Best communication awards 2020
In 2020, the ESAFORM association has created a new event for young researchers engaged in a PhD activity, the Best communication award. On Tuesday May 5th, the winners were announced at the general assembly of the 2020 virtual conference as:
1) Mr Andeas Hetzel, from Friedrich-Alexander-Universität (Germany)
Enhancement of the forming limits for orbital formed tailored blanks by local short-term heat treatment
https://www.sciencedirect.com/science/article/pii/S2351978920312373
Graphical abstract:
Â
2) Ms Wenqi Liu, from Aalto University (Finland) and RWTH Aachen University (Germany)
Microstructure effects on the plastic anisotropy of a fine-structured dual-phase steel
https://www.sciencedirect.com/science/article/pii/S2351978920314165
Graphical abstract:
Â
3) Mr Clemens Zimmerling, from Karlsruhe Institute of Technology (Germany)
Estimating optimum process parameters in textile draping of variable part geometries - A reinforcement learning approach
https://www.sciencedirect.com/science/article/pii/S2351978920313299
Graphical abstract:
Best communication awards 2020
In 2020, the ESAFORM association has created a new event for young researchers engaged in a PhD activity, the Best communication award. On Tuesday May 5th, the winners were announced at the general assembly of the 2020 virtual conference as:
1) Mr Andeas Hetzel, from Friedrich-Alexander-Universität (Germany)
Enhancement of the forming limits for orbital formed tailored blanks by local short-term heat treatment
https://www.sciencedirect.com/science/article/pii/S2351978920312373
Graphical abstract:
Â
2) Ms Wenqi Liu, from Aalto University (Finland) and RWTH Aachen University (Germany)
Microstructure effects on the plastic anisotropy of a fine-structured dual-phase steel
https://www.sciencedirect.com/science/article/pii/S2351978920314165
Graphical abstract:
Â
3) Mr Clemens Zimmerling, from Karlsruhe Institute of Technology (Germany)
Estimating optimum process parameters in textile draping of variable part geometries - A reinforcement learning approach
https://www.sciencedirect.com/science/article/pii/S2351978920313299
Graphical abstract:
Recent Comments