The goal of this course is to teach basic tools and principles of writing good code, in the context of scientific computing. Specific topics include an overview of relevant compiled and interpreted languages, build tools and source managers, design patterns, design of interfaces, debugging and testing, profiling and improving performance, portability, and an introduction to parallel computing in both shared memory and distributed memory environments. The focus is on writing code that is easy to maintain and share with others. Students develop these skills through a series of programming assignments and a group project.

Overview and fundamentals of numerical algorithms and models for computational fluid dynamics. Numerical approaches discussed include finite difference, finite volume, finite element, and spectral methods on both structured and unstructured grids. Coverage includes asymptotically zero Mach number (incompressible), low-speed compressible, and high-speed compressible flows. Introduction to modeling of turbulent flows.