AMES, Iowa – Three thin leaflets blew open and blood blasted through an artificial heart valve, the center stream firing reds and yellows, the colors indicating a flow speed up to 125 centimeters per second. When the leaflets slammed shut, the flow turned to light blue eddies, indicating blood flow had nearly stopped.
And then Ming-Chen Hsu, an Iowa State University assistant professor of mechanical engineering, searched his computer for another video and clicked play.
This time the tip of a wind turbine blade appeared on his monitor, constantly moving, flexing and vibrating as the blade rotated around the rotor hub. Red indicated air moving at a relative speed of 52 meters per second over the top of the blade; blue and green marked the slower air around the blade.
These are computer models featuring technologies called computational mechanics, fluid-structure interaction and isogeometric analysis. They show the flow fields and stresses that mechanical systems have to withstand. And they’re part of a toolkit Hsu and his research group are developing to improve the design, engineering and operation of all kinds of machines.
“If we are able to use computers to model and simulate these engineering designs, we can save a lot of time and money,” Hsu said. “We don’t have to build and test every prototype anymore.”
Hsu said it would be impractical, for example, for the wind energy industry to build and test full-scale prototypes of each and every idea for improving the performance of wind turbines.
Instead, the wind energy industry can opt for computational models. Hsu said they’re based on complex mathematical equations. They’re full of data. And studies show they’re accurate.
Using the models, “We can predict the real physics of the problems we are looking at,” he said.
And so those videos showing blood flowing through an artificial heart valve or the vibrations of a wind turbine blade are a lot more than colorful graphics. To engineers, they can be as good as full-scale prototypes for studying durability and performance.
Hsu has a background in computational mechanics and started modeling wind turbines during his doctoral studies at the University of California, San Diego. He started modeling heart valves as a postdoctoral research associate at the University of Texas at Austin.
He’s been at Iowa State since the fall of 2013 and has built a research group that currently includes doctoral students Austin Herrema, Chenglong Wang, Michael Wu and Fei Xu plus undergraduate student Carolyn Darling. The group is now working on two wind turbine studies and an engine project:
- They’re modeling the performance of the “Hexcrete” concrete wind turbine towers being developed by Sri Sritharan, Iowa State’s Wilson Engineering Professor in Civil, Construction and Environmental Engineering. The goal is to use prefabricated concrete to build taller wind turbine towers that can access the steadier winds at 120 meters and higher. The project is primarily supported by the U.S. Department of Energy.
- They’re also developing software to help engineers design wind turbine blades. The software will bridge a wide gap between blade design tools and performance simulations. The project is supported by a National Science Foundation grant that established Iowa State’s graduate program in wind energy science, engineering and policy.
- And Hsu’s research group is modeling the performance of the rotors inside gas turbines. The models will help engineers design the next generation of turbine engines. The project is supported by a grant from the U.S. Army Research Office.
Hsu, who teaches courses in fluid mechanics, said the modeling can be applied to all sorts of questions about a machine. In wind turbines, for example, the models can provide answers about material stress and fatigue, rotor aerodynamics, blade design, the wake behind turbines and power efficiency.
“Ten to 15 years ago, computational fluid-structure interaction was new to everyone,” Hsu said. “But with the success of this field, more and more methods are being picked up by industry. Our computational methods are improving engineering designs.”