Data Flow Between Experiment, Continuum Models, and Atomistic Models

A key challenge of learning from the outcomes of experiments and simulations is consistency of data formats and analysis techniques.  We have developed the ability to seamlessly integrate findings from atomistic simulations, mesoscale simulations, and experiments. 

Gregory S. Rohrer, Carnegie Mellon University

A key challenge of learning from the outcomes of experiments and simulations is consistency of data formats and analysis techniques.  We have developed the ability to seamlessly integrate findings from atomistic simulations, mesoscale simulations, and experiments.  By using the same data structures, we are able tomove data and results back and forth between the different simulations and experiments and analyze the results with exactly the same computer programs, ensuring that the findings from different techniques are comparable.  This outcome will make it possible to refine simulation techniques based on experimental findings and understand mechanisms of grain boundary migration.  Reaching this goal demanded a close interaction among all of the project participants and a fully  collaborative environment.

Designing Materials to Revolutionize and Engineer our Future (DMREF)