Publications

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One explanation for wind turbine power degradation is insect roughness. Historical studies on insect-induced power degradation have used simulation methods which are either un- representative of actual insect roughness or too costly or time-consuming to be applied to wide-scale testing. Furthermore, the role of airfoil geometry in determining the relations between insect impingement locations and roughness sensitivity has not been studied. To link the effects of airfoil geometry, insect impingement locations, and roughness sensitivity, a simulation code was written to determine representative insect collection patterns for different airfoil shapes. Insect collection pattern data was then used to simulate roughness on an NREL S814 airfoil that was tested in a wind tunnel at Reynolds numbers between 1.6 x 10⁶ and 4.0 x 10⁶. Results are compared to previous tests of a NACA 63₃ -418 airfoil. Increasing roughness height and density results in decreased maximum lift, lift curve slope, and lift-to-drag ratio. Increasing roughness height, density, or Reynolds number results in earlier bypass transition, with critical roughness Reynolds numbers lying within the historical range. Increased roughness sensitivity on the 25% thick NREL S814 is observed compared to the 18% thick NACA 63 3 -418. Blade-element-momentum analysis was used to calculate annual energy production losses of 4.9% and 6.8% for a NACA 63₃ -418 turbine and an NREL S814 turbine, respectively, operating with 200 μm roughness. These compare well to historical field measurements.

The impact of surface roughness on flows over aerodynamically designed surfaces is of interested in a number of different fields. It has long been known the surface roughness will likely accelerate the laminar- turbulent transition process by creating additional disturbances in the boundary layer. However, there are very few tools available to predict the effects surface roughness will have on boundary layer flow. There are numerous implications of the premature appearance of a turbulent boundary layer. Increases in local skin friction, boundary layer thickness, and turbulent mixing can impact global flow properties compounding the effects of surface roughness. With this motivation, an investigation into the effects of surface roughness on boundary layer transition has been conducted. The effort involved both an extensive experimental campaign, and the development of a high fidelity roughness model implemented in a R ANS solver. Vast a mounts of experimental data was generated at the Texas A&M Oran W. Nicks Low Speed Wind Tunnel for the calibration and validation of the roughness model described in this work, as well as future efforts. The present work focuses on the development of the computational model including a description of the calibration process. The primary methodology presented introduces a scalar field variable and associated transport equation that interacts with a correlation based transition model. The additional equation allows for non-local effects of surface roughness to be accounted for downstream of rough wall sections while maintaining a "local" formulation. The scalar field is determined through a boundary condition function that has been calibrated to flat plate cases with sand grain roughness. The model was initially tested on a NACA 0012 airfoil with roughness strips applied to the leading edge. Further calibration of the roughness model was performed using results from the companion experimental study on a NACA 63₃ -418 airfoil. The refined model demonstrates favorable agreement predicting changes to the transition location, as well as drag, for a number of different leading edge roughness configurations on the NACA 63₃-418 airfoil. Additional tests were conducted on a thicker S814 airfoil, with similar roughness configurations to the NACA 63₃-418. Simulations run with the roughness model compare favorably with the results obtained in the experimental study for both airfoils.

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Wind turbine loads predictions by blade-element momentum theory using the standard tip-loss correction have been shown to over-predict loading near the blade tip in comparison to experimental data. This over-prediction is theorized to be due to the assumption of light rotor loading, inherent in the standard tip-loss correction model of Glauert. A higher- order free-wake method, WindDVE, is used to compute the rollup process of the trailing vortex sheets downstream of wind turbine blades. Results obtained serve an exact correction function to the Glauert tip correction used in blade-element momentum methods. It is found that accounting for the effects of tip vortex rollup within the Glauert tip correction indeed results in improved prediction of blade tip loads computed by blade-element momentum methods.

Leading edge erosion and roughness accumulation is an issue observed with great variability by wind plant operators, but with little understanding of the effect on wind turbine performance. In wind tunnels, airfoil models are typically tested with standard grit roughness and trip tape to simulate the effects of roughness and erosion observed in field operation, but there is a lack of established relation between field measurements and wind tunnel test conditions. A research collaboration between lab, academic, and industry partners has sought to establish a method to estimate the effect of erosion in wind turbine blades that correlates to roughness and erosion measured in the field. Measurements of roughness and erosion were taken off of operational utility wind turbine blades using a profilometer. The field measurements were statistically reproduced in the wind tunnel on representative tip and midspan airfoils. Simultaneously, a computational model was developed and calibrated to capture the effect of roughness and erosion on airfoil transition and performance characteristics. The results indicate that the effects of field roughness fall between clean airfoil performance and the effects of transition tape. Severe leading edge erosion can cause detrimental performance effects beyond standard roughness. The results also indicate that a heavily eroded wind turbine blade can reduce annual energy production by over 5% for a utility scale wind turbine.

Wind turbine loads predictions by blade-element momentum theory using the standard tip-loss correction have been shown to over-predict loading near the blade tip in comparison to experimental data. This over-prediction is theorized to be due to the assumption of light rotor loading, inherent in the standard tip-loss correction model of Glauert. A higher- order free-wake method, WindDVE, is used to compute the rollup process of the trailing vortex sheets downstream of wind turbine blades. Results obtained serve an exact correction function to the Glauert tip correction used in blade-element momentum methods. Lastly, it is found that accounting for the effects of tip vortex rollup within the Glauert tip correction indeed results in improved prediction of blade tip loads computed by blade-element momentum methods.

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The total energy produced by a wind farm depends on the complex interaction of many wind turbines operating in proximity with the turbulent atmosphere. Sometimes, the unsteady forces associated with wind negatively influence power production, causing damage and increasing the cost of producing energy associated with wind power. Wakes and the motion of air generated by rotating blades need to be better understood. Predicting wakes and other wind forces could lead to more effective wind turbine designs and farm layouts, thereby reducing the cost of energy, allowing the United States to increase the installed capacity of wind energy. The Wind Energy Technologies Department at Sandia has collaborated with the University of Minnesota to simulate the interaction of multiple wind turbines. By combining the validated, large-eddy simulation code with Sandia’s HPC capability, this consortium has improved its ability to predict unsteady forces and the electrical power generated by an array of wind turbines. The array of wind turbines simulated were specifically those at the Sandia Scaled Wind Farm Testbed (SWiFT) site which aided the design of new wind turbine blades being manufactured as part of the National Rotor Testbed project with the Department of Energy.

A Verification and Validation (V&V) framework is presented for the development and execution of coordinated modeling and experimental program s to assess the predictive capability of computational models of complex systems through focused, well structured, and formal processes.The elements of the framework are based on established V&V methodology developed by various organizations including the Department of Energy, National Aeronautics and Space Administration, the American Institute of Aeronautics and Astronautics, and the American Society of Mechanical Engineers. Four main topics are addressed: 1) Program planning based on expert elicitation of the modeling physics requirements, 2) experimental design for model assessment, 3) uncertainty quantification for experimental observations and computational model simulations, and 4) assessment of the model predictive capability. The audience for this document includes program planners, modelers, experimentalist, V &V specialist, and customers of the modeling results.

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Rotor design and analysis work has been performed to support the conceptualization of a wind tunnel test focused on studying wake dynamics. This wind tunnel test would serve as part of a larger model validation campaign that is part of the Department of Energy Wind and Water Power Program’s Atmosphere to electrons (A2e) initiative. The first phase of this effort was directed towards designing a functionally scaled rotor based on the same design process and target full-scale turbine used for new rotors for the DOE/SNL SWiFT site. The second phase focused on assessing the capabilities of an already available rotor, the G1, designed and built by researchers at the Technical University of München.

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The objective of this document is to accurately predict, assess and optimize wind plant performance utilizing High Performance Modeling (HPC) tools developed in a community-based, open-source simulation environment to understand and accurately predict the fundamental physics and complex flows of the atmospheric boundary layer, interaction with the wind plant, as well as the response of individual turbines to the complex flows within that plant

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