The research objective of this award is to develop optimal design methodologies that account for manufacturing defects and demand uncertainties in small-scale structures. In engineering design, there is a natural tendency to push the limits of capacity of existing materials or employ new high performance materials. While this increases efficiency by using more sparse and slender elements, the designs also become more susceptible to flaws that may impair response. The research will address this issue by incorporating fabrication and demand uncertainties into methods of topology optimization, which is an emerging class of design tools for optimizing material distribution across a design domain. The PIs will exploit the relationships between the model for the system uncertainties and the mathematical forms used in the algorithms for topology optimization. Furthermore, methods will be explored for identifying those parameters whose uncertainties have a dominant influence on design. To ensure that the methods can be practically applied, fabrication is included in the scope of work. Tests results from fabricated specimens will be used to quantify fabrication errors and provide feedback for updating the uncertainty models.

If successful, the results of this research will facilitate design of efficient structures with optimized and/or tailored reliability. Potential applications include high performance material microstructures, compliant mechanisms, and tunable capacitors. The optimization under uncertainty theory will be incorporated into a general (non-heuristic) topology optimization methodology to ensure wide impact of the results. The educational plan of the project includes curriculum development and research opportunities for undergraduate and graduate education. It also includes engineering design outreach activities to Baltimore Polytechnic High School. The investigators will leverage the visually appealing aspects of topology optimization to attract undergraduates and high school students to research opportunities provided by the project.

Project Start
Project End
Budget Start
2009-09-01
Budget End
2013-08-31
Support Year
Fiscal Year
2009
Total Cost
$360,000
Indirect Cost
Name
Johns Hopkins University
Department
Type
DUNS #
City
Baltimore
State
MD
Country
United States
Zip Code
21218