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All sources NASA NTRS DOE OSTI

DOE OSTI2021

Quantifying Turbine-Level Risk to Golden Eagles Using a High-Fidelity Updraft Model and a Stochastic Behavioral Model

To minimize the effects of wind farms on Golden Eagle (Aquila chrysaetos) populations while enabling sustainable development of renewable energy resources, it is important to understand how eagles interact with atmospheric flows, terrain features, and anthropogenic structures. Models that predict migratory flight paths provide one tool that helps us grasp how the location of wind farms may influence interactions and impacts on migrating Golden Eagles. The current state-of-the-art in predicting migratory flight paths uses a deterministic fluid-flow analogy to predict eagle trajectory using only an orographic updraft potential computed from topographical features. This model does not take into account variables, such as thermal updrafts and time varying atmospheric conditions that are known to influence migratory behavior. In this work, we improve on the model with the objective of developing tools that advance our understanding of how atmospheric flows and terrain features affect migratory eagle behavior and their interactions with wind farms. Specifically, we 1) incorporate both orographic and thermal updraft information in simulating eagle flight paths; 2) incorporate stochasticity into eagle travel patterns to better capture the influence of exogenous factors on, and the inherent stochasticity of eagle behavior; 3) consider spatio-temporal atmospheric data at wind-farm-scale when computing updraft potential; and 4) account for how atmospheric conditions and the direction of migration change seasonally and how these changes affect eagle migratory flight behavior. We tested the model using a 50km by 50km region with 50 m resolution in the western United States. We simulated 900 independent, probabilistic eagle tracks during southerly and northerly migration, assuming eagles solely rely on orographic updrafts. The preliminary results indicate that the inclusion of finer resolution atmospheric data allows for the inclusion of realistic conditions that an eagle experiences. The stochasticity in eagle tracks provides a platform to include uncertainty in eagle decision making and help produce robust eagle presence maps. We will deploy updraft and downdraft velocities computed using a high-fidelity, wind farm scale, computational fluid dynamics solver under development at National Renewable Energy Laboratory. This work is a first step in the development of a predictive and generalizable eagle behavior model at the wind farm scale that does not rely on empirical data collection. Although the current model is intended for migratory eagles, we will extend and refine this model to inform the development of additional behavioral modes, including resident eagle behavior. This modeling approach improves our ability to understand eagle use of the landscape at a fine scale, and it is our hope that this work will ultimately help advance strategies that minimize the impact of wind development on Golden Eagle populations.

49 EE - Wind and Water Power Program - Wind (EE-4W↗

NASA NTRS2009

Carbon Emissions from Deforestation in the Brazilian Amazon Region

A simulation model based on satellite observations of monthly vegetation greenness from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate monthly carbon fluxes in terrestrial ecosystems of Brazilian Amazon and Cerrado regions over the period 2000-2002. The NASA-CASA (Carnegie Ames Stanford Approach) model estimates of annual forest production were used for the first time as the basis to generate a prediction for the standing pool of carbon in above-ground biomass (AGB; gC/sq m) for forested areas of the Brazilian Amazon region. Plot-level measurements of the residence time of carbon in wood in Amazon forest from Malhi et al. (2006) were interpolated by inverse distance weighting algorithms and used with CASA to generate a new regional map of AGB. Data from the Brazilian PRODES (Estimativa do Desflorestamento da Amazonia) project were used to map deforested areas. Results show that net primary production (NPP) sinks for carbon varied between 4.25 Pg C/yr (1 Pg=10(exp 15)g) and 4.34 Pg C for the region and were highest across the eastern and northern Amazon areas, whereas deforestation sources of CO2 flux from decomposition of residual woody debris were higher and less seasonal in the central Amazon than in the eastern and southern areas. Increased woody debris from past deforestation events was predicted to alter the net ecosystem carbon balance of the Amazon region to generate annual CO2 source fluxes at least two times higher than previously predicted by CASA modeling studies. Variations in climate, land cover, and forest burning were predicted to release carbon at rates of 0.5 to 1 Pg C/yr from the Brazilian Amazon. When direct deforestation emissions of CO2 from forest burning of between 0.2 and 0.6 Pg C/yr in the Legal Amazon are overlooked in regional budgets, the year-to-year variations in this net biome flux may appear to be large, whereas our model results implies net biome fluxes had actually been relatively consistent from year to year during the period 2000-2002. This is the first study to use MODIS data to model all carbon pools (wood, leaf, root) dynamically in simulations of Amazon forest deforestation from clearing and burning of all kinds.

Potter, C.↗

NASA NTRS1990

Velocity mapping and models of the elliptical galaxies NGC 720, NGC 1052, and NGC 4697

CCD surface photometry and extensive long-slit spectroscopy are used to construct detailed models of the flattened ellipticals NGC 720, 1052, and 4697. The models are combined with the Jeans equations to yield predicted fields of line-of-sight velocity dispersion and streaming velocity. By comparing these fields with observed velocities, it is concluded that none of these systems can have isotropic velocity dispersion tensors, and diminishing the assumed inclination of any given galaxy tends to decrease the line-of-sight velocity dispersion and, counterintuitively, to increase the line-of-sight rotation speeds. The ratio of the line-of-sight velocity dispersion along the minor axis to that along the major axis is found to be a sensitive diagnostic of the importance of a third integral for the galaxy's structure.

Binney, J. J.↗

NASA NTRSDate not supplied

Formational History and Geomorphic Preservation of Sea Level Highstands Over the Last 150 ky Near Cape Canaveral, Florida, USA

Cape Canaveral, Florida, is perhaps one of the most important stretches of coastline in the United States of America (USA) due to its critical strategic role in the pursuit of space exploration and as the locus of advanced technological innovation. Due to its geographical setting, the entirety of Cape Canaveral, including its infrastructure, facilities, and important natural habitats (e.g., wetlands, estuaries and dunes) is vulnerable to coastal hazards such as continued sea level rise, storm surges, erosion and flooding. As such, accurate sea level characterization and coastal resiliency predictions are essential to promoting long-term coastal planning and sustainability in the area. This study aims to better understand the temporal and spatial evolution of this area with the purpose of more accurately documenting historical sea level fluctuations and calibrating more localized projections at this site. The Cape Canaveral coastline is situated on a passive margin mostly affected by oceanic (sea level change and wave impact) and atmospheric (aeolian) alteration. This sector is part of the east Florida coast microtidal (1.2 m) setting and low wave energy (1.2-1.6 m and 6.1-8.2 sec for average significant waves) regime and is defined by a well delineated set of beach ridge or cape systems. While the name “Cape Canaveral” is often used as a generic term to describe the geographic area, it is actually an amalgamation or complex of multiple preserved capes. The preserved Cape Canaveral beach ridge plain has largely documented the paleo-sea level highstand history over the last 150 ky. High-resolution mapping of these beach ridges is completed using GPS, LiDAR, aerial, as well as satellite imagery. In order to reconstruct the formational history of the Cape Kennedy Complex and the preserved record of sea level highstands, these detailed geomorphological observations are integrated with OSL and C14 dating techniques. The chronological framework delineated by the OSL dates coupled with detailed geomorphological mapping allows for the creation of high-resolution calibrated site-specific sea level curves that reflect the local environmental and geological conditions. This refinement has the potential to improve the understanding of past sea level variability which is crucial for predicting future trends and assessing the impacts on coastal regions such as Cape Canaveral.

geomorphology↗

DOE OSTI2024

Anomalous localization in a kicked quasicrystal

Abstract Quantum transport can distinguish between dynamical phases of matter. For instance, ballistic propagation characterizes the absence of disorder, whereas in many-body localized phases, particles do not propagate for exponentially long times. Additional possibilities include states of matter exhibiting anomalous transport in which particles propagate with a non-trivial exponent. Here we report the experimental observation of anomalous transport across a broad range of the phase diagram of a kicked quasicrystal. The Hamiltonian of our system has been predicted to exhibit a rich phase diagram, including not only fully localized and fully delocalized phases but also an extended region comprising a nested pattern of localized, delocalized and multifractal states, which gives rise to anomalous transport. Our cold-atom realization is enabled by new Floquet engineering techniques, which expand the accessible phase diagram by five orders of magnitude. Mapping transport properties throughout the phase diagram, we observe disorder-driven re-entrant delocalization and sub-ballistic transport, and we present a theoretical explanation of these phenomena based on eigenstate multifractality.

Physics↗

DOE OSTI2024

A dynamic solvent chamber propagation estimation framework using RNN for warm solvent injection in heterogeneous reservoirs

Warm solvent injection (WSI), injecting low-temperature solvent into formations to reduce the viscosity of heavy oil, is a clean technology for heavy oil production through reducing greenhouse gas emissions and water usage. The success of WSI operation depends on the uniform development and propagation of solvent chambers in reservoirs. However, reservoir heterogeneity stemming from shale barriers plays a detrimental role in the conformance of solvent chamber development and oil production rate. In this work, we developed a novel recurrent neural network (RNN)-based framework with the capability of efficiently tracking and estimating the solvent chamber positions in heterogeneous reservoirs based on only production time-series data. The developed estimation model utilizes the “sequence-to-sequence" mapping methodology to correlate observed production time-series sequence and solvent chamber edge sequence via a long short-term memory (LSTM) algorithm. The trained RNN models exhibit high accuracy, evidenced by the predicted dynamic solvent chamber locations match the corresponding true locations from numerical simulation, with a high coefficient of determination (R 2 ) and a low mean squared error. Specifically, the achieved R 2 values exceed 0.98 on both the training and testing data. The developed RNN-based workflow was tested via several cases from both regularly- and irregularly-shaped shale barriers, and the results were promising. The predicted solvent chambers showed strong agreement with those obtained from numerical simulations. The major benefits of this workflow include reducing computational time and saving overall monitoring and tracking costs for conventional techniques. In conclusion, the present work would provide a good demonstration of the capability of practical integration of machine learning methods in solving engineering problems.

58 GEOSCIENCES↗

DOE OSTI2024

Physics-informed KNN milling stability model with process damping effects

This paper describes a k-nearest neighbors, or KNN, model for milling stability including process damping effects. A physics-based, frequency domain milling stability solution is used to generate the training data, but does not incorporate process damping effects. The data set is then updated using limited tests to capture the process damping behavior. A “stair step” approach is used to select the test points, where a first spindle speed-axial depth combination is selected based on the physics-based stability map, subsequent tests are defined using the previous test result, and data points are updated by knowledge of process damping behavior and the test results. Furthermore, the KNN modeling approach demonstrates the ability to predict both stable and unstable results, including process damping behavior.

42 ENGINEERING↗

DOE OSTI2025

Unveiling X-ray absorption signatures of boron nitride via first-principles simulation and machine learning

Boron nitride (BN) allotropes hold great promise in many advanced applications ranging from optical and photonic devices to energy storage and battery systems to tribological components. The diverse functionalities of this material stem from BN’s highly tunable structural and electronic properties, which are governed by the versatile boron–nitrogen bonding configurations. Exploring the structural landscape of BN can unveil novel structures possessing unique properties suited for specific applications, therefore accelerating the design of next-generation advanced functional materials. In this work, we leverage boron K-edge X-ray absorption spectroscopy (XAS) as an effective probe for local structural features and chemical environments. A total of 210 BN crystal structures are generated via analogies to the extensive array of carbon allotropes, and XAS is simulated for each unique local motif within the resulting collection of structures. A mapping between structural features and spectral signatures was established by synergizing first-principle simulations with data-driven based post-analysis approaches. Specifically, we developed a neural network model that can satisfactorily predict spectra line shapes from local structural descriptors. Toward automatic spectroscopic interpretation of any new BN structures, supervised machine learning models, trained on this structure–spectrum dataset, can accurately infer local coordination environments from simulated XAS, highlighting the strength of this unique approach of combining high-fidelity first-principles simulation and machine-learning to accelerate target design of novel BN materials via rational understanding of local structure-spectrum correlations.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Quantitative agreement between dynamical rocking curves in ultrafast electron diffraction for x-ray lasers

Electron diffraction through a thin patterned silicon membrane can be used to create complex spatial modulations in electron distributions. By precisely varying parameters such as crystallographic orientation and wafer thickness, the intensity of reflections in the diffraction plane can be controlled and by placing an aperture to block all but one spot, we can form an image with different parts of the patterned membrane, as is done for bright-field imaging in microscopy. The patterned electron beams can then be used to control phase and amplitude of subsequent x-ray emission, enabling novel coherent x-ray methods. Furthermore, the electrons themselves can also be used for femtosecond time resolved diffraction and microscopy. As a first step toward patterned beams, we demonstrate experimentally and through simulation the ability to accurately predict and control diffraction spot intensities. We simulate MeV transmission electron diffraction patterns using the multislice method for various crystallographic orientations of a single crystal Si(001) membrane near beam normal. The resulting intensity maps of the Bragg reflections are compared to experimental results obtained at the Accelerator Structure Test Area Ultrafast Electron Diffraction (ASTA UED) facility at SLAC. Furthermore, the fraction of inelastic and elastic scattering of the initial charge is estimated along with the absorption of the membrane to determine the contrast that would be seen in a patterned version of the Si(001) membrane.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Alfvénic modes excited by the kink instability in PHASMA

Magnetic flux ropes have been successfully created with plasma guns in the newly commissioned PHAse Space MApping (PHASMA) experiment. The flux ropes exhibit the expected m = 1 kink instability. The observed threshold current for the onset of this kink instability is half of the Kruskal–Shafranov current limit, consistent with predictions for the non-line tied boundary condition of PHASMA. The helicity, paramagnetism, and growth rate of the observed magnetic fluctuations are also consistent with kink instability predictions. The observed fluctuation frequency appears to be a superposition of a real frequency due to a Doppler shift of the kink mode arising from plasma flow (~2kHz) and a contribution from a wave mode (~5 kHz). The dispersion of the wave mode is consistent with an Alfvén wave. Distinct from most previ-ous laboratory studies of flux ropes, the working gas in PHASMA is argon. Thus, the ion cyclotron frequency in PHASMA is quite low and the frequency of the Alfvénic mode plateaus at ~0.5 of the ion gyro frequency with increasing background magnetic field strength.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Modeling bicarbonate formation in an alkaline solution with multi-level quantum mechanics/molecular dynamics simulations

Understanding carbonate speciation and how it may be modulated is essential for the advancement of carbon dioxide (CO 2 ) capture and storage technologies, which often rely on the transformation of CO 2 into carbonate, e.g. via the formation of carbonate minerals. To date, few atomic-level, quantum-mechanics-based simulations have been carried out to characterize how carbonic acid (H 2 CO 3 ) and bicarbonate ($HCO^{-}_{3}$) form in aqueous solution, and how pH affects this process. Recently, Martirez and Carter utilized rare-event sampling density functional theory molecular dynamics simulations in combination with multi-level embedded correlated wavefunction theory, thus accounting for both solvent dynamics and electron correlation accurately, to elucidate the mechanism of H 2 CO 3 formation in neutral solution (J. Am. Chem. Soc., 145, 12561, 2023). Here, we perform a complementary simulation using the same method to map out the energetics of $HCO^{-}_{3}$ formation from dissolved CO 2 in basic solution. We find that, as in H 2 CO 3 formation, including water dynamics is important to obtain an accurate prediction of the energetics for the aforementioned reaction. Furthermore, only with MD did we identify the correct pathway for the reaction, in which water – not hydroxide – acts as the initial nucleophile and only at the transition state does it lose a proton.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2023

The first two chromosome‐scale genome assemblies of American hazelnut enable comparative genomic analysis of the genus Corylus

Summary The native, perennial shrub American hazelnut ( Corylus americana ) is cultivated in the Midwestern United States for its significant ecological benefits, as well as its high‐value nut crop. Implementation of modern breeding methods and quantitative genetic analyses of C. americana requires high‐quality reference genomes, a resource that is currently lacking. We therefore developed the first chromosome‐scale assemblies for this species using the accessions ‘Rush’ and ‘Winkler’. Genomes were assembled using HiFi PacBio reads and Arima Hi‐C data, and Oxford Nanopore reads and a high‐density genetic map were used to perform error correction. N50 scores are 31.9 Mb and 35.3 Mb, with 90.2% and 97.1% of the total genome assembled into the 11 pseudomolecules, for ‘Rush’ and ‘Winkler’, respectively. Gene prediction was performed using custom RNAseq libraries and protein homology data. ‘Rush’ has a BUSCO score of 99.0 for its assembly and 99.0 for its annotation, while ‘Winkler’ had corresponding scores of 96.9 and 96.5, indicating high‐quality assemblies. These two independent assemblies enable unbiased assessment of structural variation within C. americana , as well as patterns of syntenic relationships across the Corylus genus. Furthermore, we identified high‐density SNP marker sets from genotyping‐by‐sequencing data using 1343 C. americana , C. avellana and C. americana × C. avellana hybrids, in order to assess population structure in natural and breeding populations. Finally, the transcriptomes of these assemblies, as well as several other recently published Corylus genomes, were utilized to perform phylogenetic analysis of sporophytic self‐incompatibility (SSI) in hazelnut, providing evidence of unique molecular pathways governing self‐incompatibility in Corylus .

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Software for High-Resolution Flood Mapping With Sentinel-1 and Sentinel-2 via Misalignment-Robust Cross-Sensor Learning and Generative Despeckling

SF-26-078 This software provides a high-level workflow for satellite-based flood and surface-water mapping using Sentinel-1 SAR and Sentinel-2 multispectral imagery. It supports preparation of remote-sensing data, training and evaluation of deep-learning models, and generation of high-resolution water extent predictions, including methods to improve robustness to SAR speckle noise and cross-sensor image misalignment.

Feinstein, Jeremy [Argonne National Laboratory (AN↗

DOE OSTI2020

Optimization of Window Positions for Wind-Driven Natural Ventilation Performance

This paper optimizes opening positions on building facades to maximize the natural ventilation’s potential for ventilation and cooling purposes. The paper demonstrates how to apply computational fluid dynamics (CFD) simulation results to architectural design processes, and how the CFD-driven decisions impact ventilation and cooling: (1) background: A CFD helps predict the natural ventilation’s potential, the integration of CFD results into design decision-making has not been actively practiced; (2) methods: Pressure data on building facades were obtained from CFD simulations and mapped into the 3D modeling environment, which were then used to identify optimal positions of two openings of a zone. The effect of the selected opening positions was validated with building energy simulations; (3) results: The cross-comparison study of different window positions based on different geographical locations quantified the impact on natural ventilation effectiveness; and (4) conclusions: The optimized window position was shown to be effective, and some optimal solutions contradicted the typical cross-ventilation strategy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1975

Skylab altimeter observations over terrain

The author has identified the following significant results. Data obtained by Skylab radar altimeter (S193) over the continental U.S.A. for pass 1 of SL-3 were analyzed to relate radar return signal parameters such as range, power, and waveform to ground track terrain features. The altimeter, which was originally designed for ocean observations, performed predictably well over terrain with moderate to low relief. The maximum return from more complex areas corresponded usually to the lower flatter regions within the seven kilometer diameter footprint. Altimeter measured heights correlated with map topography with an rms deviation of + or - 30 m for terrain topography with large height dispersion (passes 1 and 28) and + or - 5 m for slowly varying terrain (passes 16, 17, and 18). Analysis of the waveform and statistical characteristics of the individual signals indicated that larger signal power was usually related to dominantly specular reflections from patches 100 m or larger. Results established the capability of a spacecraft altimeter system to observe characteristic radar signatures for different types of terrain within the bandwidth restrictions of the AGC and range tracker loops.

Shapiro, A.↗

NASA NTRS1975

M-DAS: System for multispectral data analysis

M-DAS is a ground data processing system designed for analysis of multispectral data. M-DAS operates on multispectral data from LANDSAT, S-192, M2S and other sources in CCT form. Interactive training by operator-investigators using a variable cursor on a color display was used to derive optimum processing coefficients and data on cluster separability. An advanced multivariate normal-maximum likelihood processing algorithm was used to produce output in various formats: color-coded film images, geometrically corrected map overlays, moving displays of scene sections, coverage tabulations and categorized CCTs. The analysis procedure for M-DAS involves three phases: (1) screening and training, (2) analysis of training data to compute performance predictions and processing coefficients, and (3) processing of multichannel input data into categorized results. Typical M-DAS applications involve iteration between each of these phases. A series of photographs of the M-DAS display are used to illustrate M-DAS operation.

Johnson, R. H.↗

NASA NTRS1982

Effects of heat loss, preferential diffusion, and flame stretch on flame-front instability and extinction of propane/air mixtures

Flame configurations, flame-front cellular instability, and extinction of propane/air mixtures in the stagnation-point flow are experimentally studied for their dependence on downstream heat loss, preferential diffusion, and flame stretch. Boundaries for lean- and rich-limit extinction, stabilization of corrugated flames, and local extinction caused by sharp curvatures are mapped for varying propane concentrations and freestream velocities. Flame location and temperature at extinction are determined as functions of stagnation surface temperature, extent of preheating, propane concentration, and freestream velocity. Results substantiate the theoretical predictions of the different extinction modes for lean and rich flames in the absence of downstream heat loss, and yield useful insight on the extinction characteristics when finite downstream heat loss does exist. It is further shown that flame-front instability occurs only for rich mixtures in accordance with preferential diffusion considerations, and that flame stretch has a stabilizing effect such that flame-front instability is completely inhibited before the onset of extinction.

Ishizuka, S.↗

NASA NTRS1986

Review and evaluation of recent developments in melic inlet dynamic flow distortion prediction and computer program documentation and user's manual estimating maximum instantaneous inlet flow distortion from steady-state total pressure measurements with full, limited, or no dynamic data

A review of the Melick method of inlet flow dynamic distortion prediction by statistical means is provided. These developments include the general Melick approach with full dynamic measurements, a limited dynamic measurement approach, and a turbulence modelling approach which requires no dynamic rms pressure fluctuation measurements. These modifications are evaluated by comparing predicted and measured peak instantaneous distortion levels from provisional inlet data sets. A nonlinear mean-line following vortex model is proposed and evaluated as a potential criterion for improving the peak instantaneous distortion map generated from the conventional linear vortex of the Melick method. The model is simplified to a series of linear vortex segments which lay along the mean line. Maps generated with this new approach are compared with conventionally generated maps, as well as measured peak instantaneous maps. Inlet data sets include subsonic, transonic, and supersonic inlets under various flight conditions.

Schweikhard, W. G.↗