Better Combustion for Power Generation

Estimated reading time: 10 minutes

In 2014, one such pulsation caught researchers' attention during a full-scale test of a gas turbine. The test revealed a combustion instability that hadn't been observed during combustor development testing. The company determined the instability levels were acceptable for sustained operation and would not affect gas turbine performance. But GE researchers wanted to understand its cause, an investigation that could help them predict how the pulsations could manifest in future designs.

The company suspected the pulsations stemmed from an interaction between adjacent combustors, but they had no physical test capable of confirming this hypothesis. Because of facility airflow limits, GE is able to test only one combustor at a time. Even if the company could test multiple combustors, access-visibility and camera technology currently limit the researchers' ability to understand and visualize the causes of high-frequency flame instabilities. So GE placed a bet on high-fidelity modeling and simulation to reveal what the physical tests could not.

The company asked its team of computational scientists, led by Yan, to see if it could reproduce the instability virtually using high-performance computers. GE also asked Yan's team to use the resulting model to determine whether the pulsations might manifest in a new GE engine incorporating DOE-funded technology and due to be tested in late 2015, less than a year away. GE then challenged Yan's team, in collaboration with the software company Cascade Technologies, to deliver these first-of-a-kind results before the 2015 test to demonstrate a truly predictive capability.

"We didn't know if we could do it," Yan said. "First, we needed to replicate the instability that appeared in the 2014 test. This required modeling multiple combustors, something we had never done. Then we needed to predict through simulation whether that instability would appear in the new turbine design and at what level."

Such enhanced modeling and simulation capabilities held the potential to dramatically accelerate future product development cycles and could provide GE with new insights into turbine engine performance earlier in the design process instead of after testing physical prototypes.

But GE faced another hurdle. To meet the challenge time frame, Yan and his team needed computing power that far exceeded GE's internal capabilities.

A computing breakthrough

In the spring of 2015, GE turned to the OLCF for help. Through the OLCF's Accelerating Competitiveness through Computational Excellence (ACCEL) industrial partnerships program, Yan's team received a Director's Discretionary allocation on Titan, a Cray XK7 system capable of 27 petaflops, or 27 quadrillion calculations per second.

Yan's team began working closely with Cascade Technologies, based in Palo Alto, California, to scale up Cascade's CHARLES code. CHARLES is a high-fidelity flow solver for large eddy simulation, a mathematical model grounded in fluid flow equations known as Navier-Stokes equations. Using this framework, CHARLES is capable of capturing the high-speed mixing and complex geometries of air and fuel during combustion. The code's efficient algorithms make it ideally suited to leverage leadership-class supercomputers to produce petabytes of simulation data.

Cascade's CHARLES solver can trace its technical roots back to Stanford University's Center for Turbulence Research and research efforts funded through DOE's Advanced Simulation and Computing program. Many of Cascade's engineering team are alumni of these programs. Although the CHARLES solver was developed to tackle problems like high-fidelity jet engine simulation and supersonic jet noise prediction, it had never been applied to predict combustion dynamics in a configuration as complex as a GE gas turbine combustion system.

Using 11.2 million hours on Titan, members of Yan's team and Cascade's engineering team executed simulation runs that harnessed 8,000 and 16,000 cores at a time, achieving a speedup in code performance 30 times greater than the original code. Cascade's Sanjeeb Bose, an alumnus of DOE's Computational Science Graduate Fellowship Program, provided significant contributions to the application development effort, upgrading CHARLES' reacting flow solver to work five times faster on Titan's CPUs.

Leveraging CHARLES' massively parallel grid generation capabilities -- a new software feature developed by Cascade -- Yan's team produced a fine-mesh grid composed of nearly 1 billion cells. Each cell captured microsecond-scale snapshots of the air-fuel mix during turbulent combustion, including particle diffusion, chemical reactions, heat transfer, and energy exchange.

Working with OLCF visualization specialist Mike Matheson, Yan's team developed a workflow to analyze its simulation data and view the flame structure in high definition. By early summer, the team had made enough progress to view the results: the first ever multicombustor dynamic instability simulation of a GE gas turbine. "It was a breakthrough for us," Yan said. "We successfully developed a model that was able to repeat what we observed in the 2014 test."

The new capability gave GE researchers a clearer picture of the instability and its causes that couldn't be obtained otherwise. Beyond reproducing the instability, the advanced model allowed the team to slow down, zoom in, and observe combustion physics at the sub-millisecond level, something no empirical method can match.

"These simulations are actually more than an experiment," Citeno said. "They provide new insights which, combined with human creativity, allow for opportunities to improve designs within the practical product cycle."

With the advanced model and new simulation methods in hand, Yan's team neared the finish line of its goal. Applying its new methods to the 2015 gas turbine, the team predicted a low instability level in the latest design that was acceptable for operation and would not affect performance. These results were affirmed during the full-scale gas turbine test, validating the predictive accuracy of the new simulation methods developed on Titan. "It was very exciting," Yan said. "GE's leadership put a lot of trust in us."

With the computational team's initial doubts now a distant memory, GE entered a world of new possibilities for evaluating gas turbine engines.

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