Tuesday, December 24, 2024

Artificial intelligence meets “up close” in a novel DARPA-funded collaboration

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A recent award from the U.S. Defense Advanced Research Projects Agency (DARPA) brought together researchers from the Massachusetts Institute of Technology (MIT), Carnegie Mellon University (CMU), and Lehigh University (Lehigh) for the program Multi-objective Engineering and Testing of Alloy Structures (METALS) Program.. The team will explore novel design tools for simultaneous optimization of shape and compositional gradients in multi-material structures that complement novel, high-throughput material testing techniques, with particular emphasis on blade disc (blisk) geometry commonly found in turbine machines (including jet engines) and rocket engines ) as an example challenge.

“This project could have important implications for a wide range of aviation technologies. Insights from this work could enable the creation of more reliable, reusable rocket engines that will power the next generation of heavy-lift launch vehicles,” says Zachary Cordero, Esther and Harold E. Edgerton Associate Professor in MIT’s Department of Aeronautics and Astronautics (AeroAstro) and principal principal investigator of the project. “This project combines classical mechanics analyzes with cutting-edge generative artificial intelligence design technologies to unlock the plastic reserve of alloys of diverse compositions, enabling safe operation in previously inaccessible conditions.”

Different close locations require different thermo-mechanical properties and performance, such as creep resistance, low-cycle fatigue, high strength, etc. Gigantic-scale production also requires cost and sustainability metrics to be incorporated into the design, such as alloy sourcing and recycling.

“Currently, with standard manufacturing and design procedures, one magic material, composition, and processing parameters must be developed to meet the material-one-part-one constraints,” says Cordero. “Desired properties are often mutually exclusive, resulting in inefficient design trade-offs.”

While a single-material approach may be optimal for a single component location, it may leave other locations vulnerable to failure or may require moving critical material throughout the part when it may only be needed at a specific location. With the rapid development of additive manufacturing processes that enable voxel-based control of composition and properties, the team sees that unique opportunities are now possible to achieve leaps in performance in structural components.

Cordero’s collaborators include Zoltan Spakovszky, T. Wilson Professor of Aeronautics (1953) at AeroAstro; A. John Hart, professor of the class of 1922 and head of the Department of Mechanical Engineering; Faez Ahmed, ABS, career development assistant professor of mechanical engineering at MIT; S. Mohadeseh Taheri-Mousavi, assistant professor of materials science and engineering at CMU; and Natasha Vermaak, associate professor of mechanical engineering and mechanics at Lehigh.

The team’s expertise includes hybrid integrated computational materials engineering and machine learning-based materials and process design, precision instrumentation, metrology, topology optimization, deep generative modeling, additive manufacturing, materials characterization, thermostructural analysis and turbine machinery.

“It is particularly rewarding to work with the graduate students and postdoctoral researchers collaborating on METALS, from developing new computational approaches to building testbeds that operate in extreme environments,” says Hart. “This is a truly unique opportunity to build breakthrough capabilities that can underpin future propulsion systems, leveraging digital design and manufacturing technologies.”

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