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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Hoffbauer, Ln
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Topics
Publications (9/9 displayed)
- 2018RESEARCH AND VALIDATION OF GLOBAL MPP IN THE RELIABILITY ANALYSIS OF COMPOSITE STRUCTURES
- 2018Bayesian inference in validation of global MPP for the reliability analysis of composite structurescitations
- 2017A RBDO APPROACH FOR THE RELIABILITY ASSESSMENT OF COMPOSITE STRUCTURES
- 2017Reliability-based design optimization and uncertainty quantification for optimal conditions of composite structures with non-linear behaviorcitations
- 2013Uncertainty assessment approach for composite structures based on global sensitivity indicescitations
- 2012A variability study on the response of composite structures based on sensitivity indices
- 2010Reliability Assessment of Composite Structures with Multiple Failure Modes
- 2010Uncertainty propagation in inverse reliability-based design of composite structurescitations
- 2008From local to global importance measures of uncertainty propagation in composite structurescitations
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article
Uncertainty propagation in inverse reliability-based design of composite structures
Abstract
An approach for the analysis of uncertainty propagation in reliability-based design optimization of composite laminate structures is presented. Using the UniformDesign Method (UDM), a set of design points is generated over a domain centered on the mean reference values of the random variables. A methodology based on inverse optimal design of composite structures to achieve a specified reliability level is proposed, and the corresponding maximum load is outlined as a function of ply angle. Using the generated UDM design points as input/output patterns, an Artificial Neural Network (ANN) is developed based on an evolutionary learning process. Then, a Monte Carlo simulation using ANN development is performed to simulate the behavior of the critical Tsai number, structural reliability index, and their relative sensitivities as a function of the ply angle of laminates. The results are generated for uniformly distributed random variables on a domain centered on mean values. The statistical analysis of the results enables the study of the variability of the reliability index and its sensitivity relative to the ply angle. Numerical examples showing the utility of the approach for robust design of angle-ply laminates are presented.