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Computational Modelling and Machine Learning for Applications in Hydropower



Two positions available: A post doc and a PhD


Hydropower is a leading renewable energy source where Norway plays a a significant role in Europe. In fact, over 90% of electricity in Norway is produced by hydropower. Nevertheless, we have recently seen significant fluctuations in electricity prices driven by a great deal of uncertainty in the water supply in the individual watercourses. This project aims to use modeling and machine learning to improve the understanding of the water supply.

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Illustrations of different water courses, determined by the topography. 


In this project we will explore multi-physics simulation models for water transport in different watercourses as shown in figure. The dynamics of watercourses, determined by weather and topography, are a coupled problem involving porous flow in the  soil and the viscous flow in streams and rivers, possibly driven by to snow and ice melting. Even in regulated watercourses, floods are often experienced due to unforeseen water flow. In this project we want to improve the understanding with multi-physics simulations based on methodology often used in bio-mechanics and geo-physics. Among other things, linked differential equations of different dimensions (1D, 2D, 3D) are included. 

Published Jan. 19, 2022 6:20 PM - Last modified Feb. 22, 2022 8:14 AM