Go straight to content

Per Pettersson

Senior Researcher

+47 56 10 71 34
Nygårdsgaten 112, 5008 Bergen, Norway

Per Pettersson has a PhD from the Institute for Computational and Mathematical Engineering, Stanford University, and a PhD in numerical analysis from Uppsala University, Sweden. Both degrees were funded by KAUST (King Abdullah University of Science and Technology).

Pettersson is active in method development, analysis, and implementation of mathematical methods for uncertainty quantification, e.g., polynomial chaos, accelerated Monte Carlo methods, and rare-event simulation. Applications include CO2 storage, CFD, flood modeling, and combustion.

He has been an employee since 2014, first at Uni Research and then NORCE.

Per Pettersson


Energy & Technology

Research Groups

Computational Geosciences and Modelling

More information about Per

See profile in Cristin

Open CV

Download pressphoto


See all
See all
Sampling-Based Methods for Uncertainty Propagation in Flood Modeling Under Multiple Uncertain Inputs: Finding Out the Most Efficient Choice – Water Resources Research 2023
Adaptive stratified sampling for nonsmooth problems – International Journal for Uncertainty Quantification 2022
Dynamic estimates of extreme-case CO2 storage capacity for basin-scale heterogeneous systems under geological uncertainty – International Journal of Greenhouse Gas Control 2022
Adaptive stratified sampling for non-smooth problems – arXiv.org 2021
Intrusive generalized polynomial chaos with asynchronous time integration for the solution of the unsteady Navier–Stokes equations – Computers & Fluids 2021
Mathematical modeling, laboratory experiments, and sensitivity analysis of bioplug technology at Darcy scale – SPE Journal 2020
Uncertainty quantification of combustion noise by generalized polynomial chaos and state-space models – Combustion and Flame 2020
Probabilistic Godunov-type hydrodynamic modelling under multiple uncertainties: robust wavelet-based formulations – Advances in Water Resources 2020
Level set methods for stochastic discontinuity detection in nonlinear problems – Journal of Computational Physics 2019
Generalized chaos expansion of state space models for uncertainty quantification in thermoacoustics – 2018
A pore-scale model for permeable biofilm: Numerical simulations and laboratory experiments – Transport in Porous Media 2018
Simulation recommendations for CO2 storage, Report no UC 44/2016 – Uni Research CIPR 2016
Final report LCSANS, Report no UC 43/2016 – Uni Research CIPR 2016
Skade Case Study. Technical Report no. UC45/2016. – Uni Research 2016
Stochastic Galerkin framework with locally reduced bases for nonlinear two-phase transport in heterogeneous formations – Computer Methods in Applied Mechanics and Engineering 2016
A well-posed and stable stochastic Galerkin formulation of the incompressible Navier-Stokes equations with random data – Journal of Computational Physics 2016
Stochastic Galerkin Formulations for CO2 Transport in Aquifers: Numerical Solutions with Uncertain Material Properties – Transport in Porous Media 2015
Polynomial Chaos Methods for Hyperbolic Partial Differential Equations Numerical Techniques for Fluid Dynamics Problems in the Presence of Uncertainties – Springer 2015
Stochastic Galerkin Method for the Buckley-Leverett Problem in Heterogeneous Formations – 2014
See all publications in Cristin