Session: DAC-06-1: Design for Additive Manufacturing

Paper Number: 141977

141977 - A Graph Algorithm for the Design of Functionally Graded Alloy Components 

One of the promising capabilities of metal additive manufacturing (AM) is the potential to manufacture components having spatially varying alloy composition. These compositionally graded alloy (CGA) components can satisfy competing cost and performance requirements that cannot be met with a monolithic alloy. However, there are significant challenges in their design and manufacture, such as the formation of deleterious material phases and cracking due to thermal gradients during AM. Prior work addresses CGA design only between two alloy targets in trivial geometries. Existing approaches are unable to consider the full complexity of designing and placing CGAs between more than two materials within a complex part geometry. In practice, most manufactured CGAs are unidirectional, with composition changing in planar, cylindrical, or spherical shells/layers. In this paper, we introduce a novel graph-based algorithm for designing manufacturable general CGA components. Given a component geometry with alloy composition targets at select locations, the algorithm uses a labeled property graph representation of material compatibilities and properties to generate a valid alloy gradient across the entire component. We show that the algorithm is guaranteed to find an alloy gradient solution if one exists, demonstrate it on subsea valve body problem using the Fe-Ni-Cr ternary system, and study the algorithm's scalability with respect to several key problem discretization parameters.

Presenting Author: Marshall Allen Texas A&M University

Presenting Author Biography: Marshall Allen is a Ph.D. candidate in the Department of Mechanical Engineering at Texas A&M University. He is co-advised by Dr. Richard Malak and Dr. Raymundo Arroyave. Marshall’s research focus is developing information representations and design methodologies for multi-material metal additive manufacturing.

Authors:

Marshall Allen Texas A&M University
Raymundo Arróyave Texas A&M University
Richard Malak Texas A&M University