B
Bernt Lie
Researcher at Sewanee: The University of the South
Publications - 140
Citations - 1009
Bernt Lie is an academic researcher from Sewanee: The University of the South. The author has contributed to research in topics: Modelica & Computer science. The author has an hindex of 16, co-authored 124 publications receiving 822 citations. Previous affiliations of Bernt Lie include Equinor & Norwegian Institute of Technology.
Papers
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Journal ArticleDOI
Dynamic modelling of the absorber of a post-combustion CO2 capture plant: Modelling and simulations
TL;DR: A model for the absorption column of a post-combustion CO 2 capture plant is developed following the rate based approach to represent heat and mass transfer and predictions of the transient behaviour of the developed absorber model appear realistic and comply with standard steady state models.
Journal ArticleDOI
State estimation and model-based control of a pilot anaerobic digestion reactor
Finn Haugen,Rune Bakke,Bernt Lie +2 more
TL;DR: In this paper, a state estimator and various model-based control systems have been designed for a real anaerobic digestion (AD) pilot reactor fed with dairy manure, and the model used is a modified Hill model which is a relatively simple dynamical AD process model.
Proceedings ArticleDOI
The OpenModelica Integrated Modeling, Simulation, and Optimization Environment
Peter Fritzson,Adrian Pop,Adeel Asghar,Bernhard Bachmann,Willi Braun,Robert Braun,Lena Buffoni,Francesco Casella,Rodrigo Castro,Alejandro Danós,Rüdiger Franke,Mahder Gebremedhin,Bernt Lie,Alachew Mengist,Kannan M. Moudgalya,Lennart Ochel,Arunkumar Palanisamy,Wladimir Schamai,Martin Sjölund,Bernhard Thiele,Volker Waurich,Per Östlund +21 more
TL;DR: An up-to-date brief description of the capabilities of the OpenModelica system, and the main vision behind its development are given.
Journal ArticleDOI
Adapting Dynamic Mathematical Models to a Pilot Anaerobic Digestion Reactor
Finn Haugen,Rune Bakke,Bernt Lie +2 more
TL;DR: In this article, a dynamic model has been adapted to a pilot anaerobic reactor fed diary manure, which can predict the methane gas flow produced in the reactor and can be used for optimal reactor design and operation, state estimation and control.
Proceedings ArticleDOI
Machine Learning in Python for Weather Forecast based on Freely Available Weather Data
TL;DR: A Python API to read meteorological data has been developed, and ANN models have been developed using TensorFlow, to study whether an artificial neural network can be a good candidate for prediction of weather conditions in combination with large data sets.