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Computational Science 1 Introduction to Computational Science PRESENTERS: Robert R. Gotwals, Jr. The Shodor Education Foundation, Inc. Ozone O3 creation normal decay depletion ~ O3 per cl radical ~ impact of cl Post 1994 message O Molecules ~ Ozone Guess Kirstin Riesbeck UNC-Chapel Hill/ NSF REU Fellow

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Computational Science 2 SCIENCE: the study of how nature behaves Observational Science Experimental Science Theoretical Science Computational Science

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Computational Science 3 Computational Science: A Tripartite Approach

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Computational Science 4 Applications Chemistry: electronic structure determinations Physics: astrophysics (galaxy simulations) Biology: population dynamics Mathematics: fractals Environmental Science: acid rain deposition models Linguistics: analysis of language transference Economics: Adam Smith models Political Science/History: causative factors in Bosnian War conflict Medicine: epidemiology, pharmacokinetics models

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Computational Science 5 Algorithms creating a mathematical representation of the problem -- the "mathematical model" choosing the appropriate numerical "recipe" to solve the problem »Examples –Linear Least Squares: for fitting data to a line –Newton's Method: for finding roots of an equation –Euler's Method: for solving integrals –Runge-Kutta Methods: for solving integrals –Cramer's Rule: for solving systems of equations

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Computational Science 6 Architecture choosing the appropriate "platform" to solve the problem »single-user personal computer (IBM PC, Macintosh) »scientific workstation (SGI Indy 2) »workstation clusters »supercomputer (Cray T3D MPP system) –scalar/serial processors –vector processors –parallel processors –vector/parallel machines

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Computational Science 7 Computational Science Tools Types of Tools for solving computational problems »Programming: Fortran, BASIC, C, Pascal »Spreadsheets »Equation-Solvers: Mathematica, TKSolver, Maple, MathCAD »Dynamic Modelers: STELLA II, VenSim »Scientific Visualization Programs: NCSA Scientific Visualization Tools, Spyglass, AVS, Wavefront »Discipline-Specific Software: GAUSSIAN94, MOPAC, UAM, PAVE, etc.

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Computational Science 8 BUT!! Why do we need this? solve hard problems that are: »too tedious to solve problems using calculators »too dangerous to try to solve problems in the laboratory »too expensive to try to solve problems in the laboratory »only solvable using mathematical techniques or models establish a true marriage between mathematics, computing and science Who cares?

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Computational Science 9 Who Cares? 21st Century Science: The Grand Challenges »Molecular and structural biology »Cosmology »Environmental Hydrology »Warfare and Survivability »Chemical Engineering and electronic structure »Weather prediction »Nanomaterials Solve any PART of one of these problems, and ….

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Computational Science 10

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Computational Science 11 Hand-on Activities

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Computational Science 12 Surface Water Runoff Model http://www.shodor.org/master/environmental/water/runoff Exploration: »What is the difference in runoff between: –Woods –Woods with Grass –Open Urban Area –Residential –Parking Lots »Run conditions –Hydrologic Soil Group B –Good hydrologic conditions –25-year, 24-hour storm

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Computational Science 13 Surface Water Runoff Results

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Computational Science 14 Fire! http://www.shodor.org/interactivate/activities/firealt Exploration »Run fire on different size forests »Run fire with different burn speeds »Run fire after changing configuration probabilities

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