Prerequisites: ME 200 or equivalent; ME 240A is recommended
Description: Introduces data analysis, including discrete Fourier transforms, sampling theorem, and power spectra. Reviews Sturm- Liouville eigenfunction expansions, Gibbs phenomenon, convergence theorems, and Chebyschev transforms. Additional topics include Galerkin, tau, collocation, and pseudospectral methods, aliasing, time-advancement, and numerical stability. Explores applications to incompressible Navier-Stokes equations, compressible flows, reacting flows, and complex geometries. May be taken Satisfactory (S) or No Credit (NC) with consent of instructor and graduate advisor. Course is repeatable as content changes.