Learn more about blade-resolved wind turbine and wind farm simulations using WAKE3D.
Much of my research focuses around the application of wind energy and developing predictive physics software tools. The goal of this research is to develop aerodynamically-accurate simulation software whereby the wind turbine models are resolved geometrically (known as blade resolved) in contrast to lower-fidelity models which used parameterized models to generate wakes. Though the development of our multiscale CFD tool, WAKE3D, we are able to solve problems with spatial scales ranging from 10+ km all the way down to sub-micron levels at the blade! Some highlights regarding this work are shown below including the highest fidelity simulation of a wind turbine to date.
Wake Breakdown, Turbulence, and Interactions
Wind turbines generate complex wake structures which mix with free air to reenergize the flow but over vast distances. These wakes can cause significant drops in energy generation efficiency of neighboring downstream wind turbines. Understanding these interactions and engineering mitigation strategies can result in significant increases in energy production each year.
Wake interactions between two wind turbines.
Wind Farm Simulations
Much of this wind energy research was performed on the NCAR-Wyoming Cheyenne and Yellowstone supercomputers. This video highlights the work done as part of my Ph.D. dissertation research.
Isocontour visualization of the tip vortices generated by the NREL Phase VI wind turbine. Uniform inflow of 10 m/s.
Wind Energy Publications
Wind farm simulations using an overset hp-adaptive approach with blade-resolved turbine models
Andrew C Kirby, Michael J Brazell, Zhi Yang, and 5 more authors
The International Journal of High Performance Computing Applications 2019
@article{kirby2019wind,title={Wind farm simulations using an overset hp-adaptive approach with blade-resolved turbine models},author={Kirby, Andrew C and Brazell, Michael J and Yang, Zhi and Roy, Rajib and Ahrabi, Behzad R and Stoellinger, Michael K and Sitaraman, Jay and Mavriplis, Dimitri J},journal={The International Journal of High Performance Computing Applications},volume={33},number={5},pages={897--923},year={2019},publisher={SAGE Publications},}
Effects of Blade Load Distributions on Wind Turbine Wake Evolution Using Blade-Resolved Computational Fluid Dynamics Simulations
Anthony P Edmonds, Arash Hassanzadeh, Andrew C Kirby, and 2 more authors
@article{edmonds2019effects,title={Effects of Blade Load Distributions on Wind Turbine Wake Evolution Using Blade-Resolved Computational Fluid Dynamics Simulations},author={Edmonds, Anthony P and Hassanzadeh, Arash and Kirby, Andrew C and Mavriplis, Dimitri J and Naughton, Jonathan W},journal={AIAA SciTech 2019 Forum},volume={2019-2081},year={2019},month=jan,publisher={American Institute of Aeronautics and Astronautics},}
Dynamic SGS modeling in LES using DG with kinetic energy preserving flux schemes
Michael K Stoellinger, Anthony P Edmonds, Andrew C Kirby, and 2 more authors
@article{stoellinger2019dynamic,title={Dynamic SGS modeling in LES using DG with kinetic energy preserving flux schemes},author={Stoellinger, Michael K and Edmonds, Anthony P and Kirby, Andrew C and Mavriplis, Dimitri J and Heinz, Stefan},journal={AIAA SciTech 2019 Forum},volume={2019-1648},year={2019},month=jan,publisher={American Institute of Aeronautics and Astronautics},}
Enabling high-order methods for extreme-scale simulations
@phdthesis{kirby2018enabling,title={Enabling high-order methods for extreme-scale simulations},author={Kirby, Andrew C},school={University of Wyoming},year={2018},publisher={University of Wyoming},journal={{PhD} Dissertation, University of Wyoming},}
Wind turbine wake dynamics analysis using a high-fidelity simulation framework with blade-resolved turbine models
Andrew C Kirby, Arash Hassanzadeh, Dimitri J Mavriplis, and 1 more author
@article{kirby2018wind,title={Wind turbine wake dynamics analysis using a high-fidelity simulation framework with blade-resolved turbine models},author={Kirby, Andrew C and Hassanzadeh, Arash and Mavriplis, Dimitri J and Naughton, Jonathan W},volume={2018-0256},year={2018},month=jan,publisher={American Institute of Aeronautics and Astronautics},}
Visualization and Data Analytics Challenges of Large-Scale High-Fidelity Numerical Simulations of Wind Energy Applications
Andrew C Kirby, Zhi Yang, Dimitri J Mavriplis, and 2 more authors
@article{kirby2018data,title={Visualization and Data Analytics Challenges of Large-Scale High-Fidelity Numerical Simulations of Wind Energy Applications},author={Kirby, Andrew C and Yang, Zhi and Mavriplis, Dimitri J and Duque, Earl P and Whitlock, Brad J},volume={2018-1171},year={2018},month=jan,publisher={American Institute of Aeronautics and Astronautics},}
Wind Farm Simulations Using an Overset hp-Adaptive Approach with Blade-Resolved Turbine Models
Andrew C Kirby, Michael J Brazell, Zhi Yang, and 5 more authors
23rd AIAA Computational Fluid Dynamics Conference Jun 2017
@article{kirby2017,title={Wind Farm Simulations Using an Overset hp-Adaptive Approach with Blade-Resolved Turbine Models},author={Kirby, Andrew C and Brazell, Michael J and Yang, Zhi and Roy, Rajib and Ahrabi, Behzad R. and Mavriplis, Dimitri J. and Sitaraman, Jayanarayanan and Stoellinger, Michael K.},journal={23rd AIAA Computational Fluid Dynamics Conference},volume={2017-3958},year={2017},month=jun,publisher={American Institute of Aeronautics and Astronautics},}
An Overset Adaptive High-Order Approach for Blade-Resolved Wind Energy Applications
Andrew Kirby, M Brazell, J Sitaraman, and 1 more author
@article{kirby2016overset,title={An Overset Adaptive High-Order Approach for Blade-Resolved Wind Energy Applications},author={Kirby, Andrew and Brazell, M and Sitaraman, J and Mavriplis, D},journal={AHS Forum},volume={2016-72},year={2016},month=may,publisher={American Helicopter Society},}
