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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Subsonic aerodynamic characteristic of semispan commercial transport model with wing-mounted advanced ducted propeller operating in reverse thrust

A test was conducted in the Langley 14 by 22 Foot Subsonic Tunnel to determine the effect of the reverse-thrust flow field of a wing-mounted advanced ducted propeller on the aerodynamic characteristics of a semispan subsonic high-lift transport model. The advanced ducted propeller (ADP) model was mounted separately in position alongside the wing so that only the aerodynamic interference of the propeller and nacelle affected the aerodynamic performance of the transport model. Mach numbers ranged from 0.14 to 0.26; corresponding Reynolds numbers ranged from 2.2 to 3.9 x 10(exp 6). The reverse-thrust flow field of the ADP shielded a portion of the wing from the free-stream airflow and reduced both lift and drag. The reduction in lift and drag was a function of ADP rotational speed and free-stream velocity. Test results included ground effects data for the transport model and ADP configuration. The ground plane caused a beneficial increase in drag and an undesirable slight increase in lift. The ADP and transport model performance in ground effect was similar to performance trends observed for out of ground effect. The test results form a comprehensive data set that supports the application of the ADP engine and airplane concept on the next generation of advanced subsonic transports. Before this investigation, the engine application was predicted to have detrimental ground effect characteristics. Ground effect test measurements indicated no critical problems and were the first step in proving the viability of this engine and airplane configuration.

Applin, Zachary T.↗
DOE OSTI2024

Data Imbalance, Uncertainty Quantification, and Transfer Learning in Data‐Driven Parameterizations: Lessons From the Emulation of Gravity Wave Momentum Transport in WACCM

Abstract Neural networks (NNs) are increasingly used for data‐driven subgrid‐scale parameterizations in weather and climate models. While NNs are powerful tools for learning complex non‐linear relationships from data, there are several challenges in using them for parameterizations. Three of these challenges are (a) data imbalance related to learning rare, often large‐amplitude, samples; (b) uncertainty quantification (UQ) of the predictions to provide an accuracy indicator; and (c) generalization to other climates, for example, those with different radiative forcings. Here, we examine the performance of methods for addressing these challenges using NN‐based emulators of the Whole Atmosphere Community Climate Model (WACCM) physics‐based gravity wave (GW) parameterizations as a test case. WACCM has complex, state‐of‐the‐art parameterizations for orography‐, convection‐, and front‐driven GWs. Convection‐ and orography‐driven GWs have significant data imbalance due to the absence of convection or orography in most grid points. We address data imbalance using resampling and/or weighted loss functions, enabling the successful emulation of parameterizations for all three sources. We demonstrate that three UQ methods (Bayesian NNs, variational auto‐encoders, and dropouts) provide ensemble spreads that correspond to accuracy during testing, offering criteria for identifying when an NN gives inaccurate predictions. Finally, we show that the accuracy of these NNs decreases for a warmer climate (4 × CO 2 ). However, their performance is significantly improved by applying transfer learning, for example, re‐training only one layer using ∼1% new data from the warmer climate. The findings of this study offer insights for developing reliable and generalizable data‐driven parameterizations for various processes, including (but not limited to) GWs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Updates to the HTR-PROTEUS HALEU Benchmark Using Modern Analysis Methodologies

The HTR-PROTEUS IRPhEP Handbook benchmarks represent some of the highest quality benchmarks available for systems with TRISO-HALEU fuel, graphite pebbles, graphite reflector, and high neutron leakage. Nevertheless, significant variability in computed eigenvalue results was encountered in HTR-PROTEUS configurations that are relevant for transportation configurations. The team will investigate the source of these variabilities in the original benchmark. In addition, the team will investigate the HTR-PROTEUS subcritical measurements, kinetics data, and potential criticality effects from the introduction of hydrogen in the system (water ingress). The project will generate a benchmark evaluation of additional HTR-PROTEUS measurements that can significantly increase the value of these criticality benchmarks in testing nuclear codes and data to support transportation validation needs for industry and the U.S. NRC.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Automated Signal Timing Plan Reconstruction Using High-Resolution Event-Based Controller Data for Digital Twins

Transportation digital twins are essential tools for evaluating emerging technologies such as connected and automated vehicles, adaptive traffic signal control, and mobility optimization strategies. Realistic digital twins require accurate emulation of real-world signal controllers and detailed signal timing plans. However, signal timing plans are often unavailable or difficult to access, forcing researchers and modelers to rely on assumed fixed timings or halt their analysis. To overcome this challenge, we present a method that directly estimates signal timing plan parameters using high-resolution, event-based data from traffic signal controllers. The proposed method extracts key parameters, including cycle length, offset, phase sequence, coordinated phases, phase-specific minimum and maximum green durations, vehicle extensions, and splits under coordination. A rule-based deterministic signal timing reconstruction algorithm based on traffic signal operation rules, such as those outlined in the Signal Timing Manual, is developed and validated. We evaluate this method, which uses high-resolution controller event logs and verified signal timing plans, on 94 signalized intersections in Nashville, Tennessee, demonstrating their ability to generate accurate, simulation-ready signal timing plans for tools such as SUMO and Vissim.

Saroj, Abhilasha [ORNL] (ORCID:0000000191178063)↗
DOE OSTI2017

Personalized Infrastructure: Leveraging Behavioral Strategies for Future Mobility

For decades, the transportation system has been built to position the personal automobile at the pinnacle of mobility options. This prominence is strongly reflected in individual and population behaviors, and supported by coevolved transportation policy, social norms, funding, and physical structures. Such has been the status quo for the living memory of the U.S. population. However, with the advent of emergent, technologically driven mobility options, the transportation system is in an era of rapid and disruptive change. No longer is transportation infrastructure an externality predominantly composed of physical elements; it is also now a personalized interface carried in the pockets of the majority of the population. Perceptions of personal mobility are evolving, in large part because of the proliferation of smartphone technology and the related Internet of Things (IoT), which will become increasingly essential within future transportation systems. With the emergence of personalized mobility infrastructure, many intervention approaches to influence transportation behavior do not adequately acknowledge the complexity of the social/digital environment within which transportation decisions are made. Transportation decisions are influenced by multiple facets, including costs and benefits in time and money, but also by sociocultural elements shaped by social norms and diffusion of ideas. Understanding of factors that lead to transportation behaviors can help to identify incentives and leverage points whereby alternative choices may be most accepted by individuals, and which, if well coordinated, may lead to improved transportation energy outcomes. How can change be initiated to shift away from the transportation status quo? Is it possible to use technologically delivered incentives to produce meaningful changes in transportation behavior? What types of incentives and at what perceived value is necessary to induce changes in behavior? As transportation agencies look toward an ever more complex mobility landscape, and with a quickly growing population, we look for answers to these questions as the core of developing strategies for the future of transportation. Using available data from emergent modes, and experiments conducted as part of an Advanced Research Projects Agency - Energy (ARPA-E) Traveler Response Architecture using Novel Signaling for Network Efficiency in Transportation (TRANSNET) project, we look at how the sharing economy and transportation mobility services have begun to radically alter transportation behavior, while operating in parallel with traditional transportation infrastructure. Emerging modes and practices are affecting car dependence and enabling multimodality. We weigh influences on travel behaviors, identify decision breakpoints where inelastic behavior becomes elastic, incentives, and societal leverage points.

25 ENERGY STORAGE↗
DOE OSTI2022

Panoramic Mapping of Phonon Transport from Ultrafast Electron Diffraction and Scientific Machine Learning

Abstract One central challenge in understanding phonon thermal transport is a lack of experimental tools to investigate frequency‐resolved phonon transport. Although recent advances in computation lead to frequency‐resolved information, it is hindered by unknown defects in bulk regions and at interfaces. Here, a framework that can uncover microscopic phonon transport information in heterostructures is presented, integrating state‐of‐the‐art ultrafast electron diffraction (UED) with advanced scientific machine learning (SciML). Taking advantage of the dual temporal and reciprocal‐space resolution in UED, and the ability of SciML to solve inverse problems involving coupled Boltzmann transport equations, the frequency‐dependent interfacial transmittance and frequency‐dependent relaxation times of the heterostructure from the diffraction patterns are reliably recovered. The framework is applied to experimental Au/Si UED data, and a transport pattern beyond the diffuse mismatch model is revealed, which further enables a direct reconstruction of real‐space, real‐time, frequency‐resolved phonon dynamics across the interface. The work provides a new pathway to probe interfacial phonon transport mechanisms with unprecedented details.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Large resistance change on magnetic tunnel junction based molecular spintronics devices

Here, molecular bridges covalently bonded to two ferromagnetic electrodes can transform ferromagnetic materials and produce intriguing spin transport characteristics. This paper discusses the impact of molecule induced strong coupling on the spin transport. To study molecular coupling effect the octametallic molecular cluster (OMC) was bridged between two ferromagnetic electrodes of a magnetic tunnel junction (Ta/Co/NiFe/AlOx/NiFe/Ta) along the exposed side edges. OMCs induced strong inter-ferromagnetic electrode coupling to yield drastic changes in transport properties of the magnetic tunnel junction testbed at the room temperature. These OMCs also transformed the magnetic properties of magnetic tunnel junctions. SQUID and ferromagnetic resonance studies provided insightful data to explain transport studies on the magnetic tunnel junction based molecular spintronics devices.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Updated Kd Estimates for Modeling Sorption of Cs, Sr, and Pu Isotopes in Hydrostratigraphic Units of Rainier Mesa and Shoshone Mountain

Linear sorption (Kd) coefficients in bulk porous (matrix) rock were estimated for modeling of radionuclide transport in groundwater at Rainier Mesa (RM) and Shoshone Mountain (SM). These Kd estimates were derived from a “component additivity approach” applied in other areas of the Nevada National Security Site. This approach utilizes two types of variables: 1. average mass percentages of sorbing minerals: smectite, mica/illite, hematite, calcite, and zeolite determined from X-ray diffraction (XRD); and 2. linear coefficients derived from reactive chemistry models of surface complexation/ion exchange processes in representative groundwater. This study estimates Kd for Cs, Pu, and Sr isotopes using the same coefficients for component additivity approach applied to RM and SM in the earlier report, but instead uses an updated XRD mineralogy database that expands on the original XRD database. As transport modeling scope for RM/SM evolved since 2011, new considerations have emerged: Transport modeling or sorbing radionuclides has expanded from RM proper to adjacent areas; Probabilistic modeling approaches require examination of transport parameter uncertainty; and, More XRD data will improve estimates of Kd with consideration of uncertainty in mineralogy. This report addresses the above considerations by expanding the analysis of XRD data from two boreholes on RM to over twenty boreholes on RM, SM, and adjacent areas. This analysis focuses on XRD data relevant to potential radionuclide transport pathways sourced from RM and SM.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

Engineering-Scale Integrated Energy System Data Projection Demonstration via the Dynamic Energy Transport and Integration Laboratory

The objective of this study is to demonstrate and validate the Dynamic Energy Transport and Integration Laboratory (DETAIL) preliminary scaling analysis using Modelica language system-code Dymola. The DETAIL preliminary scaling analysis includes a multisystem integral scaling package between thermal-storage and hydrogen-electrolysis systems. To construct the system of scaled equations, dynamical system scaling (DSS) was applied to all governing laws and closure relations associated with the selected integral system. The existing Dymola thermal-energy distribution system (TEDS) facility and high-temperature steam electrolysis (HTSE) facility models in the Idaho National Laboratory HYBRID repository were used to simulate a test case and a corresponding scaled case for integrated system HYBRID demonstration and validation. The DSS projected data based on the test-case simulations and determined scaling ratios were generated and compared with scaled case simulations. The preliminary scaling analysis performance was evaluated, and scaling distortions were investigated based on data magnitude, sequence, and similarity. The results indicated a necessity to change the normalization method for thermal storage generating optimal operating conditions of 261 kW power and mass flow rate of 6.42 kg/s and the possibility of reselecting governing laws for hydrogen electrolysis to improve scaling predictive properties. To enhance system-scaling similarity for TEDS and HTSE, the requirement for scaling validation via physical-facility demonstration was identified.

08 HYDROGEN↗
NASA NTRS1993

Lunar laser ranging data processing in a Unix/X windows environment

In cooperation with the NASA Crustal Dynamics Project initiative placing workstation computers at each of its laser ranging stations to handle data filtering and normalpointing, MLRS personnel have developed a new generation of software to provide the same services for the lunar laser ranging data type. The Unix operating system and X windows/Motif provides an environment for both batch and interactive filtering and normalpointing as well as prediction calculations. The goal is to provide a transportable and maintainable data reduction environment. This software and some sample displays are presented. that the lunar (or satellite) datacould be processed on one computer while data was taken on the other. The reduction of the data was totally interactive and in no way automated. In addition, lunar predictions were produced on-site, another first in the effort to down-size historically mainframe-based applications. Extraction of earth rotation parameters was at one time attempted on site in near-realtime. In 1988, the Crustal Dynamics Project SLR Computer Panel mandated the installation of Hewlett-Packard 9000/360 Unix workstations at each NASA-operated laser ranging station to relieve the aging controller computers of much of their data and communications handling responsibility and to provide on-site data filtering and normal pointing for a growing list of artificial satellite targets. This was seen by MLRS staff as an opportunity to provide a better lunar data processing environment as well.

Ricklefs, Randall L.↗
NASA NTRS1950

The application of the statistical theory of extreme values to gust-load problems

An analysis is presented which indicates that the statistical theory of extreme values is applicable to the problems of predicting the frequency of encountering the larger gust loads and gust velocities for both specific test conditions as well as commercial transport operations. The extreme-value theory provides an analytic form for the distributions of maximum values of gust load and velocity. Methods of fitting the distribution are given along with a method of estimating the reliability of the predictions. The theory of extreme values is applied to available load data from commercial transport operations. The results indicate that the estimates of the frequency of encountering the larger loads are more consistent with the data and more reliable than those obtained in previous analyses. (author)

Press, Harry↗
NASA NTRS1990

Model-data comparisons of moments of nonbreaking shoaling surface gravity waves

The predictions of linear and nonlinear (Boussinesq) shoaling wave models for nonbreaking unidirectional surface gravity waves are compared to field observations, with particular emphasis on quantities that may be important for cross-shore sediment transport. The extensive data sets were obtained on two natural beaches, span water depths between 1 and 10 m, and include incident wave power spectra with narrow, broad, and bimodal shapes. Significant wave heights varied between approximately 30 and 100 cm, and peak periods between approximately 8 and 18 s. The evolution of total variances of sea surface elevation, cross-shore velocity, and horizontal acceleration is modeled at least qualitatively well by both linear and nonlinear theories. Only the nonlinear theory predicts the increasingly asymmetric sea surface elevations and horizontal velocities (pitched-forward wave shapes) and the weaker variation of skewness (difference between crest and trough profiles) which are observed to occur during shoaling. The nonlinear theory also models qualitatively well the large skewed accelerations which occur during the passage of asymmetric waves.

Elgar, Steve↗
NASA NTRS1988

Molecular and particulate contaminants - A contamination data base within ENVIRONET

The Space Transportation System contamination environment appears in the ENVIRONET data base in two parallel chapters, Molecular Contamination and Particulate Environment. The design objectives and a description of the content of this contamination data base are presented. A treatment of the use of the data base is intended to interest the reader in accessing and browsing these chapters. Future plans are discussed briefly, with the emphasis on the approach to providing a dynamic data base.

Barengoltz, Jack↗
NASA NTRS2016

Semantic Representation and Scale-Up of Integrated Air Traffic Management Data

Each day, the global air transportation industry generates a vast amount of heterogeneous data from air carriers, air traffic control providers, and secondary aviation entities handling baggage, ticketing, catering, fuel delivery, and other services. Generally, these data are stored in isolated data systems, separated from each other by significant political, regulatory, economic, and technological divides. These realities aside, integrating aviation data into a single, queryable, big data store could enable insights leading to major efficiency, safety, and cost advantages. In this paper, we describe an implemented system for combining heterogeneous air traffic management data using semantic integration techniques. The system transforms data from its original disparate source formats into a unified semantic representation within an ontology-based triple store. Our initial prototype stores only a small sliver of air traffic data covering one day of operations at a major airport. The paper also describes our analysis of difficulties ahead as we prepare to scale up data storage to accommodate successively larger quantities of data -- eventually covering all US commercial domestic flights over an extended multi-year timeframe. We review several approaches to mitigating scale-up related query performance concerns.

data management↗
NASA NTRS2016

Semantic Representation and Scale-Up of Integrated Air Traffic Management Data

Each day, the global air transportation industry generates a vast amount of heterogeneous data from air carriers, air traffic control providers, and secondary aviation entities handling baggage, ticketing, catering, fuel delivery, and other services. Generally, these data are stored in isolated data systems, separated from each other by significant political, regulatory, economic, and technological divides. These realities aside, integrating aviation data into a single, queryable, big data store could enable insights leading to major efficiency, safety, and cost advantages. In this paper, we describe an implemented system for combining heterogeneous air traffic management data using semantic integration techniques. The system transforms data from its original disparate source formats into a unified semantic representation within an ontology-based triple store. Our initial prototype stores only a small sliver of air traffic data covering one day of operations at a major airport. The paper also describes our analysis of difficulties ahead as we prepare to scale up data storage to accommodate successively larger quantities of data -- eventually covering all US commercial domestic flights over an extended multi-year timeframe. We review several approaches to mitigating scale-up related query performance concerns.

air traffic management↗