CFMS has a high performance computing (HPC) facility available for CFD which comes into its own when used for complex unsteady analyses with high cell number meshes. While this seems an easy solution to the computational resource problem, even with thousands of cores an analysis may take days or weeks, which comes at a cost.
CFMS are now adopting AI methods to reduce the level of computational power needed to solve complex CFD problems. Using a combination of simulated and real world data an AI surrogate can be trained to create a digital twin of the problem in hand simplifying the computational need and potentially realising analysis in real-time.
Overall, the approach to combine CFD with automation and AI is one of many examples of integrating different disciplines for faster, better workflows. Much like CFD is a branch of fluid mechanics, CFD and Data Science is already an integrated discipline at CFMS. By supplying each part of the CFD process with new solutions and methods these are helping to reduce uncertainties, saving time and costs, obtaining better solutions every day.
The beauty of this approach is that, while traditionally CFD is associated with aviation, any application involving a fluid interacting with an object is an ideal field of application. From automotive to trains, to buildings, to microchips… if you have something flowing onto something, CFD and AI are there to make life easier and better.
If the dialogue from Apollo 13 sounded like “let me put it this way. All potential issues have been resolved automatically, no more obstacles to overcome”, it would have probably been a boring movie but a desirable engineering outcome. In reality, this is exactly what the CFMS simulation team is now doing.