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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Combined TREAT-LOC & SATS Integral LOCA Experiment Plan

The Transient Reactor Test Facility (TREAT) loss-of-coolant (LOC) and highburnup (HBu) experiment series, along with the Severe Accident Test Station (SATS) HBu experiment series, are integral LOC accident (LOCA) experiments planned under the Department of Energy (DOE) Advanced Fuels Campaign (AFC) program, which aims to support burnup extension needs by addressing identified R&D priorities in order to achieve an improved understanding of fuel fragmentation, relocation, and dispersal (FFRD) of HBu fuel during LOCA events. Priorities have been identified by the Electric Power Research Institute (EPRI)’s Collaborative Research on Advanced Fuel Technologies (CRAFT) Fuel Performance and Testing Technical Experts Group (FPTTEG). The data produced under this plan will be used to further validate and confirm existing models and inform future R&D and model development. The experimental program was specifically developed to address data gaps and opportunities identified via detailed review of the existing public knowledge base on LOCA FFRD, as well as reviewing specific experimental development activities regarding prototypic LOCA conditions for light-water reactor (LWR) systems. The test program relies on a unique combination of in- and out-of-pile experimental approaches to provide a clear tieback to the existing integral and semi-integral LOCA experiment database, using state-of-the-art facilities. More importantly, the program will systematically investigate the impacts of prototypic HBu fuel/cladding thermomechanical behaviors under postulated LWR LOCA conditions not yet fully investigated. These conditions correspond with prototypic decay-energy heatup (DEH) and stored-energy heatup (SEH) conditions. First, TREAT’s unique capability will enable the first evaluation of the impact of SEH conditions on HBu fuels. The test program will emphasize the development of an improved mechanistic understanding of key phenomena through independent experimental systems, development of a database to support fuel performance modeling tools, world-leading advanced materials characterization, and the most advanced approach to in situ diagnostics ever deployed to evaluate FFRD. The results will represent a significant leap forward in evaluating prototypic conditions and novel data to support modeling development and validation, as well as to inform the technical basis for LOCA-induced FFRD.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Application of community data to surface complexation modeling framework development: Iron oxide protolysis

This study presents a comprehensive community data-driven surface complexation modeling framework for simulating potentiometric titration of mineral surfaces. Compiled community data for ferrihydrite, goethite, hematite, and magnetite are fit to produce representative protolysis constants that can reproduce potentiometric titration data collected from multiple literature sources. Using this framework, the impact of surface complexation model type and surface site density (SSD) on the fit quality and protolysis constants can be readily evaluated. For example, the non-electrostatic model yielded a poor data fit compared to diffuse double layer model and constant capacitance models due to the absence of known surface charge effects. Regardless of the choice of iron oxide mineral, pK a1 decreased with increasing SSD while the opposite tendency was observed for pK a2 . This newly developed framework demonstrates a method to reconcile community data-wide potentiometric titration data using Findable, Accessible, Interoperable, Reusable data principles to produce mineral protolysis constants that improve robustness of surface complexation models for applications in metal sorption and reactive transport modeling. The framework is readily expandable (as community data increase) and extensible (as the number of minerals increase). The framework provides a path forward for developing self-consistent, comprehensive, and updateable surface complexation databases for surface complexation and reactive transport modeling.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Integration of Models for the Hanford Integrated Disposal Facility Performance Assessment - 18541

The Department of Energy Office of River Protection and its contractors have performed a performance assessment for the near-surface disposal of low-level and mixed low-level waste at the Hanford Integrated Disposal Facility. The long-term performance of the Hanford Integrated Disposal Facility to be protective of human health and the environment was evaluated under the requirements of United States Department of Energy Order 435.1, Radioactive Waste Management. Computer simulations were performed to evaluate whether or not the disposal facility would comply with the performance objectives specified in the order. The evaluation was performed using numerical models to simulate source term releases from vitrified and cement-based waste forms. Source term releases were subsequently transported through the facility into the natural system beneath the facility (comprised of an 85-meter thick vadose zone and thinner but highly conductive saturated zone overlying basalt) to a point of compliance 100-meters downstream from the disposed waste. Due to the differing scales in the finite difference models developed for the source terms and those developed for the natural system, numerical models for source term release and natural system flow and transport were not directly coupled. Instead, the output from the source term simulations were used as input to the natural system flow and transport simulations. The decoupling of the modeled systems makes it difficult to explore synergies and investigate the impact of parameter uncertainties. In order to explore system synergies and evaluate parameter uncertainty, an integrated system model was developed that includes source term release models, natural system transport models, and dose calculations. This paper will describe how the numerical models were used to develop abstractions that could be incorporated into the integrated system level model that was then used to explore system synergies and parameter uncertainties. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Measurements of e p → e ' π + π – p ' cross sections with CLAS at 1.40 GeV < W < 2.0 GeV and 2.0 GeV 2 < Q 2 < 5.0 GeV 2

This study reports new exclusive cross sections for ep→e'π + π – p' using the CLAS detector at Jefferson Laboratory. These results are presented for the first time at photon virtualities 2.0 GeV 2 < Q 2 < 5.0 GeV 2 in the center-of-mass energy range 1.4 GeV < W < 2.0 GeV, which covers a large part of the nucleon resonance region. Using a model developed for the phenomenological analysis of electroproduction data, we see strong indications that the relative contributions from the resonant cross sections at W < 1.74 GeV increase with Q 2 . These data considerably extend the kinematic reach of previous measurements. Exclusive ep→e'π + π – p' cross section measurements are of particular importance for the extraction of resonance electrocouplings in the mass range above 1.6 GeV.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2013

Transmission Line Jobs and Economic Development Impact (JEDI) Model User Reference Guide

The Jobs and Economic Development Impact (JEDI) models, developed through the National Renewable Energy Laboratory (NREL), are freely available, user-friendly tools that estimate the potential economic impacts of constructing and operating power generation projects for a range of conventional and renewable energy technologies. The Transmission Line JEDI model can be used to field questions about the economic impacts of transmission lines in a given state, region, or local community. This Transmission Line JEDI User Reference Guide was developed to provide basic instruction on operating the model and understanding the results. This guide also provides information on the model's underlying methodology, as well as the parameters and references used to develop the cost data contained in the model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Predictive and mechanistic multivariate linear regression models for reaction development

Multivariate Linear Regression (MLR) models utilizing computationally-derived and empirically-derived physical organic molecular descriptors are described in this review. Several reports demonstrating the effectiveness of this methodological approach towards reaction optimization and mechanistic interrogation are discussed. A detailed protocol to access quantitative and predictive MLR models is provided as a guide for model development and parameter analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

PRIME: Protein Representation Inference for Mutation Evaluation

Protein language machine learning models built upon existing ESM-2 model developed by Evolutionary Scale (evolutionaryscale.ai) and an in-house protein language model based on the BERT model developed by Google. The code also includes model training scripts and saved checkpoints from our own training using publicly available SARS-CoV-2 protein sequences.

Gibson, Kaetlyn [Los Alamos National Lab]↗
DOE OSTI2017

Evaluation of scenario-specific modeling approaches to predict plane of array solar irradiation

The two main objectives of this study are to evaluate the extent to which the prediction of plane of array irradiance is improved when diffuse radiation is predicted using location-specific regression models developed from onsite measured data as against using generalized models and to estimate the expected uncertainties associated with plane of array irradiance predictions under different data collection scenarios likely to be encountered in practical situations.

Moslehi, Salim↗
DOE OSTI2022

The Terrestrial Biosphere Model Farm

Model Intercomparison Projects (MIPs) are fundamental to our understanding of how the land surface responds to changes in climate. However, MIPs are challenging to conduct, requiring the organization of multiple, decentralized modeling teams throughout the world running common protocols. We explored centralizing these models on a single supercomputing system. We ran nine offline terrestrial biosphere models through the Terrestrial Biosphere Model Farm: CABLE, CENTURY, HyLand, ISAM, JULES, LPJ-GUESS, ORCHIDEE, SiB-3, and SiB-CASA. All models were wrapped in a software framework driven with common forcing data, spin-up, and run protocols specified by the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) for years 1901–2100. We ran more than a dozen model experiments. We identify three major benefits and three major challenges. The benefits include: (a) processing multiple models through a MIP is relatively straightforward, (b) MIP protocols are run consistently across models, which may reduce some model output variability, and (c) unique multimodel experiments can provide novel output for analysis. The challenges are: (a) technological demand is large, particularly for data and output storage and transfer; (b) model versions lag those from the core model development teams; and (c) there is still a need for intellectual input from the core model development teams for insight into model results. A merger with the open-source, cloud-based Predictive Ecosystem Analyzer (PEcAn) ecoinformatics system may be a path forward to overcoming these challenges.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Multiscale Modeling of CO 2 Migration and Trapping in Fractured Reservoirs with Validation by Model Comparison and Real-Site Applications (Final Technical Report)

This report documents the accomplishments achieved during the project titled “Multiscale Modeling of CO 2 Migration and Trapping in Fractured Reservoirs with Validation by Model Comparison and Real-Site Applications” funded by the US Department of Energy, Office of Fossil Energy. The objectives of the project were to develop modeling capabilities for predicting CO 2 and brine migration in fractured reservoirs during geologic carbon storage and to investigate the feasibility of carbon storage in fractured reservoirs using the newly developed modeling capabilities. To achieve these objectives new mass transfer functions were developed to adapt existing dual-continuum approaches – a commonly used approach in hydrocarbon reservoir modeling – to the CO 2 -brine system. In the dual-continuum approach the undisturbed rock matrix and the fractures are modeled as two separate continua, which are coupled through mass exchange of CO 2 and brine between the two continua. Mass transfer functions represent the mass exchange between fractures and the rock matrix, without requiring highly resolved numerical grids of individual fractures, thus allowing large modeling domains relevant to geologic carbon storage questions (tens of meters to hundreds of kilometers). Mass transfer functions for the exchange of both free-phase CO 2 and brine between fractures and rock matrix were developed for both the injection phase and the post-injection phase. During the injection phase the fractures are filled with CO 2 , while the rock matrix is initially filled with brine. Therefore, a mass transfer function was developed that is based on vertical displacement of brine by CO 2 in the rock matrix due to gravitational forces. Once CO 2 injection ceases and CO 2 migrates away from the direct vicinity of the injection site, the fractures will begin to re-fill with brine, while the rock matrix will have high CO 2 saturations. For these conditions a mass transfer functions was developed that is based on spontaneous imbibition, as the pore spaces in the rock matrix are much smaller than in the fractures. For formations with low permeability or high capillary entry pressure of the rock matrix, free-phase CO 2 may not be able to enter the rock matrix. However, free-phase CO 2 at the interface between fractures and rock matrix can dissolve into brine resident in the rock matrix. Therefore, additional mass transfer functions were developed based on aqueous-phase diffusion of CO 2 through the rock matrix. These mass transfer functions are based on existing solutions for diffusion and were expanded to be applicable to a variety of block shapes relevant to dual-continuum modeling. Implementations of the newly developed mass transfer functions showed that they give accurate results when compared to highly resolved models. In addition to developing new transfer functions, a new vertically-integrated dual-continuum modeling framework was developed. This development takes advantage of fast vertical segregation of CO 2 and brine in the fractures due to the density difference between CO 2 and brine and the high permeability of the fractures. Therefore, a vertically-integrated vertical equilibrium model for the fractures is coupled with a vertically-distributed model for the rock matrix. The newly developed approach significantly reduces the computational effort, but is only accurate for fracture permeabilities of 100 mD or higher. Finally, the newly developed models were applied to real and hypothetical geologic carbon storage sites to investigate the feasibility of using fractured reservoirs for carbon storage. The general results were, that storage of CO 2 – both as free-phase and dissolved – is feasible, but that storage capacities are likely lower than in unfractured systems. While the high permeability of the fractures reduces the injection pressure (or permits higher injection rates), fast migration of CO 2 may limit the overall storage volume, because CO 2 may escape laterally with not enough of the rock matrix being swept for effective storage.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Modelling the development of capillary pressure in freshly 3D-printed concrete elements

3D concrete printing is a promising technology recently developed to automate construction. Since no formwork is used in this technology to support and protect fresh concrete, there are two aspects which considerably accelerate the development of capillary pressure in 3D-printed concrete in comparison to conventionally placed concrete: i) high stiffness of 3D-printed needed to provide sufficient buildability, and ii) very early and fast evaporation of pore water. Accelerated development of capillary pressure may lead to severe plastic shrinkage cracking in 3D-printed elements and, hence, need to be mitigated. This investigation aims at providing a poromechanical model for capillary pressure development in 3D-printed elements. To simulate the development of capillary pressure and plastic shrinkage, environmental factors, material properties, and element geometry need to be considered as a whole. The model inputs – coefficient of permeability, static bulk modulus, air entry pressure and chemical shrinkage rate – were determined experimentally. The model was validated for two fine-grained concretes. Both 3D-printed materials yielded faster capillary pressure increase in comparison to cast concrete, while partial substitution of cement with silica fume further accelerated the capillary pressure development. Furthermore, due to the lower permeability of the mixture containing silica fume, the gradient of capillary pressure between 3D-printed layers increased, as did the gradient of plastic shrinkage.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Development, Demonstration and Validation of Data-Driven Compact Diode Models for Circuit Simulation and Analysis

Compact semiconductor device models are essential for efficiently designing and analyzing large circuits. However, traditional compact model development requires a large amount of manual effort and can span many years. Moreover, inclusion of new physics (e.g., radiation effects) into an existing model is not trivial and may require redevelopment from scratch. Machine Learning (ML) techniques have the potential to automate and significantly speed up the development of compact models. In addition, ML provides a range of modeling options that can be used to develop hierarchies of compact models tailored to specific circuit design stages. In this paper, we explore three such options: (1) table-based interpolation, (2) Generalized Moving Least-Squares, and (3) feedforward Deep Neural Networks, to develop compact models for a p-n junction diode. We evaluate the performance of these "data-driven" compact models by (1) comparing their voltage-current characteristics against laboratory data, and (2) building a bridge rectifier circuit using these devices, predicting the circuit's behavior using SPICE-like circuit simulations, and then comparing these predictions against laboratory measurements of the same circuit.

1N4148 switching diode↗
DOE OSTI2016

Recovering New Type of Sources by Off-Site Source Recovery Project for WIPP Disposal - 16604

OSRP uses two types of eligible packaging configurations for Cm-244 and Cf-252 disposal to WIPP: an S-100 drum and a 12'' Pipe Overpack (POC) drum. Both types of packaging are WIPP accepted configurations for Contact Handled (CH) waste, which offer different advantages and disadvantages when used in the case of the two isotopes. The S-100 is a poly-shielded type A, 55 gallon drum, containing a 6'' diameter POC. The 12'' POC drum is a type A, 55 gallon drum without the internal poly-shield and with a pipe component of 12'' diameter. The S-100 drum presents the advantage of poly-shielding which is very important for neutron sources, such as the Cf-252, or Cm-244Be, at the expense of reduced internal volume. The 12'' POC drum presents a larger pipe component accommodating many more sources, like Cm-244 alpha emitters or shielded Cf-252, for which the CH dose rate is not an issue. All the sources prepared for disposal to WIPP are required to be special form, as defined in 49 CFR 173.403. When OSRP recovers normal form sources, these can be packaged in a field closable DOT certified Special Form Capsule (SFC) model II or model III, thus becoming special form. These capsules are then packaged in the type-A containers. The difference between the two types of packaging is that the 12'' POC can hold more sources, or a mix of sources and capsules at the expense of less shielding. This becomes important when the TRU content criteria of 100 nCi/g of TRU waste has to be met for the drums that are packaged for WIPP disposal. Measured neutron dose rates for Cm-244 packaged in S-100 agree reasonably well with calculated dose rates based on the models developed with MCNP. Future work will include validating the model for Cm-244 packaged in 12'' POC. A 1:1 ratio of neutron to gamma is expected for Cm-244Be dose rates packaged in S-100 drums. For Cf-252 packaged in S-100 and 12'' POC, the contribution of Cf-250 to the total emission neutron rate had to be taken into account due to the increasing role of Cf-250 as sources age. The uncertainty in the measurement of Cf-252 neutron dose rate for S-100 drum was quite high due to a high neutron background. A larger Cf- 252 source needs to be used for measurements in the future, in order to fully validate the model developed. A better agreement for measured versus calculated rate was obtained for a Cf-252 packaged in 12'' POC. For the WIPP disposal of these sources, OSRP will use the best packaging configuration for these isotopes in order to minimize the dose rate and maximize the TRU content. The S-100 packaging will be used for Cf-252 and Cm-244Be sources, when neutron dose reduction by the poly-shielding is important. Neutron dose rates will be estimated using the new MCNP correlations.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2014

Damsel: A Data Model Storage Library for Exascale Science

Computational science applications have been described as having one of seven motifs (the “seven dwarfs”), each having a particular pattern of computation and communication. From a storage and I/O perspective, these applications can also be grouped into a number of data model motifs describing the way data is organized and accessed during simulation, analysis, and visualization. Major storage data models developed in the 1990s, such as Network Common Data Format (netCDF) and Hierarchical Data Format (HDF) projects, created support for more complex data models. Development of both netCDF and HDF5 was influenced by multi-dimensional dataset storage requirements, but their access models and formats were designed with sequential storage in mind (e.g., a POSIX I/O model). Although these and other high-level I/O libraries have had a beneficial impact on large parallel applications, they do not always attain a high percentage of peak I/O performance due to fundamental design limitations, and they do not address the full range of current and future computational science data models. The goal of this project is to enable exascale computational science applications to interact conveniently and efficiently with storage through abstractions that match their data models. The project consists of three major activities: (1) identifying major data model motifs in computational science applications and developing representative benchmarks; (2) developing a data model storage library, called Damsel, that supports these motifs, provides efficient storage data layouts, incorporates optimizations to enable exascale operation, and is tolerant to failures; and (3) productizing Damsel and working with computational scientists to encourage adoption of this library by the scientific community. The product of this project, Damsel library, is openly available for download from http://cucis.ece.northwestern.edu/projects/DAMSEL. Several case studies and application programming interface reference are also available to assist new users to learn to use the library.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

2015 Annual Report

For more than 20 years, the Atmospheric Radiation Measurement (ARM) Climate Research Facility has blazed the trail in providing the world’s atmospheric scientists with continuous observations of cloud and aerosol properties and their impacts on Earth’s energy balance. The result is an unprecedented data set that has proved invaluable for understanding the atmosphere and improving the predictive capabilities of earth system models. Over the past year, plans have been put in place to create a powerful new capability for furthering ARM’s mission and achieving the vision outlined in the Decadal Vision, the strategy for the ARM Facility for the next 5 to 10 years. The result is a significant reconfiguration for the ARM Facility that will provide more complete data sets to support process studies and model development. The combined observational and modeling elements will enable a new level of scientific inquiry. To achieve the next-generation ARM Facility, plans underway include the following: Establishing observation “megasites” at the Southern Great Plains and North Slope of Alaska sites Enhancing ARM measurement excellence to support U.S. Department of Energy climate science research Producing routine high-resolution model simulations over domains coincident with ARM sites Developing data products and software tools that facilitate analysis and enable the evaluation of models using ARM data Strengthening interactions with the broader atmospheric science and modeling communities. Changes being implemented at the megasites will provide additional spatial sampling of atmospheric and surface information to support a new ARM capability—the routine operation of high-resolution process models at ARM sites. The result will be even more comprehensive scientific data and the processes and tools for scientists to more easily use ARM data for climate model development.

Southern Great Plains, North Slope of Alaska, larg↗
DOE OSTI2020

Development of the INL Thermal Energy Distribution System (TEDS) in the Modelica Eco-System for Validation and Verification

This report provides an overview on the development of the Thermal Energy Distribution System (TEDS) in the Modelica process model eco-system at Idaho National Laboratory as part of the integrated energy system initiative. Model development has led to the creation of a dynamic process model of the experimental TEDS facility housed within the Engineering Science Laboratory (ESL) at INL. The model was then used during the pre-construction phase of the experimental effort to inform experimental design (insulation requirements, bypass line placement, expected performance of components) and to test innovative control schemes prior to the initial operation. The TEDS model developed in Modelica includes the primary components of the TEDS experimental unit including: a 200kW Chromalox heater, a single-tank packed bed thermal energy storage system filled with 0.125 inch Alumina (Al 2 O 3 ), an ethylene-glycol to Therminol-66 heat exchanger, system piping, six control valves, and all associated temperature, pressure, and mass flow sensors. The model does not include nitrogen fill gas tanks, or associated overfill tanks, as these are not part of standard system control. Two simulation sets were run. The first is a five-hour test that operates as a shakedown test for the facility. This simulation puts the facility through all five potential operating modes and showcases the ability of valving, control sensors, and component controllers to meet the system demands. The second case imposes a typical summer day demand on the system from a region with mixed commercial and residential electrical needs where the generator alone cannot meet peak demand but instead requires the thermal storage unit to act as a peaking unit. Over the course of the fifteen-hour discharge cycle heat losses account for a heat loss of approximately 15°C in outlet temperature. Such heat losses would lead to a decrease in overall system efficiency and may lead to additional design changes for such designs in the future that may include a topping heater. Through commencement of this work, a systems level model of TEDS with associated control systems, sensors, piping diameters, and component capabilities has been created. This model has been utilized in the pre-experimental phase to inform system design, insulation thicknesses, and potential control schemes to operate the system effectively and safely. Once TEDS begins operation, this model will be refined, tuned, and used for validation and verification purposes.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Statistical Analysis of CO 2 Exposed Wells to Predict Long Term Leakage through the Development of an Integrated Neural-Genetic Algorithm

The objective of this project is to develop a computerized statistical model with the Integrated Neural-Genetic Algorithm (INGA) for predicting the probability of long-term leak of wells in CO 2 sequestration operations. This object has been accomplished by conducting research in three phases: 1) data mining of CO 2 -explosed wells, 2) INGA computer model development, and 3) evaluation of the predictive performance of the computer model with data from field tests. Data mining was conducted for 510 wells in two CO 2 sequestration projects in the Texas Gulf Coast region. They are the Hasting West field and Oyster Bayou field in the Southern Texas. Missing wellbore integrity data were estimated using an analytical and Finite Element Method (FEM) model. The INGA was first tested for performances of convergence and computing efficiency with the obtained data set of high dimension. It was concluded that the INGA can handle the gathered data set with good accuracy and reasonable computing time after a reduction of dimension with a grouping mechanism. A computerized statistical model with the INGA was then developed based on data pre-processing and grouping. Comprehensive training and testing of the model were carried out to ensure that the model is accurate and efficient enough for predicting the probability of long-term leak of wells in CO 2 sequestration operations. The Cranfield in the southern Mississippi was select as the test site. Observation wells CFU31F2 and CFU31F3 were used for pressure-testing, formation-logging, and cement-sampling. Tools run in the wells include Isolation Scanner, Slim Cement Mapping Tool (SCMT), Cased Hole Formation Dynamics Tester (CHDT), and Mechanical Sidewall Coring Tool (MSCT). Analyses of the obtained data indicate no leak of CO 2 cross the cap zone while it is evident that the well cement sheath was invaded by the CO 2 from the storage zone. This observation is consistent with the result predicted by the INGA model which indicates the well has a CO 2 leak-safe probability of 72%. This comparison implies that the developed INGA model is valid for future use in predicting well leak probability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

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↗