Utilizing ICME Models to More Effectively Predict Process-Structure-Property Relationships for Better Property Optimization and Design in Aerospace Alloys

Precipitation-hardening is an important strengthening mechanism common in many aerospace alloys with mechanical properties that can vary significantly as a function of traditional processing methods. Due to the multiple underlying physical mechanism  that are involved, it is difficult to optimize the composition and processing requirements for an aluminum alloy for a specific set of performance requirements with traditional design methodologies.

To try and meet this design challenge, the strategy taken here utilizes an ICME approach to develop process-structure tools independently of structure-property tools that can be effectively integrated to establish the process-structure-property relationships necessary for alloy design and optimization.

To support the models, eighteen plates of 7050 aluminum were processed varying quench rates, solution- and heat-treatments to create a broad range of microstructures and mechanical properties. The grain size, degree of recrystallization, dispersoids, and precipitate characteristics were measured using SEM and optical microscopy. The strength and fracture toughness were measured for each plate.

Here, empirical computational tools, based on artificial neural networks, are used to link these traditional processing parameters to the microstructure characteristics measured experimentally. Predictive computational models based on well understood physical mechanisms were developed to relate these microstructure characteristics to strength and fracture toughness. The strength model captures the influence of several strengthening mechanisms, including solution strengthening, precipitation hardening, and the influence of substructure. Fracture toughness is considered to be a combination of both intergranular and transgranular fracture, and is related to the degree of recrystallization, the grain boundary characteristics, and the strength of the grain interior. Integrating these vastly different tools facilitates the optimization of processing parameters, composition, and overall microstructure to achieve the best performance of a given alloy.