The following is an excerpt.

SFI CASA´s new PhD candidate Håvard Næss aims to make numerical simulations more accurate concerning plasticity and fracture. Without increasing the computational and calibration costs.

Håvard Næss´s (in the foreground) relations to CASA started in autumn 2020. Then, he wrote his project thesis based on experiments performed in collaboration with Simen Halvor Landsverk Johansen (photo: Sølvi W. Normannsen).

Name: Håvard Næss
Age: 26
From: Mære/Steinkjer, Norway

Background: Master’s degree in Mechanical engineering from NTNU. I wrote my master’s thesis on the structural response of plated offshore structures due to violent wave impacts. The MSc thesis was a part of the KPN SLADE project. It was mainly a numerical study. However, the simulations were validated using available experimental results to investigate important modelling parameters in dynamic fluid-structure interaction problems.

Could you give a short description of the PhD- project?
To study how machine learning can contribute to solving the upscaling problem in material mechanics.

Two male student investigating a metal specimen after blast load
In his project assignment, Næss studied the behaviour of braced aluminium panels exposed to extreme pressure loads. Here, he and fellow student Simen Halvor Landsverk Johansen investigated aluminium panels after an experiment.

What is the goal?
The goal is to make numerical simulations more accurate concerning plasticity and fracture without increasing the computational and calibration costs.

Who needs this knowledge?
The industry can save money in design by applying this technology. Besides, more accurate simulations lead to less material consumption and thus more sustainable structures. Furthermore, the research community will be interested in the potential of machine learning in upscaling problems.

Why did you choose a doctorate in SFI CASA?
A PhD position offers the opportunity to focus on a narrow field for a longer period. In fact, and I have considered it for several years. Through the last year of my master’s degree, I got to know the research group, and I found the field very interesting. As a result of that, I decided to join the group as a PhD candidate. 

How would you describe yourself – in keyword form?
Positive, curious and flexible

Håvard Næss´s supervisors are Professor Odd Sture Hopperstad and Associate professor David Morin.