There is a great deal interest in minimizing thermal and residual stresses at the interfaces of metals and ceramics. These stresses develop because of the large mismatch in thermally induced strains that exists between these two materials. The differences are significant enough to cause premature component failure in a variety of applications, including thermal barrier coatings (TBCs) for turbine blades and ceramic coatings for cutting tools. One approach to minimizing these stresses involves functionally grading the material distribution at the metal-ceramic interface. A significant amount of effort has been focused on the development of functionally graded nickel-alumina composites as a model system to determine the architectural features of the material gradient that will minimize these stresses. This effort has led to the development of an experimentally verified modeling approach based on thermomechanical, elastoplastic finite element analysis that can be used to predict the stress distributions in functionally graded metal-ceramic composite materials. This approach has been coupled with a mathematical optimization technique, known as a Genetic Algorithm (GA), to determine the optimal architecture for minimizing thermal and residual stresses at metal-ceramic interfaces.

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