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Probability analysis of bistable composite laminates using the subset simulation method
Composite Structures, Volume: 271, Start page: 114120
Swansea University Author: Michael Friswell
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DOI (Published version): 10.1016/j.compstruct.2021.114120
Bistable composite laminates are advanced composite structures which are potential candidates for morphing structure applications. The geometrical dimensions, material properties, ambient temperature and moisture have significant effects on the bistable behaviour, and the effect of uncertain paramet...
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Bistable composite laminates are advanced composite structures which are potential candidates for morphing structure applications. The geometrical dimensions, material properties, ambient temperature and moisture have significant effects on the bistable behaviour, and the effect of uncertain parameters should be quantified. Reliability analysis is well established for the quantitative assessment of the probability of an event due to parameter uncertainty. Thus, subset simulation is applied to the reliability and sensitivity analysis of bistable composite plates with multiple random parameters. The bistability probability is estimated using the principle of minimum energy; the Rayleigh-Ritz method is used to develop the equations of motion and the limit state function. The results indicate that the stacking sequence has a large effect on bistability probability, and cross-ply composite laminates are most likely to be bistable. Moreover, moisture absorption by the laminate can dramatically reduce this probability. The sensitivity reliability analysis demonstrates that for bistable laminates subject to humidity, the coefficient of thermal and moisture expansions have the greatest influence on the bistability probability. However, for bistable laminates without moisture the thickness is the most important factor. The accuracy and efficiency of the subset simulation method is validated by Monte Carlo simulation.
Bistable Composite Laminate, Reliability Analysis, Subset Simulation, Sensitivity Analysis, Uncertainty Quantification, Advanced Composites
Faculty of Science and Engineering