Marvel*, Patricia Mooney, Cherry Murray, Elizabeth A. Rogan*,. Bahaa E. A. Saleh, Charles E. Schmid, Joseph Serene, Benjamin. B. Snavely (ex officio)*, A. F. ...
From The Editors
The Promise of Science-Based Computational Engineering By Douglass Post, Associate Editor in Chief
T
he field of engineering is poised to enter a new and exciting era. The exponential growth in computing capa-
bility from one floating-point operation per second (flops) in 1945 to 1015 in 2008 is helping us replace the standard engineering process of iterated empirical design–build–test cycles with an iterated design–mesh–analyze paradigm based on physics-based computational tools. It helps engineers be more productive and also helps manufacturers reduce time-to-market and design costs, better respond to changing market conditions, and increase their technical workforce and testing facilities’ productivity. One real-world example illustrates what we can now achieve with this paradigm. In the early 1990s, Goodyear Tire faced intense international competition. Its rivals had more engineering design resources, testing capacity, and lower production costs—Goodyear was rapidly falling behind. To respond and develop a competitive advantage, it replaced the traditional engineering process (design, build, test, and repeat) that had served it well for more than 100 years with physics-based computational engineering tools to design, mesh, and analyze new products. Engineers built and tested just the final, optimized designs, thereby reducing Goodyear’s time to market from three years to less than a year. The company started producing several new designs a year instead of one or two every few years. Goodyear is now the largest US tire manufacturer and is competitive in the world market. Whirlpool, Proctor and Gamble, Boeing, Ping Golf, and Pratt and Whitney, to name a few, have also adopted this new paradigm with similar success. This revolution is urgently needed. Today’s US dominance of advanced technology isn’t guaranteed tomorrow, and the rest of the world is rapidly catching up. US industry continues to lose market share in the US and abroad, and every spring, the Government Accounting Office’s report on 40 US major weapon system procurements concludes that most are behind schedule, over budget, and fail to meet performance goals.
May/June 2009
To survive, the US must improve the way it develops and delivers advanced technologies. The design– build–test paradigm requires large engineering staffs and extensive test facilities, takes a long time, and is costly. New designs typically are based on empirical extrapolations, which often results in products with major flaws and without sufficient innovation to compete. In contrast, physics-based computational engineering tools for iterated design, meshing, and analysis of “virtual prototypes” can result in innovative products that work. The laws of physics are simply better than empirical “rules of thumb” for designing products based on new materials and concepts: engineers can develop optimized and tested designs more quickly, make less use of test facilities, and enhance their productivity But, just as in every past technology revolution, successful adoption of this paradigm faces many challenges. The major bottlenecks are the time and resources required to develop, deploy, and support these tools, which use complex computers to integrate many complex physics and engineering effects to solve complex problems. Generally, it takes multidisciplinary teams of 20 or more engineers, programmers, and computer scientists five to 10 years to develop and deploy such tools, which must include the right physics and engineering to provide accurate, reliable answers. Moreover, • the tools must be verified and validated; • problems must be easy to set up and run; • geometry and mesh generation must be quick and easy; • the tools must run efficiently on highly complex, massively parallel computers; and • the results must be timely.
Copublished by the IEEE CS and the AIP
1521-9615/09/$25.00 © 2009 IEEE
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From the Editors
CiSE Welcomes New Editorial Board Member
P
edro Trancoso is an assistant professor in the Department of Computer Science at the University of Cyprus. His research interests include computer architecture and database systems, power-performance-efficient systems, datadriven multithreading, and general-purpose application execution on graphics processors. Trancoso has a PhD in computer science from the University of Illinois, Urbana-Champaign. Contact him at pedro at cs dot ucy dot ac dot cy.
The American Institute of Physics is a not-for-profit membership corporation chartered in New York State in 1931 for the purpose of promoting the advancement and diffusion of the knowledge of physics and its application to human welfare. Leading societies in the fields of physics, astronomy, and related sciences are its members. In order to achieve its purpose, AIP serves physics and related fields of science and technology by serving its member societies, individual scientists, educators, students, R&D leaders, and the general public with programs, services, and publications—information that matters. The Institute publishes its own scientific journals as well as those of its member societies; provides abstracting and indexing services; provides online database services; disseminates reliable information on physics to the public; collects and analyzes statistics on the profession and on physics education; encourages and assists in the documentation and study of the history and philosophy of physics; cooperates with other organizations on educational projects at all levels; and collects and analyzes information on federal programs and budgets. The scientists represented by the Institute through its member societies number more than 134 000. In addition, approximately 6000 students in more than 700 colleges and universities are members of the Institute’s Society of Physics Students, which includes the honor society Sigma Pi Sigma. Industry is represented through the membership of 37 Corporate Associates. Governing Board: Louis J. Lanzerotti (chair)*, Lila M. Adair, David E. Aspnes, Anthony Atchley*, Arthur Bienenstock, Charles W. Carter Jr*, Timothy A. Cohn*, Bruce H. Curran*, Morton M. Denn*, Alexander Dickison, Michael D. Duncan, H. Frederick Dylla (ex officio)*, Janet Fender, Judith Flippen-Anderson, Judy R. Franz*, Brian J. Fraser, Jaime Fucugauchi, John A. Graham, Timothy Grove, Mark Hamilton, Warren W. Hein*, William Hendee, James Hollenhorst, Judy C. Holoviak, Leo Kadanoff, Angela R. Keyser, Timothy L. Killeen, Harvey Leff, Rudolf Ludeke*, Kevin B. Marvel*, Patricia Mooney, Cherry Murray, Elizabeth A. Rogan*, Bahaa E. A. Saleh, Charles E. Schmid, Joseph Serene, Benjamin B. Snavely (ex officio)*, A. F. Spilhaus Jr, Gene Sprouse, Hervey (Peter) Stockman, Quinton L. Williams. *Members of the Executive Committee.
Management Committee: H. Frederick Dylla, Executive Director and CEO; Richard Baccante, Treasurer and CFO; Theresa C. Braun, Vice President, Human Resources; Catherine O’Riordan, Vice President, Physics Resources; John S. Haynes, Vice President, Publishing; Benjamin B. Snavely, Secretary.
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Additionally, each tool is highly specialized to each application, so a computational tire design tool probably isn’t very useful for airplane design. The complexity of the tools results in a failure rate for their development that ranges from 25 to 50 percent. Most companies don’t have the time, resources, or expertise to develop their own computational tools, so they tend to rely on commercial or other externally developed tools, but most independent software vendors can’t make a business case for the large, longterm investment needed to produce such tools. These tools also need a high level of support, including continual upgrades, maintenance, and porting to new platforms, all of which results in their slow development and adoption. It’s not all doom and gloom, though—a growing community is working to overcome those challenges, and the number of industries willing to invest in such tools is increasing. The US Department of Defense has launched a program to develop computational engineering tools as a key element of its effort to improve the acquisition of major weapons systems, and the National Science Foundation, NASA, and the Department of Energy are investing in computational science and engineering. The use of computational tools such as Matlab is becoming a standard part of the university engineering curriculum, and the power of workstations continues to improve in lockstep with supercomputers, meaning the computing power in today’s supercomputers will be available in workstations in five to 10 years. The history of technology shows that all major engineering paradigm shifts have been fraught with challenges and difficulties. Overcoming them often takes several generations, if not a century or two. These challenges provide the opportunity for today’s engineers to be leaders in effecting a major engineering paradigm shift and for the next generation of engineers to have an exciting and productive time exploiting this new paradigm. Douglass Post is the chief scientist at the Department of Defense High Performance Computing Modernization Program and is an associate editor in chief of this magazine. Contact him at post@ ieee.org.
Computing in Science & Engineering
