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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 1,135 records · Page 63

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Extraction and Analysis of Time Series Data from Building Automation Systems Using Large Language Models

Semantic schemas like Haystack 4, Brick and ASHRAE standard 223 enable the structured, standardized, and machine-readable representation of building data, facilitating interoperability, data integration, and advanced analytics. However, extracting information from these models requires specialized expertise in SPARQL and other programming languages, skills that are not commonly found among building professionals. Recent advancements in Large Language Models (LLMs), such as ChatGPT, enable the construction of queries using natural language, making it easier for individuals to interact with these systems in a manner that resembles everyday speech. However, these methods have not yet been tested on building semantic ontologies. This paper introduces a novel workflow and tool for enabling users to ask questions about a specific building's data, using natural language and receive answers automatically generated by GPT-4o. Our approach integrates semantic ontologies with advanced LLM capabilities to automate three critical steps: (1) generating SPARQL queries to retrieve time series references from ontological models, (2) extracting the corresponding time series data from the Building Automation System, and (3) performing computations and visualizations tailored to the user's query. The proposed method simplifies access to BAS data, allowing both domain experts and non-specialists to conduct sophisticated analyses without needing extensive technical knowledge of semantic web technologies. By demonstrating this pipeline, we facilitate more accessible and scalable data-driven decision-making in building operations and management.

Mulayim, Ozan Baris↗

DOE OSTI2025

Extraction and Analysis of Time Series Data from Building Automation Systems Using Large Language Models

Mulayim, Ozan Baris↗

DOE OSTI2026

A Fast and Accurate Reduced-Order Model for High-Intensity Transferred Arc Discharges

Arc discharges are widely used in welding, plasma smelting, and other industrial processes, where variations in operating conditions strongly affect arc stability, temperature distribution, and energy transfer. Accurate modeling of these phenomena typically requires computationally expensive high-fidelity simulations. This study presents a hierarchy of three arc discharge models with progressively reduced physical fidelity. The high-fidelity model provides a fully physics-resolved reference, the reduced-order model reproduces the dominant thermal and flow characteristics of the arc with reasonable accuracy, and the Elenbaas-Heller model captures key trends in a simplified, rapid formulation. This hierarchy demonstrates that reduced-order model can effectively balance predictive fidelity and computational efficiency, providing practical tools for arc simulation and parametric studies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Diagnosis of convective organization and cold pools using ARM datasets and evaluation of a unified convection parameterization (UNICON)

Tropical thunderstorms often cluster together. Studies have suggested that the degree to which the tropical thunderstorms are clustered impacts Earth's energy balance and water cycle, as well as extreme precipitation events. However, the processes controlling the spatial distribution of the thunderstorms are poorly understood and are not properly represented in most computer models for weather and climate prediction. Under the goals of better understanding how convection organizes at the mesoscale and advancing the representation of mesoscale convective organization in global climate models, we i) objectively quantified the degrees of convective organization and diagnosed cold pool processes using ARM field campaign observations, ii) examined the organization processes in storm-resolving model simulations, and iii) evaluated the impacts of mesoscale convective organization in global model simulations. The project yielded a firm reference against which the global model representation of mesoscale convective organization and cold pools can be evaluated against and shed new light into the role of parameterized convective organization in the global model simulation of the basic state and variability. Our results revealed two distinct phases of convective clustering during the two-day rain episodes (Cheng et al. 2018) and a new mechanism through which vertical wind shear in the low-troposphere can aid convective organization over tropical oceans (Cheng et al. 2020). It was demonstrated that the interactive representation of cold pools and mesoscale convective organization is key for global models to successfully simulate both the mean state and intraseasonal variability in the tropics (Ahn et al. 2019; 2020).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1978

Atmospheric disturbance modelling requirements for flying qualities applications

Flying qualities are defined as those airplane characteristics which govern the ease or precision with which the pilot can accomplish the mission. Some atmospheric disturbance modelling requirements for aircraft flying qualities applications are reviewed. It is concluded that some simplifications are justified in identifying the primary influence on aircraft response and pilot control. It is recommended that a universal environmental model be developed, which could form the reference for different applications. This model should include the latest information on winds, turbulence, gusts, visibility, icing and precipitation. A chosen model would be kept by a national agency and updated regularly by feedback from users. A user manual is believed to be an essential part of such a model.

Moorhouse, D. J.↗

NASA NTRS1983

Spectral decontamination of a real-time helicopter simulation

Nonlinear mathematical models of a rotor system, referred to as rotating blade-element models, produce steady-state, high-frequency harmonics of significant magnitude. In a discrete simulation model, certain of these harmonics may be incompatible with realistic real-time computational constraints because of their aliasing into the operational low-pass region. However, the energy is an aliased harmonic may be suppressed by increasing the computation rate of an isolated, causal nonlinearity and using an appropriate filter. This decontamination technique is applied to Sikorsky's real-time model of the Black Hawk helicopter, as supplied to NASA for handling-qualities investigations.

Mcfarland, R. E.↗

NASA NTRS1993

The role of ionospheric plasma in the magnetosphere

During the course of this project we have made a great deal of progress developing and using a new plasma modeling technique which we now refer to as the Generalized Semikinetic (GSK) model. It has been used to study the development of plasma flows in the plasmasphere, the polar cap and auroral zones, and the transition region. Below we describe some of the major accomplishments of this grant.

Wilson, Gordon R.↗

DOE OSTI2022

Overview of Base Model in Parametric Studies Specific to Performance of U-Mo Plates

This paper provides an overview of the base model specifically developed to perform parametric sensitivity studies on the U-10Mo monolithic fuel system. U-Mo monolithic fuels are being considered for the conversion of test reactors into high-performance research reactors that operate using proliferation-resistant, low-enriched uranium (LEU) fuels. These plate-type fuels contain a high-density, low-enrichment fuel sandwiched between zirconium diffusion barriers and encapsulated in aluminum claddings. All U.S. high-performance research reactors have released the designs of their LEU monolithic fuel reactor cores. These designs include nearly 50 distinct fuel plate geometries with different operational parameters. Consequently, a single generic plate geometry representing all the extreme points in this design matrix is unrealistic. To evaluate the performance for various parameters, a set of sensitivity studies was performed. These studies considered various input parameters (i.e., geometric, operational, and material property-related). The results revealed valuable information about plate performance and the sensitivity of this performance to various modeling inputs. To establish a reference state for comparing these result, base model featuring representative irradiation conditions was developed. To capture in-reactor behavior accurately, incorporation of representative constitutive models capable of evolving properties with respect to temperature, irradiation time, and burnup was needed. The behavioral models considered burnup-dependent properties, swelling, creep, and degradation. This paper introduces the base model created for the parametric sensitivity studies. The detailed description of the procedure includes the model geometry, model discretization, thermo-mechanical coupling, material properties and behavioral models. This paper also provides selected results and assesses the performance of the base model.

42 ENGINEERING↗

DOE OSTI2026

Reproducible benchmark for the SNAP 8 experimental reactor at operating conditions

This work presents fully reproducible multiphysics benchmark models of the Systems for Nuclear Auxiliary Power (SNAP) 8 Experimental Reactor at operating conditions with coolant flow. Wet experiment (with coolant, at power) validation benchmarks are presented using both deterministic (Serpent-Griffin) and Monte-Carlo (OpenMC-Cardinal) multiphysics frameworks coupled with thermal-hydraulic solvers in MOOSE. Reactivity coefficient measurements including fuel temperature, isothermal temperature, and power coefficients show good agreement with experiments, with discrepancies within experimental uncertainty. Reactivity worth experiments for coolant, samarium, and xenon poisoning are reproduced with differences under 200 pcm. Comparison between Serpent-Griffin and OpenMC-Cardinal frameworks reveal multiphysics coupling introduces positive reactivity effects (100-200 pcm) compared to uniform temperature and density fields at nominal operating conditions. Comparison between Serpent-Griffin and reference Serpent solution shows that power distributions maintain consistent radial and axial peaking behavior. All models, assumptions, thermophysical and thermomechanical properties, and material definitions are thoroughly documented with cited references; model inputs and model generating scripts are stored in the snapReactors GitHub repository.

SNAP↗

NASA NTRS1995

Recent improvements to and validation of the one dimensional NASA wave rotor model

A numerical model has been developed at the NASA Lewis Research Center which can predict both the unsteady flow quantities within a wave rotor passage and the steady averaged flows in the ports. The model is based on the assumptions of one-dimensional, unsteady, perfect gas flow. The model assesses not only the dominant wave behavior, but the loss effects of finite passage opening time, leakage from the passage ends, viscosity, and heat transfer to and from the passages. The model operates in the rotor reference frame; however, until recently no account was made for the often significant effect of the rotor circumferential velocity component. The present model accounts for this by modifying the passage boundary conditions, allowing the internal computational scheme to remain the rotor reference frame, while quantities such as inlet duct stagnation properties may be specified in the fixed or absolute reference frame. Accurate modeling of this effect is critical to successful wave rotor analysis and design, particularly in off-design predictions where the flows in the inlet ducts are mismatched with the rotor passages and significant turning may take place (i.e., work is done on the gas). The relative simplicity of the model makes it useful for design and optimization, as well as analysis, of wave rotor cycles for many applications. This report, building on several earlier papers, describes the most recent modifications to the model. These include accounting for the relative/absolute transition at the passage boundaries and refinements to the viscous source term correlation which resulted from this accounting. Comparison of model predictions with measured data is then presented and discussed.

Paxson, Daniel E.↗

DOE OSTI2025

Reference Shapefiles and Pre-trained Random Forest Classification Models for Detecting Aufeis on the North Slope of Alaska in Landsat Imagery

This dataset provides shapefiles and trained machine learning models used for aufeis detection at four sites on the North Slope of Alaska. It includes reference data for evaluating Landsat-based detection methods, supporting research on remote sensing approaches for identifying aufeis. The ReferenceData folder contains ArcGIS shapefiles of semi-automated land cover classifications for 217 Landsat Collection 2 images, categorizing pixels into six classes: aufeis, snow, ground, none, water, and cloud. The SiteBuffers.zip file includes 10-kilometer buffer shapefiles defining regions of interest around four aufeis fields (Canning21, FH1, Firth, and Kuparuk), used to test three detection techniques. Additionally, the TrainedRFModels folder contains six pre-trained Scikit-Learn Random Forest classifiers (100 trees, max depth = 30) designed to predict aufeis presence in Landsat Collection 2 Surface Reflectance images using Red, Blue, SWIR2, NDVI, and NDWI bands. This dataset supports the development and validation of remote sensing methods for mapping aufeis in Arctic environments.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2017

Multi-Organization Multi-Discipline Effort Developing a Mitigation Concept for Planetary Defense

There have been significant recent efforts in addressing mitigation approaches to neutralize Potentially Hazardous Asteroids (PHA). One such research effort was performed in 2015 by an integrated, inter-disciplinary team of asteroid scientists, energy deposition modeling scientists, payload engineers, orbital dynamist engineers, spacecraft discipline engineers, and systems architecture engineer from NASAs Goddard Space Flight Center (GSFC) and the Department of Energy (DoE) National Nuclear Security Administration (NNSA) laboratories (Los Alamos National Laboratory (LANL), Lawrence Livermore National Laboratories (LLNL) and Sandia National Laboratories). The study team collaborated with GSFCs Integrated Design Centers Mission Design Lab (MDL) which engaged a team of GSFC flight hardware discipline engineers to work with GSFC, LANL, and LLNL NEA-related subject matter experts during a one-week intensive concept formulation study in an integrated concurrent engineering environment. This team has analyzed the first of several distinct study cases for a multi-year NASA research grant. This Case 1 study references the Near-Earth Asteroid (NEA) named Bennu as the notional target due to the availability of a very detailed Design Reference Asteroid (DRA) model for its orbit and physical characteristics (courtesy of the Spectral Interpretation, Resource Identification, Security-Regolith Explorer (OSIRIS-REx) mission team). The research involved the formulation and optimization of spacecraft trajectories to intercept Bennu, overall mission and architecture concepts, and high-fidelity modeling of both kinetic impact (spacecraft collision to change a NEAs momentum and orbit) and nuclear detonation effects on Bennu, for purposes of deflecting Bennu.

Planetary Defense↗

DOE OSTI2025

Denoising Seismograms in the Time Domain Using a Deep Learning Model

Deep learning has emerged as a transformative tool for enhancing the extraction of reliable information from seismograms, addressing the increasing demand for precise and efficient seismic data analysis. We introduce an innovative encoder–decoder deep learning model, named WaveDenoiser, designed for noise reduction in the time domain, thereby eliminating the need for spectrogram computations that have been used for existing deep learning tools and significantly improving processing speed. Utilizing the benchmark dataset that is Stanford Earthquake Dataset, we developed three models of varying sizes: base, medium, and large. Notably, the large (referred to as WaveDenoiser) model demonstrated superior performance, achieving a median signal‐to‐noise ratio improvement of 8.8 dB on in‐distribution unseen data (in the same geographic region) and 7.7 dB on out‐distribution unseen data (in a new geographic region), outpacing both the base and medium models. Further evaluation of the WaveDenoiser model revealed a reduction in median arrival‐time errors by 0.02 s for P waves and 0.01 s for S waves when processing waveforms prior to phase picking using PhaseNet on in‐distribution unseen data. When tested on out‐distribution unseen data, the model also effectively reduced the P‐wave median arrival‐time error by 0.02 and 0.01 s in median arrival‐time error for S waves. Importantly, the application of WaveDenoiser resulted in a significant reduction of phase picking outliers by 1.1% to 3.6% for both P and S waves. In addition, we achieved over five times acceleration in processing speed compared with the seisBench implementation of DeepDenoiser. Our findings underscore the potential of WaveDenoiser as a powerful tool for improving seismic data analysis and processing efficiency.

P-waves↗

NASA NTRS1993

Kalman filter estimation of attitude and gyro bias with the QUEST observation model

The loss function for the Wahba attitude estimation problem employs unit vector observations with scalar weights. It is usually associated with the QUEST observation model, where the actual sensor noise is assumed the same for all components of the observed vector, regardless of the position in the field of view. The QUEST model has the great advantage of being sensor-independent except for the scalar parameter that characterizes the sensor errors. Although efficient algorithms for solving the Wahba problem exist, extending these algorithms to estimate gyro biases or sensor alignments has had mixed success. However, it is straightforward to estimate bias and alignment parameters with a Kalman filter. This paper investigates the use of an extended Kalman filter for the attitude and gyro bias that incorporates the QUEST observation model, to be referred to as the Unit Vector Filter (UVF). The UVF results are compared with those from a more conventional filter, the Real-Time Sequential Filter (RTSF), for which the residual is the two-dimensional projection of the unit vector onto the plane perpendicular to the sensor boresight. The RTSF is similar in design to that used by Multimission Modular Spacecraft for onboard attitude determination. An apparent obstacle to the use of unit vectors as measurements is their singular noise covariance matrix. Shuster has shown that this problem should not affect filter performance. The UVF and RTSF are tested using actual flight data from the Extreme Ultraviolet Explorer (EUVE). It is found that these filters generate nearly identical attitude and gyro bias estimates, thus validating the use of unit vectors and the QUEST noise model.

Sedlak, J.↗

NASA NTRS2020

SISO Space Reference FOM - Tools and Testing

The Simulation Interoperability Standards Organization (SISO) Space Reference Federation Object Model (SpaceFOM) version 1.0 is nearing completion. Earlier papers have described the use of the High Level Architecture (HLA) in Space simulation as well as technical aspects of the SpaceFOM. This paper takes a look at different SpaceFOM tools and how they were used during the development and testing of the standard.The first organizations to develop SpaceFOM-compliant federates for SpaceFOM development and testing were NASA's Johnson Space Center (JSC), the University of Calabria (UNICAL), and Pitch Technologies.JSC is one of NASA's lead centers for human space flight. Much of the core distributed simulation technology development, specifically associated with the SpaceFOM, is done by the NASA Exploration Systems Simulations (NExSyS) team. One of NASA's principal simulation development tools is the Trick Simulation Environment. NASA's NExSyS team has been modifying and using Trick and TrickHLA to help develop and test the SpaceFOM.The System Modeling And Simulation Hub Laboratory (SMASH-Lab) at UNICAL has developed the Simulation Exploration Experience (SEE) HLA Starter kit, that has been used by most SEE teams involved in the distributed simulation of a Moon base. It is particularly useful for the development of federates that are compatible with the SpaceFOM. The HLA Starter Kit is a Java based tool that provides a well-structured framework to simplify the formulation, generation, and execution of SpaceFOM-compliant federates.Pitch Technologies, a company specializing in distributed simulation, is utilizing a number of their existing HLA tools to support development and testing of the SpaceFOM. In addition to the existing tools, Pitch has developed a few SpaceFOM specific federates: Space Master for managing the initialization, execution and pacing of any SpaceFOM federation; EarthEnvironment, a simple Root Reference Publisher; and Space Monitor, a graphical tool for monitoring reference frames and physical entities.Early testing of the SpaceFOM was carried out in the SEE university outreach program, initiated in SISO. Students were given a subset of the FOM, that was later extended. Sample federates were developed and frameworks were developed or adapted to the early FOM versions.As drafts of the standard matured, testing was performed using federates from government, industry, and academia. By mixing federates developed by different teams the standard could be tested with respect to functional correctness, robustness and clarity.These frameworks and federates have been useful when testing and verifying the design of the standard. In addition to this, they have since formed a starting point for developing SpaceFOM-compliant federations in several projects, for example for NASA, ESA as well as SEE.

Möller, Björn↗

DOE OSTI2020

SMART Mobility. Mobility Decision Science Capstone Report

The U.S. Department of Energy’s Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Consortium is a multiyear, multi-laboratory collaborative, managed by the Energy Efficient Mobility Systems Program of the Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office, dedicated to further understanding the energy implications and opportunities of advanced mobility technologies and services. The first three-year research phase of SMART Mobility occurred from 2017 through 2019, and included five research pillars: Connected and Automated Vehicles, Mobility Decision Science, Multi-Modal Freight, Urban Science, and Advanced Fueling Infrastructure. A sixth research thrust integrated aspects of all five pillars to develop a SMART Mobility Modeling Workflow to evaluate new transportation technologies and services at scale. This report summarizes the work of the Mobility Decision Science Pillar. The Mobility Decision Science Pillar sought to fill gaps in existing knowledge about the human role in the mobility system including travel decision-making and technology adoption in the context of future mobility. The objective was to study how underlying preferences, needs, and contextual factors might constrain or hasten future transportation system scenarios. For information about the other Pillars and about the SMART Mobility Modeling Workflow, please refer to the relevant pillar’s Capstone Report.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

SMART Mobility. Connected and Automated Vehicles Capstone Report

The U.S. Department of Energy’s Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Consortium is a multiyear, multi-laboratory collaborative, managed by the Energy Efficient Mobility Systems Program of the Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office, dedicated to further understanding the energy implications and opportunities of advanced mobility technologies and services. The first three-year research phase of SMART Mobility occurred from 2017 through 2019 and included five research pillars: Connected and Automated Vehicles, Mobility Decision Science, Multi-Modal Freight, Urban Science, and Advanced Fueling Infrastructure. A sixth research thrust integrated aspects of all five pillars to develop a SMART Mobility Modeling Workflow to evaluate new transportation technologies and services at scale. This report summarizes the work of the Connected and Automated Vehicles (CAVs) Pillar. This Pillar investigated the energy, technology, and usage implications of vehicle connectivity and automation and identified efficient CAV solutions. For information about the other Pillars and about the SMART Mobility Modeling Workflow, please refer to the relevant Pillar’s Capstone Report.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRSDate not supplied

Development of the Artemis Distributed Simulation FOMs

The National Aeronautics and Space Administration (NASA) is formulating and developing the Artemis Program, a collaboration with domestic commercial and international partners that will establish a long term human presence on the Moon and extend human exploration beyond the Earth-Moon system ahead of exploring Mars. These Artemis partners are developing a portfolio of space and surface systems to support human missions to the lunar surface and beyond. The Artemis systems will provide the mobility, habitation, and logistics infrastructure that will support human exploration and foster robust scientific investigations. Each partner will contribute one or more elements to the Artemis Program with NASA having the overarching responsibility for defining the Artemis architecture and guiding the integration of this complex system of space systems. To successfully accomplish this audacious task, NASA will rely on the development and execution of many complex models and simulations. Many of these simulations will be provided by the Artemis partners. While each of these simulations will provide important insight into the characteristics and performance of an associated system, individually they will not provide insight into the integrated performance of the architecture and the system of systems working in concert to execute a given Artemis mission. To address this need, NASA is developing a distributed simulation capability called the Artemis Distributed Simulation (ADS). ADS’s distributed nature supports the complex aggregation of constituent Artemis element simulations. Artemis partner simulations will be able to join into an ADS-based distributed simulation and interact with other Artemis element simulations while limiting the exposure of proprietary designs and data. ADS is defining a distributed simulation capability built on international simulation interoperability standards, specifically the High Level Architecture (HLA) and the Space Reference Federation Object Model (SpaceFOM). While HLA and SpaceFOM provide the substantive necessary technology basis for ADS, additional common datatypes, message definitions, and execution protocols are required. These extensions constitute the ADS Federation Object Model (FOM). This paper describes the fundamental architectural elements of ADS and the FOM extensions needed to support the complex nature of the Artemis Program. This includes the examination of the ADS FOM modules, ADS base datatypes, ADS SpaceFOM Object Class extensions, new ADS Object Classes, and new ADS Interaction Classes.

HLA↗