Alloy Design for Corrosion Resistance Via Computational Optimization Route

The objective of the proposed SBIR Phase I study is to evolve an aluminum alloy (7xxx series) with superior corrosion resistance and mechanical properties making use of computational tools. The methodology of this approach is to obtain corrosion data from the literature as input data and then perform optimization trials making use of the multi-objective hybrid evolutionary optimization software packages and response surface methodologies of Florida International University. This software has the proven capability to deal with various alloy design applications using minimal experimental data. The computational trials will yield optimal alloy composition for the best combination of corrosion resistance and mechanical properties, simultaneously. The evolutionary optimization approach minimizes the effort needed for alloy design by avoiding a large volume of experimentation, characteristic of conventional alloy development, and guarantees the mathematically best possible solutions. The results of optimization will be experimentally validated by processing an alloy of predicted composition and evaluating its corrosion resistance and mechanical properties in Phase I. More intensive evaluations of alloy developed in Phase I will continue towards implementation of Phase I results into practice in Phase II.