Keywords: composite laminates, cure optimization, finite element analysis, heat transfer, Nelder-Mead algorithm, simplex.

Thermosetting composite materials are actually considered as a valid alternative to relatively more conventional materials. In several cases, the preformed parts are subject to a curing process, based on opportunely designed pressure and temperature cycles and using a vacuum facility, to obtain the desired superior mechanical properties. An opportune design of the cure process is crucial to obtain the desired material shaping and consolidation, to remove the resin excess and entrapped volatiles, and to reach the full cure of the material without thermal degradation of the resin system or part distortion related to excessive thermal stress or to undesired out-in solidification. In the recent past, the curing cycles were typically planned using trial and error procedures, which are, in most cases, time and cost expensive. Actually, these procedures seem no more acceptable to realize an efficient and competitive production and, as a consequence, remarkable research effort has been focused on the development of analytical and numerical models of the curing process to be used for process analysis and computational optimization.

In this paper an approach to the computational optimization of the thermal cure cycle of thick composite laminates has been investigated. The simulation based optimization procedure has been obtained by the coupling of the Nelder-Mead algorithm and a thermo-chemical finite element model. Several simulations have been performed to test the proposed method. In particular, the optimization procedure has been tested coupling the Nelder-Mead algorithm with an initial random exploration of the search space to define the starting simplex; and assuming a supplier suggested thermal cycle as an exploratory point for the starting simplex.

Taking into account results obtained, the effectiveness of the Nelder-Mead algorithm for the optimized design of the thermal cure cycle of composite laminates can be outlined; in particular, some advantages can be obtained by means of a preliminary exploration of the search space, finalized to the definition of the initial simplex. The number of the preliminary exploration trials significantly influences the algorithm convergence and best fitness scores.

The suggestion of a potential vertex has not implied an improvement in algorithm performance; however, as a first approximation, the scarce influence of this vertex, as well as the differences between the thermal cycles provided by the performed routines, seem to be related to the relatively permissive limitations adopted to define the penalty function.

Finally, taking into account the strong influence of the initial simplex definition of the algorithm convergence to a global optimum, it seems opportune to investigate the opportunity of coupling the Nelder-Mead algorithm with other optimization techniques, such as genetic algorithms or simulated annealing.

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