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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.

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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

System for detecting objects in streaming 3D images formed from data acquired with a medium penetrating sensor

A detection system that detects subsurface objects within a medium and estimates various features of the objects is provided. The detection system receives a streaming sequence of image frames of the medium at various along-medium locations. An image frame contains voxel values (intensities) representing characteristics of the medium across the medium and in the depth (range) direction. The detection system depth-compensates the intensities for determining which voxels are part of an object using an unsupervised binary classifier. The detection system then connects object voxels into distinct objects and recursively estimates the features of those objects as the image frames stream based on the locations and intensities of the object voxels.

Paglieroni, David W.↗
DOE OSTI2026

Ecological connectivity and habitat loss shape patterns of genetic diversity in a threatened salamander

Context The maintenance of genetic diversity is essential for preserving adaptive potential in populations, yet it is increasingly threatened by landscape alteration. The field of landscape genetics offers a framework for assessing how patch-level landscape conditions, modeled at multiple scales, influence genetic diversity. Objectives We sought to assess how local environmental features and connectivity influence genetic diversity across 74 four-toed salamander (Hemidactylium scutatum) breeding wetlands in the southeastern United States. Methods Using next-generation sequencing data and hierarchical Bayesian models, we examined genome-wide heterozygosity in relation to local landscape features and ecological connectivity. We also assessed the scale of effect of landscape features and tested for temporal lag effects. Results Genetic diversity was lower in wetlands with higher levels of historic deforestation and lower connectivity. An interaction between deforestation and connectivity indicated that deforestation had stronger negative effects in isolated wetlands but weaker effects in well-connected wetlands. Accounting for scale of effect and temporal lags was critical for detecting these relationships. Conclusions Our analyses highlight the importance of assessing the spatial scale (scale of effect) and temporal lag of landscape features to detect key drivers of genetic diversity. In line with population genetic theory, our results indicate that the genetic consequences of habitat loss do not affect populations uniformly and are most severe in isolated populations where gene flow cannot buffer against loss of diversity. Altogether, we highlight the importance of considering the interaction of habitat loss and connectivity in conservation genetic management.

Hemidactylium scutatum↗
NASA NTRS1985

International Ultraviolet Explorer Atlas of O-typespectra from 1200 to 1900 Angstrom

The IUE archives provide an unprecedented sample of uniform, high-quality ultraviolet stellar spectra. In particular, they contain high-resolution SWP data for nearly 200 different O stars. We have undertaken a survey of the 1200-1900 A region in about 120 of them having homogeneous optical spectral classifications to investigate systematically the behavior of the ultraviolet features, incuding the prominent stellar wind profiles and the degree to which they correlate with the optical types. The standard extracted spectrograms have been rebinned to a constant wavelength resolution of 0.25A and uniformly normalized (not dereddened) at the GSFC RDAF. They are then plotted at 10A/cm, with reseau, photometric quality and echelle order junction flags available. This atlas contains such plots for about 100 stars, arranged in spectral-type, luminosity and peculiar object sequences. The results show a high degree of correlation between the ultraviolet features, both photospheric and stellar-wind, and the optical classifications for the majority of the O-type stars.

Walborn, N. R.↗
DOE OSTI2024

Genome-scale model development and genomic sequencing of the oleaginous clade Lipomyces

The Lipomyces clade contains oleaginous yeast species with advantageous metabolic features for biochemical and biofuel production. Limited knowledge about the metabolic networks of the species and limited tools for genetic engineering have led to a relatively small amount of research on the microbes. Here, a genome-scale metabolic model (GSM) of Lipomyces starkeyi NRRL Y-11557 was built using orthologous protein mappings to model yeast species. Phenotypic growth assays were used to validate the GSM (66% accuracy) and indicated that NRRL Y-11557 utilized diverse carbohydrates but had more limited catabolism of organic acids. The final GSM contained 2,193 reactions, 1,909 metabolites, and 996 genes and was thus named iLst996. The model contained 96 of the annotated carbohydrate-active enzymes. iLst996 predicted a flux distribution in line with oleaginous yeast measurements and was utilized to predict theoretical lipid yields. Twenty-five other yeasts in the Lipomyces clade were then genome sequenced and annotated. Sixteen of the Lipomyces species had orthologs for more than 97% of the iLst996 genes, demonstrating the usefulness of iLst996 as a broad GSM for Lipomyces metabolism. Pathways that diverged from iLst996 mainly revolved around alternate carbon metabolism, with ortholog groups excluding NRRL Y-11557 annotated to be involved in transport, glycerolipid, and starch metabolism, among others. Overall, this study provides a useful modeling tool and data for analyzing and understanding Lipomyces species metabolism and will assist further engineering efforts in Lipomyces .

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1983

The C2H, C2, and CN electronic absorption bands in the carbon star HD 19557

Infrared spectrophotometry of the R-type carbon star HD 19557 is presented. Two unusual spectroscopic features are seen: a 3.1 micron band is lacking and a 2.8 micron band is present. Identifications are proposed for three previously unreported stellar absorption bands with electronic sequences of C2, CN, and C2H. The latter is proposed to be responsible for the 2.8 micron feature. The atmospheric structure of the star is studied with synthetic spectra, and an effective temperature between 2600 K and 3000 K is suggested. No SiC emission is seen at 11.3 microns, indicating that grain formation is not a viable process around the star. The lack of dust in R stars may suggest a salient difference between R and N types.

Goebel, J. H.↗
DOE OSTI2020

Short-term load demand forecasting through rich features based on recurrent neural networks

With the emerging penetration of renewables and dynamic loads, the understanding of grid edge loading conditions becomes increasingly substantial. Load modelling researches commonly consist of explicitly expressed load models and non-explicitly expressed techniques, of which artificial intelligence approaches turn out to be the major path. This paper reveals the artificial intelligence-based load modelling technique to enhance the knowledge of current and future load information considering geographical and weather dependencies. This paper presents a recurrent neural network based sequence to sequence (Seq2Seq) model to forecast the short-term power loads. Also, a feature attention mechanism, which is along channel and time directions, is developed to improve the efficiency of feature learning. The experiments over three publicly available datasets demonstrate the accuracy and effectiveness of the proposed model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

SERS-based ssDNA composition analysis with inhomogeneous peak broadening and reservoir computing

Surface-enhanced Raman spectroscopy employed in conjunction with post-processing machine learning methods is a promising technique for effective data analysis, allowing one to enhance the molecular and chemical composition analysis of information rich DNA molecules. In this work, we report on a room temperature inhomogeneous broadening as a function of the increased adenine concentration and employ this feature to develop one-dimensional and two dimensional chemical composition classification models of 200 long single stranded DNA sequences. Afterwards, we develop a reservoir computing chemical composition classification scheme of the same molecules and demonstrate enhanced performance that does not rely on manual feature identification.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

The hTERT core promoter forms three parallel G-quadruplexes

The structure of the 68 nt sequence with G-quadruplex forming potential within the hTERT promoter is disputed. One model features a structure with three stacked parallel G-quadruplex units, while another features an unusual duplex hairpin structure adjoined to two stacked parallel and antiparallel quadruplexes. We report here the results of an integrated structural biology study designed to distinguish between these possibilities. As part of our study, we designed a sequence with an optimized hairpin structure and show that its biophysical and biochemical properties are inconsistent with the structure formed by the hTERT wild-type sequence. By using circular dichroism, thermal denaturation, nuclear magnetic resonance spectroscopy, analytical ultracentrifugation, small-angle X-ray scattering, molecular dynamics simulations and a DNase I cleavage assay we found that the wild type hTERT core promoter folds into a stacked, three-parallel G-quadruplex structure. The hairpin structure is inconsistent with all of our experimental data obtained with the wild-type sequence. All-atom models for both structures were constructed using molecular dynamics simulations. These models accurately predicted the experimental hydrodynamic properties measured for each structure. We found with certainty that the wild-type hTERT promoter sequence does not form a hairpin structure in solution, but rather folds into a compact stacked three-G-quadruplex conformation.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1989

Ultraviolet spectroscopy of pre-main-sequence accretion disks

Low-resolution, ultraviolet spectra of the pre-main-sequence objects Z Canis Majoris, V1057 Cygni, and FU Orionis are presented. Ultraviolet absorption features indicate spectral types of A5 I for FU Ori and F5 I for Z CMa. These results are in reasonable agreement with predictions of simple accretion disk models. The lack of significant veiling of ultraviolet absorption features implies that a hot boundary layer at the inner edge of the disk contributes less than 20 percent of the radiation at 2600-3200 A, which is significantly smaller than expected. It is suggested that accretion has significantly modified the structure of the underlying pre-main-sequence stars in these systems (perhaps by expanding the photosphere or by spinning up a radiative photosphere close to breakup velocity, or both), or that the boundary layer region is much more extended above the disk midplane than standard thin disk theories predict.

Kenyon, S. J.↗
DOE OSTI2019

Fractional Operators Applied to Geophysical Electromagnetics

A growing body of applied mathematics literature in recent years has focused on the application of fractional calculus to problems of anomalous transport. In these analyses, the anomalous transport (of charge, tracers, fluid, etc.) is presumed attributable to long–range correlations of material properties within an inherently complex, and in some cases self-similar, conducting medium. Rather than considering an exquisitely discretized (and computationally intractable) representation of the medium, the complex and spatially correlated heterogeneity is represented through reformulation of the governing equation for the relevant transport physics such that its coefficients are, instead, smooth but paired with fractional–order space derivatives. Here we apply these concepts to the scalar Helmholtz equation and its use in electromagnetic interrogation of Earth’s interior through the magnetotelluric method. We outline a practical algorithm for solving the Helmholtz equation using spectral methods coupled with finite element discretizations. Execution of this algorithm for the magnetotelluric problem reveals several interesting features observable in field data: long–range correlation of the predicted electromagnetic fields; a power–law relationship between the squared impedance amplitude and squared wavenumber whose slope is a function of the fractional exponent within the governing Helmholtz equation; and, a non–constant apparent resistivity spectrum whose variability arises solely from the fractional exponent. In geologic settings characterized by self–similarity (e.g. fracture systems; thick and richly–textured sedimentary sequences, etc.) we posit that these diagnostics are useful for geologic characterization of features far below the typical resolution limit of electromagnetic methods in geophysics.

58 GEOSCIENCES↗
DOE OSTI2021

Z-Sequence: photometric redshift predictions for galaxy clusters with sequential random k-nearest neighbours

ABSTRACT We introduce Z-Sequence, a novel empirical model that utilizes photometric measurements of observed galaxies within a specified search radius to estimate the photometric redshift of galaxy clusters. Z-Sequence itself is composed of a machine learning ensemble based on the k-nearest neighbours algorithm. We implement an automated feature selection strategy that iteratively determines appropriate combinations of filters and colours to minimize photometric redshift prediction error. We intend for Z-Sequence to be a standalone technique but it can be combined with cluster finders that do not intrinsically predict redshift, such as our own DEEP-CEE. In this proof-of-concept study, we train, fine-tune, and test Z-Sequence on publicly available cluster catalogues derived from the Sloan Digital Sky Survey. We determine the photometric redshift prediction error of Z-Sequence via the median value of |Δ$z$|/(1 + $z$) (across a photometric redshift range of 0.05 ≤ $z$ ≤ 0.6) to be ∼0.01 when applying a small search radius. The photometric redshift prediction error for test samples increases by 30–50 per cent when the search radius is enlarged, likely due to line-of-sight interloping galaxies. Eventually, we aim to apply Z-Sequence to upcoming imaging surveys such as the Legacy Survey of Space and Time to provide photometric redshift estimates for large samples of as yet undiscovered and distant clusters.

Chan, Matthew C.↗
DOE OSTI2018

Universality Classes of Interaction Structures for NK Fitness Landscapes

Kauffman’s NK-model is a paradigmatic example of a class of stochastic models of genotypic fitness landscapes that aim to capture generic features of epistatic interactions in multilocus systems. Genotypes are represented as sequences of L binary loci. The fitness assigned to a genotype is a sum of contributions, each of which is a random function defined on a subset of k≤L loci. These subsets or neighborhoods determine the genetic interactions of the model. Whereas earlier work on the NK model suggested that most of its properties are robust with regard to the choice of neighborhoods, recent work has revealed an important and sometimes counter-intuitive influence of the interaction structure on the properties of NK fitness landscapes. Here we review these developments and present new results concerning the number of local fitness maxima and the statistics of selectively accessible (that is, fitness-monotonic) mutational pathways. In particular, we develop a unified framework for computing the exponential growth rate of the expected number of local fitness maxima as a function of L, and identify two different universality classes of interaction structures that display different asymptotics of this quantity for large k. Moreover, we show that the probability that the fitness landscape can be traversed along an accessible path decreases exponentially in L for a large class of interaction structures that we characterize as locally bounded. Finally, we discuss the impact of the NK interaction structures on the dynamics of evolution using adaptive walk models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

A novel bacterial protein family that catalyses nitrous oxide reduction

Nitrous oxide (N 2 O), a driver of global warming and climate change, has reached unprecedented concentrations in Earth’s atmosphere. Current N 2 O sources outpace N 2 O sinks, emphasizing the need for comprehensive understanding of processes that consume N 2 O. Microbes that express the enzyme N 2 O reductase (N 2 OR) convert N 2 O to climate change-neutral dinitrogen (N 2 ). Known N 2 ORs belong to the canonical clade I and clade II NosZ reductases and are considered key enzymes for N 2 O reduction. Here we report a previously unrecognized protein family with a role in N 2 O reduction, clade III lactonase-type N 2 OR (L-N 2 OR), which diverges in sequence from canonical NosZ but conserves three-dimensional protein structural features. Integrated physiological, metagenomic, proteomic and structural modelling studies demonstrate that L-N 2 ORs catalyse N 2 O reduction. L-N 2 OR genes occur in several phyla, predominantly in uncultured taxa with broad geographic distribution. Our findings expand the known diversity of N 2 ORs and implicate previously unrecognized taxa (for example, Nitrospinota) in N 2 O consumption. In conclusion, the expansion of N 2 OR diversity and the identification of a novel type of catalyst for N 2 O reduction advances the understanding of N 2 O sinks, has implications for greenhouse gas emission and climate change modelling, and expands opportunities for innovative biotechnologies aimed at curbing N 2 O emissions.

He, Guang 何广 [Univ. of Tennessee, Knoxville, TN (U↗
DOE OSTI2026

Explaining System-Level Prognostics with Established Machine Learning Methods

System-level prognostics is crucial for ensuring reliability and enabling predictive maintenance in complex systems with interconnected components. This study presents a framework that integrates data-driven methods to predict the remaining useful life (RUL) of a subsystem under multiple and concurrent faults within a nuclear power plant system with explainable artificial intelligence (XAI). A nuclear power plant (NPP) operation was simulated to model the degradation behavior of NPP components, and four machine learning models—Gradient Boosting Regressor (GBR), Support Vector Regressor (SVR), Fully Connected Neural Network (FCNN), and Long Short-Term Memory (LSTM)—were evaluated for prognostics with a novel system RUL parameter. The LSTM model demonstrated potential superior repeatability, while SHAP (SHapley Additive exPlanations) for explainability provided consistent and trustworthy global explanations. In contrast, LIME (Local Interpretable Model-agnostic Explanations) offered localized interpretability but showed reduced stability for sequential data. Key findings include the interplay between component-level degradation and system-wide performance, with LSTM effectively capturing these dynamics through sequence-level predictions. The XAI techniques enhanced transparency by identifying critical features influencing model predictions and aligning with domain knowledge. Furthermore, this framework has significant implications for improving trust and understanding in predictive maintenance, particularly in safety-critical industries like nuclear energy.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

GQLink: an implementation of Quantized State Systems (QSS) methods in Geant4

Simulations in high energy physics (HEP) often require the numerical solution of ordinary differential equations (ODE) to determine the trajectories of charged particles in a magnetic field when particles move throughout detector volumes. Each crossing of a volume interrupts the underlying numerical method that solves the equations of motion, triggering iterative algorithms to estimate the intersection point within a given accuracy. The computational cost of this procedure can grow significantly depending on the application at hand. Quantized State System (QSS) is a recent family of discrete-event driven numerical methods exhibiting attractive features for this type of problems, such as native dense output (sequences of polynomial segments updated only by accuracy-driven events) and lightweight detection and handling of volume crossings. In this work we present GQLink, a proof-of-concept integration of QSS with the Geant4 simulation toolkit which stands as an interface for co-simulation that orchestrates robustly and transparently the interaction between the QSS simulation engine and aspects such as geometry definition and physics processes controlled by Geant4. In conclusion, we validate the accuracy and study the performance of the method in simple geometries (subject to intense volume crossing activity) and then in a realistic HEP application using a full CMS detector configuration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Optical evolution of AT 2024wpp: the high-velocity outflows in Cow-like transients are consistent with high spherical symmetry

ABSTRACT We present the analysis of optical/near-infrared (NIR) data and host galaxy properties of a bright, extremely rapidly evolving transient, AT 2024wpp, which resembles the enigmatic AT 2018cow. AT 2024wpp rose to a peak brightness of $c=-21.9$ mag in 4.3 d and remained above the half-maximum brightness for only 6.7 d. The blackbody fits to the photometry show that the event remained persistently hot ($T\gtrsim 20\, 000$ K) with a rapidly receding photosphere ($v\sim 11\, 500$ km s$^{-1}$), similarly to AT 2018cow albeit with a several times larger photosphere. $JH$ photometry reveals an NIR excess over the thermal emission at $\sim +20$ d, indicating a presence of an additional component. The spectra are consistent with blackbody emission throughout our spectral sequence ending at $+21.9$ d, showing a tentative, very broad emission feature at $\sim 5500$ Å – implying that the optical photosphere is likely within a near-relativistic outflow. Furthermore, reports of strong X-ray and radio emission cement the nature of AT 2024wpp as a likely Cow-like transient. AT 2024wpp is the second event of the class with optical polarimetry. Our $BVRI$ observations obtained from $+6.1$ to $+14.4$ d show a low polarization of $P\lesssim 0.5$ per cent across all bands, similar to AT 2018cow that was consistent with $P\sim 0$ per cent during the same outflow-driven phase. In the absence of evidence for a preferential viewing angle, it is unlikely that both events would have shown low polarization in the case that their photospheres were aspherical. As such, we conclude that the near-relativistic outflows launched in these events are likely highly spherical, but polarimetric observations of further events are crucial to constrain their ejecta geometry and stratification in detail.

Pursiainen, M.↗
DOE OSTI2017

Spin-reorientation transitions in the Cairo pentagonal magnet Bi 4 Fe 5 O 13 F

Here, we show that interlayer spins play a dual role in the Cairo pentagonal magnet Bi 4 Fe 5 O 13 F, on one hand mediating the three-dimensional magnetic order, and on the other driving spin-reorientation transitions both within and between the planes. The corresponding sequence of magnetic orders unraveled by neutron diffraction and Mössbauer spectroscopy features two orthogonal magnetic structures described by opposite local vector chiralities, and an intermediate, partly disordered phase with nearly collinear spins. A similar collinear phase has been predicted theoretically to be stabilized by quantum fluctuations, but Bi 4 Fe 5 O 13 F is very far from the relevant parameter regime. While the observed in-plane reorientation cannot be explained by any standard frustration mechanism, our ab initio band-structure calculations reveal strong single-ion anisotropy of the interlayer Fe 3+ spins that turns out to be instrumental in controlling the local vector chirality and the associated interlayer order.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗