Abstract
Engineering models are becoming increasingly complex, involving a larger number of variables. As a result, engineers struggle to deeply understand the models and therefore validate and properly use them. Sensitivity analyses (SA) are usually conducted to help with this task. Nonetheless, the knowledge and computational efforts required to conduct SA increases with the complexity of the model. This paper presents a conceptually simple method to conduct the SA of extreme-based engineering problems, that is, those problems whose outcome of interest is their maximum or minimum values. This type of problems is of relevance for reliability-based design. The method requires to iteratively maximize or minimize the model by fixing one input factor at each time. Then, the variation of the optimal surface is evaluated. The method permits the visualization and measure of the input factors’ influence on the extreme model response, with no need of defining the probability distribution of the input factors. Both the easiness of application and interpretation, along with a low computational cost for problems dealing with extreme values, make the proposed method very convenient to practitioners.
Original language | English |
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Article number | 107997 |
Number of pages | 12 |
Journal | Reliability Engineering and System Safety |
Volume | 216 |
DOIs | |
Publication status | Published - 2021 |
Keywords
- Global methods
- Importance measure
- Local methods
- Optimization
- Reliability analysis
- Visualization