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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Validation of Simplified Load Equations through Loads Measurement and Modeling of a Small Horizontal-Axis Wind Turbine Tower; NREL (National Renewable Energy Laboratory)

As part of an ongoing effort to improve the modeling and prediction of small wind turbine dynamics, NREL tested a small horizontal axis wind turbine in the field at the National Wind Technology Center (NWTC). The test turbine was a 2.1-kW downwind machine mounted on an 18-meter multi-section fiberglass composite tower. The tower was instrumented and monitored for approximately 6 months. The collected data were analyzed to assess the turbine and tower loads and further validate the simplified loads equations from the International Electrotechnical Commission (IEC) 61400-2 design standards. Field-measured loads were also compared to the output of an aeroelastic model of the turbine. Ultimate loads at the tower base were assessed using both the simplified design equations and the aeroelastic model output. The simplified design equations in IEC 61400-2 do not accurately model fatigue loads. In this project, we compared fatigue loads as measured in the field, as predicted by the aeroelastic model, and as calculated using the simplified design equations.

17 WIND ENERGY↗
DOE OSTI2020

Dynamic domain kinematic modelling for predicting interflow over leaky impeding layers

Traditional Boussinesq or kinematic simulations of interflow (i.e., lateral subsurface flow) assume no leakage through the impeding layer and require a no-flow boundary condition at the ridge top. However, recent analyses of many interflow-producing landscapes indicate that leaky impeding layers are common, that most interflow percolates well before reaching the toe slope, and therefore, the downslope contributing length is shorter than the hillslope length. In watersheds characterised by perched interflow over a low conductivity layer through permeable topsoil, interflow with percolation may be modelled with a kinematic wave model using a mobile upslope boundary condition defining the hillslope portion contributing interflow to valleys. Here, we developed and applied a dynamic interflow model to simulate interflow using a downslope travel distance concept such that only the active contributing length is modelled at any time. The model defines a variable active area based on the depth of the perched layer, the topographic slope and the ratio of the hydraulic conductivity of topsoil to that of the impeding layer. It incorporates a two-layer soil moisture accounting water balance analysis, a pedo-transfer function, and percolation and evaporation routines to predict interflow rates in continuous and event-based scenarios. We tested the modelling concept on two sets of data (2-year dataset of rainfall observations for the continuous simulation and a multi-day irrigation experiment for the event simulation) from a 121-m-long open interflow collection trench on an experimental hillslope at the Savannah River Site, South Carolina. The continuous model simulation partially represented the observed interflow hydrograph and perched water depth in the experimental hillslope with correlation coefficients of 0.85 and 0.35, respectively. Model performance improved significantly at event-scale analysis. The modelling approach realistically represents interflow dynamics in hillslopes with leaky impeding layers and can be integrated into catchment-scale hydrology models for more detailed hillslope process modelling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Tank Closure Cesium Removal Project CST Simulant Cesium Batch Contact Kinetics Test Results and Column Performance Predictions

To evaluate the cesium removal capabilities of the caustic-washed R9120-B version of crystalline silicotitanate (CST) ion exchange media from Savannah River Site (SRS) waste during Tank Closure Cesium Removal (TCCR) column processing, batch contact kinetics tests were performed at 23 °C in SRS Average simulant. Cesium loading kinetics data was also collected (in current and previous testing; King, et al., 2018a) using the same simulant for an older CST sample (IE- 911) which was caustic-washed by the vendor many years ago and was recently retrieved from drums stored at SRS. (Note that R9120-B and IE-911 are believed to be identical materials, after the R9120-B was caustic washed by SRNL, and differ only by particle size and manufacturing date, and thus can be considered different batches). Although cesium loading kinetics testing can be conducted more rigorously using dynamic column tests, the batch contact method requires less simulant and considerably less experimental effort. Average percent removal data for batch contact samples for the two CST batches are provided in Table ES-1. Faster cesium uptake was observed with IE-911, although the loading rates for the two media batches were similar. After 5.5 hours of CST contact, 81% cesium removal was observed with R9120-B versus 86% removal with IE-911. Although these differences are small, the trend is consistent across the timed results, with the larger bead material always loading slower. These seemingly small differences in percent removal are believed to have a large impact on the column performance. Cesium loading curves for the two CST batches are provided in Figure ES-1 below. Faster cesium loading with IE-911 CST is presumed to be associated with the smaller average particle diameter (408 μm mean volume diameter) versus R9120-B (572 μm diameter). Cesium loading kinetic data was needed to conduct column performance comparisons (i.e., model predictions) for the two CST batches.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

From atomistic models to machine learning: Predictive design of nanocarbons under extreme conditions

The formation of technologically valuable nanocarbon structures under extreme conditions, such as those produced during high-explosive detonations, remains poorly understood but holds significant potential for the development of controlled synthesis pathways. While detonation shockwaves provide the high-pressure, high-temperature environment required for nanodiamond formation, subsequent cooling and decompression dictate whether the diamond phase is preserved or transformed into other nanocarbon structures. Here, in this study, we employ GPU-accelerated reactive molecular dynamics (ReaxFF) simulations to investigate the graphitization and structural remodeling of detonation nanodiamond under nonlinear quench and pressure-release trajectories. We further investigate how the initial nanodiamond morphology; cuboctahedral, octahedral, or hexagonal prism influences the resulting transformation products. Evolution of nanostructure, allotrope (via simulated x-ray diffraction), carbon hybridization, and ring statistics are tracked during a two-stage quench from 5000 K to 60 GPa. Rapid cooling combined with slow decompression optimizes cubic diamond retention, whereas slow cooling with rapid pressure release promotes surface-to-core graphitization, producing concentric sp 2 -hybridized layers and hollowed inner shells. Octahedral nanodiamonds evolve into carbon nano-onions, initially forming bucky diamonds that progressively transform into fully sp 2 -hybridized structures, while hexagonal prisms preferentially form parallel-stacked graphite layers resembling carbon dots. Transient hexagonal diamond (lonsdaleite) emerges as an interfacial phase, suggesting potential reversibility in the shock-induced graphite-to-diamond transformation pathway transformation route. To extend predictive capabilities, we trained machine learning (ML) regressors on over 10 5 node-hours of molecular dynamics (MD) trajectories. A multilayer perceptron (MLP) model reliably predicts the number of graphitized layers from temperature–pressure trajectories with a coefficient of determination (R 2 ) exceeding 0.90. This high predictive fidelity enables efficient, high-throughput mapping of the synthesis parameter space for optimized graphitization outcomes. Collectively, morphological control combined with optimized quench–decompression conditions promote the selective synthesis of nanocarbon allotropes. This work establishes a data-driven framework for the rational, a priori design of carbon nanomaterials for applications in energy storage, sensing, and biomedicine.

Detonation nanodiamond remodeling↗
DOE OSTI2014

A computational tool integrating host immunity with antibiotic dynamics to study tuberculosis treatment

While active tuberculosis (TB) is a treatable disease, many complex factors prevent its global elimination. Part of the difficulty in developing optimal therapies is the large design space of antibiotic doses, regimens and combinations. Computational models that capture the spatial and temporal dynamics of antibiotics at the site of infection can aid in reducing the design space of costly and time-consuming animal pre-clinical and human clinical trials. The site of infection in TB is the granuloma, a collection of immune cells and bacteria that form in the lung, and new data suggest that penetration of drugs throughout granulomas is problematic. In this paper, we integrate our computational model of granuloma formation and function with models for plasma pharmacokinetics, lung tissue pharmacokinetics and pharmacodynamics for two first line anti-TB antibiotics. The integrated model is calibrated to animal data. We make four predictions. First, antibiotics are frequently below effective concentrations inside granulomas, leading to bacterial growth between doses and contributing to the long treatment periods required for TB. Second, antibiotic concentration gradients form within granulomas, with lower concentrations toward their centers. Third, during antibiotic treatment, bacterial subpopulations are similar for INH and RIF treatment: mostly intracellular with extracellular bacteria located in areas non-permissive for replication (hypoxic areas), presenting a slowly increasing target population over time. In conclusion, we find that on an individual granuloma basis, pre-treatment infection severity (including bacterial burden, host cell activation and host cell death) is predictive of treatment outcome.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

In Situ Characterization of Surface Recombination in p-Si/SiO x Based Photoelectrochemical Cells

Time-resolved infrared (TRIR) and electrochemical impedance spectroscopy (EIS) were utilized to quantify surface states present at silicon oxide (SiO x ) protected crystalline p-Si electrolyte interfaces. The primary goal was to identify p-Si/SiO x photoelectrodes with both low surface recombination rates and efficient multi-electron transfer to an acceptor present in the external electrolyte. Three SiO x layers were investigated: native oxide (nOx), chemical oxide (cOx), and rapid thermal annealed (RTA) thermal oxide (tOx). Comparative study with [Ru(bpy) 3 ](PF 6 ) 2 as the electron acceptor indicated that tOx was most optimal with a small effective recombination rate, multi-electron transfer capability, and photovoltage of 500 ± 50 mV. A secondary goal was to analyze the surface recombination rates with the Shockley–Read–Hall (SRH) kinetic model. Two surface states were identified from this analysis, one closer to the CB edge (V t,1 ) and the other near the midgap (V t,2 ). EIS and SRH analyses revealed that a forming gas (5% H 2 /N 2 ) anneal (FGA) decreased surface recombination for tOx and nOx through a lower density of surface states. In the case of tOx, the infrared data indicated that V t,2 was completely removed. Here, the energetic positions of the band edges were correlated with the surface state density; low densities corresponded to more favorable potentials for inversion layer formation, which is expected to be most optimal for photocatalysis. Collectively this study indicates that the free carrier dynamics provided by TRIR represent a powerful in situ probe of the band edge and the surface state energetics in silicon based photoelectrochemical cells.

Electrochemical Impedance Spectroscopy↗
DOE OSTI2024

A Novel Method to Train Classification Models for Structure Detection in In Situ Spacecraft Data

We present a method for creating spacecraft-like data which can be used to train Machine Learning (ML) models to detect and classify structures in in situ spacecraft data. First, we use the Grad-Shafranov equation to numerically solve for several magnetohydrostatic equilibria which are variations on a known analytic equilibrium. These equilibria are then used as the initial conditions for Particle-In-Cell simulations in which the structures of interest are observed and labeled. We then take one-dimensional slices through the simulations to replicate what a spacecraft collecting data from the simulation would observe. This sliced data then can be used as training data for the initial training of ML models intended for use on spacecraft data. We demonstrate the method applied to the problem of detecting small-scale plasmoids in the magnetotail, which is important for understanding complex magnetotail reconnection dynamics. The simple 1D classifier we train is able to detect more than 70% of the plasmoid points in the data set but also produces a large number of false positives. Our further work on this example problem is detailed, and further potential uses of the method are discussed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

CryoDRGN-AI: neural ab initio reconstruction of challenging cryo-EM and cryo-ET datasets

Proteins and other biomolecules form dynamic macromolecular machines that are tightly orchestrated to move, bind, and perform chemistry. Cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET) can access the intrinsic heterogeneity of these complexes and are therefore key tools for understanding their function. However, 3D reconstruction of the collected imaging data presents a challenging computational problem, especially without any starting information, a setting termed ab initio reconstruction. Here, in this study, we introduce cryoDRGN-AI, a method leveraging an expressive neural representation and combining an exhaustive search strategy with gradient-based optimization to process challenging heterogeneous datasets. Using cryoDRGN-AI, we reveal new conformational states in large datasets, reconstruct previously unresolved motions from unfiltered datasets, and demonstrate ab initio reconstruction of biomolecular complexes from in situ data. With this expressive and scalable model for structure determination, we hope to unlock the full potential of cryo-EM and cryo-ET as a high-throughput tool for structural biology and discovery.

Levy, Axel [Stanford Univ., CA (United States); SL↗
DOE OSTI2016

Microscopic modeling of mass and charge distributions in the spontaneous fission of 240 Pu

We propose a methodology to calculate microscopically the mass and charge distributions of spontaneous fission yields. We combine the multidimensional minimization of collective action for fission with stochastic Langevin dynamics to track the relevant fission paths from the ground-state configuration up to scission. The nuclear potential energy and collective inertia governing the tunneling motion are obtained with nuclear density functional theory in the collective space of shape deformations and pairing. As a result, we obtain a quantitative agreement with experimental data and find that both the charge and mass distributions in the spontaneous fission of 240 Pu are sensitive both to the dissipation in collective motion and to adiabatic fission characteristics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Effects of Port Angle on Scavenging of an Opposed Piston Two-Stroke Engine

Opposed-piston 2-stroke (OP-2S) engines have the potential to achieve higher thermal efficiency than a typical diesel engine. However, the uniflow scavenging process is difficult to control over a wide range of speeds and loads. Scavenging performance is highly sensitive to pressure dynamics, port timings, and port design. This study proposes an analysis of the effects of port vane angle on the scavenging performance of an opposed-piston 2-stroke engine via simulation. A CFD model of a three-cylinder opposed-piston 2-stroke was developed and validated against experimental data collected by Achates Power Inc. One of the three cylinders was then isolated in a new model and simulated using cycle-averaged and cylinder-averaged initial/ boundary conditions. This isolated cylinder model was used to efficiently sweep port angles from 12 degrees to 29 degrees at different pressure ratios. Results indicate that scavenging performance is correlated with the bulk swirl ratio generated by these port angles. Scavenging performance is also sensitive to the pressure ratio across the engine. It was concluded that, for a given pressure ratio, the smallest port angle produces the best scavenging; however, previous work indicates lower bulk swirl ratio during combustion can have an impact on emissions formation.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1977

Determination of thermospheric quantities from simple ionospheric observations using numerical simulation

Measured ionospheric electron content and peak electron concentration data are introduced into a numerical simulation of the ionosphere to yield values of induced plasma drifts and exospheric neutral temperatures consistent with the observations. Data collected on 23-24 March 1970 on the East Coast of the U.S.A. are analyzed and the results are in agreement with incoherent radar measurements at Millstone Hill, Massachusetts. Neutral winds and meridional exospheric temperature gradients that give rise to the computed plasma drifts are calculated through the use of a dynamic model of the thermosphere.

Antoniadis, D. A.↗
NASA NTRS1983

Planetary atmospheres

During the period from 1979 to 1982, Pioneer and Voyager missions to Venus, Jupiter, and Saturn combined with ongoing analysis and data collection from the Viking-Mars mission have contributed greatly to an understanding of planetary atmospheres. Research concerning the atmosphere of Venus is discussed, taking into account the atmospheric composition, the isotopic ratios of noble gases, data concerning temperature and pressure, information regarding various atmospheric layers, atmospheric density data, and models regarding the dynamical properties of Venus' atmosphere. Information concerning the atmosphere of Mars is also examined. Isotopic ratios of carbon and oxygen are considered along with altitude profiles, diurnal heating and cooling, and thermal tides and their relationship to dust storms. Attention is given to the temperature structure of the Jovian atmosphere, the morphology of Jovian cloud features, features in the Saturnian atmosphere, information with respect to the atmosphere of Titan, the rotation rates of Uranus, masses and densities of Uranus and Neptune, and the identification of Pluto as a small icy body.

Beebe, R.↗
NASA NTRS1995

Laser-Induced Incandescence Calibration via Gravimetric Sampling

Various beam imaging and/or sheet forming optics delivered light at 1064 nm from a pulsed Nd:YAG laser for use either as a beam of 3 mm radius or as a laser sheet. Imaging measurements were performed with a grated intensified array camera equipped with an ultraviolet f4.5 lens and a 40 mm extension tube. Point measurements were performed using an ultraviolet 250 mm focal length lens to collect and focus the laser induced incandescence (LII) signal into a 1 meter long quartz optical fiber which directed the LII signal to a 1/4 meter monochromator. An aperture preceding the lens restricted the signal collection region to 1 cm along the laser beam at the center of the gravimetric chimney. Signals from the PMT were processed by a boxcar integrator whereas the images were captured digitally using a frame-grabber with 16 MByte of on-board memory. Both 'point' and planar measurements were made with detector gates of 250 ns to minimize possible morphology bias in collection of the LII signal. Additionally, the imaging measurements were performed with broadband spectral collection of the LII signal to maximize the signal and again minimize any potential effects of morphology dependent heating and/or cooling rates. Digital delay generators controlled the firing of he laser, detector gates and data acquisition. Neutral density filters were used for both sets of measurements to maintain signal levels within linear dynamic ranges of the detectors, the range being determined prior to experiments.

VanderWal, R. L.↗
NASA NTRS1994

FAST User Guide

The Flow Analysis Software Toolkit, FAST, is a software environment for visualizing data. FAST is a collection of separate programs (modules) that run simultaneously and allow the user to examine the results of numerical and experimental simulations. The user can load data files, perform calculations on the data, visualize the results of these calculations, construct scenes of 3D graphical objects, and plot, animate and record the scenes. Computational Fluid Dynamics (CFD) visualization is the primary intended use of FAST, but FAST can also assist in the analysis of other types of data. FAST combines the capabilities of such programs as PLOT3D, RIP, SURF, and GAS into one environment with modules that share data. Sharing data between modules eliminates the drudgery of transferring data between programs. All the modules in the FAST environment have a consistent, highly interactive graphical user interface. Most commands are entered by pointing and'clicking. The modular construction of FAST makes it flexible and extensible. The environment can be custom configured and new modules can be developed and added as needed. The following modules have been developed for FAST: VIEWER, FILE IO, CALCULATOR, SURFER, TOPOLOGY, PLOTTER, TITLER, TRACER, ARCGRAPH, GQ, SURFERU, SHOTET, and ISOLEVU. A utility is also included to make the inclusion of user defined modules in the FAST environment easy. The VIEWER module is the central control for the FAST environment. From VIEWER, the user can-change object attributes, interactively position objects in three-dimensional space, define and save scenes, create animations, spawn new FAST modules, add additional view windows, and save and execute command scripts. The FAST User Guide uses text and FAST MAPS (graphical representations of the entire user interface) to guide the user through the use of FAST. Chapters include: Maps, Overview, Tips, Getting Started Tutorial, a separate chapter for each module, file formats, and system administration.

Walatka, Pamela P.↗
NASA NTRS2024

High Spectral Resolution Lidar – Generation 2 (HSRL-2) Retrievals of Ocean Surface Wind Speed: Methodology and Evaluation

Ocean surface wind speed (i.e., wind speed 10 m above sea level) is a critical parameter used by atmospheric models to estimate the state of the marine atmospheric boundary layer (MABL). Accurate surface wind speed measurements in diverse locations are required to improve characterization of MABL dynamics and assess how models simulate large-scale phenomena related to climate change and global weather patterns. To provide these measurements, this study introduces and evaluates a new surface wind speed data product from the NASA Langley Research Center nadir-viewing High Spectral Resolution Lidar – generation 2 (HSRL-2) using data collected as part of the NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) mission. The HSRL-2 can directly measure vertically resolved aerosol backscatter and extinction profiles without additional constraints or assumptions, enabling the instrument to accurately derive atmospheric attenuation and directly determine surface reflectance (i.e., surface backscatter). Also, the high horizontal spatial resolution of the HSRL-2 retrievals (0.5 s or ∼ 75 m along track) allows the instrument to probe the fine-scale spatial variability in surface wind speeds over time along the flight track and over breaks in broken cloud fields. A rigorous evaluation of these retrievals is performed by comparing coincident HSRL-2 and National Center for Atmospheric Research (NCAR) Airborne Vertical Atmosphere Profiling System (AVAPS) dropsonde data, owing to the joint deployment of these two instruments on the ACTIVATE King Air aircraft. These comparisons show correlations of 0.89, slopes of 1.04 and 1.17, and y intercepts of −0.13 and −1.05 m s−1 for linear and bisector regressions, respectively, and the overall accuracy is calculated to be 0.15 ± 1.80 m s−1. It is also shown that the dropsonde surface wind speed data most closely follow the HSRL-2 distribution of wave slope variance using the distribution proposed by Hu et al. (2008) rather than the ones proposed by Cox and Munk (1954) and Wu (1990) for surface wind speeds below 7 m s−1, with this category comprising most of the ACTIVATE data set. The retrievals are then evaluated separately for surface wind speeds below 7 m s−1 and between 7 and 13.3 m s−1 and show that the HSRL-2 retrieves surface wind speeds with a bias of ∼ 0.5 m s−1 and an error of ∼ 1.5 m s−1, a finding not apparent in the cumulative comparisons. Also, it is shown that the HSRL-2 retrievals are more accurate in the summer (−0.18 ± 1.52 m s−1) than in the winter (0.63 ± 2.07 m s−1), but the HSRL-2 is still able to make numerous (N=236) accurate retrievals in the winter. Overall, this study highlights the abilities and assesses the performance of the HSRL-2 surface wind speed retrievals, and it is hoped that further evaluation of these retrievals will be performed using other airborne and satellite data sets.

Sanja Dmitrovic↗
NASA NTRSDate not supplied

Initial Validation of a Gas-Granular Flow Solver Using a Subscale, Reduced Pressure Plume Surface Interaction Ground Test

With NASA’s goal to land the next humans on the lunar surface in the next few years, it is vitally important to have a better understanding of the plume surface interaction (PSI) between the landing vehicles and the lunar regolith. The Fluid Dynamics Branch at NASA/MSFC has previously used the gas-granular flow solver Loci/GGFS to qualitatively predict crater formation due to PSI effects in a lunar (near vacuum) ambient environment. In this paper, validation of Loci/GGFS crater width and depth predictions in ambient near-lunar conditions are provided using experimental data collected at MSFC during the Physics-Focused Ground Test 1 (PFGT-1) campaign in 2022. To observe sensitivity to soil models, simulations were conducted with both monodisperse glass bead (MGB) and BP-1 lunar regolith simulant soil models in Loci/GGFS. Crater depth and width comparisons are made with PFGT-1 Run 56, which used BP-1 soil. The Loci/GGFS BP-1 soil model performed slightly better with a mean predicted crater depth within 10% of the experiment. Both soil models predicted crater width within 10%. Cratering occurred more quickly with the MGB soil model. Mesh and spatial order sensitivity are also examined for the BP-1 soil model.

Validation↗
NASA NTRS2019

Deriving High-Resolution Reservoir Bathymetry from ICESat-2 Prototype Photon-Counting Lidar and Landsat Imagery

Knowledge of reservoir bathymetry is essential for many studies on terrestrial hydrological and biogeochemical processes. However, there are currently no cost-effective approaches to derive reservoir bathymetry at the global scale. This study explores the potential of generating high-resolution global bathymetry using elevation data collected by the 532-nm Advanced Topographic Laser Altimeter System (ATLAS) onboard the Ice, Cloud, and Land Elevation Satellite (ICESat-2). The novel algorithm was developed and tested using the ICESat-2 airborne prototype, the Multiple Altimeter Beam Experimental Lidar (MABEL), with Landsat-based water classifications (from 1982 to 2017). MABEL photon elevations were paired with Landsat water occurrence percentiles to establish the elevation-area (E-A) relationship, which in turn was applied to the percentile image to obtain partial bathymetry over the historic dynamic range of reservoir area. The bathymetry for the central area was projected to achieve the full bathymetry. The bathymetry image was then embedded onto the digital elevation model (DEM). Results were validated over Lake Mead against survey data. Results over four transects show coefficient of determination (R²) values from 0.82 to 0.99 and root-mean-square error (RMSE) values from 1.18 to 2.36 m. In addition, the E-A and elevation-storage (E-S) curves have RMSEs of 1.56 m and 0.08 km³, respectively. Over the entire dynamic reservoir area, the derived bathymetry agrees very well with independent survey data, except for within the highest and lowest percentile bands. With abundant overpassing tracks and high spatial resolution, the newly launched ICESat-2 should enable the derivation of bathymetry over an unprecedented number of reservoirs.

Yao Li↗