Description
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
and on the page with our numerical codes for Multiscale Plasma Dynamics.
View a photo of the Multiscale Dynamics group in January 2020 and in January 2018.
Vacancies
No vacancies currently.
News
AIDA: Exploring space with Artificial Intelligence
The EU H2020 project 'AIDA' on using artificial intelligence in space physics was signed in May. The Multiscale Dynamics Group at CWI is one of the eight research partners involved. The ultimate goal is to create an intelligent system that enables new scientific discoveries in space.
CWI researchers simulate how ‘coherent structures’ affect solar wind heating
CWI researchers have further developed our understanding of how solar wind particles get accelerated and heated. In particular, they discovered how ‘coherent structures’ in the solar wind, places where the magnetic fields and electrical currents are enhanced, affect the energy transfer responsible for heating. The results were published in Physical Review Letters on 19 March 2018.
Better simulations for lightning and high-voltage technology
Until recently, it was not clear how lightning could start. CWI PhD student Casper Rutjes modelled and simulated the origin of lightning and ionizing radiation from storm clouds and explained the physics of these phenomena. On 15 March he defended his PhD thesis. His results are important for lightning research, high-voltage technology and nuclear medicine models.
Radio telescope LOFAR shows how lightning grows
Dutch radio telescope LOFAR can observe the creation of lightning flashes at an unprecedented one-metre resolution, which may lead to better lightning protection. The results were published by an international scientific team with RUG, ASTRON, CWI, RU and VUB on 16 February 2018 in the Journal of Geophysical Research: Atmospheres.
Current events
PhD Defense Andy Martinez (Multiscale Dynamics)
- 2022-02-18T13:30:00+01:00
- 2022-02-18T14:30:00+01:00
PhD Defense Andy Martinez (Multiscale Dynamics)
Start: 2022-02-18 13:30:00+01:00 End: 2022-02-18 14:30:00+01:00
Everyone is invited to attend the public defense of Andy Martinez of his PhD thesis:
Computational Investigations of Streamers: From Input Cross Sections to Evolution of Plasma Species
Promotor: prof.dr. Ute Ebert (CWI / TU/e)
Co-promotor: prof.dr. Sander Nijdam (TU/e)
Co-promotor: dr. Jannis Teunissen (CWI)
- Email: Andy Martinez
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iCal
Members
Associated Members
Publications
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Li, X, Dijcks, S, Nijdam, S, Sun, A.B, Ebert, U, & Teunissen, H.J. (2021). Comparing simulations and experiments of positive streamers in air: Steps toward model validation. Plasma Sources Science and Technology, 30. doi:10.1088/1361-6595/ac1b36
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Bouwman, D.D, Martinez, A, Braams, B.J, & Ebert, U. (2021). Neutral dissociation of methane by electron impact and a complete and consistent cross section set. Plasma Sources Science and Technology, 30(7). doi:10.1088/1361-6595/ac0b2b
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Abbas, M.F, Sun, G.Y, Yuan, X.C, Li, X, Zhang, X, Sun, A.B, & Zhang, G.J. (2021). The influence of O2 on positive streamer initiation in supercritical CO2 with field ionization using a 3-D particle model. IEEE Transactions on Plasma Science, 49(6), 1786–1793. doi:10.1109/TPS.2021.3080038
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Li, W, Zhao, D, He, C, Shen, Y, Hu, A, & Zhang, K. (2021). Application of a multi-layer artificial neural network in a 3-D global electron density model using the long-term observations of COSMIC, Fengyun-3C, and Digisonde. Space Weather, 19(3). doi:10.1029/2020SW002605
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Hu, A, Sisti, M, Finelli, F, Califano, F, Dargent, J, Faganello, M, … Teunissen, H.J. (2020). Identifying magnetic reconnection in 2D Hybrid Vlasov Maxwell simulations with Convolutional Neural Networks. Astrophysical Journal, 900(1). doi:10.3847/1538-4357/aba527
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Wang, L, He, C, Hu, A, Zhao, D, Shen, Y, & Zhang, K. (2020). A new method for improving the performance of an ionospheric model developed by multi-instrument measurements based on artificial neural network. Advances in Space Research. doi:10.1016/j.asr.2020.07.032
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Li, X, Sun, A.B, & Teunissen, H.J. (2020). A computational study of negative surface discharges: Characteristics of surface streamers and surface charges. IEEE Transactions on Dielectrics and Electrical Insulation, 27(4), 1178–1186. doi:10.1109/TDEI.2020.008880
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Li, X, Sun, A.B, Zhang, G.J, & Teunissen, H.J. (2020). A computational study of positive streamers interacting with dielectrics. Plasma Sources Science and Technology, 29(6). doi:10.1088/1361-6595/ab8f75
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Chandorkar, M.H, Camporeale, E, Furtlehner, C, Poduval, B, & Sebag, M. (2020). Dynamic Time-Lag Regression: Predicting what & when. In Eighth International Conference on Learning Representations.
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Trinh, T.N.G, Scholten, O, Buitink, S, Ebert, U, Hare, B.M, Krehbiel, P.R, … Winchen, T. (2020). Determining electric fields in thunderclouds with the radiotelescope LOFAR. Journal of Geophysical Research: Atmospheres, 125(8). doi:10.1029/2019JD031433
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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Making plasma-assisted combustion efficient ()
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Artificial Intelligence Data Analysis (AIDA)
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European Science Cluster of Astronomy & Particle physics ESFRI research infrastructures (ESCAPE)
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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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Plasma for Plants: Towards controlled and efficient plasma-activated water generation for a cleaner environment (Plasma for Plants)
Related partners
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CNRS
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Universita di Pisa
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Katholieke Universiteit Leuven
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Technische Universiteit Eindhoven