Introduction to Computational Science PRESENTERS Robert R Gotwals

Introduction to Computational Science PRESENTERS: Robert R. Gotwals, Jr. The Shodor Education Foundation, Inc. Kirstin Riesbeck UNC-Chapel Hill/ NSF REU Fellow Ozone O 3 creation ~ O Molecules Ozone Guess ~ O 3 per cl radical ~ normal decay impact of cl Post 1994 message depletion Computational Science 1

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

Computational Science: A Tripartite Approach Computational Science 3

Applications l l l l l 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 Computational Science 4

Algorithms l l 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 Computational Science 5

Architecture l choosing the appropriate "platform" to solve the problem » single-user personal computer (IBM PC, Macintosh) » scientific workstation (SGI Indy 2) » workstation clusters » supercomputer (Cray T 3 D MPP system) – scalar/serial processors – vector processors – parallel processors – vector/parallel machines Computational Science 6

Computational Science Tools l Types of Tools for solving computational problems » Programming: Fortran, BASIC, C, Pascal » Spreadsheets » Equation-Solvers: Mathematica, TKSolver, Maple, Math. CAD » Dynamic Modelers: STELLA II, Ven. Sim » Scientific Visualization Programs: NCSA Scientific Visualization Tools, Spyglass, AVS, Wavefront » Discipline-Specific Software: GAUSSIAN 94, MOPAC, UAM, PAVE, etc. Computational Science 7

BUT!! Why do we need this? l l l 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? Computational Science 8

Who Cares? l l 21 st 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 …. Computational Science 9

Computational Science 10

Hand-on Activities Computational Science 11

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

Surface Water Runoff Results Computational Science 13

Fire! l l 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 Computational Science 14