Unmanned aerial vehicle (UAV) applications have evolved to a wide range of fields in the last decade. One of the main challenges in autonomous tasks is the UAV stability during maneuvers. Thus, attitude and position control ...

One long-standing characteristic of schools in Norway is inclusive education as a primary goal. The last years, the Norwegian government has emphasised increased parent-school cooperation as a way to limit risks, i.e. of ...

Abstract—In graph neural networks (GNNs), pooling operators compute local summaries of input graphs to capture their global properties, and they are fundamental for building deep GNNs that learn hierarchical representations. ...

The choice of a prior model can have a large impact on the ability to assimilate data. In standard applications of ensemble-based data assimilation, all realizations in the initial ensemble are generated from the same ...

In this article, we consider a nonlocal (in time) two‐phase flow model. The nonlocality is introduced through the wettability alteration induced dynamic capillary pressure function. We present a monotone fixed‐point iterative ...

In sequential field development planning, past decisions not only directly affect the maximum achievable expected NPV but also influence the future information that can be used to reduce geological uncertainty. To act ...

During drilling, to maximize future expected production of hydrocarbon resources, the experts commonly adjust the trajectory (geosteer) in response to new insights obtained through real-time measurements. Geosteering ...

‘Defence in depth’ (DID) is a fundamental safety principle applied in several industries, including nuclear. The key is to protect safety critical systems by employing multiple layers of protection, i.e. barriers. The ...

This work presents an ensemble-based workflow to simultaneously assimilate multiple types of field data in a proper and consistent manner. The aim of using multiple field datasets is to improve the reliability of estimated ...