A streamlined,physics-based kinetic model was formulated, calibrated, and validated on a nickel-base superalloy. It was designed to be simplified and streamlined, to speed up calculations and facilitate linkage to finite element modeling thermal codes. The model describes and predicts the formation of y' precipitates during the heat treatment process. Standardized experimental methods were employed to calibrate and initially validate the microstructure model. The model was then validated on an oil-quenched generic disk. Predictions of primary cooling y' size and area fraction agreed well with experimental measurements over a large range of values and cooling rates.

A review of advances for aircraft engine structural materials and processes is presented. Improved materials, such as superalloys, and the processes for making turbine disks and blades have had a major impact on the capability of modern gas turbine engines. New structural materials, notably composites and intermetallic materials, are emerging that will eventually further enhance engine performance, reduce engine weight, and thereby enable new aircraft systems. In the future, successful aerospace manufacturers will combine product design and materials excellence with improved manufacturing methods to increase production efficiency, enhance product quality, and decrease the engine development cycle time.

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Integrated Computational Materials Engineering OverviewThe accelerated insertion of materials (AIM) initiative provides the opportunity to reduce the materials development cycle time by up to 50% and thereby lessen the lead time required for new materials and processes. The program was founded to revolutionize the way designers and materials engineers interact, to achieve a leap forward in the application of computational materials science and integration with design engineering tools, and to create an environment where the design/materials team can learn from and build on previous developments. The centerpiece of the AIM system is the designer knowledge base, which provides a framework for managing experimental data, executing linked models describing processing, microstructure, properties, and producibility, and calculating confi dence bounds for system predictions.

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