Analysis of the melting and solidification process of aluminum in a mirror furnace using Fiber-Bragg-Grating and numerical models
Guest Speaker: Prof. Wolfram Volk, Member of Acatech-National Academy of Science and Engineering, Technical University of Munich
Date & Time: 14:30-16:00, Nov. 20, 2024
Location: Meeting Room 304，E Building of SMSE
Inviter: Prof. Jun Chen, Assoc.Prof. Qi Hu
Biography
Prof. Dr.-Ing. Wolfram Volk studied physics and mechanics at TU Darmstadt and received his diploma in 1994. His work as research associate under the direction of Prof. Dr.-Ing. Wolfgang Ehlers led to his Ph. D. in 1999. After that he worked in different positions in the fields of metal forming with focus on simulation, product and process planning as well as concept development at BMW AG in Munich. Since April 2011, Prof. Volk holds the Chair of Metal Forming and Casting as a full professor at the Technical University of Munich. The chair focuses on the three production processes of casting, blanking and metal forming. Prof. Volk has about 40 scientists at his institute working on research projects, which vary from fundamental research to industrial application. Since July 2016 he is also a member of the board at the Fraunhofer Institute for Casting, Composite and Processing Technology IGCV. He is also involved in the research community in many ways, e.g. as member of National Academy of Science and Engineering, review board member of the German Research Foundation DFG), CIRP Fellow member and Coordinator of the German National Group of the IDDRG.
Abstract：
This presentation focuses on the research of an adequate real time strain measurement method in aluminum casting. The Fiber-Bragg-Grating measurements have great potential in the data collection of the melting, solidification and remelting process of the fiber alloy compound. Besides, the behavior of the interaction between the fiber and the alloy can be described with the combination with the transient multi domain heat transfer simulation and the structural finite element model.