Ford Motor Company has recognized HPC as a strategic imperative since the 1980s. Today, the company uses HPC clusters from IBM and HP to bring new innovations to market faster and to reduce production costs. Ford engineers recently applied this capability with great success to optimize the design of their EcoBoost engine technology, which is expected to enable better fuel economy in more than 80 percent of Ford’s models by 2013.
Lawrence Livermore National Laboratory has worked with several domestic oil companies to develop an advanced reservoir-monitoring technology. Using the supercomputing power of its HPC machines, Livermore and its industry partners developed a technique that integrates separate measurement data to predict subsurface fluid distribution, temperature and pressure. The system obviates the need for numerous observation wells, and the low-cost system works well for oil and gas recovery; carbon capture and sequestration; and geothermal energy.
Established in 1898, Goodyear Tire and Rubber Company is the only major domestic tire company. Coming into the 21st century, Goodyear needed to improve its time to market for new products to remain competitive in the global tire market. Goodyear focused its efforts on designing a new, innovative, all-season tire that would provide major improvements in performance and safety—and the company used HPC modeling and simulation to do it.
Boeing is a world leader in the aerospace industry and a largest manufacturer of commercial jetliners and military aircraft. Boeing uses HPC modeling and simulation to remain a leader in an increasingly competitive global market. Receiving a grant from the Department of Energy’s Innovative and Novel Computational Impact on Theory and Experiment (INCITE) competition, Boeing partnered with Oak Ridge National Laboratory to undertake a large-scale computational science project aimed at helping the company build a better airplane.
A team of LLNL scientists, led by Dr. Kambiz Salari, in partnership with engineers from Navistar, NASA, the U.S. Air Force and other industry leaders, utilized HPC modeling and simulation to develop technologies that increase semi-truck fuel efficiency by 17 percent. The team’s results, if applied to all U.S. trucks, would save 6.2 billion gallons of diesel fuel and reduce CO2 emissions by 63 million tons annually. Projected annual cost savings, based on U.S. average diesel fuel costs of $3.91, are approximately $24.2 billion.
Accurate wind forecasting is essential to efficiently harness wind power and to help the wind energy industry achieve its wind-power production goals. Working with industry partners, scientists and engineers at Lawrence Livermore National Laboratory are using supercomputers to blaze new ground in this field. Siemens Energy, Inc. has collaborated with Lawrence Livermore National Laboratory to create high-resolution atmospheric models to improve the efficiency of individual wind turbines and entire wind farms.