TOOLED THICK COMPOSITES by ARVEN H. SAUNDERS III ...

solved in a similar manner, using the values obtained from the optimal cure temperature cycle.
The iterative sequence through the optimizer and numerical model and decision block was
carried out until the optimality conditions were satisfied. At convergence, the values of the
decision variables constituted the time-optimal cure cycle. Nielsen (Nielsen, 2002b) used finite
difference numerical models to simulate a resin transfer molding (RTM) process. The simulation
was used on-the-fly in real time to predict and guide controller decisions. The controller
accomplished uniform mold fill by controlling the flow rate of three independent resin injection
pumps.
Citing limitations of gradient-based methods, many researchers have employed
evolutionary methods such as genetic algorithms (GAs) As pointed out by Bag et al (2009)
classical gradient-based search techniques may not be optimal in the sense that they can be
trapped in local minima and require the objective function to be continuous within the search
space. In contrast, stochastic optimization techniques, such as GAs, can overcome these
difficulties and are capable of finding the global solution. Other evolutionary methods include
simulated annealing and differential evolution. Pettersson et al (2009) used a GA yielding states
of operation for a blast furnace on a Pareto-optimal front with nondominated solutions. Mitra et
al (2009) carried out multiobjective pareto optimization for an iron ore induration process using
an evolutionary (GA) algorithm. Mahfouf et al (2005) used GAs to tackle optimization of heat
treatment and chemical constituent percentages for steel alloys.
2.8 Material And Process Variability Effects On Optimal Cure Cycles
The types of empirical cure and viscosity models previously discussed provide good
predictions in relation to the actual measured data that are based upon. These models are
routinely used as if they are deterministic in nature, but this does not account for several
sources of variability seen in practice. Composite materials can exhibit significant batch -to-
batch variability and undergo out-time effects that can significantly change their behaviors
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