Computational Design of Gradient Paths in Additively Manufactured Functionally Graded Materials

Additive manufacturing (AM) has enabled the creation of a near infinite set of functionally graded materials (FGMs). One limitation on the manufacturability and usefulness of these materials is the presence of undesirable phases along the gradient path. For example, such phases may increase brittleness, diminish corrosion resistance, or severely compromise the printability of the part altogether. In the current work, a design methodology is proposed to plan an FGM gradient path for any number of elements that avoids undesirable phases at a range of temperatures. Gradient paths can also be optimized for a cost function. A case study is shown to demonstrate the effectiveness of the methodology in the FeNiCr system. Paths were successfully planned from 316L Stainless Steel (316L SS) to pure Cr that either minimize path length or maximize separation from undesirable phases. Examinations on the stochastic variability, parameter dependency, and computational efficiency of the method are also presented. Several avenues of future research are proposed that could improve the manufacturability, utility, and performance of FGMs through gradient path design.

Computational Design of Gradient Paths in Additively Manufactured Functionally Graded Materials Academic Article