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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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DOE OSTI2020

WHONDRS Summer 2019 Sampling Campaign: Global River Corridor Sediment FTICR-MS, Dissolved Organic Carbon, Aerobic Respiration, Elemental Composition, Grain Size, Total Nitrogen and Organic Carbon Content, Bacterial Abundance, and Stable Isotopes (v10)

The WHONDRS Summer 2019 Sampling (S19S) Campaign collected samples in 97 globally distributed river corridor systems between July and September 2019. Surficial streambed sediments were collected at three locations within each site (upstream, midstream, and downstream). Surface water was collected at the downstream site. This dataset includes a portion of the data types produced from the sediment samples and does not include any results from the surface water. Surface water data can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1603775. The S19S campaign was designed with the science community to ask questions associated with links among core/transient metabolomes, microbial metabolism, biogeochemical function, and physical properties of watershed and river corridor systems. This data package was originally published in December 2020. It was updated in April 2021 (v2; modified files), May 2022 (v3; new and modified files), November 2022 (v4; new and modified files), January 2023 (v5 and v6; new and modified files), February 2023 (v7; new and modified files), August 2023 (v8; new and modified files), July 2025 (v9; new and modified files), and June 2026 (v10; new and modified files). Version 10 includes major restructuring of the files and their formats. See the change history in the readme for details. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset contains (1) readme, (2) data dictionary, (3) file level metadata, (4) sampling protocol, (5) a data checks report, (6) field metadata, (7) international generic sample number (IGSN) mapping file, (8) joint genome institute (JGI) mapping file, (9) a folder of site photos, and (10) a folder of sample data. The sample data folder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) and FTICR methods; (2) respiration rates and normalized respiration rates calculated from laboratory sediment incubations, (3) X-ray fluorescence (XRF) elemental composition, (4) grain size distribution from the < 2 millimeter fraction of sediment, (5) total organic carbon and total nitrogen content, (6) bacterial abundance flow cytometry data, (7) sediment stable isotopes (C and N), (8) laboratory methods, (9) water and sediment mass and volume used in incubations, (10) a folder with code, inputs, and plots for the respiration rates, (11) a folder containing XRF data, (12) a folder containing unaligned, peak-picked high resolution characterization of dissolved organic matter from sediment via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory), (12) and a folder containing processed FTICR-MS data. All files are .msa, .txt, .spx, .xml, .csv, .pdf, .txt, .jpg, or .jpeg.

13C↗

DOE OSTI2022

Sample Preparation and Experimental Design for In Situ Multi-Beam Transmission Electron Microscopy Irradiation Experiments

We discuss the need to understand materials exposed to overlapping extreme environments such as high temperature, radiation, or mechanical stress. When these stressors are combined there may be synergistic effects that enable unique microstructural evolution mechanisms to activate. Understanding of these mechanisms is necessary for the input and refinement of predictive models and critical for engineering of next generation materials. The basic physics and underlying mechanisms require advanced tools to be investigated. The in situ ion irradiation transmission electron microscope (I 3 TEM) is designed to explore these principles. To quantitatively probe the complex dynamic interactions in materials, careful preparation of samples and consideration of experimental design is required. Particular handling or preparation of samples can easily introduce damage or features that obfuscate the measurements. There is no one correct way to prepare a sample; however, many mistakes can be made. The most common errors and things to consider are highlighted within. The I 3 TEM has many adjustable variables and a large potential experimental space, therefore it is best to design experiments with a specific scientific question or questions in mind. Experiments have been performed on large number of sample geometries, material classes, and with many irradiation conditions. The following are a subset of examples that demonstrate unique in situ capabilities utilizing the I 3 TEM. Au nanoparticles prepared by drop casting have been used to investigate the effects of single ion strikes. Au thin films have been used in studies on the effects of multibeam irradiation on microstructure evolution. Zr films have been exposed to irradiation and mechanical tension to examine creep. Ag nanopillars were subjected to simultaneous high temperature, mechanical compression, and ion irradiation to study irradiation induced creep as well. These results impact fields including: structural materials, nuclear energy, energy storage, catalysis, and microelectronics in space environments.

47 OTHER INSTRUMENTATION↗

NASA NTRS2011

Drop Size Distribution Measurements Supporting the NASA Global Precipitation Measurement Mission: Infrastructure and Preliminary Results

Global Precipitation Measurement Mission (GPM) retrieval algorithm validation requires datasets that characterize the 4-D structure, variability, and correlation properties of hydrometeor particle size distributions (PSD) and accumulations over satellite fields of view (5 -- 50 km). Key to this process is the combined use of disdrometer and polarimetric radar platforms. Here the disdrometer measurements serve as a reference for up-scaling dual-polarimetric radar observations of the PSD to the much larger volumetric sampling domain of the radar. The PSD observations thus derived provide a much larger data set for assessing DSD variability, and satellite-based precipitation retrieval algorithm assumptions, in all three spatial dimensions for a range of storm types and seasons. As one component of this effort, the GPM Ground Validation program recently acquired five 3rd generation 2D Video disdrometers as part of its Disdrometer and Radar Observations of Precipitation Facility (DROP), currently hosted in northern Alabama by the NASA Marshall Space Flight Center and the University of Alabama in Huntsville. These next-generation 2DVDs were operated and evaluated in different phases of data collection under the scanning domain of the UAH ARMOR C-band dual-polarimetric radar. During this period approximately 7500 minutes of PSD data were collected and processed to create gamma size distribution parameters using a truncated method of moments approach. After creating the gamma parameter datasets the DSDs were then used as input to T-matrix code for computation of polarimetric radar moments at C-band. The combined dataset was then analyzed with two basic objectives in mind: 1) the investigation of seasonal variability in the rain PSD parameters as observed by the 2DVDs; 2) the use of combined polarimetric moments and observed gamma distribution parameters in a functional form to retrieve PSD parameters in 4-D using the ARMOR radar for precipitation occurring in different seasons and for different rain system types. Preliminary results suggest that seasonal variations in the DSD parameters do occur, but are most pronounced when comparing tropical PSDs to either winter or summer convective precipitation. For example the previously documented shift to relatively smaller drop diameters in higher number concentrations for equivalent rain rate bins was observed in tropical storm rainbands occurring over Huntsville. On a more inter seasonal basis empirical fits between parameters such as D0 and ZDR do not appear to exhibit robust seasonal biases- i.e., one fit seems to work for all seasons within acceptable standard error (O[10%]) for estimates of D0. In polarimetric retrievals of the vertical variability in PSD (rain layer) for a tropical rainband we find that the Do varies with height when partitioned by specified precipitation categories (e.g., convective or stratiform, heavy and light stratiform etc.) but this variation is of order 10-20% and is smaller than the difference in D0 observed between the basic delineation of convective and stratiform precipitation types. Currently we are expanding our analysis of the vertical structure of the PSD to include several seasonally and/or dynamically-different storm system types (e.g., winter convection and stratiform events; summer mid-latitude convective etc.) sampled by ARMOR. The study will present the results of our combined analyses.

Petersen, Walter A.↗

DOE OSTI2015

Effect of spatial sampling from European flux towers for estimating carbon and water fluxes with artificial neural networks

Abstract Empirical modeling approaches are frequently used to upscale local eddy covariance observations of carbon, water, and energy fluxes to regional and global scales. The predictive capacity of such models largely depends on the data used for parameterization and identification of input‐output relationships, while prediction for conditions outside the training domain is generally uncertain. In this work, artificial neural networks (ANNs) were used for the prediction of gross primary production (GPP) and latent heat flux (LE) on local and European scales with the aim to assess the portion of uncertainties in extrapolation due to sample selection. ANNs were found to be a useful tool for GPP and LE prediction, in particular for extrapolation in time (mean absolute error MAE for GPP between 0.53 and 1.56 gC m −2 d −1 ). Extrapolation in space in similar climatic and vegetation conditions also gave good results (GPP MAE 0.7–1.41 gC m −2 d −1 ), while extrapolation in areas with different seasonal cycles and controlling factors (e.g., the tropical regions) showed noticeably higher errors (GPP MAE 0.8–2.09 gC m −2 d −1 ). The distribution and the number of sites used for ANN training had a remarkable effect on prediction uncertainty in both, regional GPP and LE budgets and their interannual variability. Results obtained show that for ANN upscaling for continents with relatively small networks of sites, the error due to the sampling can be large and needs to be considered and quantified. The analysis of the spatial variability of the uncertainty helped to identify the meteorological drivers driving the uncertainty.

Papale, Dario↗

DOE OSTI2015

The radial profile and flattening of the Milky Way’s stellar halo to 80 kpc from the SEGUE K-giant survey

We characterize the radial density, metallicity, and flattening profile of the Milky Way’s stellar halo, based on the large sample of spectroscopically confirmed giant stars from SDSS/SEGUE-2, spanning galactocentric radii 10 kpc ≤ r{sub GC} ≤ 80 kpc. After excising stars that were algorithmically attributed to apparent halo substructure (including the Sagittarius stream), the sample has 1757 K giants, with a typical metallicity precision of 0.2 dex and a mean distance accuracy of 16%. Compared to blue horizontal branch stars or RR Lyrae variables, giants are more readily understood tracers of the overall halo star population, with less bias in age or metallicity. The well-characterized selection function of the sample enables forward modeling of those data, based on ellipsoidal stellar density models, ν{sub *}(R, z), with Einasto profiles and (broken) power laws for their radial dependence, combined with a model for the metallicity gradient and the flattening profile. Among models with constant flattening, these data are reasonably well fit by an Einasto profile of n = 3.1 ± 0.5 with an effective radius r{sub eff}=15±2 kpc and a flattening of q = 0.7 ± 0.02, or comparably well by an equally flattened broken power law, with radial slopes of α{sub in} = 2.1 ± 0.3 and α{sub out} = 3.8 ± 0.1, with a break radius of r{sub break} = 18 ± 1 kpc; this is largely consistent with earlier work. We find a modest but significant metallicity gradient within the “outer” stellar halo, [Fe/H] decreasing outward. If we allow for a variable flattening q=f(r{sub GC}), we find the distribution of halo giants to be considerably more flattened at small radii, q(10 kpc) = 0.55 ± 0.02, compared to q(>30 kpc) = 0.8 ± 0.03. Remarkably, the data are then very well fit by a single power law with index of 4.2 ± 0.1 on the variable r{sub q}≡√(R{sup 2}+(z/q(r)){sup 2}). In this simple and better-fitting model, there is a break in flattening at ∼20 kpc, instead of a break in the radial density function. While different parameterizations of the radial profile vary in their parameters, their implied density gradient, ∂lnν{sub ∗}/∂lnr, is stable along a direction intermediate between major and minor axis; this gradient is crucial in any dynamical modeling that uses halo stars as tracers.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2014

Discovery of a Similar to 5 Day Characteristic Timescale in the Kepler Power Spectrum of Zw 229-15

We present time series analyses of the full Kepler dataset of Zw 229− 15. This Kepler light curve- with a baseline greater than three years, composed of virtually continuous, evenly sampled 30-minute measurements - is unprecedented in its quality and precision. We utilize two methods of power spectral analysis to investigate the optical variability and search for evidence of a bend frequency associated with a characteristic optical variability timescale. Each method yields similar results. The first interpolates across data gaps to use the standard Fourier periodogram. The second, using the CARMA-based time-domain modeling technique of Kelly et al., does not need evenly-sampled data. Both methods find excess power at high frequencies that may be due to Kepler instrumental effects. More importantly both also show strong bends (delta alpha is approx. 2) at timescales of approx. 5 days, a feature similar to those seen in the X-ray PSDs of AGN but never before in the optical. This observed approx. 5 day timescale may be associated with one of several physical processes potentially responsible for the variability. A plausible association could be made with light -crossing, dynamical or thermal timescales, depending on the assumed value of the accretion disk size and on unobserved disk parameters such as alpha and H¬R. This timescale is not consistent with the viscous timescale, which would be years in a approx. 10(exp7) solar mass AGN such as Zw 229− 15. However there must be a second bend on long (& 1 year) timescales, and that feature could be associated with the viscous timescale.

timescale↗

DOE OSTI2020

Quantification of Brønsted Acid Sites in Zeolites by Water Desorption Thermogravimetry

The many studies that have been conducted on water adsorption on zeolites were carried out in “adsorption” mode, from adsorption isotherms or single-point measurements, with the samples being first degassed at high temperature, and then exposed to water vapor at variable partial pressure. Here, we report Thermogravimetric Analysis (TGA) studies of HZSM-5 saturated with water at room temperature, thus studying water adsorption in “desorption” mode. In this work, TGA was used to ascertain the amount of water remaining as a function of the pretreatment temperature, and to identify the temperature at which one water molecule per framework Al atom persists. Solid-state 1H NMR spectroscopy, combined with molecular modeling, provided evidence for water molecules hydrogen bonded to Brønsted acid sites and formation of oxonium species for distinct water per framework Al atom. TGA is shown to be a simple and expeditious technique to measure the number of Brønsted acid sites in aluminosilicate zeolites, with advantages over the traditional methods of IR or TPD of dangerous adsorbed ammonia or pyridine. TGA of adsorbed water also provides information on the water clusters formed at the acid sites of HZSM-5, which are proportional to the number of acid sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Fabrication of Biodegradable Superabsorbent Using RSM Design for Controlled Release of KNO{sub 3}

Present study envisaged the sequential experimental design approach for the development of biodegradable Gelatin-Tapoica/polyacrylamide superabsorbent. Percentage water uptake efficacy of candidate sample was optimized using Response Surface Methodology (RSM) design under microwave irradiation. Different process variables such as potassium persulphate and ammonium persulphate (KPS:APS) ratio, pH, reaction time concentration of acrylamide and N,N-methylene-bis-acrylamide (MBA) were investigated as a function of percentage swelling using sequential experimental design. Maximum liquid efficacy of 1550% was obtained at KPS:APS = 1.0:0.5; acrylamide = 7.67 × 10{sup −1} mol L{sup −1}; MBA = 1.76 × 10{sup −2} mol L{sup −1}; pH 10 and time = 110 s. The 3D crosslinked network formed was characterized using Fourier Transformation Infrared spectroscopy (FTIR), X-ray diffraction (XRD), Scanning Electron Microscopic (SEM) techniques and thermal stability was ensured by Thermal gravimetric Analysis/Differential Thermal Analysis/Differential Thermal Gravimetric (TGA/DTA/DTG) studies. Superabsorbent synthesized could increase the moisture content in different type of soils and was found to enhance the water-holding capability of the soil upto 60 days in clayey, 40 days in sandy and 51 days in mixture of two soils under controlled conditions. Further, candidate polymer was investigated for the in-vitro controlled release of the KNO{sub 3} with diffusion exponent ‘n’ was found to be 0.4326 indicating Fickian type diffusion. Also, initial diffusion coefficient (D{sub I} = 3.49 × 10{sup −5} m{sup 2} h{sup −1}) was found to be greater than the lateral diffusion coefficient (D{sub L} = 3.76 × 10{sup −6} m{sup 2} h{sup −1}) indicated rapid release of KNO{sub 3} during initial hours with slow release afterwards. The ecofriendly nature of the synthesized polymer was also tested by conducting biodegradation studies and it was found to degrade upto 94% and 88.1% within 70 days with degradation rate of 1.34 and 1.26% per day using composting method and vermicomposting method respectively. So, the synthesized candidate polymer was found to be boon for agriculture-horticulture sector with wide applicability.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Multi-lab study on the pure-gas permeation of commercial polysulfone (PSf) membranes: Measurement standards and best practices

Gas-separation membranes are a critical industrial component for a low-carbon and energy-efficient future. As a result, many researchers have been testing membrane materials over the past several decades. Unfortunately, almost all membrane-based testing systems are home-built, and there are no widely accepted material standards or testing protocols in the literature, making it challenging to accurately compare experimental results. Further, in this multi-lab study, ten independent laboratories collected high-pressure pure-gas permeation data for H 2 , O 2 , CH 4 , and N 2 in commercial polysulfone (PSf) films. Equipment information, testing procedures, and permeation data from all labs were collected to provide (1) accepted H 2 , O 2 , CH 4 , and N 2 permeability values at 35°C in PSf as a reference standard, (2) statistical analysis of lab-to-lab uncertainties in evaluating permeability, and (3) a list of best practices for sample preparation, equipment set-up, and permeation testing using constant-volume variable-pressure apparatuses. Results summarized in this work provide a reference standard and recommended testing protocols for pure-gas testing of membrane materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Accounting for multi-dimensional dependencies among decision-makers within a generalized model framework: An application to understanding shared mobility service usage levels

Activity-travel choices of individuals are influenced by spatial dependency effects. As individuals interact and exchange information with, or observe the behaviors of, those in close proximity of themselves, they are likely to shape their behavioral choices accordingly. For this reason, econometric choice models that account for spatial dependency effects have been developed and applied in a number of fields, including transportation. However, spatial dependence models to date have largely defined the strength of association across behavioral units based on spatial or geographic proximity. In the current context of social media platforms and ubiquitous internet and mobile connectivity, the strength of associations among individuals is no longer solely dependent on spatial proximity. Rather, the strength of associations among individuals may be based on shared attitudes and preferences as well. In other words, behavioral choice models may benefit from defining dependency effects based on attitudinal constructs in addition to geographical constructs. In this paper, frequency of usage of car-sharing and ride-hailing services is modeled using a generalized heterogeneous data model (GHDM) framework that incorporates multi-dimensional dependencies among decision-makers. The model system is estimated on the 2014-2015 Puget Sound Regional Travel Study survey sample, with proximity in latent attitudinal constructs defined by a number of personality trait variables. Model estimation results show that social dependency effects arising from similarities in attitudes and preferences are significant in explaining shared mobility service usage. Ignoring such effects may lead to erroneous estimates of the adoption and usage of future transportation technologies and mobility services.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Explore Spatio‐Temporal Learning of Large Sample Hydrology Using Graph Neural Networks

Abstract Streamflow forecasting over gauged and ungauged basins play a vital role in water resources planning, especially under the changing climate. Increased availability of large sample hydrology data sets, together with recent advances in deep learning techniques, has presented new opportunities to explore temporal and spatial patterns in hydrological signatures for improving streamflow forecasting. The purpose of this study is to adapt and benchmark several state‐of‐the‐art graph neural network (GNN) architectures, including ChebNet, Graph Convolutional Network (GCN), and GraphWaveNet, for end‐to‐end graph learning. We explicitly represent river basins as nodes in a graph, learn the spatiotemporal nodal dependencies, and then use the learned relations to predict streamflow simultaneously across all nodes in the graph. The efficacy of the developed GNN models is investigated using the Catchment Attributes and MEteorology for Large‐sample Studies (CAMELS) data set under two settings, fixed graph topology (transductive learning), and variable graph topology (inductive learning), with the latter applicable to prediction in ungauged basins (PUB). Results indicate that GNNs are generally robust and computationally efficient, achieving similar or better performance than a baseline model trained using the long short‐term memory (LSTM) network. Further analyses are conducted to interpret the graph learning process at the edge and node levels and to investigate the effect of different model configurations. We conclude that graph learning constitutes a viable machine learning‐based method for aggregating spatiotemporal information from a multitude of sources for streamflow forecasting

Sun, Alexander Y.↗

DOE OSTI2021

Confinement effects and acid strength in zeolites

Chemical reactivity and sorption in zeolites are coupled to confinement and—to a lesser extent—to the acid strength of Brønsted acid sites (BAS). In presence of water the zeolite Brønsted acid sites eventually convert into hydronium ions. The gradual transition from zeolite Brønsted acid sites to hydronium ions in zeolites of varying pore size is examined by ab initio molecular dynamics combined with enhanced sampling based on Well-Tempered Metadynamics and a recently developed set of collective variables. While at low water content (1–2 water/BAS) the acidic protons prefer to be shared between zeolites and water, higher water contents (n > 2) invariably lead to solvation of the protons within a localized water cluster adjacent to the BAS. At low water loadings the standard free energy of the formed complexes is dominated by enthalpy and is associated with the acid strength of the BAS and the space around the site. Conversely, the entropy increases linearly with the concentration of waters in the pores, favors proton solvation and is independent of the pore size/shape.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Evaluation of subsurface transport processes of delayed gas signatures applicable to underground nuclear explosions

Radioactive gas signatures from underground nuclear explosions (UNEs) result from gas-migration processes occurring in the subsurface. The processes considered in this study either drive or retard upward migration of gases from the detonation cavity. The relative importance of these processes is evaluated by simulating subsurface transport in a dual-permeability medium for the multi-tracer Noble Gas Migration Experiment (NGME) originally intended to study some aspects of transport from a UNE. For this experiment, relevant driving processes include weak two-phase convection driven by the geothermal gradient, over pressuring of the detonation cavity, and barometric pumping while gas sorption, dissolution, radioactive decay, and usually diffusion represent retarding processes. From deterministic simulations we found that over-pressuring of the post-detonation chimney coupled with barometric pumping produced a synergistic effect amplifying the tracer-gas reaching the surface. Bounding simulations indicated that the sorption and dissolution of gases, tending to retard transport, were much smaller than anticipated by earlier laboratory studies. The NGME observations themselves show that differences in gas diffusivity have a larger effect on influencing upward transport than do the combined effects of tracer-gas sorption and dissolution, which is consistent with a Sobol’ sensitivity analysis. Both deterministic simulations and those considering parametric uncertainties of transport-related properties predict that the excess in concentration of SF 6 compared to 127 Xe as might be captured in small volumetric samples should be much smaller than the order-of-magnitude contrast found in the large-volume gas samples taken at the site. While extraction of large-volume subsurface gas samples is shown to be capable of distorting in situ gas compositions, the highly variable injection rate of SF 6 into the detonation cavity relative to that of 127 Xe at the start of the field experiment is the most likely explanation for the large difference in observed concentrations.

58 GEOSCIENCES↗

DOE OSTI2018

Hg isotopes reveal in-stream processing and legacy inputs in East Fork Poplar Creek, Oak Ridge, Tennessee, USA

In this paper, natural abundance stable Hg isotope measurements were used to place new constraints on sources, transport, and transformations of Hg along the flow path of East Fork Poplar Creek (EFPC), a point-source contaminated headwater stream in Oak Ridge, Tennessee. Particulate-bound Hg in the water column of EFPC within the Y-12 National Security Complex, was isotopically similar to average metallic Hg(0) used in industry, having a mean δ 202 Hg value of -0.42 ± 0.09‰ (1SD) and near-zero Δ 199 Hg. On average, particulate fraction δ 202 Hg values increased downstream by 0.53‰, while Δ 199 Hg decreased by -0.10‰, converging with the Hg isotopic composition of the fine fraction of streambed sediment along the 26 km flow path. The dissolved fraction behaved differently. Although initial Δ 199 Hg values of the dissolved fraction were also near-zero, these values increased transiently along the flow path. Initial δ 202 Hg values of the dissolved fraction were more variable than in the particulate fraction, ranging from -0.44 to 0.18‰ among three seasonal sampling campaigns, but converged to an average δ 202 Hg value of 0.01 ± 0.10‰ (1SD) downstream. Dissolved Hg in the hyporheic and riparian pore water had higher and lower δ 202 Hg values, respectively, compared to dissolved Hg in stream water. Finally, variations in Hg isotopic composition of the dissolved and suspended fractions along the flow path suggest that: (1) physical processes such as dilution and sedimentation do not fully explain decreases in total mercury concentrations along the flow path; (2) in-stream processes include photochemical reduction, but microbial reduction is likely more dominant; and (3) additional sources of dissolved mercury inputs to EFPC at baseflow during this study predominantly arise from the hyporheic zone.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2019

A comprehensive dataset for the accelerated development and benchmarking of solar forecasting methods

We describe and release a comprehensive solar irradiance, imaging, and forecasting dataset. Our goal with this release is to provide standardized solar and meteorological datasets to the research community for the accelerated development and benchmarking of forecasting methods. The data consist of three years (2014–2016) of quality-controlled, 1-min resolution global horizontal irradiance and direct normal irradiance ground measurements in California. In addition, we provide overlapping data from commonly used exogenous variables, including sky images, satellite imagery, and Numerical Weather Prediction forecasts. We also include sample codes of baseline models for benchmarking of more elaborated models.

Remote sensing↗

DOE OSTI2021

Neutron irradiation induced defects in oxides and their impact on the oxide properties

Understanding the irradiation-induced defects in oxides is of interest for a wide range of applications. ZnO is an interesting oxide with mixed ionic and covalent bonding that contains a variety of point defect structures—making it an excellent model for studying irradiation-induced defects and their impact on properties. Here, we investigate the effects of neutron irradiation on the formation of defects and on the structural, optical, and electrical properties of ZnO single crystals. We observe the formation of vacancies and voids via positron annihilation spectroscopy. Neutron irradiation led to a significant deterioration of the ZnO structure and formed a high concentration of point defects, vacancy clusters, and voids with large disparities in their structure across variable irradiation times. It also led to significant changes in the optical properties and sample color. Irradiation for 444 h induced a high concentration of Cu acceptors as well as a high concentration of Ga donors. Additionally, temperature-dependent Hall effect measurements revealed the competing production of donors and acceptors and showed an increase in the slope of the carrier freeze-out curve with increasing irradiation dose. This work demonstrates the combined effects of neutron irradiation in producing a wide range of structural defects, impurities, and dopants in oxides and their enormous impact on modifying the oxide structure and both the optical and electronic properties. It particularly emphasizes the importance of considering the production of new impurities and dopants during the neutron irradiation of oxides.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2015

Gamma-ray bursts: Temporal scales and the bulk Lorentz factor

For a sample of Swift and Fermi gamma-ray bursts, we show that the minimum variability timescale and the spectral lag of the prompt emission is related to the bulk Lorentz factor in a complex manner. For small Γ's, the variability timescale exhibits a shallow (plateau) region. For large Γ's, the variability timescale declines steeply as a function of Γ (δT∝Γ{sup −4.05±0.64}). Evidence is also presented for an intriguing correlation between the peak times, t{sub p}, of the afterglow emission and the prompt emission variability timescale.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Signal-Compensation-Based Adaptive PID Control for Fused Magnesia Smelting Processes

For fused magnesia smelting processes, the proportional-integral-derivative (PID) controller is difficult to regulate the smelting currents within desired ranges due to unexpected variations of the dynamics caused by material feeding operations. To solve this problem, we first proposed its dynamic model composed of a linear model and an uncertain nonlinear dynamic system that describes the unknown time-varying dynamics of nonlinearity and strong couplings among controlled variables. Then, using the accurately calculated value of the uncertain part at the previous sampling time instant and the tracking error that reflects the influence of its change rate, we developed a feedforward and a one-step optimal control to obtain two signal compensators to eliminate the impact of frequent variations of the uncertainties. For the compensators, we proposed a weight selection method to minimize the sum of the squared tracking error with ensured closed-loop stability. Based on the abovementioned modeling and control structure, we finally developed a novel adaptive PID controller augmented with signal compensators to control the whole process. Industrial applications have shown that the proposed method can always keep the tracking error and the control input within their targeted ranges, leading to a significantly reduced energy consumption per ton and increased fused magnesia production.

Wang, Weizhou↗