Engineering models both for analysis and experimental data reduction include variables that have uncertainties associated with them. Analyzing these models without considering the uncertainties may provide misleading results. In this paper, several methods for evaluating uncertainty are summarized. In particular, second-order uncertainty analysis method is illustrated using Taylor series expansion. It is the intent of this paper to compare the first-order and second-order propagation methods, Monte Carlo simulation methods and sequential perturbation uncertainty analysis methods and investigate the situation that second-order propagation method is necessary through examples studies by MathCad worksheet.
| Identifer | oai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-4876 |
| Date | 13 December 2002 |
| Creators | Zhang, Yanyang |
| Publisher | Scholars Junction |
| Source Sets | Mississippi State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
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