Nickel is a strategic element in the military industry due to its unique physical and electrochemical properties, particularly its high corrosion resistance, thermal stability, and variety of structural and functional applications. Nickel is used in the production of protective coatings, power system components, and shape memory alloys used in the smart structures of aircraft and military vehicles.

The objective of this study is to design and optimize an advanced nickel-magnesium alloy that meets the performance requirements of high-tech defence applications by achieving a multi-criteria balance of hardness, corrosion resistance, and specific gravity.

To achieve this goal, a hybrid Artificial Neural Network (ANN)-based methodology is employed to generate a predictive model of the complex structure-property relationships, while Genetic Optimization (GA) algorithms are applied to explore the optimal composition space.

The study presents quantitative results, supported by numerical simulation and statistical analysis, confirming the effectiveness of the proposed methodology in predicting alloy properties and guiding its development towards optimal performance in harsh operating environments.