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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Evidence for the Magnetic Breakout Model in an Equatorial Coronal-Hole Jet

Small, impulsive jets commonly occur throughout the solar corona, but are especially visible in coronal holes. Evidence is mounting that jets are part of a continuum of eruptions that extends to much larger coronal mass ejections and eruptive flares. Because coronal-hole jets originate in relatively simple magnetic structures, they offer an ideal testbed for theories of energy buildup and release in the full range of solar eruptions. We analyzed an equatorial coronal-hole jet observed by the Solar Dynamics Observatory (SDO)/AIA (Atmospheric Imaging Assembly)) on 2014 January 9 in which the magnetic-field structure was consistent with the embedded-bipole topology that we identified and modeled previously as an origin of coronal jets. In addition, this event contained a mini-filament, which led to important insights into the energy storage and release mechanisms. SDO/HMI (Solar Dynamics Observatory/Helioseismic and Magnetic Imager) magnetograms revealed footpoint motions in the primary minority-polarity region at the eruption site, but show negligible flux emergence or cancellation for at least 16 hours before the eruption. Therefore, the free energy powering this jet probably came from magnetic shear concentrated at the polarity inversion line within the embedded bipole. We find that the observed activity sequence and its interpretation closely match the predictions of the breakout jet model, strongly supporting the hypothesis that the breakout model can explain solar eruptions on a wide range of scales.

Sun: filaments↗
NASA NTRS1992

The structure and development of streamwise vortex arrays embedded in a turbulent boundary layer

The results of an experimental investigation of the structure and development of streamwise vortices embedded in a turbulent boundary layer are presented. Measurements of secondary velocity in the crossplane are used to characterize the vortex array structure. Measurements in the crossplane at two streamwise locations characterize the influence of interactions among the vortices on the array structure when the initial spacing between vortices is varied. Evidence of the merging of counter-rotating cores is found in embedded arrays of closely spaced vortices. A model of vortex interaction and development is constructed from the experimental results. This model is based on the structure of the two dimensional Ossen vortex. The decay of vortex circulation due to the merging of the cores is correlated with the crossplane gradient in streamwise vorticity occurring between an embedded vortex and its adjacent counter-rotating neighbors.

Wendt, Bruce J.↗
NASA NTRS1990

Local stresses in metal matrix composites subjected to thermal and mechanical loading

An elasticity solution has been used to analyze matrix stresses near the fiber/matrix interface in continuous fiber-reinforced metal-matrix composites, modeling the micromechanics in question in terms of a cylindrical fiber and cylindrical matrix sheath which is embedded in an orthotropic medium representing the composite. The model's predictions for lamina thermal and mechanical properties are applied to a laminate analysis determining ply-level stresses due to thermomechanical loading. A comparison is made between these results, which assume cylindrical symmetry, and the predictions yielded by a FEM model in which the fibers are arranged in a square array.

Highsmith, Alton L.↗
NASA NTRS1996

Modeling and Analysis of Composite Wing Sections for Improved Aeroelastic and Vibration Characteristics Using Smart Materials

The objective of this research is to develop analysis procedures to investigate the coupling of composite and smart materials to improve aeroelastic and vibratory response of aerospace structures. The structural modeling must account for arbitrarily thick geometries, embedded and surface bonded sensors and actuators and imperfections, such as delamination. Changes in the dynamic response due to the presence of smart materials and delaminations is investigated. Experiments are to be performed to validate the proposed mathematical model.

Chattopadhyay, Aditi↗
DOE OSTI2026

Self-supervised and multi-fidelity learning for extended predictive soil spectroscopy

Infrared spectroscopy is a cost-effective, non-destructive, and environmentally benign technology that is increasingly recognized as an important solution for meeting the global demand for soil data. While both near-infrared (NIR) and mid-infrared (MIR) diffuse reflectance spectroscopy enable rapid estimation of soil properties, they present a significant trade-off: NIR offers superior scalability and lower operational costs, whereas MIR provides higher analytical fidelity by capturing fundamental molecular vibrations. In this study, we propose a self-supervised, multi-fidelity learning framework designed to bridge this gap. Our approach leverages large-scale MIR spectral libraries to learn a compact, transferable latent representation, into which NIR spectra are subsequently aligned for downstream prediction. The workflow consists of pretraining a latent model on a large MIR library, adapting the representation using a smaller paired NIR–MIR dataset, and evaluating generalization on an independent external test set. Across a range of chemical and physical soil properties, we found that MIR-derived embeddings improved prediction accuracy relative to baseline models that used raw MIR inputs. Predictions derived from the spectrum conversion (NIR to MIR) task did not match the performance of the original MIR spectra but were similar or superior to predictive performance of NIR-only models, suggesting the unified spectral latent space can effectively leverage the larger and more diverse MIR dataset for prediction of soil properties not well represented in current NIR libraries.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Analytic Neural Network Gaussian Process Enabled Chance-Constrained Voltage Regulation for Active Distribution Systems with PVs, Batteries and EVs

This paper proposes an analytic neural network Gaussian process (NNGP)-based chance-constrained real-time voltage regulation method for active distribution systems with photovoltaics (PVs), batteries, and electric vehicles (EVs). NNGP can utilize historical measurement data to achieve real-time probabilistic node voltage estimation through Bayesian inference. Then, NNGP is fully analytically embedded into the optimal power flow model to perform voltage regulation and adapt to various topological changes. The uncertainties of voltage estimations are easily considered via the chance constraint, and it has been shown that the adoption of this chance constraint can significantly improve the reliability of voltage regulation under various scenarios. The comparison results with other methods, carried out on a real 759-node distribution system located in western Colorado, U.S., show that the proposed method can achieve accurate voltage estimation across different topologies and reliably perform voltage regulation considering PVs, batteries, and EVs.

active distribution systems↗
DOE OSTI2025

Detecting Living-off-the-land Attacks Using K-means And Graph Convolutional Networks

The code ingests Zeek logs derived from network packet captures and goes through data preprocessing before it gets passed into a K-Means model that labels each device as either a client or server. Graph Convolutional Network (GCN) model is used to obtain the embeddings to represent the features in lower dimension. Last, K-means cluster analysis is used to cluster the embeddings for each class.

Quach, Anna [Idaho National Laboratory (INL), Idah↗
DOE OSTI2024

Flux REaction TArget Prioritization (Flux RETAP) v1

Metabolic engineering is evolving rapidly as a result of new advances in synthetic biology and automation, as well as the irruption of machine learning (ML). ML has been shown to provide the predictive power synthetic biology lacked and needed, and to be able to effectively guide the metabolic engineering process. However, current technical limitations prevent the independent application of ML approaches to metabolic engineering without the use of previous biological knowledge in the form of a prioritized list of desirable engineering targets. Here, we present FluxRETAP, a simple and computationally inexpensive method that leverages the prior mechanistic knowledge embedded in genome-scale metabolic models (GSMs) for suggesting targets for genetic overexpression, downregulation or deletion, with the final goal of increasing metabolite production. FluxRETAP captured 100% of reaction targets experimentally verified to improve Escherichia coli isoprenol production in the literature accessible to us, 50% of targets that experimentally improved taxadiene production in E. coli and ~60% of genetic targets from a verified minimal constrained cut-set in Pseudomonas putida while providing additional high priority targets that could be tested. Overall, FluxRETAP is an efficient algorithm for identifying a prioritized list of testable genetic and reaction targets which can also be utilized in ML pipelines.

Czajka, Jeffrey [Battelle Memorial Institute, Paci↗
DOE OSTI2024

Life Cycle Greenhouse Gas Emissions of Coal-Biomass Co-Firing Power Plants with Carbon Capture and Storage

The United States has set a target to achieve the net-zero economy by 2050. Bioenergy with Carbon Capture and Sequestration (BECCS) is one of the promising negative-emission routes in the mitigation portfolio to help meet this goal. Coal-biomass co-firing with carbon capture and storage (CCS) is a key BECCS technology to realize the carbon mitigation at fossil-fuel power plants. The mitigation potential of co-firing option is affected by numerous critical factors, such as biomass properties, co-firing level, and carbon capture rate. The objectives of the study are to characterize and estimate the life cycle greenhouse gas (GHG) emissions and performance of coal-biomass co-firing power plants with CCS, determine the breakeven co-firing level at power plants necessary to achieve net-zero life cycle emissions, and quantify the variabilities and uncertainties in life cycle emissions. The scope of the life cycle assessment includes the fuel supply, combustion-based power generation, and CO2 transport and storage. A fuel-based life cycle module is developed and embedded in the Integrated Environmental Control Model (IECM), a fossil-fuel power plant modeling tool. This study then applies the enhanced IECM to conduct the process-based life cycle assessment for an array of biomass co-firing scenarios. Deterministic analysis indicates that reaching net-zero life cycle emissions in a biomass co-firing plant without CCS deployment is challenging. Combining biomass co-firing and CCS deployment can significantly lower the overall life cycle emissions of power plants. Net-zero life cycle emissions can be achieved with a 20 wt.% co-firing level and 90% CCS when the Powder River Basin coal is co-fired with energy crops or forestry residues. However, the breakeven co-firing level for net-zero emissions depend on the selected fuel properties. Fuel supply and plant operation are the critical stages influencing the life cycle emissions of power plants with 90% CCS. Deployment of deep CCS beyond 90% CO2 capture can remarkably reduce operational emissions and the breakeven co-firing level. With 99% CCS, the breakeven co-firing rate can be reduced to 12% on average. These findings highlight the trade-offs between technical performance and environmental impact of biomass co-firing at coal-fired power plants and emphasize the role of deep CCS in achieving a net-zero emissions future.

Wu, Wanying↗
NASA NTRS1984

Heat transfer distributions around nominal ice accretion shapes formed on a cylinder in the NASA Lewis icing research tunnel

Local heat transfer coefficients were obtained on irregular cylindrical shapes which typify the accretion of ice on circular cylinders in cross flow. The ice shapes were grown on a 5.1 cm (2.0 in.) diameter cylinder in the NASA Lewis Icing Research Tunnel. The shapes were 2, 5, and 15 min accumulations of glaze ice and 15 min accumulation of rime ice. Heat transfer coefficients were also measured around the cylinder with no ice accretion. These icing shapes were averaged axially to obtain a nominal shape of constant cross section for the heat transfer tests. Heat transfer coefficients around the perimeter of each shape were measured with electrically heated copper strips embedded in the surface of the model which was cast from polyurethane foam. Each strip contained a thermocouple to measure the local surface temperature. The models were run in a 15.2 x 68.6 cm (6 x 27 in.) wind tunnel at several velocities. Background turbulence in the wind tunnel was less than 0.5 percent. The models were also run with a turbulence producing grid which gave about 3.5 percent turbulence at the model location with the model removed. The effect of roughness was also simulated with sand grains glued to the surface. Results are presented as Nusselt number versus angle from the stagnation line for the smooth and rough models for both high and low levels of free stream turblence. Roughness of the surface in the region prior to flow separation plays a major role in determining the heat transfer distribution.

Vanfossen, G. J.↗
NASA NTRS1985

A Residuals Approach to Filtering, Smoothing and Identification for Static Distributed Systems

An approach for state estimation and identification of spatially distributed parameters embedded in static distributed (elliptic) system models is advanced. The method of maximum likelihood is used to find parameter values that maximize a likelihood functional for the system model, or equivalently, that minimize the negative logarithm of this functional. To find the minimum, a Newton-Raphson search is conducted that from an initial estimate generates a convergent sequence of parameter estimates. For simplicity, a Gauss-Markov approach is used to approximate the Hessian in terms of products of first derivatives. The gradient and approximate Hessian are computed by first arranging the negative log likelihood functional into a form based on the square root factorization of the predicted covariance of the measurement process. The resulting data processing approach, referred to here by the new term of predicted data covariance square root filtering, makes the gradient and approximate Hessian calculations very simple. A closely related set of state estimates is also produced by the maximum likelihood method: smoothed estimates that are optimal in a conditional mean sense and filtered estimates that emerge from the predicted data covariance square root filter.

Rodriguez, G.↗
NASA NTRS1988

Modeling of Some Coplanar Waveguide Discontinuities

Presented are lumped equivalent circuit models for several coplanar waveguide discontinuities such as an open circuit, a series gap, and a symmetric step, and their element values as a function of the discontinuity physical dimensions. The model element values are de-embedded from measured S-parameters. The frequency dependence of the effective dielectric constant was measured and compared to computed values.

Simons, Rainee N.↗
NASA NTRS1988

Modeling of some coplanar waveguide discontinuities

Presented are lumped equivalent circuit models for several coplaar waveguide discontinuities such as an open circuit, a series gap, and a symmetric step, and their element values as a function of the discontinuity physical dimensions. The model element values are de-embedded from measured S parameters. The frequency dependence of the effective dielectric constant is measured and compared to computed values.

Simons, Rainee N.↗
NASA NTRS1993

Nonlinear waves and solitons in molecular clouds

We begin a study of nonlinear wave phenomena in molecular clouds. These clouds exhibit highly nonlinear structure that is often described in terms of 'clumps' and 'filaments' which are bouncing around, twisting, and colliding within the cloud. These clouds are important because they ultimately produce the initial conditions for the star formation process. Our motivation is to explore the possibility that solitons (i.e., spatially localized, single-hump wave entities which often exhibit remarkable stability) can live in these molecular clouds and produce their observed structure. In this paper we focus on the case of one spatial dimension, and we show that a rich variety of nonlinear waves can exist in molecular cloud fluid systems (where self-gravity is included). We show that in the absence of magnetic fields no true soliton solutions are allowed, although highly nonlinear waves (whose crests become widely spaced and thus soliton-like) do exist. For clouds with embedded magnetic fields, we derive a model equation which describes the behavior of wave phenomena; this model equation allows solutions which correspond to nonlinear waves, solitons, and topological solitons. We briefly consider the stability of these wave entities and discuss the possible role they play in molecular cloud dynamics.

Adams, Fred C.↗
NASA NTRS1993

Polarimetric backscattering from sea ice

Polarimetric backscattering from sea ice is presented. Theoretical models for backscattering are first presented for various ice types. Then, theoretical results are compared with experimental data for new thin ice, first-year ice, and multi-year ice. Sea ice is modeled as a layer medium containing random scatterers and rough interfaces. For multi-year sea ice with snow cover, the sea ice layer is modeled as an ice background with embedded spheroidal air bubbles and the snow layer as air with ice grains. The hummocky topography on multi-year ice is characterized by a Gaussian distribution which has an averaging effect on backscattering coefficients. First-year sea ice is described by an ice medium hosting ellipsoidal brine inclusions. These inclusions are oriented preferentially in the vertical direction due to the columnar structure of first-year sea ice. Azimuthally, the orientation of the brine pockets are random corresponding to the random c-axes in sea ice, unless the axes are oriented by sea currents. For thin ice in newly opened leads, it has been observed that there exists a thin brine layer with very high salinity on the top surface of the new ice. This brine layer is depicted as a medium with high permittivity which can significantly affect electromagnetic scattering signatures from the lower thin ice layer, with a higher fractional volume of brine inclusions due to higher salinity as compared to thick first-year sea ice. The rough medium interfaces are described as Gaussian rough surfaces characterized by root-mean-square heights and surface correlation lengths. The contribution from rough surface, calculated under the Kirchhoff approximation or small perturbation method, is assumed to be independent from volume scattering. The total loss including absorption and scattering losses in the scattering media is represented by the imaginary part of effective permittivity obtained from the strong fluctuation theory. The polarimetric scattering coefficients for different ice types are then derived under the distorted Born approximation.

Nghiem, S. V.↗
NASA NTRS1997

Introduction and Highlights of the Workshop

Four generations of CAD/CAM systems can be identified, corresponding to changes in both modeling functionality and software architecture. The systems evolved from 2D and wireframes to solid modeling, to parametric/variational modelers to the current simulation-embedded systems. Recent developments have enabled design engineers to perform many of the complex analysis tasks, typically performed by analysis experts. Some of the characteristics of the current and emerging CAD/CAM/CAE systems are described in subsequent presentations. The focus of the workshop is on the potential of CAD/CAM/CAE systems for use in simulating the entire mission and life-cycle of future aerospace systems, and the needed development to realize this potential. First, the major features of the emerging computing, communication and networking environment are outlined; second, the characteristics and design drivers of future aerospace systems are identified; third, the concept of intelligent synthesis environment being planned by NASA, the UVA ACT Center and JPL is presented; and fourth, the objectives and format of the workshop are outlined.

Noor, Ahmed K.↗
NASA NTRS1998

Analysis of Linear Aerospike Plume Induced X-33 Base Heating Environment

Computational analysis is conducted to study the effect of an linear aerospike engine plume on the X-33 base-heating environment during ascent flight. To properly account for the freestream-body interaction and to allow for potential plume-induced flow-separation, the thermo-flowfield of the entire vehicle at several trajectory points is computed. A sequential grid-refinement technique is used in conjunction with solution-adaptive, patched, and embedded grid methods to limit the model to a manageable size. The computational methodology is based on a three-dimensional, finite-difference, viscous flow, chemically reacting, pressure-based computational fluid dynamics formulation, and a three-dimensional, finite-volume, spectral-line based weighted-sum-of-gray-gases absorption, computational radiation heat transfer formulation. The computed forebody and afterbody surface pressure coefficients and base pressure characteristic curves are compared with those of a cold-flow test. The predicted convective and radiative base-heat fluxes, the effect of base-bleed, and the potential of plume-induced flow separation are presented.

Wang, Ten-See↗
NASA NTRS2004

Ocean Carbon Flux, Transport, and Burial Within the Western and Eastern US Coastal Zones

This project has been to develop and apply a regional. eddy-resolving circulation and biogeochemistry model of both the western and eastern U.S. coastal regions, capable of simulating the processes that control the carbon cycle. Validation has been by statistical comparison with analyses from various satellite measurements, including those from EOS sensors, as well as from in situ measurements. Sensitivity studies were carried out to investigate how the coastal ecosystem and biogeochemical cycles respond to changes in climate, large-scale eutrophication from indus- trial pollution, and other anthropogenic induced changes. The research has been conducted in collaboration with research groups at UCLA. NASA/GSFC (Wallops), Rutgers, and SIO. Overall. the project was focused on several key modeling issues, each of which tie back into completing the primary task of developing a coastal carbon model for both the eastern and western US. coasts. Individual groups within the entire program are still collaborating to address these specific tasks. These include: implementation of the coupled circulation/biogeochemical model within the U.S. West Coast. including high-resolution, embedded subdomains for the Southern California Bight and Monterey Bay region; development of a biogeochemical model with resolved carbon, nitrogen and oxygen cycles; development of data assimilation techniques for use of satellite data sets; reconfiguration of the model domain to U.S. East Coast; development of coastal forcing fields: development of methods to compare the model against remotely sensed data; and, the test of model sensitivity to environmental conditions. Below, we present a summary of the progress made toward achieving these soak. Because this has been a multi-institutional, collaborative effort, we note the groups involved with particular activities.

McWilliams, James C.↗