The Birth of a Simulation Benchmark Model
When design engineers run a simulation in their favorite engineering software, massive amounts of number crunching occurs behind the scenes to simulate a particular event. Such simulation is critical to designers who can save time and costs by doing fewer real-world tests and more digital tests of their designs. But how do we know the simulations are accurate?
Let’s take a look at one example recently featured in ORNL Review. A team of mechanical engineers at Sandia National Laboratory was given 60 million processor hours this year on Oak Ridge Leadership Computing Facility‘s Jaguar supercomputer to conduct high-fidelity simulations of combustion in advanced engines.
The models they create are validated against benchmark experiments to simulate turbulent combustion at different scales. Once validated, the models can be used by design engineers, as the article explains:
These models are then used in engineering-grade simulations, which run on desktops and clusters to optimize designs of combustion devices using diverse fuels. Because industrial researchers must conduct thousands of calculations around a single parameter to optimize a part design, calculations need to be inexpensive.
The Jaguar supercomputer is a Cray XT5. It has a peak speed of 2.33 petaflops. That’s more than two thousand trillion calculations per second. Multiply that by the 60 million processor hours Sandia was given to simulate combustion, and it equals quite a bit of confidence in their benchmarks.
Learn more about Jaguar in the videos below.
Source: ORNL Review.