Topology Optimization of Additively Manufactured Structures Accounting for Variabilities

Topology Optimization under Uncertainty, Topology Optimization for Additive Manufacturing

Jamie Guest (PI)

Additional Team Members:

Alberto Torres (GS)

This project seeks to develop design methods that account for uncertainties that may arise in the manufacture and operation of components and structures produced through Additive Manufacturing (AM). These uncertainties may have many sources, such as variations of material properties throughout an AM build or uncertainty in loading scenarios. To address these issues, gradient-based Topology Optimization is used to design components that specifically account for these uncertainties in probabilistic constraint and/or cost functions.  Such an algorithm would reduce sensitivity of designs to uncertainties, leading to more reliable performance and reducing the need for iterative testing and overly conservative knockdown factors.