Continuum / Atomics Coupling
Dr.-Ing. Wenzhe Shan
The JRG led by Dr.-Ing. Wenzhe Shan focuses on multiscale models with the coupling of the traditional finite element method and atomic models. As a former mechanical engineering student at Shanghai Jiao Tong University and the University of Michigan, Dr. Shan has just received his doctorate degree from Leibniz Universität Hannover and is now proceeding with his research work at MUSIC.
“My research will be focused on developing adaptively coupled finite element/atomistic models for simulating material behaviour at different scales. The area of application in the future will be the material design at atomic level and investigating the internal structures of materials. The current experimental techniques for such tasks are still limited. Therefore, effective simulation programs based on multiscale models are expected to become powerful tools. At the current stage, such simulation programs are still far away from being sophisticated. Reducing the computational time, widening the material database and developing robust and efficient program structures are still the main tasks in the foreseeable future.”
Dr. Shan’s vision is to put together a multi-disciplinary team where researchers in physics, mathematics and engineering fields can work together with each other. “Cooperation with other institutes is also an important task for us,” he adds. “Multiscale modelling is a big research field where many well-established researchers, both at home and abroad, have already been working on various topics. Therefore, constructive cooperation, such as exchange programmes, guest lecturers or co-authoring of articles could be very beneficial. Moreover, we also need help from institutes with sophisticated experimental facilities for verifying our numerical models.”
In fact, the experimental validation is an important issue for almost any simulation results. There are now 14 institutes from the university participating at MUSIC and each of them offers unique possibilities for experimental testing. They form a magnificent background for validating the simulation data, which leads to a higher degree of significance and acceptance.