Description
Leader of the group Scientific Computing: Daan Crommelin.
The SC groups develops efficient mathematical methods to simulate and predict real-world phenomena with inherent uncertainties. Such uncertainties arise from e.g. uncertain model parameters, chaotic dynamics or intrinsic randomness, and can have major impact on model outputs and predictions. Our work is targeted in particular at applications in climate, energy, finance and biology. In these vital areas, the ability to assess uncertainties and their impact on model predictions is of paramount importance. Expertise in the SC group includes uncertainty quantification, data assimilation, stochastic multiscale modeling and risk assessment. The availability of data to inform and improve simulations and predictions, for example through learning and data-driven modeling, plays an important role in our research.
News
Stieltjes Prize 2013 for Benjamin Sanderse
Benjamin Sanderse, former PhD Student of CWI, has been awarded the Stieltjes Prize 2013, the prize for the best PhD thesis in mathematics in the Netherlands in 2013. In March 2013 Sanderse defended his thesis 'Energy-conserving discretization methods for the incompressible Navier-Stokes equations' at Eindhoven University of Technology under the supervision of Prof. dr. ir. Barry Koren.
CWI and ExxonMobil Chemical start research on imaging of nanomaterials
Researchers from CWI and ExxonMobil Chemical Europe Inc. in Machelen (Belgium) are starting a joint research program on three-dimensional imaging of nanomaterials.
Five Veni grants for CWI researchers
The Netherlands Organisation for Scientific Research (NWO) has awarded Veni grants to Jop Briët, Jiyin He, Wouter Koolen, Marc Stevens and Xiaodong Zhuge of CWI.
Daan Crommelin professor of Numerical Analysis and Dynamical Systems
Daan Crommelin has been appointed as professor by special appointment of Numerical Analysis and Dynamical Systems at the University of Amsterdam's (UvA) Faculty of Science. The chair was established on behalf of the Stichting voor Hoger Onderwijs in de Toegepaste Wiskunde.
Members
Associated Members
Publications
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van der Stoep, A.W. (2019, March 26). Pricing and calibration with stochastic local volatility models in a Monte Carlo setting.
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Bisewski, K.L, Crommelin, D.T, & Mandjes, M.R.H. (2018). Simulation-based assessment of the stationary tail distribution of a stochastic differential equation. In Proceedings of the 2018 Winter Simulation Conference.
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Suárez-Taboada, M, Witteveen, J.A.S, Grzelak, L.A, & Oosterlee, C.W. (2018). Uncertainty quantification and Heston model. Journal of Mathematics in Industry, 8(1). doi:10.1186/s13362-018-0047-2
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Jüling, A, Viebahn, J.P, Drijfhout, S.S, & Dijkstra, H.A. (2018). Energetics of the Southern Ocean Mode. Journal of Geophysical Research: Oceans. doi:10.1029/2018JC014191
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Viebahn, J.P, Crommelin, D.T, & Dijkstra, H.A. (2018). Towards a turbulence closure based on energy modes. Journal of Physical Oceanography. doi:10.1175/JPO-D-18-0117.1
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Rodrigo, C, Hu, X, Ohm, P, Adler, J.H, Gaspar, F.J, & Zikatanov, L.T. (2018). New stabilized discretizations for poroelasticity and the Stokes’ equations. Computer Methods in Applied Mechanics and Engineering, 341, 467–484. doi:10.1016/j.cma.2018.07.003
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Jansson, F.R, van den Oord, G, Siebesma, A.P, & Crommelin, D.T. (2018). Resolving clouds in a global atmosphere model - a multiscale approach with nested models. In Proceedings - IEEE 14th International Conference on eScience, e-Science 2018. doi:10.1109/eScience.2018.00043
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Kumar, P, Luo, P, Gaspar, F.J, & Oosterlee, C.W. (2018). A multigrid multilevel Monte Carlo method for transport in the Darcy–Stokes system. Journal of Computational Physics, 371, 382–408. doi:10.1016/j.jcp.2018.05.046
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Eggels, A.W, & Crommelin, D.T. (2018). UQ with dependent inputs: Wind and waves. In Proceedings of ECCM 6 and ECFD 7.
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Bisewski, K.L, Crommelin, D.T, & Mandjes, M.R.H. (2018). Controlling the time discretization bias for the supremum of Brownian Motion. ACM Transactions on Modeling and Computer Simulation, 28(3). doi:10.1145/3177775
Current projects with external funding
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Accurate prediction of slugs in multiphase pipe flow simulation for improved oil and gas production
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Towards cloud-resolving climate simulations
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Valuation Adjustments for Improved Risk Management (ABC-EU-XVA)
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Physics based ICT: The digital twin in pipelines (DP-Trans)
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Excellence in Uncertainty Reduction of Offshore Wind Systems (EUROS)
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Rare Event Simulation for Climate Extremes (RESClim)
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Sloshing of Liquefied Natural Gas: subproject Variability (14-10-project2) (SLING)
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Verified Exascale Computing for Multiscale Applications (VECMA)
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WIND Turbine Rotor aeroelasticity UncErtainty quantification (WINDTRUE)
Related partners
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DNV GL Netherlands B.V
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FOM
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Max Planck Institute for Informatics
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Shell, Amsterdam
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Bull Sas
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CBK Sci Con Ltd
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Bayerische Akademie der Wissenschaften
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MeitY
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Instytut Chemii Bioorganicznej Polskiej Akademii Nauk
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Rijksuniversiteit Groningen
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Suzlon Blades Technology
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TNO
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Technische Universiteit Eindhoven
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Technische Universiteit Delft
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Brunel University London
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University College London
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Universiteit van Amsterdam