World’s first exascale supercomputer shows how worn turbine blades drain jet engine power

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World’s first exascale supercomputer shows how worn turbine blades drain jet engine power
EfficiencyEnergy &AmpEnvironment
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Scientists have used the Frontier supercomputer to find how microscopic turbine blade damage cuts jet engine efficiency and durability.

Scientists have used one of the world’s most powerful supercomputers to find out how microscopic damage to turbine blade s undermines jet engine performance, fuel efficiency and durability.The project brought together researchers from the University of Melbourne, GE Aerospace, and the Oak Ridge National Laboratory , who ran simulations on the Frontier supercomputer.

The system is the first exascale supercomputer for open science, capable of more than one quintillion calculations per second.Known as the Hewlett Packard Enterprise Frontier , the Frontier, which is the world’s most powerful supercomputer for open science analyzed how surface degradation on high-pressure turbine blades affects aerothermal efficiency and heat transfer inside jet engines. “Degradation happens at the microscale, and that makes it very difficult to simulate because of the discrepancy in time and length scales – you’ve got a big blade, but then you’ve got all these minute changes to the surface,” Richard Sandberg, chair of computational mechanics in the University of Melbourne’s Department of Mechanical Engineering, said.Tiny microscopic flawsHigh-pressure turbines in jet engines operate under extreme conditions, with gas temperatures exceeding 3,600 degrees Fahrenheit . Over time, turbine blades are exposed to surface roughness due to erosion, oxidation and mechanical wear.“This roughness can significantly increase aerodynamic loss, which leads to worse fuel efficiency, and heat flux, which leads to reduced durability and more frequent engine maintenance,” Greg Sluyter, a Turbine Aerodynamics team senior engineer at GE Aerospace, noted. While this degradation is unavoidable, predicting its impact on engine efficiency has long challenged engineers. To address the issue, the team used the Frontier’s exascale computing power to perform simulations containing between 10 and 20 billion grid points in size with 1017 degrees of freedom.The instantaneous wall heat flux on the suction surface of turbine blades in a high-pressure turbine engine.Credit: Thomas Jelly, University of Melbourne in AustraliaThey revealed that the previous notions of how roughness affects viscous flow in simple geometries do not apply well to the geometries of turbine engines. “All of our understanding of roughness effects has been built on what we call canonical problems,” Thomas Jelly, PhD, professor at the University of Melbourne and first author of the study, stated. “But when you look at roughness effects on a blade, it’s actually quite different because there are a lot of fluid dynamic and thermodynamic phenomena that are absent in these canonical cases but present inside jet engines,” he continued.The novel simulations showed that roughness effects on turbine blades behave very differently. This is largely due to the fact that the blades transition between laminar and turbulent flow.An engineering challengeAccording to the team, surface roughness was found to accelerate this transition, significantly increasing heat transfer to the blade and raising aerodynamic losses. Both effects reduced engine efficiency and shortened component lifespan. It led to higher fuel consumption and more frequent maintenance.The simulations relied on direct numerical simulation, a method that resolves all relevant turbulence scales without using modeling assumptions. To enable this, the team upgraded its in-house computational code, the High-Performance Solver for Turbulence and Aeroacoustics Research . They then optimized it for Frontier’s AMD GPU architecture. Individual simulation cases took weeks to complete. Running the same calculations on a standard laptop would have required more than a thousand years. Flow past HPT vane with micron-scale surface roughness at Reynolds number=590,000 and Mach number=0.92.Credit: Thomas Jelly, University of Melbourne in AustraliaGE Aerospace engineers are already using these insights to next-gen HPT designs. This includes joint work with NASA on the Hybrid Thermally Efficient Core Project to improve fuel efficiency in commercial engines.The research also supports broader efforts to reduce aviation’s fuel consumption and emissions. More efficient turbines mean less fuel burned for the same thrust, which directly reduces operating costs and environmental impact. The team is also exploring better cooling strategies.“In the long term, we will develop models that can better predict this so that the designers can have more confidence in their predictions and therefore design a more efficient engine,” Sandberg concluded in a press release.The study has been published in the ASME Journal of Turbomachinery.

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