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At least 1,621 records · Page 90

Crowd cluster data in the USA for analysis of human response to COVID-19 events and policies

We provide data on daily social contact intensity of clusters of people at different types of Points of Interest (POI) by zip code in Florida and California. This data is obtained by aggregating fine-scaled details of interactions of people at the spatial resolution of 10 m, which is then normalized as a social contact index. We also provide the distribution of cluster sizes and average time spent in a cluster by POI type. This data will help researchers perform fine-scaled, privacy-preserving analysis of human interaction patterns to understand the drivers of the COVID-19 epidemic spread and mitigation. Current mobility datasets either provide coarse-level metrics of social distancing, such as radius of gyration at the county or province level, or traffic at a finer scale, neither of which is a direct measure of contacts between people. We use anonymized, de-identified, and privacy-enhanced location-based services (LBS) data from opted-in cell phone apps, suitably reweighted to correct for geographic heterogeneities, and identify clusters of people at non-sensitive public areas to estimate fine-scaled contacts.

60 APPLIED LIFE SCIENCES↗

Cost of Fish Exclusion and Passage Technologies for Hydropower

Hydropower represents a reliable source of renewable energy and accounts for approximately 7% of the total electrical generation in the United States. Future expansion of hydropower is likely to be in the form of either smaller new stream development projects or powering existing non-powered dams. For these new projects to be successful, careful analysis of risks, costs, and uncertainty to offset reduced power production as well as ensuring the protection and safe passage of migratory fish to gain public support, will be required. Exclusion and passage are two common approaches to protect fish from entrainment and impingement at hydropower facilities. The thresholds for entrainment risk and requirements for exclusion and passage often differ depending on the species involved, the characteristics of the facility, and the goals of stakeholders. While the costs associated with environmental mitigations represent a large proportion of the total costs required for the licensing of hydropower facilities, little quantitative information is present within the literature regarding the specific costs of fish exclusion and passage. Working with FOA awardee Natel Energy, scientists at Oak Ridge National Laboratory were tasked with assessing the capital construction costs for downstream fish exclusion and passage infrastructure. This report used keyword searches of an existing environmental mitigation cost data set and manual extraction of additional cost data associated with protection, mitigation, and enhancement (PM&E) measures related to positive barrier screening and passage from regulatory licensing documents available in the Federal Energy Regulatory Commission (FERC) eLibrary. This approach yielded a total of 50 PM&E mitigation measures with estimated capital construction costs pertaining to positive barrier screens, 142 pertaining to passage studies, and 26 pertaining to passage-related studies. PM&E measures associated with positive barrier screens represented <10% of the 171 total FERC project dockets available in the data set. These data were highly skewed toward conventional relicensing projects, as <7% were associated with new stream development (NSD) projects. Results from these data indicate highly variable costs associated with fish screening, with flow-normalized costs one to two orders of magnitude higher for screening with the highest exclusion capability (≤0.09 in. spacing) compared with coarser screening (1 to 2 in.). Furthermore, estimated capital costs of passage infrastructure were positively related to the scale of the project based on installed capacity for some, but not all, types of passage. These data provide an initial baseline for estimating exclusion and passage costs for hydropower development and may help developers consider options for more fish-friendly generation technologies, though gaps remain relating to a lack of data, particularly for NSD projects. More data may still be available within the FERC eLibrary, but significant effort will be required to manually identify and extract the data for future analyses.

13 HYDRO ENERGY↗

Foam Fracturing Study for Stimulation Development of Enhanced Geothermal Systems

This is a final technical report for the project: Foam Fracturing Study for Stimulation Development of Enhanced Geothermal Systems (EGS). The goal is to demonstrate the feasibility of foam fracturing in EGS applications. The project, led by Oak Ridge National Laboratory (ORNL), was conducted in collaboration with Temple University. The report describes the research activities with Task 1 at ORNL: foam fracturing testing system development and experimental study on foam fracturing, and Task 2 at Temple University: foam testing and foam characterization. Main findings are: 1. A foam fracturing test system has been developed at ORNL, which can be used to perform foam fracturing under pressure up to 6,000 psi. The system monitors foam density during fracturing online and is capable of testing materials in both monotonic and cyclic (up to 50 Hz) injections. 2. Foam fracturing tests were carried out on Charcoal black granite specimens with a blind borehole to the middle length. Two diameters of blind borehole were tested; G2 series: 9.53 mm and G3 series: 4.76 mm. N2-in-water foam was used with AOS as a surfactant. 3. There was a hole-size effect on fracture initiation pressure. The effect is smaller in the case of foam, which was influenced by the high penetrability of gas in foam. Breakdown pressure showed a behavior just as that of fracture pressure; namely an increased value for small hole samples, while the effect in water fracture was more impressive than in foam fracture. 4. Water mass was reduced in foam fracturing within similar range of breakdown pressures. In G2 series, it was decreased from 10.44 g for water fracturing to 5.17 g, representing more than 50% water reduction. Therefore, there is the potential to reduce water use in EGS stimulation through foam fracturing. 5. Use of cyclic injection has the potential to reduce the breakdown pressure and seismicity in EGS application. Experiments using 4-s cycle period found that specimens can be fractured with a low number of cycles. The fatigue pressure was approximately 64 - 77% of monotonic breakdown pressure for water fracturing and 58 - 94% of the breakdown pressure for foam fracturing. 6. A foam stability testing system has been developed that can test foam at 220 Deg C to 2,000 psi. Tested components of candidate foams included two gases: N2 and CO2; 4 surfactants: AOS, SDS, NP-40 and CTAC; 5 stabilizing agents: guar, bentonite clay, borate salt, silica NPs, and GO. 7. N2 and AOS provided the most stable performance over the tested ranges. Furthermore, the AOS foam with stabilizing agents of guar and borate salt (crosslinker) offered the highest half-life of 20 minutes at 200 Deg C and 1,000 psi. 8. Arrhenius equation and modified power law have been demonstrated to fit well the half-time vs. temperature and pressure data, respectively. These relations can be useful to provide the suggestion for future foam stability study. This submission contains the supporting data developed during the project: 1) A final technical report 2) Granite fracturing data in monotonic and cyclic injections with water and N2 foam Foam performance data in various temperatures and pressures, including half-time, is submitted separately.

15 GEOTHERMAL ENERGY↗

Research on Orbital Plasma: Electrodynamics (ROPE)

Enhancements of the temperature of electrons in spacecraft plasma wakes have been reported for numerous cases and this phenomenon has been discussed both empirically and theoretically. However, very few measurements seem to have been made of the ion temperature within plasma wakes-possibly because the great majority of ion measurements were focussed on obtaining geophysical parameters and, hence, were confined to the region ahead of the spacecraft. Recently, however, an enhancement of the temperature of ions was discovered in data obtained in the wake of the Space Shuttle during the Spacelab-2 mission. At the time of that publication, this was the only known observation of this type. Herein, we report an additional case of ion temperature enhancement in a plasma wake. The data were taken during the Tethered Satellite System Reflight mission (TSS-1R) in the wake of the tethered satellite during passive (no current flow) operations. The measurements were obtained with the Differential Ion Flux Probe, or DIFP.

Samir, Uri↗

Ion Temperature Enhancement in the Wakes of Ionospheric Spacecraft

Enhancements of the temperature of electrons in spacecraft plasma wakes have been reported for numerous cases, and this phenomenon has been discussed both empirically and theoretically. However, very few measurements seem to have been made of the ion temperature within plasma wakes, possibly because the great majority of ion measurements were focused on obtaining geophysical parameters and hence were confined to the region ahead of the spacecraft. Recently, however, an enhancement of the temperature of ions was discovered in data obtained in the wake of the space shuttle during the Spacelab 2 mission. At the time of that publication this was the only known observation of this type. Herein we report an additional case of ion temperature enhancement in a plasma wake. The data were taken during the tethered satellite system reflight (TSS-IR) mission in the wake of the tethered satellite during passive (no current flow) operations. The measurements were obtained with the Differential Ion Flux Probe.

Samir, U.↗

Baseline experimental investigation of an electrohydrodynamically assisted heat pipe

The increases in power demand and associated thermal management requirements of future space programs such as potential Lunar/Mars missions will require enhancing the operating efficiencies of thermal management devices. Currently, the use of electrohydrodynamically (EHD) assisted thermal control devices is under consideration as a potential method of increasing thermal management system capacity. The objectives of the currently described investigation included completing build-up of the EHD-Assisted Heat Pipe Test bed, developing test procedures for an experimental evaluation of the unassisted heat pipe, developing an analytical model capable of predicting the performance limits of the unassisted heat pipe, and obtaining experimental data which would define the performance characteristics of the unassisted heat pipe. The information obtained in the currently proposed study will be used in order to provide extensive comparisons with the EHD-assisted performance observations to be obtained during the continuing investigation of EHD-Assisted heat transfer devices. Through comparisons of the baseline test bed data and the EHD assisted test bed data, accurate insight into the performance enhancing characteristics of EHD augmentation may be obtained. This may lead to optimization, development, and implementation of EHD technology for future space programs.

Duncan, A. B.↗

Enhancing Streamflow Forecast and Extracting Insights Using Long-Short Term Memory Networks With Data Integration at Continental Scales

Recent observations with varied schedules and types (moving average, snapshot, or regularly spaced) can help to improve streamflow forecasts, but it is challenging to integrate them effectively. Based on a long short-term memory (LSTM) streamflow model, we tested multiple versions of a flexible procedure we call data integration (DI) to leverage recent discharge measurements to improve forecasts. DI accepts lagged inputs either directly or through a convolutional neural network unit. DI ubiquitously elevated streamflow forecast performance to unseen levels, reaching a record continental-scale median Nash-Sutcliffe Efficiency coefficient value of 0.86. Integrating moving-average discharge, discharge from the last few days, or even average discharge from the previous calendar month could all improve daily forecasts. Directly using lagged observations as inputs was comparable in performance to using the convolutional neural network unit. Importantly, we obtained valuable insights regarding hydrologic processes impacting LSTM and DI performance. Before applying DI, the base LSTM model worked well in mountainous or snow-dominated regions, but less well in regions with low discharge volumes (due to either low precipitation or high precipitation-energy synchronicity) and large interannual storage variability. DI was most beneficial in regions with high flow autocorrelation: it greatly reduced baseflow bias in groundwater-dominated western basins and also improved peak prediction for basins with dynamical surface water storage, such as the Prairie Potholes or Great Lakes regions. However, even DI cannot elevate performance in high-aridity basins with 1-day flash peaks. Despite this limitation, there is much promise for a deep-learning-based forecast paradigm due to its performance, automation, efficiency, and flexibility.

54 ENVIRONMENTAL SCIENCES↗

Investigation of octupole collectivity near the A = 72 shape-transitional point

Enhanced octupole collectivity is expected in the neutron-deficient Ge, Se and Kr isotopes with neutron number N ≈ 40 and has indeed been observed for 70,72 Ge. Shape coexistence and configuration mixing are, however, a notorious challenge for theoretical models trying to reliably predict octupole collectivity in this mass region, which is known to feature rapid shape changes with changing nucleon number and spin of the system. To further investigate the microscopic configurations causing the prolate-oblate-triaxial shape transition at A ≈ 72 and their influence on octupole collectivity, the rare isotopes 72 Se and 74,76 Kr were studied via inelastic proton scattering in inverse kinematics. While significantly enhanced octupole strength of ≈32 Weisskopf units (W.u.) was observed for 72 Se, only strengths of ≈15 W.u. were observed for 74,76 Kr. In combination with existing data, the new data clearly question a simple origin of enhanced octupole strengths around N = 40. Furthermore, the present work establishes two regions of distinct octupole strengths with a sudden strength increase around the A = 72 shape transitional point.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Pioneer 10 observations of the solar wind and its interaction with Jupiter - Plasma electron results

Typical plasma electron spectra obtained during transversal of the Jovian magnetosheath are discussed. Data from the outer magnetosphere show an enhanced energy tail between approximately 50 eV and 200 eV, indicating heating of the solar wind electrons across the Jovian bow shock. Transversal of the inner magnetosphere produced data implying even higher electron temperatures. Results are consistent with ion observations of a high Mach number bow shock and magnetosheath flow field. They are consistent with a contraction of the Jovian magnetosphere resulting from an increase in the solar wind dynamic pressure similar to, but on a larger scale than that observed in the case of the earth's bow shock.

Intriligator, D. S.↗

Development, Validation, and Potential Enhancements to the Second-Generation Operational Aerosol Product at the National Environmental Satellite, Data, and Information Service of the National Oceanic and Atmospheric Administration

A revised (phase 2) single-channel algorithm for aerosol optical thickness, tau(sup A)(sub SAT), retrieval over oceans from radiances in channel 1 (0.63 microns) of the Advanced Very High Resolution Radiometer (AVHRR) has been implemented at the National Oceanic and Atmospheric Administration's National Environmental Satellite Data and Information Service for the NOAA 14 satellite launched December 30, 1994. It is based on careful validation of its operational predecessor (phase 1 algorithm), implemented for NOAA 14 in 1989. Both algorithms scale the upward satellite radiances in cloud-free conditions to aerosol optical thickness using an updated radiative transfer model of the ocean and atmosphere. Application of the phase 2 algorithm to three matchup Sun-photometer and satellite data sets, one with NOAA 9 in 1988 and two with NOAA 11 in 1989 and 1991, respectively, show systematic error is less than 10%, with a random error of sigma(sub tau) approx. equal 0.04. First results of tau(sup A)(sub SAT) retrievals from NOAA 14 using the phase 2 algorithm, and from checking its internal consistency, are presented. The potential two-channel (phase 3) algorithm for the retrieval of an aerosol size parameter, such as the Junge size distribution exponent, by adding either channel 2 (0.83 microns) from the current AVHRR instrument, or a 1.6-microns channel to be available on the Tropical Rainfall Measurement Mission and the NOAA-KLM satellites by 1997 is under investigation. The possibility of using this additional information in the retrieval of a more accurate estimate of aerosol optical thickness is being explored.

Stowe, Larry L.↗

Inter-Comparison of CHARM Data and WSR-88D Storm Integrated Rainfall

A localized precipitation network has been established over a 4000 sq km region of northern Alabama in support of local weather and climate research at the Global Hydrology and Climate Center (GHCC) in Huntsville. This Cooperative Huntsville-Area Rainfall Measurement (CHARM) network is comprised of over 80 volunteers who manually take daily rainfall measurements from 85 sites. The network also incorporates 20 automated gauges that report data at 1-5 minute intervals on a 24 h a day basis. The average spacing of the gauges in the network is about 6 kin, however coverage in some regions benefit from gauges every 1-2 km. The 24 h rainfall totals from the CHARM network have been used to validate Stage III rainfall estimates of daily and storm totals derived from the WSR-88D radars that cover northern Alabama. The Stage III rainfall product is produced by the Lower Mississippi River Forecast Center (LMRFC) in support of their daily forecast operations. The intercomparisons between the local rain gauge and the radar estimates have been useful to understand the accuracy and utility of the Stage III data. Recently, the Stage III and CHARM rainfall measurements have been combined to produce an hourly rainfall dataset at each CHARM observation site. The procedure matches each CHARM site with a time sequence of Stage III radar estimates of precipitation. Hourly stage III rainfall estimates were used to partition the rain gauge values to the time interval over which they occurred. The new hourly rain gauge dataset is validated at selected points where 1-5 minute rainfall measurements have been made. This procedure greatly enhances the utility of the CHARM data for local weather and hydrologic modeling studies. The conference paper will present highlights of the Stage III intercomparison and some examples of the combined radar / rain gauge product demonstrating its accuracy and utility in deriving an hourly rainfall product from the 24 h CHARM totals.

Jedlovec, Gary J.↗

EverGREEN 2045: An Energy Mix to Decarbonize Washington State

Washington State’s future resource mix is likely to be comprised of intermittent renewables and carbon-free generation including hydropower by 2045. Generation will likely be comprised of wind, solar photovoltaic (PV), batteries, pumped storage hydropower (PSH), existing nuclear power plants, and potentially enhanced geothermal systems and advanced nuclear reactor technologies. To assess the cost and stability of the future resource mix, we partner with X-energy (advanced reactor design) and AltaRock Energy (enhanced geothermal system) for proprietary cost data. After estimating the costs of these two new technologies, we design plausible future resource mix scenarios to meet Washington State’s Clean Energy Transformation Act which transitions the state to carbon-free generation by 2045. We assess the cost and stability of the future resource mix with power system analysis tools, finding revenues are sufficient to cover variable operating and maintenance costs for most technologies providing power in 2030 and 2045, but capacity payments or power purchase agreements will likely be necessary for flexible resources, including enhanced geothermal systems and advanced nuclear reactors, to participate in the future resource mix.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

On evaluating the accuracy of SAR sea-ice classification using multifrequency polarimetric AIRSAR data

We investigate how multifrequency and polarimetric synthetic aperture radar (SAR) imagery enhances present capability to discriminate different ice conditions in single-frequency, single-polarization satellite SAR data. Frequencies considered are C- (lambda = 5.6cm), L- (lambda = 24cm) and P- (lambda = 68cm) band. Radar backscatter characteristics of six radiometrically and polarimetrically distinct ice types are selected from a cluster analysis of the multifrequency polarimetric SAR data and used to classify SAR images. Validation of these ice conditions is based on information provided by aerial photos, weather and ice surface measurements acquired at an ice camp, together with airborne passive microwave imagery, and visual analysis of the SAR data. The six identified sea-ice types are: (1) multiyear sea-ice; (2) compressed first year ice; (3) first year rubble and ridges; (4) first year rough ice; (5) first year smooth ice; and (6) thin ice. Open water is absent in all analyzed data. Classification of the SAR imagery into those six ice types is performed using a Bayesian Maximum A Posteriori classifier. Two complete scenes acquired at different dates in different locations are classified. The scenes were chosen such that they are representative of typical ice conditions in the Beaufort Sea in March 1988 and because ancillary information is available for validating the segmentation of various ice surface conditions.

Drinkwater, Mark R.↗

Wind and Structural Loads on Parabolic Trough Solar Collectors at Nevada Solar One

Wind loading is a main contributor to structural design costs of Concentrating Solar Power (CSP) collectors, such as heliostats and parabolic troughs. These structures must resist the mechanical forces generated by turbulent wind. At the same time, the reflector surfaces must exhibit the necessary rigidity to maintain their optimal optical performance in windy conditions. Over two years, NREL conducted comprehensive field measurements of the atmospheric turbulent wind conditions and the resulting structural wind loads on parabolic troughs at the Nevada Solar One (NSO) plant. The measurement set-up included meteorological masts and structural load sensors on four trough rows. Additionally, we commissioned a lidar scanning the horizontal plane over the trough field. This data set catalogs the high-resolution data set characterizing the complex flow field and resulting structural loads on parabolic trough collectors. By providing this first-of-its-kind data set to the CSP community, we aim to enhance the community's understanding of wind-loading experienced by CSP collector structures. This data set will also help design next-generation solar collectors and photovoltaic trackers.

Array↗

Identifying Large Transients within ARTEMIS Solar Wind Data for Nightside Time Domain Electromagnetic Sounding

Mysteries regarding the Moon’s internal composition persist. By studying the induced magnetic fields produced by the Moon in response to changes in the magnetic field of the surrounding solar wind, inferences can be made regarding the associated eddy currents and thus regarding the electrical conductivities of the lunar regions hosting these currents. In this manner, a greater understanding of the Moon’s inner geophysical properties can be garnered. This investigative strategy, known as electromagnetic sounding, can be employed using magnetic field data from the ARTEMIS satellites. In particular, data taken from time intervals in which one satellite is within the lunar wake and within 500 km of the surface while the other is relatively far from the surface immersed within the pristine solar wind. Per Faraday’s Law, the steeper the magnetic transient from the solar wind, the greater the current induced within the Moon, and per Ampère’s Law, the greater this induced current, the larger the magnetic field it produces. Larger signals generally feature higher signal-to-noise ratios (SNRs). Thus, larger transients tend to produce more valuable data in terms of sounding. The enhanced separation between source signal and reaction signal via the aforementioned positioning of the probes during time intervals of interest augments the SNRs as well. Here we discuss tools developed in Python (making use of the PySPEDAS package) that expedites the task of identifying large magnetic transients within these time frames of interest. These exceptional changes in magnetic field are then evaluated for use in electromagnetic sounding as described above. We have identified 51 major transient events (during times of interest) from 8/1/2011 to 7/31/2021. One key hurdle we overcame was identifying and navigating data gaps. These data gaps would often interfere with our time intervals of interest, necessitating an algorithm to avoid them.

Moons↗

Digital Twin Empowered PV Power Prediction

The accurate prediction of photovoltaic (PV) power generation is significant to ensure the economic and safe operation of power systems. To this end, the paper proposes a new digital twin (DT) empowered PV power prediction framework that is capable of ensuring reliable data transmission and employing the DT to achieve high accuracy of power prediction. With this framework, considering potential data contamination in the collected PV data, a generative adversarial network is employed to restore the historical data set, which offers a prerequisite to ensure accurate mapping from the physical space to the digital space. Further, a new DT empowered PV power prediction method is proposed. Therein, we model a DT that encompasses a digital physical model for reflecting the physical operation mechanism and a neural network model (i.e., a parallel network of convolution and bidirectional long-short-term memory model) for capturing the hidden spatial-temporal features. The proposed method enables the use of the DT to take advantages of the digital physical model and the neural network model, resulting in enhanced prediction accuracy. Finally, a real data set is conducted to access the effectiveness of the proposed method.

14 SOLAR ENERGY↗