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Integration of Computational Fluid Dynamics and Experimentation in Undergraduate Fluid Mechanics

[+] Author Affiliations
Amir Jokar

Washington State University at Vancouver

Paper No. IMECE2006-15256, pp. 143-150; 8 pages
  • ASME 2006 International Mechanical Engineering Congress and Exposition
  • Innovations in Engineering Education: Mechanical Engineering Education, Mechanical Engineering Technology Department Heads
  • Chicago, Illinois, USA, November 5 – 10, 2006
  • Conference Sponsors: Mechanical Engineering Education, Mechanical Engineering Technology Department Heads
  • ISBN: 0-7918-4781-0 | eISBN: 0-7918-3790-4
  • Copyright © 2006 by ASME


A combination of computational and experimental analyses with the conventional lectures and problem-solving in a fundamental course such as fluid mechanics can enhance students' learning enormously. This teaching model has been examined within the mechanical engineering curriculum at WSU Vancouver, and successful results have been obtained thus far. The goal in this course was first to seed concepts and theorems of fluid mechanics in general terms, followed by numerical solutions and hands-on experimentation on selective subjects. This would allow the students to gain a deep understanding of the contents within the course timeframe. For selective fluid problems with more complications, such as the flow in the entrance region of a pipe, a computational fluid dynamic (CFD) software known as FlowLab was used to obtain numerical solutions. The assigned computational projects could open the eyes of students to the world of CFD analysis in thermal/fluid systems design. The results of the numerical analysis were then compared to the theoretical and experimental results. For experimentation, the students were divided into groups to design experimental procedures, conduct experiments, collect and interpret data, and report the results in an appropriate format. The selective experiments were relevant to the course topics including Burdon pressure gauges, manometers, flow-rate measurements, pipe flow, and flow around immersed bodies in a water tunnel. The present study addresses the details, results, and advantages of such a multi-dimensional and more interactive learning model.

Copyright © 2006 by ASME



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