Description
Leader of the group Multiscale Dynamics: Ute Ebert.
Nature and technology are full of dynamics, often involving multiple scales in length, time and energy. To model these processes, we combine scientific computing with model reduction and machine learning, with particular focus on plasma dynamics in lightning and space weather, and in high voltage and plasma technology.
Our research addresses questions in nature such as start and propagation of lightning strokes, terrestrial gamma-ray flashes and space weather, and closely related technological problems such as switch gear for long-distance electricity nets, air purification and disinfection with corona reactors, and protection of satellites and electricity nets from space weather.
Within national and European projects, we collaborate with colleagues in applied plasma physics, electrical and mechanical engineering, atmospheric electricity, and cosmic particle and space science, and with non-academic partners such as ABB, DNV-GL, ESA-ESTEC and NASA.
Find more about our work (including publications) on the personal homepages of the staff scientists:
- Ute Ebert (group leader)
- Enrico Camporeale
- Jannis Teunissen (starting 1 October 2018)
and on the page with our numerical codes for Multiscale Plasma Dynamics.
View a photo of the Multiscale Dynamics group.
News
Faster computation times for numerical solutions
Shock waves are difficult to simulate on a computer. Due to the large, rapid changes, often oscillations occur in the mathematical solutions.
Members
Associated Members
Publications
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Diniz, G, Rutjes, C, Ebert, U. M, Ferreira, I.S, & São Sabbas, E.F.M.T. (2018). Modeling neutron emissions in high energy atmospheric phenomena. Journal of Geophysical Research: Atmospheres. doi:10.1029/2018JD028962
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Bagheri Varnousfaderani, B, Teunissen, H.J, Ebert, U. M, Becker, M.M, Chen, S, Ducasse, O, … Yousfi, M. (2018). Comparison of six simulation codes for positive streamers in air. Plasma Sources Science and Technology, 27(9). doi:10.1088/1361-6595/aad768
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Teunissen, H.J, & Ebert, U. M. (2018). Afivo: A framework for quadtree/octree AMR with shared-memory parallelization and geometric multigrid methods. Computer Physics Communications. doi:10.1016/j.cpc.2018.06.018
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Mascini, N.E, Teunissen, H.J, Noorlag, R, Willems, S.M, & Heeren, R.M.A. (2018). Tumor classification with MALDI-MSI data of tissue microarrays: A case study. Methods. doi:10.1016/j.ymeth.2018.04.004
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Camporeale, E, Sorriso-Valvo, L, Califano, F, & Retinò, A. (2018). Coherent structures and spectral energy transfer in turbulent plasma: A space-filter approach. Physical Review Letters, 120. doi:10.1103/PhysRevLett.120.125101
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Hare, B.M, Scholten, O, Bonardi, A, Buitink, S, Corstanje, A, Ebert, U. M, … Winchen, T. (2018). LOFAR lightning imaging: Mapping lightning with nanosecond precision. Journal of Geophysical Research - Atmospheres. doi:10.1002/2017JD028132
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Elkholy, A, Shoshyn, Y, Nijdam, S, van Oijen, J, van Veldhuizen, E.M, Ebert, U. M, & de Goey, L.P.H. (2018). Burning velocity measurement of lean methane-air flames in a new nanosecond DBD microplasma burner platform. Experimental Thermal and Fluid Science, 95, 18–26.
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The Computational Pan-Genomics Consortium, Marschall, T, Marz, M, Abeel, T, Dijkstra, L.J, Dutilh, B.E, … Schönhuth, A. (2018). Computational pan-genomics: status, promises and challenges. Briefings in Bioinformatics, 19(1), 118–135. doi:10.1093/bib/bbw089
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Rutjes, C, Diniz, G, Ferreira, I.S, & Ebert, U. M. (2017). TGF afterglows: A new radiation mechanism from thunderstorms. Geophysical Research Letters, 44(20), 10702–10712. doi:10.1002/2017GL075552
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Chandorkar, M.H, Camporeale, E, & Wing, S.P. (2017). Probabilistic forecasting of the disturbance storm time index: An autoregressive Gaussian process approach. Space Weather, 15. doi:10.1002/2017SW001627
Software
Afivo: A framework for adaptive mesh refinement with geometric multigrid methods
Afivo, short for Adaptive Finite Volume Octree, is a framework for adaptive mesh refinement on quadtree (2D) and octree (3D) meshes with shared memory parallelization (OpenMP) and geometric multigrid methods.
PumpKin: Analyzing complex chemistry models
PumpKin, short for Pathway Reduction Method for Plasma Kinetic Models, is a tool for post-processing results from zero-dimensional plasma kinetics solvers.
Current projects with external funding
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Real-time forecasting of killer electrons on satellite orbits
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Artificial Intelligence Data Analysis (AIDA)
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Let CO2 spark! Understand breakdown dynamics for high voltage technology and lightning Abstract Sparks, (Let CO2 spark!)
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Science and Innovation with Thunderstorms (SAINT)
Related partners
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CNRS
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CSIC
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IT-DTU Lyngby
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Universita di Pisa
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Universitetet i Bergen
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University of Bath
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Bristol Industrial and Research Associates Limited
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DENA DESARROLLOS SL
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Katholieke Universiteit Leuven
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Technische Universiteit Eindhoven
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Universidad Politecnica Catalunya
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Université Paul Sabatier (Toulouse III)