The pitch for GE Research is easy, as Richard Arthur, senior director of computational methods research for GE Research, explained at the latest meeting of the DOE’s Advanced Scientific Computing Advisory Committee (ASCAC): a third of the electrons in the world that flow through devices are generated on GE equipment; every two seconds, a plane takes off using GE engines; 16,000 medical scans are performed on GE equipment every minute — the list goes on. At the meeting, Arthur highlighted how crucial HPC resources — specifically, DOE-provided HPC resources — have been to the company’s gargantuan operations and research endeavors and highlighted how the exascale era stands to transform them even more.
GE’s equipment, Arthur said, is tightly regulated, has a long expected life and is very expensive. “When they’re not working, there are significant consequences,” he said. So, when GE Research runs models during the development of this equipment: “It is very important that these not be ‘garbage in, garbage out’ kinds of models.”
A lot of GE Research’s work occupies “the swim lane of computational fluid dynamics,” Arthur continued: the flow of gases through jet engines, the flow of water through hydroelectric plants, the flow of wind through wind turbines and so forth. In service of this work is a lot — a lot — of time and grants from the Department of Energy.
“By 2017,” Arthur said. “in peer-reviewed competitive grants, GE had already used over 1 billion core-hours on the National Lab machines across a number of the labs, and by today, that’s 14 INCITE awards, 22 ALCC [ASCR Leadership Computing Challenge] awards, 6 HPC4Manufacturing [awards], and other directors’ discretionary grants.”
Energy
The time, of course, is put to good use. Some years ago, GE — the largest supplier of gas turbines in the world — was struggling to isolate a problem affecting its turbines. “Before having access to these machines, we could only look at one combustor at a time,” Arthur said. “But there was an interaction between multiple combustors that was creating some problems that we would only be able to see once we were able to simulate multiple combustors.”
So GE received assistance from the National Labs, managing to simulate multiple combustors, isolate the problem (a fuel hole that needed to be moved by a fraction of an inch) and dramatically improve its turbine efficiency. (This work also won HPCwire’s 2016 Readers’ Choice Award for Best Use of HPC in Energy).
With regard to wind turbines, GE Research has been using a 2020 ALCC award to understand the impact of coastal low-level jets on wind energy. “We wanted to understand these effects so that we could predict what the performance of the wind turbine farm would be and understand the reliability of the operations,” Arthur said. Further, GE Research is now working to understand the wake effects that the first turbines to encounter wind have on the turbines further back — an effect that Arthur said could reduce efficiency by up to 40 percent, for which no physical wind tunnel is available for testing.
“But [we’re] still not able to do complex interactions with things like wave swells and more complicated atmospheric phenomena [or] interactions between wind farms,” Arthur said. “With exascale, we believe that the wind farm-wind farm interactions become feasible [to simulate].”
Aviation
Another of the major efforts being undertaken by GE Research is the so-called “RISE” jet engine program, which stands for “Revolutionary Innovation for Sustainable Engines.” RISE is a joint venture between GE and French multinational Safran and the third in a line of aircraft modeling and improvement initiatives dating back to 1979. The previous generation of modeling, called LEAP, achieved a 15 percent increase in fuel efficiency for GE’s engine designs; RISE has a goal of a 20 to 100 percent reduction in carbon emissions and a further 20 percent reduction in fuel burn.
“This is seen as a path to hydrogen [fuel],” Arthur said. “But to get the benefit of the zero carbon emissions out of hydrogen as a fuel, there are things you need to address.” Those include: price per kilometer (hydrogen fuel is expensive); increased volume per joule (hydrogen takes up more space); and, relatedly, decreased range (as less fuel can be stored). “In order to make hydrogen viable,” Arthur said, “we have to improve the propulsive efficiency significantly.” (RISE, Arthur later added, “is the path to hydrogen, but also to other things, such as open fan design as opposed to the nacelle.)
Doing this means conducting extremely detailed, unprecedented simulations of the engines in question. At the start of its simulation efforts many years ago, GE was only able to simulate one blade of a turbine at a time, which was of limited use. (“Really, what we care about in terms of the airflow is not the blade but the passage between two blades.”) That scaled up over time: first to multiple blades, then to multiple rows of blades, then to multiple stages of the engine. Simulating the full engine at full scale and exacting accuracy, Arthur explained, is the dream.
But, of course: “At any given time, we’ve only been able to simulate a problem as large as will fit on a given system,” Arthur said. Over the years, GE Research had leveraged a variety of systems for its turbine simulation work, ranging from Oak Ridge National Laboratory’s Jaguar system to Argonne National Laboratory’s Mira system to its own internal Cray systems. And, while these produced valuable results — Arthur said that the research on Mira drastically changed their approach to handling ice formation — the full engine simulation has remained elusive.
“Before we can run a flight test, we run a rig test,” Arthur said. “This is typically done in a wind tunnel, but these wind tunnels are smaller than the actual product. … We build this tiny version that will fit into NASA’s wind tunnel, and the relevant Reynolds numbers for the airflow of the small engine are significantly lower when compared to the fans that you see in the full product. So there is no wind tunnel that we can use to test the design at the product scale. So that is not tested until the flight test.”
So, when GE Research was dreaming of exascale back in 2019, some of their dreams included the use of exascale systems to reach another level of engine simulations.
“We laid some foundation for this with the 2021 INCITE [program] and this completed the first-of-their-kind wall-resolved large eddy simulations of the full 3D open fan at a high Reynolds number,” Arthur said. “This was still at rig test scale. … If we wanted to perform these same kinds of simulations at the flight scale, we would need a much bigger machine.”
“And this,” Arthur continued, “is where we approached Oak Ridge and ultimately put into the ALCC program this proposal to leverage basically everything we could possibly get access to.”
And the award was successful: significant time on the first official exascale system, Frontier, as well as time on Oak Ridge’s Summit system and NERSC’s Perlmutter system. (“And you can bet that if anybody leaves spare hours available we will be eagerly seeking to scoop those up,” Arthur said.)
“To run the takeoff test at the rig test scale, that simulation would be about 70,000 node hours on Summit,” Arthur added. “That same simulation at product scale … is over 6 million node hours on Summit.”
“So,” Arthur concluded, “we love Frontier!”