Loren Miller of Goodyear Tire & Rubber spoke about the company’s switch to analysis-based tire design in 1994. The traditional design – build – test process was very expensive and clearly needed to be changed, but engineers were skeptical about switching to modeling and analysis. Why? Modeling tires is difficult and complex. The simple-looking tire conceals all kinds of hidden complexity: 18 components, 12 compounds, 2 fabrics, 2 kinds of steel, and 60 other raw materials. And the rubber itself is a pain; it’s incompressible. The estimate on turnaround time for the kind of modeling and analysis the company wanted to do with the technology they had was 16 years.

What to do? Goodyear worked with SANDIA to develop codes specifically for Goodyear that slashed turnaround time. Over time, Goodyear designed its own automated design/ analysis systems and increased its Linux clusters from 16 to 128 nodes.

To date, expenditures on tire building and testing dropped from 40% of R&D budgets to 15%, resulting in $100 million dollars redirected to other R & D needs. Key product design times went from three years to one. Mr. Miller describes Goodyear as an innovation company, not a tire company, with one winning strategy: continue to invest in R&D.

 

Doug Ball of Boeing described his company’s use of numerical simulations and computational fluid dynamics to impact the design of the 787. Computational modeling has touched every element of the 787: engine, aerodynamics, structures, materials, systems, air traffic management, and engine/ airframe integration.

For example: When the 777 was designed, 77 physical wings were tested in the wind tunnel. For the 787, that number was reduced to 11. For the next plane off the line, they’ll have it down to six.

Computational models can predict air and structure temperatures inside the engine and model problems such as lost fan blades. Static engine tests and modeling of compression and shock patterns are part of Boeing’s goal to confine the 787’s noise to the runway.

Mr. Ball recapped the shortening of the product development cycle and its ongoing challenges:

·         In 1980, they had the equations they needed, but not the hardware to solve them.

·         Today the hardware is improved, but the equations have advanced.

·         Boeing’s investment in legacy software is huge.

·         They need more efficient ways to move applications between HW options.

·         The industry needs timely access to new hardware for testing.

He also posed a parting, provoking question: Today, aircraft certification is done by demonstration. Tomorrow, aircraft certification will be done by simulation. When is tomorrow, and how do we get there? He’s certainly come to the right place – SC08 – to find the next generation of innovators who are working on answers like those.