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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence 9 - Raw Data

Sequences 8 and 9: Downwind Sonics (F,P) and Downwind Sonics Parked (P) This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged from 5 m/s to 25 m/s. Yaw angles of 0° to 60° were achieved. The blade tip pitch was 3°. The rotor rotated at 72 RPM during Sequence 8, but it was parked during Sequence 9. Blade pressure measurements were collected. The five-hole probes were removed and the plugs were installed. Plastic tape 0.03-mm-thick was used to smooth the interface between the plugs and the blade. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. During post-processing, the probe channels were set to read -99999.99. Sonic anemometers were mounted on a strut downwind of the turbine. The strut was mounted to the T-frame, which was rotated to align the anemometers aft of the 9% and 49% radius locations at hub height. Because of this configuration, the tunnel balance data are considered invalid. Sequence 9 was designed to compare the downwind sonic anemometer readings with the upwind sonic anemometers without interference from the turbine. The rotor was parked with the instrumented blade at 0° azimuth. All pressure measurements obtained in Sequence 9 are invalid because sufficient time for temperature stabilization did not occur, thus all associated data values were flagged as not applicable by setting the measured values in the data file to 0.0000 Pa. This test is further described in Appendix G.

17 WIND ENERGY↗
DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence H - Raw Data

Sequences H, I, and J: Upwind Baseline (F), Upwind Low Pitch (F), Upwind High Pitch (F) This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged from 5 m/s to 25 m/s. Yaw angles of –30 to 180° were achieved at low wind speeds, and angles of ±10° were achieved for high wind speeds. The blade tip pitch was 3° for sequence H, 0° for sequence I, and 6° for sequence J. These three sequences were interleaved during testing because the pitch angle change was easily made by the turbine operator. The rotor rotated at 72 RPM. Blade and probe pressure measurements were collected. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pretensioned to 40,000 N. In addition to the standard 30-second campaigns, yaw sweeps were done at 7 m/s and 10 m/s. These 6-minute campaigns were collected while the yaw drive rotated the turbine 360° at a rate of 1°/s. The file names for these campaigns use the letter designation, followed by two digits for wind speed, followed by YS, followed by 000.

17 WIND ENERGY↗
DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence I - Raw Data

Sequences H, I, and J: Upwind Baseline (F), Upwind Low Pitch (F), Upwind High Pitch (F) This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged from 5 m/s to 25 m/s. Yaw angles of –30° to 180° were achieved at low wind speeds, and angles of ±10° were achieved for high wind speeds. The blade tip pitch was 3° for sequence H, 0° for sequence I, and 6° for sequence J. These three sequences were interleaved during testing because the pitch angle change was easily made by the turbine operator. The rotor rotated at 72 RPM. Blade and probe pressure measurements were collected. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. In addition to the standard 30-second campaigns, yaw sweeps were done at 7 m/s and 10 m/s. These 6-minute campaigns were collected while the yaw drive rotated the turbine 360° at a rate of 1°/s. The file names for these campaigns use the letter designation, followed by two digits for wind speed, followed by YS, followed by 000.

17 WIND ENERGY↗
DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence J - Raw Data

Sequences H, I, and J: Upwind Baseline (F), Upwind Low Pitch (F), Upwind High Pitch (F) This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged from 5 m/s to 25 m/s. Yaw angles of –30° to 180° were achieved at low wind speeds, and angles of ±10° were achieved for high wind speeds. The blade tip pitch was 3° for sequence H, 0° for sequence I, and 6° for sequence J. These three sequences were interleaved during testing because the pitch angle change was easily made by the turbine operator. The rotor rotated at 72 RPM. Blade and probe pressure measurements were collected. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. In addition to the standard 30-second campaigns, yaw sweeps were done at 7 m/s and 10 m/s. These 6-minute campaigns were collected while the yaw drive rotated the turbine 360° at a rate of 1°/s. The file names for these campaigns use the letter designation, followed by two digits for wind speed, followed by YS, followed by 000.

17 WIND ENERGY↗
DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence N - Raw Data

Sequence N: Sin AOA, Rotating (P) This sequence was designed to quantify the blade 3-D unsteady aerodynamic response in the presence of rotational influences by varying blade pitch angle. Test sequence N used an upwind, rigid turbine with a 0° cone angle. The wind speed was 15 m/s, and the yaw angle was 0° throughout the sequence. The rotor rotated at 72 RPM. Blade and probe pressure measurements were collected. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. Sinusoidal angle-of-attack histories were designed to emulate 2-D S809 dynamic data obtained at the Ohio State University (OSU) wind tunnel (Reuss Ramsey et al. 1995) and the 1P yawed flow angle-of-attack variations the turbine could be expected to encounter in routine operation. The reduced frequency (K), mean angle of attack (αm), and oscillation amplitude (αω) were computed for each of the five primary span locations. The file lengths varied according to the time required to complete 40 oscillations at the specified frequency. The file name convention used the sequence designation N, followed by two digits for the span location (30, 47, 63, 80, or 95), followed by two digits representing the condition specified in the test matrix, followed by the repetition digit. Due to time constraints, most of the test conditions corresponding to the 63% span location were eliminated. Test points with a static pitch angle of 3° were collected throughout the sequence to ascertain instrumentation fidelity.

17 WIND ENERGY↗
DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence O - Raw Data

Sequence O: Sin AOA, Parked (P) This sequence was designed to quantify the blade 3-D unsteady aerodynamic response in the absence of rotational influences by varying blade pitch angle. This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged from 18.9 m/s to 39.3 m/s, and the yaw angle was 0° throughout the sequence. The rotor was parked with the instrumented blade fixed at 0° azimuth, and the rotor lock was installed (see Appendix A). Blade and probe pressure measurements were collected. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to -99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. Sinusoidal angle-of-attack histories were designed to emulate 2-D S809 dynamic data obtained at the OSU wind tunnel (Reuss Ramsey et al. 1995) as well as 1P yawed flow angle-of-attack variations the turbine could be expected to encounter in routine operation. The reduced frequency (K), mean angle of attack (αm), and oscillation amplitude (αω) were computed for each of the five primary span locations. The file lengths varied according to the time required to complete 40 oscillations at the specified frequency. The file name convention used the sequence designation O, followed by two digits for the span location (30, 47, 80, or 95), followed by two digits representing the condition specified in the test matrix, followed by the repetition digit. Due to time constraints, the test conditions corresponding to the 63% span location were eliminated. Test points with a static pitch angle of 3° were collected throughout the sequence to ascertain instrumentation fidelity.

17 WIND ENERGY↗
DOE OSTI2026

Beyond sequence similarity: toward function-based screening of nucleic acid synthesis

Synthetic nucleic acids are a key input to modern biotechnology, yet they represent dual-use materials that require robust screening to mitigate biosecurity risks. The prevailing screening paradigm, which identifies sequences of concern (SoCs) through sequence similarity to controlled pathogens and toxins, may not fully capture risks posed by AI tools that can decouple biomolecular function from reliance on known sequences. Rapidly advancing biodesign capabilities enable the generation of genes and proteins that might evade sequence-based detection. We highlight the critical need for function-based screening approaches that can detect sequences capable of hazardous biological functions, regardless of similarity to known SoCs. We examine the feasibility of function-based screening with an initial focus on proteins, arguing that, while protein sequence space is vast, biologically functional proteins are significantly constrained by biophysical and biochemical requirements that can be learned and modeled. We propose a concrete implementation framework organized along a continuum of complexity, starting with toxins as the most tractable targets before expanding to more complex pathogenic functions. We then discuss open challenges and describe a research and development strategy to address them.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Deep Sequencing of MHC-Adapted Viral Lines Reveals Complex Recombinational Exchanges With Endogenous Retroviruses Leading to High-Frequency Variants

Experimental evolution (serial passage) of Friend virus complex (FVC) in mice demonstrates phenotypic adaptation to specific host major histocompatibility complex (MHC) genotypes. These evolved viral lines show increased fitness and virulence in their host-genotype-of-passage, but display fitness and virulence tradeoffs when infecting unfamiliar host MHC genotypes. Here, we deep sequence these viral lines in an attempt to discover the genetic basis of FVC adaptation. The principal prediction for genotype-specific adaptation is that unique mutations would rise to high frequency in viral lines adapted to each host MHC genotype. This prediction was not supported by our sequencing data as most observed high-frequency variants were present in each of our independently evolved viral lines. However, using a multi-variate approach to measure divergence between viral populations, we show that populations of replicate evolved viral lines from the same MHC congenic mouse strain were more similar to one another than to lines derived from different MHC congenic mouse strains, suggesting that MHC genotype does predictably act on viral evolution in our model. Sequence analysis also revealed rampant recombination with endogenous murine leukemia virus sequences (EnMuLVs) that are encoded within the BALB/c mouse genome. The highest frequency variants in all six lines contained a 12 bp insertion from a recombinant EnMuLV source, suggesting such recombinants were either being favored by selection or were contained in a recombinational hotspot. Interestingly, they did not reach fixation, as if they are low fitness. The amount of background mutations linked to FVC/EnMuLV variable sites indicated that FVC/EnMuLV recombinants had not reached mutation selection equilibrium and thus, that EnMuLV sequences are likely continuously introgressing into the replicating viral population. These discoveries raise the question: is the expression of EnMuLV sequences in mouse splenocytes that permit recombination with exogenous FVC a pathogen or host adaptation?

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Multidimensional metrics for estimating phage abundance, distribution, gene density, and sequence coverage in metagenomes

Phages are the most abundant biological entities on Earth and play major ecological roles, yet the current sequenced phage genomes do not adequately represent their diversity, and little is known about the abundance and distribution of these sequenced genomes in nature. Although the study of phage ecology has benefited tremendously from the emergence of metagenomic sequencing, a systematic survey of phage genes and genomes in various ecosystems is still lacking, and fundamental questions about phage biology, lifestyle, and ecology remain unanswered. To address these questions and improve comparative analysis of phages in different metagenomes, we screened a core set of publicly available metagenomic samples for sequences related to completely sequenced phages using the web tool, Phage Eco-Locator. We then adopted and deployed an array of mathematical and statistical metrics for a multidimensional estimation of the abundance and distribution of phage genes and genomes in various ecosystems. Experiments using those metrics individually showed their usefulness in emphasizing the pervasive, yet uneven, distribution of known phage sequences in environmental metagenomes. Using these metrics in combination allowed us to resolve phage genomes into clusters that correlated with their genotypes and taxonomic classes as well as their ecological properties. By adding this set of metrics to current metaviromic analysis pipelines, where they can provide insight regarding phage mosaicism, habitat specificity, and evolution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Analysis of Plant Pan-Genomes and Transcriptomes with GET_HOMOLOGUES-EST, a Clustering Solution for Sequences of the Same Species

The pan-genome of a species is defined as the union of all the genes and noncoding sequences found in all its individuals. However, constructing a pan-genome for plants with large genomes is daunting both in sequencing cost and the scale of the required computational analysis. A more affordable alternative is to focus on the genic repertoire by using transcriptomic data. Here, the software GET_HOMOLOGUES-EST was benchmarked with genomic and RNA-seq data of 19 Arabidopsis thaliana ecotypes and then applied to the analysis of transcripts from 16 Hordeum vulgare genotypes. The goal was to sample their pan-genomes and classify sequences as core, if detected in all accessions, or accessory, when absent in some of them. The resulting sequence clusters were used to simulate pan-genome growth, and to compile Average Nucleotide Identity matrices that summarize intra-species variation. Although transcripts were found to under-estimate pan-genome size by at least 10%, we concluded that clusters of expressed sequences can recapitulate phylogeny and reproduce two properties observed in A. thaliana gene models: accessory loci show lower expression and higher non-synonymous substitution rates than core genes. Finally, accessory sequences were observed to preferentially encode transposon components in both species, plus disease resistance genes in cultivated barleys, and a variety of protein domains from other families that appear frequently associated with presence/absence variation in the literature. These results demonstrate that pan-genome analyses are useful to explore germplasm diversity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

classLog: Logistic regression for the classification of genetic sequences

Introduction Sequencing and phylogenetic classification have become a common task in human and animal diagnostic laboratories. It is routine to sequence pathogens to identify genetic variations of diagnostic significance and to use these data in realtime genomic contact tracing and surveillance. Under this paradigm, unprecedented volumes of data are generated that require rapid analysis to provide meaningful inference. Methods We present a machine learning logistic regression pipeline that can assign classifications to genetic sequence data. The pipeline implements an intuitive and customizable approach to developing a trained prediction model that runs in linear time complexity, generating accurate output rapidly, even with incomplete data. Our approach was benchmarked against porcine respiratory and reproductive syndrome virus (PRRSv) and swine H1 influenza A virus (IAV) datasets. Trained classifiers were tested against sequences and simulated datasets that artificially degraded sequence quality at 0, 10, 20, 30, and 40%. Results When applied to a poor-quality sequence data, the classifier achieved between >85% to 95% accuracy for the PRRSv and the swine H1 IAV HA dataset and this increased to near perfect accuracy when using the full dataset. The model also identifies amino acid positions used to determine genetic clade identity through a feature selection ranking within the model. These positions can be mapped onto a maximum-likelihood phylogenetic tree, allowing for the inference of clade defining mutations. Discussion Our approach is implemented as a python package with code available at https://github.com/flu-crew/classLog .

Zeller, Michael A.↗
DOE OSTI2025

Diversity of Sordariales Fungi: Identification of Seven New Species of Naviculisporaceae Through Morphological Analyses and Genome Sequencing

Thanks to next-generation sequencing (NGS) technologies, the diversity of fungi can now be investigated through the analysis of their genome sequences. Naviculisporaceae is a family within the Sordariales, whose diversity is not well-known, with only one genome sequence published for this family. Here, we report on the isolation and cultivation of 20 new strains of Naviculisporaceae. Their genome sequences, as well as those of the five commercially available strains, were determined, thus providing complete genome sequences for 25 new Naviculisporaceae strains. Species delimitation was conducted using a combination of (1) ITS + LSU phylogenetic analysis of the new isolates along with other known species of the family, (2) comparisons between DNA barcode sequences of the new strains with those of the known species, and (3) average genome-wide nucleotide identity calculation. We built a phylogenomic tree and studied the organization of the mating-type locus. In vitro fruiting was obtained for 16 strains, enabling the definition of seven new species, namely Pseudorhypophila gallica, Pseudorhypophila guyanensis Rhypophila alpibus, Rhypophila brasiliensis, Rhypophila camarguensis, Rhypophila reunionensis and Rhypophila thailandica, as well as two new combinations, namely Pseudorhypophila latipes and Pseudorhypophila oryzae. Eight strains for which in vitro fruiting was not obtained may belong to additional new species. These results expand the known diversity of the Naviculisporaceae and greatly enlarge the genomic data available for the family.

Naviculisporaceae↗
DOE OSTI2014

Genome sequence of the mud-dwelling archaeon Methanoplanus limicola type strain (DSM 2279 T ), reclassification of Methanoplanus petrolearius as Methanolacinia petrolearia and emended descriptions of the genera Methanoplanus and Methanolacinia

Methanoplanus limicola Wildgruber et al. 1984 is a mesophilic methanogen that was isolated from a swamp composed of drilling waste near Naples, Italy, shortly after the Archaea were recognized as a separate domain of life. Methanoplanus is the type genus in the family Methanoplanaceae , a taxon that felt into disuse since modern 16S rRNA gene sequences-based taxonomy was established. Methanoplanus is now placed within the Methanomicrobiaceae , a family that is so far poorly characterized at the genome level. The only other type strain of the genus with a sequenced genome, Methanoplanus petrolearius SEBR 4847 T , turned out to be misclassified and required reclassification to Methanolacinia . Both, Methanoplanus and Methanolacinia , needed taxonomic emendations due to a significant deviation of the G+C content of their genomes from previously published (pregenome-sequence era) values. Until now genome sequences were published for only four of the 33 species with validly published names in the Methanomicrobiaceae . Here we describe the features of M. limicola , together with the improved-high-quality draft genome sequence and an notation of the type strain, M3 T . The 3,200,946 bp long chromosome (permanent draft sequence) with its 3,064 protein-coding and 65 RNA genes is a part of the Genomic Encyclopedia of Bacteria and Archaea project.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1973

Science sequence design

The activities of the following members of the Navigation Team are recorded: the Science Sequence Design Group, responsible for preparing the final science sequence designs; the Advanced Sequence Planning Group, responsible for sequence planning; and the Science Recommendation Team (SRT) representatives, responsible for conducting the necessary sequence design interfaces with the teams during the mission. The interface task included science support in both advance planning and daily operations. Science sequences designed during the mission are also discussed.

Koskela, P. E.↗
NASA NTRS1974

Families of shift-register sequences with impulsive correlation properties

A study of the linear feedback shift registers corresponding to a subset of nonprimitive irreducible polynomials over GF(2) has uncovered a class of sequences with interesting structures and cyclic correlation properties. These families of sequences are made up of interleaved identical sequences which are from primitive irreducible polynomials. Furthermore, they have correlation functions which are two or three valued, being constant at zero or a small value throughout most of their length with the exception of a small number of impulses. Each interval between such impulses on the correlograms uniquely corresponds to (and thus uniquely identifies) the member sequence or sequences producing it. It is shown that these families of sequences have direct application as error-correcting codes.

Lee, J.-J.↗
NASA NTRS1983

A catalogue of photometric sequences (suppl. 3)

In stellar photometry studies, certain difficulties have arisen because of the lack of suitable photometric sequences for calibrating astronomical photographs. In order to eliminate these difficulties, active observers were contacted with a view to drawing up lists of suitable sequences. Replies from 63 authors offering data on 412 sequences were received. Most data were in the UBV system and had been obtained between 1968 and 1973. These were included in the original catalogue. The Catalogue represents a continuation of the earlier Photometric Catalogue compiled by Sharov and Jakimova (1970). A small supplement containing 69 sequences was issued in 1973. Supplement 2 was produced in 1976 and contained 320 sequences. Supplement 3 has now been compiled. It contains 1271 sequences.

Argue, A. N.↗
NASA NTRS1986

Sequencing Voyager II for the Uranus encounter

The process of developing the programmed sequence of events necessary for the Voyager 2 spacecraft to return desired data from its Uranus encounter is discussed. The major steps in the sequence process are reviewed, and the elements of the Mission Sequence Software are described. The design phase and the implementation phase of the sequence process are discussed, and the Computer Command Subsystem architecture is examined in detail. The software's role in constructing the sequences and converting them into onboard programs is elucidated, and the problems unique to the Uranus encounter sequences are considered.

Morris, R. B.↗
NASA NTRS1986

Elimination sequence optimization for SPAR

SPAR is a large-scale computer program for finite element structural analysis. The program allows user specification of the order in which the joints of a structure are to be eliminated since this order can have significant influence over solution performance, in terms of both storage requirements and computer time. An efficient elimination sequence can improve performance by over 50% for some problems. Obtaining such sequences, however, requires the expertise of an experienced user and can take hours of tedious effort to affect. Thus, an automatic elimination sequence optimizer would enhance productivity by reducing the analysts' problem definition time and by lowering computer costs. Two possible methods for automating the elimination sequence specifications were examined. Several algorithms based on the graph theory representations of sparse matrices were studied with mixed results. Significant improvement in the program performance was achieved, but sequencing by an experienced user still yields substantially better results. The initial results provide encouraging evidence that the potential benefits of such an automatic sequencer would be well worth the effort.

Hogan, Harry A.↗