M
Mona J. Mølnvik
Researcher at SINTEF
Publications - 27
Citations - 1200
Mona J. Mølnvik is an academic researcher from SINTEF. The author has contributed to research in topics: Software deployment & Pipeline transport. The author has an hindex of 14, co-authored 27 publications receiving 1065 citations.
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Journal ArticleDOI
Dynamis CO2 quality recommendations
Erika de Visser,Chris Hendriks,Maria Barrio,Mona J. Mølnvik,Gelein de Koeijer,Stefan Liljemark,Yann Le Gallo +6 more
TL;DR: In this paper, the authors investigate and recommend likely maximum allowable concentrations of impurities in the CO2 for safe transportation in pipelines, including safety and toxicity limits, compression work, hydrate formation, corrosion and free water formation.
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Ship Transport of CO2: Technical Solutions and Analysis of Costs, Energy Utilization, Exergy Efficiency and CO2 Emissions
TL;DR: In this article, a ship transport concept is developed as an alternative to pipeline transport, which includes all the elements in the transport chain, namely liquefaction, intermediate storage, loading system, semi-pressurized ship and offshore unloading system.
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Hydrogen quality from decarbonized fossil fuels to fuel cells
Brian Besancon,Vladimir Hasanov,Raphaëlle Imbault-Lastapis,Robert Benesch,Maria Barrio,Mona J. Mølnvik +5 more
TL;DR: In this paper, the authors examined the effects of impurities on fuel cell performance and assessed the capabilities of hydrogen production from decarbonized fossil fuels to meet the purity requirements dictated by use in fuel cells.
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Thermodynamic Models for Calculating Mutual Solubilities in H2O–CO2–CH4 Mixtures
TL;DR: In this article, the authors developed a database of reliable experimental data on solubility of H2O, CO2 and CH4 based on data collected from literature, and used the data to establish and suggest model parameters based on the database, and test and document the ability of the various EOS models to predict the solubilities of H 2O in CO2 or a mixture of CO 2 and CH 4.
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Optimization of a simple LNG process using sequential quadratic programming
TL;DR: The efficiency of using sequential quadratic programming (SQP) for the optimization of a PRICO process for the production of liquefied natural gas (LNG) is demonstrated.