Air travel is notoriously carbon-inefficient, with many airlines going as far as to offer purchasable carbon offsets to ease the guilt over large-footprint travel. But even over just the last decade, major aircraft models have become up to a third more fuel-efficient, making much air traffic environmentally competitive with cars, and even some trains. Now, a team of researchers have leveraged supercomputing resources from the Oak Ridge Leadership Computing Facility (OLCF) to design yet more efficient jet-engine turbines.
“When designing turbines, there is a balance to be struck between maximizing aerodynamic efficiency, which can reduce with increased blade spacing, and minimizing overall weight, which increases with reduced blade spacing,” said Peter Vincent, a professor of computational fluid dynamics at Imperial College London, in an interview with Oak Ridge’s Matt Lakin. “Designers want to keep the blades close together to avoid unsteadiness in the flow and extract as much energy as possible, but they also want as few blades as possible in order to keep the engine light. To help strike the right balance, they need computational tools that can accurately capture the unsteady, turbulent flow physics in the vicinity of the complex blade geometries. That capability so far has been missing from the industry’s standard set of tools.”
Because that capability has been missing, researchers have instead relied on wind tunnels and less precise simulations. “Because you’re averaging everything out, you’re losing a lot of the unsteady physics,” Vincent said. “So, it’s certainly cheap but not necessarily trustworthy.”
To remedy this, the team turned to the OLCF’s (now-retired) Titan supercomputer, which delivered 17.6 Linpack petaflops. On Titan, they used 5,760 GPUs and over 180 million core hours to model 3D airflow over a jet turbine – a simulation with tens of billions of potential values that operated through a Python-based framework called PyFR.
“The OLCF was completely enabling for us,” said Freddie Witherden, who is an assistant professor of engineering at Texas A&M University. “Before Titan, this study wouldn’t have been possible. These were some of the largest and most accurate computational fluid dynamics calculations ever undertaken, capturing all the physics at very high fidelity. The scale of the problem was so big it simply would not have been possible to run it on any other machine. It took two years to set up and run the simulations, and then we analyzed the data.”
Ultimately, the researchers hope to more widely distribute the simulation tools, which they believe could help engineers transform jet engine design and reduce reliance on wind tunnels. “Reducing or eliminating the need for wind-tunnel testing would be a transformational development, and this study demonstrates how it could be possible,” Vincent said. “The technology we are developing is very accurate and captures all the flow physics, including the turbulence. So, it could one day start to replace wind tunnels as the gold standard, helping make flight cheaper, cleaner, and more economical.”