Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “IDENTIFICATION”

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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Testing Novel CR-39 Detector Deployment System for Identification of Subsurface Fractures, Soda Springs, ID

The Environmental Protection Agency (EPA) has teamed with Battelle Energy Alliance, LLC (BEA) at Idaho National Laboratory (INL) to facilitate further testing of geologic-fracture-identification methodology at a field site near the Monsanto Superfund Site located in Soda Springs, Idaho. INL has the necessary testing and technological expertise to perform this work. Battelle Memorial Institute (BMI) has engaged INL to perform this work through a Work for Others (WFO) Agreement. This study continues a multi-year collaborative effort between INL and EPA to test the efficacy of using field deployed Cr-39 radon in soil portals. This research enables identification of active fractures capable of transporting contaminants at sites where fractures are suspected pathways into the subsurface. Current state of the art methods for mapping fracture networks are exceedingly expensive and notoriously inaccurate. The proposed WFO will evaluate the applicability of using cheap, readily available, passive radon detectors to identify conductive geologic structures (i.e. fractures, and fracture networks) in the subsurface that control the transport of contaminants at fracture-dominated sites. The proposed WFO utilizes proven off-the-shelf technology in the form of CR-39 radon detectors, which have been widely deployed to detect radon levels in homes and businesses. In an existing collaborative EPA/INL study outside of this workscope, CR-39 detectors are being utilized to determine the location of active transport fractures in a fractured granitic upland adjacent to a landfill site at the Fort Devens, MA that EPA-designated as National Priorities List (NPL) site. The innovative concept of using an easily deployed port that allows the CR-39 to measure the Rn-222 in the soil or alluvium above the fractured rock, while restricting atmospheric Rn-222 and soil sourced Ra from contaminating the detector is unique to INL and EPA approach previously developed. By deploying a series of these inexpensive detector-casing combinations statistical samples of the Rn-222 flux can be measured, elucidating the most communicative fractures (i.e. fractures that are actively transporting water and gasses). The Rn-222 measurements can then be used as an input to create a more accurate conceptual model to be used for transport modeling and related cleanup activities. If the team’s approach is demonstrated to be applicable to a wide variety of rock types and soil conditions it might potentially offer significant cost saving without a reduction in data quality at Monsanto Superfund and other sites underlain by fracture-dominated bedrock.

58 GEOSCIENCES↗
DOE OSTI2017

MODAL TRACKING of A Structural Device: A Subspace Identification Approach

Mechanical devices operating in an environment contaminated by noise, uncertainties, and extraneous disturbances lead to low signal-to-noise-ratios creating an extremely challenging processing problem. To detect/classify a device subsystem from noisy data, it is necessary to identify unique signatures or particular features. An obvious feature would be resonant (modal) frequencies emitted during its normal operation. In this report, we discuss a model-based approach to incorporate these physical features into a dynamic structure that can be used for such an identification. The approach we take after pre-processing the raw vibration data and removing any extraneous disturbances is to obtain a representation of the structurally unknown device along with its subsystems that capture these salient features. One approach is to recognize that unique modal frequencies (sinusoidal lines) appear in the estimated power spectrum that are solely characteristic of the device under investigation. Therefore, the objective of this effort is based on constructing a black box model of the device that captures these physical features that can be exploited to “diagnose” whether or not the particular device subsystem (track/detect/classify) is operating normally from noisy vibrational data. Here we discuss the application of a modern system identification approach based on stochastic subspace realization techniques capable of both (1) identifying the underlying black-box structure thereby enabling the extraction of structural modes that can be used for analysis and modal tracking as well as (2) indicators of condition and possible changes from normal operation.

42 ENGINEERING↗
DOE OSTI2018

Performance of b Jet Identification at $\sqrt{s}$ = 13 TeV with the ATLAS Detector at CERN [Slides]

The efficient identification of jets from bottom quarks (b-jets) is one of the most important techniques for many physics analyses at the Large Hadron Collider, including studies of the Higgs boson, the top quark, and searches beyond the Standard Model. The performance is characterized by b-tagging efficiency (probability to identify a b-jet as such) and the mistag rate (probability to mistakenly accept a non-b-jet).The mistag occurs as a result of finite detector resolution, presence of long-lived particles, and material interactions. As these effects can be different between the experimental data and Monte Carlo (MC) simulation, it is important to measure the b-tagging performance in data and derive the MC correction factors. I will describe various methods to measure the performance of b jet identification in pp collisions at √s = 13 TeV with the ATLAS detector and will report on Direct Tag method which is recently developed in the ATLAS collaboration for Light jet calibration.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Software Requirement Document: Benchmarking Algorithms for RadioNuclide Identification (BARNI)

The Department of Energy (DOE) Office of Nuclear Smuggling Detection and Deterrence (NSDD) seeks to improve the performance of RadioIsotope Identification Devices (RIIDs). RIIDs enable users to identifying threat nuclides in applications such as secondary search, facility inspection, and emergency response. As part of this effort NSDD has developed Replicative Assessment of Spectroscopic Equipment (RASE), an open-source tool which generates synthetic spectra and analyzes them with vendor’s radionuclide identification software in order to evaluate performance.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2019

Software Requirements Document: Benchmarking Algorithm for RadioNuclide Identification (BARNI)

This document provides the requirements for the Benchmark Algorithm for Radio-Nuclide Identification (BARNI) software, an open-source tool for comparing radionuclide identification algorithm performance. It specifies the requirements for the user interface, maintainability, documentation and testing. In addition, this document outlines the core functionality of the product, which will align with the needs of the Office of Nuclear Smuggling Detection and Deterrence (NSDD). Specifically, these include interoperability with RASE, and compatibility with the FLIR R400.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Minimum Resolution Requirements for Gamma Identification Algorithms

Each year there are millions of dollars spent on the research and production of high-resolution detectors. This research indicates that the pursuit of higher resolution detectors is not always necessary. The terminal resolution of a NaI detector, or highest detector resolution, at which identification algorithms fail to identify highly enriched uranium (HEU) was evaluated using GADRAS, Genie, and GammaVision. GADRAS employs a template matching algorithm, while Genie and GammaVision utilize a mathematical approach for peak search and identification. The NaI spectra utilized for evaluation were generated using the GADRAS Inject tab and source modeling functions. Each spectrum included terrestrial and cosmic background from Dallas, TX. The resolutions for each spectrum were increased from a default 8.92% to a point where each algorithm would fail to identify 235 U from a HEU source. Six different source configurations were used in this research: bare HEU, 50% shielded HEU, 90% shielded HEU, bare HEU with an interference source of 99 mTc, bare HEU with 99 mTc both shielded 50%, and bare HEU with 99 mTc both shielded 90%. T

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Random Forest Optimization for Radionuclide Identification

Radionuclide identification through gamma-ray spectroscopy is an indispensable tool in combatting the illicit smuggling of nuclear material. The radionuclide identification devices used in the field need to provide ready-made answers to non-experts, and therefore require sophisticated algorithms that can interpret the underlying data. We investigated the Random Forest classifier as a tool for identifying the radionuclide that is consistent with the data. We were provided with training and validations data sets and used them to optimize the two hyperparameters of the classifiers: maximum features required, and minimum samples used to split each node. The F1 score, a harmonic mean of precision and recall, was used to evaluate the performance of each built classifier. We found the optimal performance with minimum samples of 5 and maximum features of 50, with the F1 score of 0.95.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Gamma Spectroscopy Detector Candidates and Radioisotope Identification Algorithms for Use in National Security Applications

In 2006, the United States Congress mandated for the Department of Homeland Security (DHS) to screen all cargo containers to protect against terrorist acts and ensure the safety and security of the nation. Containers are screened by gamma and neutron detectors to ensure threat material is not smuggled into the country. However, because commerce is radioactive, detecting the presence of radioactive materials is not sufficient in ensuring the safety and security of the nation. Radioactive materials must also be identified in real time, thus distinguishing threat sources (Uranium-235 and Plutonium-230) from non-threat sources (kitty litter, pot ash, medical isotopes). Screening cargo containers can be considered a two-step process (1) alerting to the presence of radioactive material when gamma counts exceed a threshold setting, and (2) once alerted, identifying the type of radioactive material, which is done by collecting a gamma spectra and analyzing it with an analysis tool/algorithm. For this reason, it is important to evaluate not only emerging technology in neutron and gamma detection, but also investigate new advances in algorithm development for radioisotope identification (RIID). New candidates in detection and on-board algorithm analysis might offer opportunities to make the scanning, detection, and identification process more efficient while still ensuring the health and safety of the public. This research will investigate emerging technology in radiation detection focused on gamma spectroscopy capabilities and RIID algorithms for DHS applications.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

Likelihood-Based Particle Identification in SBND

Accurate particle identification is crucial in any high-energy physics experiment, allowing scientists to understand the unique interactions and mechanisms at play in a detector. In this project, I develop and study a likelihood-based particle identification (PID) algorithm for the Short-Baseline Near Detector, which offers a more physically motivated strategy for PID.

Vanderwaal, Sophia [U. Alabama, Huntsville]↗
DOE OSTI2016

Automated Reconstruction, Signal Processing and Particle Identification in DUNE

Liquid Argon TPC (LArTPC) technology is increasingly prevalent in large-scale detectors de- signed to observe neutrino scattering events induced by accelerators or by natural sources. LArTPCs consist of a very high fraction of active detector material with spatial resolutions on the order of a few millimeters. Three-dimensional interactions are imaged in multiple two- dimensional views by the process of projection onto planes of wires. The goal of automated reconstruction is to correctly classify each neutrino scattering event by the flavor of the incoming neutrino, to separate charged-current events from neutral-current and other backgrounds, and to measure the energies of the incoming neutrinos. Detection of neutrinos from supernova bursts and also searching for nucleon decay are important uses of automated reconstruction algorithms. Be- cause the amount of spatial detail is high and the amount of scattering is high, this reconstruction presents many challenges that are now being investigated with sophisticated techniques. Signal processing, track and shower identification, particle identification, and event classification by a variety of innovative algorithms are reviewed

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Automated Reconstruction, Signal Processing and Particle Identification in DUNE

Liquid Argon TPC (LArTPC) technology is increasingly prevalent in large-scale detectors designed to observe neutrino scattering events induced by accelerators or by natural sources. LArTPCs consist of a very high fraction of active detector material with spatial resolutions on the order of a few millimeters. Three-dimensional interactions are imaged in multiple two-dimensional views by the process of projection onto planes of wires. The goal of automated reconstruction is to correctly classify each neutrino scattering event by the flavor of the incoming neutrino, to separate charged-current events from neutral-current and other backgrounds, and to measure the energies of the incoming neutrinos. Detection of neutrinos from supernova bursts and also seaching for nucleon decay are important uses of automated reconstruction algorithms. Because the amount of spatial detail is high and the amount of scattering is high, this reconstruction presents many challenges that are now being investigated with sophisticated techniques.Signal processing, track and shower identification, particle identification, and event classification by a variety of innovative algorithms are reviewed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

An empirical DNA-based identification of morphologically similar snappers (Lutjanus campechanus, Lutjanus purpureus) using a versatile bioinformatics workflow for the discovery and analysis of informative single-nucleotide polymorphisms

The commercially important speciesLutjanus campechanus(Northern/Gulf red snapper) andLutjanus purpureus(Southern/Caribbean red snapper) are the protagonists of a decade’s long taxonomic debate over their species delimitation, due in part to partial habitat overlap, extensive morphological similarity, and the lack of resolution when applying canonically reliable DNA barcoding approaches. In this study, we leveraged publicly available RAD-Seq data forL. campechanusandL. purpureusto identify species-informative single‐nucleotide polymorphisms (SNPs) at the genome scale that were successful in distinguishing the Northern and Southern red snappers, while also detecting individuals exhibiting introgression. This 4-step empirical approach demonstrates the value of applying novel bioinformatics pipelines to existing genome-scale data to maximize the distillation of informative subsets. Our results facilitate economically relevant species identification in addition to confirming or challenging species identifications for specimens with data in public databases. These findings and their applications will benefit future sustainability strategies and broader research questions surrounding these overfished and evolutionarily entangled snapper species.

Environmental Sciences & Ecology↗
DOE OSTI2016

Phylogenetic Analyses of Shigella and Enteroinvasive Escherichia coli for the Identification of Molecular Epidemiological Markers: Whole-Genome Comparative Analysis Does Not Support Distinct Genera Designation

As a leading cause of bacterial dysentery, Shigella represents a significant threat to public health and food safety. Related, but often overlooked, enteroinvasive Escherichia coli (EIEC) can also cause dysentery. Current typing methods have limited ability to identify and differentiate between these pathogens despite the need for rapid and accurate identification of pathogens for clinical treatment and outbreak response. We present a comprehensive phylogeny of Shigella and EIEC using whole genome sequencing of 169 samples, constituting unparalleled strain diversity, and observe a lack of monophyly between Shigella and EIEC and among Shigella taxonomic groups. The evolutionary relationships in the phylogeny are supported by analyses of population structure and hierarchical clustering patterns of translated gene homolog abundance. Lastly, we identified a panel of 404 single nucleotide polymorphism (SNP) markers specific to each phylogenetic cluster for more accurate identification of Shigella and EIEC. Our findings show that Shigella and EIEC are not distinct evolutionary groups within the E. coli genus and, thus, EIEC as a group is not the ancestor to Shigella. The multiple analyses presented provide evidence for reconsidering the taxonomic placement of Shigella. The SNP markers offer more discriminatory power to molecular epidemiological typing methods involving these bacterial pathogens.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Research on Chemically Deuterated Cellulose Macroperformance and Fast Identification

Chemically deuterated cellulose fiber was expected to provide novel applications due to its spectral, biological, and kinetic isotope effect. In this research, the performance of the chemically deuterated cotton fibers, including their mechanical property, enzymatic degradation performance, effect on bacterial treatment, and fast identification (near-infrared modeling) was investigated. The breaking tenacity of the deuterated cotton fibers was slightly lower, which might be attributed to the structural damage during the chemical deuteration. The glucose yield by enzymatic hydrolysis was less than that of the protonic cotton fibers, implying the deuterated fibers are less sensitive to enzymatic degradation. Furthermore, the deuterated fibers could promote the growth of bacteria such as Escherichia. coli, which was associated with the released low-level deuterium content. At last, the near-infrared technique combined with partial least squares regression successfully achieved a fast identification of the protiated and deuterated cotton fibers, which significantly promoted the potential application of deuterated cellulose as anticounterfeiting materials (e.g., special paper).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Characterizing Families of Spectral Similarity Scores and Their Use Cases for Gas Chromatography–Mass Spectrometry Small Molecule Identification

Metabolomics provides a unique snapshot into the world of small molecules and the complex biological processes that govern the human, animal, plant, and environmental ecosystems encapsulated by the One Health modeling framework. However, this “molecular snapshot” is only as informative as the number of metabolites confidently identified within it. The spectral similarity (SS) score is traditionally used to identify compound(s) in mass spectrometry approaches to metabolomics, where spectra are matched to reference libraries of candidate spectra. Unfortunately, there is little consensus on which of the dozens of available SS metrics should be used. This lack of standard SS score creates analytic uncertainty and potentially leads to issues in reproducibility, especially as these data are integrated across other domains. In this work, we use metabolomic spectral similarity as a case study to showcase the challenges in consistency within just one piece of the One Health framework that must be addressed to enable data science approaches for One Health problems. Here, using a large cohort of datasets comprising both standard and complex datasets with expert-verified truth annotations, we evaluated the effectiveness of 66 similarity metrics to delineate between correct matches (true positives) and incorrect matches (true negatives). We additionally characterize the families of these metrics to make informed recommendations for their use. Our results indicate that specific families of metrics (the Inner Product, Correlative, and Intersection families of scores) tend to perform better than others, with no single similarity metric performing optimally for all queried spectra. This work and its findings provide an empirically-based resource for researchers to use in their selection of similarity metrics for GC-MS identification, increasing scientific reproducibility through taking steps towards standardizing identification workflows.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Intrahost SARS-CoV-2 k-mer Identification Method (iSKIM) for Rapid Detection of Mutations of Concern Reveals Emergence of Global Mutation Patterns

Despite unprecedented global sequencing and surveillance of SARS-CoV-2, timely identification of the emergence and spread of novel variants of concern (VoCs) remains a challenge. Several million raw genome sequencing runs are now publicly available. We sought to survey these datasets for intrahost variation to study emerging mutations of concern. We developed iSKIM (“intrahost SARS-CoV-2 k-mer identification method”) to relatively quickly and efficiently screen the many SARS-CoV-2 datasets to identify intrahost mutations belonging to lineages of concern. Certain mutations surged in frequency as intrahost minor variants just prior to, or while lineages of concern arose. The Spike N501Y change common to several VoCs was found as a minor variant in 834 samples as early as October 2020. This coincides with the timing of the first detected samples with this mutation in the Alpha/B.1.1.7 and Beta/B.1.351 lineages. Using iSKIM, we also found that Spike L452R was detected as an intrahost minor variant as early as September 2020, prior to the observed rise of the Epsilon/B.1.429/B.1.427 lineages in late 2020. iSKIM rapidly screens for mutations of interest in raw data, prior to genome assembly, and can be used to detect increases in intrahost variants, potentially providing an early indication of novel variant spread.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

LINE IDENTIFICATIONS OF TYPE I SUPERNOVAE: ON THE DETECTION OF Si II FOR THESE HYDROGEN-POOR EVENTS

Here we revisit line identifications of type I supernovae (SNe I) and highlight trace amounts of unburned hydrogen as an important free parameter for the composition of the progenitor. Most one-dimensional stripped-envelope models of supernovae indicate that observed features near 6000–6400 Å in type I spectra are due to more than Si ii λ6355. However, while an interpretation of conspicuous Si ii λ6355 can approximate 6150 Å absorption features for all SNe Ia during the first month of free expansion, similar identifications applied to 6250 Å features of SNe Ib and Ic have not been as successful. When the corresponding synthetic spectra are compared with high-quality timeseries observations, the computed spectra are frequently too blue in wavelength. Some improvement can be achieved with Fe ii lines that contribute redward of 6150 Å; however, the computed spectra either remain too blue or the spectrum only reaches a fair agreement when the rise-time to peak brightness of the model conflicts with observations by a factor of two. This degree of disagreement brings into question the proposed explosion scenario. Similarly, a detection of strong Si ii λ6355 in the spectra of broadlined Ic and super-luminous events of type I/R is less convincing despite numerous model spectra used to show otherwise. Alternatively, we suggest 6000–6400 Å features are possibly influenced by either trace amounts of hydrogen or blueshifted absorption and emission in Hα, the latter being an effect which is frequently observed in the spectra of hydrogen-rich, SNe II.

79 ASTRONOMY AND ASTROPHYSICS↗