Introduction to Scientific Programming Computational Problem Solving Using Maple and C

"Introduction to Computational Science" was developed over a period of two years at the University of Utah Department of Computer Science in conjunction with the U.S. Department of Energy-funded Undergraduate Computation in Engineering Science (UCES) program. Each chapter begins by introducing a problem and then guiding the student through its solution. The computational techniques needed to solve the problem are developed as necassary, making the motivation for learning the computing alwasy apparent. Each chapter will introduce a single problem that will be used to motivate a single computing concept. The notes currently consist of 15 chapters. The first seven chapters deal with Maple and the last eight with C. The textbook will contain 20 to 30 chapters covering a similar mix of concepts at a finer level of detail.

1 Computational Science.- 1.1 Experiment, Theory, and Computation.- 1.2 Solving Computational Problems.- 1.3 Onward.- 2 Population Density: Computational Properties of Numbers.- 2.1 Model.- 2.2 Method.- 2.3 Implementation.- 2.4 Arithmetic Expressions.- 2.5 Rational Numbers in Maple.- 2.6 Rational Number Errors.- 2.7 Floating-Point Numbers in Maple.- 2.8 Floating-Point Number Errors.- 2.9 Assessment.- 2.10 Key Concepts.- 2.11 Exercises.- 3 Eratosthenes: Significant Digits and Interval Arithmetic.- 3.1 Model.- 3.2 Method.- 3.3 Implementation.- 3.4 Implementation Assessment.- 3.5 Method Assessment.- 3.6 Model Assessment.- 3.7 Problem Assessment.- 3.8 Key Concepts.- 3.9 Exercises.- 4 Stairway to Heaven: Accumulation of Roundoff Error.- 4.1 An Inductive Model.- 4.2 Summing the Harmonic Series.- 4.3 Comparing Rational and Floating-Point Arithmetic.- 4.4 Assessment.- 4.5 Key Concepts.- 4.6 Exercises.- 5 Kitty Hawk: Programmer-Defined Functions.- 5.1 Model.- 5.2 Method.- 5.3 Implementation.- 5.4 Assessment.- 5.5 Key Concepts.- 5.6 Exercises.- 6 Baby Boom: Symbolic Computation.- 6.1 Simple Interest.- 6.2 Compound Interest.- 6.3 Continuous Interest.- 6.4 Assessment.- 6.5 Key Concepts.- 6.6 Exercises.- 7 Ballistic Trajectories: Scientific Visualization.- 7.1 Ballistic Motion.- 7.2 Scientific Visualization.- 7.3 Motion Functions.- 7.4 Two-Dimensional Plots.- 7.5 Multiple-Curve Plots.- 7.6 Parametric Plots.- 7.7 Animation.- 7.8 Key Concepts.- 7.9 Exercises.- 8 The Battle for Leyte Gulf: Symbolic Mathematics.- 8.1 Fixed Trajectory.- 8.2 Arbitrary Trajectories.- 8.3 Effects of Drag.- 8.4 Piecewise Trajectories.- 8.5 Final Assessment.- 8.6 Key Concepts.- 8.7 Exercises.- 9 Old Macdonald’s Cow: Procedural Programming.- 9.1 Solving Equations in Maple.- 9.2 Bisection Method.- 9.3 ABisection Procedure.- 9.4 Assessment.- 9.5 Key Concepts.- 9.6 Exercises.- 10 Introduction to C.- 10.1 Maple Background.- 10.2 C Background.- 10.3 An Example C Program.- 10.4 Interpreters versus Compilers.- 10.5 Differences Between Maple and C.- 10.6 Learning C.- 10.7 Eratosthenes’s Problem.- 10.8 Kitty Hawk Problem.- 10.9 Key Concepts.- 10.10 Exercises.- 11 Robotic Weightlifting: Straight-Line Programs.- 11.1 Trigonometry of a Link Diagram.- 11.2 Components of a Straight-Line Program.- 11.3 Types.- 11.4 Expressions.- 11.5 Simple Statements.- 11.6 Main Function.- 11.7 Libraries.- 11.8 Assessment.- 11.9 Key Concepts.- 11.10 Exercises.- 12 Sliding Blocks: Conditionals and Functions.- 12.1 A Infinite Ramp without Friction.- 12.2 An Infinite Ramp with Friction.- 12.3 A Finite Ramp with Friction.- 12.4 Programmer-Defined Functions.- 12.5 Assessment.- 12.6 Key Concepts.- 12.7 Exercises.- 13 Rod Stacking: Designing with Functions.- 13.1 Decomposing the problem.- 13.2 Design.- 13.3 Implementation.- 13.4 Assessment.- 13.5 Key Concepts.- 13.6 Exercises.- 14 Newton’s Beam: Repetition.- 14.1 Newton’s Method.- 14.2 Implementation of Newton’s Method.- 14.3 Bisection Method Implementation.- 14.4 Assessment.- 14.5 Key Concepts.- 14.6 Exercises.- 15 Numerical Integration: Multiple-File Programs.- 15.1 Numerical Integration.- 15.2 Rectangular Method.- 15.3 Rectangular Method Implementation.- 15.4 Trapezoidal Method.- 15.5 Trapezoidal Method Implementation.- 15.6 Multiple-File Programs.- 15.7 Comparison of Rectangular and Trapezoidal Methods.- 15.8 Key Concepts.- 15.9 Exercises.- 16 Harmonic Oscillation: Structures and Abstract Datatypes.- 16.1 Newton’s Method with Complex Roots.- 16.2 Rod Stacking Revisited.- 16.3 Newton’s Method Revisited.- 16.4 Assessment.- 16.5 KeyConcepts.- 16.6 Exercises.- 17 Heat Transfer in a Rod: Arrays.- 17.1 Modeling Heat Flow.- 17.2 A Finite-Element Method.- 17.3 Implementation.- 17.4 Assessment.- 17.5 Key Concepts.- 17.6 Exercises.- 18 Visualizing Heat Transfer: Arrays as Parameters.- 18.1 Arrays as Parameters.- 18.2 File Input.- 18.3 File Output.- 18.4 Assessment.- 18.5 Key Concepts.- 18.6 Exercises.- A Maple Functions and Constants.- B C Library Functions.