MACHINE LEARNING BASED ROTOR ALLOY DESIGN SYSTEM

• Main Authors: Oshin, Olusegun T, Somanath, Nagendra, Noraas, Ryan B, Giering, Michael J
• Format: Patent
• Language: English
• Published: 08.04.2021
• Subjects: AIRCRAFT; AVIATION; CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COSMONAUTICS; COUNTING; DESIGNING, MANUFACTURING, ASSEMBLING, CLEANING, MAINTAINING ORREPAIRING AIRCRAFT, NOT OTHERWISE PROVIDED FOR; GROUND OR AIRCRAFT-CARRIER-DECK INSTALLATIONS SPECIALLYADAPTED FOR USE IN CONNECTION WITH AIRCRAFT; HANDLING, TRANSPORTING, TESTING OR INSPECTING AIRCRAFTCOMPONENTS, NOT OTHERWISE PROVIDED FOR; PERFORMING OPERATIONS; PHYSICS; TRANSPORTING

A method for designing a material for an aircraft component according to one example includes training a neural network to correlate microstructural features of an alloy with material properties of the alloy by at least providing a set of images of the alloy. Each of the images in the set of images has varied constituent compositions and at least one patch of corresponding data is embedded into the image. The method also includes determining non-linear relationships between the microstructural features and corresponding empirically determined material properties via a machine learning algorithm, receiving a set of desired material properties of the alloy for aircraft component, and determining a set of microstructural features capable of achieving the desired material properties of the alloy based on the determined non-linear relationships.