Optimization of crystallographic texture for sheet-forming applications using Taylor-based Models

Plastic deformation of metallic materials is an inherently anisotropic process as a result of the presence of preferential orientations in their crystallographic texture. Crystal plasticity modeling, which allows simulating the response of polycrystal aggregates taking into account their texture and other microstructural parameters, has been extensively used to predict this behavior. In this work, crystal plasticity models are used to deal with the opposite problem: given a desired behavior, determine how to modify a texture to approximate this behavior in the most efficient way. This goal can be expressed as an optimization problem, in which the objective is to find the texture with the best formability properties among all the possible ones. An incremental optimization method, based on the gradient descent algorithm, has been developed and applied to different initial textures corresponding to typical steel and aluminum sheet products. According to expectations, the textures found present a stronger γ fiber component. Moreover, the method sets the basis for the development of more complicated optimization schemes directed toward optimizing specific materials and forming processes.