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Helge Avlesen

Guest Researcher
  • E-mailhelge.avlesen@uib.no
  • Visitor Address
    Allégaten 70
    5007 Bergen
  • Postal Address
    Postboks 7803
    5020 Bergen

Mostly working on projects where I use and develop our in house ocean model, the Bergen Ocean Model (BOM): http://org.uib.no/bom/.

Examples of applications are modeling dispersion of water masses with pollutants, such as micro plastics, in the fjord system around Bergen,  dispersion of dissolved CO2 in the North Sea and methods to aid detection of seeps, see publication list. 

Academic article
  • Show author(s) (2022). Topographic effects on buoyancy driven flows along the slope. Environmental Fluid Mechanics. 1-20.
  • Show author(s) (2022). Assuring the integrity of offshore carbon dioxide storage. Renewable & Sustainable Energy Reviews. 9 pages.
  • Show author(s) (2020). Impact and detectability of hypothetical CCS offshore seep scenarios as an aid to storage assurance and risk assessment. International Journal of Greenhouse Gas Control.
  • Show author(s) (2019). The role of eddies on pathways, transports, and entrainment in dense water flows along a slope. Ocean Dynamics. 841-860.
  • Show author(s) (2018). Effects of the bottom boundary condition in numerical investigations of dense water cascading on a slope. Ocean Dynamics. 553-573.
  • Show author(s) (2017). Using Bayes theorem to quantify and reduce uncertainties when monitoring varying marine environments for indications of a leak. Energy Procedia. 3607-3612.
  • Show author(s) (2016). Simulating spatial and temporal varying CO2 signals fromsources at the seafloor to help designing risk-basedmonitoring programs. Journal of Geophysical Research (JGR): Oceans. 745-757.
  • Show author(s) (2016). Gravity currents down canyons: effects of rotation. Ocean Dynamics. 1353-1378.
  • Show author(s) (2015). Layout of CCS monitoring infrastructure with highest probability of detecting a footprint of a CO2 leak in a varying marine environment. International Journal of Greenhouse Gas Control. 274-279.
  • Show author(s) (2015). Internal pressure gradient errors in σ-coordinate ocean models in high resolution fjord studies. Ocean Modelling. 42-55.
  • Show author(s) (2012). Stratified flow over complex topography: A model study of the bottom drag and associated mixing. Continental Shelf Research. 41-52.
Report
  • Show author(s) (2019). Underpinning data for monitoring activities (including current statistics and carbon tracer quantifications). .
  • Show author(s) (2019). Strøm- og temperaturforhold i Evangervatnet under smoltutgangen i 2018. 330. 330. .
  • Show author(s) (2019). Modelling of extreme currents along the planned bridge in Bjørnafjorden. Part II: the importance of mixing schemes . .
  • Show author(s) (2018). Modelling of extreme currents along the planned bridge in Bjørnafjorden. .
  • Show author(s) (2014). Technical report on environmental conditions and possible leak scenarios in the North Sea. .
  • Show author(s) (2013). Technical report on verified and validated application of droplet/bubble plume-, geochemical- and general flow- models. .
  • Show author(s) (2012). Numerisk simulering av strøm i Sørfjorden. 29. 29. .
  • Show author(s) (2011). Tracking of passive, neutrally buoyant particles using the Bergen Ocean Model. 27. 27. .
  • Show author(s) (1998). A study of two new splitting methods for the gravity part of the shallow water equations. 145. 145. .
  • Show author(s) (1998). A convergence study of two prognostic, sigma coordinate ocean models on a density driven flow in a quadratic basin. 157. 157. .
  • Show author(s) (1998). A convergence study of two prognostic, sigma coordinate ocean models on a dencity driven flow in a quadratic basin. No. 157. No. 157. .
Lecture
  • Show author(s) (2018). Effekten av Evanger kraftverk på strømforholda i Evangervatnet under smoltutgangen 2018 – målingar og modeller.
Academic lecture
  • Show author(s) (2018). Machine Learning in CO2 leak detection.
  • Show author(s) (2018). Ensuring efficient and robust offshore storage – the role of marine system modelling.
  • Show author(s) (2018). Combining Models and Machine Learning Techniques to Design Leak Detection Monitoring .
  • Show author(s) (2018). Combining Environmental Statistics and Marine Process Modelling to Design Monitoring Programs for Offshore CO2 Storage.
  • Show author(s) (2017). The role of Ekman drainage in numerical investigations of dense water cascading on a slope: Sensitivity to vertical resolution and bottom boundary condition.
  • Show author(s) (2013). Spatial footprint of a leak.
Doctoral dissertation
  • Show author(s) (2000). On the choice of numerical algorithms for ocean modeling.
Academic chapter/article/Conference paper
  • Show author(s) (2017). Numerical investigations of dense water cascading on a slope - the role of the bottom boundary layer. 13 pages.
Poster
  • Show author(s) (2019). Ensuring efficient and robust carbon storage: marine modelling for environmental monitoring.
  • Show author(s) (2018). Model Reduction for Tracer Transport and Applications.
  • Show author(s) (2018). Mathematical methods for detection and localization of CO2 leaks.
  • Show author(s) (2017). Bayes’ theorem as the fundament to design monitoring programs.
  • Show author(s) (2017). Assessment of machine learning methods as a tool in detecting leakages.
  • Show author(s) (2017). Assessment of Topological Data Analysis and Machine Learning Technologies as Tools for Seep Detection.
  • Show author(s) (2016). Using Bayes Theorem to Quantify and Reduce Uncertainties when Monitoring Varying Marine Environments for Indications of a Leak.
  • Show author(s) (2016). Bayes’ theorem as the fundament to design monitoring programs.

More information in national current research information system (CRIStin)