![](https://www.dem9.fau.de/files/2023/03/Azema.jpg) |
Exploring the scales in highly deformable grain assemblies when compressed far beyond the jammed state
Emilien Azéma
Université de Montpellier, France |
![](https://www.dem9.fau.de/files/2023/05/Hongyang_Cheng-240x300.jpg) |
From Granular Randomness to Predictive Digital Twins: Integrating Data-Driven and Coupled Models for Uncertainty Quantification
Hongyang Cheng
University of Twente, The Netherlands |
![](https://www.dem9.fau.de/files/2023/03/Feng.jpg) |
The Developments of the Energy-Conserving Contact (ECC) Theory and Contact Models for Arbitrarily Shaped Particles
Yuntian Feng
Swansea University, United Kingdom |
![](https://www.dem9.fau.de/files/2023/03/Govender.jpeg) |
Particle shape effects in granular material using GPU DEM: An industry perspective
Nicolin Govender
(1) Department of Mechanical Engineering, University of Johannesburg, South Africa;
(2) Research Center Pharmaceutical Engineering GmbH, Graz 8010, Austria |
![](https://www.dem9.fau.de/files/2023/03/Karatza.jpg) |
Bridging the gap between simulation and reality through full-field experimental data
Zeynep Karatza
National Technical University of Athens, Greece |
![](https://www.dem9.fau.de/files/2023/03/Munjiza.jpg) |
Grand Challenge of AI-based Virtual Experimentation using DEM, FDEM, and Hybrid Simulation Technology
Antonio Munjiza
University of Split and Croatian Academy of Science, Croatia |
![](https://www.dem9.fau.de/files/2023/03/Parteli.jpg) |
Particle-based simulations of dry cohesive granular materials
Eric Parteli
Universität Duisburg-Essen, Germany
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![](https://www.dem9.fau.de/files/2023/03/Sakai-1.jpg) |
What technologies are essential in development of the DEM-based digital twin?
Mikio Sakai
University of Tokyo |