![]() ![]() In about four weeks of a regularly scheduled course, they become moderately proficient programmers and are motivated to start discussing more theoretical matters. As they analyze their results, they learn about numerical diffusion, accuracy and convergence. As they progress, they naturally practice code re-use and they incrementally learn programming and plotting techniques. The incremental nature of the exercises means they get a sense of achievement at the end of each assignment, and they feel they are learning with low effort. Guiding students through these steps (without skipping any!), they learn many valuable lessons. We wrote this set of Jupyter notebooks in 2013 to teach an intensive two-day course in Mendoza, Argentina. Barba and her students over several semesters teaching the CFD course. Barba's lab until 2011, and the lessons were refined by Prof. ![]() The "steps" were inspired by ideas of Dr. The module assumes only basic programming knowledge (in any language) and some background in partial differential equations and fluid mechanics. Barba since moved to the George Washington University). Lorena Barba between 20 in the Mechanical Engineering department at Boston University (Prof. The module was part of a course taught by Prof. the 12 steps to Navier-Stokes, is a practical module for learning the foundations of Computational Fluid Dynamics (CFD) by coding solutions to the basic partial differential equations that describe the physics of fluid flow. Journal of Open Source Education, 1(9), 21, ĬFD Python, a.k.a. ![]() CFD Python: the 12 steps to Navier-Stokes equations. Please cite as: Barba, Lorena A., and Forsyth, Gilbert F. ![]()
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