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At least 1,351 records · Page 75

Data for "Implications of Zoning Ordinances for Rural Utility-Scale Solar Deployment and Power System Decarbonization in the Great Lakes Region".

This dataset includes the Energy Zoning Database and geographic shapefiles used to identify suitable rural areas for utility-scale solar development. Additionally, it contains the input data required for the capacity expansion model, including information on existing electric generators and their associated costs, solar resource potential, and transmission infrastructure data. These datasets collectively support the analysis presented in the paper, ensuring a comprehensive assessment of zoning regulations, land suitability, and the economic and technical feasibility of solar deployment in rural areas.

Owusu-Obeng, Papa Yaw (ORCID:0000000334385183)↗

Influence of temperature and the role of chromium on the kinetics of sulfidation of 310 stainless steel

The sulfidation of 310 stainless steel was studied over the temperature range from 910 K to 1285 K. By adjusting the ratio of hydrogen sulfide, variations in sulfur potential were obtained. The effect of temperature on sulfidation was determined at three different sulfur potentials: 39/sqNm, 0.014/sqNm, and 0.00015/sqNm. All sulfide scales contained one or two surface layers in addition to a subscale. The second outer layer (OL-II), furthest from the alloy, contained primarily Fe-Ni-S. The first outer layer (OL-I), nearest the subscale, contained FE-Cr-S. The subscale consisted of sulfide inclusions in the metal matrix. At a given temperature and sulfur potential, the weight gain data obeyed the parabolic rate law after an initial transient period. The parabolic rate constants obtained at the sulfur potential of 39/sqNm did not show a break when the logarithm of the rate constant was plotted as a function of the inverse of absolute temperature. Sulfidation carried out at sulfur potentials below 0.02/sqNm, however, did show a break at 1145 K, which is termed as the transition temperature. This break was found to be associated with the changes which had occurred in the Fe:Cr ratio of OL-I. Below the transition temperature the activation energy was found to be approximately 125 kj/mole. Above the transition temperature the rate of sulfidation decreased with temperature but dependent on the Fe:Cr ratio in the iron-chromium-sulfide layers of the OL-I. A reaction mechanism consistent with the experimental results has been proposed.

Rao, D. B.↗

Meteorological and dynamical requirements for MST radar networks: Waves

Studies of wave motions using the MST radar have concentrated on single station time series analyses of gravity waves and tides. Since these radars collect high time resolution data they have the potential to become a significant tool for mesoscale research. In addition, radars are operated almost continuously unattended and, consequently, data sets are available for analyzing longer period wave motions such as tides and planetary scale waves. Although there is much to learn from single station data, the possibilities of new knowledge from a network of radars is exciting. The scales of wave motions in the atmosphere cover a broad range. Consequently the choice of a radar network depends to a large extent on the types of wave motions that are studied. There are many outstanding research problems that would benefit from observations from a MST radar network. In particular, there is a strong need for measurements of gravity wave parameters and equatorial wave motions. Some of the current problems in wave dynamics are discussed.

Avery, S. K.↗

Using Laser Altimetry to Detect Topographic Change in Long Valley Caldera, California

Long Valley caldera California, is a site of extensive volcanism, persistent seismicity, and uplift of a resurgent dome, currently at a rate of about 3 cm/year. Airborne laser altimetry was used to determine the surface topography of the region in 1993. A repeat mission occurred in 1995. Three different laser altimeters were flown, dubbed ATLAS, SLICER and RASCAL. Data processing consists of the combination of the aircraft trajectory and attitude data with the laser range, the determination of an atmospheric delay, laser pulse timing errors, laser system biases, and data geolocation to obtain the position of the laser spot on the ground. Results showed that using the ATLAS and SLICER instruments, the elevation of an overflown lake is determined to precisions of 3.3 cm and 2.9 cm from altitudes of 500 m and 3 km above the ground, and about 10 cm using the RASCAL instrument from 500 m above ground. Comparison with tide gauge data showed the laser measurements are able to resolve centimeter-level changes in the lake elevation over time. Repeat pass analysis of tracks over flat surfaces indicate no systematic biases affect the measurement procedure of the ATLAS and SLICER instruments. Comparison of GPS and laser-derived elevations of easily-identifiable features in the caldera confirm the horizontal accuracy of the measurement is within the diameter of the laser footprint, and vertical accuracy is within the error inherent in the measurement. Crossover analysis shows that the standard error of the means at track intersection points within the caldera, and dome (i.e., where zero and close to the maximum amount of uplift is expected) are about I cm, indicating elevation change at the 3 cm/year level should be detectable. We demonstrate one of the powerful advantages of scanning laser altimetry over other remote sensing techniques; the straightforward creation of precise digital elevation maps of overflown terrain. Initial comparison of the 1993-1995 data indicates uplift occurred, but filtering is required to remove vegetation effects. Although research continues to utilize the full potential of laser altimetry data, the results constitute a successful demonstration that the technique may be used to perform geodetic monitoring of surface topographic change.

Hofton, M. A.↗

Using Laser Altimetry to Detect Topographic Change at Long Valley Caldera, California

Long Valley caldera, California, is a site of extensive volcanism, persistent seismicity, and uplift of a resurgent dome, currently at a rate of approximately 3 cm/year. Airborne laser altimetry was used to determine the surface topography of the region in 1993. A repeat mission occurred in 1995. Three different laser altimeters were flown, dubbed ATLAS, SLICER and RASCAL. Data processing consists of the combination of the aircraft trajectory and attitude data with the laser range, the determination of an atmospheric delay, laser pulse timing errors, laser system biases, and data geolocation to obtain the position of the laser spot on the ground. Results showed that using the ATLAS and SLICER instruments, the elevation of an overflown lake is determined to precisions of 3.3 cm and 2.9 cm from altitudes of 500 m and 3 km above the ground, and approximately 10 cm using the RASCAL instrument from 500 m above ground. Comparison with tide gauge data showed the laser measurements are able to resolve centimeter-level changes in the lake elevation over time. Repeat pass analysis of tracks over flat surfaces indicate no systematic biases affect the measurement procedure of the ATLAS and SLICER instruments. Comparison of GPS and laser-derived elevations of easily-identifiable features in the caldera confirm the horizontal accuracy of the measurement is within the diameter of the laser footprint, and vertical accuracy is within the error inherent in the measurement. Crossover analysis shows that the standard error of the means at track intersection points within the caldera and dome (i.e., where zero and close to the maximum amount of uplift is expected) are about 1 cm, indicating elevation change at the 3 cm/year level should be detectable. We demonstrate one of the powerful advantages of scanning laser altimetry over other remote sensing techniques; the straightforward creation of precise digital elevation maps of overflown terrain. Initial comparison of the 1993-1995 data indicates uplift occurred, but filtering is required to remove vegetation effects. Although research continues to utilize the full potential of laser altimetry data, the results constitute a successful demonstration that the technique may be used to perform geodetic monitoring of surface topographic change.

Hofton, M. A.↗

A Machine Learning-Derived Atomistic Potential for Y2Si2O7

Incorporation of SiC/SiC ceramic matrix composite (CMC) hot section components into aircraft engines promises to increase efficiency and safety. However, SiC/SiC CMCs are subject to water vapor-induced oxidation and recession at the high temperatures of engine operation, and thus environmental barrier coatings (EBCs) are required to reduce this degradation and enable their widespread adoption. An understanding of EBCs failure mechanisms, including thermochemical and thermomechanical mechanisms, is essential as coating degradation leads to reduced CMC component service life. Computational modeling approaches can provide insight into EBC material properties important for coating design. However, density functional theory (DFT) is computationally expensive and atomistic potentials are lacking for materials of interest. In this work, we utilize a machine learning approach and DFT training data to parameterize atomistic potentials for two candidate EBC materials, Y2Si2O7 and Yb2Si2O7. These potentials enable near DFT-accurate calculations of thermodynamic and thermomechanical properties essential to EBC design.

Cameron J Bodenschatz↗

A Cluster-based Method to Map Urban Area from DMSP/OLS Nightlights

Accurate information of urban areas at regional and global scales is important for both the science and policy-making communities. The Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime stable light data (NTL) provide a potential way to map urban area and its dynamics economically and timely. In this study, we developed a cluster-based method to estimate the optimal thresholds and map urban extents from the DMSP/OLS NTL data in five major steps, including data preprocessing, urban cluster segmentation, logistic model development, threshold estimation, and urban extent delineation. Different from previous fixed threshold method with over- and under-estimation issues, in our method the optimal thresholds are estimated based on cluster size and overall nightlight magnitude in the cluster, and they vary with clusters. Two large countries of United States and China with different urbanization patterns were selected to map urban extents using the proposed method. The result indicates that the urbanized area occupies about 2% of total land area in the US ranging from lower than 0.5% to higher than 10% at the state level, and less than 1% in China, ranging from lower than 0.1% to about 5% at the province level with some municipalities as high as 10%. The derived thresholds and urban extents were evaluated using high-resolution land cover data at the cluster and regional levels. It was found that our method can map urban area in both countries efficiently and accurately. Compared to previous threshold techniques, our method reduces the over- and under-estimation issues, when mapping urban extent over a large area. More important, our method shows its potential to map global urban extents and temporal dynamics using the DMSP/OLS NTL data in a timely, cost-effective way.

Cities↗

Geothermal direct heat use: Market potential/penetration analysis for Federal Region 9

A preliminary study was made of the potential for geothermal direct heat use in Arizona, California, Hawaii, and Nevada (Federal Region 9). An analysis was made of each state to: (1) define the resource, based on the latest available data; (2) assess the potential market growth for geothermal energy; and (3) estimate the market penetration, projected to 2020. Findings of the study include the following: (1) Potentially economical hydrothermal resources exist in all four states of the Region: however, the resource data base is largely incomplete, particularly for low to moderate temperature resources. (2) In terms of beneficial heat, the total hydrothermal resource identified so far for the four states is on the order of 43 Quads, including an estimated 34 Quads of high temperature resources which are suitable for direct as well as electrical applications. (3) In California, Hawaii, and Nevada, the industrial market sector has somewhat greater potential for penetration than the residential/commercial sector. In Arizona, however, the situation is reversed, due to the collocation of two major metropolitan areas (Phoenix and Tucson) with potential geothermal resources.

Powell, W.↗

Subsonic balance and pressure investigation of a 60-deg delta wing with leading-edge devices (data report)

The drag reduction potential of leading edge devices on a 60 degree delta wing at high lift was examined. Geometric variations of fences, chordwise slots, pylon type vortex generators, leading edge vortex flaps, and sharp leading edge extensions were tested individually and in specific combinations to improve high-alpha drag performance with a minimum of low-alpha drag penalty. The force, moment, and surface static pressure data for angles of attack up to 23 degrees, at Mach and Reynolds numbers of 0.16 and 3.85 x 10 to the 6th power per meter are documented.

Rao, D. M.↗

A Parameter Estimation Scheme for Multiscale Kalman Smoother (MKS) Algorithm Used in Precipitation Data Fusion

A new approach is presented in this paper to effectively obtain parameter estimations for the Multiscale Kalman Smoother (MKS) algorithm. This new approach has demonstrated promising potentials in deriving better data products based on data of different spatial scales and precisions. Our new approach employs a multi-objective (MO) parameter estimation scheme (called MO scheme hereafter), rather than using the conventional maximum likelihood scheme (called ML scheme) to estimate the MKS parameters. Unlike the ML scheme, the MO scheme is not simply built on strict statistical assumptions related to prediction errors and observation errors, rather, it directly associates the fused data of multiple scales with multiple objective functions in searching best parameter estimations for MKS through optimization. In the MO scheme, objective functions are defined to facilitate consistency among the fused data at multiscales and the input data at their original scales in terms of spatial patterns and magnitudes. The new approach is evaluated through a Monte Carlo experiment and a series of comparison analyses using synthetic precipitation data. Our results show that the MKS fused precipitation performs better using the MO scheme than that using the ML scheme. Particularly, improvements are significant compared to that using the ML scheme for the fused precipitation associated with fine spatial resolutions. This is mainly due to having more criteria and constraints involved in the MO scheme than those included in the ML scheme. The weakness of the original ML scheme that blindly puts more weights onto the data associated with finer resolutions is overcome in our new approach.

multiscale↗

Subsonic wind-tunnel investigation of leading-edge devices on delta wings (data report)

The drag reduction potential of leading edge devices on delta wings at high lift is presented. Fences, pylon type vortex generators, chordwise slots, and sharp plate extensions were tested on wing models with 60 and 74 degree swept blunt leading edges at angles of attack to 32 degrees. Six component balance and leading edge surface pressure measurements were taken with various geometry and spanwise arrangements of the devices. Tables listing the data, without analysis, are presented.

Dhanvada, M. R.↗

Ecosystem Controls on Methylmercury Production by Periphyton Biofilms in a Contaminated Stream: Implications for Predictive Modeling

Periphyton biofilms produce a substantial fraction of the overall monomethylmercury (MMHg) flux in East Fork Poplar Creek, an industrially contaminated, freshwater creek in Oak Ridge, Tennessee. We examined periphyton MMHg production across seasons, locations, and light conditions using mercury stable isotopes. Methylation and demethylation rate potentials (km, trans av and kd, trans av, respectively) were calculated using a transient availability kinetic model. Light exposure and season were significant predictors of km, trans av, with greater values in full light exposure and in the summer. Season, light exposure, and location were significant predictors of kd, trans av, which was highest in dark conditions, in the spring, and at the upstream location. Light exposure was the controlling factor for net MMHg production, with positive production for periphyton grown under full light exposure and net demethylation for periphyton grown in the dark. Ambient MMHg and km, trans av were significantly correlated. Transient availability rate potentials were 15 times higher for km and 9 times higher for kd compared to full availability rate potentials (km, full av and kd, full av) calculated at 1 d. No significant model for the prediction of km, full av or kd, full av could be constructed using light, season, and location. In addition, there were no significant differences among treatments for the full availability km, full av, kd, full av, or net MMHg calculated using the full availability rate potentials. km, full av was not correlated with ambient MMHg concentrations. The present results underscore the importance of applying transient availability kinetics to MMHg production data when estimating MMHg production potential and flux.

Schwartz, Grace E.↗

Analysis of phase stability and chemical segregation in the Mo-V alloys using a generalized embedded atom method potential

A new interatomic potential for the Mo-V system is introduced to facilitate the study of phase stability and mechanical properties at lower temperatures. This potential is based on a generalization of the embedded atom method and includes contributions from embedding energy, explicit two- and three-body interactions and nonlocal many-body interaction terms. The parameters of the potential are optimized by using data from ab initio density functional theory (DFT) calculations. The potential is rigorously validated across a range of physical properties, such as elastic constants, equation of states, phonon dispersion curves, point defect properties and melting temperatures for different compositions. Even though our potential is trained on a small dataset, its accuracy is comparable to available machine learning potentials for Mo and V. Furthermore, our results show that an ordered B2 phase is stable at low temperatures in alloys containing 50% V, but the solid solution phase is stable above 800 K. However, such long-range ordering is not observed in V-rich or Mo-rich alloys. In addition, our results show that V segregates to dislocation cores and grain boundaries.

36 MATERIALS SCIENCE↗

A search for ultrahigh-energy neutrinos associated with astrophysical sources using the third flight of ANITA

The ANtarctic Impulsive Transient Antenna (ANITA) long-duration balloon experiment is sensitive to interactions of ultrahigh-energy (E>10 18 eV) neutrinos in the Antarctic ice sheet. The third flight of ANITA, lasting 22 days, began in December 2014. We develop a methodology to search for energetic neutrinos spatially and temporally coincident with potential source classes in ANITA data. This methodology is applied to several source classes: the potential IceCube-identified neutrino sources TXS 0506+056 and NGC 1068, flaring high-energy blazars reported by the Fermi All-Sky Variability Analysis, gamma-ray bursts, and supernovae. Among searches within the five source classes, one candidate was identified as associated with SN 2015D, although not at a statistically significant level. Finally, we proceed to place upper limits on the source classes. We further comment on potential application of this methodology to more sensitive future instruments.

79 ASTRONOMY AND ASTROPHYSICS↗

The Manufacturing Data and Machine Learning Platform: Enabling Real-time Monitoring and Control of Scientific Experiments via IoT

IoT devices and sensor networks present new opportunities for measuring, monitoring, and guiding scientific experiments. Sensors, cameras, and instruments can be combined to provide previously unachievable insights into the state of ongoing experiments. However, IoT devices can vary greatly in the type, volume, and velocity of data they generate, making it challenging to fully realize this potential. Indeed, synergizing diverse IoT data streams in near-real time can require the use of machine learning (ML). In addition, new tools and technologies are required to facilitate the collection, aggregation, and manipulation of sensor data in order to simplify the application of ML models and in turn, fully realize the utility of IoT devices in laboratories. Here we will demonstrate how the use of the Argonne-developed Manufacturing Data and Machine Learning (MDML) platform can analyze and use IoT devices in a manufacturing experiment. MDML is designed to standardize the research and operational environment for advanced data analytics and AI-enabled automated process optimization by providing the infrastructure to integrate AI in cyber-physical systems for in situ analysis. We will show that MDML is capable of processing diverse IoT data streams, using multiple computing resources, and integrating ML models to guide an experiment.

Machine Learning↗

Asymptotic Normalization Coefficients in a Potential Model Involving Forbidden States

It is shown that values obtained for asymptotic normalization coefficients by means of a potential fitted to experimental data on elastic scattering depend substantially on the presence and the number n of possible forbidden states in the fitted potential. The present analysis was performed within exactly solvable potential models for various nuclear systems and various potentials without and with allowance for Coulomb interaction. Various methods for changing the number n that are based on the use of various versions of the change in the parameters of the potential model were studied. A compact analytic expression for the asymptotic normalization coefficients was derived for the case of the Hulthén potential. Specifically, the d + α and α + {sup 12}C systems, which are of importance for astrophysics, were examined. It was concluded that an incorrect choice of n could lead to a substantial errors in determining the asymptotic normalization coefficients. From the results of our calculations, it also follows that, for systems with a low binding energy and, as a consequence, with a large value of the Coulomb parameter, the inclusion of the Coulomb interaction may radically change the asymptotic normalization coefficients, increasing them sharply.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Fracture Toughness Characterization of Highly irradiated Reactor Pressure Weld from the ATR-2 Experiment

The UCSB ATR-2 irradiation experiment is designed to generate a new database on a wide variety of irradiated reactor pressure vessel (RPV) steels to fill a critical gap in predicting high fluence embrittlement for extended plant operation up to 80 years. A major focus in this experiment is to characterize the effects of irradiation temperature, neutron flux and fluence, and alloy chemistry on MNSP evolution, and model how these features impact hardening and embrittlement, manifested as shifts in ductile-to-brittle transition temperature. As part of these efforts, disk compact tension (DCT) specimens of three representative materials were included in the ATR-2 experiment to have direct measurement of transition fracture toughness shift and, thus, to have some benchmark data to compare outcoming predictive models with actual fracture toughness shifts. In addition, the attempts would be made to use these fracture toughness data to address the potential effect of high dose irradiation on the shape of the Master Curve for highly embrittled RPV material.This report provides data for the fracture toughness characterization of highly embrittled weld from Palisades steam generator.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Investigating Temperature Uniformity and Accuracy in PV Module Lamination: A Verification Study

This study investigates the temperature uniformity and accuracy of a photovoltaic (PV) module lamination process by addressing inconsistencies identified in 2017 data where irregular temperature changes were observed across setpoints. The 2017 data showed a notable drop in temperature upon bladder initiation, except for the 145 degrees Celsius profile. This inconsistency indicated potential inaccuracies in manual data recording methods. To address this concern, a verification experiment was conducted to evaluate temperature uniformity across the 2014 Bent River SPL2828 laminator platen and within test samples. Thermocouples, paired with Omega data acquisition software, were deployed to measure temperatures at multiple platen locations and within test samples. The experiment compared lamination temperatures of polyethylene-co-vinyl acetate (EVA) encapsulant when paired with solite glass or TPE backsheets. The methodology included verifying temperature uniformity directly on the platen and by using a large glass/EVA/glass sample using multiple thermocouples. Smaller samples were built with glass/EVA/glass and glass/EVA/backsheet configurations with one centered thermocouple to verify and compare sample temperatures. This verification aims to refine lamination temperature profiles, enhance data accuracy and provide insights into optimal process control for uniform module lamination. Ensuring consistent and uniform lamination may improve the accuracy and reliability of research outcomes.

14 SOLAR ENERGY↗