June 15, 2019
June 15, 2019
June 19, 2019
Uncertainty is involved in all engineering measurements, and it must be taken into account before making any critical engineering decision. It is essential to draw the attention of engineering students to uncertainty analysis. The law of propagation of uncertainty is conventionally taught in undergraduate engineering programs. However, many students find it cumbersome and intimidating for complex performance functions. In this paper, two alternative methods, Monte Carlo Simulation (MCS) and Sequential Perturbation (SP) are discussed, and their effectiveness in understanding and applying the notion of uncertainty is investigated. The MCS and SP methods are introduced to a group of junior engineering students, who are already familiar with the law of propagation of uncertainty. The students’ perception of uncertainty analysis and their performance in conducting uncertainty analysis through a class activity are compared after the new methods are introduced.
Norouzi, M., & Pawloski, J. S., & Qi, H., & Jafari, F. (2019, June), Enhancing Uncertainty Analysis for Engineering Students Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. 10.18260/1-2--32753
ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2019 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015