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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A machine-learning-aided data recovery approach for predicting multi-material thermal behaviors in advanced test reactor capsules

Instrumented experiments conducted at test reactors are essential to the deployment of new advanced reactor systems. Designing new experiments and generating data on specific reactor conditions require significant investments in terms of both time and cost. Finite element analysis software can be used to create high-fidelity models of experiment environments in order to support the actual experiments, but computation time remains a concern in terms of applying outcomes to real-time usage of data (e.g., a digital twin [DT]). Here, the present research proposes a machine-learning (ML) aided approach to making temperature and displacement predictions based on the thickness of the outer gas gap on the experimental capsule used for in-pile demonstration of a novel new thermal conductivity probe in the Advanced Test Reactor (ATR). This capsule consisted of U10Zr fuel, a rodlet, sodium, and inner and outer capsules. Gas gaps existed between the fuel and the rodlet, and between the inner and the outer capsule. The learning data pertained to an experimental capsule's radial distributions of temperature and displacement, as obtained based on Abaqus and the physical features. For the first step of ML sequence, the temperature was predicted using three positional parameters. Next, the displacement was predicted using seven additional parameters. Each physical feature was normalized in order to be both nondimensional and standardized. The temperature and displacement predictions showed good agreement with the simulation results in all cases involving interpolation and extrapolation. Furthermore, data similarity enhancement increased the similarity between the training and the target data, thereby increasing the predictive accuracy of the ML models. In certain extrapolation cases involving limited original ML model accuracy, data similarity enhancement and data recovery was able to somewhat improve this accuracy.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2018

Radio-hosted Flight / Ground Interface for Operations Standardization

The interface between a spacecraft and its ground operations segment includes the flow of commands, configuration, and sequencing elements to the spacecraft, and the flow of telemetry and data products from the spacecraft. Creating and implementing a complete definition of this interface simplifies and standardizes mission operations, allowing easy sharing of operations personnel across missions. Early spacecraft featured a simple flight / ground interface (FGI) using hardware command decoding in the radio, driven by technological limitations of the time. Modern spacecraft use command and data handling (CDH) avionics on which flight software executes, which in turn controls and configures the mission, executes subsystem and instrument instructions, and implements critical fault protection actions. Deep space missions feature advanced operations software for running sequenced activities over a period of weeks, which allows them to function with only infrequent ground contact. This approach comes at the cost of increased complexity in the FGI, requiring expensive modifications to heritage flight software and ground systems. By hosting the interface in the radio instead of the CDH avionics, modern missions can approximate the FGI design simplicity of early spacecraft, with significant advantages for vendor competition, lowered costs, standardization of operations, and reduction of implementation risk.

Lock, Patricia D.↗
DOE OSTI2022

Methods for rule-based genome design

Methods and systems for designing, testing, and validating genome designs based on rules or constraints or conditions or parameters or features and scoring are described herein. A computer-implemented method includes receiving data for a known genome and a list of alleles, identifying and removing occurrences of each allele in the known genome, determining a plurality of allele choices with which to replace occurrences in the known genome, generating a plurality of alternative gene sequences for a genome design based on the known genome, wherein each alternative gene sequence comprises a different allele choice, applying a plurality of rules or constraints or conditions or parameters or features to each alternative gene sequence by assigning a score for each rule or constraint or condition or parameter or feature in each alternative gene sequence, resulting in scores for the applied plurality of rules or constraints or conditions or parameters or features, scoring each alternative gene sequence based on a weighted combination of the scores for the plurality of rules or constraints or conditions or parameters or features, and selecting at least one alternative gene sequence as the genome design based on the scoring.

Kuznetsov, Gleb↗
NASA NTRS1997

The Carbon-Rich Dust Sequence: Infrared Spectral Classification of Carbon Stars

We have developed a classification system for the infrared spectral emission from carbon stars, using a sample of 96 bright carbon-rich variables associated with the asymptotic giant branch. In addition to the stellar contribution, most spectra include the 11.2 micron emission feature from SiC and either a smooth cool continuum from amorphous carbon or a secondary emission feature at 9.0 microns. We have identified a carbon-rich dust sequence along which the amorphous carbon component grows while the 9.0 micron feature declines in strength. Along this spectral sequence, the fraction of Miras increases, as does the period of variability, the mass-loss rate, and the thickness of the circumstellar shell. Thus the carbon-rich dust sequence appears to be an evolutionary sequence. One class of spectra shows a particularly strong 9.0 micron feature, Enhanced C/O ratio, and several other unusual properties that suggest a different sequence, perhaps related to J stars.

Solan, G. C.↗
DOE OSTI2023

Unsupervised acoustic detection of fatigue-induced damage modes from wind turbine blades

This paper proposes a new in-situ damage detection approach for wind turbine blades, which leverages blade-internal non-stationary acoustic pressure fluctuations caused by the mechanical loading as the main source of excitation. This acoustic excitation was leveraged for the detection of fatigue-related damage modes on a full-scale wind turbine blade undergoing edgewise fatigue testing. An unsupervised, data-driven structural health monitoring strategy was developed to learn the normal cavity-internal acoustic sequences generated by the blade’s load cycles and to detect damage-related anomalies in the context of those sequences. A linear cepstral-coefficient based feature set was used to characterize the cavity-internal acoustics and LSTM-autoencoders were trained to accurately reconstruct healthy-case sequences. The reconstruction error was then used to characterize anomalous acoustic patterns within the blade cavity. The technique was able to detect a damage event earlier than a strain-based system by 120,000 load cycles.

17 WIND ENERGY↗
DOE OSTI2016

HUBBLE TARANTULA TREASURY PROJECT. V. THE STAR CLUSTER HODGE 301: THE OLD FACE OF 30 DORADUS

Based on color–magnitude diagrams (CMDs) from the Hubble Space Telescope Hubble Tarantula Treasury Project (HTTP) survey, we present the star formation history of Hodge 301, the oldest star cluster in the Tarantula Nebula. The HTTP photometry extends faint enough to reach, for the first time, the cluster pre-main sequence (PMS) turn-on, where the PMS joins the main sequence. Using the location of this feature, along with synthetic CMDs generated with the latest PARSEC models, we find that Hodge 301 is older than previously thought, with an age between 26.5 and 31.5 Myr. From this age, we also estimate that between 38 and 61 Type II supernovae exploded in the region. The same age is derived from the main sequence turn-off, whereas the age derived from the post-main sequence stars is younger and between 20 and 25 Myr. Other relevant parameters are a total stellar mass of ≈8800 ± 800 M {sub ⊙} and average reddening E ( B − V ) ≈ 0.22–0.24 mag, with a differential reddening δE ( B − V ) ≈ 0.04 mag.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Using Explainable Artificial Intelligence to Predict Perovskite Solar Cell Electrical Metastability from Operando Photoluminescence Images in Accelerated Stress Testing

Metal halide perovskite (MHP) solar cells exhibit a metastable response to bias governed by coupled ionic–electronic processes, complicating the conventional reciprocity relation between luminescence intensity and device open-circuit voltage (V oc ). This limits the use of luminescence as a diagnostic for device screening or accelerated stress testing, motivating new approaches that can interpret photoluminescence (PL) signals under nonequilibrium conditions. From the artificial intelligence perspective, we develop an explainable deep learning framework that integrates convolutional neural networks (CNN), long short-term memory (LSTM) layers, and an attention mechanism to learn spatiotemporal features from operando photoluminescence PL image sequences. The model achieves a mean absolute error of ±0.027 V in predicting open-circuit voltage transients and reduces extreme-tail errors by up to 78% compared to physics-based reciprocity calculations. Gradient-weighted Class Activation Mapping (Grad-CAM) provides interpretability by highlighting physically meaningful regions such as electrode edges and emergent defect features. From the engineering application perspective, this framework enables accurate, contactless prediction of device V oc and identification of degradation-relevant features during accelerated aging of perovskite solar cells. This approach demonstrates how explainable AI can enhance operando diagnostics and reliability analysis in photovoltaic devices under nonequilibrium conditions.

14 SOLAR ENERGY↗
NASA NTRS1992

Relative timing of substorm features in MHD simulations

An investigation of the temporal sequence of substorm phenomena based on three dimensional MHD (magnetohydrodynamic) simulations of magnetic reconnection and plasmoid formation is presented. The investigation utilizes a spatially localized resistivity model which leads to a significantly faster evolution than found in previous investigations. The analysis of the results concentrates on substorm features that have received considerable attention in the past. The formation of magnetic neutral lines, the occurrence of fast flows directed both earthward and tailward, and the magnetic field changes leading to the formation of the substorm current wedge, and to the depolarization of the magnetic field earthward of the reconnection region and its dependence on the spatial distribution of resistivity, are discussed. These phenomena are seen as an integral part of the nonlinear evolution of the three dimensional tearing instability.

Hesse, Michael↗
NASA NTRS1987

Spectrophotometry of comets Giacobini-Zinner and Halley

Optical window spectrophotometry was performed on comets Giacobini-Zinner and Halley over the interval 300-1000 nm. Band and band-sequence fluxes were obtained for the brightest features of OH, CN, NH, and C2, special care having been given to determinations of extinction, instrumental sensitivities, and corrections for Fraunhofer lines. C2 Swan band-sequence flux ratios were determined with unprecedented accuracy and compared with the predictions of the detailed equilibrium models of Krishna Swamy et al. (1977, 1979, 1981, and 1987). It is found that these band sequences do not agree with the predictions, which calls into question the assumptions made in deriving the model, namely resonance fluorescence statistical equilibrium. Suggestions are made as to how to resolve this discrepancy.

Tegler, Stephen C.↗
DOE OSTI2018

MicroPheno: predicting environments and host phenotypes from 16S rRNA gene sequencing using a k-mer based representation of shallow sub-samples

Microbial communities play important roles in the function and maintenance of various biosystems, ranging from the human body to the environment. A major challenge in microbiome research is the classification of microbial communities of different environments or host phenotypes. The most common and cost-effective approach for such studies to date is 16S rRNA gene sequencing. Recent falls in sequencing costs have increased the demand for simple, efficient and accurate methods for rapid detection or diagnosis with proved applications in medicine, agriculture and forensic science. We describe a reference- and alignment-free approach for predicting environments and host phenotypes from 16S rRNA gene sequencing based on k-mer representations that benefits from a bootstrapping framework for investigating the sufficiency of shallow sub-samples. Deep learning methods as well as classical approaches were explored for predicting environments and host phenotypes. A k-mer distribution of shallow sub-samples outperformed Operational Taxonomic Unit (OTU) features in the tasks of body-site identification and Crohn’s disease prediction. Aside from being more accurate, using k-mer features in shallow sub-samples allows (i) skipping computationally costly sequence alignments required in OTU-picking and (ii) provided a proof of concept for the sufficiency of shallow and short-length 16S rRNA sequencing for phenotype prediction. In addition, k-mer features predicted representative 16S rRNA gene sequences of 18 ecological environments, and 5 organismal environments with high macro-F1 scores of 0.88 and 0.87. For large datasets, deep learning outperformed classical methods such as Random Forest and Support Vector Machine.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1997

Mitochondrial gene arrangement of the horseshoe crab Limulus polyphemus L.: conservation of major features among arthropod classes

Numerous complete mitochondrial DNA sequences have been determined for species within two arthropod groups, insects and crustaceans, but there are none for a third, the chelicerates. Most mitochondrial gene arrangements reported for crustaceans and insect species are identical or nearly identical to that of Drosophila yakuba. Sequences across 36 of the gene boundaries in the mitochondrial DNA (mtDNA) of a representative chelicerate. Limulus polyphemus L., also reveal an arrangement like that of Drosophila yakuba. Only the position of the tRNA(LEU)(UUR) gene differs; in Limulus it is between the genes for tRNA(LEU)(CUN) and ND1. This positioning is also found in onychophorans, mollusks, and annelids, but not in insects and crustaceans, and indicates that tRNA(LEU)(CUN)-tRNA(LEU)(UUR)-ND1 was the ancestral gene arrangement for these groups, as suggested earlier. There are no differences in the relative arrangements of protein-coding and ribosomal RNA genes between Limulus and Drosophila, and none have been observed within arthropods. The high degree of similarity of mitochondrial gene arrangements within arthropods is striking, since some taxa last shared a common ancestor before the Cambrian, and contrasts with the extensive mtDNA rearrangements occasionally observed within some other metazoan phyla (e.g., mollusks and nematodes).

Non-NASA Center↗
DOE OSTI2026

Genomic Language model for Annotation of Repetitive Elements (GLARE) v1.0

GLARE (Genomic Language model for Annotation of Repetitive Elements) is a tool that classifies transposable elements (TEs)—the mobile, repetitive DNA sequences that make up large fractions of eukaryotic genomes. GLARE fine-tunes the NTv3-650M genomic language model on a harmonized collection of curated TE sequences from the PanTEon and Repbase reference databases, assigning each input sequence to one of 11 orders and 32 superfamilies in a Wicker-compatible taxonomy. Features. From nucleotide FASTA input, GLARE outputs per-sequence predictions, class summaries, composition figures, and an annotated FASTA. It provides calibrated confidence scores with optional abstention and runs on CPU or GPU. Uses. GLARE serves as a classification component in genome-annotation pipelines, downstream of TE discovery, supporting genome annotation and comparative and evolutionary genomics. Advantages. GLARE is the first repeat-element classifier to leverage a pretrained genomic language model. Combined with multi-database training, this approach outperformed all nine classifiers in the PanTEon benchmark, generalized better to unseen taxonomic clades, and remained robust to sequence orientation—a common failure mode of existing tools.

Bruna, Tomas [Lawrence Berkeley National Laborator↗
DOE OSTI2020

Sequencing and Analysis of the Sex Determination Region of Populus trichocarpa

The ages and sizes of a sex-determination region (SDR) are difficult to determine in non-model species. Due to the lack of recombination and enrichment of repetitive elements in SDRs, the quality of assembly with short sequencing reads is universally low. Unique features present in the SDRs help provide clues about how SDRs are established and how they evolve in the absence of recombination. Several Populus species have been reported with a male heterogametic configuration of sex (XX/XY system) mapped on chromosome 19, but the exact location of the SDR has been inconsistent among species, and thus far, none of these SDRs has been fully assembled in a genomic context. Here we identify the Y-SDR from a Y-linked contig directly from a long-read PacBio assembly of a Populus trichocarpa male individual. We also identified homologous gene sequences in the SDR of P. trichocarpa and the SDR of the W chromosome in Salix purpurea. We show that inverted repeats (IRs) found in the Y-SDR and the W-SDR are lineage-specific. We hypothesize that, although the two IRs are derived from the same orthologous gene within each species, they likely have independent evolutionary histories. Furthermore, the truncated inverted repeats in P. trichocarpa may code for small RNAs that target the homologous gene for RNA-directed DNA methylation. These findings support the hypothesis that diverse sex-determining systems may be achieved through similar evolutionary pathways, thereby providing a possible mechanism to explain the lability of sex-determination systems in plants in general.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Dynamic Graph Sequence Data from Simulated Neutron Reflectometry Measurements

This dataset comprises dynamic graph sequences derived from simulated in-situ neutron reflectometry measurements, capturing the gradual evolution of a layer structure over time. Each graph sequence represents a synthetic sample, with node features detailing the scattering vector and corresponding reflectivity measurements, while adjacency matrices have corresponding reference material parameters attached as metadata. The dataset spans multiple sets, each with a different number of sequences, offering a comprehensive basis for training models that handle dynamic input sequences with embedded physics. This dataset is particularly suited for tackling inverse problems with hidden physical states that evolve over time, challenges that are typically difficult to address using conventional iterative fitting methods.

36 MATERIALS SCIENCE↗
NASA NTRS1972

An unusual absorption feature in the far-ultraviolet spectrum of early-type supergiants.

The OAO-II satellite has been used to obtain far-UV scans of six early-type supergiants. The data reveal the presence of a distinct, broad absorption feature centered near 1720 A. This feature is unique in that it remains essentially constant in strength, breadth, and central position over the spectral type range BO I to A2 I. The feature also appears in the spectrum of the B-type shell star zeta Tau, with a strength comparable to that observed for the supergiants. It appears weakly, or not at all, in the B and A main-sequence spectra examined. The presence of the feature in spectra of supergiants and a shell star supports the hypothesis that it is an extended-envelope phenomenon.

Underhill, A. B.↗
NASA NTRS2004

Neural network tracking and extension of positive tracking periods

Feature detectors have been considered for the role of supplying additional information to a neural network tracker. The feature detector focuses on areas of the image with significant information. Basically, if a picture says a thousand words, the feature detectors are looking for the key phrases (keypoints). These keypoints are rotationally invariant and may be matched across frames. Application of these advanced feature detectors to the neural network tracking system at JPL has promising potential. As part of an ongoing program, an advanced feature detector was tested for augmentation of a neural network based tracker. The advance feature detector extended tracking periods in test sequences including aircraft tracking, rover tracking, and simulated Martian landing. Future directions of research are also discussed.

feature extraction↗
DOE OSTI2024

Phyllosticta paracitricarpa is synonymous with the EU quarantine fungus P. citricarpa based on phylogenomic analyses

Phyllosticta citricarpa is an important citrus-pathogen and a quarantine organism in the European Union. Its recently described relative, P. paracitricarpa, is very closely related and not listed as a quarantine organism. P. paracitricarpa is very difficult to distinguish from P. citricarpa, since its morphological features overlap and the barcoding gene sequences that were originally used to delimit them as distinct species have a low number of species-specific polymorphisms that have subsequently been shown to overlap between the two clades. Therefore, we performed extensive genomic analyses to determine whether the genetic variation between P. citricarpa and P. paracitricarpa strains should be considered to represent infraspecific variation within P. citricarpa, or whether it is indicative of distinct species. Using a phylogenomic analysis with 3,000 single copy ortholog genes and whole-genome comparisons, we determined that the variation between P. citricarpa and P. paracitricarpa can be considered as infraspecies variation within P. citricarpa. We also determined the level of variation in mitochondrial assemblies of several Phyllosticta species and concluded there are only minimal differences between the assemblies of P. citricarpa and P. paracitricarpa. Thus, using several orthogonal approaches, we here demonstrate that variation within the nuclear and mitochondrial genomes of other Phyllosticta species is larger than variation between genomes obtained from P. citricarpa and P. paracitricarpa strains. Thus, P. citricarpa and P. paracitricarpa should be considered as conspecific.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Proteogenomic characterization of difficult-to-treat breast cancer with tumor cells enriched through laser microdissection

Abstract Background Breast cancer (BC) is the most commonly diagnosed cancer and the leading cause of cancer death among women globally. Despite advances, there is considerable variation in clinical outcomes for patients with non-luminal A tumors, classified as difficult-to-treat breast cancers (DTBC). This study aims to delineate the proteogenomic landscape of DTBC tumors compared to luminal A (LumA) tumors. Methods We retrospectively collected a total of 117 untreated primary breast tumor specimens, focusing on DTBC subtypes. Breast tumors were processed by laser microdissection (LMD) to enrich tumor cells. DNA, RNA, and protein were simultaneously extracted from each tumor preparation, followed by whole genome sequencing, paired-end RNA sequencing, global proteomics and phosphoproteomics. Differential feature analysis, pathway analysis and survival analysis were performed to better understand DTBC and investigate biomarkers. Results We observed distinct variations in gene mutations, structural variations, and chromosomal alterations between DTBC and LumA breast tumors. DTBC tumors predominantly had more mutations inTP53,PLXNB3, Zinc finger genes, and fewer mutations inSDC2,CDH1,PIK3CA,SVIL, andPTEN. Notably, Cytoband 1q21, which contains numerous cell proliferation-related genes, was significantly amplified in the DTBC tumors. LMD successfully minimized stromal components and increased RNA–protein concordance, as evidenced by stromal score comparisons and proteomic analysis. Distinct DTBC and LumA-enriched clusters were observed by proteomic and phosphoproteomic clustering analysis, some with survival differences. Phosphoproteomics identified two distinct phosphoproteomic profiles for high relapse-risk and low relapse-risk basal-like tumors, involving several genes known to be associated with breast cancer oncogenesis and progression, includingKIAA1522,DCK,FOXO3,MYO9B,ARID1A,EPRS,ZC3HAV1, andRBM14. Lastly, an integrated pathway analysis of multi-omics data highlighted a robust enrichment of proliferation pathways in DTBC tumors. Conclusions This study provides an integrated proteogenomic characterization of DTBC vs LumA with tumor cells enriched through laser microdissection. We identified many common features of DTBC tumors and the phosphopeptides that could serve as potential biomarkers for high/low relapse-risk basal-like BC and possibly guide treatment selections.

Oncology↗