On the synergy between texture classification and deformation process sequence selection for the control of texture-dependent properties

Because of the computational complexity involved in multi-length scale formulations involving polycrystal plasticity, innovative algorithms need to be incorporated in techniques for designing processes to realize materials with optimized properties. This paper demonstrates the synergy between classification of fcc polycrystal texture and multi-scale process design for achieving desired properties in such materials. The inverse problem of designing processing stages that lead to a desired texture or texture-dependent property is addressed by mining a database of orientation distribution functions (ODFs). Given a desired ODF, the hierarchical classifier matches its ODF features in the form of pole density functions of important orientation fibers to a class of textures in the database. Texture classes are affiliated with processing information; hence, enabling identification of multiple process paths that lead to a desired texture. The process parameters identified by the classifier are fine-tuned using a gradient optimization algorithm driven by continuum sensitivity analysis of texture evolution. An adaptive reduced-order model for texture evolution based on proper orthogonal decomposition in which the reduced ODF modes corresponding to the intermediate stages of the design process are adaptively selected from the database is employed.