(19b) Computation in Undergraduate Chemical Engineering Education

Over the past 100 years, computation has changed, particularly in the last quarter century. A brief history is presented of computation (as illustrated in publications) from 1908 to 1958. Growth of computing using ‘computing machines' began in the 1950s, first with large machines housed in secure rooms, then on calculators, but the calculations remained fairly primitive. In the last quarter century, though, students have had access to process simulation, first for steady state and then for transient situations and process control. More recently, methods have been developed to solver partial differential equations, in spreadsheets or with an interpretative language like MATLAB. Now with computational fluid dynamics (CFD), students can solve realistic transport problems in three dimensions and time.

Current approaches are described about (1) where students learn programming concepts (computer science courses, engineering courses, chemical engineering course, or not at all), (2) what language they learn (C++, Java, MATLAB, Visual Basic, Excel), and (3) how computing is integrated into the curriculum and the key programming concepts needed (www.cache.org.)

Finally, a new paradigm is presented in which students do some programming, but mainly learn to solve chemical engineering problems using existing programs and show they've solved the problem correctly. This is all the more necessary since our students are competing in a global economy, and working fast may be necessary. It also responds to what CACHE has found, namely that few practicing engineers actually program. Illustrations will be given from the author's new book, Introduction to Chemical Engineering Computing, Wiley (2006). This book shows students how to solve traditional problems but it also poses problems that go far beyond existing textbooks. These problems motivate students because they are real problems.

Finally, possible future applications in undergraduate education are described as they apply to molecular engineering and multi-scale analysis.