Ellen Marie Nordgård-Hansen

• Nordgård-Hansen, Ellen Marie; Fjellså, Ingvild Firman; Medgyes, Tamás; Guðmundsdóttir, María; Pétursson, Baldur & Miecznik, Maciej [Show all 10 contributors for this article] (2023). Differences in Direct Geothermal Energy Utilization for Heating and Cooling in Central and Northern European Countries. Energies. ISSN 1996-1073. 16(18). doi: 10.3390/en16186465. Show summary

  Geothermal energy has emerged as an alternative heating source that can replace fossil energy. This mature technology is already in use all over Europe, but there are significant differences in its use between European countries. One possible explanation for this phenomenon concerns societal differences directly related to geothermal energy, the topic that is investigated in this study. The present work proposes using the societal embeddedness level (SEL) method to analyze and compare the status of non-technical factors affecting geothermal energy use in Hungary, Iceland, Norway, Poland, and Slovakia. The method considers four dimensions: environment, stakeholder involvement, policy and regulations, and markets and financial resources. Only Iceland fully covers the four dimensions by reaching all the milestones in the SEL framework. Iceland has the advantage of a long history of active use of geothermal energy for domestic use. The other countries face challenges within several of the dimensions, while the form and cause of these challenges are specific to each country. The findings illustrate that to mitigate climate change and drive the energy transition forward, both technical and societal factors related to various renewable energy sources must be assessed.

• Falconer, Shaun; Krause, Peter; Bäck, Thomas; Nordgård-Hansen, Ellen Marie & Grasmo, Geir (2022). Condition Classification of Fibre Ropes during Cyclic Bend over Sheave testing Using Machine Learning. International Journal of Prognostics and Health Management. ISSN 2153-2648. 13(1). doi: 10.36001/IJPHM.2022.v13i1.3105. Full text in Research Archive Show summary

  Fibre ropes have been shown to be a viable alternative to steel wire rope for offshore lifting operations. Visual inspection remains a common method of fibre rope condition monitoring and has the potential to be further automated by machine learning. This would provide a valuable aid to current inspection frameworks to make more accurate decisions on recertification or retirement of fibre ropes in operational use. Three different machine learning algorithms: decision tree, random forest and support vector machine are compared to classical statistical approaches such as logistic regression, k-nearest neighbours and Naïve-Bayes for condition classification for fibre ropes under cyclic-bend-over-sheave (CBOS) testing. By measuring the rope global elongation throughout the CBOS tests, a binary classification system has been used to label recorded samples as healthy or close to rupture. Predictions are made on one rope through leave-one-out cross validation. The models are then assessed through calculating the accuracy, probability of detection, probability of false alarm and Matthew’s Correlation Coefficient, and ranked based on the results. The results show that both machine learning and classical statistical methods are effective options for condition classification of fibre ropes under CBOS regimes. Typical values for Matthews Correlation Coefficient (MCC) were shown to exceed 0.8 for the best performing methods.

• Nordgård-Hansen, Ellen Marie; Kishor, Nand; Midttømme, Kirsti; Risinggård, Vetle Kjær & Kocbach, Jan (2021). Case study on optimal design and operation of detached house energy system: Solar, battery, and ground source heat pump. Applied Energy. ISSN 0306-2619. 308. doi: 10.1016/j.apenergy.2021.118370. Show summary

  Government policy impacts the level of sustainability for which houseowners design and operate their energy system. Consequently, there is a need to consider the sustainability level resulting from different policies, assuming optimal design and operation. The present work focuses on detached residential houses, where the energy system consists of photovoltaic systems for energy generation and batteries and optional ground-source heat pump systems for energy storage. A mixed-integer linear programming model is presented, which takes policies and other constraints into account when optimizing system size and operation. The results allow overall sustainability validation through parameters like self-sufficiency and self-sustainability, as well as a detailed drill-down of the optimal operation. From the analysis, two modes of ground-source heat pump usage are seen. With a feed-in tariff present, its main use is as an energy source, while without this tariff the optimal use is for seasonal energy storage. It is also found that ground-source heat pump systems contribute to increased sustainability, but they may not be economically beneficial for single-family homes having low or medium heating requirements. Demands for heating and cooling change with time and place, as do available area for photovoltaic energy generation and externally available energy sources. Therefore, a detailed analysis of the kind presented here is recommended before new energy policies are implemented. For each specific house or project, this kind of analysis will also be useful to evaluate the sensitivity of an energy system’s performance towards changing policies.

• Falconer, Shaun; Nordgård-Hansen, Ellen Marie & Grasmo, Geir (2021). Remaining useful life estimation of HMPE rope during CBOS testing through machine learning. Ocean Engineering. ISSN 0029-8018. 238. doi: 10.1016/j.oceaneng.2021.109617. Full text in Research Archive Show summary

  Fibre rope used in cranes for offshore deployment and recovery has significant potential to perform lifts with smaller cranes and vessels to reach depths limited by weight of steel wire rope. Current condition monitoring methods based on manual inspection and time-based and reactive maintenance have significant potential for improvement coupled with more accurate remaining useful life (RUL) prediction. Machine learning has found use as a condition monitoring approach, coupled with vast improvements in data acquisition methods. This paper details data-driven RUL prediction methods based on machine learning algorithms applied on cyclic-bend-over-sheave (CBOS) tests performed on two fibre rope types until failure. Data extracted through computer vision and thermal monitoring is used to predict RUL through neural networks, support vector machines and random forest. Random forest and neural networks methods are shown to be particularly adept at predicting RUL compared to support vector machines . Additionally, improved RUL predictions can be achieved by combining data from distinct rope types subject to different test conditions.

• Falconer, Shaun; Nordgård-Hansen, Ellen Marie & Grasmo, Geir (2020). Computer vision and thermal monitoring of HMPE fibre rope condition during CBOS testing. Applied Ocean Research. ISSN 0141-1187. 102. doi: 10.1016/j.apor.2020.102248. Full text in Research Archive Show summary

  Fibre rope usage in deep sea lifting operations is gaining more prominence in recent times. With rope minimum break loads (MBL) comparable to that of their steel wire counterparts, the use of high modulus polyethylene (HMPE) ropes is seen as a viable option for use in subsea construction cranes. The ropes are worn out during use and visual inspection remains one of the main methods of determining whether a fibre rope is to be retired from use, therefore a natural extension is condition monitoring through computer vision. Creep and temperature are constraining with HMPE ropes and should be monitored continuously, particularly when the rope is cyclically bent over sheaves. Additionally, interpreting the thermal history of the rope during use could give insight into deterioration. In this paper, a condition monitoring system based on combined computer vision and thermal monitoring is used during cyclic bend over sheave tests performed on 560 kN break load of 12 strand braided HMPE ropes. New monitoring features such as local length and width through computer vision algorithms combined with surface thermal monitoring and global elongation are presented and their effectiveness as condition monitoring features is assessed.

• Falconer, Shaun; Nordgård-Hansen, Ellen Marie & Grasmo, Geir (2020). Temperature Measurements as a Method for Monitoring Ropes. In Liyanage, Jayantha Prasanna; Amadi-Echendu, Joe E. & Mathew, Joseph (Ed.), Engineering assets and public infrastructures in the age of digitalization : Proceedings of the 13th world congress on engineering asset management. Springer. ISSN 9783030480202. p. 772–779. doi: 10.1007/978-3-030-48021-9_85.
• Kovacs, Attila; Breward, Chris J.W.; Einarsrud, Kristian Etienne; Halvorsen, Svenn Anton; Nordgård-Hansen, Ellen Marie & Manger, Eirik [Show all 8 contributors for this article] (2020). A heat and mass transfer problem for the dissolution of an alumina particle in a cryolite bath. International Journal of Heat and Mass Transfer. ISSN 0017-9310. 162, p. 1–12. doi: 10.1016/j.ijheatmasstransfer.2020.120232. Show summary

  We investigate the spherically symmetric dissolution of an initially cold alumina particle in a bath of molten cryolite. The cryolite initially freezes on the particle, forming a shell that must melt before the particle can dissolve. We derive asymptotic solutions valid in the limits of small-superheat and of small Stefan number. In the small-superheat limit, the evolution of the boundary exhibits a two-scale behaviour. In the small Stefan number limit, we find that the behaviour of a particle could be limited by either the dissolution (in the case where the temperature differences are small) or by heat transfer (when the latent heat is large and the temperature gradients are large). Our asymptotic predictions are validated by a front fixing numerical scheme that we initiate using the early-time asymptotics.

• Falconer, Shaun; Grasmo, Geir & Nordgård-Hansen, Ellen Marie (2019). Condition monitoring of HMPE fibre rope using computer vision during CBOS testing. In Dohm, M. A. R. (Eds.), Exploring Opportunities - Synthetic/Steel - Proceedings of the OIPEEC Conference 2019. OIPEEC. ISSN 978-1-7336004-0-8. p. 129–147. Show summary

  The paper details the results of recent cyclic-bend-over-sheave (CBOS) experiments performed at the Mechatronics Innovation Lab (MIL) located at the University of Agder, Norway. A method for measuring diameter and elongation of discrete sections of fibre rope using computer vision is detailed. Estimations of the change in roundness of the rope are also explored based on the diameter measurements. These measurements are then assessed for their suitability as condition indicators.

• Nordgård-Hansen, Ellen Marie; Hassel, Håkon Jarle & Schlanbusch, Rune (2019). Chemometrics as a Tool to Gain Insight into Fiber Rope Aging from Infrared Images. Proceedings of the Annual Conference of the Prognostics and Health Management Society, PHM. ISSN 2325-0178. p. 1–13.
• Nordgård-Hansen, Ellen Marie; Schlanbusch, Rune & Sørensen, Thore Jarle (2017). Modeling of a lay-flat plastic hose extrusion process. MIC Journal: Modeling, Identification and Control. ISSN 0332-7353. 38(3), p. 111–121. doi: 10.4173/mic.2017.3.1.
• Roberts, Lindon; Nordgård-Hansen, Ellen Marie; Mikkelsen, Øyvind; Halvorsen, Svenn Anton & Van Gorder, Robert A. (2017). A heat and mass transfer study of carbon paste baking. International Communications in Heat and Mass Transfer. ISSN 0735-1933. 88, p. 9–19. doi: 10.1016/j.icheatmasstransfer.2017.07.025.
• Nordgård-Hansen, Ellen Marie & Hildal, Kjetil (2016). Skull formation in dynamic modelling of silicon refining. IFAC-PapersOnLine. ISSN 2405-8963. 49(20), p. 173–177. doi: 10.1016/j.ifacol.2016.10.116. Show summary

  An offline simulation tool for silicon refining is extended with an improved model for skull formation. In this model, skulls are seen as highly viscous slag with droplets of refined silicon trapped within. Since slag viscosity depends strongly on its lime content, the degree of skull formation varies with how much calcium is removed from the melt. The skulls influence the geometry of the ladle as well as the heat balance, and accumulate from tap to tap. It is seen that the simulation results reflect data from normal operation.

• Hansen, Ellen Marie; Egner, Espen & Kjelstrup, Signe (1998). Peltier effects in electrode carbon. Metallurgical and Materials Transactions A. ISSN 1073-5623. 29B, p. 69–76.
• Hansen, Ellen Marie & Kjelstrup, Signe (1997). Application of nonequilibrium thermodynamics to the ledge surface of aluminium electrolysis cells. Light Metals. ISSN 0147-0809. p. 355–361.
• Kjelstrup, Signe; Bedeaux, Dick & Hansen, Ellen Marie (1997). Surface contributions to EMF and half cell potentials of nonisothermal electrode concentration cells. Periodika polytchnika Ser. Chem. eng.. 41(2), p. 125–142.
• Hansen, Ellen Marie; Kjelstrup, Signe; Flem, Belinda Eline & Bedeaux, Dick (1996). Application of nonequilibrium thermodynamics to aluminium electrolysis cells. Light Metals. ISSN 0147-0809. p. 211–217.
• Hansen, Ellen Marie & Kjelstrup, Signe (1996). Application of nonequilibrium thermodynamics to the electrode surfaces of aluminum electrolysis cells. Journal of the Electrochemical Society. ISSN 0013-4651. 143(11), p. 3440–3447.
• Kjelstrup, Signe; Sauar, Erik; Hansen, Ellen Marie; Lien, Kristian Myklebust & Hafskjold, Bjørn (1995). Analysis of Entropy Production Rates for Design of Distillation Columns. Industrial & Engineering Chemistry Research. ISSN 0888-5885. 34(9), p. 3001–3007.

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• Nordgård-Hansen, Ellen Marie (2024). Control of electrode position—present and future ideas.
• Midttømme, Kirsti & Nordgård-Hansen, Ellen Marie (2023). Possibilities of practical results' implementation, bottle necks in Norway.
• Nordgård-Hansen, Ellen Marie & Midttømme, Kirsti (2023). NORCE and geothermal energy - User4GeoEnergy presentations May 2023.
• Nordgård-Hansen, Ellen Marie & Midttømme, Kirsti (2023). NORCE and geothermal energy - User4GeoEnergy presentations May 2023.
• Nordgård-Hansen, Ellen Marie & Midttømme, Kirsti (2023). Status og utfordringer for geotermisk energi i Agder.
• Nordgård-Hansen, Ellen Marie (2022). Bergvarme kan brukes som batteri. [Newspaper]. Fædrelandsvennen. Show summary

  Bergvarme fører til økt bærekraft, men bergarme er dyrt og foreløpig ikke lønnsomt for enkeltstående eneboliger

• Midttømme, Kirsti; Nordgård-Hansen, Ellen Marie & Tryggvason, Heimir (2022). WP3: Exchange of experiences between partners in the field of low- and medium-temperature heating.
• Nordgård-Hansen, Ellen Marie (2022). Reduksjon av CO2-utslipp ved bruk av karbon nanofiber.
• Nordgård-Hansen, Ellen Marie & Haugen, Øyvind (2022). Optimalisering av kombinasjonen brenselceller – batterier for små fartøy.
• Fromreide, Mads & Nordgård-Hansen, Ellen Marie (2022). Test av nylontau for flytende havvind – Materialtester fra prosjektet FIRM.
• Midttømme, Kirsti; Nordgård-Hansen, Ellen Marie & Risinggård, Vetle Kjær (2022). Geothermal heat pumps in Norway .
• Nygaard, Tor Anders; Zhang, Bin; Andersen, Håkon; Nordgård-Hansen, Ellen Marie & Kaynia, Amir M. (2021). FibreRope Mooring for Floating Wind Turbines.
• Kovacs, Attila; Breward, Chris; Oliver, James; Münch, Andreas; Halvorsen, Svenn Anton & Nordgård-Hansen, Ellen Marie [Show all 7 contributors for this article] (2019). Mathematical modelling of alumina feeding.
• Falconer, Shaun; Grasmo, Geir & Nordgård-Hansen, Ellen Marie (2019). Condition monitoring of HMPE fibre rope using computer vision during CBOS testing.
• Nordgård-Hansen, Ellen Marie; Hassel, Håkon Jarle & Schlanbusch, Rune (2019). Chemometrics as a Tool to Gain Insight into Fiber Rope Aging from Infrared Images.
• Kovacs, Attila; Breward, Chris; Oliver, James; Münch, Andreas; Halvorsen, Svenn Anton & Nordgård-Hansen, Ellen Marie [Show all 7 contributors for this article] (2019). Mathematical modelling of alumina feeding.
• Kovacs, Attila; Breward, Chris; Oliver, James; Münch, Andreas; Halvorsen, Svenn Anton & Nordgård-Hansen, Ellen Marie [Show all 7 contributors for this article] (2019). Mathematical modelling of alumina feeding.
• Nordgård-Hansen, Ellen Marie; Erdelyi, Szilvia; Vigier, Xavier & Buschmann, Markus (2019). Tretthetsvurdering av offhsorekraner.
• Nordgård-Hansen, Ellen Marie; Erdelyi, Szilvia; Vigier, Xavier & Buschmann, Markus (2019). Fatigue evaluation of offshore cranes based on operational data.
• Falconer, Shaun; Nordgård-Hansen, Ellen Marie & Grasmo, Geir (2018). Temperature measurements as a method for monitoring ropes.
• Kovacs, Attila; Oliver, James M.; Münch, Andreas; Halvorsen, Svenn Anton & Nordgård-Hansen, Ellen Marie (2018). Mathematical modelling of alumina feeding.
• Herland, Egil Vålandsmyr; Finlay, Christopher C.; Olsen, Nils; Edvardsen, Inge; Nordgård-Hansen, Ellen Marie & Laundal, Karl Magnus [Show all 7 contributors for this article] (2017). The CHAOS-X Model and Uncertainty Values for Magnetic Directional Surveying.
• Nordgård-Hansen, Ellen Marie & Schlanbusch, Rune (2023). Condition monitoring and maintenance for fibre rope moorings in offshore wind. Aibel. Show summary

  The FIRM project aims to develop innovative mooring systems for floating wind farms based on fibre ropes, including new and more efficient methods for installation, condition monitoring, maintenance, and decommissioning. The project shall deliver designs for three different mooring systems. This document describes the contents of work package H7 in the FIRM project.

• Nordgård-Hansen, Ellen Marie (2022). Smart meters and messaging: Task 1.5 in the project “Integrated Renewable Resources and Storage: Operation and Management”. NORCE Norwegian Research Centre. ISSN 978-82-8408-171-7. Show summary

  Monte Carlo-type simulations based on data from the Skarpnes village have been used to assess the benefits of smart meters for rooftop PV systems. The results show that when installing PV panels on private homes on the south coast of Norway, it is not immediately economically beneficial to also install batteries and smart meters. This will change if the present feed-in tariff is reduced or removed, and it may also change if the load patterns are changed.

• Alagic, Edin; Blomgren, Atle; Guo, Ying; Nordgård-Hansen, Ellen Marie & Thisted, Ulrik (2022). Reduction in CO2 emissions from using carbon nanofiber additives. NORCE Norwegian Research Centre.
• Risinggård, Vetle Kjær & Nordgård-Hansen, Ellen Marie (2020). Utnyttelse av spillvarme i Lista Renewable Energy Park. NORCE Norwegian Research Centre. Show summary

  I denne rapporten er det sett på utradisjonelle bruksområder for spillvarme fra en battericellefabrikk med temperatur fra 35–40 °C og opp mot 80 °C. Mellomlagring av spillvarme for utjevning av variasjoner i produksjon eller forbruk kan gjøres i industriell skala og bør vurderes. Direkte bruk av varmen til oppvarming eller tørking kan også gjøres med gode virkningsgrader. Spesielt nevnes tørking av tømmer for trekullproduksjon som en relevant anvendelse. Videre er kjøling og renseprosesser spennende områder. Vannrensing kan være aktuelt for landbasert oppdrett eller akvaponi. Absorpsjonskjøling kan blant annet være aktuelt for bruk i et datasenter. Det anbefales også en grundig gjennomgang av mulighetene for å redusere mengden spillvarme ved best mulig varmeintegrasjon internt i battericellefabrikken.

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