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Angela B. Shiflet and George W. Shiflet:
Introduction to Computational Science
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MODULE 1.1
Overview of Computational Science
Many significant applied and basic research questions in science today are interdis-
ciplinary in nature, involving physical and/or biological sciences, mathematics, and
computer science. For example, Nature reported that John Krebs, chief executive of
Britain’s Natural Environment Research Council, considers that the environment
“requires a ‘new breed’ of scientist, and new ways of problem solving that cut across
traditional disciplines” and that Britain expects a shortage of “environmental scien-
tists with mathematical, computational and statistical skills.” (Masood 1998)
The Human Genome Project “has created the need for new kinds of scientific
specialists who can be creative at the interface of biology and other disciplines, such
as computer science, engineering, mathematics, physics, chemistry, and the social
sciences. As the popularity of genomic research increases, the demand for these spe-
cialists greatly exceeds the supply.... There is an urgent need to train more scien-
tists in interdisciplinary areas that can contribute to genomics,” according to Francis
Collins in an article in Science (Collins et al. 1998).
Computational science is a fast-growing interdisciplinary field that is at the in-
tersection of the sciences, computer science, and mathematics. There is a critical
need for scientists who have a strong background in computational science. Much
scientific investigation now involves computing as well as theory and experiment.
Computing can often stimulate the insight and understanding that theory and experi-
ment alone cannot achieve.
This field of computational science combines computer simulation, scientific
visualization, mathematical modeling, computer programming and data structures,
networking, database design, symbolic computation, and high performance com-
puting with various scientific disciplines. Computer simulation and modeling offer
valuable approaches to problems in many areas, as the following examples indicate.
1. Scientists at Los Alamos National Laboratory and the University of Min-
nesota wrote, “mathematical modeling has impacted our understanding of
HIV pathogenesis. Before modeling was brought to bear in a serious manner,
AIDS was thought to be a slow disease in which treatment could be delayed until
symptoms appeared, and patients were not monitored very aggressively. In the
4
Module 1.1
lar
ge, multicenter AIDS cohort studies aimed at monitoring the natural history
of the disease, blood typically was drawn every six months. There was a poor
understanding of the biological processes that were responsible for the observed
levels of virus in the blood and the rapidity at which the virus became drug re-
sistant. Modeling, coupled with advances in technology, has changed all of
this.” Dynamic modeling not only has revealed important features of HIV
pathogenesis but has advanced the drug treatment regime for AIDS patients
(Perelson and Nelson 1999).
2. Boeing Airline engineers completely designed The Boeing 777 jetliner us-
ing three-dimensional computer graphics. “Preassembly” of the airplane on the
computer at every stage of the design process eliminated the necessity of a
costly, full-scale mock-up and reduced error, adjustments, and revisions by 50
percent (Boeing). The pilots that fly these and other large airplanes train on so-
phisticated, computer flight simulators, which enable the pilots to practice deal-
ing with dangerous situations, such as engine fire and wind shear.
3. From the 1960s, numerical weather prediction has revolutionized forecast-
ing. “Since then, forecasting has improved side-by-side with the evolution of
computing technology, and advances in computing continue to drive better fore-
casting as weather researchers develop improved numerical models” (Pittsburgh
Supercomputing Center 2001).
4. Researchers at the University of Washington’s School of Fisheries are em-
ploying mathematical modeling to examine the impact on fish survival of the
removal of four dams on the lower Snake River. Another team at the Univer-
sity of Tennessee’s Institute for Environmental Modeling is using computa-
tional ecology to study complex options for ecological management of the
Everglades. Louis Gross, Director of the Institute, says that “computational
technology, coupled with mathematics and ecology, will play an ever-increasing
role in generating vital information society needs to make tough decisions about
its surroundings” (Helly et al.).
5. A group of engineers and computer scientists at Carnegie Mellon University
and seismologists from the University of Southern California and the National
University of Mexico is building three-dimensional computer simulations of
ground motion during earthquakes to predict how areas, such as the Greater
Los Angeles Basin, will behave during such a disaster. Using powerful parallel-
processing computer systems, one simulation indicated a complex pattern of
basin ground motion with some sites experiencing nine times greater motion
than others. With such information, scientists can predict the damage in an area
(Pittsburgh Supercomputing Center 1997). Seattle, Washington is another area
prone to earthquakes. The National Tsunami Hazard Mitigation Program has an
extensive simulation modeling effort to assess the hazards of tsunami threats
after earthquakes in the Puget Sound region so that officials can plan and miti-
gate their dangers (Koshimura and Mofjeld 2001). With computational models,
others have studied the economic impact of disruption to the water supply
caused by an earthquake in the Portland, Oregon region and appropriate re-
sponses to minimize the consequences (Rose and Liao).
5 Overview
Such collaboration among scientists, mathematicians, engineers, and computer
scientists is indicative of much computational science research and practice. The
fruits of these researchers’ models and simulations are a deeper understanding of
complex systems, a better foundation for important decisions, and a revolution in
scientific advances that are helping people all over the world.
Projects
1. Investigate three applications of computational science involving different
scientific areas and write at least a paragraph on each. List references.
2. Investigate an application of computational science and write a three-page,
typed, double-spaced paper on the topic. List references.
References
Boeing. “Boeing 777 Program Information.” http://www.boeing.com/commercial/
777family/index.html
Collins, Francis S., et al. 1998. “New Goals for the U.S. Human Genome Project:
1998–2003.” Science, 282 (October 23): 682–689.
Helly, John, et al., eds. “The State of Computational Ecology.” San Diego Super-
computer Center. http://www.sdsc.edu/compeco_workshop/report/helly_publication
.html
Koshimura, Shunichi, and Harold O. Mofjeld. 2001. “Inundation Modeling of Local
Tsunamis in Puget Sound, Washington, Due to Potential Earthquakes.” ITS 2001
Proceedings, Session 7, Number 7–18.
Masood, Ehsan. 1998. “UK Seeks Physicists for Environmental Research.” Nature,
393 (June 4): 400.
Perelson, Alan S., and Patrick W. Nelson. 1999. “Mathematical Analysis of HIV-1
Dynamics in Vivo.” SIAM Review, 41(1): 3–44.
Pittsburgh Supercomputing Center. 1997. “Getting Ready for the Big One.” http://
www.psc.edu/science/Bielak97/bielak97.html
———. 2001. “Pittsburgh System Marks a Watershed in Weather Prediction.”
News Release December 4, 2001. http://www.psc.edu/publicinfo/news/2001/
weather-12-04-01.html
Rose, Adam, and Shu-Yi Liao. “Modeling Regional Economic Resiliency to Earth-
quakes: A Computable General Equilibrium Analysis of Lifeline Disruptions.”
Public Works Research Institute. http://www.pwri.go.jp/eng/ujnr/joint/34/paper/
24rose.pdf
