MC4DT

Our urgent need to understand and adapt to our changing world has led to an increasing interest in Digital Twins in science, industry, and public administration. Understanding and predicting the behaviour of our environment requires integrating simulation models with each other and with databases describing the history and state of these systems. This requires advanced techniques such as model coupling, data assimilation and uncertainty quantification. We currently have many projects involving these kinds of simulations (see below), and more to come amongst others from our current call on Digital Twins.

Our eScience toolkit currently contains two tools that aim to make the construction of coupled simulations easier: AMUSE and MUSCLE3. Our constant growth and the increasing importance of the topic have resulted in a need to better disseminate these technologies within the eScience Center. The goal of this project is to disseminate knowledge of model coupling within the eScience Center by organising an internal workshop on MUSCLE3 and AMUSE, and to create teaching materials for it that can be reused in the future.