A multi-task learning-based optimization approach for finding diverse sets of material microstructures with desired properties and its application to texture optimization
Abstract:The optimization along the chain processing-structure-propertiesperformance is one of the core objectives in data-driven materials science. In this sense, processes are supposed to manufacture workpieces with targeted material microstructures. These microstructures are defined by the material properties of interest and identifying them is a question of materials design. In the present paper, we addresse this issue and introduce a generic multi-task learning-based optimization approach. The approach enables the… Show more
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