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Home > Multidiscipline Modeling in Materials and Structures > Volume 5 issue 2 > Reliability Based Finite Element Analysis of Mechanical Components
Multidiscipline Modeling in Materials and Structures
ISSN: 1573-6105
Online from: 2005
Subject Area: Mechanical & Materials Engineering
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Reliability Based Finite Element Analysis of Mechanical Components
| Title: | Reliability Based Finite Element Analysis of Mechanical Components |
|---|---|
| Author(s): | M.H Hojjati, (Faculty of Mechanical Engineering, Babol University of Technology, Babol, Iran), A. Sadighi, (Faculty of Mechanical Engineering, Babol University of Technology, Babol, Iran) |
| Citation: | M.H Hojjati, A. Sadighi, (2009) "Reliability Based Finite Element Analysis of Mechanical Components", Multidiscipline Modeling in Materials and Structures, Vol. 5 Iss: 2, pp.151 - 162 |
| Keywords: | Finite element analysis, Normal distribution, Probabilistic design, Statistics |
| Article type: | General review |
| DOI: | 10.1163/157361109787959886 (Permanent URL) |
| Publisher: | Emerald Group Publishing Limited |
| Abstract: | In a conventional finite element analysis, material properties, dimensions and applied loads are usually defined as deterministic quantities. This simplifying assumption however, is not true in practical applications. Using statistics in engineering problems enables us to consider the effects of the input variables dispersion on the output parameters in an analysis. This provides a powerful tool for better decision making for more reliable design. In this paper, a probabilistic based design is presented which evaluates the sensitivity of a mechanical model to random input variables. To illustrate the effectiveness of this method, a simple bracket is analyzed for stress-strain behavior using commercially available finite element software. Young’s modulus, applied pressure and dimensions are considered as random variables with Gaussian distribution and their effects on maximum stress and displacement is evaluated. The finite element results are compared with reliability based theoretical results which show very good agreement. This demonstrates the capability of commercially available software to handle probabilistic approach design. |
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