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At least 37 records · Page 2

A Heterogeneous System for Eagle Detection, Deterrent, and Wildlife Collision Detection for Wind Turbines (Final Technical Report)

This report summarizes the design, implementation, and test of an integrated system for automated detection and deterrence of eagles, with included wind turbine blade strike detection and imaging functionality. A machine learning approach was used in conjunction with a 360° camera system for automated detection and classification of golden eagles. This was developed using footage obtained from trained golden eagles and other raptors, in collaboration with wildlife biologists and professional bird handlers. Oregon State University developed a visual deterrent system, which uses inflatable anthropomorphic sculptures with random, kinetic motion to deter eagles, and conducted limited field testing on live eagles; the deterrent can be triggered by the visual detection of eagles using the vision system. Finally, a multi-sensor module was developed that is mounted at the turbine blade root. This module measures vibration and other motions to detect blade strikes, and an integrated on-blade camera captures an image of any impacting objects. Long-term, this blade strike detection system is intended to support an automatic monitoring and certification system for the eagle detection and deterent system. Independent field testing of each system component is described. Testing of the integrated system on an operational wind turbine was conducted across three separate field tests. This includes multi-day fields tests on a General Electric 1.5MW wind turbine at the National Renewable Energy Laboratory (NREL) National Wind Technology Center (NWTC) in Boulder, CO in October 2018 and July 2019; installation procedures, test procedures, and a summary of collected data are presented. A third multi-day on-turbine field test is also presented, which was performed using a General Electric 1.5MW wind turbine at the North American Wind Research and Training Center (NAWRTC) at Mesalands Community College, Tucumcari, NM in April 2019. Across these field tests, the vision system was demonstrated using unmanned aerial vehicles (UAV), and the eagle classification algorithm was not tested; the visual deterrent system was demonstrated, including automatic, remote deployment following surrogate visual detections; and, multi-sensor on-blade data was recorded across multiple wind turbine operational conditions and through more than 100 surrogate blade strikes using soft projectiles, including the successful demonstration of automatic image capture of striking objects. This data set was also used for offline development and validation of enhanced collision detection algorithms. As summarized in this report, the development and field validation of an integrated detection, deterrent, and blade collision detection system represents a critical proof of concept for future technology development of related detection and deterrent technologies, where both deterrent as well as collision detection recording devices are needed for future siting, monitoring, and operation of wind turbine installations, both onshore and offshore.

17 WIND ENERGY↗

Standoff Detection of Chemical Plumes Using Swept-ECQCL Remote Detection Technology: Results from EMRTC Complex Terrain Dual Tracer Experiment

As part of the Complex Terrain Dual Tracer Experiments performed in support of the LYNM program, a swept-wavelength external cavity quantum cascade laser (swept-ECQCL) remote detection system was deployed to measure chemical plume propagation with high temporal resolution. The swept-ECQCL remote detection technology was initially developed at PNNL, and is now under further development at Opticslah, LLC under SBIR funding from DOE (DOE SBIR Phase I Project DE-SC0019855, Remote Detection Technologies, Program Manager Chris Ramos). The swept-ECQCL technology provides a single-frequency infrared laser source which is rapidly scanned over a large wavelength range to measure the infrared absorption of gases, liquids, or solids. Analysis of the measured infrared absorption spectrum is used to detect, identify, and quantify the chemical species which are present. While most previous laser-based techniques used small wavelength tuning ranges to measure only a few isolated spectral lines of a few species, the swept-ECQCL provides the large tuning range needed to measure multiple species simultaneously, and to detect broad absorption features from large molecules or condensed phase materials. In addition, the swept-ECQCL systems have high enough spectral resolution and sensitivity to measure narrow lines of small molecules and determine isotope ratios. The remote detection system for gas plumes is based on the swept-ECQCL technology, and consists of a swept-ECQCL source, infrared detector, control electronics, and beam transmitting and alignment optics. The remote detection system directs the infrared output of the swept-ECQCL to a target retro reflector typically located at ~10-10,000 m distance. The swept-ECQCL wavelength is varied continuously over a large wavelength range (>1000 nm) at rates up to 1000 Hz. The swept ECQCL light reflected from the remote target is collected and focused onto an infrared photodetector. By measuring the detector signal continuously as the swept-ECQCL wavelength is varied, a time-series of absorption spectra are measured for the gases along the beam line of-sight. Based on analysis and fitting of the measured absorption spectra, the time-dependent chemical concentrations of species are determined. Multiple species and mixtures can be detected simultaneously, for all species with absorption features above the sensor noise floor. The sensor output is thus a continuous, high-speed record of identified chemicals along with their concentrations and isotope ratios of interest. The high-speed operation enables low-noise operation in conditions of atmospheric turbulence and allows tracking of fluctuating concentrations in transient chemical plumes as needed for reliable remote detection applications. All components operate with minimal cooling requirements and no cryogens are needed. In addition, the output infrared light is invisible with an intensity below the maximum permissible exposure (MPE) threshold of 100 mW/cm2 for these infrared wavelengths and thus eye safe. The measurement concept for plume detection using the swept-ECQCL remote detection system is as follows. The ECQCL beam is directed toward a remote retro-reflector, which reflects the beam back to the ECQCL system where it is focused onto an infrared photodetector. The line-of-sight from the ECQCL system to the retro-reflector defines the measurement path. The detected infrared signal is recorded continuously and detects the absorption of molecular species along the measurement path. Before a plume release, the system measures absorption from atmospheric constituents, which in this LWIR band consist primarily of lines from H 2 O and CO 2 , with additional weaker absorption from N 2 O, NH 3 , and O 3 possibly contributing. The system then measures any changes in absorption due to the tracer compounds when they enter the measurement path. The shape of absorption features is used to distinguish and identify the different tracer compounds, and the strength of the absorption is used to determine the path-integrated concentration – also called the column density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spectroelectrochemical Sensor for Spectroscopically Hard-to-detect Metals by in situ Formation of a Luminescent Complex Using Ru(II) as a Model Compound

Fast, robust, and cost-effective means of detecting spectroscopically inactive metal species are necessary for field detection and applications within a variety of areas including industry and the nuclear safeguards fields. A sensor based on spectroelectrochemistry is an excellent candidate to meet these needs as it provides improved selectivity for specifically quantifying metal ions by simultaneously monitoring at least two physio-chemical properties. Ruthenium was chosen as a model system for this study due to its spectroscopic and electrochemical characteristics as well as its relevance within the fuel cycle and industrial fields. Aqueous Ru displays multiple redox couples in which all available oxidation states have poor sensitivity for detection by visible absorption spectroscopy because of the low molar absorptivities. Ru can, however, form complexes with sensitizing ligands such as 2,2'-bipyridine, where the resulting [Ru(ligand)3]2+ complex displays a red luminescence with a high quantum yield of emission. This significantly improves detection limits for Ru and allows for the spectroelectrochemical detection of the otherwise hard-to-detect metal ion. This work explores the in-situ generation of Ru(bpy)3 complexes in simulated field samples and their subsequent spectroelectrochemical sensing using our sensor methodology.

Lines, Amanda M.↗

Trace explosive residue detection of HMX and RDX in post-detonation dust from an open-air environment

Explosives are often used in industry, geology, mining, and other applications, but it is not always clear what remains after a detonation or the fate and transport of any residual material. The goal of this study was to determine to what extent intact molecules of high explosive (HE) compounds are detectable and quantifiable from post-detonation dust and particulates in a field experiment with varied topography. We focused on HMX (1,3,5,7-Tetranitro-1,3,5,7-tetrazocane), which is less studied in field detonation literature, as the primary explosive material and RDX (1,3,5-Trinitroperhydro-1,3,5-triazine) as the secondary material. The experiment was conducted at Site 300, Lawrence Livermore National Laboratory’s Experimental Test Site, in California, USA. Two 20.4 kg and one 40.8 kg above ground explosions (primarily comprised of LX-14, an HMX-based polymer-bonded high explosive) were detonated on an open-air firing area on separate days. The complex terrain of the firing area (e.g., buildings, berm, low-height obstacles) was advantageous to study HE deposition in relation to plume dynamics. Three types of samples were collected up to 100 m away from each shot: surface swipes of aluminum plates, surface swipes of fixed objects, and filters from air samples. We used atmospheric flow tube-mass spectrometry (AFT-MS) to quantify picogram levels of molecular residue of HE material in the post-detonation dust. An aliquot of sample extract in methanol (e.g., 1 µL of 0.5 mL) was placed onto a resistive material and then thermally desorbed into the AFT-MS. We successfully detected and quantified both HMX and RDX in many of the samples. Based on mass (pg) detected and solution dilution, we back-calculated the mass collected on the swipe or filter (ng per sample). The aerial distribution of molecular residue was consistent with the path of the plume, which was strongly determined by wind speed and direction at the time of each shot. The quantity of material detected appeared to correlate more with distance from the shot and the wind conditions than with shot size. This study demonstrates that the picogram detection levels of AFT-MS are well-suited for quantification of analytes (e.g., HMX and RDX) in environmental samples.

atmospheric flow tube-mass spectrometry (AFT-MS), ↗

Development of nanosecond time-resolved infrared detection at the LEAF pulse radiolysis facility

When coupled with transient absorption spectroscopy, pulse radiolysis, which utilizes high-energy electron pulses from an accelerator, is a powerful tool for investigating the kinetics and thermodynamics of a wide range of radiation-induced redox and electron transfer processes. The majority of these investigations detect transient species in the UV, visible, or near-IR spectral regions. Unfortunately, the often-broad and featureless absorption bands in these regions can make the definitive identification of intermediates difficult. Time-resolved vibrational spectroscopy would offer much improved structural characterization, but has received only limited application in pulse radiolysis. In this paper, we describe in detail the development of a unique nanosecond time-resolved infrared (TRIR) detection capability for condensed-phase pulse radiolysis on a new beam line at the LEAF facility of Brookhaven National Laboratory. The system makes use of a suite of high-power, continuous wave external-cavity quantum cascade lasers as the IR probe source, with coverage from 2330-1051 cm⁻¹. The response time of the TRIR detection setup is ~40 ns, with a typical sensitivity of ~100 µOD after 4-8 signal averages using a dual-beam probe/reference normalization detection scheme. As a result, this new detection method has enabled mechanistic investigations of a range of radiation-induced chemical processes, some of which are highlighted here.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The third catalog of active galactic nuclei detected by the FERMI Large Area Telescope

The third catalog of active galactic nuclei (AGNs) detected by the Fermi-LAT (3LAC) is presented. It is based on the third Fermi-LAT catalog (3FGL) of sources detected between 100 MeV and 300 GeV with a Test Statistic greater than 25, between 2008 August 4 and 2012 July 31. The 3LAC includes 1591 AGNs located at high Galactic latitudes (|b|>10{sup ∘}), a 71% increase over the second catalog based on 2 years of data. There are 28 duplicate associations, thus 1563 of the 2192 high-latitude gamma-ray sources of the 3FGL catalog are AGNs. Most of them (98%) are blazars. About half of the newly detected blazars are of unknown type, i.e., they lack spectroscopic information of sufficient quality to determine the strength of their emission lines. Based on their gamma-ray spectral properties, these sources are evenly split between flat-spectrum radio quasars (FSRQs) and BL Lacs. The most abundant detected BL Lacs are of the high-synchrotron-peaked (HSP) type. About 50% of the BL Lacs have no measured redshifts. A few new rare outliers (HSP-FSRQs and high-luminosity HSP BL Lacs) are reported. The general properties of the 3LAC sample confirm previous findings from earlier catalogs. The fraction of 3LAC blazars in the total population of blazars listed in BZCAT remains non-negligible even at the faint ends of the BZCAT-blazar radio, optical, and X-ray flux distributions, which hints that even the faintest known blazars could eventually shine in gamma-rays at LAT-detection levels. The energy-flux distributions of the different blazar populations are in good agreement with extrapolation from earlier catalogs.

79 ASTRONOMY AND ASTROPHYSICS↗

Comparative Analysis of Soft-Error Detection Strategies: A Case Study with Iterative Methods

Undetected soft errors caused by transient bit flips can lead to silent data corruption (SDC), an undesirable outcome where invalid results pass for valid ones. This has motivated the design of soft error detectors to minimize SDCs. However, the detectors have been studied under different contexts, making comparative evaluation difficult. In this paper, we present the first comprehensive evaluation of four online soft error detection techniques in detecting the adverse impact of soft errors on iterative methods. We observe that, across five iterative methods, the detectors studied achieve high but not perfect detection rates. To understand the potential for improved detection, we evaluate a machine-learning based detector that takes as features that are the runtime features observed by the individual detectors to arrive at their conclusions. Our evaluation demonstrates improved but still far from perfect detection accuracy for the machine learning based detectors. This extensive evaluation demonstrates the need for designing error detectors to handle the evolutionary behavior exhibited by iterative solvers.

Silent data corruption, Soft error detection, Iter↗

FERMI- LAT GAMMA-RAY DETECTIONS OF CLASSICAL NOVAE V1369 CENTAURI 2013 AND V5668 SAGITTARII 2015

We report the Fermi Large Area Telescope (LAT) detections of high-energy (>100 MeV) γ -ray emission from two recent optically bright classical novae, V1369 Centauri 2013 and V5668 Sagittarii 2015. At early times, Fermi target-of-opportunity observations prompted by their optical discoveries provided enhanced LAT exposure that enabled the detections of γ -ray onsets beginning ∼2 days after their first optical peaks. Significant γ -ray emission was found extending to 39–55 days after their initial LAT detections, with systematically fainter and longer-duration emission compared to previous γ -ray-detected classical novae. These novae were distinguished by multiple bright optical peaks that encompassed the time spans of the observed γ -rays. The γ -ray light curves and spectra of the two novae are presented along with representative hadronic and leptonic models, and comparisons with other novae detected by the LAT are discussed.

79 ASTRONOMY AND ASTROPHYSICS↗

Time Series Discord Detection in Medical Data using a Parallel Relational Database [PowerPoint]

Recent advances in sensor technology have made continuous real-time health monitoring available in both hospital and non-hospital settings. Since data collected from high frequency medical sensors includes a huge amount of data, storing and processing continuous medical data is an emerging big data area. Especially detecting anomaly in real time is important for patients’ emergency detection and prevention. A time series discord indicates a subsequence that has the maximum difference to the rest of the time series subsequences, meaning that it has abnormal or unusual data trends. In this study, we implemented two versions of time series discord detection algorithms on a high performance parallel database management system (DBMS) and applied them to 240 Hz waveform data collected from 9,723 patients. The initial brute force version of the discord detection algorithm takes each possible subsequence and calculates a distance to the nearest non-self match to find the biggest discords in time series. For the heuristic version of the algorithm, a combination of an array and a trie structure was applied to order time series data for enhancing time efficiency. The study results showed efficient data loading, decoding and discord searches in a large amount of data, benefiting from the time series discord detection algorithm and the architectural characteristics of the parallel DBMS including data compression, data pipe-lining, and task scheduling.

47 OTHER INSTRUMENTATION↗

Condition monitoring and anomaly detection in cyber-physical systems

The modern industrial environment is equipping myriads of smart manufacturing machines where the state of each device can be monitored continuously. Such monitoring can help identify possible future failures and develop a cost-effective maintenance plan. However, it is a daunting task to perform early detection with low false positives and negatives from the huge volume of collected data. This requires developing a holistic machine learning framework to address the issues in condition monitoring of high priority components and develop efficient techniques to detect anomalies that can detect and possibly localize the faulty components. This paper presents a comparative analysis of recent machine learning approaches for robust, cost-effective anomaly detection in cyber-physical systems. While detection has been extensively studied, very few researchers have analyzed the localization of the anomalies. We show that supervised learning outperforms unsupervised algorithms. For supervised cases, we achieve near-perfect accuracy of 98% (specifically for tree-based algorithms). In contrast, the best-case accuracy in the unsupervised cases was 63%—the area under the receiver operating characteristic curve (AUC) exhibits similar outcomes as an additional metric.

Marfo, William↗

Non-target RNA depletion strategy to improve sensitivity of next-generation sequencing for the detection of RNA viruses in poultry

PCR-based assays have become the benchmark for detecting pathogens of poultry and other livestock; however, these techniques are limited in their ability to detect multiple infecting agents, provide limited genetic information on the pathogen, and, for RNA viruses, must be reviewed frequently to assure high sensitivity and specificity. In contrast, untargeted, high-throughput sequencing can rapidly detect all infecting agents in a sample while providing genomic sequence information to allow more in-depth characterization of viruses. Although next-generation sequencing (NGS) offers many advantages, one of its primary limitations is low sensitivity to pathogens given the abundance of host and other non-target sequences in sequencing libraries. We explored methods for improving the sensitivity of NGS to detect respiratory and enteric viruses in poultry from RNA extracts of swab samples. We employed commercial and custom-designed negative enrichment strategies to selectively deplete the most abundant rRNA reads from the host and non-target bacteria; host RNA was diminished from up to 40% of total reads to as low as 3%, and the total number of reads assigned to abundant bacterial classes were reduced greatly. Our treatment resulted in up to a 700-fold increase in the number of viral reads, detection of a greater number of viral agents, and higher average genome coverage for pathogens. Depletion assays added only 2 h to the NGS library preparation workflow. Custom depletion probe design offered significant cost savings (US$7–12 per sample) compared to commercial kits (US$30–50 per sample).

Parris, D. Joshua↗

Single-shot, multi-signature remote detection of uranium by filament-induced breakdown spectroscopy

Filament-induced breakdown spectroscopy (FIBS) is an attractive remote detection approach that is potentially applicable to nuclear materials, such as uranium (U). Simultaneous detection of atomic U and uranium monoxide features is demonstrated in a single laser shot with detection probabilities of 52.2% and 39.0%, respectively, and with a 1% false-alarm probability. It is shown that a nearly 100% detection probability can be reached with 1% false alarm probability in .1 second when using an 80-Hz laser and data acquisition system. Atomic U and UO signal features are identifiable in the remote measurement with comparable signal-to-background ratios, suggesting that, despite being broader than the U I emission line, the UO band is also suitable for remote detection of uranium by FIBS.

(020.3260) Isotope shifts, (140.3440) Laser-induce↗

Attribute and topology based change detection in a constellation of previously detected objects

A system that applies attribute and topology based change detection to networks of objects that were detected on previous scans of a structure, roadway, or area of interest. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, size, elongation, orientation, etc. The topology of the network of previously detected objects is maintained in a constellation database that stores attributes of previously detected objects and implicitly captures the geometrical structure of the network. A change detection system detects change by comparing the attributes and topology of new objects detected on the latest scan to the constellation database of previously detected objects.

97 MATHEMATICS AND COMPUTING↗

On Anomaly Detection for Transactive Energy Systems with Competitive Market

Two anomaly-detection criteria are proposed for transactive energy systems with competitive markets. Participants of transactive energy systems seek an optimal power allocation through hybrid economic-control methods to facilitate the integration of various types of distributed energy resources to power distribution systems. In transactive energy systems, every participant is assumed to be a rational entity, and consumers have diminishing marginal utility and suppliers have increasing marginal cost. With the first proposed anomaly-detection criterion, the monotonicity of marginal cost and marginal utility are examined. The impact of line flow constraints is also taken into consideration. Then, the second anomaly-detection criterion is proposed for TESs with marginal cost and marginal utility which change faster than a certain rate. The second criterion is more accurate than the first one for TES with marginal cost and marginal utility which change faster than a certain rate, but it requires the knowledge of that rate. Neither criteria requires more data than those necessary to find the optimal power allocation and the market-clear price in a transactive energy system. Therefore, the proposed criteria do not disclose any more data than necessary. As the monotonicity of marginal cost and marginal utility in a TES with competitive markets results in convex objective functions in an optimization problem and strongly convex ones when marginal cost and marginal utility changes faster than a certain rate, the two detection criteria are also applicable to anomaly detection of general convex optimization problems. Simulations are carried out to show the efficacy of the proposed criteria to detect anomalies caused by cyberattacks.

Wang, Peng↗

Polar Liquid Cloud Base Detection Algorithms for High Spectral Resolution or Micropulse Lidar Data

Liquid layers in clouds affect their microphysical processes, as well as the atmospheric energy budget. However, explicit liquid cloud base height (LCBH) detection algorithms using ground-based instruments (e.g., lidars) are currently absent in the literature. Most studies use either fixed lidar parameter thresholds or cloud base height data products that do not distinguish between ice and liquid, all of which might introduce inconsistencies and errors in the resolved LCBHs. In this paper, two LCBH detection algorithms are presented; the first algorithm uses the high spectral resolution lidar (HSRL) data, and yields satisfactory results. The second algorithm incorporates micropulse lidar (MPL) data for the LCBH detection. A 1-year long comparison of data gathered at Barrow, Alaska, and McMurdo Station, Antarctica, which includes other cloud base detection methodologies (ceilometer, MPL value-added product cloud base height, LCBHs detected using a fixed MPL depolarization threshold) emphasize the merits of the MPL algorithm.

Silber, Israel↗

Halo-independent tests of dark matter direct detection signals: local DM density, LHC, and thermal freeze-out

From an assumed signal in a Dark Matter (DM) direct detection experiment a lower bound on the product of the DM-nucleon scattering cross section and the local DM density is derived, which is independent of the local DM velocity distribution. This can be combined with astrophysical determinations of the local DM density. Within a given particle physics model the bound also allows a robust comparison of a direct detection signal with limits from the LHC. Furthermore, the bound can be used to formulate a condition which has to be fulfilled if the particle responsible for the direct detection signal is a thermal relic, regardless of whether it constitutes all DM or only part of it. We illustrate the arguments by adopting a simplified DM model with a Z{sup ′} mediator and assuming a signal in a future xenon direct detection experiment.

43 PARTICLE ACCELERATORS↗

Radiation Effects on Line Heat Detection Cable AP Hot Cells Fire Detection at Brookhaven National Laboratory

Hot cells are used to safely shield workers from high radiation environments while allowing a process to take place within the cell's shielded enclosure, often with the assistance of remote manipulators. The interior of a cell may not be accessible by personnel for years at a time, either due to the lingering radiation environment or due to the constant use of these specialized pieces of equipment. High radiation levels are known to cause undesirable effects and changes to different materials in varying degrees. Selecting equipment for a radiation environment requires an evaluation of materials used (preferably completed assembles), to ensure all interactions of materials are known and ensure that the equipment will have a high degree of reliability and functionality over the intended life of the facility. Hot cells contain systems to support the primary purpose of the enclosure. Fire detection is one such support system. Safety of hot cell operations often establish limits on the amounts of combustibles with the cells, but the presence of some combustible materials is unavoidable. Fire detection is provided to quickly detect a fire and summon manual intervention before damage is too great. Detection may also be used to initiate fire suppression systems. As a safety system, fire detection needs to remain functional to protect the facility throughout the facility's life. Equally important is that the false alarms from the fire detection are minimized to retain confidence in the alarm system and avoid unnecessary interruptions in the hot cell operations. There are many types of fire detection available with various pros and cons. Not all types of fire detection are suited for hot cell application.

36 MATERIALS SCIENCE↗

Supercontinuum Fourier transform spectrometry with balanced detection on a single photodiode

We demonstrate a method of combining a supercontinuum light source with a commercial Fourier transform spectrometer, using a novel approach to dual-beam balanced detection, implemented with phase-sensitive detection on a single light detector. A 40 dB reduction in the relative intensity noise is achieved for broadband light, analogous to conventional balanced detection methods using two matched photodetectors. Unlike conventional balanced detection, however, this method exploits the time structure of the broadband source to interleave signal and reference pulse trains in the time domain, recording the broadband differential signal at the fundamental pulse repetition frequency of the supercontinuum. The method is capable of real-time correction for instability in the supercontinuum spectral structure over a broad range of wavelengths and is compatible with commercially designed spectrometers. A proof-of-principle experimental setup is demonstrated for weak absorption in the 1500-1600 nm region.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗