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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Robust System Separation Strategy Considering Online Wide-Area Coherency Identification and Uncertainties of Renewable Energy Sources

With the fast growth of renewable energy sources (RES), more and more uncertainties are involved and influencing the stable operation of power systems. Controlled islanding is the last measure to prevent power system blackouts, thus this paper aims to propose a novel model of system separation based on Online Coherency Identification and Adjustable Robust Optimization Programming (OCI-AROP) for minimizing load shedding considering the uncertainties of RES. First, Fuzzy C-Means (FCM) clustering method with F-statistics is utilized to identify the coherent generator groups with the frequency data measured by Phasor Measurement Units (PMUs). Then, the OCI-AROP model considering coherent group constraints, connectivity constraints and robustness constraints about RES are presented. Finally, the case studies on IEEE-39 bus system and WECC-179 bus system are employed to demonstrate the effectiveness of the proposed OCI-AROP model, and comparisons among the OCI-AROP model and the other models are also given to show its superiority.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Guaranteed Phase & Topology Identification in Three Phase Distribution Grids

We present a method for joint phase identification and topology recovery in unbalanced three phase radial networks using only voltage measurements. By recovering phases and topology jointly, we utilize all three phase voltage measurements and can handle networks where some buses have a subset of three phases. Our method is theoretically justified by a novel linearized formulation of unbalanced three phase power flow and makes precisely defined and reasonable assumptions on line impedances and load statistics. We validate our method on three IEEE test networks simulated under realistic conditions in OpenDSS, comparing our performance to the state of the art. In addition to providing a new method for phase and topology recovery, our intuitively structured linearized model will provide a foundation for future work in this and other applications.

42 ENGINEERING↗
DOE OSTI2019

Combined DNA Typing and Protein Identification from Unfired Brass Cartridges

Biological evidence in the form of contact traces is of major importance in forensic laboratories but success rates are affected by the low amounts and degraded state of the DNA present on these items. Combining DNA polymorphisms with markers individualizing the more abundant protein fraction is a promising new approach. In this study touched brass cartridges were successfully tested for DNA polymorphisms and signature peptides after a single collection and enzyme digestion step. A comparison between moistened swabs and adhesive tape for the collection step resulted in slightly better quality DNA profiles for the tape samples, but no significant difference for protein identifications. The detected proteins showed the expected prominence of different keratins and were generally consistent with previously described skin proteomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Identification of synthetic consortia from a set of plant-beneficial bacteria

The use of microbial inoculants in agriculture as biofertilisers and/or biopesticides is an appealing alternative to replace or reduce the practice of agrochemicals. Plant microbiota studies are revealing the different bacterial groups which are populating plant microbiomes re-energising the plant probiotic bacteria (PPB) translational research sector. Some single-microbial strain bioinoculants have proven valid in agriculture (e.g., based on Trichoderma, mycorrhiza or rhizobia); however, it is now recommended to consider multistrain consortia since plant-beneficial effects are often a result of community-level interactions in plant microbiomes. A limiting step is the selection of a fitting combination of microbial strains in order to accomplish the best beneficial effect upon plant inoculation. In this study, we have used a subset of 23 previously identified and characterised rice-beneficial bacterial colonisers to design and test a series of associated experiments aimed to identify potential PPB consortia which are able to co-colonise and induce plant growth promotion. Bacterial strains were co-inoculated in vitro and in planta using several different methods and their co-colonisation and co-persistence monitored. Results include the identification of two 5-strain and one 2-strain consortia which displayed plant growth-promoting features. Future practical applications of microbiome research must include experiments aimed at identifying consortia of bacteria which can be most effective as crop amendments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Efficient population representation with more genetic markers increases performance of a steelhead (Oncorhynchus mykiss) genetic stock identification baseline

Abstract Genetic stock identification (GSI) is an important fisheries management tool to identify the origin of fish harvested in mixed stock fisheries. Periodic updates of genetic baselines can improve performance via the addition of unsampled or under‐sampled populations and the inclusion of more informative markers. We used a combination of baselines to evaluate how population representation, marker number, and marker type affected the performance and accuracy of genetic stock assignments (self‐assignment, bias, and holdout group tests) for steelhead ( Oncorhynchus mykiss ) in the Snake River basin. First, we compared the performance of an existing genetic baseline with a newly developed one which had a reduced number of individuals from more populations using the same set of markers. Self‐assignment rates were significantly higher ( p < 0.001; +5.4%) for the older, larger baseline, bias did not differ significantly between the two, but there was a significant improvement in performance for the new baseline in holdout results ( p < 0.001; mean increase of 25.0%). Second, we compared the performance of the new baseline with increased numbers of genetic markers (~2x increase of single‐nucleotide polymorphisms; SNPs) for the same set of baseline individuals. In this comparison, results produced significantly higher rates of self‐assignment ( p < 0.001; +9.7%) but neither bias nor leave‐one‐out were significantly affected. Third, we compared 334 SNPs versus opportunistically discovered microhaplotypes from the same amplicons for the new baseline, and showed the latter produced significantly higher rates of self‐assignment ( p < 0.01; +2.6%), similar bias, but slightly lower holdout performance (−0.1%). Combined, we show the performance of genetic baselines can be improved via representative and efficient sampling, that increased marker number consistently improved performance over the original baseline, and that opportunistic discovery of microhaplotypes can lead to small improvements in GSI performance.

Hargrove, John S.↗
DOE OSTI2025

Genetic Identification of Lamprey Genera and Anadromous Ecotypes in Watersheds of the Northeastern Pacific Ocean

ABSTRACT Nonparasitic, nonmigratory Western Brook Lamprey (WBL; Lampetra ayresii ), and parasitic, anadromous Western River Lamprey (WRL; L. ayresii ) are sympatric lampreys that likely represent different life history variations of a single species. Novel genetic tools are critical for differentiating WBL and WRL, whose larvae preclude morphological identification (ID) and will enable comprehensive assessment of imperiled native lampreys of the Northeastern Pacific (including WBL, WRL, and Pacific Lamprey, Entosphenus tridentatus ). We developed 47 candidate single nucleotide polymorphism (SNP) markers using whole genome resequencing of WBL ( N = 24) and WRL ( N = 15) from Ksi Ts'oohl Ts'ap Creek (Nass River, British Columbia, Canada) which are likely ecotypes distinguished by few divergent SNPs across multiple chromosomes. We used five novel candidate SNPs to perform genetic ID of WBL and WRL ecotypes in collections of mixed native lampreys from lower Columbia River tributaries ( N = 1474), Ksi Ts'oohl Ts'ap Creek ( N = 352), and ocean phase WRL from the Georgia Basin (Salish Sea, British Columbia, Canada; N = 91). Two previously published SNPs were used to ID genera, Entosphenus versus Lampetra . Morphological ID utilized photographs collected from a subset of genotyped lampreys, and high concordance was demonstrated between ID methods for genera (99%) and Lampetra ecotypes (> 98%). We characterized spatial and temporal composition of lamprey genera and ecotypes surveyed across NE Pacific tributaries under the expectation these compositions would be similar across nearby sites and across years at the same site. Proportions of lamprey genera were highly variable within regions and across years; however, Lampetra ecotypic proportions were spatially and temporally stable. WRL were rare in lower Columbia tributaries (~1% average rate among Lampetra ) and common further north (> 40% of Lampetra ). Genetic ID methods are powerful monitoring tools that create the novel ability to ascertain genera and ecotypes regardless of life stage, while increasing the efficiency of surveys by eliminating time‐intensive morphological data collection.

Silver, G. S. [Columbia River Inter‐Tribal Fish Co↗
DOE OSTI2021

Identification and analysis of stem‐specific promoters from sugarcane and energy cane for oil accumulation in their stems

Abstract Considerable recent progress has been achieved in bioengineering oil accumulation in the vegetative tissues of plants, opening an opportunity for large scale production of biodiesel, jet fuel, lubricants, and high‐value lipid bioproducts. For the highly productive C4 crops, such as sugarcane, energy cane, Miscanthus, and fiber sorghums, the bulk of the biomass is the stem. However, little success has been made in accumulating oil in the stem. Since engineering a trait with a constitutive promoter often results in pleiotropic effects that counter trait improvement, identification of stem parenchyma‐specific promoters is a prerequisite for efficient use of the ample photoassimilates stored in mature stem parenchyma cells. In this study, we first identified two TST genes encoding homologues of tonoplast sugar transporters that were strongly and almost exclusively expressed in the stems of canes via a combination of RNA‐seq atlas analysis, in silico analysis of a sugarcane genome, phylogenetic analysis, and quantitative PCR analysis. They were further confirmed in the pith parenchyma cells of the mature stem by RNA in situ hybridization. When fused with the β‐Glucuronidase (GUS) reporter gene, the promoters of two alleles, TST2b‐1A and TST2b‐1C , from one TST gene demonstrated that they could drive the GUS expression exclusively in the stem in Arabidopsis.

09 BIOMASS FUELS↗
DOE OSTI2017

Identification of bottlenecks in the accumulation of cyclic fatty acids in camelina seed oil

Modified fatty acids (mFA) have diverse uses, e.g., cyclopropane fatty acids (CPA) are feedstocks for producing coatings, lubricants, plastics, and cosmetics. The expression of mFA-producing enzymes in crop and model plants generally results in lower levels of mFA accumulation than in their natural-occurring source plants. In order to further our understanding of metabolic bottlenecks that limit mFA accumulation, we generated transgenic Camelina sativa lines co-expressing Escherichia coli cyclopropane synthase (EcCPS) and Sterculia foetida lysophosphatidic acid acyltransferase (SfLPAT). In contrast to transgenic CPA-accumulating Arabidopsis, CPA accumulation in camelina caused only minor changes in seed weight, germination rate, oil accumulation, and seedling development. CPA accumulated to much higher levels in membrane than storage lipids, comprising more than 60% of total fatty acid in both phosphatidylcholine (PC) and phosphatidylethanolamine (PE) versus 26% in diacylglycerol (DAG) and 12% in triacylglycerol (TAG) indicating bottlenecks in the transfer of CPA from PC to DAG and from DAG to TAG. Upon coexpression of SfLPAT with EcCPS, di-CPA-PC increased by ~50% relative to lines expressing EcCPS alone with the di-CPA-PC primarily observed in the embryonic axis and mono-CPA-PC primarily in cotyledon tissue. EcCPS-SfLPAT lines revealed a redistribution of CPA from the sn-1 to sn-2 positions within PC and PE that was associated with a doubling of CPA accumulation in both DAG and TAG. Finally, the identification of metabolic bottlenecks in acyl transfer between site of synthesis (phospholipids) and deposition in storage oils (TAGs) lays the foundation for the optimizing CPA accumulation through directed engineering of oil synthesis in target crops.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Evaluating Model Robustness for Defect Identification and Classification in a Composite Aerostructure Material

Aircraft structures are required to have a high level of quality to satisfy their need for light weight, efficient flight, and withstanding high loads over their lifespan. These aerostructures are typically made from a composite material due to their good tensile strength and resistance to compression. To ensure their structural integrity, the composite material requires inspection for common flaws such as porosity, delaminations, voids, foreign object debris, and other defects. Ultrasonic testing (UT) is a popular non-destructive inspection (NDI) technique used for effectively evaluating the composite material. Current inspection methods rely heavily on human experience and are extremely time consuming. Therefore, there is a need for the development of techniques to reduce the manual inspection time. This work compares the performance of different deep learning-based methods in the identification and classification of defects. Deep learning has shown great promise in numerous fields, and we show its effectiveness in the evaluation of the composite aerostructure material. The methods developed here are both highly reliable with a top recall value of 98.64% as well as extremely efficient requiring an average of 4 s during the inferencing stage to evaluate new composites. Lastly, we investigate model robustness to concept drift by measuring its performance over time.

36 MATERIALS SCIENCE↗
DOE OSTI2019

High-Frequency Acoustic Mode Identification of Unstable Combustors

Abstract High frequency thermoacoustic instabilities are becoming increasingly problematic in modern combustion systems. Understanding which acoustic mode is being excited is important for understanding potential mechanisms and control approaches — for example, influence of a helical shear layer mode on the flame has profoundly different effects on the first tangential acoustic mode, than a higher order axial mode of similar frequency. Nonetheless, the modal density increases with frequency and it becomes increasingly difficult to determine which acoustic mode is self-excited, based upon frequency calculations alone. Moreover, access issues and cost usually limit the number of pressure probes that can be distributed axially and azimuthally in the combustor. This paper presents a methodology for identifying the acoustic mode by using high temperature pressure transducers flush mounted in a combustion chamber. Modal identification is demonstrated with a siren under non-reacting conditions. The siren is mounted on the chamber to excite longitudinal and azimuthal waves. Five acoustic sensors at different axial and azimuthal locations measure the pressure fluctuations simultaneously. Given the forcing frequency and the speed of sound, the pressure distribution in the combustor is reconstructed in the time domain from the measured data by using a least squares method to determine its mode shapes. In addition, the finite element method (FEM) solver is used to provide the eigenfrequencies and corresponding mode shapes. The test results demonstrate that the mode shapes from the reconstructed data and corresponding frequencies are consistent with those predicted from the FEM, which validates the methodology in this study. In addition, the methodology is extended to practical reacting cases without the siren to determine the acoustic mode shapes of naturally occurring instabilities. In these cases, the modal features have strong stochastic features, such as what appear to be stochastic variations in overall amplitude and relative amplitudes of clockwise and counterclockwise waves.

Kim, J.↗
DOE OSTI2023

Comparative Study on Deep Learning Methods for Defect Identification and Classification in Composite Aerostructure Material

Aircraft structures are required to have a high level of quality to satisfy their need for light weight, efficient flight, and withstanding high loads over their lifespan. These aerostructures are typically made from composite material due to their good tensile strength and resistance to compression. To ensure their structural integrity, the composite material requires inspection for common flaws such as porosity, delaminations, voids, foreign object debris, and other defects. Ultrasonic testing (UT) is a popular non-destructive inspection (NDI) technique used for effectively evaluating composite material. Current inspection methods rely heavily on human experience and are extremely time consuming. Therefore, there is a need for the development of techniques to reduce the manual inspection time. This work compares the performance of different deep learning-based methods in the identification and classification of defects. Deep learning has shown great promise in numerous fields, and we show its effectiveness in the evaluation of composite aerostructure material. Furthermore, the methods developed here are both highly reliable with a top recall value of 98.63% as well as extremely efficient requiring an average of 4 seconds during the inferencing stage to evaluate new composites.

composites↗
DOE OSTI2019

Clutter Identification based on sparse recovery with dynamically changing dictionary sizes for cognitive radar

Existing radar algorithms assume stationary statistical characteristics for environment/clutter. In practical scenarios, the statistical characteristics of the clutter can dynamically change depending on where the radar is operating. Non-stationarity in the statistical characteristics of the clutter may negatively affect the radar performance. Cognitive radar that can sense the changes in the clutter statistics, learn the new statistical characteristics, and adapt to these changes has been proposed to overcome these shortcomings. We have recently developed techniques for detection of statistical changes and learning the new clutter distribution for cognitive radar. In this work, we will extend the learning component. More specifically, in our previous work, we have developed a sparse recovery based clutter distribution identification to learn the distribution of the new clutter characteristics after the detected change in the statistics of the clutter. In our method, we have built a dictionary of clutter distributions and used this dictionary in orthogonal matching pursuit to perform sparse recovery of the clutter distribution assuming that the dictionary includes the new distribution. In this work, we propose a hypothesis testing based approach to detect whether the new distribution of the clutter is included in the dictionary or not, and suggest a method to dynamically update the dictionary. We envision that the successful outcomes of this work will be of high relevance to the adaptive learning and cognitive augmentation of the radar systems that are used in remotely piloted vehicles for surveillance and reconnaissance operations.

Zhu, Yuansheng↗
DOE OSTI2021

SINGLE: Atomic-resolution structure identification of nanocrystals by graphene liquid cell EM

Analysis of the three-dimensional (3D) structures of nanocrystals with solution-phase transmission electron microscopy is beginning to reveal their unique physiochemical properties. We developed a “one-particle Brownian 3D reconstruction method” based on imaging of ensembles of colloidal nanocrystals using graphene liquid cell electron microscopy. Projection images of differently rotated nanocrystals are acquired using a direct electron detector with high temporal (<2.5 ms) resolution and analyzed to obtain an ensemble of 3D reconstructions. Here, we introduce computational methods required for successful atomic-resolution 3D reconstruction: (i) tracking of the individual particles throughout the time series, (ii) subtraction of the interfering background of the graphene liquid cell, (iii) identification and rejection of low-quality images, and (iv) tailored strategies for 2D/3D alignment and averaging that differ from those used in biological cryo–electron microscopy. Our developments are made available through the open-source software package SINGLE.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

High-throughput identification of spin-photon interfaces in silicon

Color centers in host semiconductors are prime candidates as spin-photon interfaces for quantum applications. Finding an optimal spin-photon interface in silicon would move quantum information technologies toward a mature semiconducting host. However, the space of possible charged defects is vast, making the identification of candidates from experiments alone extremely challenging. Here, we use high-throughput first-principles computational screening to identify spin-photon interfaces among more than 1000 charged defects in silicon. The use of a single-shot hybrid functional approach is critical in enabling the screening of many quantum defects with a reasonable accuracy. We identify three promising spin-photon interfaces as potential bright emitters in the telecom band: Ti$^+_i$, Fe$^0_i$, and Ru$^0_i$. These candidates are excited through defect-bound excitons, stressing the importance of such defects in silicon for telecom band operations. Our work paves the way to further large-scale computational screening for quantum defects in semiconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Identification of proteins influencing CRISPR-associated transposases for enhanced genome editing

CRISPR-associated transposases (CASTs) hold tremendous potential for microbial genome editing because of their ability to integrate large DNA cargos in a programmable, site-specific manner. However, their widespread application has been hindered by poorly understood host factor requirements for transposition. To address this gap, we conducted the first genome-wide screen for host factors affecting Vibrio cholerae CAST (VchCAST) activity using an Escherichia coli RB-TnSeq library and identified 15 genes affecting VchCAST transposition. Of these, seven factors were validated to improve VchCAST activity, and two were inhibitory. Guided by the identification of homologous recombination effectors, RecD and RecA, we tested the λ-Red recombineering system in our VchCAST editing vectors and increased editing efficiency by 55.2-fold in E. coli, 5.6-fold in Pseudomonas putida, and 10.8-fold in Klebsiella michiganensis while maintaining high target specificity and similar insertion arrangements. This study improves the understanding of factors affecting VchCAST activity and enhances its efficiency as a bacterial genome editor.

Song, Leo C T↗
DOE OSTI2017

Identification of Glutaminyl Cyclase Genes Involved in Pyroglutamate Modification of Fungal Lignocellulolytic Enzymes

The breakdown of plant biomass to simple sugars is essential for the production of second-generation biofuels and high-value bioproducts. Currently, enzymes produced from filamentous fungi are used for deconstructing plant cell wall polysaccharides into fermentable sugars for biorefinery applications. A post-translational N-terminal pyroglutamate modification observed in some of these enzymes occurs when N-terminal glutamine or glutamate is cyclized to form a five-membered ring. This modification has been shown to confer resistance to thermal denaturation for CBH-1 and EG-1 cellulases. In mammalian cells, the formation of pyroglutamate is catalyzed by glutaminyl cyclases. Using the model filamentous fungus Neurospora crassa , we identified two genes ( qc-1 and qc-2 ) that encode proteins homologous to mammalian glutaminyl cyclases. We show that qc-1 and qc-2 are essential for catalyzing the formation of an N-terminal pyroglutamate on CBH-1 and GH5-1. CBH-1 and GH5-1 produced in a Δqc-1 Δqc-2 mutant, and thus lacking the N-terminal pyroglutamate modification, showed greater sensitivity to thermal denaturation, and for GH5-1, susceptibility to proteolytic cleavage. QC-1 and QC-2 are endoplasmic reticulum (ER)-localized proteins. The pyroglutamate modification is predicted to occur in a number of additional fungal proteins that have diverse functions. The identification of glutaminyl cyclases in fungi may have implications for production of lignocellulolytic enzymes, heterologous expression, and biotechnological applications revolving around protein stability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Genome-Wide Identification of Transcription Start Sites in Two Alphaproteobacteria , Rhodobacter sphaeroides 2.4.1 and Novosphingobium aromaticivorans DSM 12444

Here, we report the genome-wide identification of transcription start sites (TSSs) from two Alphaproteobacteria grown under conditions that result in significant changes in gene expression. TSSs that were identified as present in one condition or both will be an important resource for future studies of these, and possibly other, Alphaproteobacteria .

Myers, Kevin S.↗
DOE OSTI2018

Identification of Absorption Bands of Monomers and Aggregates in a Layer of Cyanine Dye and Determination of the Orientation of Molecules

The problem of allocating bands of individual monomers or aggregates of the absorption spectrum of a multicomponent structure arises in the study of molecular layers or organic thin films. Not counting the concentrations of the components, the optical properties of this kind of samples are determined by the tilt of the molecules relative to the substrate surface. Molecular orientation can be determined from the dichroic ratio spectra recorded with the tilt probing of samples. Using the example of the tricarbocyanine dye layers, the following two independent methods for the identification of the spectra of the components from the absorption spectrum of a layer are compared: by comparing the spectra of layers of different thicknesses and based on the dichroic ratio spectra. The effect of laser radiation on the samples, which leads to a change in the dichroic ratio, is studied. Photoinduced changes of the orientation angles of molecules are calculated, which allows one to refine the range of possible values of these angles.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗