Benjamin Sanderse

Biography

Research

My research interest is to develop efficient methods for making predictions under uncertainty of physical systems by developing new methodologies that combine physical modelling approaches and data-driven techniques, in particular to applications involving fluid dynamic problems.

Currently the following two topics have my main interest:

• Uncertainty quantification: surrogate modelling for parametric PDEs, efficient solvers for Bayesian inverse problems, statistical learning for closure models, novel quadrature rules (with Laurent van den Bos, Yous van Halder).
• Computational fluid dynamics (CFD): time integration methods for differential-algebraic equations arising from fluid dynamic problems, such as incompressible single-phase and multi-phase Navier-Stokes equations.

Applications:

• Wind energy and in particular turbulent wind turbine wakes (EUROS project).
• Multi-phase flow in reservoirs, wells, and pipelines.
• Sloshing of liquids in tankers (SLING project).

Publications

• Sanderse, B, & Veldman, A.E.P. (2019). Constraint-consistent Runge–Kutta methods for one-dimensional incompressible multiphase flow.
• van den Bos, L.M.M, Sanderse, B, Blonk, L, Bierbooms, W.A.A.M, & Van Bussel, G.J.W. (2018). Efficient ultimate load estimation for offshore wind turbines using interpolating surrogate models. In Modeling and Simulation Technology. doi:10.1088/1742-6596/1037/6/062017
• Sanderse, B, Misra, S, Dubinkina, S, Henkes, R.A.W.M, & Oosterlee, C.W. (2018). Numerical simulation of roll waves in pipelines using the two-fluid model. In 11th North American Conference on Multiphase Technology (pp. 373–386).
• van Zwieten, J, Sanderse, B, Hendrix, M.H.W, Vuik, C, & Henkes, R.A.W.M. (2017). Efficient simulation of one-dimensional two-phase flow with a high-order h-adaptive space-time Discontinuous Galerkin method. Computers & Fluids, 156, 34–47. doi:10.1016/j.compfluid.2017.06.010
• Sanderse, B, Eskerud Smith, I, & Hendrix, M.H.W. (2017). Analysis of time integration methods for the compressible two-fluid model for pipe flow simulations. International Journal of Multiphase Flow, 95, 155–174. doi:10.1016/j.ijmultiphaseflow.2017.05.002
• Capuano, F, Sanderse, B, De Angelis, E.M, & Coppola, G. (2017). A minimum-dissipation time-integration strategy for large-eddy simulation of incompressible turbulent flows. In AIMETA 2017 Proceedings of the XXIII Conference of the Italian Association of Theoretical and Applied Mechanics (pp. 2311–2323). Retrieved from http://hdl.handle.net/11588/689710
• Capuano, F. (Francesco), Sanderse, B, De Angelis, E.M. (Enrico M.), & Coppola, G. (Gennaro). (2017). A minimum-dissipation time-integration strategy for large-eddy simulation of incompressible turbulent flows. In AIMETA 2017 - Proceedings of the 23rd Conference of the Italian Association of Theoretical and Applied Mechanics (pp. 2311–2323).
• Hendrix, M.H.W, Eskerud Smith, I, van Zwieten, J, & Sanderse, B. (2016). Comparison of numerical methods for slug capturing with the two-fluid model. In Proceedings of the 9th International Conference on Multiphase Flow.
• Sanderse, B, Haspels, M, & Henkes, R.A.W.M. (2015). Simulation of elongated bubbles in a channel using the two-fluid model. Journal of Dispersion Science and Technology, 36(10), 1407–1418. doi:10.1080/01932691.2014.989571
• Sanderse, B, Verstappen, R.W.C.P, & Koren, B. (2014). Boundary treatment for fourth-order staggered mesh discretizations of the incompressible Navier-Stokes equations. Journal of Computational Physics, 257(Part B), 1472–1505. doi:10.1016/j.jcp.2013.10.002

Current projects with external funding

• Excellence in Uncertainty Reduction of Offshore Wind Systems / Loads and Damage (EUROS)
• Sloshing of Liquefied Natural Gas: subproject Variability (14-10-project2) (SLING)
• WIND Turbine Rotor aeroelasticity UncErtainty quantification (WINDTRUE)

Awards

• Stieltjes prijs 2013 (2013)
• 5th PhD seminar on wind energy in Europe, Durham - Best paper 30 September - 1 October (2009)