Optimization of composite patch repair processes with the use of genetic algorithms

The aim of this contribution is the optimization of some parameters of the composite patch repair technique (CPR). This technique is mainly used by the aircraft industry, as it offers high reliability, short repair times and reduced cost in compare to other methods, such as the riveted joints. CPR consists of adhesively bonding thin composite patches over cracked or corroded areas with heat supply. As the polymer‐matrix composite patch is heated, it cures and toughens. Proper curing insures structural reliability of the repair. Short duration curing cycles are of great importance for the aircraft availability. With the use of Genetic Algorithms, we design minimum time curing cycles. The optimization is subjected to the following constraints: (1) Maximum allowed temperature in order to avoid residual stresses, (2) Minimum temperature in order to initiate the cure reaction, (3) Sufficient degree of cure at the end of the process and (4) Maximum heat generation rate that can be achieved by the device. Our design vector contains the duration of the plateau stage of the cure cycle and the characteristic thermal profile. The degree of cure is estimated with the use of the Kamal cure rate model for thermosetting polymers. For the numerical time integration of the cure rate equation, a second order, implicit Runge‐Kutta scheme is employed.