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At least 757 records · Page 42

Boiling Closure Model Validation/Development Effort with TAMU Experimental Data

This report describes a model validation and developmental effort in INL based on the analysis of experimental data taken from TAMU subcooled flow boiling facility. This report first describes briefly the test loop, experimental strategy, measurement techniques, data quality achieved, and test boundary conditions. Then, two main topics are discussed based on the experimental observation, bubble departure frequency and sliding bubble characteristics. The comparison of experimental data with the prediction of bubble departure frequency models shows that the predictive capability of existing models depends strongly on flow conditions. Also, the best performance region of each bubble departure frequency model could be determined from this analysis. Another critical achievement through this study is that the limitation of existing CFD boiling models dealing with sliding bubble effect was clearly identified. Specifically, the experimental observation indicates that the wall area influenced by sliding bubbles is not just a function of bubble size, but also depends strongly on sliding bubble trajectory and sliding distance. As a result, the bubble influence factor ( K ) for the small size of sliding bubbles was often found substantially higher than those reported in literature. In this regard, an effort is currently being made in INL to develop a new model to predict the sliding bubble effect on wall heat transfer based on the insight achieved from TAMU subcooled flow boiling experiment.

42 ENGINEERING↗

Benchmark Progress towards TREAT M8CAL Core Loading to Support Validation of TREAT Operations

Benchmark experiment data is necessary to validate modeling and simulation activities to support Transient Reactor Experiment Test (TREAT) Facility restart and operations. Key measurements of interest include criticality, control rod worth, excess reactivity, and shutdown margin for varying core loading sizes. Benchmark evaluations are being developed according the guidelines provided in the International Handbook of Evaluated Reactor Physics Benchmark Experiments (IRPhEP Handbook) that can also support advanced modeling and simulation activities, new experiment design for advanced reactors and accident tolerant fuel, and potential low-enriched uranium conversion of the TREAT reactor. This summary discusses development activities supporting a benchmark evaluation of the TREAT M8CAL core loading, which will be submitted for peer-review and publication in the IRPhEP Handbook with the identifier TREAT-FUND-RESR-002. Detailed models of TREAT were developed and evaluated to prepare benchmark models of the minimum critical mass configuration. Calculations were performed using MCNP6.1 with ENDF/B-VII.1 nuclear data libraries. Discussion of results.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Modeling Shock-Driven Reaction in Low-Density Non-energetic polymeric materials

Shock experiments on low density polyurethane foams reveal evidence of reaction at low impact pressures. However, these reaction thresholds are not evident over the low pressures reported for historical Hugoniot data of highly distended polyurethane at densities below 0.1 g/cc. To fill this gap, impact data for PMDI foam with a density of 0.087 g/cc were acquired for model validation. An equation of state (EOS) was developed to predict the shock response of these highly distended materials over the full range of impact conditions representing compaction of the inert material, low-pressure decomposition, and compression of the reaction products. A tabular SESAME EOS of the reaction products was generated using the JCZS database in the TIGER equilibrium code. In particular, the Arrhenius Burn EOS, a two-state model which transitions from an unreacted to a reacted state using Arrhenius kinetics, as implemented in the shock physics code CTH, was modified to include a statistical distribution of states. Hence, a single EOS is presented that predicts the onset to reaction due to shock loading in PMDI-based polyurethane foams. This methodology was also used to predict the anomalous compaction of PMDI foams over published data sets from 0.087 to 0.87 g/cc, and solid Polyurethane at a theoretical maximum density (TMD) of 1.264 g/cc. Likewise, similar modeling techniques were used to predict the performance of SX-358 foam, an RTV-based stress cushion material at a nominal density of 0.41 g/cc, and the matrix material, with properties similar to Sylgard, at 1.1 g/cc. At the start of this study, data were only available at a single impact condition below the threshold for reaction; hence, the decomposition of this material at higher pressures was revealed as a significant finding of this work. The decomposition of SX-358 at higher impact pressures to product species including solid, liquid, and gaseous molecules was estimated with thermochemical equilibrium calculations using TIGER. with thermochemical equilibrium calculations using TIGER. This modeling approach, developed for PMDI foam, was shown to predict gas gun data, acquired as part of this study, up to pressures of 14 GPa. Furthermore, additional phase transitions were predicted in the product species under shock compression. To date, this study is the first known to the authors that demonstrates and successfully predicts the decomposition of these low-density polymer-based foams using a single model applicable to a broad range of impact loading conditions.

36 MATERIALS SCIENCE↗

Mechanical performance of short models for MQXF, the Nb3Sn low-β quadrupole for the Hi-Lumi LHC

In the framework of the Hi-Lumi LHC Project, CERN and U.S. LARP are jointly developing MQXF, a 150-mm aperture high-field Nb3Sn quadrupole for the upgrade of the inner triplet of the low-beta interaction regions. The magnet is supported by a shell-based structure, providing the preload by means of bladder-key technology and differential thermal contraction of the various components. Two short models have been produced using the same cross section currently considered for the final magnet. The structures were preliminarily tested replacing the superconducting coils with blocks of aluminum. This procedure allows for model validation and calibration, and also to set performance goals for the real magnet. Strain gauges were used to monitor the behavior of the structure during assembly, cool down and also excitation in the case of the magnets. The various structures differ for the shell partitioning strategies adopted and for the presence of thick or thin laminations. This study presents the results obtained and discusses the mechanical performance of all the short models produced up to now.

43 PARTICLE ACCELERATORS↗

Big Area Additive Manufacturing (BAAM) Materials Development and Reinforcement with Advanced Composites

Additive manufacturing (AM) by extrusion deposition is rapidly developing as an energy efficient process that greatly reduces development time for new products including vehicle structures. Development of reinforced thermoplastic compounds that are specifically tailored to the AM process and possess the properties necessary for engineering structures is currently underway. This project focused on developing a fundamental understanding of printability by performing a number of polymer characterization tests, initial printability screenings, and basic mechanical property determinations for a number of compounds. Structural evaluations of more complex printed articles were also performed in order to build a database of mechanical performance for validation of structural simulations planned for Phase II. Included in the structural tests were components that were reinforced using a number of methods including over-wrapping with dry fabric and resin infusing to form an advanced composite having the shape of the 3D printed structure. The results indicate a number of factors that affect printability of materials, and initial structural analysis shows that the data generated will be useful for model validation.

36 MATERIALS SCIENCE↗

Downloadable Dynamometer Database (D3): Public Test Data on Advanced-Technology Vehicles

Access to high-quality, independent vehicle test data is critical to advancing energy-efficient transportation research. The Downloadable Dynamometer Database (D3) is a public repository of dynamometer test data on advanced-technology vehicles, generated at the Advanced Mobility Technology Laboratory (AMTL) at Argonne National Laboratory and hosted by the Transportation and Power Systems Division. The database has been made available to support researchers, students, and professionals engaged in energy-efficient vehicle research, development, and education. A wide range of vehicle categories has been tested (i.e., alternative fuel vehicles, conventional gasoline and diesel vehicles, all-electric vehicles, hybrid electric vehicles, and plug-in hybrid electric vehicles), as well as various drive cycles and test conditions documented in the accompanying D3 user presentation. Stakeholders can select a vehicle type, identify a vehicle of interest, and download the associated test data for use in their own analyses. Data downloaded from D3 must be accompanied by the required attribution: "This data is from the Downloadable Dynamometer Database and was generated at the Advanced Mobility Technology Laboratory (AMTL) at Argonne National Laboratory." These data are critical to vehicle modeling, validation, technology assessment, and educational use.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Benchmark Development for TREAT Minimum Critical Mass Core Loading to Support Validation of TREAT Operations

Benchmark experiment data is necessary to validate modeling and simulation activities to support Transient Reactor Experiment Test (TREAT) Facility restart and operations. Key measurements of interest include criticality, control rod worth, excess reactivity, and shutdown margin for varying core loading sizes. Benchmark evaluations are being developed according the guidelines provided in the International Handbook of Evaluated Reactor Physics Benchmark Experiments (IRPhEP Handbook) that can also support advanced modeling and simulation activities, new experiment design for advanced reactors and accident tolerant fuel, and potential low-enriched uranium conversion of the TREAT reactor. This summary discusses development activities supporting a benchmark evaluation of the TREAT minimum critical mass core loading, which will be submitted for peer-review and publication in the IRPhEP Handbook with the identifier TREAT-FUND-RESR-001. Detailed models of TREAT were developed and evaluated to prepare benchmark models of the minimum critical mass configuration. Calculations were performed using MCNP6.1 with ENDF/B-VII.1 nuclear data libraries. Discussion of results.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

High-resolution leaf area index maps generated from unoccupied aerial system, Teller Mile 27, Seward Peninsula, Alaska

Leaf area index (LAI), a measure of the amount of one-side leaf area per ground unit, is an important indicator of plant carbon, energy, and water cycle. In the heterogeneous Arctic landscapes, it has been challenging to accurately measure LAI across species and space needed for Earth system model validation. Here, we use multispectral unoccupied aerial systems (UASs) to scale up and map leaf area index (LAI) , in a low-Arctic tundra landscape on the Seward Peninsula, Alaska. We linked previous published LAI measurements with high-resolution, UAS-collected multispectral data collected over the region of Next Generation Ecosystem Experiments in the Arctic (NGEE Arctic)’s Teller Mile Maker 27 site in 2022 to develop random forest (RF) machine learning models to predict and map LAI. 100 RF models were developed to account for uncertainties in ground LAI plot measurements and process scaling. This dataset includes a raster (*.tif) map of the mean LAI value of the 100 RF models, a raster (*.tif) map of the standard deviation of the RF-modeled LAI data, and a user guide (*.pdf).

54 ENVIRONMENTAL SCIENCES↗

Application of Machine Learning Techniques to an Agent-Based Model of Pantoea

Agent-based modeling (ABM) is a powerful simulation technique which describes a complex dynamic system based on its interacting constituent entities. While the flexibility of ABM enables broad application, the complexity of real-world models demands intensive computing resources and computational time; however, a metamodel may be constructed to gain insight at less computational expense. Here, we developed a model in NetLogo to describe the growth of a microbial population consisting of Pantoea . We applied 13 parameters that defined the model and actively changed seven of the parameters to modulate the evolution of the population curve in response to these changes. We efficiently performed more than 3,000 simulations using a Python wrapper, NL4Py . Upon evaluation of the correlation between the active parameters and outputs by random forest regression, we found that the parameters which define the depth of medium and glucose concentration affect the population curves significantly. Subsequently, we constructed a metamodel, a dense neural network, to predict the simulation outputs from the active parameters and found that it achieves high prediction accuracy, reaching an R 2 coefficient of determination value up to 0.92. Our approach of using a combination of ABM with random forest regression and neural network reduces the number of required ABM simulations. The simplified and refined metamodels may provide insights into the complex dynamic system before their transition to more sophisticated models that run on high-performance computing systems. The ultimate goal is to build a bridge between simulation and experiment, allowing model validation by comparing the simulated data to experimental data in microbiology.

59 BASIC BIOLOGICAL SCIENCES↗

EnergyPlus-MCP: A model-context-protocol server for ai-driven building energy modeling

Traditional building energy modeling with the EnergyPlus building performance simulation engine requires domain expertise, programming skills, and intensive manual efforts limiting its effective adoption. This paper introduces EnergyPlus-MCP, the first open-source Model Context Protocol (MCP) server specifically designed for EnergyPlus simulation workflows, establishing a new foundational infrastructure for AI-driven building energy modeling. The MCP server implements a layered architecture with 35 specialized tools spanning model management, editing and analysis, HVAC and other systems configuration inspection, and simulation execution, enabling Large Language Models to interact with EnergyPlus through conversational interfaces. The server addresses critical workflow barriers by automating model validation, streamlining energy efficiency measures modification, and providing intelligent output management with interactive visualization. Through practical demonstrations using a multi-zone building retrofit analysis, we show how the EnergyPlus-MCP server significantly reduces manual efforts while maintaining full simulation rigor. By providing accessible natural language interfaces to sophisticated building energy analysis, this approach enables scalable deployment of simulation expertise across public and private organizations, educational institutions, and research teams, fundamentally transforming traditional building energy modeling practices.

AI↗

First Double-Differential Cross Section Measurement of Neutral-Current 𝜋 0 Production in Neutrino-Argon Scattering in the MicroBooNE Detector

We report the first double-differential cross section measurement of neutral-current neutral pion (NC⁢𝜋 0 ) production in neutrino-argon scattering, as well as single-differential measurements of the same channel in terms of final states with and without protons. The kinematic variables of interest for these measurements are the 𝜋 0 momentum and the 𝜋 0 scattering angle with respect to the neutrino beam. A total of 4971 candidate NC⁢𝜋 0 events fully contained within the MicroBooNE detector are selected using data collected at a mean neutrino energy of ∼0.8 GeV from 6.4 ×10 20 protons on target from the Booster Neutrino Beam at the Fermi National Accelerator Laboratory. After extensive data-driven model validation to ensure unbiased unfolding, the Wiener-singular-value-decomposition method is used to extract nominal flux-averaged cross sections. The results are compared to predictions from commonly used neutrino event generators, which tend to overpredict the measured NC⁢𝜋 0 cross section, especially in the 0.2–0.5 GeV/c 𝜋 0 momentum range and at forward scattering angles. Events with at least one proton present in the final state are also underestimated. This data will help improve the modeling of NC⁢𝜋 0 production, which represents a major background in measurements of charge-parity violation in the neutrino sector and in searches for new physics beyond the standard model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Impacts of High Levels of Distributed PV and Load Dynamics on Bulk Power Transient Stability: Preprint

The addition of large amounts of wind and solar generation to bulk power systems that are traditionally subject to operating constraints set by transient stability and frequency response limitations is the subject of considerable concern in the industry in all North American grids. The U.S. Western Interconnection is expected to experience substantial additional growth in both wind and solar generation. This generation will, to some extent, displace large central station thermal generation, both coal and gas-fired, which have traditionally helped maintain stability. A substantial fraction of the new photovoltaic (PV) solar generation will be deeply embedded in the distribution system and will be electrically in close proximity to customer loads. Several aspects of this renewable generation on transient stability and frequency response have been investigated and reported elsewhere in summaries of a study that included an investigation of the dynamic performance of the Western Interconnection with high penetrations of wind and solar generation. In this paper, modeling and the impact of distributed PV generation and dynamic loads are reported. The key finding is that the transient performance, particularly the fault ride-through behavior of embedded PV, is critical to system stability. Poor ride-through characteristics on distributed generation are shown in the study to collapse the entire grid. The dynamic behavior of the loads, aside from the embedded PV is also shown to be a critical element. The investigation reinforces the need for valid models and for thorough system planning studies.

14 SOLAR ENERGY↗

Thermal Modeling of a Loaded Magnastor Storage System at Catawba Nuclear Station

This report represents fulfillment of the M2 Milestone M2FT-16PN080203031, “High Heat Load Thermal Analyses,” under Work Package FT-16PN08020303. The report documents the analysis of the NAC International, Inc. (NAC) Modular, Advanced Generation, Nuclear All-purpose STORage (MAGNASTOR) module at Duke’s Catawba Nuclear Station. As part of the Used Fuel Disposition Campaign of the U.S. Department of Energy, a high-burnup fuel storage demonstration is planned for a storage module in the North Anna Nuclear Station’s Independent Spent Fuel Storage Installation (ISFSI). The storage module selected for this demonstration is an AREVA TN-32B High Burnup cask. The main goals of this proposed test are to provide confirmatory data for model validation and potential improvement, support license renewals and new licenses for ISFSIs, and support transportation licensing for high burnup spent nuclear fuel (EPRI 2014). The focus of the Demonstration test is the performance of the high-burnup fuel. To support the High Burnup Spent Fuel Data Project, Pacific Northwest National Laboratory (PNNL) staff performed a detailed thermal analysis (Fort et al. 2016) of the TN-32B cask. It was found that when conservatisms were removed from the thermal models and especially from the calculated decay heats, the predicted peak cladding temperatures (PCTs) were significantly below the 400°C (752°F) regulatory guidance limit, as specified in Interim Staff Guidance 11, Revision 3, (U.S. NRC 2003).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Overview of the OECD-NEA Working Party on International Nuclear Data Evaluation Cooperation (WPEC)

The OECD Nuclear Energy Agency (NEA) Working Party on International Nuclear Data Evaluation Cooperation (WPEC) was established in 1989 to facilitate collaboration in nuclear data activities. Over its thirty year history, different Subgroups have been created to address topics in nearly every aspect of nuclear data, including: experimental measurements, evaluation, validation, model development, quality assurance of databases and the development of software tools. WPEC has recently completed activities on fission yield evaluation, the general nuclear database structure (GNDS) to replace the ENDF-6 format, methods to provide feedback to evaluation, studies of specific capture cross sections, new methods in thermal scattering kernel evaluation and the Collaborative International Evaluated Library Organisation (CIELO) Pilot Project. Ongoing activities in GNDS application programming interface (API) development, methods for covariance evaluation and quality assurance in nuclear data validation using the International Criticality Safety Benchmark Evaluation Project (ICSBEP) database are complemented by the work of two Expert Groups that oversee the High-Priority Request List (HPRL) for Nuclear Data and the continuous development of the GNDS. New activities on the use of integral experiments for nuclear data validation and adjustment, as well as the use of the Shielding Integral Benchmark Archive and Database (SINBAD) for validation have begun and will be coordinated alongside future Subgroups. After three decades we will review the status of WPEC, how it integrates other collections and activities organised by the NEA and how it dovetails with the initiatives of the IAEA and other bodies to effectively coordinate international activities in nuclear data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Quantification of Residual Water in Spent Fuel Dry Storage Canisters Using Mass Spectrometry

The purpose of this report is to document updates on the apparatus to simulate commercial vacuum drying procedures at the Nuclear Energy Work Complex at Sandia National Laboratories. Validation of the extent of water removal in a dry spent nuclear fuel storage system based on drying procedures used at nuclear power plants is needed to close existing technical gaps. Operational conditions leading to incomplete drying may have potential impacts on the fuel, cladding, and other components in the system during subsequent storage and disposal, such as fuel degradation; cladding corrosion, embrittlement, or breaching; and the creation of a flammable environment via radiolysis of water. A general lack of data suitable for model validation of commercial nuclear canister drying processes necessitates well-designed investigations of drying process efficacy and water retention. Scaled tests that incorporate relevant physics and well-controlled boundary conditions are essential to provide insight and guidance to the simulation of prototypic systems undergoing drying processes. This report documents details on the quantification of residual water in the Advanced Drying Cycle Simulator (ADCS), an apparatus built to simulate commercial drying procedures and quantify the amount of residual water remaining in a pressurized water reactor (PWR) fuel assembly after drying. The ADCS was constructed with a prototypic 17×17 PWR fuel skeleton and waterproof heater rods to simulate decay heat. The ADCS is outfitted with thermocouples to measure the thermal response of the ADCS to simulated decay heats and internal helium fill pressures relevant to commercial drying procedures. The ADCS is also instrumented with pressure transducers to measure the pressures and vacuum levels observed during simulated commercial drying. The most unique instrumentation used for quantifying residual water in the ADCS is a Hiden Analytical HPR-30 mass spectrometer (MS), which measures gas compositions of the ADCS internal free volume, based on partial pressures calculated from relative proportions of gas molecules detected by the MS. This report details the methodology used to implement MS measurements in quantifying residual water in the ADCS. This methodology includes the calibration of the HPR-30 MS to a Buck Research Instruments CR-4 chilled mirror hygrometer, which itself is calibrated to a NIST-traceable standard. Data collected by both the MS and the chilled mirror hygrometer from water/helium mixtures ranging from 150 to 500,000 ppmv water in helium were used to generate calibration curves, establishing a source of verification of MS measured water contents. Details regarding water content measurement uncertainties are included in this report, defining the accuracy and verifiability of the HPR-30 MS in measuring residual water content in simulated dry storage canister environments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Predicting Particle-Size Distributions in Fuel-Cell Inks

Prediction of the catalyst-activated carbon particle sizes of fuel-cell inks remains a critical challenge in enhancing the performance and durability of fuel cells. The performance and structural integrity of the catalyst layers in the cell depend not only on the properties of the ionomer, but also on the carbon supports that host the catalyst. To investigate how these carbon aggregate structures form, we present a model that calculates the cooperative size distributions of ionomer and carbon aggregates in various water/alcohol mixtures and compares those results to available experimental data. Aggregation of both the suspended ionomers and the carbon particles is interwoven as the carbon aggregation depends heavily on the ionic strength of its environment, namely protons dissociating from the ionomer’s sulfonic-acid-group side chains. We demonstrate that the surrounding mixed solvent as well as Nafion TM binder concentration strongly influence the degree of aggregation for carbon particles. The validated model provides a framework for exploring aggregation under a wide range of conditions for various electrochemical-technology inks.

Srivastav, Harsh [University of California, Berkel↗

GRIZZLY Model of Multi-Reactive Species Diffusion, Moisture/Heat Transfer and Alkali-Silica Reaction for Simulating Concrete Aging and Degradation

Concrete is widely used in the construction of nuclear facilities because of its structural strength and its ability to shield radiation. The use of concrete in nuclear power plants for containment and shielding of radiation and radioactive materials has made its performance crucial for the safe operation of the facility. As such, when life extension is considered for nuclear power plants, it is critical to have accurate and reliable predictive tools to address concerns related to various aging processes of concrete structures and the capacity of structures subjected to age-related degradation. The goal of this report is to document the progress of the development and implementation of a fully coupled thermo-hydro-mechanical-chemical model in GRIZZLY code with the ultimate goal to reliably simulate and predict long-term performance and response of aged NPP concrete structures subjected to a number of aging mechanisms including external chemical attacks and volume-changing chemical reactions within concrete structures induced by alkali-silica reactions and long-term exposure to irradiation. Based on a number of survey reports of concrete aging mechanisms relevant to nuclear power plants and recommendations from researchers in concrete community, we’ve implemented three modules during FY15 in GRIZZLY code, (1) multi-species reactive diffusion model within cement materials; (2) coupled moisture and heat transfer model in concrete; and (3) anisotropic, stress-dependent, alkali-silica reaction induced swelling model. The multi-species reactive diffusion model was implemented with the objective to model aging of concrete structures subjected to aggressive external chemical attacks (e.g., chloride attack, sulfate attack, etc.). It considers multiple processes relevant to external chemical attacks such as diffusion of ions in aqueous phase within pore spaces, equilibrium chemical speciation reactions and kinetic mineral dissolution/precipitation. The moisture/heat transfer module was implemented to simulate long-term spatial and temporal evolutions of the moisture and temperature fields within concrete structures at both room and elevated temperatures. The ASR swelling model implemented in GRIZZLY code can simulate anisotropic expansions of ASR gel under either uniaxial, biaxial and triaxial stress states, and can be run simultaneously with the moisture/heat transfer model and coupled with various elastic/inelastic solid mechanics models that were implemented in GRIZZLY code previously. This report provides detailed descriptions of the governing equations, constitutive equations and numerical algorithms of the three modules implemented in GRIZZLY during FY15, simulation results of example problems and model validation results by comparing simulations with available experimental data reported in the literature. The close match between the experiments and simulations clearly demonstrate the potential of GRIZZLY code for reliable evaluation and prediction of long-term performance and response of aged concrete structures in nuclear power plants.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Curled-Skewed Wakes behind Yawed Wind Turbines Subject to Veered Inflow

This work presents a new engineering analytical model that predicts the effect of both the turbine yaw misalignment and the inflow wind veer on the wake flow distribution downwind of a wind turbine. To consider the veered inflow, two methods were examined. In the first method, the curled shape of the wake due to the yaw offset is initially modelled. The wake shape is then laterally skewed at each height due to the wind veer based on the assumption that the turbine wake is transported downstream by the incoming flow. The second method is a more realistic approach that accounts for the effect of wind veer on the wind velocity direction and the yaw angle seen by the wind turbine. This models the wake region in a local coordinate system defined based on the wind direction at each height. A coordinate transformation is then performed to represent the wake flow distribution in the global coordinate system attached to the ground. The results show that while the two methods provide similar outputs for small variations in the wind direction across the rotor, the difference becomes more evident with an increase in wind veer. High-fidelity simulations for a turbine subject to a neutral atmospheric boundary layer were employed to validate model predictions for different operating conditions.

17 WIND ENERGY↗