New Publication on Artificial Neural Networks for Real-Time Predictions in Mechanized Tunnelling

A new paper with the title “Artificial neural network surrogate modelling for real-time predictions and control of building damage during mechanised tunnelling” is published in the journal Advances in Engineering Software. The paper is a joint work of the Institute for Structural Mechanics and the Institute of Concrete Structures at Ruhr University Bochum within the Collaborative Research Center SFB 837 “Interaction Modeling in Mechanized Tunneling”. In the paper, finite element simulations in combination with recurrent and feed-forward neural networks are used to predict settlements and damage risks of buildings during tunnel construction processes in real-time.

The paper can be downloaded here: https://doi.org/10.1016/j.advengsoft.2020.102869

Free download is available until August 14, 2020 via https://authors.elsevier.com/a/1bI9s_LzjZiNlv