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CPP: Fachverband Chemische Physik und Polymerphysik

CPP 14: Topical Session: Data Driven Materials Science - Materials Design I (joint session MM/CPP)

CPP 14.1: Topical Talk

Montag, 16. März 2020, 10:15–10:45, BAR 205

Data-Mining Strategies for Understanding Strength and Failure of Materials — •Stefan Sandfeld — TU Bergakademie Freiberg, Lampadiusstr. 4, 09599 Freiberg

Experimental observations and simulation data should -- in principle -- help to shed light on the 'inner workings' of a physical system, say, a material or specimen. There, the 'inner workings' would be the interaction of microstructural features among themselves, with the surfaces of the specimen, with defects, or with phase boundaries, to name but a few. Both experiment and simulation, however, suffer from particular problems which in many situations makes it difficult to directly compare them or to use results from one as input or support for the other.

In this presentation, we will start by giving an overview over current attempts for integrating experiment and simulation. We will then demonstrate, on the one hand, how data science approaches might be used to access data from experiments that would be otherwise inaccessible and, on the other hand, how data science also might help to reduce the high level of abstraction inherent to most simulations. With those methods, experiment and simulation might get a little closer to each, thereby helping to understand relevant mechanisms in strength and failure from a new point of view.