Welcome to Workshop Wednesday, a regular feature of the Tecplot blog. Here, we show you how engineers use our visualization software to create inspiringly accurate—sometimes even world-changing—design simulations.
Darrieus wind turbine
Courtesy of Wind Turbine Zone
When it comes to alternative energy, every advancement counts, every improvement is welcome.
It’s all good.
So when Travis Carrigan, a technical sales engineer with Pointwise, Inc., which creates software used for grid generation and preprocessing for computational fluid dynamics (CFD), published his thesis proving that the efficiency of a Darrieus wind turbine could be increased by at least 7 percent using independent wind turbine CFD post-processing tools and automated methods for optimizing the blade shape, it didn’t go unnoticed.
Until recently, most research in wind energy technology has been focused on macro power generation devices like horizontal axis wind turbines. These massive devices, which are typically more than 100 meters in height and generate at least a megawatt of power, are well-suited for commercial interests in large industrialized regions in the U.S. and Europe. This has been due in part to the fact that researchers could achieve greater levels of optimization with macro power devices on the limited funds that were available.
Thanks to the U.S. government’s increased commitment to green technology, however, quite a bit more research funding has begun flowing into micro power generating devices like vertical axis wind turbines. Small, quiet, and easy to install, vertical axis wind turbines operate well in fluctuating turbulent wind conditions like those found around buildings in cities, and suburban or urban areas. Rotating around an axis that’s perpendicular to the wind, they can take wind from any direction, consistently outputting a few kilowatts of power.
And it was these that Carrigan’s studies focused on.
Any independent tools can be implemented in the optimization process, but for this particular problem, Carrigan selected Pointwise for the geometry generation and meshing, ANSYS FLUENT for the solver, and Tecplot 360 for the post-processing.
“My motivation was to maximize the efficiency of a vertical axis wind turbine by allowing the blade shape to change as the optimization progressed,” said Carrigan. His objective was to maximize blade efficiency, reduce reliance on designer experience—which varies widely—and ultimately reduce design time and cost.
To read more about how he pulled this off and what this means for the wind power industry, click here.