Abstract
With the presence of powerful simulation tools in today’s engineering practice, the challenge in designing an introductory course in computational mathematics is twofold: students must be convinced of the necessity of opening some of the black boxes, and the mathematics education they receive must prove useful in controlling the solving process and use of the tools. The paper provides guidelines and suggestions to help meet these challenges.
We live in a world of black boxes, all of us do,
however well we may be educated.
Isaac Asimov, 1967.
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Notes
- 1.
This perception has led to the CDIO Initiative, an educational framework developed by engineering schools around the world with input from academics, industry, engineers and students. It aims at providing students with an education stressing engineering fundamentals set in the context of conceiving—designing—implementing—operating real-world systems and products. http://www.cdio.org
- 2.
These perceptions can be inferred from students’ internship reports.
- 3.
MODFLOW is open source software that was developed by the US Geological Survey (USGS), which is a science agency within the US Department of the Interior.
- 4.
One such property often overlooked is the linearity of the solution which, when it applies, can allow the breaking of a problem into its elementary components and can help reduce the cost of a solution.
- 5.
This was done by the Special Interest Group on “Quality and Trust in Industrial Computational Fluid Dynamics” within the European Research Community on Flow, Turbulence and Combustion.
- 6.
American Institute of Aeronautics and Astronautics.
References
AIAA (1998). Guide for the Verification and Validation of Computational Fluid Dynamics Simulations (G-077-1998e). AIAA Standards Series. Canadian Engineering Qualifications Board (2001). Guideline on the Environment and Sustainability for all Professional Engineers. Ottawa: Canadian Council of Professional Engineers.
Enelund, M., & Larsson, S. (2006). A computational mathematics education for students of mechanical engineering. World Transactions on Engineering and Technology Education, 5(2), 329.
ERCOFTAC Special Interest Group on Quality and Trust in Industrial CFD (2000). Best practice guidelines for industrial computational fluid dynamics. Lausanne, Switzerland: ERCOFTAC Coordination Centre.
Hodgson, B. R. (1987). Symbolic and numerical computation: the computer as a tool in mathematics. In D. C. Johnson & F. Lovis (Eds.), Informatics and the teaching of mathematics—Proceedings of the International Federation for Information Processing (IFIP) TC 3/WG 3.1 Working Conference. North-Holland.
Information and Privacy Commissioner/Ontario (2009). ORDER MO-2449—Appeal MA07-365—County of Simcoe. Toronto: Tribunal Services Department.
Roache, P. J. (1998). Verification and validation in computational science and engineering. Albuquerque: Hermosa Publishers.
Roache, P. J. (2008). Validation: Definitions or Descriptions? 3rd Workshop on CFD Uncertainty Analysis. Lisbon.
Acknowledgments
This work was made possible by a Discovery Grant from the National Science and Engineering Research Council of Canada.
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Caron, F., Garon, A. (2013). Tackling the Challenges of Computational Mathematics Education of Engineers. In: Damlamian, A., Rodrigues, J., Sträßer, R. (eds) Educational Interfaces between Mathematics and Industry. New ICMI Study Series, vol 16. Springer, Cham. https://doi.org/10.1007/978-3-319-02270-3_37
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DOI: https://doi.org/10.1007/978-3-319-02270-3_37
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