|
Abstract:
|
When computational methods or predictive simulations are used to model complex phenomena such as the response of physical systems to a range of conditions or configurations, researchers, analysts and decision-makers are not only interested in understanding the data but are also interested in understanding the uncertainty present in the data as well. Quantification, communication and interpretation of uncertainty are necessary for the understand and control of the impact of variability; these three — quantification, communication and interpretation of uncertainty — help add both understanding and robustness to the design process.
In this talk, we present an overview of the multiscale modeling and uncertainty quantification efforts accomplished as part of the Center for Multiscale Modeling of Electronic Materials (MSME), a collaborative partnership between academia and the Army Research Laboratory. In particular, we will focus on our successes in cross-cutting areas — bringing uncertainty quantification techniques originally developed within a particular discipline to a broader class of materials by design problems.
|
