Search NASA⌕ Search

SEARCH · Search NASA

Results for “embedding model”

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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Concepts and Development of Bio-Inspired Distributed Embedded Wired/Wireless Sensor Array Architectures for Acoustic Wave Sensing in Integrated Aerospace Vehicles

This paper discusses the modeling of acoustic emissions in plate structures and their sensing by embedded or surface bonded piezoelectric sensor arrays. Three different modeling efforts for acoustic emission (AE) wave generation and propagation are discussed briefly along with their advantages and disadvantages. Continuous sensors placed at right angles on a plate are being discussed as a new approach to measure and locate the source of acoustic waves. Evolutionary novel signal processing algorithms and bio-inspired distributed sensor array systems are used on large structures and integrated aerospace vehicles for AE source localization and preliminary results are presented. These systems allow for a great reduction in the amount of data that needs to be processed and also reduce the chances of false alarms from ambient noises. It is envisioned that these biomimetic sensor arrays and signal processing techniques will be useful for both wireless and wired sensor arrays for real time health monitoring of large integrated aerospace vehicles and earth fixed civil structures. The sensor array architectures can also be used with other types of sensors and for other applications.

Ghoshal, Anindya↗
DOE OSTI2024

AstroCLIP: a cross-modal foundation model for galaxies

ABSTRACT We present AstroCLIP, a single, versatile model that can embed both galaxy images and spectra into a shared, physically meaningful latent space. These embeddings can then be used – without any model fine-tuning – for a variety of downstream tasks including (1) accurate in-modality and cross-modality semantic similarity search, (2) photometric redshift estimation, (3) galaxy property estimation from both images and spectra, and (4) morphology classification. Our approach to implementing AstroCLIP consists of two parts. First, we embed galaxy images and spectra separately by pre-training separate transformer-based image and spectrum encoders in self-supervised settings. We then align the encoders using a contrastive loss. We apply our method to spectra from the Dark Energy Spectroscopic Instrument and images from its corresponding Legacy Imaging Survey. Overall, we find remarkable performance on all downstream tasks, even relative to supervised baselines. For example, for a task like photometric redshift prediction, we find similar performance to a specifically trained ResNet18, and for additional tasks like physical property estimation (stellar mass, age, metallicity, and specific-star-formation rate), we beat this supervised baseline by 19 per cent in terms of R2. We also compare our results with a state-of-the-art self-supervised single-modal model for galaxy images, and find that our approach outperforms this benchmark by roughly a factor of two on photometric redshift estimation and physical property prediction in terms of R2, while remaining roughly in-line in terms of morphology classification. Ultimately, our approach represents the first cross-modal self-supervised model for galaxies, and the first self-supervised transformer-based architectures for galaxy images and spectra.

Parker, Liam (ORCID:0009000749521674)↗
DOE OSTI2025

Quantum sensing of paramagnetic analytes by nanodiamonds in levitated microdroplets and aqueous solutions

Nanodiamonds (ND) hosting negatively charged nitrogen-vacancy (NV-) color centers have received attention for applications in magnetic field, electric field, chemical, and bio-sensing. The versatility of these probes is their excellent room-temperature optical and spin properties, along with their small size, functionalized surfaces and resistance to bleaching, making them ideal as nanoscopic sensors in picoliter volumes (e.g. single cells, but also microcompartments and aerosols). For quantitative ND-NV- sensing of paramagnetic analytes in such contexts, however, there remains an incomplete understanding of how factors related to the aqueous phase environment control detection efficiency. To address this, optically detected magnetic resonance (ODMR) is measured in bulk macroscale solutions and single levitated microdroplets as a function of Gd+3 concentration (340 nM to 1.5 mM), nanodiamond size, pH, competitor ions, and ligands. The ODMR response to [Gd+3] is found to be nonlinear, and pH, ND and sample volume dependent; indicating the detection of Gd+3 requires efficient adsorption of the analyte to the diamond surface. Langmuir adsorption isotherms embedded in a quantitative photophysical model links the ODMR response to adsorption thermodynamics of Gd+3. The equilibrium constant for Gd+3 adsorption to a carboxylated ND surface is determined to be (1 ± 0.5) x 105 M-1 corresponding to a free energy of adsorption of (-28 ± 1) kJ mol-1. These results provide general insight into how complex aqueous and microscale environments impact nanodiamond based quantum sensing modalities, and portend their application as quantitative chemical sensors in microenvironments.

Brown, Emily K↗
DOE OSTI2024

Exploring dielectric properties in atomistic models of amorphous boron nitride

Abstract We report a theoretical study of dielectric properties of models of amorphous Boron Nitride, using interatomic potentials generated by machine learning. We first perform first-principles simulations on small (about 100 atoms in the periodic cell) sample sizes to explore the emergence of mid-gap states and its correlation with structural features. Next, by using a simplified tight-binding electronic model, we analyse the dielectric functions for complex three dimensional models (containing about 10.000 atoms) embedding varying concentrations of sp 1 , sp 2 and sp 3 bonds between B and N atoms. Within the limits of these methodologies, the resulting value of the zero-frequency dielectric constant is shown to be influenced by the population density of such mid-gap states and their localization characteristics. We observe nontrivial correlations between the structure-induced electronic fluctuations and the resulting dielectric constant values. Our findings are however just a first step in the quest of accessing fully accurate dielectric properties of as-grown amorphous BN of relevance for interconnect technologies and beyond.

Materials Science↗
DOE OSTI2026

The ballad of LLM agents: philosophical reasoning for chemistry

Large language models (LLMs) show remarkable potential for scientific reasoning but often produce unreliable or scientifically unactionable outputs when faced with multi-step logic, domain grounding, and interpretability challenges, especially in complex fields like chemistry and materials science. Here, we introduce a framework of philosophical reasoning agents, inspired by canonical thinkers such as Socrates, Descartes, Kant, and Hume, to guide LLM behavior via structured prompt engineering. These agents embody distinct reasoning paradigms (dialectical inquiry, deductive logic, rule-based judgment, and empirical validation) and are evaluated across multiple chemistry subdomains, physical, analytical, general, inorganic, and organic chemistry, using the ChemBench benchmark. Our agentic prompting approach yields substantial accuracy gains on open-ended numerical chemistry questions, with gains of +11.5 percentage points for GPT-4o with Hume, +4.5 percentage points for GPT-5 with Kant, and +21.8 percentage points for GPT-5.1 with Socrates at the strict 1% error threshold, relative to the corresponding base models. Beyond accuracy, we observe benchmark-level model–agent performance patterns, suggesting that different prompting styles interact differently with each base model. These findings demonstrate that embedding philosophy-of-science principles into multi-agent frameworks can improve and produce interpretable, adaptive, and domain-aligned scientific LLMs.

Harb, Hassan [Argonne National Laboratory (ANL), A↗
DOE OSTI2025

CAFE AU LAIT: Compute-Aware Federated Augmented Low-Rank AI Training

Federated finetuning is crucial for unlocking the knowledge embedded in pretrained Large Language Models (LLMs) when data are geographically distributed across clients. Unlike finetuning with data from a single institution, federated finetuning allows collaboration across multiple institutions, enabling the utilization of diverse and decentralized datasets while preserving data privacy. Given the high computing costs of LLM training and the emphasis on energy efficiency in Federated Learning (FL), Low-Rank Adaptation (LoRA) has emerged as a widely adopted algorithm due to its significantly reduced number of trainable parameters. However, this assumes that all data silos have the necessary computing resources to compute local updates of LLMs. Nevertheless, in practice, the computing resources across clients are highly heterogeneous: while some may have access to hundreds of GPUs, others might have limited or no GPU access. Recently, federated finetuning using synthetic data has been proposed, allowing clients to participate in a collaborative training run without training LLMs locally. However, our experimental results reveal a performance gap between models trained using synthetic data and those trained using local updates. Motivated by the observed heterogeneity in computing resources and the performance gap, we propose a novel two-stage algorithm that leverages the storage and computing capabilities of a strong server. In the first stage, under the coordination of the strong server, clients with limited computing resources collaborate to generate synthetic data, which is transferred to and stored on the strong server. In the second stage, the strong server uses this synthetic data on behalf of the resource-constrained clients to perform federated LoRA finetuning alongside clients with sufficient computing resources. This approach ensures that all clients can participate in the finetuning process. Experimental results demonstrate that incorporating local updates from even a small fraction of clients improves performance compared to using synthetic data for all clients. Furthermore, we incorporate the Gaussian mechanism in both stages to guarantee client-level differential privacy.

Wang, Jiayi [ORNL]↗
DOE OSTI2026

Self-Admitted Technical Debt in Scientific Software: Prioritization, Sentiment, and Propagation Across Artifacts

Self-admitted technical debt (SATD) impairs scientific software (SSW), yet its prioritization, sentiment, persistence, and propagation remains underexplored. Understanding how SSW developers express, and address SATD is crucial for improving SSW maintenance, and tooling. This study investigates how SATD types and artifacts in SSW are prioritized, how sentiment relates to urgency, SATD removal and resolution rates, and the extent to which SATD propagates across artifacts. We analyzed nine SSW repositories using a SATD classification model and a semantic embedding-based prioritization heuristic. SATD was examined across multiple artifacts, with sentiment assessed via a fine-tuned transformer. Propagation was traced, priority scores compared to static analysis, and removal and resolution rates quantified. SATD in comments, commits, and pull requests receive higher priority than SATD in issues, with negative sentiment amplifying urgency. Resolution and removal rates lag behind open-source software (OSS) averages. Most SATD remains confined to the originating artifact, but longer propagation chains are rare and correlate with higher priority, highlighting persistent and high impact debt. Prioritization is influenced by artifact type and sentiment, while low removal and resolution rates signal persistent debt. Cross-artifact propagation marks high priority, unresolved SATD, providing empirical guidance for targeted monitoring, review prioritization, and tool supported maintenance in SSW.

Melin, Eric [Boise State University]↗
DOE OSTI2026

V-HAMSTeR v1.0.0

V-HAMSTeR is a bioinformatics software tool designed to predict the hosts of viruses directly from genomic sequences. It can be used by researchers to predict animal, prokaryotic, plant, protist or fungal viral hosts including viruses that may be fragmented or discovered in environmental metagenomic datasets. Features & Uses: The software employs a novel dual-stream deep learning architecture that dynamically fuses implicit sequence embeddings from a genomic foundation model with 13 explicit, handcrafted biological features (e.g., coding density and strand switch rates). To ensure maximum reliability, V=HAMSTeR deploys a 5-fold deep ensemble calibrated via Joint Temperature Scaling, providing users with statistically rigorous confidence probabilities. It also features an automated sequence chunking and mean-pooling module to seamlessly process variable-length contigs. Advantages Over Similar Technologies: Existing tools (e.g., IPEV, RNAVirHost) typically rely on either basic k-mers or isolated neural networks. V-HAMSTeR's hybrid architecture captures both broad genomic context and specific biological motifs that standalone foundation models often miss. Furthermore, unlike competitor tools that struggle with incomplete data or exhibit extreme overconfidence, V-HAMSTeR is explicitly benchmarked and mathematically calibrated for fragmented assemblies (1kb–10kb). This makes it uniquely robust, accurate, and trustworthy for the messy reality of real-world environmental viromics.

Grigson, Susie [Lawrence Berkeley National Laborat↗
NASA NTRS1984

The nature of AFGL 2591 and its associated molecular outflow: Infrared and millimeter-wave observations

The results of infrared photometry from 2 to 160 microns of AFGL and CO(12) observations of its associated molecular cloud and high velocity molecular outflow are presented and discussed. The observed solar luminosity is 6.7 x 10(4) at a distance of 2 kpc. The spectrum of AFGL 2591 is interpreted in the context of a model in which a single embedded object is the dominant source of the infrared luminosity. This object is determined to be surrounded by a compact, optically thick dust shell with a temperature in excess of several hundred degrees kelvin. The extinction to this source is estimated to be between 26 and 50 visual magnitudes. The absolute position of the infrared sources at 10 microns was determined to an accuracy of + or in. This indicates for the first time that the IR source and H2O source are not coincident. The CO(12) observations show the high-velocity molecular flow near AFGL 2591 to be extended, bipolar and roughly centered on the infrared emission. The observations suggest that the red-shifted flow component extends beyond the boundary of the ambient cloud within which AFGL 2591 is embedded. The CO(12) observations also show that AFGL 2591 is embedded in a molecular cloud with an LSR velocity of -5 km/s.

Lada, C. J.↗
NASA NTRS1984

The nature of AFGL 2591 and its associated molecular outflow Infrared and millimeter-wave observations

The results of infrared photometry from 2 to 160 microns of AFGL and CO(12) observations of its associated molecular cloud and high velocity molecular outflow are presented and discussed. The observed solar luminosity is 6.7 x 10(4) at a distance of 2 kpc. The spectrum of AFGL 2591 is interpreted in the context of a model in which a single embedded object is the dominant source of the infrared luminosity. This object is determined to be surrounded by a compact, optically thick dust shell with a temperature in excess of several hundred degrees kelvin. The extinction to this source is estimated to be between 26 and 50 visual magnitudes. The absolute position of the infrared sources at 10 microns was determined to an accuracy of + or - 1 in. This indicates for the first time that the IR source and H2O source are not coincident. The CO(12) observations show the high-velocity molecular flow near AFGL 2591 to be extended, bipolar and roughly centered on the infrared emission. The observations suggest that the red-shifted flow component extends beyond the boundary of the ambient cloud within which AFGL 2591 is embedded. The CO(12) observations also show that AFGL 2591 is embedded in a molecular cloud with an LSR velocity of -5 km/s.

Lada, C. J.↗
NASA NTRS1995

Use of midlatitude soil moisture and meteorological observations to validate soil moisture simulations with biosphere and bucket models

Soil moisture observations in sites with natural vegetation were made for several decades in the former Soviet Union at hundreds of stations. In this paper, the authors use data from six of these stations from different climatic regimes, along with ancillary meteorological and actinometric data, to demonstrate a method to validate soil moisture simulations with biosphere and bucket models. Some early and current general circulation models (GCMs) use bucket models for soil hydrology calculations. More recently, the Simple Biosphere Model (SiB) was developed to incorporate the effects of vegetation on fluxes of moisture, momentum, and energy at the earth's surface into soil hydrology models. Until now, the bucket and SiB have been verified by comparison with actual soil moisture data only on a limited basis. In this study, a Simplified SiB (SSiB) soil hydrology model and a 15-cm bucket model are forced by observed meteorological and actinometric data every 3 h for 6-yr simulations at the six stations. The model calculations of soil moisture are compared to observations of soil moisture, literally 'ground truth,' snow cover, surface albedo, and net radiation, and with each other. For three of the stations, the SSiB and 15-cm bucket models produce good simulations of seasonal cycles and interannual variations of soil moisture. For the other three stations, there are large errors in the simulations by both models. Inconsistencies in specification of field capacity may be partly responsible. There is no evidence that the SSiB simulations are superior in simulating soil moisture variations. In fact, the models are quite similar since SSiB implicitly has a bucket embedded in it. One of the main differences between the models is in the treatment of runoff due to melting snow in the spring -- SSiB incorrectly puts all the snowmelt into runoff. While producing similar soil moisture simulations, the models produce very different surface latent and sensible heat fluxes, which would have large effects on GCM simulations.

Robock, Alan↗
NASA NTRS2004

Analysis of SMA Hybrid Composite Structures using Commercial Codes

A thermomechanical model for shape memory alloy (SMA) actuators and SMA hybrid composite (SMAHC) structures has been recently implemented in the commercial finite element codes MSC.Nastran and ABAQUS. The model may be easily implemented in any code that has the capability for analysis of laminated composite structures with temperature dependent material properties. The model is also relatively easy to use and requires input of only fundamental engineering properties. A brief description of the model is presented, followed by discussion of implementation and usage in the commercial codes. Results are presented from static and dynamic analysis of SMAHC beams of two types; a beam clamped at each end and a cantilevered beam. Nonlinear static (post-buckling) and random response analyses are demonstrated for the first specimen. Static deflection (shape) control is demonstrated for the cantilevered beam. Approaches for modeling SMAHC material systems with embedded SMA in ribbon and small round wire product forms are demonstrated and compared. The results from the commercial codes are compared to those from a research code as validation of the commercial implementations; excellent correlation is achieved in all cases.

Turner, Travis L.↗
NASA NTRS2000

Mechanical forces in plant growth and development

Plant cells perceive forces that arise from the environment and from the biophysics of plant growth. These forces provide meaningful cues that can affect the development of the plant. Seedlings of Arabidopsis thaliana were used to examine the cytoplasmic tensile character of cells that have been implicated in the gravitropic response. Laser-trapping technology revealed that the starch-containing statoliths of the central columella cells in root caps are held loosely within the cytoplasm. In contrast, the peripheral cells have starch granules that are relatively resistant to movement. The role of the actin cytoskeleton in affecting the tensile character of these cells is discussed. To explore the role that biophysical forces might play in generating developmental cues, we have developed an experimental model system in which protoplasts, embedded in a synthetic agarose matrix, are subjected to stretching or compression. We have found that protoplasts subjected to these forces from five minutes to two hours will subsequently elongate either at right angles or parallel to the tensive or compressive force vector. Moreover, the cortical microtubules are found to be organized either at right angles or parallel to the tensive or compressive force vector. We discuss these results in terms of an interplay of information between the extracellular matrix and the underlying cytoskeleton.

Non-NASA Center↗
NASA NTRS2005

Analysis of SMA Hybrid Composite Structures in MSC.Nastran and ABAQUS

A thermoelastic constitutive model for shape memory alloy (SMA) actuators and SMA hybrid composite (SMAHC) structures was recently implemented in the commercial finite element codes MSC.Nastran and ABAQUS. The model may be easily implemented in any code that has the capability for analysis of laminated composite structures with temperature dependent material properties. The model is also relatively easy to use and requires input of only fundamental engineering properties. A brief description of the model is presented, followed by discussion of implementation and usage in the commercial codes. Results are presented from static and dynamic analysis of SMAHC beams of two types; a beam clamped at each end and a cantilever beam. Nonlinear static (post-buckling) and random response analyses are demonstrated for the first specimen. Static deflection (shape) control is demonstrated for the cantilever beam. Approaches for modeling SMAHC material systems with embedded SMA in ribbon and small round wire product forms are demonstrated and compared. The results from the commercial codes are compared to those from a research code as validation of the commercial implementations; excellent correlation is achieved in all cases.

Turner, Travis L.↗
NASA NTRS2006

Molecular-dynamics Simulation-based Cohesive Zone Representation of Intergranular Fracture Processes in Aluminum

A traction-displacement relationship that may be embedded into a cohesive zone model for microscale problems of intergranular fracture is extracted from atomistic molecular-dynamics simulations. A molecular-dynamics model for crack propagation under steady-state conditions is developed to analyze intergranular fracture along a flat 99 [1 1 0] symmetric tilt grain boundary in aluminum. Under hydrostatic tensile load, the simulation reveals asymmetric crack propagation in the two opposite directions along the grain boundary. In one direction, the crack propagates in a brittle manner by cleavage with very little or no dislocation emission, and in the other direction, the propagation is ductile through the mechanism of deformation twinning. This behavior is consistent with the Rice criterion for cleavage vs. dislocation blunting transition at the crack tip. The preference for twinning to dislocation slip is in agreement with the predictions of the Tadmor and Hai criterion. A comparison with finite element calculations shows that while the stress field around the brittle crack tip follows the expected elastic solution for the given boundary conditions of the model, the stress field around the twinning crack tip has a strong plastic contribution. Through the definition of a Cohesive-Zone-Volume-Element an atomistic analog to a continuum cohesive zone model element - the results from the molecular-dynamics simulation are recast to obtain an average continuum traction-displacement relationship to represent cohesive zone interaction along a characteristic length of the grain boundary interface for the cases of ductile and brittle decohesion. Keywords: Crack-tip plasticity; Cohesive zone model; Grain boundary decohesion; Intergranular fracture; Molecular-dynamics simulation

Yamakov, Vesselin I.↗
NASA NTRS2014

Sound Transmission Loss Through a Corrugated-Core Sandwich Panel with Integrated Acoustic Resonators

The goal of this study is to better understand the effect of structurally integrated resonators on the transmission loss of a sandwich panel. The sandwich panel has facesheets over a corrugated core, which creates long aligned chambers that run parallel to the facesheets. When ports are introduced through the facesheet, the long chambers within the core can be used as low-frequency acoustic resonators. By integrating the resonators within the structure they contribute to the static load bearing capability of the panel while also attenuating noise. An analytical model of a panel with embedded resonators is derived and compared with numerical simulations. Predictions show that acoustic resonators can significantly improve the transmission loss of the sandwich panel around the natural frequency of the resonators. In one configuration with 0.813 m long internal chambers, the diffuse field transmission loss is improved by more than 22 dB around 104 Hz. The benefit is achieved with no added mass or volume relative to the baseline structure. The embedded resonators are effective because they radiate sound out-of-phase with the structure. This results in destructive interference, which leads to less transmitted sound power.

Schiller, Noah H.↗
NASA NTRS2015

Numerical Computation of a Continuous-thrust State Transition Matrix Incorporating Accurate Hardware and Ephemeris Models

A significant body of work exists showing that providing a nonlinear programming (NLP) solver with expressions for the problem constraint gradient substantially increases the speed of program execution and can also improve the robustness of convergence, especially for local optimizers. Calculation of these derivatives is often accomplished through the computation of spacecraft's state transition matrix (STM). If the two-body gravitational model is employed as is often done in the context of preliminary design, closed form expressions for these derivatives may be provided. If a high fidelity dynamics model, that might include perturbing forces such as the gravitational effect from multiple third bodies and solar radiation pressure is used then these STM's must be computed numerically. We present a method for the power hardward model and a full ephemeris model. An adaptive-step embedded eight order Dormand-Prince numerical integrator is discussed and a method for the computation of the time of flight derivatives in this framework is presented. The use of these numerically calculated derivatieves offer a substantial improvement over finite differencing in the context of a global optimizer. Specifically the inclusion of these STM's into the low thrust missiondesign tool chain in use at NASA Goddard Spaceflight Center allows for an increased preliminary mission design cadence.

Low Thrust↗