 photometric catalogs. From -18,000 input targets, there are WISE detections comprising 344 "naked" WDs (detection of the WD photosphere only), 1020 candidate WD+M dwarf binaries, 42 candidate WD+BD systems, 52 candidate WD+dust disk systems, and 69 targets with indeterminate infrared excess. We classified all of the detected targets through spectral energy distribution model fitting of the merged optical, near-IR, and WISE photometry. Some of these detections could be the result of contaminating sources within the large (approx. 6") WISE point-spread function; we make a preliminary estimate for the rates of contamination for our WD+BD and WD+disk candidates and provide notes for each target of interest. Each candidate presented here should be confirmed with higher angular resolution infrared imaging or infrared spectroscopy. We also present an overview of the observational characteristics of the detected WDs in the WISE photometric bands, including the relative frequencies of candidate WD+M, WD+BD, and WD+disk systems.

Debes, John H.↗
DOE OSTI2023

PathTrace and MPVEASI: A Path Analysis Comparative Validation Study

Developed in 2018, PathTrace is a software package built with the intention of making path analysis simple and intuitive. PathTrace is a top-down pathway analysis software where a user is able to explore vulnerable pathways into a facility. The intention of utilizing a software tool like PathTrace is to characterize an existing physical protection system (PPS) and to upgrade the system to achieve a high level of response interruption, or probability of interruption (P I ) of the adversary. There are four steps for conducting path analysis using PathTrace. The first step is to identify an image to use to build the model and scale the model within PathTrace using a section of known distance (wall or fence perimeter, for example). The scaling process will produce a grid of cells through which the user is able to build a model. The second step is to fill out the grid of cells with four categories of materials: Barriers, Detection Areas, Jumps, and Targets. These materials apply associated delay and detection values to the cells in which they are applied. The third step is to represent the adversary and response forces. The adversaries are represented by their capabilities in interacting with the materials identified in step two, and the response is represented by how quickly they will be able to respond to an adversary attack. Finally, the user is able to take all of the information from the previous three steps and perform a Most Vulnerable Path (MVP) analysis. In this stage, the user is able to visualize vulnerable adversary pathways and reason about how to upgrade these pathways to provide a high level of P I .

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

NuSTAR broad-band X-ray observation campaign of energetic pulsar wind nebulae in synergy with VERITAS, HAWC and Fermi gamma-ray telescopes

We report recent progress on the on-going NuSTAR observation campaign of 8 TeV-detected middle-aged pulsar wind nebulae (PWNe). This campaign constitutes a major part of our NuSTAR study of some of the most energetic TeV sources in our Galaxy detected by VERITAS and HAWC. NuSTAR is the first focusing X-ray telescope operating above 10 keV in space with sub-arcminute angular resolution. Broad-band X-ray imaging and spectroscopy data, obtained by NuSTAR, allow us to probe sub-PeV electron populations through detecting synchrotron X-ray radiation. Our targets include PeVatron candidates detected by HAWC, the Boomerang nebula, PWNe crushed by supernova remnant shocks (or relic PWNe) and G0.9‚0.1 in the Galactic Center. Combined with Fermi-LAT data and available TeV data, we aim to provide a complete, multi-wavelength view of a diverse class of middle-aged (~10–100 kyrs old) PWNe. Our NuSTAR analysis detected hard X-ray emission from the Eel and Boomerang PWNe and characterized their broad-band X-ray spectra most accurately. We plan to apply both time-evolution and multi-zone PWNe models to multi-wavelength spectral energy distribution (SED) data over the radio, X-ray, GeV and TeV bands. In this proceeding, we will review our observation campaign and discuss the preliminary results for some PWNe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Clinical 6 MV X-Ray Facility Photo-Neutron/Fission Interrogations with TMFD Sensors

Detection of several targets (U, Be, D2O) of interest to national security has been achieved at Purdue University’s 6 MV (~104 R/h) X-Ray clinical linear accelerator (CLINAC), from photoneutron/fission induced neutron signatures using a Centrifugally Tensioned Metastable Fluid Detector (CTMFD). Traditional neutron detection schemes were saturated and ineffective under the intense (to ~104 R/h) photon environment; however, the CTMFD sensor technology was capable of measuring the relatively insignificant (~10-12x lower intensity) neutron field produced from 6 MeV-end point X-Ray beam interactions with the CLINAC components and surroundings. This is in stark contrast to published results based on conventional belief for immeasurable neutron dose in 6 MV CLINAC facilities. Photoneutron and photofission neutron production rates were detected and analyzed at various standoffs from the isocenter, with and without special nuclear material (SNM) related targets ranging in mass from 5 g of Be, to ~0.6 kg of UO2. It was confirmed that 6 MV X-Ray photons do result in measurable neutron dose above normal cosmic background. Additionally, in threshold mode, the CTMFD operating under a tensioned metastable pressure of -5bar, enabled conclusive rejection of background photoneutrons, while enabling the rapid detection of: Be, D2O, C and U targets within seconds to minutes while operating in and around 104 R/h photon fields.

Ozerov, Stepan↗
NASA NTRS1983

Investigation of image enhancement techniques for the development of a self-contained airborne radar navigation system

This study was devoted to an investigation of the feasibility of applying advanced image processing techniques to enhance radar image characteristics that are pertinent to the pilot's navigation and guidance task. Millimeter (95 GHz) wave radar images for the overwater (i.e., offshore oil rigs) and overland (Heliport) scenario were used as a data base. The purpose of the study was to determine the applicability of image enhancement and scene analysis algorithms to detect and improve target characteristics (i.e., manmade objects such as buildings, parking lots, cars, roads, helicopters, towers, landing pads, etc.) that would be helpful to the pilot in determining his own position/orientation with respect to the outside world and assist him in the navigation task. Results of this study show that significant improvements in the raw radar image may be obtained using two dimensional image processing algorithms. In the overwater case, it is possible to remove the ocean clutter by thresholding the image data, and furthermore to extract the target boundary as well as the tower and catwalk locations using noise cleaning (e.g., median filter) and edge detection (e.g., Sobel operator) algorithms.

Phatak, A. V.↗
NASA NTRS2010

Multi-Stage System for Automatic Target Recognition

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an artificial neural network classifier. The multi-stage system allows tuning the detection sensitivity and the identification specificity individually in each stage. It is easier to achieve optimized ATR operation based on its specific goal. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar and video image datasets.

Chao, Tien-Hsin↗
DOE OSTI2025

DELVE-DEEP Survey: The Faint Satellite System of NGC 55

We report the first comprehensive census of the satellite dwarf galaxies around NGC 55 (2.1 Mpc) as a part of the DECam Local Volume Exploration DEEP (DELVE-DEEP) survey. NGC 55 is one of four isolated, Magellanic analogs in the Local Volume around which DELVE-DEEP aims to identify faint dwarfs and other substructures. We employ two complementary detection methods: one targets fully resolved dwarf galaxies by identifying them as stellar overdensities, while the other focuses on semiresolved dwarf galaxies, detecting them through shredded unresolved light components. As shown through extensive tests with injected galaxies, our search is sensitive to candidates down to M V ≲ −6.6 and surface brightness μ ≲ 28.5 mag arcsec 2 , and ∼80% complete down to M V ≲ −7.8. We do not report any new confirmed satellites beyond two previously known systems, ESO 294–010 and NGC 55-dw1. We construct the satellite luminosity function of NGC 55 and find it to be consistent with the predictions from cosmological simulations. As one of the first complete luminosity functions for a Magellanic analog, our results provide a glimpse of the constraints on low-mass-host satellite populations that will be further explored by upcoming surveys, such as the Vera C. Rubin Observatory’s Legacy Survey of Space and Time.

Medoff, Jonah [Univ. of Chicago, IL (United States↗
NASA NTRS2003

"Smoke": Characterization Of Smoke Particulate For Spacecraft Fire Detection

The "Smoke" experiment is a flight definition investigation that seeks to increase our understanding of spacecraft fire detection through measurements of particulate size distributions of preignition smokes from typical spacecraft materials. Owing to the catastrophic risk posed by even a very small fire in a spacecraft, the design goal for spacecraft fire detection is to detect the fire as quickly as possible, preferably in the preignition phase before a real flaming fire has developed. Consequently the target smoke for detection is typically not soot (typical of established hydrocarbon fires) but instead, pyrolysis products, and recondensed polymer particles. At the same time, false alarms are extremely costly as the crew and the ground team must respond quickly to every alarm. The U.S. Space Shuttle (STS: Space Transportation System) and the International Space Station (ISS) both use smoke detection as the primary means of fire detection. These two systems were designed in the absence of any data concerning low-gravity smoke particle (and background dust) size distributions. The STS system uses an ionization detector coupled with a sampling pump and the ISS system is a forward light scattering detector operating in the near IR. These two systems have significantly different sensitivities with the ionization detector being most sensitive (on a mass concentration basis) to smaller particulate and the light scattering detector being most sensitive to particulate that is larger than 1 micron. Since any smoke detection system has inherent size sensitivity characteristics, proper design of future smoke detection systems will require an understanding of the background and alarm particle size distributions that can be expected in a space environment.

Urban, David L.↗
NASA NTRS2016

Predictable Patterns in Planetary Transit Timing Variations and Transit Duration Variations Due to Exomoons

We present new ways to identify single and multiple moons around extrasolar planets using planetary transit timing variations (TTVs) and transit duration variations (TDVs). For planets with one moon, measurements from successive transits exhibit a hitherto undescribed pattern in the TTV-TDV diagram, originating from the stroboscopic sampling of the planet's orbit around the planet-moon barycenter. This pattern is fully determined and analytically predictable after three consecutive transits. The more measurements become available, the more the TTV-TDV diagram approaches an ellipse. For planets with multiple moons in orbital mean motion resonance (MMR), like the Galilean moon system, the pattern is much more complex and addressed numerically in this report. Exomoons in MMR can also form closed, predictable TTV-TDV figures, as long as the drift of the moons' pericenters is suciently slow.We find that MMR exomoons produce loops in the TTV-TDV diagram and that the number of these loops is equal to the order of the MMR, or the largest integer in the MMR ratio.We use a Bayesian model and Monte Carlo simulations to test the discoverability of exomoons using TTV-TDV diagrams with current and near-future technology. In a blind test, two of us (BP, DA) successfully retrieved a large moon from simulated TTV-TDV by co-authors MH and RH, which resembled data from a known Kepler planet candidate. Single exomoons with a 10 percent moon-to-planet mass ratio, like to Pluto-Charon binary, can be detectable in the archival data of the Kepler primary mission. Multi-exomoon systems, however, require either larger telescopes or brighter target stars. Complementary detection methods invoking a moon's own photometric transit or its orbital sampling effect can be used for validation or falsification. A combination of TESS, CHEOPS, and PLATO data would offer a compelling opportunity for an exomoon discovery around a bright star.

stroboscopic sampling↗