Benjamin Sanderse

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Barry Korenprofessor scientific computing, Eindhoven University of TechnologyVerified email at tue.nl
R.A.W.M. HenkesProfessor Fluid Flow at Delft University of TechnologyVerified email at tiscali.nl
Gerard J.W. van BusselFull professor wind energy, TU Delft, NetherlandsVerified email at tudelft.nl
Yous van HalderPhD, CWI AmsterdamVerified email at cwi.nl
Roel VerstappenAssociate professor of Computational Mechanics and Numerical Mathematics, University of GroningenVerified email at rug.nl
Kees VuikDelft University of TechnologyVerified email at tudelft.nl
Marco CaboniECN part of TNOVerified email at tno.nl
Cornelis W. OosterleeUtrecht University, Mathematical InstituteVerified email at uu.nl
Svetlana DubinkinaAssistant professor, VU AmsterdamVerified email at vu.nl
A.E.P. VeldmanInstitute for Mathematics and Computer Science, University of GroningenVerified email at rug.nl
Edgar WeipplUniversity of Vienna, Head of SQI CD-Laboratory, SBA ResearchVerified email at univie.ac.at
Giovanni StabileSISSA - International School for Advanced StudiesVerified email at sissa.it
Gianluigi RozzaFull Professor of Numerical Analysis, SISSA, Int. School for Adv. Studies, Italy and ERC PIVerified email at sissa.it
Joris DegrooteGhent UniversityVerified email at ugent.be
Francesco CapuanoUniversità di Napoli Federico IIVerified email at unina.it
G J F van HeijsteindhovenVerified email at tue.nl
Gennaro CoppolaUniversità di Napoli 'Federico II'Verified email at unina.it
Wim-Paul BreugemAssociate professor at Delft University of Technology (TU Delft)Verified email at tudelft.nl
Kelbij StarPhD student at University of GhentVerified email at UGent.be
Luc E. CoffengAssistant Professor, Erasmus MC University Medical Center Rotterdam, Rotterdam, The NetherlandsVerified email at erasmusmc.nl

Benjamin Sanderse

Centrum Wiskunde & Informatica,

Verified email at cwi.nl - Homepage

numerical mathematics incompressible flow multiphase flow Runge-Kutta methods uncertainty quantification


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Review of computational fluid dynamics for wind turbine wake aerodynamics B Sanderse, SP Pijl, B Koren Wind Energy 14 (7), 799-819, 2011	540	2011
Aerodynamics of wind turbine wakes B Sanderse Energy research Centre of the Netherlands, ECN-E-09-016, 2009	312*	2009
Accuracy analysis of explicit Runge–Kutta methods applied to the incompressible Navier–Stokes equations B Sanderse, B Koren Journal of Computational Physics 231 (8), 3041-3063, 2012	86	2012
Energy-conserving Runge-Kutta methods for the incompressible Navier-Stokes equations B Sanderse Journal of Computational Physics 233, 100-131, 2013	67	2013
Boundary treatment for fourth-order staggered mesh discretizations of the incompressible Navier–Stokes equations B Sanderse, R Verstappen, B Koren Journal of Computational Physics 257, 1472-1505, 2014	11	2014
Energy-Conserving Navier-Stokes Solver. Verification of steady laminar flows B Sanderse Energy research Centre of the Netherlands, ECN-E-11-042, 2011	9	2011
Bayesian model calibration with interpolating polynomials based on adaptively weighted Leja nodes LMM van den Bos, B Sanderse, W Bierbooms, GJW van Bussel arXiv preprint arXiv:1802.02035, 2018	8	2018
Analysis of time integration methods for the compressible two-fluid model for pipe flow simulations B Sanderse, IE Smith, MHW Hendrix International Journal of Multiphase Flow 95, 155-174, 2017	8	2017
Simulation of Elongated Bubbles in a Channel Using the Two-Fluid Model B Sanderse, M Haspels, R Henkes Journal of Dispersion Science and Technology 36 (10), 1407-1418, 2015	6	2015
Numerical simulation of roll waves in pipelines using the two-fluid model B Sanderse, S Misra, S Dubinkina, R Henkes, CW Oosterlee 11th North American Conference on Multiphase Production Technology, 2018	5	2018
Energy-conserving discretization methods for the incompressible Navier-Stokes equations: application to the simulation of wind-turbine wakes B Sanderse Technische Universiteit Eindhoven, 2013	5	2013
Generating nested quadrature rules with positive weights based on arbitrary sample sets L van den Bos, B Sanderse, W Bierbooms, G van Bussel SIAM/ASA Journal on Uncertainty Quantification 8 (1), 139-169, 2020	4	2020
An Adaptive Minimum Spanning Tree Multielement Method for Uncertainty Quantification of Smooth and Discontinuous Responses YV Halder, B Sanderse, B Koren SIAM Journal on Scientific Computing 41 (6), A3624-A3648, 2019	4	2019
Constraint-consistent Runge–Kutta methods for one-dimensional incompressible multiphase flow B Sanderse, AEP Veldman Journal of Computational Physics 384, 170-199, 2019	4	2019
Digital Twins Introduction E Weippl, B Sanderse ERCIM NEWS, 6-7, 2018	4	2018
Non-linearly stable reduced-order models for incompressible flow with energy-conserving finite volume methods B Sanderse Journal of Computational Physics 421, 109736, 2020	3	2020
Adaptive sampling-based quadrature rules for efficient Bayesian prediction LMM van den Bos, B Sanderse, W Bierbooms Journal of Computational Physics 417, 109537, 2020	3	2020
Efficient simulation of one-dimensional two-phase flow with a new high-order Discontinuous Galerkin method JSB Van Zwieten, B Sanderse, MHV Hendrix, C Vuik, R Henkes Reports of the Delft Institute of Applied Mathematics, 15-07, 2015	3	2015
Cartesian grid methods for preliminary aircraft design B Sanderse TU Delft, Delft, Netherlands, 2008	3	2008
Machine Learning for Closure Models in Multiphase Flow Applications J Buist, B Sanderse, Y van Halder, B Koren, G van Heijst 3rd International Conference on Uncertainty Quantification in Computational …, 2019	2	2019

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