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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

The orbital record in stratigraphy

Orbital signals are being discovered in pre-Pleistocene sediments. Due to their hierarchical nature these cycle patterns are complex, and the imprecision of geochronology generally makes the assignment of stratigraphic cycles to specific orbital cycles uncertain, but in sequences such as the limnic Newark Group under study by Olsen and pelagic Cretaceous sequence worked on by our Italo-American group the relative frequencies yield a definitive match to the Milankovitch hierarchy. Due to the multiple ways in which climate impinges on depositional systems, the orbital signals are recorded in a multiplicity of parameters, and affect different sedimentary facies in different ways. In platform carbonates, for example, the chief effect is via sea-level variations (possibly tied to fluctuating ice volume), resulting in cycles of emergence and submergence. In limnic systems it finds its most dramatic expression in alternations of lake and playa conditions. Biogenic pelagic oozes such as chalks and the limestones derived from them display variations in the carbonate supplied by planktonic organisms such as coccolithophores and foraminifera, and also record variations in the aeration of bottom waters. Whereas early studies of stratigraphic cyclicity relied mainly on bedding variations visible in the field, present studies are supplementing these with instrumental scans of geochemical, paleontological, and geophysical parameters which yield quantitative curves amenable to time-series analysis; such analysis is, however, limited by problems of distorted time-scales. My own work has been largely concentrated on pelagic systems. In these, the sensitivity of pelagic organisms to climatic-oceanic changes, combined with the sensitivity of botton life to changes in oxygen availability (commonly much more restricted in the Past than now) has left cyclic patterns related to orbital forcing. These systems are further attractive because (1) they tend to offer depositional continuity, and (2) presence of abundant microfossils yields close ties to geochronology. A tantalizing possibility that stratigraphy may yield a record of orbital signals unrelated to climate has turned up in magnetic studies of our Cretaceous core. Magnetic secular variations here carry a strong 39 ka periodicity, corresponding to the theoretical obliquity period of that time - Does the obliquity cycle perhaps have some direct influence on the magnetic field?

Fischer, Alfred G.↗
NASA NTRS1992

Data management for JGOFS: Theory and design

The Joint Global Ocean Flux Study (JGOFS), currently being organized under the auspices of the Scientific Committee for Ocean Research (SCOR), is intended to be a decade long internationally coordinated program. The main goal of JGOFS is to determine and understand on a global scale the processes controlling the time-varying fluxes of carbon and associated biogenic elements in the ocean and to evaluate the related exchanges with the atmosphere, sea floor and continental boundaries. 'A long-term goal of JGOFS will be to establish strategies for observing, on long time scales, changes in ocean biogeochemical cycles in relation to climate change'. Participation from a large number of U.S. and foreign institutions is expected. JGOFS investigators have begun a set of time-series measurements and global surveys of a wide variety of biological, chemical and physical quantities, detailed process-oriented studies, satellite observations of ocean color and wind stress and modeling of the bio-geochemical processes. These experiments will generate data in amounts unprecedented in the biological and chemical communities; rapid and effortless exchange of these data will be important to the success of JGOFS.

Flierl, Glenn R.↗
NASA NTRS1992

Astronomical CCD observing and reduction techniques

CCD instrumentation and techniques in observational astronomy are surveyed. The general topics addressed include: history of large array scientific CCD imagers; noise sources and reduction processes; basic photometry techniques; introduction to differential time-series astronomical photometry using CCDs; 2D imagery; point source spectroscopy; extended object spectrophotometry; introduction to CCD astrometry; solar system applications for CCDs; CCD data; observing with infrared arrays; image processing, data analysis software, and computer systems for CCD data reduction and analysis. (No individual items are abstracted in this volume)

Howell, Steve B.↗
NASA NTRS1992

Navier-Stokes computations of cavity aeroacoustics with suppression devices

Effectiveness of two devices to suppress the cavity acoustics was computationally investigated. Two dimensional, computational simulations were performed for the transonic, turbulent flows past a cavity, which was first equipped with a rear face ramp and then with a spoiler. The Reynolds-averaged, unsteady, compressible, full Navier-Stokes equations were solved time accurately by a second-order accurate, implicit, upwind, finite-volume method. The effect of turbulence was included through a Baldwin-Lomax model with modifications for the multiple-wall effects and for the highly vortical flow with a shear layer. The results included instantaneous and time-averaged flow properties, and time-series analyses of the pressure inside the cavity, which compared favorably with the available experimental data. These results were also contrasted with the computed aeroacoustics of the same cavity (length-to-depth ratio of 4.5), but without a device, to demonstrate the suppression effectiveness.

Baysal, Oktay↗
NASA NTRS1992

Orographically forced oscillations in a dynamical model of the Martian atmosphere

The barotropic, orographically-forced intraseasonal oscillations of the Martian atmosphere are presently analyzed by means of a single-layer shallow-water model. An oscillation with 85-Martian day mean period is noted in a time-series of the model global atmospheric angular momentum, and its robustness is verified. The oscillation has a standing zonal component whose centers of action are located upstream and downstream of salient orographic features. A resemblance arises between the oscillation's northern-hemisphere features and those of the terrestrial 40-day oscillation.

Keppenne, Christian L.↗
NASA NTRS1992

Geologic process studies using Synthetic Aperture Radar (SAR) data

The use of SAR data to study geologic processes for better understanding of recent tectonic activity and climate change as well as the mitigation of geologic hazards and exploration for nonrenewable resources is discussed. The geologic processes that are particularly amenable to SAR-based data include volcanism; soil erosion, degradation, and redistribution; coastal erosion and inundation; glacier fluctuations; permafrost; and crustal motions. When SAR data are combined with data from other planned spaceborne sensors including ESA ERS, the Japanese Earth Resources Satellite, and the Canadian Radarsat, it will be possible to build a time-series view of temporal changes over many regions of earth.

Evans, Diane L.↗
NASA NTRS1992

Forced unsteady deceleration of a turbulent boundary layer from a temporal perspective

The behavior of a turbulent boundary layer which has been subjected to a local ramp-like deceleration in the external velocity field, which leads to forced separation, has been studied experimentally. The data of this study are re-interpreted in light of more recent findings concerning the temporal nature of boundary layer turbulence in the presence of forced unsteady shear. In particular, the robustness of the near-wall turbulent motions to organized deformation is recognized. Their resilence during unsteady shearing action promotes continued efficient turbulent mixing and rapid redistribution of turbulent kinetic energy during forced transients. In aerodynamic problems, the rapid nature of the adjustment of the turbulence field to a new temporal boundary condition necessitates equally rapid remedial measures to be taken if means of control/prevention of forced unsteady separation are to be deployed to maximum effect. This requirement suggests exploration of the use of simple, real-time statistical forecasting techniques, based upon time-series analysis of easily-measurable features of the flow, to help assure timely deployment of mechanisms of boundary-layer control. This paper focuses upon the nature of turbulence in boundary layers undergoing forced deceleration which would lead to separation. A preliminary form of a forecasting model is presented and evaluated. Using observations of the previous two large eddies passing a detector, it forecasts the behavior of the future large eddy rather well.

Brereton, G. J.↗
NASA NTRS1986

Periodic extinction of families and genera

Eight major episodes of biological extinction of marine families over the past 250 million years stand significantly above local background (P < 0.05). These events are more pronounced when analyzed at the level of genus, and generic data exhibit additional apparent extinction events in the Aptian (Cretaceous) and Pliocene (Tertiary) Stages. Time-series analysis of these records strongly suggests a 26-million-year periodicity. This conclusion is robust even when adjusted for simultaneous testing of many trial periods. When the time series is limited to the four best-dated events (Cenomanian, Maestrichtian, upper Eocene, and middle Miocene), the hypothesis of randomness is also rejected for the 26-million-year period (P < 0.0002).

Non-NASA Center↗
DOE OSTI2025

AI-Enabled Operations at Fermi Complex: Multivariate Time Series Prediction for Outage Prediction and Diagnosis

The Main Control Room of the Fermilab accelerator complex continuously gathers extensive time-series data from thousands of sensors monitoring the beam. However, unplanned events such as trips or voltage fluctuations often result in beam outages, causing operational downtime. This downtime not only consumes operator effort in diagnosing and addressing the issue but also leads to unnecessary energy consumption by idle machines awaiting beam restoration. The current threshold-based alarm system is reactive and faces challenges including frequent false alarms and inconsistent outage-cause labeling. To address these limitations, we propose an AI-enabled framework that leverages predictive analytics and automated labeling. Using data from $2,703$ Linac devices and $80$ operator-labeled outages, we evaluate state-of-the-art deep learning architectures, including recurrent, attention-based, and linear models, for beam outage prediction. Additionally, we assess a Random Forest-based labeling system for providing consistent, confidence-scored outage annotations. Our findings highlight the strengths and weaknesses of these architectures for beam outage prediction and identify critical gaps that must be addressed to fully harness AI for transitioning downtime handling from reactive to predictive, ultimately reducing downtime and improving decision-making in accelerator management.

Jain, Milan [PNL, Richland] (ORCID:000000021676111↗
DOE OSTI2025

A Dynamic Hierarchical Attention Framework for Multimodal Malware Detection

The increasing use of Android in the worldwide mobile ecosystem has come along with a significant increase in advanced malware, highlighting the critical necessity for efficient, scalable, and adaptable detection systems. Despite recent advancements in machine learning improving malware detection, the majority of current solutions are limited to one, two, or three data modalities, hence neglecting the comprehensive behavioral spectrum of contemporary multi-vector threats. This thesis presents the first comprehensive multimodal framework for Android malware detection, which combines textual, time-series (temporal), graph-based (structural), and visual information using an innovative hierarchical attention mechanism and Dynamic Fusion Controller (DFC). Our methodology consistently classifies and processes modalities as either sequential or structural, facilitating content-adaptive weighting and resilient cross-modal representation learning. We advance the implementation of cutting-edge time series techniques, such as MiniRocket, for malware detection, hence creating new opportunities for temporal analysis in cybersecurity. Comprehensive experimental assessment shows that our framework performs exceptionally well, with 99.46% classification accuracy and 97.15% detection accuracy, significantly outperforming existing approaches through effective multimodal integration and hierarchical attention mechanisms.

Nazmin, Tamanna↗
DOE OSTI2025

Workflow for Process Automation of Soil Gas Results from an Automated Soil Gas-Sampling System for Application in Carbon Storage Projects

Extended abstract for Geoconvention, Calgary, Alberta, Canada, May 12–14, 2025. The Energy & Environmental Research Center (EERC) developed an automated workflow for processing soil gas measurements collected from the automated soil gas-sampling systems deployed across the project site. Raw soil gas measurements are collected from each station every 4 hours and automatically uploaded to a cloud database. The workflow begins by writing code to download the data to a workstation automatically, then the data are published to an online dashboard that visualizes the measurements in time-series plots and a process-based decision-making framework. This automated workflow accelerates the time from data acquisition to decision-making. It supports carbon storage project operators by preparing and delivering a live, standardized dataset for quick analysis and source attribution to provide assurance of containment and overall permit compliance.

02 PETROLEUM↗
DOE OSTI2026

The South Pole Telescope AGN Monitoring Campaign: First Release of SPTpol Bright AGN Light Curves

The South Pole Telescope (SPT) collaboration has recently embarked upon a campaign to monitor the brightness of a sample of active galactic nuclei (AGN), both in real time and in archival SPT data. The original design of the SPT was optimized for observations of the cosmic microwave background (CMB) at arc-minute and larger angular scales, and it has been used for this purpose for nearly twenty years, using three generations of CMB cameras. Recently it has been recognized that data from CMB experiments have the potential to be used for AGN monitoring. In this paper, we present the first public release of data from a full sample of SPT-monitored AGN, comprising 158 AGN light curves and associated data from the SPTpol camera, which was operational from 2012-2016. These light curves were created using observations from the SPTpol 500 deg$^{2}$ survey, in which the instrument was used to scan a 500 deg$^2$ patch of the sky several times per day with detectors sensitive to radiation in bands centered at 90 and 150 GHz. We provide a comprehensive description of the observations, the data processing methods, and the resulting light curve catalog. As an example of analyses that these data enable, we searched for a correlation between variability and spectral index, and we looked for ``bluer-when-brighter'' trends in the sample. Our analysis finds $> 10 σ$ correlation between fractional intrinsic variance and mean spectral index in the sample, but no significant evidence for bluer-when-brighter trends. The datasets from this study can be accessed through the SPT Treasury Record of AGN With Historical Activity and Time-Series or STRAWHAT catalog. This initial data release includes SPTpol light curves at 90 and 150 GHz, focusing on total intensity. In later updates, SPTpol polarization data and new observations from the SPT-3G instrument at 90, 150, and 220 GHz will be included.

Hood, J.C., II [Chicago U., KICP; Chicago U., Astr↗
DOE OSTI2026

Integrating Immersive Visualization in Molten-Salt Reactor Waste Management for Experimental Design and Planning

Molten-salt reactors (MSRs) represent a promising solution for next-generation nuclear energy, offering advantages in safety, fuel efficiency, and waste minimization. However, their liquid-fueled design presents unique challenges for spent fuel management, making post-shutdown waste characterization essential for developing effective strategies. Despite this need, there is a notable absence of visualization platforms specifically tailored to the unique characteristics and analytical requirements of MSR waste management. Existing tools in the nuclear industry are primarily designed for reactor operations or generic data exploration and lack both integration with MSR-specific multiphysics frameworks and the ability to simultaneously visualize time-dependent thermal fields, chemical composition evolution, and radiation distribution patterns. To address these limitations, this paper presents an immersive virtual reality (VR) visualization platform that processes and displays high-fidelity multiphysics simulation output from the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework in real-time, using Unity. The platform visualizes MSR waste characteristics such as nuclide decay, salt cooling, and corrosion by using Exodus II output data and running on a VR headset. It includes a user-friendly interface with features such as visibility toggling, cross-sectional slicing, and time-series animation for exploring simulation data. These capabilities support experimental design, stakeholder engagement, and public communication by making complex reactor behavior more accessible and understandable. By enhancing spatial reasoning and reducing cognitive load, this immersive environment fosters more effective communication and decision-making in MSR waste management.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Measurement-informed Dynamic Aggregation of Distribution Systems

This paper proposes a measurement-informed dynamic aggregation methodology in order to create equivalent representations of distribution systems that are compatible with large-scale transmission analysis. By optimizing an equivalent feeder parameters using time-series measurements of active power, reactive power, and voltage at the Point of Interconnection (POI), the approach yields simplified yet dynamically accurate equivalents. Implemented in PSCAD with models of photovoltaic–battery systems, three-phase motors, and static loads, the method employs hybrid differential evolution and bounded least-squares optimization laying the foundation for for real-time state estimation and optimized sensor placement in distribution networks.

Ahmed, Kazi Ishrak [University of Tennessee, Knoxv↗
DOE OSTI2026

Latency Analysis of the Nexus Digital Twin Framework

Real-time digital catalogs are increasingly relied upon to track metadata and connect disparate data sources for cloud-based data integration efforts. One such tool, Deeplynx Nexus is supporting real-time digital twin efforts through event-driven data integration and time-series queries. Nexus’s usefulness for these applications depends critically on how quickly individual records can be uploaded and downloaded, since delays directly affect the responsiveness of any system built on top of it. However, the actual latency a user should expect from Nexus has not been systematically measured before, particularly for the small, frequent transactions typical of live sensor feeds. Here we show that single-record round-trip latency is 61.1 ms on a local Nexus instance and 391.7 ms on the hosted production infrastructure, a roughly 6.4x difference driven primarily by fixed per-request overhead rather than data volume. This overhead dominates at small scale: comparing single-record and ten-record trials suggests approximately 56 ms of each single-record request is fixed connection and authentication cost rather than data-transfer time, meaning batching even a handful of records is substantially more efficient than transmitting them individually. At large batch sizes, this pattern reverses for uploads, which converge to near parity between local and hosted environments by 25,000-50,000 records, while download latency remains persistently 5.7-6.4x slower on hosted infrastructure even at scale. These results suggest that Nexus deployments intended for real-time digital twin applications should prioritize record batching over single-record transactions, and that download-path optimization on hosted infrastructure offers the largest remaining opportunity to reduce latency at scale. We anticipate these baseline measurements will serve as a reference point for future digital twin projects evaluating whether Nexus’s latency profile meets their real-time requirements, and as a benchmark for tracking the effect of future infrastructure or API changes.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Evaluation of a generalized least squares algorithm for infrasound beamforming with coherent background noise

Infrasonic signals of interest can occur during periods with persistent, coherent, background noise, which may be natural or anthropogenic. For high signal-to-noise (SNR) ratio transient signals, an ‘overprinting’ of the coherent background may occur, and the signal may still be detected. However, this approach fails for low SNR signals of interest, which may be obscured by coherent noise. An infrasound beamforming method based on generalized least squares (GLS) is investigated for detecting transient signals of interest in the presence of coherent and incoherent background noise. This approach relies on an estimate of the noise covariance, captured in a covariance matrix, to effectively null contributions to the array response from noisy directions of arrival. Synthetic array data is used to investigate the performance of the GLS beamformer compared to the Bartlett beamformer when coherent and incoherent backgrounds are present. Additionally, the effects of array element number and relative strength of the interfering signal on the GLS estimates is investigated. GLS empirical area under the curve estimates suggest that the beamformer can recover coherent power for a signal of interest lower in amplitude than the coherent background, but this effectiveness degrades more quickly with SNR for a four element array compared to a six or eight element infrasound array. Finally, infrasound from the Forensic Surface Experiment, a bolide signal observed at IMS array I37NO, and a volcanic signal recorded at the Alaska Volcano Observatory array ADKI are used to evaluate GLS performance on recorded data. A ten minute window was used to capture the background noise, and the coherent background signal was nulled in all three examples.

58 GEOSCIENCES↗
DOE OSTI2025

Short-Term Forecasting of Thermostatic and Residential Loads Using Long Short-Term Memory Recurrent Neural Networks

Internet of Things (IoT) devices in smart grids enable intelligent energy management for grid managers and personalized energy services for consumers. Investigating a smart grid with IoT devices requires a simulation framework with IoT devices modeling. However, there lack comprehensive study on the modeling of IoT devices in smart grids. This paper investigates the IoT device modeling of a thermostatic load and implements the recurrent neural networks model for short-term load forecasting in this IoT-based thermostatic load. The recurrent neural network structure is leveraged to build a load forecasting model on temporal correlation. The temporal recurrent neural network layers including long short-term memory cells are employed to learn the data from both the simulation platform and New South Wales residential datasets. The simulation results are provided for demonstration.

electric load forecasting↗