Computational Design & Manufacturing Lab

University of Wisconsin-Madison

 

 

 

 

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 Research Interests

The goal of our research is to develop computer methods for design and manufacturing automation.

Current research

 

Multi-physics topology optimization


 

Topology optimization aims to determine optimal shape and connectivity of material distributions under physical constraints. We are studying methods for topology optimization of multi-physics systems, where human intuition is often inadequate to cope with the coupling nature of multi-physics systems.

We have used the continuous adjoint approach to study the optimization of electromechanical systems for the design of actuators, the optimization of thermofluid systems under tangent thermal gradient constraints, and the optimal design of electric field for light absorption in organic solar cells.

 

 

Isogeometric analysis on triangulations


 

We are creating a new method for integrating CAD and finite element analysis and it is based on rational triangular Bezier elements. It has the advantages of enabling automatic parameterization, ease of local refinement, and being applicable to geometry of complex topology.

We have also developed a smooth-refine-smooth procedure to achieve optimal convergence with Cr smooth triangular elements.

 

Statistical shape modeling

We are developing methods to model shape variation across a family of objects. It has applications in dimensional metrology, personalized product development, and image segmentation. It can also be useful for assessing and characterizing biological growth. We have developed a direct diffeomorphic reparameterization method for correspondence optimization in statistical shape modeling (SSM).

We have extended the SSM to the construction of a statistical atlas for efficient creation of subject-specific finite element mesh.

 

 

Recent work

 

 

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Direct Digital design and manufacturing from massive scan data

This research in geometry processing of scan data is necessitated by the ubiquitousness of three-dimensional (3D) scanning and growing use of scan data in product design, analysis and manufacturing, and in biomedical diagnosis, intervention and treatment planning. Dense discrete scan data poses computational and mathematical challenges in how to process them into meaningful geometric forms for subsequent design, analysis and manufacturing applications.

 

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AFM based nano manipulation

This research aims to develop a cyber-physical approach for automating manipulation of nanoscale particles, tubes, and wires via atomic force microscopes with the eventual goal of nanoscale device prototyping.

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Resolving tip effect in atomic force microscopy (AFM)

The research objective is to develop theories and algorithms for tip-specimen shape interaction modeling for an emerging class of scanning probe microscopy (SPM) instruments that is capable of imaging general 3D structures with vertical sidewalls and undercut features at the nanometer or even atomic scale.

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Dynamic sensing-and modeling approach to multi-sensor integration

The objective of this research is to develop foundational shape digitization theories and algorithms for a multimodal digitization system that can couple 3D sensing and post-sensing shape reconstruction in a dynamic manner in order to fundamentally improve digitization automation level, speed, efficiency and the resulting surface quality.

 

 

 

Last updated Feb 21, 2014.

 

 

 

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