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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 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Evaluating Text Analytic Frameworks for Mental Health Surveillance

Reducing suicide incidence among US veterans is one of the highest priorities for the US Department of Veterans Affairs (VA). We are implementing a suicide risk detection system, in collaboration with the VA, that would serve as a surveillance system for risk factors appearing in clinical text data. Primary requirements for this system are fast search capability, feature and information extraction, and delivery of data to up-stream natural language processing models. As such, we are evaluating scalable storage solutions on the basis of performance, fault tolerance, and scalability. In this paper we present our current approach to evaluation, preliminary findings, and the work in progress towards a more robust text analysis pipeline.

Mayer, Benjamin W.↗
DOE OSTI2025

Enhancing Smart Home Privacy: A Tutorial on Local Differential Privacy Techniques for Frequency and Mean Estimation

The ubiquity of Internet of Things (IoT) systems has seamlessly integrated into our daily lives, particularly in smart homes where devices continuously monitor and optimize our living environments. These systems significantly contribute to home automation, energy efficiency, and overall comfort. However, this widespread connectivity poses inherent risks linked to the streaming of sensitive household data, necessitating robust privacy preservation mechanisms. This tutorial systematically examines privacy preservation through local differential privacy (LDP), with a particular focus on frequency and mean estimation techniques for smart home applications. Here, we present a comprehensive taxonomy of smart home data formats and provide detailed implementation guidance for event-based and w-event LDP mechanisms. Through practical examples using smart thermostats and HVAC systems, we demonstrate how these techniques can be effectively deployed in real-world scenarios. The tutorial concludes by examining emerging research directions, including adaptive privacy budgets and federated learning approaches, establishing a foundation for privacy-preserving smart home deployments.

Kotevska, Olivera [Oak Ridge National Laboratory (↗
DOE OSTI2016

Radioactive source localization in urban environments with sensor networks and the Internet of Things

The use of radiation detectors as an element in the so-called “Internet of Things” has recently become viable with the available of low-cost, mobile radiation sensors capable of streaming geo-referenced data. New methods for fusing the data from multiple sensors on such a network is presented. The traditional simple and ordinary Kriging methods present a challenge for such a network since the assumption of a constant mean is not valid in this application. In conclusion, a variety of Kalman filters are introduced in an attempt to solve the problem associated with this variable and unknown mean. Results are presented on a deployed sensor network.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

HIDES (Hybrid Intrusion Detection for Energy Systems) [SWR-19-65]

Hybrid Intrusion Detection for Energy Systems (HIDES) is a conglomerate detector that incorporates three major components: (1) Signature-based detection that involves information technology (IT) related anomaly detection rules, (2) Behavior-based detection that utilizes specially crafted rulesets for detecting abnormal behavior regarding the power system's supervisory control and data acquisition (SCADA) communication streams, and (3) Learning-based detection that combines SCADA communication with phasor measurements to identify otherwise non-detectible attack vectors. The software itself interconnects intrusion detection engine (IDE) enabling communications between the generated OT and IT alerts with phasor measurements for the learning-based detection system. The resulting detection system can detect a wide array of IT, OT, and physical attacks in a real-time setting.

Rivera, Joshua↗
DOE OSTI2021

Land Surface Modeling 2.0 for agricultural climate change impact assessments

Focus Area: This white paper addresses DOE AI4ESP focus area #2 by providing a sketch blueprint for a next generation, hybrid AI/process-based global Land Surface Modeling (LSM) framework to improve projections of climate change impacts on the land surface system including agriculture and the hydrological cycle. Science Challenge: Climate change impacts on agriculture are highly uncertain: -50% to +150% global production changes for major grains under high-end climate change, for example. The core challenge in land surface system predictability is the large gap between the scale at which the relevant biological processes act and the scale at which the risks need to be assessed. Conventional empirical and process-based modeling approaches are insufficient. A new multi-scale modeling paradigm which employs AI/ML to learn from new streams of remote sensing data and targeted ’gene-to-global’ simulations is needed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Colorado State University Extension Industrial Assessment Center

Since its inception in 1984, the Colorado State University Industrial Assessment Center has performed industrial assessments at more than 720 manufacturing facilities in Colorado, Montana, Nebraska, Nevada, New Mexico, North Dakota, South Dakota, Utah, and Wyoming. From 2017 to 2019 there was a funding gap and the IAC shutdown. In 2020 through DOE extension funding the University relaunched the IAC as an extension center in order to provide assessments to underserved areas. Under this award, the CSU Industrial Assessment Center (IAC) was rebuilt with the help of student employees and the director. The CSU team experienced difficulty as the program was in the process of being restarted right as the 2020 pandemic hit. Nonetheless, the CSU IAC was instrumental in providing energy assessments to manufacturers in Colorado and Wyoming during the period of performance of 09/2019 – 12/2022. The Department of Energy's Industrial Assessment Centers (IACs) provide a valuable service to small and medium-sized manufacturers seeking to optimize their operations. These university-based centers offer no-cost, on-site assessments conducted by engineering faculty and students, analyzing energy consumption, production processes, and waste streams. They utilize advanced data acquisition systems to record operational data, and then use the data to create assessment recommendations. These recommendations form the foundation of the comprehensive energy report. The comprehensive report delivers actionable recommendations for enhancing energy efficiency, reducing waste, and reducing greenhouse gas emissions and improving productivity, often identifying significant cost savings. Furthermore, IACs facilitate access to implementation grants, enabling the businesses to readily adopt these improvements. This program not only strengthens individual businesses but also contributes to national goals of training the next generation of energy experts, as well as increasing industrial competitiveness and reduced environmental impact.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

An Efficient Storage-Driven Machine Learning Model for Performance in the Era of Multimodal Scientific Data

Scientific workflows are increasingly relying on machine learning (ML), simulation, and hybrid techniques to predict, understand, and optimize the behavior of complex experiments. High-performance computing has greatly improved researchers’ ability to acquire diverse data modalities in these workflows. Recent studies suggest that the performance of machine learning models can be improved by integrating data from various sources. Unfortunately, these workloads pose unprecedent pressure on the network storage to meet the demands associated with accessing these multimodal data. To mitigate the impact of intensive IO, we propose a solution that utilizes a multi-tier High-Performance Computing (HPC) distributed storage and data processing framework, placing computation where the data resides for better performance. By adopting this project, the scientific community will gain new opportunities to explore multimodal storage-driven possibilities, integrating multiple scientific data sources with advanced streaming frameworks. Additionally, our framework effectively utilizes computing resources and bridges the gaps identified by HPC experts. Our proposed approach tackles scalability and persistence challenges by leveraging native persistency, which has posed difficulties in traditional approaches. Furthermore, we seek to enhance fault-tolerance and load-balance of computations by leveraging real-time streaming in diverse scientific computing environments, thereby propelling advanced scientific computing research into the next generation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Waveform Simulation Framework: User Manual with Tutorials

This manuscript describes the Waveform Simulation Framework (WSF), a Python-based framework that provides a unified, programmable interface for generating synthetic seismograms for applications such as seismic array design, method development, and special event analysis. WSF standardizes how users define sources, receivers, and velocity models while abstracting simulator-specific configuration details, enabling workflows that are largely independent of the underlying numerical engine. The document provides installation guidance and tutorial-driven examples for three WSF simulator wrappers—WSF PyFK, WSF SW4, and WSF SPECFEM2D—illustrating end-to-end workflows from forward waveform simulation to common post-processing tasks (e.g., visualization and backprojection) using consistent data products (e.g., ObsPy Stream objects and SAC files).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Coherent Structures at Ion Scales in Fast Solar Wind: Cluster Observations

We investigate the nature of magnetic turbulent fluctuations, around ion characteristic scales, in a fast solar wind stream, by using Cluster data. Contrarily to slow solar wind, where both Alfvénic (δb{sub ⊥}≫δb{sub ∥}) and compressive (δb{sub ∥}≫δb{sub ⊥}) coherent structures are observed, the turbulent cascade of fast solar wind is dominated by Alfvénic structures, namely, Alfvén vortices, with a small and/or finite compressive part, with the presence also of several current sheets aligned with the local magnetic field. Several examples of vortex chains are also recognized. Although an increase of magnetic compressibility around ion scales is observed also for fast solar wind, no strongly compressive structures are found, meaning that the nature of the slow and fast winds is intrinsically different. Multispacecraft analysis applied to this interval of fast wind indicates that the coherent structures are almost convected by the flow and aligned with the local magnetic field, i.e., their normal is perpendicular to B, which is consistent with a two-dimensional turbulence picture. Understanding intermittency and the related generation of coherent structures could provide a key insight into the nonlinear energy transfer and dissipation processes in magnetized and collisionless plasmas.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1972

Turbulent mixing film cooling correlation

Film cooling effectiveness correlation predicts air flow requirement for cooling gas turbine combustors. Turbulent mixing model accounts for mixing rate between cooling film and hot gas stream. Resulting equation correlates data within plus or minus 20 percent.

Juhasz, A. J.↗
NASA NTRS1972

Nonuniform flow field generation for supersonic compressor stator development: Design and preliminary results

Design and preliminary results are given for a technique which can generate a nonuniform flow similar to the discharge of an impulse supersonic compressor rotor. The technique utilizes a carefully contoured, two-dimensional blunt body in a conventional hypersonic wind tunnel to generate the required flow field. To show the effects of the flow vorticity, a cascade of impulse-type blades was tested in this test stream. Some preliminary performance data are given along with comparison with previously determined uniform flow results.

Lipfert, F. W.↗
NASA NTRS1972

Applications of ERTS-A Data Collection System (DCS) in the Arizona Regional Ecological Test Site (ARETS)

The author has identified the following significant results. Preliminary analysis of DCS data from the USGS Verde River stream flow measuring site indicates the DCS system is furnishing high quality data more frequently than had been expected. During the 43-day period between Nov. 3, and Dec. 15, 1972, 552 DCS transmissions were received during 193 data passes. The amount of data received far exceeded the single high quality transmission per 12-hour period expected from the DCS system. The digital-parallel ERTS-1 data has furnished sufficient to accurately compute mean daily gage heights. These in turn, are used to compute average daily streamflow rates during periods of stable or slowly changing flow conditions. The digital-parallel data has also furnished useful information during peak flow periods. However, the serial-digital DCS capability, currently under development for transmitting streamflow data, should provide data of greater utility for determining times of flood peaks.

Schumann, H. H.↗
NASA NTRS1983

Algorithm development for a spacecraft autonomous power system

Two algorithms were developed to demonstrate the implementation of autonomous functions in an existing spacecraft power system. The functions selected for autonomous operation include a typical performance monitoring function, battery state of charge, and a fault detection and response function represented by a battery state of charge below a preselected limit. The constraints imposed by the existing power system configuration are the available data in the telemetry stream and the existing commands and command structure. The areas requiring future development are the degree of battery characterization, the effects of hardware/software faults, and the verification of faults.

Bridgeforth, A. O.↗
NASA NTRS1988

Propulsive-jet flow field analysis using the three-dimensional Navier-Stokes equations

A three-dimensional Navier-Stokes code has been applied to the analysis of flow fields containing propulsive jets. Specifically, the application was made to a flow field containing a supersonic jet injected at an angle of 90 degrees to a subsonic free stream. Although wind tunnel data were available, the computational results were not readily comparable to the experimental data because of significant differences between the two plume trajectories. Reasons for the differences are suggested in the report and include: (1) incomplete convergence, (2) inadequate grid resolution in the high gradient regions, and (3) use of a low-order turbulence closure model.

Reed, C. L.↗
NASA NTRS1991

Interannual variations of ozone - Interpretation of 4 years of satellite observations of total ozone

Observations show that the monthly zonal mean total ozone between 1978 and 1982 varies by as much as 5 percent with respect to the 4-year average. These variations have been analyzed with the aid of a two-dimensional chemistry transport model. Observed temperatures and meridional stream functions, calculated from data, were used as inputs for the model. Deviations of the model-calculated total ozone from the 4-year mean were compared with the observed variations. It is shown that a substantial part of the observed variability of total ozone is reproduced by the model, despite uncertainties in the heating rates and without any special attempts to obtain consistent eddy diffusion or otherwise to tune the model. Results indicate that the temperature dependence of the ozone gas phase chemistry plays a negligible role in explaining the observed interannual variations in total ozone. A large part of the variability can be explained by the year-to-year differences in the transport circulation. The variability of the diabatic circulation is shown to be largely independent of the ozone fluctuations and to be a consequence of the observed temperature variations.

Schneider, Hans R.↗
NASA NTRS1993

Vortex generation and mixing in three-dimensional supersonic combustors

The generation and evolution of the flow vorticity established by instream injector ramps in a high Mach number/high enthalpy scramjet combustor flow-field are described in detail for a number of computational cases. Classical fluid dynamic circulation is presented for these cases in order to clarify the spatial distribution and convection of the vorticity. The ability of the simulations to accurately represent Stokes Law of circulation is discussed and shown. In addition, the conservation of swirl (effectively the moment-of-momentum theorem) is presented for these flows. The impact of both turbulent diffusion and the vortex/ramp non-uniformity on the downstream mixing rate is clearly illustrated. A correlation over the length of the combustor between fuel-air mixing and a parameter called the vortex stirring length is demonstrated. Finally, computational results for a representative ramp injector are compared with experimental data. Influence of the stream vorticity on the effective turbulent Prandtl number used in the simulation is discussed.

Riggins, D. W.↗
NASA NTRS1991

System monitoring and diagnosis with qualitative models

A substantial foundation of tools for model-based reasoning with incomplete knowledge was developed: QSIM (a qualitative simulation program) and its extensions for qualitative simulation; Q2, Q3 and their successors for quantitative reasoning on a qualitative framework; and the CC (component-connection) and QPC (Qualitative Process Theory) model compilers for building QSIM QDE (qualitative differential equation) models starting from different ontological assumptions. Other model-compilers for QDE's, e.g., using bond graphs or compartmental models, have been developed elsewhere. These model-building tools will support automatic construction of qualitative models from physical specifications, and further research into selection of appropriate modeling viewpoints. For monitoring and diagnosis, plausible hypotheses are unified against observations to strengthen or refute the predicted behaviors. In MIMIC (Model Integration via Mesh Interpolation Coefficients), multiple hypothesized models of the system are tracked in parallel in order to reduce the 'missing model' problem. Each model begins as a qualitative model, and is unified with a priori quantitative knowledge and with the stream of incoming observational data. When the model/data unification yields a contradiction, the model is refuted. When there is no contradiction, the predictions of the model are progressively strengthened, for use in procedure planning and differential diagnosis. Only under a qualitative level of description can a finite set of models guarantee the complete coverage necessary for this performance. The results of this research are presented in several publications. Abstracts of these published papers are presented along with abtracts of papers representing work that was synergistic with the NASA grant but funded otherwise. These 28 papers include but are not limited to: 'Combined qualitative and numerical simulation with Q3'; 'Comparative analysis and qualitative integral representations'; 'Model-based monitoring of dynamic systems'; 'Numerical behavior envelopes for qualitative models'; 'Higher-order derivative constraints in qualitative simulation'; and 'Non-intersection of trajectories in qualitative phase space: a global constraint for qualitative simulation.'

Kuipers, Benjamin↗