Physics-based modeling of materials and uncertainty quantification as drivers for exascale computing
Presenter
February 3, 2017
Abstract
Physics-based modeling of materials and uncertainty quantification as drivers for exascale computing
Jaime Marian
University of California, Los Angeles (UCLA)
The availability and/or prospects of peta and exascale computing has transformed modeling of materials behavior into a new paradigm where simulations must be mined to extract useful data that can be compared to experiments on a meaningful basis. Moreover, materials modeling must now be accompanied by a minimum uncertainty quantification exercise that sets reasonable limits on the validity of the simulation/experimental comparison. This is particularly true within the standard paradigm of ‘multi scale’ or ‘parameter-passing’ modeling approach, where a conscientious efforts is made to transfer what is perceived as the most useful information emanating from a particular temporal or spatial scale to another. In this presentation we will show several examples of advanced materials modeling cases where such transformation is being made and we will discuss future directions.