Skip to content. | Skip to navigation

Personal tools
You are here: Home Dr. Stucker Receives $450K Grant from ONR

Dr. Stucker Receives $450K Grant from ONR

Stucker2Dr. Brent Stucker, Professor and Clark Chair of Computer Aided Engineering, in the Department of Industrial Engineering, received a 3-yr, $450,000 research grant from the Office of Naval Research. The project,  “Modeling Closed Loop Control of Multi-Material Ultrasonic Consolidation”,  will run June 2011-June 2014. 

Research over the past 4 years, funded by the Office of Naval Research, has resulted in a significant body of knowledge regarding Ultrasonic Consolidation (UC). A novel Dislocation Density based Crystal Plasticity Finite Element (DDCP-FEM) model has been developed, a better understanding of bonding has been achieved, and the multi-material/multi-functional part fabrication capabilities of UC have been clearly established. It has now been conclusively demonstrated that, as a low-temperature, solid-state additive manufacturing process, UC is uniquely suited amongst metal additive manufacturing processes to produce multi-material/ multi-functional structures which include embedded electronics, actuators and other features.

In this project, Dr. Stucker proposes to extend the DDCP-FEM model to include bonding between dissimilar FCC metals, to homogenize the model to include all relevant length scales, and to use that knowledge to implement a closed-loop feedback control system to ensure bond quality is maintained when building complex multi-material structures using UC.  He plans to take the DDCP-FEM model created over the past couple of years and move it from a model capable of predicting microscopic changes in materials to one which predicts the macroscopic properties of multi-material parts made using UC.  He will use the model’s ability to predict microstructural changes in parts as they are being built in connection with real-time ultrasonic non-destructive testing techniques to monitor the changes in microstructure and bonding during the UC process and control the UC machine using a closed-loop control algorithm based around predictive models and real-time sensor data.

For more information on this project, contact Dr. Stucker at 502-852-2509, or brent.stucker@louisville.edu.

 

Document Actions
Personal tools