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Wind Turbine Sound Setbacks and Supply Curves: Ordinances and Extrapolated Trends, 110 Hub Height, 130 Rotor Diameter

This dataset provides a comprehensive set of wind turbine sound setbacks from every residential structure in the contiguous United States (CONUS). A sound setback is defined as the minimum required distance between a residential structure and a hypothetical turbine installation site to ensure that modeled sound levels received at the residence do not exceed local sound ordinances, which are commonly expressed in A-weighted decibels (dBA). Therefore, sound setbacks are a local spatial assessment combining multiple factors, including the sound pressure curve as a function of the observer location (distance and direction) relative to the turbine, local sound regulations, and the geographical distribution of residential structures. The dataset is organized into multiple scenario-based products, detailed as follows: 1. Existing and extrapolated sound setbacks. An existing scenario characterizes sound setbacks only in states or counties that have implemented sound regulations as of 2022. The extrapolated scenarios extend a constant sound threshold to counties that lack explicit sound regulations, with thresholds ranging from 35 to 60 dBA, in 5-dBA increments reflecting the variation observed in current sound ordinances. 2. Sound setbacks in directional and worst scenarios. The directional scenario accounts for the distance and orientation of residential structures relative to a hypothetical turbine location, utilizing the turbine's sound emissions in that specific direction. In contrast, the worst scenario takes loudest sound level at each distance step from the turbine, irrespective of directional considerations, which aligns with current industry practice. 3. Supply curves for Open and Reference Access scenarios. This dataset includes supply curves generated by the reV model, which integrates each of the above sound setbacks into both Open and Reference siting scenarios. In addition, two Open and Reference baselines scenarios were included which do not consider sound setbacks for comparative analysis. All sound setback data are stored in TIF files, with partial maps of the data provided in PNG format. The values in the sound setback raster range from 0 to 1, representing the fraction of developable land within a 90 meter by 90 meter pixel due to sound ordinances. A value of 0 indicates areas where wind energy development is prohibited, while a value of 1 signifies areas fully permissible. The wind turbine parameters used in the sound modeling are based on the land-based turbine from International Energy Agency (IEA), featuring a rated electrical power of 3.4 MW, a rotor diameter of 130 meters, and a hub height of 110 meters. The atmospheric conditions, including wind speed/direction, turbulence, air temperature, relative humidity, and air pressure, that drive the sound generation are obtained from the WIND Toolkit dataset.

Array

Performance of wind assessment datasets in United States coastal areas

The atmospheric dynamics that occur near the intersection of land and water offer exciting and challenging opportunities for wind energy deployment in coastal locations. New models and tools are continually being developed in support of wind resource assessment, and three recent products are explored in this work for their performance in representing characteristics of the wind resource at coastal locations: the Global Wind Atlas 3 (GWA3), the 2023 National Offshore Wind dataset (NOW-23), and the wind climate simulations that are a component of the Wind Integration National Dataset (WIND) Toolkit Long-Term Ensemble Dataset (WTK-LED Climate). These relatively new products are freely available and user-friendly so that anyone – from a utility-scale developer to a resident or business owner – can evaluate the potential for wind energy generation at their location of interest. The validations in this work provide guidance on the accuracy of wind resource assessments for coastal customers interested in installing small or midsize wind turbines (≤ 1 MW in capacity) to support energy needs at the residential, business, or community scale, such as the island and remotely located participants of the U.S. Department of Energy's Energy Transitions Initiative Partnership Project. At 23 coastal locations across the United States, dataset performance varies according to different evaluation metrics. All three recent datasets tend to overestimate the observed coastal wind resource. GWA3 produces the smallest annual average wind speed relative errors, whereas WTK-LED Climate is in best agreement in terms of representing diurnal wind speed cycles. NOW-23 is the highest performing of the datasets for representing seasonal and interannual trends in the coastal wind resource. While GWA3 and WTK-LED Climate are relatively insensitive to the dataset output heights selected for wind resource assessment at small and midsize wind turbine hub heights (20–60 m), significant variation in the NOW-23 representation of wind shear across the wind profile in the lowest 100 m of the atmosphere leads to notable differences in wind speed estimates according to the dataset output heights selected for evaluation. GWA3 exhibits challenges in the representation of observed wind speed diurnal cycles at small and midsize turbine hub heights, likely due to the dataset's consistent treatment of hourly wind speed trends regardless of altitude.

17 WIND ENERGY

Bias Correcting NOAA's High-Resolution Rapid Refresh (HRRR) Wind Resource Data for Grid Integration Applications [Slides]

Many weather years of high-quality wind data are widely accepted in the grid integration community to be important for studying wind energy technical potential, energy system operations, and grid resilience. NREL makes high-quality wind and solar resource data available. NREL's Grid-Atmosphere workshop (March 2024) identified NREL National Solar Radiation Database as widely used in grid integration modeling, but there is less agreement on commonly used wind datasets. One important factor identified by ESIG's 2023 report 'Weather Dataset Needs for Planning and Analyzing Modern Power Systems' for gold standard wind data is regular updates. To address the need for regular updates, NREL's team can now process all currently available and regularly updated High-Resolution Rapid Refresh (HRRR) outputs. HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Administration (NOAA) (Dowell et al., 2022). One barrier to NREL using HRRR is systematic bias and consistency with NREL's existing wind datasets (e.g. WIND Toolkit, 'WTK') across weather years. To address this barrier, we show that the HRRR can be interpolated and bias-corrected to be consistent with NRE's existing datasets. We call the new dataset BC-HRRR (bias-corrected HRRR). As with historical datasets like the WTK, BC-HRRR is intended for use in grid integration modeling (e.g., capacity expansion, production cost, and resource adequacy modeling). BC-HRRR's (2015-present) consistency with WTK (2007-2013) allows NREL to extend internal grid integration tooling with 15+ weather years of wind data with low-overhead extensibility to future years as they are made available by NOAA. The rest of this slide deck documents the BC-HRRR processing methods, validation, and its implications for intended use.

17 WIND ENERGY

NASA Tech Briefs, January 2013

Topics include: Single-Photon-Sensitive HgCdTe Avalanche Photodiode Detector; Surface-Enhanced Raman Scattering Using Silica Whispering-Gallery Mode Resonators; 3D Hail Size Distribution Interpolation/Extrapolation Algorithm; Color-Changing Sensors for Detecting the Presence of Hypergolic Fuels; Artificial Intelligence Software for Assessing Postural Stability; Transformers: Shape-Changing Space Systems Built with Robotic Textiles; Fibrillar Adhesive for Climbing Robots; Using Pre-Melted Phase Change Material to Keep Payloads in Space Warm for Hours without Power; Development of a Centrifugal Technique for the Microbial Bioburden Analysis of Freon (CFC-11); Microwave Sinterator Freeform Additive Construction System (MS-FACS); DSP/FPGA Design for a High-Speed Programmable S-Band Space Transceiver; On-Chip Power-Combining for High-Power Schottky Diode-Based Frequency Multipliers; FPGA Vision Data Architecture; Memory Circuit Fault Simulator; Ultra-Compact Transputer-Based Controller for High-Level, Multi-Axis Coordination; Regolith Advanced Surface Systems Operations Robot Excavator; Magnetically Actuated Seal; Hybrid Electrostatic/Flextensional Mirror for Lightweight, Large-Aperture, and Cryogenic Space Telescopes; System for Contributing and Discovering Derived Mission and Science Data; Remote Viewer for Maritime Robotics Software; Stackfile Database; Reachability Maps for In Situ Operations; JPL Space Telecommunications Radio System Operating Environment; RFI-SIM: RFI Simulation Package; ION Configuration Editor; Dtest Testing Software; IMPaCT - Integration of Missions, Programs, and Core Technologies; Integrated Systems Health Management (ISHM) Toolkit; Wind-Driven Wireless Networked System of Mobile Sensors for Mars Exploration; In Situ Solid Particle Generator; Analysis of the Effects of Streamwise Lift Distribution on Sonic Boom Signature; Rad-Tolerant, Thermally Stable, High-Speed Fiber-Optic Network for Harsh Environments; Towed Subsurface Optical Communications Buoy; High-Collection-Efficiency Fluorescence Detection Cell; Ultra-Compact, Superconducting Spectrometer-on-a-Chip at Submillimeter Wavelengths; UV Resonant Raman Spectrometer with Multi-Line Laser Excitation; Medicine Delivery Device with Integrated Sterilization and Detection; Ionospheric Simulation System for Satellite Observations and Global Assimilative Model Experiments - ISOGAME; Airborne Tomographic Swath Ice Sounding Processing System; flexplan: Mission Planning System for the Lunar Reconnaissance Orbiter; Estimating Torque Imparted on Spacecraft Using Telemetry; PowderSim: Lagrangian Discrete and Mesh-Free Continuum Simulation Code for Cohesive Soils; Multiple-Frame Detection of Subpixel Targets in Thermal Image Sequences; Metric Learning to Enhance Hyperspectral Image Segmentation; Basic Operational Robotics Instructional System; Sheet Membrane Spacesuit Water Membrane Evaporator; Advanced Materials and Manufacturing for Low-Cost, High-Performance Liquid Rocket Combustion Chambers; Motor Qualification for Long-Duration Mars Missions.

Source record

Super-Resolution for Renewable Energy Resource Data with Wind from Reanalysis Data and Application to Ukraine

With a potentially increasing share of the electricity grid relying on wind to provide generating capacity and energy, there is an expanding global need for historically accurate, spatiotemporally continuous, high-resolution wind data. Conventional downscaling methods for generating these data based on numerical weather prediction have a high computational burden and require extensive tuning for historical accuracy. In this work, we present a novel deep learning-based spatiotemporal downscaling method using generative adversarial networks (GANs) for generating historically accurate high-resolution wind resource data from the European Centre for Medium-Range Weather Forecasting Reanalysis version 5 data (ERA5). In contrast to previous approaches, which used coarsened high-resolution data as low-resolution training data, we use true low-resolution simulation outputs. We show that by training a GAN model with ERA5 as the low-resolution input and Wind Integration National Dataset Toolkit (WTK) data as the high-resolution target, we achieved results comparable in historical accuracy and spatiotemporal variability to conventional dynamical downscaling. This GAN-based downscaling method additionally reduces computational costs over dynamical downscaling by two orders of magnitude. We applied this approach to downscale 30 km, hourly ERA5 data to 2 km, 5 min wind data for January 2000 through December 2023 at multiple hub heights over Ukraine, Moldova, and part of Romania. With WTK coverage limited to North America from 2007–2013, this is a significant spatiotemporal generalization. The geographic extent centered on Ukraine was motivated by stakeholders and energy-planning needs to rebuild the Ukrainian power grid in a decentralized manner. This 24-year data record is the first member of the super-resolution for renewable energy resource data with wind from the reanalysis data dataset (Sup3rWind).

17 WIND ENERGY

Alaska Meteorology, Energy, and Transmission (MET) Toolkit

The Alaska MET (Meteorology, Energy, and Transmission) Toolkit is the National Laboratory of the Rockies' (NLR) new flagship atmospheric dataset, designed to support comprehensive long-term planning and operations across the entire power sector. Serving as the regional counterpart to CONUS-wide HRRR MET Toolkit, this dataset provides a comprehensive, high-fidelity meteorological record covering Alaska.The Alaska MET Toolkit is delivered at an hourly resolution on a standardized 2-km horizontal grid. This dataset is repackaged from the National Oceanic and Atmospheric Administration's (NOAA) operational High-Resolution Rapid Refresh for Alaska (HRRR-AK) forecasts. Spanning from 2019 to 2025, it overcomes the technical barriers of native weather models by providing spatial regridding from the native 3-km HRRR-AK horizontal resolution to a 2-km grid, temporal gap-filling, and vertical interpolation at key energy-relevant heights. By delivering highly accurate, validation-backed data across a comprehensive suite of atmospheric variables - including temperature, pressure, humidity, and wind characteristics - the Alaska MET Toolkit provides a highly accessible and strictly standardized foundation for modern power system modeling.

17 WIND ENERGY

Using multiple high-resolution datasets to benchmark the energy exascale earth system model (E3SM) for renewable resource assessment

The United States is accelerating its shift toward a renewable energy system. However, renewable resources, which harness energy from the Earth system, are susceptible to both present-day climate variability and future climate change. For example, variations in regional climate can alter renewable energy production patterns and site viability. The use of high-resolution climate model projections can therefore facilitate and may be critical to long-term planning of renewable energy investments. However, climate models must first be validated for renewable resource assessment. This research employs multiple high-spatiotemporal-resolution datasets to assess the capability of the Department of Energy’s (DOE) Energy Exascale Earth System Model version 2 North American Regionally Refined Model (E3SMv2-NARRM) for predicting multi-year climatological values of solar and wind energy capacity factors in the continental U.S., with a focus on regional and seasonal variability. Present-day E3SMv2-NARRM simulations are compared with reported utility-scale production data obtained from the Energy Information Administration (EIA). In addition, E3SMv2-NARRM data are evaluated against non-climate benchmark models from the National Renewable Energy Laboratory, including the Wind Integration National Dataset Toolkit and the National Solar Radiation Database (NSRDB), as well as three wind energy datasets from PLUSWIND. Our analysis indicates that solar capacity factors from E3SM closely match those from the NSRDB dataset. However, both datasets tend to overestimate values by 10% in comparison to EIA data. Furthermore, biases in wind capacity factors within E3SM are notably pronounced in the West Coast regions, where the seasonal cycle diverges from EIA data.

Energy forecasting, Capacity factor, Renewable ene

On the effectiveness of neural operators at zero-shot weather downscaling

Machine-learning (ML) methods have shown great potential for weather downscaling. These data-driven approaches provide a more efficient alternative for producing high-resolution weather datasets and forecasts compared to physics-based numerical simulations. Neural operators, which learn solution operators for a family of partial differential equations, have shown great success in scientific ML applications involving physics-driven datasets. Neural operators are grid-resolution-invariant and are often evaluated on higher grid resolutions than they are trained on, i.e., zero-shot super-resolution. Given their promising zero-shot super-resolution performance on dynamical systems emulation, we present a critical investigation of their zero-shot weather downscaling capabilities, which is when models are tasked with producing high-resolution outputs using higher upsampling factors than are seen during training. To this end, we create two realistic downscaling experiments with challenging upsampling factors (e.g., 8x and 15x) across data from different simulations: the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) and the Wind Integration National Dataset Toolkit. While neural operator-based downscaling models perform better than interpolation and a simple convolutional baseline, we show the surprising performance of an approach that combines a powerful transformer-based model with parameter-free interpolation at zero-shot weather downscaling. We find that this Swin-Transformer-based approach mostly outperforms models with neural operator layers in terms of average error metrics, whereas an Enhanced Super-Resolution Generative Adversarial Network-based approach is better than most models in terms of capturing the physics of the ground truth data. We suggest their use in future work as strong baselines.

17 WIND ENERGY

CROCUS Urban Canyons - Space Science and Engineering Center (SPARC) Doppler lidar data

This is the netCDF format output from the Halo Photonics Streamline XR Doppler lidar that was deployed next to the Space Science and Engineering Center (SPARC) trailer at the University of Illnois-Chicago greenhouse parking lot during CROCUS Urban Canyons. The purpose of collecting this dataset is to provide vertical and horizontal wind profiles for studying the characteristics of turbulence over the urban canyon of Chicago. This data contains the radial velocity, intensity, and backscatter from the vertical profile, range height indicator, and sector scans that were performed over both Intensive Operating Period 1 and 2 of CROCUS Urban Canyons. There are four different types of files: * The Range Height Indicator (RHI) files contain scans that are along a constant azimuth, spanning the entire hemisphere of elevation values above the surface. * The Velocity Azimuth Display (VAD) files contain the raw radial velocity data from the 6-beam, 60 degree scans. * The User1 files contain stacked Plan Position Indicator scans over a 45 degree quadrant over downtown Chicago. * The Stare files contain vertically pointing scans. These are standard netCDF files that can be opened using xarray. The VAD scans can be processed from their raw radial velocities to horizontal wind speeds with the Atmospheric data Community Toolkit (https://arm-doe.github.io/ACT/).

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC WINDS

NASCAP-2K: An Overview

Nascap-2k is the modern replacement for the older 3-D charging codes NASCAP/GEO, NASCAP/LEO, POLAR, and DynaPAC. Built on the DynaPAC kernel and incorporating surface charging, environment and space potential models from the older codes, Nascap-2k performs charging calculations for a wide variety of space environments under control of a unified graphical interface. In this paper we illustrate the use of Nascap-2k for spacecraft charging calculations. We touch on some of the unique physical and mathematical models on which the code is based. Examples/demos include the use of Object Toolkit, charging calculations in geosynchronous substorm, solar wind, low earth orbit, and auroral environments, and display and analysis of surface potentials, space potentials and particle trajectories.

Mandell, M. J.

Analysis of Surface Charging for a Candidate Solar Sail Mission Using Nascap-2k

The characterization of the electromagnetic interaction for a solar sail in the solar wind environment and identification of viable charging mitigation strategies are critical solar sail mission design task. Spacecraft charging has important implications both for science applications and for lifetime and reliability issues of sail propulsion systems. To that end, surface charging calculations of a candidate 150-meter-class solar sail spacecraft for the 0.5 AU solar polar and 1.0 AU L1 solar wind environments are performed. A model of the spacecraft with candidate materials having appropriate electrical properties is constructed using Object Toolkit. The spacecraft charging analysis is performed using Nascap-2k, the NASA/AFRL sponsored spacecraft charging analysis tool. Nominal and atypical solar wind environments appropriate for the 0.5 AU and 1.0 AU missions are used to establish current collection of solar wind ions and electrons. Finally, a geostationary orbit environment case is included to demonstrate a bounding example of extreme (negative) charging of a solar sail spacecraft. Results from the charging analyses demonstrate that minimal differential potentials (and resulting threat of electrostatic discharge) occur when the spacecraft is constructed entirely of conducting materials, as anticipated from standard guidelines for mitigation of spacecraft charging issues. Examples with dielectric materials exposed to the space environment exhibit differential potentials ranging from a few volts to extreme potentials in the kilovolt range.

Parker, Linda Neergaard

Analysis of Surface Charging for a Candidate Solar Sail Mission Using NASCAP-2K

The characterization of the electromagnetic interaction for a solar sail in the solar wind environment and identification of viable charging mitigation strategies are critical solar sail mission design tasks. Spacecraft charging has important implications both for science applications and for lifetime and reliability issues of sail propulsion systems. To that end, surface charging calculations of a candidate 150-meter-class solar sail spacecraft for the 0.5 AU solar polar and 1.9 AU LI solar wind environments are performed. A model of the spacecraft with candidate materials having appropriate electrical properties is constructed using Object Toolkit. The spacecraft charging analysis is performed using Nascap-2k. the NASA/AFRL sponsored spacecraft charging analysis tool. Nominal and atypical solar wind environments appropriate for the 0.5 AU and 1.0 AU missions are used to establish current collection of solar wind ions and electrons. Finally, a geostationary orbit environment case is included to demonstrate a bounding example of extreme (negative) charging of a solar sail spacecraft. Results from the charging analyses demonstrate that minimal differential potentials (and resulting threat of electrostatic discharge) occur when the spacecraft is constructed entirely of conducting materials, as anticipated from standard guidelines for mitigation of spacecraft charging issues. Examples with dielectric materials exposed to the space environment exhibit differential potentials ranging from a few volts to extreme potentials in the kilovolt range.

Parker, Linda Neergaard

Analysis Of Surface Charging For A Candidate Solar Sail Mission Using Nascap-2k

The characterization of the electromagnetic interaction for a solar sail in the solar wind environment, and identification of viable charging mitigation strategies, is a critical solar sail mission design task, as spacecraft charging has important implications both for science applications and for sail lifetime. To that end, we have performed surface charging calculations of a candidate 150-meter-class solar sail spacecraft for the 0.5 solar polar orbit and a 1.0 AU L1 orbit. We construct a model of the spacecraft with candidate materials having appropriate electrical properties using Object Toolkit and perform the spacecraft charging analysis using NASCAP-2k, the NASA/AFRL sponsored spacecraft charging analysis tool. We use nominal and atypical solar wind environments appropriate for the 0.5 AU and 1.0 AU missions to establish current collection of solar wind ions and electrons. In addition, we include a geostationary orbit case to demonstrate a bounding example of extreme (negative) charging of a solar sail spacecraft in the geostationary orbit environment. Results form the charging analysis demonstrate that minimal differential potentials (and resulting threat of electrostatic discharge) occur when the spacecraft is constructed entirely of conducting materials, as expected. Examples with dielectric materials exposed to the space environment exhibit differential potentials ranging from a few volts to extreme potentials in the kilovolt range.

Minow, Joseph

Analysis of Surface Charging for a Candidate Solar Sail Mission Using NASCAP-2K

The characterization of the electromagnetic interaction for a solar sail in the solar wind environment, and identification of viable charging mitigation strategies, is a critical solar sail mission design task, as spacecraft charging has important implications both for science applications and for sail lifetime. To that end, we have performed surface charging calculations of a candidate 150-meter-class solar sail spacecraft for the 0.5 AU solar polar orbit and a 1.0 AU L1 orbit. We construct a model of the spacecraft with candidate materials having appropriate electrical properties using Object Toolkit and perform the spacecraft charging analysis using NASCAP-2k, the NASA/AFRL sponsored spacecraft charging analysis tool. We use nominal and atypical solar wind environments appropriate for the 0.5 AU and 1.0 AU missions to establish current collection of solar wind ions and electrons. In addition, we include a geostationary orbit case to demonstrate a bounding example of extreme (negative) charging of a solar sail spacecraft in the geostationary orbit environment. Results from the charging analysis demonstrate that minimal differential potentials (and resulting threat of electrostatic discharge) occur when the spacecraft is constructed entirely of conducting materials, as expected. Examples with dielectric materials exposed to the space environment exhibit differential potentials ranging from a few volts to extreme potentials in the kilovolt range.

Parker, Linda Neergaard

Analysis of Surface Charging for a Candidate Solar Sail Mission Using Nascap-2k

The characterization of the electromagnetic interaction for a solar sail in the solar wind environment, and identification of viable charging mitigation strategies, is a critical solar sail mission design task, as spacecraft charging has important implications both for science applications and for sail lifetime. To that end, we have pexformed some preliminary surface charging calculations of a candidate 150 meter class solar sail spacecraft for the 0.5 AU solar polar orbit and a 1.0 AU L1 orbit. We construct a model of the spacecraft with candidate materials having appropriate electrical properties using Object Toolkit and perform the spacecraft charging analysis using Nascap-2k, the NASA/AFRL sponsored spacecraft charging analysis tool. We use mean and extreme solar wind environments appropriate for the 0.5 AU and 1.0 AU missions to establish current collection of solar wind ions and electrons. In addition, we include a geostationary orbit case to demonstrate a bounding example of extreme (negative) charging of a solar sail spacecraft in the geostationary orbit environment. Results from the charging analysis demonstrate that minimal differential potentials (and resulting threat of electrostatic discharge) occur when the spacecraft is constructed entirely of conducting materials, as expected. Examples with dielectric materials exposed to the space environment exhibit differential potentials ranging from a few volts to extreme potentials in the kilovolt range. Recommendations for further analyses include calculations of wake effects, surface current densities, and environments effects on conductivities.

Neergaard, Linda F.

Community-Centric Microgrid Feasibility Analysis Framework to Accelerate Resilience of Island Communities

Marine energy offers a reliable energy solution for island and coastal communities, which often lack traditional local generation, to support their transition to energy independence and reduce reliance on externally imported fuels. Successful deployment of new technologies in these isolated locations requires community acceptance and approval from the outset, as these communities typically lack the financial and technical resources to operate and maintain new systems. This report presents a community-centric microgrid planning framework for remote coastal and island communities. Community engagement is integrated as the first step in the planning process, incorporating community profiles and visions into energy development scenarios. A case study was conducted in St. George, Pribilof Islands, Alaska, which relies entirely on diesel yet has significant wind and wave energy potential. Community engagement revealed a unique history and current economic status, with an interest in adopting advanced energy technologies despite past failures. Various microgrid configurations were optimized, considering different technologies to meet current and future energy needs while balancing cost and energy resilience. Wave energy converters (WECs) were a key component, integrated with other energy sources using the Xendee optimization tool. The Marine Energy Microgrid Toolkit, developed as part of this work, uses commercial power system analysis tools to optimize and analyze microgrid scenarios. The developed framework and toolkit can be applied to island and coastal communities to enhance resilience and support microgrid deployments. Future enhancements will include incorporating new marine resources, developing dynamic models, and automating the integration of Xendee and PowerFactory simulations.

02 PETROLEUM

Block Island Survey and Deployment Operations Data

This dataset contains survey, navigation, and platform-design data supporting instrument deployment and positioning during the 2016-2017 RODEO field operations at Block Island. It includes an acoustic localization software toolkit and its Block Island position solutions, R/V Tioga ship navigation and underway data, CTD casts, ship-track charts, and engineering designs for the deployed moorings and arrays.

17 WIND ENERGY

SmaggIce 2D Version 1.8: Software Toolkit Developed for Aerodynamic Simulation Over Iced Airfoils

SmaggIce 2D version 1.8 is a software toolkit developed at the NASA Glenn Research Center that consists of tools for modeling the geometry of and generating the grids for clean and iced airfoils. Plans call for the completed SmaggIce 2D version 2.0 to streamline the entire aerodynamic simulation process--the characterization and modeling of ice shapes, grid generation, and flow simulation--and to be closely coupled with the public-domain application flow solver, WIND. Grid generated using version 1.8, however, can be used by other flow solvers. SmaggIce 2D will help researchers and engineers study the effects of ice accretion on airfoil performance, which is difficult to do with existing software tools because of complex ice shapes. Using SmaggIce 2D, when fully developed, to simulate flow over an iced airfoil will help to reduce the cost of performing flight and wind-tunnel tests for certifying aircraft in natural and simulated icing conditions.

Choo, Yung K.