4 papers
Diversity-Aware Batch-Mode Active Learning for Efficient Sampling in Data-Driven Constitutive Modeling
Ronak Shoghi, Lukas Morand, Dirk Helm +1
The constitutive behavior of materials is modeled through relationships between stress, strain, and possibly additional internal variables. This results in relatively high-dimensio…
Particle Trajectory Prediction in Discrete Element Simulations using a Graph-Based Interaction-Aware Model
Abhishek Setty, Lukas Morand, Poojitha Ramachandra +1
This study explores the applicability of a graph-based interaction-aware trajectory prediction model, originally developed for the transportation domain, to forecast particle traje…
Semantic orchestration and exploitation of material data: A dataspace solution demonstrated on steel and copper applications
Yoav Nahshon, Lukas Morand, Matthias Büschelberger +5
In materials science and manufacturing, vast amounts of heterogeneous data (e.g., measurement and simulation logs, process data, publications) serve as the bedrock of valuable know…
The Good, the Bad and the Ugly: Augmenting a black-box model with expert knowledge
Raoul Heese, Michał Walczak, Lukas Morand +2
We address a non-unique parameter fitting problem in the context of material science. In particular, we propose to resolve ambiguities in parameter space by augmenting a black-box…