Axel Larsson
Hi there! My name is Axel and I'm an intern at TNO, the Netherlands Organisation for Applied Scientific Research, working with Scientific Machine Learning for predicting structural responses. The internship is a part of my master thesis at University College London.
My fields of interest are computational structural engineering and computational design. Over the years, I've become more interested in more computing related topics like HPC, parallell processing and machine learning. This fall, I will move to the U.S. to start my PhD in Civil Engineering at Princeton University. I'm very interested in Julia for my future research and seeking collaborators in the Julia community.
Session
We study the utility of a scientific machine learning (SciML) model for predicting structural responses such as bridge deflections and stresses. The SciML model is compared with a data-driven neural network model for a synthetic and a real world case.In both cases, we rely on the Julia algorithmic differentiation ecosystem to efficiently fit the models. Our preliminary results indicate the superiority of the SciML mode over the data-driven one in interpolation and extrapolation as well.