Integrated DEsign Automation Laboratory

Our research in this area has been focused on quantification and propagation of all sources of uncertainties in a simulation-based design process, as well as decision-making under uncertainty. Current emphases fall into

1. metamodeling for simulation-based design,
2. model validation and uncertainty quantification, and
3. multidisciplinary design optimization under uncertainty.

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We develop computational design methods to support both the design of quasi-random microstructural material systems as well as the design of periodic or aperiodic metamaterial systems. Current topics include:

1. microstructure characterization & reconstruction (MCR),
2. machine learning of materials behavior,
3. multiscale uncertainty quantification in integrated computational materials engineering (ICME),
4. data-driven microstructural design,
5. topology optimization and metamaterials design, and
6. design for additive manufacturing.

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An enterprise-driven decision-based design framework recognizes the substantial role that decisions play in design, as well as the need to synthesize business and engineering models in an enterprise-driven collaborative design environment. Current research focuses are

1. network-based customer preference modeling, and
2. multilevel decision-based design.

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