Benjamin Sanderse

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 36

Top Topics

Adaptive Sampling

Top Venues

J. Comput. Phys.

Comput. Math. Appl.

Publications

Syver Døving Agdestein, Benjamin Sanderse
Discretize first, filter next: learning divergence-consistent closure models for large-eddy simulation. CoRR (2024)
Benjamin Sanderse, Panos Stinis, Romit Maulik, Shady E. Ahmed
Scientific machine learning for closure models in multiscale problems: a review. CoRR (2024)
Robin Klein, Benjamin Sanderse, Pedro Costa, Rene Pecnik, Ruud Henkes
Entropy-Stable Model Reduction of One-Dimensional Hyperbolic Systems using Rational Quadratic Manifolds. CoRR (2024)
Toby van Gastelen, Wouter Edeling, Benjamin Sanderse
Energy-conserving neural network for turbulence closure modeling. J. Comput. Phys. 508 (2024)
R. B. Klein, Benjamin Sanderse
Energy-conserving hyper-reduction and temporal localization for reduced order models of the incompressible Navier-Stokes equations. J. Comput. Phys. 499 (2024)
Krishan Chand, Henrik K. E. Rosenberger, Benjamin Sanderse
A pressure-free long-time stable reduced-order model for two-dimensional Rayleigh-Bénard convection. CoRR (2023)
Nikolaj Takata Mücke, Benjamin Sanderse, Sander M. Bohté, Cornelis W. Oosterlee
Markov chain generative adversarial neural networks for solving Bayesian inverse problems in physics applications. Comput. Math. Appl. 147 (2023)
Toby van Gastelen, Wouter Edeling, Benjamin Sanderse
Energy-Conserving Neural Network for Turbulence Closure Modeling. CoRR (2023)
Hugo Melchers, Daan Crommelin, Barry Koren, Vlado Menkovski, Benjamin Sanderse
Comparison of neural closure models for discretised PDEs. Comput. Math. Appl. 143 (2023)
J. F. H. Buist, Benjamin Sanderse, S. Dubinkina, Cornelis W. Oosterlee, R. A. W. M. Henkes
Energy-stable discretization of the one-dimensional two-fluid model. CoRR (2023)
Benjamin Sanderse, Francesc Xavier Trias
Energy-consistent discretization of viscous dissipation with application to natural convection flow. CoRR (2023)
Henrik K. E. Rosenberger, Benjamin Sanderse
No pressure? Energy-consistent ROMs for the incompressible Navier-Stokes equations with time-dependent boundary conditions. J. Comput. Phys. 491 (2023)
Henrik K. E. Rosenberger, Benjamin Sanderse
Momentum-conserving ROMs for the incompressible Navier-Stokes equations. CoRR (2022)
Maarten J. van den Broek, Daniel van den Berg, Benjamin Sanderse, Jan-Willem van Wingerden
Optimal Control for Wind Turbine Wake Mixing on Floating Platforms. CoRR (2022)
Maarten J. van den Broek, Delphine De Tavernier, Benjamin Sanderse, Jan-Willem van Wingerden
Adjoint Optimisation for Wind Farm Flow Control with a Free-Vortex Wake Model. CoRR (2022)
Henrik K. E. Rosenberger, Benjamin Sanderse
No pressure? Energy-consistent ROMs for the incompressible Navier-Stokes equations with time-dependent boundary conditions. CoRR (2022)
Hugo Melchers, Daan Crommelin, Barry Koren, Vlado Menkovski, Benjamin Sanderse
Comparison of neural closure models for discretised PDEs. CoRR (2022)
Syver Døving Agdestein, Benjamin Sanderse
Learning filtered discretization operators: non-intrusive versus intrusive approaches. CoRR (2022)
Benjamin Sanderse, J. F. H. Buist, R. A. W. M. Henkes
A novel pressure-free two-fluid model for one-dimensional incompressible multiphase flow. J. Comput. Phys. 426 (2021)
Federica Gugole, Luc E. Coffeng, Wouter Edeling, Benjamin Sanderse, Sake J. De Vlas, Daan Crommelin
Uncertainty quantification and sensitivity analysis of COVID-19 exit strategies in an individual-based transmission model. PLoS Comput. Biol. 17 (9) (2021)
J. F. H. Buist, Benjamin Sanderse, S. Dubinkina, R. A. W. M. Henkes, C. W. Oosterlee
Energy-conserving formulation of the two-fluid model for incompressible two-phase flow in channels and pipes. CoRR (2021)
Laurent M. M. van den Bos, Benjamin Sanderse
A geometrical interpretation of the addition of nodes to an interpolatory quadrature rule while preserving positive weights. J. Comput. Appl. Math. 391 (2021)
Nikolaj Takata Mücke, Benjamin Sanderse, Sander M. Bohté, Cornelis W. Oosterlee
Markov Chain Generative Adversarial Neural Networks for Solving Bayesian Inverse Problems in Physics Applications. CoRR (2021)
Yous van Halder, Benjamin Sanderse
Faster Flow Predictions with Intrusive Neural Networks. ERCIM News 2020 (122) (2020)
Benjamin Sanderse, J. F. H. Buist, R. A. W. M. Henkes
A novel pressure-free two-fluid model for one-dimensional incompressible multiphase flow. CoRR (2020)
Laurent M. M. van den Bos, Benjamin Sanderse, Wim Bierbooms, Gerard J. W. van Bussel
Generating Nested Quadrature Rules with Positive Weights based on Arbitrary Sample Sets. SIAM/ASA J. Uncertain. Quantification 8 (1) (2020)
Laurent M. M. van den Bos, Benjamin Sanderse, W. A. A. M. Bierbooms
Adaptive sampling-based quadrature rules for efficient Bayesian prediction. J. Comput. Phys. 417 (2020)
Yous van Halder, Benjamin Sanderse, Barry Koren
Multi-level neural networks for PDEs with uncertain parameters. CoRR (2020)
Benjamin Sanderse
Non-linearly stable reduced-order models for incompressible flow with energy-conserving finite volume methods. J. Comput. Phys. 421 (2020)
Yous van Halder, Benjamin Sanderse, Barry Koren
PDE/PDF-informed adaptive sampling for efficient non-intrusive surrogate modelling. CoRR (2019)
Yous van Halder, Benjamin Sanderse, Barry Koren
An Adaptive Minimum Spanning Tree Multielement Method for Uncertainty Quantification of Smooth and Discontinuous Responses. SIAM J. Sci. Comput. 41 (6) (2019)
Laurent M. M. van den Bos, Benjamin Sanderse, W. A. A. M. Bierbooms
Adaptive sampling-based quadrature rules for efficient Bayesian prediction. CoRR (2019)
Benjamin Sanderse, Arthur E. P. Veldman
Constraint-consistent Runge-Kutta methods for one-dimensional incompressible multiphase flow. J. Comput. Phys. 384 (2019)
Benjamin Sanderse
Non-linearly stable reduced-order models for incompressible flow with energy-conserving finite volume methods. CoRR (2019)
Laurent M. M. van den Bos, Wim Bierbooms, Armando Alexandre, Benjamin Sanderse, Gerard J. W. van Bussel
Fatigue design load calculations of the offshore NREL 5MW benchmark turbine using quadrature rule techniques. CoRR (2019)
Edgar R. Weippl, Benjamin Sanderse
Digital Twins - Introduction to the Special Theme. ERCIM News 2018 (115) (2018)
Benjamin Sanderse, R. W. C. P. Verstappen, Barry Koren
Boundary treatment for fourth-order staggered mesh discretizations of the incompressible Navier-Stokes equations. J. Comput. Phys. 257 (2014)
Benjamin Sanderse
Energy-conserving Runge-Kutta methods for the incompressible Navier-Stokes equations. J. Comput. Phys. 233 (2013)
Benjamin Sanderse, Barry Koren
Accuracy analysis of explicit Runge-Kutta methods applied to the incompressible Navier-Stokes equations. J. Comput. Phys. 231 (8) (2012)