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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 181 records · Page 10

Evaluating the WFIP2 updates to the HRRR model using scanning Doppler lidar measurements in the complex terrain of the Columbia River Basin

The wind-energy (WE) industry relies on numerical weather prediction (NWP) forecast models as foundational or base models for many purposes, including wind-resource assessment and wind-power forecasting. During the Second Wind Forecast Improvement Project (WFIP2) in the Columbia River Basin of Oregon and Washington, a significant effort was made to improve NWP forecasts through focused model development, to include experimental refinements to the High Resolution Rapid Refresh (HRRR) model physics and horizontal grid spacing. In this study, the performance of an experimental version of HRRR that includes these refinements is tested against a control version, which corresponds to that of the operational HRRR run by National Oceanic and Atmospheric Administration/National Centers for Environmental Protection at the outset of WFIP2. Furthermore, the effects of horizontal grid resolution were also tested by comparing wind forecasts from the HRRR (with 3-km grid spacing) with those from a finer-resolution HRRR nest with 750-m grid spacing. Model forecasts are validated against accurate wind-profile measurements by three scanning, pulsed Doppler lidars at sites separated by a total distance of 71 km. Model skill and improvements in model skill, attributable to physics refinements and improved horizontal grid resolution, varied by season, by site, and during periods of atmospheric phenomena relevant to WE. In general, model errors were the largest below 150 m above ground level (AGL). Experimental HRRR refinements tended to reduce the mean absolute error (MAE) and other error metrics for many conditions, but degradation in skill (increased MAE) was noted below 150 m AGL at the two lowest-elevation sites at night. Finer resolution was found to produce the most significant reductions in the error metrics.

17 WIND ENERGY↗

The Radiation Chemistry of CMPO: Part 2. Alpha Radiolysis

Here, Octylphenyl-N,N-diisobutylcarbamoylmethylphosphine oxide (CMPO) dissolved in dodecane was subjected to α-irradiation using a He-ion beam, 244 Cm isotopic α-rays, and He and Li ions created by the n,α reaction of 10 B in a nuclear reactor. Post-irradiation samples were analyzed for the radiolytically-induced decrease in CMPO concentration, the appearance of degradation products, and their Am solvent extraction distribution ratios. The –G CMPO -value for the radiolytic degradation of CMPO was found to be very low compared to values previously reported for γ-irradiation. Additionally, isotopic irradiation to absorbed α-doses as high as 600 kGy in aerated solution had no effect on Am solvent extraction or stripping. The main CMPO radiolysis products identified in He-ion beam irradiated samples by ESI-MS include amides, an acidic amide, and amines produced by bond rupture on either side of the CMPO carbonyl group. Deaerated samples irradiated using the reactor in the absence of an aqueous phase, or with a dilute nitric acid aqueous phase showed small but measurable decreases in CMPO concentration with increasing absorbed doses. Higher concentrations of nitric acid resulted in lower decomposition rates for the CMPO. The radio-protection by dissolved oxygen and nitric acid previously found for γ-irradiated CMPO also occurs for α-irradiation. This suggests that similar free-radical mechanisms operate in the high-LET system, but with lower degradation yields due to the lower overall radical concentrations produced.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center

Here, the Pathosystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center. Recent changes to PATRIC include a redesign of the web interface and some new services that provide users with a platform that takes them from raw reads to an integrated analysis experience. The redesigned interface allows researchers direct access to tools and data, and the emphasis has changed to user-created genome-groups, with detailed summaries and views of the data that researchers have selected. Perhaps the biggest change has been the enhanced capability for researchers to analyze their private data and compare it to the available public data. Researchers can assemble their raw sequence reads and annotate the contigs using RASTtk. PATRIC also provides services for RNA-Seq, variation, model reconstruction and differential expression analysis, all delivered through an updated private workspace. Private data can be compared by `virtual integration' to any of PATRIC's public data. The number of genomes available for comparison in PATRIC has expanded to over 80 000, with a special emphasis on genomes with antimicrobial resistance data. PATRIC uses this data to improve both subsystem annotation and k-mer classification, and tags new genomes as having signatures that indicate susceptibility or resistance to specific antibiotics.

59 BASIC BIOLOGICAL SCIENCES↗

The PATRIC Bioinformatics Resource Center: expanding data and analysis capabilities

The PathoSystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center funded by the National Institute of Allergy and Infectious Diseases (https://www.patricbrc.org). PATRIC supports bioinformatic analyses of all bacteria with a special emphasis on pathogens, offering a rich comparative analysis environment that provides users with access to over 250 000 uniformly annotated and publicly available genomes with curated metadata. PATRIC offers web-based visualization and comparative analysis tools, a private workspace in which users can analyze their own data in the context of the public collections, services that streamline complex bioinformatic workflows and command-line tools for bulk data analysis. Over the past several years, as genomic and other omics-related experiments have become more cost-effective and widespread, we have observed considerable growth in the usage of and demand for easy-to-use, publicly available bioinformatic tools and services. Here we report the recent updates to the PATRIC resource, including new web-based comparative analysis tools, eight new services and the release of a command-line interface to access, query and analyze data.

59 BASIC BIOLOGICAL SCIENCES↗

Dark Matter Search Results from the PICO - 60 C 3 F 8 Bubble Chamber

New results are reported from the operation of the PICO-60 dark matter detector, a bubble chamber filled with 52 kg of C 3 F 8 located in the SNOLAB underground laboratory. As in previous PICO bubble chambers, PICO-60 C 3 F 8 exhibits excellent electron recoil and alpha decay rejection, and the observed multiple-scattering neutron rate indicates a single-scatter neutron background of less than one event per month. A blind analysis of an efficiency-corrected 1167-kg day exposure at a 3.3-keV thermodynamic threshold reveals no single-scattering nuclear recoil candidates, consistent with the predicted background. In conclusion, these results set the most stringent direct-detection constraint to date on the weakly interacting massive particle (WIMP)-proton spin-dependent cross section at 3.4×10 -41 cm 2 for a 30-GeV c -2 WIMP, more than 1 order of magnitude improvement from previous PICO results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Examination of 1D Solar Cell Model Limitations Using 3D SPICE Modeling: Preprint

To examine the limitations of one-dimensional (1D) solar cell modeling, 3D SPICE-based modeling is used to examine in detail the validity of the 1D assumptions as a function of sheet resistance for a model cell. The internal voltages and current densities produced by this modeling give additional insight into the differences between the 1D and 3D models.

14 SOLAR ENERGY↗

Discrimination of xylene isomers in a stacked coordination polymer

The separation and purification of xylene isomers is an industrially important but challenging process. Developing highly efficient adsorbents is crucial for the implementation of simulated moving bed technology for industrial separation of these isomers. Herein, we report a stacked one-dimensional coordination polymer {[Mn(dhbq)(H 2 O) 2 ], H 2 dhbq = 2,5-dihydroxy-1,4-benzoquinone} that exhibits an ideal molecular recognition and sieving of xylene isomers. Its distinct temperature-adsorbate–dependent adsorption behavior enables full separation of p -, m -, and o -xylene isomers in both vapor and liquid phases. The delicate stimuli-responsive swelling of the structure imparts this porous material with exceptionally high flexibility and stability, well-balanced adsorption capacity, high selectivity, and fast kinetics at conditions mimicking industrial settings. This study may offer an alternative approach for energy-efficient and adsorption-based industrial xylene separation and purification processes.

Science & Technology - Other Topics↗

Effect of Anion Size on Conductivity and Transference Number of Perfluoroether Electrolytes with Lithium Salts

Mixtures of perfluoropolyethers (PFPE) and lithium salts with fluorinated anions are a new class of electrolytes for lithium batteries. Unlike conventional electrolytes wherein electron-donating oxygen groups interact primarily with the lithium cations, the properties of PFPE-based electrolytes appear to be dependent on interactions between the fluorinated anions and the fluorinated backbones. We study these interactions by examining a family of lithium salts wherein the size of the fluorinated anion is systematically increased: lithium bis(fluorosulfonyl)imide (LiFSI), bis(trifluoromethanesulfonyl)imide (LiTFSI) salts and lithium bis(pentafluoroethanesulfonyl)imide (LiBETI). Two short chain perfluoroethers (PFE), one with three repeat units, C6-DMC, and another with four repeat units, C8-DMC were studied; both systems have dimethyl carbonate end groups.We find that LiFSI provides the highest conductivity in both C6-DMC and C8-DMC. These systems also present the lowest interfacial resistance against lithium metal electrodes. The steady-state transference number (t + ss ) was above 0.6 for all of the electrolytes and was an increasing function of anion size. The product of conductivity and the steady-state transference number, a convenient measure of the efficacy of the electrolytes for lithium battery applications, exhibited a maximum at about 20 wt% salt in all electrolytes. Finally, amongst the systems studied, LiFSI/PFE mixtures were the most efficacious electrolytes.

25 ENERGY STORAGE↗

The Wind Forecast Improvement Project (WFIP): A Public–Private Partnership Addressing Wind Energy Forecast Needs

The Wind Forecast Improvement Project (WFIP) is a public–private research program, the goal of which is to improve the accuracy of short-term (0–6 h) wind power forecasts for the wind energy industry. WFIP was sponsored by the U.S. Department of Energy (DOE), with partners that included the National Oceanic and Atmospheric Administration (NOAA), private forecasting companies (WindLogics and AWS Truepower), DOE national laboratories, grid operators, and universities. WFIP employed two avenues for improving wind power forecasts: first, through the collection of special observations to be assimilated into forecast models and, second, by upgrading NWP forecast models and ensembles. The new observations were collected during concurrent year-long field campaigns in two high wind energy resource areas of the United States (the upper Great Plains and Texas) and included 12 wind profiling radars, 12 sodars, several lidars and surface flux stations, 184 instrumented tall towers, and over 400 nacelle anemometers. Results demonstrate that a substantial reduction (12%–5% for forecast hours 1–12) in power RMSE was achieved from the combination of improved numerical weather prediction models and assimilation of new observations, equivalent to the previous decade’s worth of improvements found for low-level winds in NOAA/National Weather Service (NWS) operational weather forecast models. Data-denial experiments run over select periods of time demonstrate that up to a 6% improvement came from the new observations. Ensemble forecasts developed by the private sector partners also produced significant improvements in power production and ramp prediction. Based on the success of WFIP, DOE is planning follow-on field programs.

17 WIND ENERGY↗

The Second Wind Forecast Improvement Project (WFIP 2): General Overview

In 2015 the U.S. Department of Energy initiated a four-year study, the second Wind Forecast Improvement Project (WFIP 2), to improve the representation of boundary-layer physics and related processes in mesoscale models for better wind and wind power forecasts. This goal challenges numerical weather prediction models in complex terrain due to inherent assumptions underlying their boundary-layer parameterizations. The WFIP 2 effort involved the wind industry, universities, NOAA, and DOE's national laboratories in an integrated observational and modeling study. Observations spanned 18-months to assure a full annual cycle of continuously recorded observations from remote-sensing and in situ measurement systems. The study area comprised the Columbia Basin of eastern Washington and Oregon, containing more than 4 GW of installed wind capacity; nests of observational systems captured important atmospheric scales from mesoscale to NWP sub-grid scale. Model improvements targeted NOAA's High-Resolution Rapid Refresh (HRRR) model to facilitate transfer of improvements to NWS operational forecast models. This paper describes the general WFIP 2 scope and objectives, the particular scientific challenges of improving wind forecasts in complex terrain, early successes of the project, and an integrated approach to archiving observations and model output. It provides an introduction for a set of more detailed BAMS papers addressing WFIP 2 observational science, modeling challenges and solutions, practical transfer of boundary layer advances to industry use, and advances in coupling improved mesoscale models to microscale models that can represent interactions between wind plants and the atmosphere.

WFIP2, boundary layer, complex terrain, forecastin↗

Characterizing NWP Model Errors Using Doppler-Lidar Measurements of Recurrent Regional Diurnal Flows: Marine-Air Intrusions into the Columbia-River Basin

Ground-based Doppler-lidar instrumentation provides atmospheric wind data at dramatically improved accuracies and spatial/temporal resolutions. These capabilities have provided new insights into atmospheric flow phenomena, but they also should have a strong role in NWP model improvement. Insight into the nature of model errors can be gained by studying recurrent atmospheric flows, here a regional summertime diurnal sea breeze and subsequent marine-air intrusion into the arid interior of Oregon-Washington, where these winds are an important windenergy resource. These marine intrusions were sampled by three scanning Doppler lidars in the Columbia-River Basin as part of the Second Wind Forecast Improvement Project (WFIP2), using data from summer 2016. Lidar time-height cross sections of wind speed identified eight days when the diurnal-flow cycle, (peak wind speeds at midnight, afternoon minima) was obvious and strong. Eight-day composite time-height cross sections of lidar wind speeds are used to validate those generated by the operational NCEP-HRRR model. HRRR simulated the diurnal wind cycle, but produced errors in the timing of onset and significant errors due to a premature nighttime demise of the intrusion flow, producing low-bias errors of 6 m s-1 . Day-to-day and in the composite, whenever a marine intrusion occurred, HRRR made these same errors. The errors occurred under a range of gradient wind conditions indicating that they resulted from the misrepresentation of physical processes within a limited region around the measurement locations. Because of their generation within a limited geographical area, field-measurement programs can be designed to find and address the sources of these NWP errors.

Banta, Robert M.↗