Unsupervised Optimal Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Engineering computation under uncertainty - Capabilities of non-traditional models
Computers and Structures
The vulnerability of structures to unforeseen events
Computers and Structures
Reliability-based design sensitivity by efficient simulation
Computers and Structures
A review of robust optimal design and its application in dynamics
Computers and Structures
A Convergence Theorem for the Fuzzy ISODATA Clustering Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Engineering computation under uncertainty - Capabilities of non-traditional models
Computers and Structures
Structural collapse simulation under consideration of uncertainty - Fundamental concept and results
Computers and Structures
A survey on approaches for reliability-based optimization
Structural and Multidisciplinary Optimization
On the use of a class of interior point algorithms in stochastic structural optimization
Computers and Structures
| Hi-index | 0.00 |
This paper presents a generally applicable numerical procedure for designing robust structures under uncertainty, which can be coupled with any arbitrary nonlinear computational model for statical or dynamic structural analysis. Based on the results from an uncertain structural analysis several permissible design domains are determined with the aid of cluster analysis methods instead of traditionally computing only one particular set of crisp design parameter values; these represent design alternatives. To identify a preference solution, a discrete three-criteria optimization problem is formulated, which is focused on maximum structural robustness and includes a safety component. A measure for the global robustness of the design alternatives is introduced based on an analog to Shannon's entropy. The goal of the resulting design is that the structural behavior is only marginally affected by uncertainty and by changes in the design parameters, which further provides comfortable decision margins to the construction engineer. The proposed procedure is demonstrated by means of a numerical example and of an example from engineering practice in vehicle crashworthiness design.