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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Mapping Pine Plantations in the Southeastern U.S. Using Structural, Spectral, and Temporal Remote Sensing Data

The southeastern U.S. produces the most industrial roundwood in the U.S. each year, largely from commercial pine plantations. The extent of plantation forests and management dynamics can be difficult to ascertain from periodic forest inventories, yet short-rotation tree plantations also present challenges for remote sensing. Here, we integrated spectral, temporal, and structural information from airborne and satellite platforms to distinguish pine plantations from natural forests and evaluate the contribution from planted forests to regional forest coverin the southeastern U.S. Within flight lines from NASA Goddard's Lidar, Hyperspectral, and Thermal (G-LiHT) Airborne Imager, lidar metrics of forest structure had the highest overall accuracy for pine plantations among single-source classifications (90%), but the combination of spectral and temporal metrics from Landsat generated comparable accuracy (91%). Combined structural, temporal, and spectral information from G-LiHT and Landsat had the highest accuracy for plantations (92%) and natural forests (88%). At a regional scale, classifications using Landsat spectral and temporal metrics had between 74 and 82% mean class accuracy for plantations.Regionally, plantations accounted for 28% of forest cover in the southeastern U.S., a result similar to plot-based estimates, albeit with greater spatial detail. Regional maps of plantation forests differed from existing map products, including the National Land Cover Database. Combining plantation extent in 2011 with Landsat based forest change data identified strong regional gradients in plantation dynamics since 1985, with distinct spatial patterns of rotation age (east-west) and plantation expansion (interior). Our analysis demonstrates the potential to improve the characterization of dynamic land cover classes, including economically important timber plantations, by integrating diverse remote sensing datasets. Critically, multi-source remote sensing provides an approach to leverage periodic forest inventory data for annual monitoring of managed forest landscapes.

Fagan, M. E.↗
DOE OSTI2024

Error and Correction Analysis for the FFA@CEBAF Energy Upgrade

An energy upgrade design for the Continuous Electron Beam Accelerator Facility (CEBAF) is under development, using fixed field alternating gradient (FFA) return arcs to recirculate electron beam up to an additional five times through the accelerating structures at CEBAF. A necessary component of any large accelerator is a beam steering and optical correction system. Small environmental changes and system errors can lower beam quality or even shut down the machine; and in pursuit of the scientific mission of JLab, high quality electron beams must be delivered to the experimental halls on a predictable schedule. Correction in the novel FFA arcs of the current upgrade design is complicated by several factors. These complexities inform the choice of correction algorithm structure and parameter values. A baseline algorithm in addition to diagnostic and correction hardware configuration is presented. The effect of this correction protocol is shown with respect to estimated errors, and several possible extensions of the algorithm are discussed. This work presents an important proof of concept for the FFA@CEBAF design effort, and provides a functional correction strategy which may be simply adjusted and optimized for future design changes.

Coxe, Alex [Old Dominion Univ., Norfolk, VA (Unite↗
DOE OSTI2025

Explainable artificial intelligence relates perovskite luminescence images to current-voltage metrics

As the demand for low-cost, high-efficiency solar energy technologies grows, metal halide perovskite (MHP) solar cells have emerged as a promising candidate for next-generation photovoltaics due to their high power conversion efficiencies. However, their poor durability and issues with manufacturing consistency remain significant barriers to commercialization. In this work, we develop deep learning models to support materials characterization and provide insight into features and processes influencing performance. The models are trained using transfer learning of a pretrained model to predict relevant current-voltage (IV) metrics based on different combinations of input electroluminescence (EL) and photoluminescence (PL) images of MHP devices. We examine which image types are most informative in accurately predicting different IV metrics. Additionally, we use explainable artificial intelligence (XAI) techniques to provide insights into specific spatial features in the devices that drive differences in performance. We find that stabilized luminescence images (e.g. those collected after biasing the devices for at least 1 min) are better for predicting metrics of open-circuit voltage (by PL) and short-circuit current (by PL with EL), but that predicting fill factor and overall power output may use the time-evolution of EL images. Based on attribution masks generated by integrated gradients for each device performance metric, we further suggest different loss mechanisms associated with categories of large and small spatial defects. Overall, this case study highlights the potential applicability of XAI methodology for streamlining MHP device analysis and accelerating detailed understanding of the relationships between spatial defects and impacts on performance.

14 SOLAR ENERGY↗
DOE OSTI2020

Autonomous adaptive data acquisition for scanning hyperspectral imaging

Non-invasive and label-free spectral microscopy (spectromicroscopy) techniques can provide quantitative biochemical information complementary to genomic sequencing, transcriptomic profiling, and proteomic analyses. However, spectromicroscopy techniques generate high-dimensional data; acquisition of a single spectral image can range from tens of minutes to hours, depending on the desired spatial resolution and the image size. This substantially limits the timescales of observable transient biological processes. To address this challenge and move spectromicroscopy towards efficient real-time spatiochemical imaging, we developed a grid-less autonomous adaptive sampling method. Our method substantially decreases image acquisition time while increasing sampling density in regions of steeper physico-chemical gradients. When implemented with scanning Fourier Transform infrared spectromicroscopy experiments, this grid-less adaptive sampling approach outperformed standard uniform grid sampling in a two-component chemical model system and in a complex biological sample, Caenorhabditis elegans. We quantitatively and qualitatively assess the efficiency of data acquisition using performance metrics and multivariate infrared spectral analysis, respectively.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Electronic transport, thermal transport, thermal expansion, and magnetization in the strongly correlated metal LaNi⁢O 3

Perovskite structured LaNiO 3 is a strongly correlated metal with intriguing thermal and magnetic properties. The volume dependence of calculated and measured physical properties can add additional critical information to develop a more in-depth understanding of this strongly correlated phenomenon. Taking advantage of recent single crystal LaNiO 3 growth using the floating-zone method, we have measured the thermal expansion, the magnetostriction, and the pressure dependence of the magnetic susceptibility, which then allows derivation of the Grüneisen parameters γ e = $\frac{dlnN(E_F)}{d lnV}$, γ χ = $\frac{dlnχ}{d lnV}$, as well as of electric and thermal transport properties. We simulate the volume dependence of structural and magnetic properties using Density Functional Theory calculations at the Generalized Gradient Approximation level. A large discrepancy between experimental values and calculated ones suggests that strong correlations are likely to be dynamic in nature. This study also provides a side-by-side comparison of measurements in single crystal and polycrystalline samples of LaNiO 3 to elucidate intrinsic materials properties. A broad hump at high temperatures in the temperature dependence of magnetization found in the single crystal sample of LaNiO 3 has been rationalized by a model that includes the influence of electron correlations on the Landau diamagnetism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Learning with Adaptive Conservativeness for Distributionally Robust Optimization: Incentive Design for Voltage Regulation

Information asymmetry between the Distribution System Operator (DSO) and Distributed Energy Resource Aggregators (DERAs) obstructs designing effective incentives for voltage regulation. To capture this effect, we employ a Stackelberg game-theoretic framework, where the DSO seeks to overcome the information asymmetry and refine its incentive strategies by learning from DERA behavior over multiple iterations. We introduce a model-based online learning algorithm for the DSO, aimed at inferring the relationship between incentives and DERA responses. Given the uncertain nature of these responses, we also propose a distributionally robust incentive design model to control the probability of voltage regulation failure and then reformulate it into a convex problem. This model allows the DSO to periodically revise distribution assumptions on uncertain parameters in the decision model of the DERA. Finally, we present a gradient-based method that permits the DSO to adaptively modify its conservativeness level, measured by the size of a Wasserstein metric-based ambiguity set, according to historical voltage regulation performance. The effectiveness of our proposed method is demonstrated through numerical experiments.

adaptation models↗
DOE OSTI2024

UT-GOM2-2 Preliminary Report: Terrebonne Basin Northern Gulf of Mexico, 30 July-28 September 2023

In the summer and fall of 2023, the Gulf of Mexico Deepwater Hydrate Coring Expedition (UT-GOM2-2) drilled, cored, made downhole measurements, and analyzed samples from the seafloor to the base of the gas hydrate stability zone in one location (Site H, WR313) in the Terrebonne basin, deepwater Gulf of Mexico. Analyses of data and samples from the expedition will inform biological, geochemical, and geomechanical models to constrain the role of gas hydrates in the carbon cycle and the potential for gas hydrates as an energy resource. Pressure and conventional cores were collected continuously to a depth of 155.1 meters below the seafloor (mbsf). At deeper depths, cores were taken periodically from hydrate-bearing sands and their bounding muds to a total depth of 861.3 mbsf. 162.6 m of conventional core and 54.8 m of pressure core were obtained. Twelve temperature measurements were made between 27.1 and 144.5 mbsf to determine the geothermal gradient. At the seafloor, more than 4 m of sandy silt of unknown origin was encountered. Beneath this sand, to a depth of ~200 mbsf, the section was composed of interbedded mud and biogenic carbonate ooze. The biogenic ooze correlated to low density and high porosity intervals observed in the previously acquired logging while drilling (LWD) data and as measured. Calcareous nannofossil biostratigraphy constrains the entire record to the Pleistocene (< 0.91 million years) with a pronounced increase in sedimentation rate with depth. Beneath 200 mbsf, the section was predominantly composed of mud with two thicker, hydrate-bearing coarse-grained intervals, which are commonly known as the Blue and Orange sands. The dissolved gas concentration was quantified from pressure cores. In the shallow section, dissolved methane concentration increased below the sulfate-methane transition zone (SMTZ) and reaches saturation (the limit of solubility for methane) at 147 mbsf. Gas expansion was very common in conventional and depressurized pressure (conventionalized) cores below the SMTZ. At deeper depths, the methane concentration within muds bounding the Blue and Orange reservoirs was generally found to be less than saturation. The dissolved and hydrate gas composition is consistent with a microbial source, containing greater than 99.99% methane and only trace concentrations of ethane, propane, and butane. The methane to ethane ratio (C 1 /C 2 ) and the methane to ethane plus propane (C 1 /(C 2 +C 3 )) decrease with depth down to at least 678 mbsf, mainly driven by the increase in ethane with depth. It is unclear if this trend continues through the Orange sand interval. The δ 13 C isotopic signature of methane ranges between -69.9 and -78.5 ‰ Vienna Pee Dee Belemnite (VPDB). Pressure core recovery of all sandy intervals was poor. However, pressure core logs of the Orange sand show intervals of low density and high velocity, which are indicative of high hydrate saturation. One core from within the Orange sand was composed of interbedded graded sandy silt and mud. The sandy silts from this core are composed of mainly quartz and feldspar with some lithics. Most of the recovered pressure core samples are maintained at near in-situ pressure and temperature (within the hydrate stability field) at the University of Texas Pressure Core Center awaiting analysis. In the shallow section, samples will be used to determine the flux of organic carbon through the basin system, find the rate at which that carbon was consumed, and understand the microbial population responsible for these processes. In the deeper section, samples from in and around the hydrate reservoirs will be used to determine the petrophysical properties of the reservoir and bounding seals in these systems.

03 NATURAL GAS↗
NASA NTRS1975

The triggering and subsequent development of a solar flare

High temporal and spatial resolution solar X-ray pictures of a flare at 1827 UT on 5 September 1973 were taken with the S-056 telescope on the Apollo telescope mount. Photographs taken at 9 sec intervals allow detailed information to be obtained about the site of the energy release, as well as about the evolution of the flare itself. Observations suggest that the flare occurred in an entire arcade of loops rather than in any single loop. Sequential brightening of different X-ray features indicates that some excitation moved perpendicular to the magnetic field of the arcade at velocities of 180 to 280 km/sec. The most intense X-ray features were located in places where the magnetic field composing the arcade had a small radius of curvature with horizontal field gradients higher than the surroundings region and where the axis of the arcade changed direction. It was felt that the arcade geometry strongly influenced the propagation of the triggering disturbance, as well as the storage and site of the subsequent deposition of energy. A magnetosonic wave is suggested as the propagating mechanism triggering instabilities that may have existed in the preflare structure.

Vorpahl, J. A.↗
NASA NTRS2010

Boundary Layers, Transitions and Separation

Effects of roughness in boundary layers have to be addressed. Until adverse pressure gradient effects are understood, roughness will not significantly drive design. Mechanisms responsible for separation not understood. Effects on Zero Pressure Gradient boundary layers (shear stress). Effects on separation in pressure gradient (prediction of separation). Effect on scalar transport (heat transfer) not understood. Model for skin friction needed in simulations - first grid point likely to be in buffer layer. Definition of roughness important for useful experiments. A lot of validation experiments will be needed. How to get to ks for roughness of engineering interest? - depends on wavelength height, etc. for engineering interest? Re-discovering the wheel should be avoided: existing knowledge (theoretical and experimental) should find its way into the engineering models. It is a task of the industry to filter out the existing information in the literature for results relevant to its application, being external or internal.

Source record↗
DOE OSTI2024

Learning with Adaptive Conservativeness for Distributionally Robust Optimization: Incentive Design for Voltage Regulation: Preprint

Information asymmetry between the Distribution System Operator (DSO) and Distributed Energy Resource Aggregators (DERAs) obstructs designing effective incentives for voltage regulation. To capture this effect, we employ a Stackelberg game-theoretic framework, where the DSO seeks to overcome the information asymmetry and refine its incentive strategies by learning from DERA behavior over multiple iterations. We introduce a model-based online learning algorithm for the DSO, aimed at inferring the relationship between incentives and DERA responses. Given the uncertain nature of these responses, we also propose a distributionally robust incentive design model to control the probability of voltage regulation failure and then reformulate it into a convex problem. This model allows the DSO to periodically revise distribution assumptions on uncertain parameters in the decision model of the DERA. Finally, we present a gradient-based method that permits the DSO to adaptively modify its conservativeness level, measured by the size of a Wasserstein metric-based ambiguity set, according to historical voltage regulation performance. The effectiveness of our proposed method is demonstrated through numerical experiments.

distribution system operator↗
DOE OSTI2023

AutoSourceID-Classifier: Star-galaxy classification using a convolutional neural network with spatial information

Aims.Traditional star-galaxy classification techniques often rely on feature estimation from catalogs, a process susceptible to introducing inaccuracies, thereby potentially jeopardizing the classification’s reliability. Certain galaxies, especially those not manifesting as extended sources, can be misclassified when their shape parameters and flux solely drive the inference. We aim to create a robust and accurate classification network for identifying stars and galaxies directly from astronomical images. Methods.The AutoSourceID-Classifier (ASID-C) algorithm developed for this work uses 32x32 pixel single filter band source cutouts generated by the previously developed AutoSourceID-Light (ASID-L) code. By leveraging convolutional neural networks (CNN) and additional information about the source position within the full-field image, ASID-C aims to accurately classify all stars and galaxies within a survey. Subsequently, we employed a modified Platt scaling calibration for the output of the CNN, ensuring that the derived probabilities were effectively calibrated, delivering precise and reliable results. Results.We show that ASID-C, trained on MeerLICHT telescope images and using the Dark Energy Camera Legacy Survey (DECaLS) morphological classification, is a robust classifier and outperforms similar codes such as SourceExtractor. To facilitate a rigorous comparison, we also trained an eXtreme Gradient Boosting (XGBoost) model on tabular features extracted by SourceExtractor. While this XGBoost model approaches ASID-C in performance metrics, it does not offer the computational efficiency and reduced error propagation inherent in ASID-C’s direct image-based classification approach. ASID-C excels in low signal-to-noise ratio and crowded scenarios, potentially aiding in transient host identification and advancing deep-sky astronomy.

Astronomy & Astrophysics↗
NASA NTRS2011

Marine Microbial Mats and the Search for Evidence of Life in Deep Time and Space

Cyanobacterial mats in extensive seawater evaporation ponds at Guerrero Negro, Baja California, Mexico, have been excellent subjects for microbial ecology research. The studies reviewed here have documented the steep and rapidly changing environmental gradients experienced by mat microorganisms and the very high rates of biogeochemical processes that they maintained. Recent genetic studies have revealed an enormous diversity of bacteria as well as the spatial distribution of Bacteria, Archaea and Eukarya. These findings, together with emerging insights into the intimate interactions between these diverse populations, have contributed substantially to our understanding of the origins, environmental impacts, and biosignatures of photosynthetic microbial mats. The biosignatures (preservable cells, sedimentary fabrics, organic compounds, minerals, stable isotope patterns, etc.) potentially can serve as indicators of past life on early Earth. They also can inform our search for evidence of any life on Mars. Mars exploration has revealed evidence of evaporite deposits and thermal spring deposits; similar deposits on Earth once hosted ancient microbial mat ecosystems.

Des Marais, David J.↗
NASA NTRS2013

A New Formulation for Hybrid LES-RANS Computations

Ideally, a hybrid LES-RANS computation would employ LES only where necessary to make up for the failure of the RANS model to provide sufficient accuracy or to provide time-dependent information. Current approaches are fairly restrictive in the placement of LES and RANS regions; an LES-RANS transition in a boundary layer, for example, yields an unphysical log-layer shift. A hybrid computation is formulated here to allow greater control over the placement of LES and RANS regions and the transitions between them. The concept of model invariance is introduced, which provides a basis for interpreting hybrid results within an LES-RANS transition zone. Consequences of imposing model invariance include the addition of terms to the governing equations that compensate for unphysical gradients created as the model changes between RANS and LES. Computational results illustrate the increased accuracy of the approach and its insensitivity to the location of the transition and to the blending function employed.

Woodruff, Stephen L.↗
NASA NTRSDate not supplied

Synergies Between Venus and Exoplanetary Observations

• How can Venus help inform Exoplanetary studies? 1. Volatile Cycling & Weathering on Venus Through Time (Foley, Höning) a) Weathering on Venus : surface water, land area, tectonic state i. Evidence for running water in tesserae? Khawja et al. 2020 ii. D/H Ratio? Hoffman et al. 1980 b) Volcanism & Outgassing: Is SO2 a proxy for on-going volcanism? c) Volatile in-gassing: Does subduction occur today? (Davaille et al.) 2. Venus’ Magnetic Field (O’Rourke) a) Is Venus’ slower interior cooling responsible for lack of magnetic field? b) Lack of a late energetic impactor (Jacobsson et al.): stable density gradients? c) Is mass a factor: larger super-Venus/Earth more likely to have magnetic field?

Exoplanets↗
NASA NTRS1981

Solar cycle signal in air temperature in North America - Amplitude, gradient, phase and distribution

The considered investigation was motivated by three factors. One is related to an extension of single-channel MESA to multi-channel by Strand (1977), Morf et al. (1978), and Jones (1978). MESA is a high-resolution signal processing and spectrum analysis technique due to Burg (1975). The considered developments resulted in the discovery of the 11-year solar cycle signal in the change of the length of day by Currie (1980, 1981). They also led Currie (1981) to study the phase spectrum of the 11-year term in height H of sea level. The investigation tries to clarify the phase relations among the involved parameters. The second factor is connected with an application of the linear time domain technique used by Currie (1981) to temperature records to obtain more accurate information regarding the signal amplitude. The third factor of motivation is related to increases in the number of stations available for an analysis, the greater average length of the records, and the more accurate data set.

Currie, R. G.↗
DOE OSTI2021

Characteristics of thermospheric infrasound predicted using ray tracing and weakly non-linear waveform analyses

Infrasonic signals refracted by thermal gradients in the rarefied upper atmosphere are modeled using a combination of ray tracing and weak shock theory to develop an understanding of thermospheric infrasound signals produced by energetic, transient sources. Canonical arrival structures in the form of u-wave signatures are identified for returns refracted at lower altitudes within the thermosphere, and possible multi-pathing produced by effective sound speed inflections are investigated to elucidate more complex arrival structures, which are found to be spatially localized. Furthermore, variability in the source characteristics is investigated and it is found that whereas some waveform phase information is lost due to finite amplitude effects, arrival characteristics are strongly dependent on the peak overpressure near the source. Variability in the propagation path is considered using archived atmospheric specifications and implies that despite uncertainties related to the dynamic and sparsely sampled nature of the atmosphere, thermospheric signatures might be useful in estimating the yield for explosive sources. Last, thermospheric arrivals from a failed rocket launch, as well as those from several large chemical explosions, are analyzed and it is found that qualitative trends match those predicted, and analyses here provide additional insight into such signatures.

42 ENGINEERING↗
NASA NTRS1981

On the growth of turbulent regions in laminar boundary layers

Turbulent spots evolving in a laminar boundary layer on a nominally zero pressure gradient flat plate are investigated. The plate is towed through an 18 m water channel, using a carriage that rides on a continuously replenished oil film giving a vibrationless tow. Turbulent spots are initiated using a solenoid valve that ejects a small amount of fluid through a minute hole on the working surface. A novel visualization technique that utilizes fluorescent dye excited by a sheet of laser light is employed. Some new aspects of the growth and entrainment of turbulent spots, especially with regard to lateral growth, are inferred from the present experiments. To supplement the information on lateral spreading, a turbulent wedge created by placing a roughness element in the laminar boundary layer is also studied both visually and with probe measurements. The present results show that, in addition to entrainment, another mechanism is needed to explain the lateral growth characteristics of a turbulent region in a laminar boundary layer. This mechanism, termed growth by destabilization, appears to be a result of the turbulence destabilizing the unstable laminar boundary layer in its vicinity. To further understand the growth mechanisms, the turbulence in the spot is modulated using drag-reducing additives and salinity stratification.

Gad-El-hak, M.↗
NASA NTRS1993

A method of wind shear detection for powered-lift STOL aircraft

A new wind shear warning system for powered-lift STOL aircraft was evaluated by using a flight simulator. Wind shear warning systems for CTOL aircraft have been designed to detect horizontal shear only. Because the approach air speed of STOL aircraft is lower than that for CTOL aircraft, STOL aircraft are more vulnerable to vertical wind due to (1) a gradient of horizontal shear that is smaller for STOL than for CTOL aircraft because of slower airspeed; (2) STOL aircraft spend longer time in a downdraft; and (3) vertical wind causes a more radical change in the STOL aircraft's flight path because of its lower airspeed. In order to detect the vertical wind, the wind shear warning system proposed calculates the difference between potential flight path measured on-board during shear traversal and trimmed flight path estimated from aircraft status. The most characteristic feature of this new system is that it utilizes only inertial information and pitot-static airspeed data; this yields a convenient means of on-board implementation. Simulation test results confirm that the new system can detect the vertical shear.

Funabiki, Kohei↗