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Introduction to Computational Science

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

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Introduction to Computational Science

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

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

  3. Computational Science: A Tripartite Approach

  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

  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

  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

  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.

  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?

  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 ….

  10. Hand-on Activities

  11. 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

  12. Surface Water Runoff Results

  13. 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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