Design Under Uncertainty

In this research area, the principles of robust design and reliability design are integrated to develop generic probabilistic approaches to engineering design under uncertainty. Our research has been focused on all aspects of uncertainty quantification, uncertainty propagation, and probabilistic optimization.  We have been investigating efficient algorithmic approaches that can reduce fundamental computational complexity for uncertainty propagation of practical problems with expensive simulations and/or large dimensions. Various sources of uncertainties in simulation-based design have been investigated.

Prognostics and Healthy Management (PHM)

Engineering systems degrade by nature, which makes time-variant reliability analysis and failure prognostics essentially important, especially for critical systems. Traditional PHM relies on sensory signals acquired from an engineered system to monitor the health condition and predict the remaining useful life of the system over its life-time. This research thrust aims to integrate data-driven PHM techniques with advanced model-driven time-variant reliability approaches for providing an advance warning of potential failures and a window of opportunity for implementing measures to avert these failures.

Design of Engineered Materials

Design of material systems with complex microstructures represents the future of materials and product development to achieve unprecedented system performance. While most of the existing methods of material design are trial-and-error based, we will develop systematic computational design methods that provide a seamless integration of design optimization, predictive materials modeling, processing/manufacturing, and data/informatics to enable the accelerated design and development of advanced materials systems.