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…
Machine learning for structure-guided materials and process design
Lukas Morand, Tarek Iraki, Johannes Dornheim +3
In recent years, there has been a growing interest in accelerated materials innovation in the context of the process-structure-property chain. In this regard, it is essential to ta…