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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Investigation of onshore wind farm wake recovery with in situ aircraft measurements during AWAKEN

The share of wind power for electricity supply is increasing worldwide. This highly variable resource requires the improved prediction of power output for network stability. The interaction between wind farm wakes and the atmospheric boundary layer (ABL) introduces uncertainties in power production that warrant detailed investigation. The flow downwind of wind farms is characterized by a reduction in wind speed and an increase in turbulence, which both vary with atmospheric conditions. During the American WAKE experimeNt (AWAKEN), the Technische Universität Braunschweig conducted measurement flights with a research aircraft upwind and downwind of onshore wind farms in the southern Great Plains in Oklahoma in the USA. This study utilizes data from 20 flights conducted at approximately hub height in September 2023 to investigate the wind field variability downwind of the wind farms and vertical profiles to observe atmospheric stratification. The flights were aligned perpendicular to the main wind direction downwind of the King Plains and Armadillo Flats wind farms. Additionally, lidar data from both upwind and downwind ground-based measurement sites and sonic anemometer data were used for comprehensive analysis. Results indicate that under stable ABL conditions, the wake persists at greater downwind distances with a higher velocity deficit in the wake relative to the undisturbed flow compared to unstable stratification. In homogeneous terrain under stable conditions, wake recovery to 95 % occurs between a distance of 4.5 and 9 km downwind of the wind farm. In the semi-complex terrain characterized by shallow hills, slopes, and valleys, the wake exhibits a higher velocity deficit compared to homogeneous terrain, while in some cases the wake was amplified by the terrain resulting in higher velocity deficit 10 km downwind of the wind farm compared to the measurements closer to the wind farm. The turbulent kinetic energy (TKE) and “TKE difference” was found to be a valuable measure in understanding wakes in a semi-complex terrain, showing a clear wake recovery and formation depending on the stratification of the ABL.

17 WIND ENERGY↗
NASA NTRS1970

Manned Space Flight Network Telemetry System

Manned space flight network telemetry system modification for Skylab, ERTS and Apollo J missions, giving data flow diagrams and equipment electrical characteristics

Underwood, T. C., Jr.↗
NASA NTRS1984

Ultranarrow linewidth, magnetically switched, long pulse, xenon chloride laser

A spectral linewidth of less than 70 fm and diffraction-limited beam divergence have been obtained from a long-pulse, electric-discharge xenon chloride laser with intracavity Fabry-Perot etalons. A gain duration of 100 ns provided for multipass operation of the etalons, significantly improving both contrast and finesse. The electrical-discharge circuit required to produce this long gain duration was comprised of a pulse-forming network, a saturable-inductor magnetic switch, and a tapered constant-impedance interface transmission line.

Pacala, T. J.↗
NASA NTRS1984

Seventh Annual Workshop on Meteorological and Environmental Inputs to Aviation Systems 26-28 October 1983, Tullahoma, Tennessee

A summary of reports and recommendations resulting from the Workshop on Meteorological and Environmental Inputs to Aviation Systems is presented. The Workshops have been held to characterize the interaction between aircraft and airport operators with the atmosphere, identify necessary meteorological enhancements, and establish criteria for meteorological data needed by the aviation community. The topics covered included winds and wind shear, turbulence, fog, visibility and ceiling, lightning and atmospheric electricity, icing, frost and snow, rain, ozone and acid rain. The recommendations issued included a denser meteorological network with more automated stations, the development of radar systems for icing forecasts and wind shear alerts, the accumulation of a greater data base on convective cells and lightning strikes, and further study of the impact of rain on aircraft performance.

Camp, D. W.↗
NASA NTRS1999

Numerical Thermal Model of a 30-cm NSTAR Ion Thruster

A thermal computer model of the NSTAR (Nasa Solar Electric Propulsion Technology Applications Readiness) xenon ion thruster has been produced using a lumped parameter thermal nodal network scheme. This model contains 104 nodes on the thruster and was implemented using SINDA (Systems Improved Numerical Differencing Analyzer) and TRASYS (Thermal Radiation Analyzer System) on various UNIX workstations. The model includes radiation and conduction heat transfer, the effect of plasma interaction on the thruster, and an account for finely perforated surfaces. The model was developed in conjunction with an NSTAR thruster outfitted with approximately 20 thermocouples for thermal testing at the NASA Lewis Research Center. The results of these experiments were used to calibrate and confirm the computer model first without and then with the plasma interaction. The calibrated model was able to predict discharge chamber temperatures to within 10 C of measured temperatures. To demonstrate the ability of the model under various circumstances the heat flux was examined for a thruster operating in the environment of space.

VanNoord, Jon↗
NASA NTRS2016

On the VHF Source Retrieval Errors Associated with Lightning Mapping Arrays (LMAs)

This presentation examines in detail the standard retrieval method: that of retrieving the (x, y, z, t) parameters of a lightning VHF point source from multiple ground-based Lightning Mapping Array (LMA) time-of-arrival (TOA) observations. The solution is found by minimizing a chi-squared function via the Levenberg-Marquardt algorithm. The associated forward problem is examined to illustrate the importance of signal-to-noise ratio (SNR). Monte Carlo simulated retrievals are used to assess the benefits of changing various LMA network properties. A generalized retrieval method is also introduced that, in addition to TOA data, uses LMA electric field amplitude measurements to retrieve a transient VHF dipole moment source.

inversion↗
NASA NTRS1995

Neural Networks Analyze Data In Particle-Impact-Noise Tests

Electronic neural networks and computers put to use in analyzing data acquired in particle-impact-noise-detection (PIND) tests of packaged electronic components. PIND tests detect loose particles in packages that cause failures during subsequent operation of packages in presence of accelerations or other effects - for example, loose electrically conductive particles that bounce into positions in which they cause short circuits. Interpretation of test data more objective and accurate. Preliminary results suggest use of neural networks result in significant improvement in quality and reliability and decrease in cost of PIND testing.

Scaglione, Lois J.↗
NASA NTRS2003

Second Law of Thermodynamics Applied to Metabolic Networks

We present a simple algorithm based on linear programming, that combines Kirchoff's flux and potential laws and applies them to metabolic networks to predict thermodynamically feasible reaction fluxes. These law's represent mass conservation and energy feasibility that are widely used in electrical circuit analysis. Formulating the Kirchoff's potential law around a reaction loop in terms of the null space of the stoichiometric matrix leads to a simple representation of the law of entropy that can be readily incorporated into the traditional flux balance analysis without resorting to non-linear optimization. Our technique is new as it can easily check the fluxes got by applying flux balance analysis for thermodynamic feasibility and modify them if they are infeasible so that they satisfy the law of entropy. We illustrate our method by applying it to the network dealing with the central metabolism of Escherichia coli. Due to its simplicity this algorithm will be useful in studying large scale complex metabolic networks in the cell of different organisms.

Nigam, R.↗
DOE OSTI2025

Evaluating Direct and Indirect Influence on EV Charging Stations Across the US

The adoption of new technology for electric vehicles (EV) and mobility applications can bring underappreciated vulnerabilities to the power grid. One area of potential fraud and adversarial influence is through the business ecosystem of startups that own and deploy EV technology. Yet, there are no models or analyses that map the network of organizations and people that have direct and indirect influence over technologies currently deployed in the grid. To fill this gap, we develop a multilayer network model to measure direct and indirect influence on EV charging stations. First, we create and adversarial socio-technical network (ASTN) model via a data fusion pipeline for different US regions of interest (ROI). Then, we develop an integrated ASTN for Chicago, Los Angeles, New York, and Philadelphia. We rank EV charging companies direct influence within each geographic region as well as indirect influence via social network analysis. While some companies have strong direct and indirect influence (i.e., ChargePoint) others show a mismatch between their influence over charging stations and their position within the social network. For example, Tesla has strong direct influence on stations and weak indirect influence over competitors. In contrast, 7Charge has weak direct influence over stations, but strong indirect influence over competitors.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗
DOE OSTI2024

Copper–Carbon Nanotube Composites Enabled by Brush Coating for Advanced Conductors

There is a growing demand for advanced conductors with enhanced electrical properties to increase the energy efficiency in various applications. A promising strategy to achieve this involves the use of ultraconductive copper (UCC) composites that incorporate highly conductive carbon materials, such as carbon nanotubes (CNTs), into the copper matrix. In this study, we present a scalable brush coating technique to incorporate CNTs onto Cu substrates to produce Cu–CNT–Cu composites. The process involves brush coating the CNT solution on Cu tape substrates, followed by vacuum-assisted thermal removal of organic moieties (e.g., surfactant/polymer). This step ensures the creation of a uniformly distributed CNT network within the Cu matrix. By addition of a thin film Cu overlayer, the fabricated Cu–CNT–Cu composite architecture demonstrates similar electrical conductivity, increased current carrying capacity, and enhanced mechanical properties compared to pure Cu reference tapes. Finally, the performance characteristics of these UCC tapes along with the scalability of the brush coating approach hold great promise for the fabrication of advanced conductors for wide-ranging energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2009

The Diagnostic Challenge Competition: Probabilistic Techniques for Fault Diagnosis in Electrical Power Systems

Reliable systems health management is an important research area of NASA. A health management system that can accurately and quickly diagnose faults in various on-board systems of a vehicle will play a key role in the success of current and future NASA missions. We introduce in this paper the ProDiagnose algorithm, a diagnostic algorithm that uses a probabilistic approach, accomplished with Bayesian Network models compiled to Arithmetic Circuits, to diagnose these systems. We describe the ProDiagnose algorithm, how it works, and the probabilistic models involved. We show by experimentation on two Electrical Power Systems based on the ADAPT testbed, used in the Diagnostic Challenge Competition (DX 09), that ProDiagnose can produce results with over 96% accuracy and less than 1 second mean diagnostic time.

Ricks, Brian W.↗
DOE OSTI2026

Dynamic Transmission Line Switching Amid Wildfire-Prone Weather Under Decision-Dependent Uncertainty

During dry and windy seasons, environmental conditions significantly increase the risk of wildfires, exposing power grids to disruptions caused by transmission line failures. Wildfire propagation exacerbates grid vulnerability, potentially leading to prolonged power outages. To address this challenge, we propose a multistage optimization model that dynamically adjusts transmission grid topology in response to wildfire propagation, aiming to develop an optimal response policy. By accounting for decision-dependent uncertainty, where line survival probabilities depend on usage, we employ distributionally robust optimization to model uncertainty in line survival distributions. We adapt the stochastic nested decomposition algorithm and derive a deterministic upper bound for its finite convergence. To enhance computational efficiency, we exploit the Lagrangian dual problem structure for a faster generation of Lagrangian cuts. Using realistic data from the California transmission grid, we demonstrate the superior performance of dynamic response policies against two-stage alternatives through a comprehensive case study. In addition, after solving the multistage formulation, we construct easy-to-implement policies that significantly reduce computational burden while maintaining good performance in real-time deployment. History: Accepted by Russell Bent, Area Editor for Network Optimization: Algorithms and Applications. Funding: This work was supported by the U.S. Department of Energy, Office of Electricity [Grant DE-AC02-05CH11231]. The work of R. Jiang was supported in part by the U.S. National Science Foundation, Division of Electrical, Communications and Cyber Systems [Grant ECCS-1845980] and the U.S. Air Force Office of Scientific Research [Grant FA9550-23-1-0323]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2025.1210 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2025.1210 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

Estrada-Garcia, Juan-Alberto↗
NASA NTRS1984

Time dependent land and vegetation canopy temperatures

A simple interactive biosphere is presented based on an electrical analog of turbulent transport processes that produce heat and moisture fluxes between land and the atmosphere. A network of resistances that effect temperature or vapor pressure fluxes are identified and entered into the quasi steady state equations. A set of solutions that depict a realistic diurnal cycle is included.

Sud, Y. C.↗
NASA NTRS1991

VHF discharges in storm cells producing microbursts

An experiment was carried out in which 3-D mapping of VHF sources was compared to a 3-D description of the reflectivity and dynamics of associated cloud cells observed by a radar network. Data from 61 microbursts were analyzed and it was found that, in 93 pct. of the cases, electrical activity precedes outflow development. The results confirm that the peak in intracloud activity precedes the maximum value of the outflow.

Laroche, P.↗
NASA NTRS2003

Techniques for Characterizing Microwave Printed Antennas

The combination of a de-embedding technique and a direct on-substrate measurement technique has been devised to enable measurement of the electrical characteristics (impedances, scattering parameters, and gains) of microwave printed antennas that may be formed integrally with feed networks that include slot lines, coplanar striplines, and/or coplanar waveguides. The combination of techniques eliminates the need for custom test fixtures, including transitions between (1) coaxial or waveguide feed lines in typical test equipment and (2) the planar waveguide structures of the printed circuits under test. The combination of techniques can be expected to be especially useful for rapid, inexpensive, and accurate characterization of antennas for miniature wireless communication units that operate at frequencies from a few to tens of gigahertz.

Simons, Rainee↗
DOE OSTI2024

3D printable feedstock inks for signal control or computation

In one aspect the present disclosure relates to a 3D printed signal control backbone apparatus. The apparatus may have a filament including a first material section and a plurality of second material sections. The first material section is bounded on opposing ends by the second material sections. The first material section is formed by an ink having a percolating network of a plurality of chiplets infused in a non-conductive polymer. The plurality of chiplets form electrically responsive elements imparting a predetermined logic function and which are responsive to a predetermined electrical signal. The second material sections are formed by an ink which is electrically conductive.

Murialdo, Maxwell↗
NASA NTRS1993

Cascaded VLSI Chips Help Neural Network To Learn

Cascading provides 12-bit resolution needed for learning. Using conventional silicon chip fabrication technology of VLSI, fully connected architecture consisting of 32 wide-range, variable gain, sigmoidal neurons along one diagonal and 7-bit resolution, electrically programmable, synaptic 32 x 31 weight matrix implemented on neuron-synapse chip. To increase weight nominally from 7 to 13 bits, synapses on chip individually cascaded with respective synapses on another 32 x 32 matrix chip with 7-bit resolution synapses only (without neurons). Cascade correlation algorithm varies number of layers effectively connected into network; adds hidden layers one at a time during learning process in such way as to optimize overall number of neurons and complexity and configuration of network.

Duong, Tuan A.↗
DOE OSTI2025

Community Choice Aggregation(CCA) Data Collection Webinar for Status and Trends in the Voluntary Market Report (2024 Data) [Slides]

We have subcontracted LEAN Energy US, to help us improve our CCA data collection effort for the Annual Voluntary Energy Markets Data Report. LEAN Energy US (Local Energy Aggregation Network) is a national 501(c)3 non-profit organization dedicated to accelerating the country's transition to clean and renewable power, supporting competition and customer choice in the energy sector, and maintaining affordable electricity rates. We work in partnership with a range of organizations to actively support the formation and operational success of Community Choice Aggregation (CCA) programs around the country. This webinar, hosted in partnership with LEAN Energy US, is intended to introduce their members to our data collection effort and encourage CCAs in their network to participate.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗