Stochastic multi-objective optimisation of the cure process of thick laminates

Show simple item record Tifkitsis, Konstantinos Mesogitis, Tassos S. Struzziero, G. Skordos, Alexandros A. 2018-07-19T17:02:39Z 2018-07-19T17:02:39Z 2018-06-11
dc.identifier.citation Tifkitsis KI, Mesogitis TS, Struzziero G, Skordos AA. (2018) Stochastic multi-objective optimisation of the cure process of thick laminates. Composites Part A: Applied Science and Manufacturing, Volume 112, September 2018, pp. 383-394 en_UK
dc.identifier.issn 1359-835X
dc.description.abstract A stochastic multi-objective cure optimisation methodology is developed in this work and applied to the case of thick epoxy/carbon fibre laminates. The methodology takes into account the uncertainty in process parameters and boundary conditions and minimises the mean values and standard deviations of cure time and temperature overshoot. Kriging is utilised to construct a surrogate model of the cure substituting Finite Element (FE) simulation for computational efficiency reasons. The surrogate model is coupled with Monte Carlo and integrated into a stochastic multi-objective optimisation framework based on Genetic Algorithms. The results show a significant reduction of about 40% in temperature overshoot and cure time compared to standard cure profiles. This reduction is accompanied by a reduction in variability by about 20% for both objectives. This highlights the opportunity of replacing conventional cure schedules with optimised profiles achieving significant improvement in both process efficiency and robustness. en_UK
dc.language.iso en en_UK
dc.publisher Elsevier en_UK
dc.rights Attribution 4.0 International *
dc.rights.uri *
dc.subject Carbon fibre en_UK
dc.subject Thermosetting resin en_UK
dc.subject Process simulation en_UK
dc.subject Cure en_UK
dc.title Stochastic multi-objective optimisation of the cure process of thick laminates en_UK
dc.type Article en_UK
dc.identifier.cris 20629519

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