In the 60s, nearly all beverage cans were a seamed wraparound of tin-plated steel. Then the aluminum industry developed a way to make seamless cans -- drawing them from a flat sheet with a separate lid clamped on after filling. "That started us into light weighting," says Trageser, "to save our can manufacturing customers' costs and to compete with steel." Of 100 billion beverage cans made in the U.S. each year, about 95 percent -- one per person per day -- are aluminum.
The story goes on. Aluminum costs more than steel, and the price has been rising. Steel "minimills" now have continuous casting processes that make sheet steel thin enough to form seamless cans. And there is competition from other materials as well. "We h ave to find ways to make cans lighter and lighter to keep fending off polymers, steel and glass. Lighter cans means lower prices to the consumer, who's then more likely to buy cans off the grocery shelf instead of two-liter bottles or glass."
ALCOA's answer is lightweighting, designing cans to use the thinnest aluminum possible within the constraints of strength and appearance.
In the 1970s the aluminum in beverage cans was nearly as thick as aluminum gutters, .015 inches. Lightweighting progress leveled-off in the early 80s, then resumed in 1984 due in part to computer modeling.
Using supercomputing at the Pittsburgh Supercomputing Center, ALCOA has developed a sophisticated approach to finite-element modeling of beverage cans that allows engineers to develop prototype can designs with a high level of confidence that the modeling accurately predicts how the can will perform under the stress of manufacturing, distribution and use. This modeling reduces the need for costly laboratory prototypes and signifcantly cuts time-to-market for a new design.
Researchers: Bob Dick & Andy Trageser, ALCOA Laboratories
Hardware: CRAY Y-MP C90
Software: User-developed code
Keywords: aluminum, finite-element, beverage can, lightweighting, sheet thickness, dynamic snap-through, dent analysis, 3-D modeling, manufacturing, can design, materials, drop test.
Related Material on the Web:
Projects in Scientific Computing, PSC's annual research report.
References, Acknowledgements & Credits