Integrated DEsign Automation Laboratory

Integrated DEsign Automation Laboratory

Robust Shape and Topology Optimization

Robust shape and topology optimization is an emerging research area that recognizes the substantial role topology optimization plays in engineering design innovation and the need to synthesize novel conceptual designs with consideration of practical random-field uncertainties, such as the variation in the loading, material properties, or geometric variations due to the imprecise manufacturing process. At the core of this research area is the establishment of a mathematically rigorous and computationally efficient method which can quantify the interrelationships among the geometric shapes, underlying physics, associated random-field uncertainties and the product performance. Our current research focus is on developing analytical approaches that bridge the gap between conventional robust design (usually set as a continuous optimization problem in finite dimensions) and infinite-dimensional shape and topology optimization. The proposed approach integrates the state-of-the-art level set methods for shape and topology optimization and the latest research development in design under uncertainty. The method has been applied to designing compliant mechanisms, actuators, and is being extended to solve multi-material and multi-physics shape and topology optimization problems in designing novel engineering systems such as energy harvesters.  A special emphasis of our work is to develop level-set based approach to simultaneous shape and topology optimization under geometric uncertainty.

The advances of manufacturing techniques, such as additive manufacturing, have provided unprecedented opportunities for producing multiscale structures with intricate latticed/cellular material microstructures to meet the increasing demands for parts with customized functionalities. However, there are still difficulties for the state-of-the-art topology optimization (TO) methods to successfully achieve manufacturable multiscale designs with cellular materials, partially due to the disconnectivity issue of neighboring material microstructures. In our research, both concurrent and hierarchical multiscale topology optimization approaches have been developed to address this challenge.

Representative Papers

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Integrated DEsign Automation Laboratory

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