Physics-based Performance
Prediction at Goodyear
Loren Miller
DataMetric Innovations, LLC
National Defense Industrial Association
"CREATE Physics-based Performance Prediction"
March 8, 2011
My Background
• While at Goodyear, responsible for physics-based
performance prediction, high performance computing, and
physics research.
• Initiated and lead Goodyear's relationship with Sandia
National Laboratories.
• Now President, DataMetric Innovations, LLC
"The Intersection of Science, Engineering, & IT"
• Opinions expressed are my own and do not necessarily reflect
the views of The Goodyear Tire & Rubber Company.
Goodyear Background
• Founded in 1898
• Headquartered in Akron, OH
• One of the world's leading tire
companies
• 57 production facilities in 23
countries
• $16.3 B in 2009
Prototype-based Design
• Historically, tires were developed by
creating a new design concept,
building prototypes, then testing them
in the lab and on the road.
• The design, build, test cycle is
complex, lengthy, and expensive.
• Significant resources were capitalized
and dedicated to experimental tire
building and testing.
• Design processes and release
procedures were written assuming the
design/build/test process.
1992 Business Background
• Tire industry is a very competitive oligopoly.
• Failed takeover attempt had drained cash reserves.
• Under pressure to reduce R&D expenditures, VP's of Research and Product
Development sponsored a study of alternative product development methods.
• Three alternatives were identified:
• More efficient process of building and testing prototypes
• Extensive use of predictive testing
• Physics-based performance prediction.
Physics-based performance prediction was only alternative
that might substantially reduce costs over time.
Vision
New
Products
1
Road Test
10
Predictive Tests
1,000 Simulations
Scientific Foundation
Technical Complexity
• Tires are surprisingly complex.
• Geometry
• Materials
• Service conditions
• 1992: state-of-the-art
performance prediction took
months per design for skilled and
dedicated finite element
analysts.
By the time designers got answers,
they’d forgotten their questions.
Internal Complexity
• Modeling Challenges
• Incompressible, non-linear, viscoelastic material with high (~40%)
cyclic strains (rubber)
• Inextensible fiber reinforcements
(polyester, steel, nylon, aramid)
• Flexible structure (sidewall)
• Detailed tread patterns
• Wide eigenvalue spectrum
• Expensive, low fidelity solutions
~ 60 Million Cycles
During an 80,000 Mile
Tire Lifetime
Material Complexities
• First tensile pull to 100% - red
circles
• Second pull to 200% - blue
triangles
• Third pull to 300% - brown
diamonds
• Initial stress/strain for sample
pulled to 300% - black
squares
Extraordinarily complex
material properties.
Hanson, Hawley, and Houlton,
Los Alamos National Laboratory,
“A Mechanism for the Mullins Effect,”
2006.
Unacceptable Solution Times
• Largest model ever run at Goodyear in 1994 had 90,000 degrees of freedom.
• Took months to run a smooth, axisymmetric static model.
• Estimated minimum model size to simulate tread wear was 250,000 degrees of
freedom.
• Tread wear requires a tread pattern and rolling at varying slip angles!
• Solution times increased as the cube of the model size.
• Estimated at 15.6 years on a Cray Y-MP using more memory than Cray ever
put in a machine.
• By comparison, build and test for tread wear required four to six months.
No commercial code was capable
of solving this problem.
Sandia Partnership
• In 1993, Goodyear partnered with Sandia National Laboratories
to develop new technology to solve its "intractable problem."
• CRADAs included both experimental and computational
projects.
• Extraordinarily successful collaboration!
• Enabled GT to solve intractable design problems.
• Enabled Sandia to solve intractable design problems.
Win-win collaboration!
Fidelity & Time
Solution time compressed from 32.2 years to 5 days!
Award-Winning Technology
Award-Winning Tires
Game Changer
• 2002 Annual Report: "Our objective this year is very simple: Drive the turnaround
of our Company.
• 2003 Annual Report: "The (Assurance) tire was developed with unprecedented
speed, utilizing our very best technology and extremely talented associates.
• 2004 Annual Report: "We accelerated the introduction of high impact new
products.
• 2009 Annual Report: "Our new product engine is poised to take advantage of the
demand for high-value-added tires and to do so with unmatched speed to
market.
• 2011 Earnings Call, February 20: "Our innovation engine, again, delivered in
2010. The percentage of new products in our overall lineup is the highest ever
and is driving record revenue per tire increases, supporting a richer mix and
increasing our ability to win in targeted markets."
Unmatched speed to market!
Lessons Learned
• Post mortem finite element analysis did not lead to breakthroughs
in time-to-market, cost, or innovation.
• Conversion to "innovation engine" took 10+ years of consistent
direction and purpose.
• Technical partnership was essential.
• Paradigm shift from prototype-based to physics-based product
development was "gut wrenching" and required extensive
verification and validation.
• Design process standardization, both platform-based and modelbased, was required.
• Product designers had to do their own physics-based performance
prediction.
Bottom Line Results
• Product development times were reduced
67%, from three years to one.
• Expenditures on prototype building and testing
dropped 62%.
• Unprecedented string of award-winning new
products resulted from the ability to evaluate
many more new product alternatives.
Physics-based performance prediction
is a strategic asset at Goodyear.
Concern for Our Future
• "The scientific and technological building
blocks critical to our economic leadership
are eroding at a time when many other
nations are gathering strength.
• "This nation must prepare with great
urgency to preserve its strategic and
economic security.
• "We are worried about the future prosperity
of the United States."
Augustine et al., "Rising Above the
Gathering Storm." US National
Academies, 2007.
Rapidly Approaching Category 5!
Global Competition
• "Our global competitors are well aware of
the great potential of computer simulation.
Throughout Europe and Asia, governments
are making major investments...
• "We are in danger, once again, of
producing world-leading science but
leaving it to our competitors to harvest the
technological and economic advantages."
Oden et al., "Simulation-Based
Engineering Science." US National
Science Foundation, May, 2006.
Leaving it to our competitors…
International Assessment
• "Today we are at a tipping point...
• "The world of computer simulation is
becoming flatter every day.
• "Our continued capability as a nation to
lead in simulation-based discovery and
innovation is key to our ability to
compete in the 21st century."
Glotzer et al., "International
Assessment of Research and
Development in Simulation-Based
Engineering and Science." WTEC,
2009.
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