Description

Leader of the group Scientific Computing: Daan Crommelin.

The world is full of uncertainties. Being able to assess those uncertainties and their impact on predictions is critical for many real-world problems. Our research group works to investigate and develop methods that contribute to a better understanding of hard-to-predict developments in vital areas such as climate, energy, and finance. It’s all about finding efficient mathematical solutions for complex problems and thereby increasing understanding. With the computational methods we develop, it is possible to quantify the range of potential outcomes of systems that are extremely difficult to predict, enabling better forecasting. Our work is targeted in particular at applications in energy systems, finance and climate science. We always aim to make the connection between fundamental research and practical application.

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Current projects with external funding

  • Accurate prediction of slugs in multiphase pipe flow simulation for improved oil and gas production
  • Geometric Structure and Data Assimilation
  • Probabilistic Uncertainty Assessments in Energy-Related Problems
  • Realibilty and Robustness of Power Grids with Uncertain Generation
  • Stochastic models for unresolved scales in geophysical flows
  • Towards cloud-resolving climate simulations
  • Uncertainty Quantication in Hydraulic Fracturing using Multi-Level Monte Carlo and Multigrid
  • Excellence in Uncertainty Reduction of Offshore Wind Systems (EUROS)
  • Efficient numerical methods for deformable porous media. Application to carbon dioxide storage (PORO SOS)
  • Rare Event Simulation for Climate Extremes (RESClim)
  • Sloshing of Liquefied Natural Gas: subproject Variability (14-10-project2) (SLING)
  • Applied mathematics for risk measures in finance and insurance, in the wake of the crisis (WAKEUPCALL)

Related partners

  • FOM
  • Shell, Amsterdam
  • Vortech
  • Rijksuniversiteit Groningen
  • Technische Universiteit Eindhoven
  • Technische Universiteit Delft