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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 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Modeling and observations of North Atlantic cyclones: Implications for U.S. Offshore wind energy

To meet the Biden-Harris administration's goal of deploying 30 GW of offshore wind power by 2030 and 110 GW by 2050, expansion of wind energy into U.S. territorial waters prone to tropical cyclones (TCs) and extratropical cyclones (ETCs) is essential. This requires a deeper understanding of cyclone-related risks and the development of robust, resilient offshore wind energy systems. Here, this paper provides a comprehensive review of state-of-the-science measurement and modeling capabilities for studying TCs and ETCs, and their impacts across various spatial and temporal scales. We explore measurement capabilities for environments influenced by TCs and ETCs, including near-surface and vertical profiles of critical variables that characterize these cyclones. The capabilities and limitations of Earth system and mesoscale models are assessed for their effectiveness in capturing atmosphere–ocean–wave interactions that influence TC/ETC-induced risks under a changing climate. Additionally, we discuss microscale modeling capabilities designed to bridge scale gaps from the weather scale (a few kilometers) to the turbine scale (dozens to a few meters). We also review machine learning (ML)-based, data-driven models for simulating TC/ETC events at both weather and wind turbine scales. Special attention is given to extreme metocean conditions like extreme wind gusts, rapid wind direction changes, and high waves, which pose threats to offshore wind energy infrastructure. Finally, the paper outlines the research challenges and future directions needed to enhance the resilience and design of next-generation offshore wind turbines against extreme weather conditions.

17 WIND ENERGY↗
DOE OSTI2015

Magnetic upflow events in the quiet-sun photosphere. I. Observations

Rapid magnetic upflows in the quiet-Sun photosphere were recently uncovered from both Sunrise/IMaX and Hinode/SOT observations. Here, we study magnetic upflow events (MUEs) from high-quality, high- (spatial, temporal, and spectral) resolution, and full Stokes observations in four photospheric magnetically sensitive Fe i lines centered at 5250.21, 6173.34, 6301.51, and 6302.50 Å acquired with the Swedish Solar Telescope (SST)/CRISP. We detect MUEs by subtracting in-line Stokes V signals from those in the far blue wing whose signal-to-noise ratio (S/N) ⩾7. We find a larger number of MUEs at any given time (2.0×10{sup −2} arcsec{sup −2}), larger by one to two orders of magnitude, than previously reported. The MUEs appear to fall into four classes presenting different shapes of Stokes V profiles with (I) asymmetric double lobes, (II) single lobes, (III) double-humped (two same-polarity lobes), and (IV) three lobes (an extra blueshifted bump in addition to double lobes), of which less than half are single-lobed. We also find that MUEs are almost equally distributed in network and internetwork areas and they appear in the interior or at the edge of granules in both regions. Distributions of physical properties, except for horizontal velocity, of the MUEs (namely, Stokes V signal, size, line-of-sight velocity, and lifetime) are almost identical for the different spectral lines in our data. A bisector analysis of our spectrally resolved observations shows that these events host modest upflows and do not show a direct indication of the presence of supersonic upflows reported earlier. Our findings reveal that the numbers, types (classes), and properties determined for MUEs can strongly depend on the detection techniques used and the properties of the employed data, namely, S/Ns, resolutions, and wavelengths.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Impact of the Annealing Temperature on the Local Se Distribution and Optical Properties in CdSexTe1-x Solar Cells by Multimodal X-ray Microscopy

The introduction of Se in CdTe solar-cell absorbers has led to multiple beneficial effects in the devices, including an increased short-circuit current and an extended charge-carrier lifetime. A critical manufacturing step of CdSexTe1-x solar cells is CdCl2 annealing at high temperatures, during which Se diffuses through the absorber layer. Understanding the local Se distribution in the absorber and its impact on optical properties of the material is key for the further development of this thin-film solar cell technology. In a multimodal x-ray scanning microscopy approach, we investigated the impact of the annealing temperature of CdSexTe1-x solar cells on the Se distribution and on optical characteristics of the material. For this purpose, we exploited an upgraded x-ray excited optical luminescence (XEOL) detection unit that enables simultaneous spectrally and temporally resolved XEOL mapping at synchrotron facilities that are ideal for studying thin-film solar-cell materials with hard x-rays featuring high penetration depth and lateral resolution.

14 SOLAR ENERGY↗
DOE OSTI2016

In situ diagnostics of the crystal-growth process through neutron imaging: application to scintillators

Neutrons are known to be unique probes in situations where other types of radiation fail to penetrate samples and their surrounding structures. In this paper it is demonstrated how thermal and cold neutron radiography can provide time-resolved imaging of materials while they are being processed ( e.g. while growing single crystals). The processing equipment, in this case furnaces, and the scintillator materials are opaque to conventional X-ray interrogation techniques. The distribution of the europium activator within a BaBrCl:Eu scintillator (0.1 and 0.5% nominal doping concentrations per mole) is studied in situ during the melting and solidification processes with a temporal resolution of 5–7 s. The strong tendency of the Eu dopant to segregate during the solidification process is observed in repeated cycles, with Eu forming clusters on multiple length scales (only for clusters larger than ~50 µm, as limited by the resolution of the present experiments). It is also demonstrated that the dopant concentration can be quantified even for very low concentration levels (~0.1%) in 10 mm thick samples. The interface between the solid and liquid phases can also be imaged, provided there is a sufficient change in concentration of one of the elements with a sufficient neutron attenuation cross section. Tomographic imaging of the BaBrCl:0.1%Eu sample reveals a strong correlation between crystal fractures and Eu-deficient clusters. The results of these experiments demonstrate the unique capabilities of neutron imaging for in situ diagnostics and the optimization of crystal-growth procedures.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Investigation of deep levels in CdZnTeSe crystal and their effect on the internal electric field of CdZnTeSe gamma-ray detector

A study of deep levels in CdZnTeSe radiationdetection materials is presented. The approach relies on electrical methods that combine time and temperature evolution of the electric field and electric current after switching on the bias voltage. Two optical methods were also applied to study the deep levels. The first method utilizes the temperature and temporal analysis of the electric-field evolution after switching off an additional light illuminating the sample at a wavelength of 940 nm. The second method involved measuring of the electric-field spectral dependence during near infrared illumination. The results are compared with those obtained with high-quality CdZnTe detector-grade material. We conclude that the introduction of Se into the lattice leads to a shift of the second ionization level of the Cd vacancy towards the conduction band, as predicted recently by first-principles calculations based on screened hybrid functionals.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Mutually promoting or constraining? Disentangling the superimposed effect of velocity and illuminance on fish motion in low-velocity flows with a novel metric

Global climate change, species invasion, and human activities such as the construction of hydraulic facilities are contributing to the worldwide degradation of fish stocks. As a pivotal environmental factor that affects fish migration and population distribution, low-velocity flow has not drawn enough attention despite its extensive presence in various ecoregions. Herein, to understand the behavioural profiles of fish in low-velocity flow, we examined the motility and swimming performance of two representative cyprinids, grass carp (GC, Ctenopharyngodon idella) and silver carp (SC, Hypophthalmichthys molitrix), under the combined effect of different flow velocities and illuminance ranges. The two species were exposed to two flow velocities (0.15 and 0.25 m/s) and three illuminance ranges (100.0 – 0.9 lx, 300.0 – 2.5 lx, and 700.0 – 4.9 lx). A novel behavioural metric, composed of light preference, cruising swimming speed, rheotaxis index (RI), swimming stability (SS), and the probability of moving forwards/backwards over a certain distance (PM f -0.1 and PM b -0.1), was developed to depict the motion strategy of fish fully. By investigating the individual distribution of the fish in light gradient, we confirmed the scototaxis of GC and found the oscillating light preference in SC that changed from 84.4 – 10.2 lx to 6.0 – 2.1 lx and disappeared with increasing illuminance. At the given velocities, the RI and SS increased in both species with a faster flow, and SC was more forward-prone and stable than GC. Despite its fluctuating light preference, the higher illuminances heightened the RI and SS in SC; while in GC, higher illuminances inhibited the SS and had no impact on the RI. The results of PM f -0.1 and PM b -0.1 indicated that a higher flow velocity could facilitate temporary upstream swimming in both species, while illuminance could promote the same effect in SC only. Finally, our study proposed possible moving manoeuvres in fine-scale spatio-temporal scenarios such as attraction flow and untraditional passages and provides valuable insights into fish community dynamics, laying the groundwork for alleviating the threat from invasive species and for future fish population recovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

BrickQA: Bridging the Semantic Gap in Building Operations with Dynamic Graph Exploration

While standardized ontologies like the Brick schema address data heterogeneity in Building Automation Systems (BAS), accessing this semantic data remains a challenge as domain experts often lack the expertise to formulate complex SPARQL queries. To bridge this gap, we present BrickQA, a Large Language Model (LLM)-based framework that translates natural language into executable SPARQL queries through structured query decomposition, dynamic schema exploration, and inline validation. BrickQA utilizes an iterative reasoning agent to actively navigate graph topology through dynamic exploration actions without requiring exhaustive context injection or model fine-tuning. This approach effectively mitigates hallucinations, particularly in large-scale building knowledge graphs. Empirical evaluation on BuildingQA, a standardized benchmark, demonstrates that BrickQA significantly outperforms ReAct baselines, delivering a 0.291–0.355 absolute F1 improvement while achieving 3 × –12.7 × higher token cost-efficiency. Beyond these metrics, the framework maintains structural fidelity across heterogeneous buildings and remains resilient to ambiguous queries without requiring site-specific fine-tuning. Furthermore, a case study on operational analytics validates the framework’s capability to handle temporal and aggregation constraints, effectively transforming abstract semantic models into actionable facility management insights.1

Ko, Yun-Dam↗
DOE OSTI2018

Moisture Content of Baled Forest and Urban Woody Biomass during Long-term Open Storage

Abstract. This article describes how the moisture content of baled woody biomass varied during long-term open-air storage under conditions in the Pacific Northwest region of the United States. Large rectangular bales of forest and urban biomass were produced beginning in August 2015 and periodically until June 2016. Weights were measured approximately monthly until the entire lot of bales was ground into fuel in December 2016. Because it was impractical to non-destructively obtain moisture content samples during the study, final moisture content was measured from the ground material. Estimated temporal moisture contents were back-calculated from the final dry weight and moisture content of bales. All bales dried considerably during the spring and summer months, achieving a minimum moisture content in the early fall of 15 to 29% (wb). Minimum early fall moisture content had no correlation with the initial moisture content at time of baling. The ending moisture content in December 2016 ranged from 44% to 57% (wb), with a mean moisture content of 53% (wb). Ending moisture content had no correlation with initial moisture content at the time of baling, but appeared to be related to the amount of fine versus coarse woody material in the bales. Bales of forest and urban woody biomass proved to be structurally stable during long-term storage to enable handling and final transport to a centralized grinding location. Keywords: Density, Logging, Baling, Bioenergy, Biofuel, Bundling, Forest operations, Forestry, MC, Seasonality, Transport, Woody biomass.

Agriculture↗
DOE OSTI2021

Spatially distributed infection increases viral load in a computational model of SARS-CoV-2 lung infection

A key question in SARS-CoV-2 infection is why viral loads and patient outcomes vary dramatically across individuals. Because spatial-temporal dynamics of viral spread and immune response are challenging to study in vivo, we developed Spatial Immune Model of Coronavirus (SIMCoV), a scalable computational model that simulates hundreds of millions of lung cells, including respiratory epithelial cells and T cells. SIMCoV replicates viral growth dynamics observed in patients and shows how spatially dispersed infections can lead to increased viral loads. The model also shows how the timing and strength of the T cell response can affect viral persistence, oscillations, and control. By incorporating spatial interactions, SIMCoV provides a parsimonious explanation for the dramatically different viral load trajectories among patients by varying only the number of initial sites of infection and the magnitude and timing of the T cell immune response. When the branching airway structure of the lung is explicitly represented, we find that virus spreads faster than in a 2D layer of epithelial cells, but much more slowly than in an undifferentiated 3D grid or in a well-mixed differential equation model. These results illustrate how realistic, spatially explicit computational models can improve understanding of within-host dynamics of SARS-CoV-2 infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The predictive skill of convolutional neural networks models for disease forecasting

In this paper we investigate the utility of one-dimensional convolutional neural network (CNN) models in epidemiological forecasting. Deep learning models, in particular variants of recurrent neural networks (RNNs) have been studied for ILI (Influenza-Like Illness) forecasting, and have achieved a higher forecasting skill compared to conventional models such as ARIMA. In this study, we adapt two neural networks that employ one-dimensional temporal convolutional layers as a primary building block—temporal convolutional networks and simple neural attentive meta-learners—for epidemiological forecasting. We then test them with influenza data from the US collected over 2010-2019. We find that epidemiological forecasting with CNNs is feasible, and their forecasting skill is comparable to, and at times, superior to, plain RNNs. Thus CNNs and RNNs bring the power of nonlinear transformations to purely data-driven epidemiological models, a capability that heretofore has been limited to more elaborate mechanistic/compartmental disease models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Validation of PRONGHORN with the SANA Experiments

In this work, we have re-established the pronghorn’s capability to simulate heat and mass transfer in pebble beds based on porous medium assumption. Although more sophisticated physics models are available, we have limited ourselves to use the simpler Darcy flow model inherited from older versions of this code. Closure correlation, such as friction coefficients in pebble beds and fluid-to-pebble heat transfer coefficients, are reviewed, selected, and implemented in pronghorn code to support simulations of interest to nuclear reactor thermal hydraulics analysis. Numerical verification was performed in form of mesh convergence study using Method of Manufactured Solutions (MMS). For both spatial and temporal integration schemes, expected order of convergence were observed. Validation of this code was performed by comparing simulation results against experimental measurements of the SANA experiment. For helium cases at three power levels, simulations results of pebble temperatures agree with experiment measurements reasonably well. For nitrogen cases, because less accurate thermal-dynamics properties were used, relatively larger discrepancies between simulation results and experiment measurements were found. However, we anticipate that this will be improved when a more accurate nitrogen gas thermal-dynamics properties package is available.

42 ENGINEERING↗
DOE OSTI2019

Imaging Macromolecular Structural Dynamics with Low-Dose, Time-Resolved Transmission Electron Microscopy

All well-established experimental methods for investigating the structure of biological macromolecules have spatial and/or temporal limitations inherent to the technique that limit their applicability to studying macromolecular dynamics. The ability to measure macromolecular dynamics is key to gaining predictive mastery of biological systems. This work demonstrates that sufficient data can be acquired from low-Z soft materials using dynamic transmission electron microscopy (DTEM) to potentially allow measurements of macromolecular motion. While a dynamic measurement of macromolecular motion or structural change requires further effort, it is evident from this work that this is feasible under specific experimental conditions that can be achieved using low-dose, time-resolved transmission electron microscopy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Predictive Skill of Deep Learning Models Trained on Limited Sequence Data

In this report we investigate the utility of one-dimensional convolutional neural network (CNN) models in epidemiological forecasting. Deep learning models, especially variants of recurrent neural networks (RNNs) have been studied for influenza forecasting, and have achieved higher forecasting skill compared to conventional models such as ARIMA models. In this study, we adapt two neural networks that employ one-dimensional temporal convolutional layers as a primary building block temporal convolutional networks and simple neural attentive meta-learner for epidemiological forecasting and test them with influenza data from the US collected over 2010-2019. We find that epidemiological forecasting with CNNs is feasible, and their forecasting skill is comparable to, and at times, superior to, RNNs. Thus CNNs and RNNs bring the power of nonlinear transformations to purely data-driven epidemiological models, a capability that heretofore has been limited to more elaborate mechanistic/compartmental disease models.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

X-Ray Spectroscopic Studies of X-Pinch Plasmas with 3-5 Picosecond Resolution: A Quest for Clear Experimental Evidence for Radiative Collapse in the X-ray Spectra (Final Report)

Dense Z-pinch plasmas produced from current-carrying exploding wires frequently produce very brief (less than 0.1 nanosecond), intense, bursts of soft X-rays from tiny (about 1 micrometer), very hot (10-30 million K) regions of the plasma. This project addresses the physical processes that lead to those tiny, high-energy density plasmas and develops means to measure the conditions just before and during the X-ray bursts. One possible relevant process is radiative collapse, which starts if the power radiated by a dense Z-pinch, proportional to the density-squared, exceeds the resistive heating rate from the current flow, thereby cooling the plasma and enabling the magnetic pinching force to exceed the outward plasma thermal pressure. As the resulting radius reduction further increases the radiation rate, this process produces a runaway magnetic implosion. A competing mechanism is a sausage-like instability that can develop in a Z-pinch plasma at a lower current than is needed to induce radiative collapse. This mechanism can also produce tiny hot spots in the neck regions of the sausage-shaped plasma column. It is also possible that these two mechanisms work together to produce the X-ray emitting hot spots. If radiative collapse does contribute to hot spot formation, it would be terminated when the plasma becomes so dense that the radiation cannot escape, enabling the plasma kinetic pressure to build up and stop the current-driven implosion. This project aims to study the development of the hot spots by means of high temporal and spatial resolution X-ray spectroscopy to determine if there is evidence for the presence of the radiative collapse mechanism. Progress toward this goal is presented. To summarize, during the four-year period 09/15/2017 - 9/14/2021, we have collected necessary spectroscopic data to determine the plasma conditions and continue to do so. We are also now in the process of calibrating diagnostic systems (especially the x-ray streak camera system) and analyzing data to determine plasma conditions as a function of time before, during and after the X-ray burst.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

OH PLIF Visualization of an Optically Accessible Rotating Detonation Combustor

OH PLIF imaging has been successfully conducted within an optically accessible race- track shaped rotating detonation combustor. The OH PLIF images taken in this study corroborate the overall flow field structure reconstructed from previous OH* chemilumi- nescence studies conducted on the same combustor. However, the increased spatial and temporal resolution achieved with the OH PLIF technique allowed for the identification of previously unknown structures present in the detonation wave and its wake. These struc- tures appear as non-uniformities in the OH PLIF signal throughout the channel. Smaller scale structures range from variations in light intensity all the way to seemingly unburnt gas pockets passing through the detonation wave, suggesting non uniform reaction across the propagating detonation wave. Also present in the flow is a relatively large structure, consisting of a dark band surrounded by regions of higher OH intensity that trails the detonation wave. This band is hypothesized to be a result of the effect of secondary waves on the injection system and subsequent fill region composition stratification. Both of these flow structures represent potential avenues for performance loss through off-design mixing and heat release being uncoupled from the detonation wave.

Chacon, Fabian↗
DOE OSTI2022

Landscape Topography and Regional Drought Alters Dust Microbiomes in the Sierra Nevada of California

Dust provides an ecologically significant input of nutrients, especially in slowly eroding ecosystems where chemical weathering intensity limits nutrient inputs from underlying bedrock. In addition to nutrient inputs, incoming dust is a vector for dispersing dust-associated microorganisms. While little is known about dust-microbial dispersal, dust deposits may have transformative effects on ecosystems far from where the dust was emitted. Using molecular analyses, we examined spatiotemporal variation in incoming dust microbiomes along an elevational gradient within the Sierra Nevada of California. We sampled throughout two dry seasons and found that dust microbiomes differed by elevation across two summer dry seasons (2014 and 2015), which corresponded to competing droughts in dust source areas. Dust microbial taxa richness decreased with elevation and was inversely proportional to dust heterogeneity. Likewise, dust phosphorus content increased with elevation. At lower elevations, early season dust microbiomes were more diverse than those found later in the year. The relative abundances of microbial groups shifted during the summer dry season. Furthermore, mutualistic fungal diversity increased with elevation, which may have corresponded with the biogeography of their plant hosts. Although dust fungal pathogen diversity was equivalent across elevations, elevation and sampling month interactions for the relative abundance, diversity, and richness of fungal pathogens suggest that these pathogens differed temporally across elevations, with potential implications for humans and wildlife. This study shows that landscape topography and droughts in source locations may alter the composition and diversity of ecologically relevant dust-associated microorganisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Spatial and temporal variability of turbulence dissipation rate in complex terrain

To improve parameterizations of the turbulence dissipation rate (ϵ) in numerical weather prediction models, the temporal and spatial variability of ϵ must be assessed. In this study, we explore influences on the variability of ϵ at various scales in the Columbia River Gorge during the WFIP2 field experiment between 2015 and 2017. We calculate ϵ from five sonic anemometers all deployed in a ~4 km 2 area as well as from two scanning Doppler lidars and four profiling Doppler lidars, whose locations span a ~300 km wide region. We retrieve ϵ from the sonic anemometers using the second-order structure function method, from the scanning lidars with the azimuth structure function approach, and from the profiling lidars with a novel technique using the variance of the line-of-sight velocity. The turbulence dissipation rate shows large spatial variability, even at the microscale, especially during nighttime stable conditions. Orographic features have a strong impact on the variability of ϵ, with the correlation between ϵ at different stations being highly influenced by terrain. ϵ shows larger values in sites located downwind of complex orographic structures or in wind farm wakes. A clear diurnal cycle in ϵ is found, with daytime convective conditions determining values over an order of magnitude higher than nighttime stable conditions. ϵ also shows a distinct seasonal cycle, with differences greater than an order of magnitude between average ϵ values in summer and winter.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Snowfall and snow accumulation during the MOSAiC winter and spring seasons

Data from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition allowed us to investigate the temporal dynamics of snowfall, snow accumulation and erosion in great detail for almost the whole accumulation season (November 2019 to May 2020). We computed cumulative snow water equivalent (SWE) over the sea ice based on snow depth and density retrievals from a SnowMicroPen and approximately weekly measured snow depths along fixed transect paths. We used the derived SWE from the snow cover to compare with precipitation sensors installed during MOSAiC. The data were also compared with ERA5 reanalysis snowfall rates for the drift track. We found an accumulated snow mass of 38 mm SWE between the end of October 2019 and end of April 2020. The initial SWE over first-year ice relative to second-year ice increased from 50 % to 90 % by end of the investigation period. Further, we found that the Vaisala Present Weather Detector 22, an optical precipitation sensor, and installed on a railing on the top deck of research vessel Polarstern, was least affected by blowing snow and showed good agreements with SWE retrievals along the transect. On the contrary, the OTT Pluvio 2 pluviometer and the OTT Parsivel 2 laser disdrometer were largely affected by wind and blowing snow, leading to too high measured precipitation rates. These are largely reduced when eliminating drifting snow periods in the comparison. ERA5 reveals good timing of the snowfall events and good agreement with ground measurements with an overestimation tendency. Retrieved snowfall from the ship-based K a -band ARM zenith radar shows good agreements with SWE of the snow cover and differences comparable to those of ERA5. Based on the results, we suggest the K a -band radar-derived snowfall as an upper limit and the present weather detector on RV Polarstern as a lower limit of a cumulative snowfall range. Based on these findings, we suggest a cumulative snowfall of 72 to 107 mm and a precipitation mass loss of the snow cover due to erosion and sublimation as between 47 % and 68 %, for the time period between 31 October 2019 and 26 April 2020. Extending this period beyond available snow cover measurements, we suggest a cumulative snowfall of 98–114 mm.

54 ENVIRONMENTAL SCIENCES↗