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Kristoffer van der Zee

Professor of Numerical Analysis & Computational Applied Mathematics, Director of Automation Innovation, Faculty of Science

Personal Details
Publications

Contact

workRoom C42 Mathematical Sciences Building
University Park
Nottingham
NG7 2RD
UK
work0115 8467914
KG.vanderZee@nottingham.ac.uk

Biography

Full Professor of Numerical Analysis & Computational Applied Mathematics, School of Mathematical Sciences, University of Nottingham (since Aug 2023)
Director of Automation Innovation, School of Mathematical Sciences, University of Nottingham (since Aug 2023)
Interim PGR Student Advisor, School of Mathematical Sciences, University of Nottingham (since Aug 2023)
Director of PGR Studies, School of Mathematical Sciences, University of Nottingham (Aug 2020-2023)
Associate Professor of Scientific Computation, School of Mathematical Sciences, University of Nottingham (Aug 2020 - Aug 2023)
Editor, Engineering with Computers, since Oct 2023 (Associate Editor, Sep 2021 - Sep 2023).
Associate Fellow of the Higher Education Academy (AFHEA) (since 2018).
Nottingham SIAM-IMA Student Chapter Faculty Advisor, inaugural (Nov 2017 - Aug 2020)
Royal Society Kan Tong Po International Exchange Fellow, City University of Hong Kong (Nov 2015 - Jan 2016)
School PGR Student Advisor, School of Mathematical Sciences, University of Nottingham (Aug 2015 - Aug 2020)
Nottingham Node Representative MAGIC (Mathematics Access Grid: Instruction and Collaboration) (Aug 2015 - Aug 2020)
Lecturer (Assistant Prof) of Scientific Computation, School of Mathematical Sciences, University of Nottingham (Oct 2013 - Aug 2020)

Other biography

Feb 2011 - Oct 2013 :: Assistant Professor (NWO Veni Early Career Fellow), Multiscale Engineering Fluid Dynamics, Dept Mathematics & Computer Science and Mechanical Engineering, Eindhoven University of Technology
July 2009 - Jan 2011 :: Postdoctoral Researcher, Multiscale Modeling Group, Institute for Computational Engineering and Sciences, The University of Texas at Austin
June 2009 :: PhD Degree, Delft University of Technology (PhD Thesis: -Link1- Goal-Adaptive Discretization of Fluid-Structure Interaction)
Oct 2004 :: MSc Degree, Aerospace Engineering, Delft University of Technology (MSc Thesis: An H¹(P^h)-Coercive Discontinuous Galerkin Formulation for The Poisson Problem: 1-D Analysis)

Research Summary

Numerical analysis, scientific computation, and computational PDEs;
Neural networks and machine-learning for scientific computation;
Optimal discretisation theory, minimal residual (MRes) and Petrov-Galerkin methods;
Foundations of error estimation and optimality of adaptive FEM;
Reduced-order, multi-scale, and adaptive modelling;
Uncertainty quantification, validation and optimal Bayesian experimental design;
Evolving-interface phenomena, free- and moving-boundary problems;
Multiphase flows and materials, and phase-field/diffuse-interface models;
Applications to fluid dynamics, mechanobiology and engineering mechanics.

Member of School of Mathematical Sciences' Research Themes and Centres

Research Theme Computational Statistics and Machine Learning
Research Theme Data-driven Modelling and Computation
Research Theme Fluid Mechanics
Research Theme Multiscale Modelling and Heterogeneous Media
Research Theme Numerical and Applied Analysis
Research Theme Wave Modelling
Centre for Mathematical Medicine and Biology

Some recent talks

Neural Networks for PDEs: Quasi-optimal convergence of quasi-minimizing neural networks, Marie Skłodowska-Curie Doctoral Network "IN-DEEP", Consortium Meeting, Bilbao (2024)
Total Variation (TV)-regularized LSQ/MinRes for 1st-order PDEs, Workshop MinRes/LS FEM, BCAM, Bilbao (2024)
Unification of Navier-Stokes Cahn-Hilliard models with non-matching densities, Workshop, MathGeo: Phase-Field Models for Geoenergy Applications (2022)
Computational Phase-Field Modelling, UKACM 2022 School, UK Association for Computational Mechanics (2022)
Minimal Residual (MinRes) Finite Element Methods in Banach Spaces, Australian Seminar Series on Computational Mathematics (2021)
Quasi-incompressible Navier-Stokes-Cahn-Hilliard systems: Thermodynamic consistency and stable schemes, Workshop, Phase 2019: Engineering to Biology, University of Pavia (2019)

Organiser

15-19 May 2023: LMS Research School Adaptive Methods and Model Reduction for PDEs (http://www.tinyurl.com/wuwmc2kp)
29 June 2022: Seminar Numerical & Applied Analysis, speaker Prof Ignacio Muga (Pontificia Universidad Católica de Valparaíso, Chile), supported by LMS Scheme 2 grant
20-22 April 2022: Conference UKACM 2022, https://www.ukacm2022.ukacm.org/
25-26 April 2019: Workshop, Scientific computation using machine-learning algorithms: Recent mathematical advances and applications

Postgraduate Projects

In-Deep (2024), Real-time inversion using self-explainable deep learning driven by expert knowledge, European Commision, MSCA Doctoral Network, PhD Vacancies: https://www.in-deep.science/job-offers
Please contact me if you're interested in pursuing a postgraduate degree in one of the above research topics! Also have a look at our School's Postgraduate Projects, Online Application Details and Funding Details.

Postdoctoral opportunities (general UK fellowships)

Teaching Summary

2024-2025

MAGIC098 - Adaptive Finite Element Methods (autumn semester) (Link to MAGIC website)
MATH3036 - Scientific Computation and Numerical Analysis (spring semester) (Link to Catalogue)
MATH31xx - PDE Modelling and Applied Analysis (development)

2023-2024

MATH2019 - Introduction to Scientific Computation (autumn semester) (Link to Catalogue)
MAGIC098 - Adaptive Finite Element Methods (autumn semester) (Link to MAGIC website)
MATH3036 - Scientific Computation and Numerical Analysis (spring semester) (Link to Catalogue)

2022-2023

MATH2019 - Introduction to Scientific Computation (autumn semester) (Link to Catalogue)
MAGIC098 - Adaptive Finite Element Methods (autumn semester) (Link to MAGIC website)
MATH3036 - Scientific Computation and Numerical Analysis (spring semester) (Link to Catalogue)

2021-2022

MATH2019 (G12ISC) - Introduction to Scientific Computation (autumn semester) (Link to Catalogue)
MATH3036 - Scientific Computation and Numerical Analysis (development)

2020-2021

MATH2019 (G12ISC) - Introduction to Scientific Computation (autumn semester) (Link to Catalogue)
MATH4064 (G14CAM) - Computational Applied Mathematics (Link to Catalogue)

2019-2020

MATH2019 (G12ISC) - Introduction to Scientific Computation (autumn semester) (Link to Catalogue)
MATH4064 (G14CAM) - Computational Applied Mathematics (Link to Catalogue)

2018-2019

MATH2019 (G12ISC) - Introduction to Scientific Computation (autumn semester) (Link to Catalogue)

2017-2018

G12ISC - Introduction to Scientific Computation (spring semester) (Link to Catalogue)
G14CAM - Computational Applied Mathematics (Link to Catalogue)

2016-2017

G12ISC - Introduction to Scientific Computation (spring semester) (Link to Catalogue)
G14CAM - Computational Applied Mathematics (Link to Catalogue)
Advanced Discretization: Theory, Applications and Numerical Implementation (part of Doctoral School in Mathematics, Valparaiso, Chile)

2015-2016

G12INM / HG2INM - Introduction to Numerical Methods (spring semester) (Link to Catalogue)
G14CAM - Computational Applied Mathematics (Link to Catalogue)

2014-2015

G12INM / HG2INM - Introduction to Numerical Methods (spring semester) (Link to Catalogue and Moodle)
HG4MPD (UK) - Mathematical Techniques in PDEs for Engineers (Link to Catalogue and Moodle)

2013-2014

HG4MPD (UK) - Mathematical Techniques in PDEs for Engineers (Link to Catalogue and Moodle)
Introduction to Phase-Field Modeling (part of EM school short-course on Adv. Topics Solid Mech.)

2012-2013

Interfaces and Free Boundaries: Modeling and Computation (Notes contents; TU/e MSc class)
Advanced Discretization Techniques (Notes contents; TU/e MSc class)
Goal-Oriented Methods: Error Estimation, Adaptive Algorithms, Multiscale Modeling (USACM short course)

2011-2012

Advanced Discretization Techniques (Notes contents; TU/e MSc class)
Fundamentals of Fluid-Structure Interaction (TU/e MSc class)
Shape Calculus (part of ECCAM school short-course on Isogeometric Analysis)
Introduction to Phase-Field Modeling (part of EM school short-course on Adv. Topics Solid Mech.)

2010, 2011

Goal-Oriented Methods: Error Estimation, Adaptive Algorithms, Multiscale Modeling (USACM short course)
Introduction to Phase-Field Modeling and the Cahn-Hilliard Equation (part of EM school short-course on Adv. Topics Solid Mech.)

Supervision

Emin Benny Chacko, Topic: Deep Learning for PDEs, Marie-Curie Network (in-deep.science) PhD project 2024-2027
Jingce Tao, Topic: Fluid Surfactant PDEs, PhD project 2024-2027
Ignacio Brevis (Postdoc), Topic: Scientific Machine Learning for membrane manufacturing, 2022-2025
Tanakorn Udomworarat, Topic: Scientific Machine Learning for wave modelling, PhD project 2022-2026
Sattam Alrashidy, Topic: Optimisation, control and estimation for nonlinear PDEs with applications in Fluid Mechanics, PhD project 2021-2024
Hamd Alsobhi, Topic: Optimisation algorithms for Minimal-Residual FEM, PhD project 2020-2023
Xuesi (Rose) Yang, Zhengyuan (Cassie) Zhang, Yu (Summer) Qi, Zeqi (Elain) Wang, Geometric Modelling of Human Bodies, UG Summer 2020
Anne Boschman, Topic: Bulk-surface phase-field modelling, PhD project 2019-2023
Isil Akpinar (Postdoc), Topic: Machine Learning for Membrane Manufacturing, 2019-2021
Fran Rourke (2nd supervisor), Topic: Adaptive FEM, PhD project 2019-2023
Yiyun Fan (2nd supervisor), Topic: Two-fluid flow asymptotics, PhD project 2019-2022
Toby Willis (with Matteo Icardi), Diffuse-domain approximations for porous media flow, UG Summer 2019, Nottingham
Matthew Tyler (with Donald Brown), Advanced discontinuous discretisation techniques for multiscale PDEs, Summer 2018 (LMS Undergraduate Bursary), Nottingham
Sarah Roggendorf, Topic: Adaptive FEM for nonlinear PDEs, PhD project 2016-2019, University of Nottingham
Yuchen Yang (2nd supervisor), Topic: Bayesian inference for PDEs, PhD project 2015-2018, University of Nottingham (VC Scholarship for Research Excellence)
Chris Miles, Topic: Solar-cell computational phase-field modelling, PhD project 2015-2019, University of Nottingham
Holly Smith (2nd supervisor), Topic: Tumour pattern formation, PhD project 2015-2018, University of Nottingham
Lee Curtin (2nd supervisor), Topic: Mathematical modelling of brain tumour growth and therapy, 30 April 2019, University of Nottingham
Xunxun Wu, Space-time adaptive methods for phase-field models, 28 June 2017, Eindhoven University of Technology
Gorkem Simsek, Numerical methods for diffuse interface models of binary flows, 21 June 2017, Eindhoven University of Technology
Benjamin Dominguez, Modelling error estimation for granular solids, MSc thesis 2015, University of Nottingham
James Malone, Truncation-induced error estimation for the Black-Scholes model, MSc thesis 2015, University of Nottingham
Ian Roper, Partitioned-domain concurrent multiscale modelling, Master's thesis 2015, University of Nottingham
Panagiotis Zacharis, Bayesian calibration and model selection for elastic continua, MSc thesis 2014, University of Nottingham
Jack Litherland, Topic: Particle-continuum multiscale modeling, 2014 BSc Summer Studentship (Dean's Fund), University of Nottingham
Rody van Tuijl, Energy stable discretisation of surfactant transport on fluid surfaces, MSc thesis 2013, Eindhoven University of Technology
Göktürk Kuru, Goal-adaptive isogeometric analysis with hierarchical splines, MSc thesis 2013, Eindhoven University of Technology
Peter Fick, Goal-oriented a-posteriori error estimation and adaptivity for fluid-structure interaction, MSc thesis 2008, Delft University of Technology
Ted Heemskerk, Discontinuous Galerkin methods with solenoidal elements for the Stokes problem, MSc thesis 2006, Delft University of Technology

Preprints

H. Alsobhi, I. Brevis, D. Kalise, K.G. van der Zee, TV-regularized Least Squares FEM for first-order PDEs, preprint
Y. Fan, J. Billingham, K.G. van der Zee, A shape-Newton method for free-boundary problems subject to the Bernoulli boundary condition, arXiv:2305.14254, 2023
M. ten Eikelder, K.G. van der Zee, D. Schillinger, Thermodynamically consistent diffuse-interface mixture models of incompressible multicomponent fluids, to appear, arXiv:2302.09287, 2023
K.G. VAN DER ZEE, S. PRUDHOMME, J.T. ODEN, Adaptive modeling for partitioned-domain concurrent multiscale continuum models
Publications at Google scholar

Selected Publications

I. BREVIS, I. MUGA, D. PARDO, O. RODRIGUEZ and K.G. VAN DER ZEE, 2024. Learning quantities of interest from parametric PDEs: An efficient neural-weighted Minimal Residual approach Computers & Mathematics with Applications. 164, 139-149
M.F.P. TEN EIKELDER, K.G. VAN DER ZEE and D. SCHILLINGER, 2024. Thermodynamically consistent diffuse-interface mixture models of incompressible multicomponent fluids Journal of Fluid Mechanics. (In Press.)
A. BOSCHMAN, L. ESPATH and K.G. VAN DER ZEE, 2024. A bulk-surface continuum theory for fluid flows and phase segregation with finite surface thickness Physica D: Nonlinear Phenomena. (In Press.)
I. BREVIS, I.M. MUGA and K.G. VAN DER ZEE, 2023. Neural Control of Discrete Weak Formulations: Galerkin, Least Squares & Minimal-Residual Methods with Quasi-Optimal Weights Computer Methods in Applied Mechanics and Engineering. (In Press.)

View all publications

A. BOSCHMAN, L. ESPATH and K.G. VAN DER ZEE, 2024. A bulk-surface continuum theory for fluid flows and phase segregation with finite surface thickness Physica D: Nonlinear Phenomena. (In Press.)
M.F.P. TEN EIKELDER, K.G. VAN DER ZEE and D. SCHILLINGER, 2024. Thermodynamically consistent diffuse-interface mixture models of incompressible multicomponent fluids Journal of Fluid Mechanics. (In Press.)
I. BREVIS, I. MUGA, D. PARDO, O. RODRIGUEZ and K.G. VAN DER ZEE, 2024. Learning quantities of interest from parametric PDEs: An efficient neural-weighted Minimal Residual approach Computers & Mathematics with Applications. 164, 139-149
I. BREVIS, I.M. MUGA and K.G. VAN DER ZEE, 2023. Neural Control of Discrete Weak Formulations: Galerkin, Least Squares & Minimal-Residual Methods with Quasi-Optimal Weights Computer Methods in Applied Mechanics and Engineering. (In Press.)
M.F.P. TEN EIKELDER, K.G. VAN DER ZEE, I. AKKERMAN and D. SCHILLINGER, 2023. A unified framework for Navier-Stokes Cahn-Hilliard models with non-matching densities Mathematical Models and Methods in Applied Sciences. (In Press.)
NINIC, J., VAN DER ZEE, K.G., ICARDI, M. and WANG, F., 2023. Editorial UKACM 2022: advances in computational mechanics Engineering with Computers: An International Journal for Simulation-Based Engineering.
M. SFERZA, J. NINIC, F. GLOCK, C. HOFER, F. DAOUD, D. CHRONOPOULOS and K. VAN DER ZEE, 2023. Global–local multidisciplinary optimisation for the evaluation of local constraints on finer meshes in preliminary aircraft design Engineering with Computers: An International Journal for Simulation-Based Engineering. 39(6), 4167-4184
P. HOUSTON, S. ROGGENDORF and K.G. VAN DER ZEE, 2022. Gibbs Phenomena For L^q-best Approximation in Finite Element Spaces ESAIM Mathematical Modelling and Numerical Analysis. 56, 177-211
F. MILLAR, I. MUGA, S. ROJAS and K.G. VAN DER ZEE, 2022. Projection in negative norms and the regularization of rough linear functionals Numerische Mathematik. (In Press.)
P. HOUSTON, C.J. ROURKE and K.G. VAN DER ZEE, 2022. Linearisation of the Travel Time Functional in Porous Media Flows SIAM Journal of Scientific Computing. (In Press.)
J. ZHANG, JOHN EVANS, H. GOMEZ and K. VAN DER ZEE, 2022. An editorial perspective: new team, aims and scope and advances of EWCO Engineering with Computers. 38, 1
IGNACIO BREVIS, IGNACIO MUGA and KRISTOFFER G VAN DER ZEE, 2021. A machine-learning minimal-residual (ML-MRes) framework for goal-oriented finite element discretizations Computers and Mathematics with Applications. 95, 186-199
LEE CURTIN, ANDREA HAWKINS-DAARUD, KRISTOFFER G VAN DER ZEE, KRISTIN R SWANSON and MARKUS R OWEN, 2020. Speed switch in glioblastoma growth rate due to enhanced hypoxia-induced migration Bulletin of Mathematical Biology. 82(3), 43
PAUL HOUSTON, SARAH ROGGENDORF and KRISTOFFER G VAN DER ZEE, 2020. Eliminating Gibbs Phenomena: A Non-linear Petrov-Galerkin Method for the Convection-Diffusion-Reaction Equation Computers and Mathematics with Applications. 80(5), 851-873
LEE CURTIN, ANDREA HAWKINS-DAARUD, ALYX B. PORTER, KRISTOFFER G. VAN DER ZEE, MARKUS R. OWEN and KRISTIN R. SWANSON, 2020. A Mechanistic Investigation into Ischemia-Driven Distal Recurrence of Glioblastoma Bulletin of Mathematical Biology. 82, 143
IGNACIO MUGA and KRISTOFFER G. VAN DER ZEE, 2020. Discretization of Linear Problems in Banach Spaces: Residual Minimization, Nonlinear Petrov-Galerkin, and Monotone Mixed Methods SIAM Journal in Numerical Analysis. 58(6), 3406-3426
JUDITH MUÑOZ-MATUTE, VICTOR M CALO, DAVID PARDO, ELISABETE ALBERDI and KRISTOFFER G VAN DER ZEE, 2019. Explicit-in-Time Goal-Oriented Adaptivity Computer Methods in Applied Mechanics and Engineering. 347, 176-200
CHRISTOPHER MILES, KRISTOFFER G VAN DER ZEE, MATTHEW E HUBBARD and RODERICK MACKENZIE, 2019. Chapter 11 Thermomechanically-Consistent Phase-Field Modeling of Thin Film Flows. In: E.H. VAN BRUMMELEN, A. CORSINI, S. PEROTTO and G. ROZZA, eds., Numerical Methods for Flows: FEF 2017 Selected Contributions. Lecture Notes in Computational Science and Engineering https://www.springer.com/gp/book/9783030307042 132. Springer.
P. HOUSTON, I. MUGA, S. ROGGENDORF and K.G. VAN DER ZEE, 2019. The convection-diffusion-reaction equation in non-Hilbert Sobolev spaces: A direct proof of the inf-sup condition and stability of Galerkin's method Computational Methods in Applied Mathematics. 19(3), 503-522
I. MUGA, M.J.W. TYLER and K.G. VAN DER ZEE, 2019. The Discrete-Dual Minimal-Residual Method (DDMRes) for Weak Advection-Reaction Problems in Banach spaces Computational Methods in Applied Mathematics. 19(3), 557-579
R. DYJA, B. GANAPATHYSUBRAMANIAN and K.G. VAN DER ZEE, 2018. Parallel-in-space-time, adaptive finite element framework for non-linear parabolic equations SIAM Journal on Scientific Computing: Software and High-Performance Computing. 40(3), C283–C304
M. SHOKRPOUR-ROUDBARI, G. SIMSEK, E.H VAN BRUMMELEN and K.G. VAN DER ZEE, 2018. Diffuse-interface two-phase flow models with different densities: A new quasi-incompressible form and a linear energy-stable method Mathematical Models and Methods in Applied Sciences. 28(4), 733–770
X. WU, K.G. VAN DER ZEE, G. SIMSEK and E.H. VAN BRUMMELEN, 2018. A-posteriori error estimation and adaptivity for nonlinear parabolic equations using IMEX-Galerkin discretization of primal and dual equations SIAM Journal on Scientific Computing: Methods and Algorithms for Scientic Computing. 40(5), A3371-A3399
E.H. VAN BRUMMELEN, M. SHOKRPOUR ROUDBARI, G. SIMSEK and K.G. VAN DER ZEE, 2017. Binary-fluid-solid interaction based on the Navier-Stokes-Cahn-Hilliard Equations. In: Fluid-Structure Interaction: Modeling, Adaptive Discretisations and Solvers De Gruyter, Vol 20 of Radon Series on Computational and Applied Mathematics.
H. GOMEZ and K.G. VAN DER ZEE, 2017. Computational Phase-Field Modeling. In: E. STEIN, R. DE BORST and T.J.R. HUGHES, eds., Encyclopedia of Computational Mechanics, 2nd Edition: Wiley, https://onlinelibrary.wiley.com/doi/book/10.1002/9781119176817
M. FEISCHL, D. PRAETORIUS and K.G. VAN DER ZEE, 2016. An abstract analysis of optimal goal-oriented adaptivity SIAM Journal of Numerical Analysis. 54(3), 1423-1448
I. MUGA and K.G. VAN DER ZEE, 2016. Adaptive discretization in Banach spaces with the nonlinear Petrov-Galerkin method: in Adaptive Algorithms, C. Carstensen, R. Stevenson, eds. Oberwolfach Reports. 13(3), 2562-2564
D. HILHORST, J. KAMPMANN, T.N. NGUYEN and K.G. VAN DER ZEE, 2015. Formal asymptotic limit of a diffuse-interface tumor-growth model Mathematical Models and Methods in Applied Sciences. 25(6), 1011-1044
G. SIMSEK, X. WU, K.G. VAN DER ZEE and E.H. VAN BRUMMELEN, 2015. Duality-based two-level error estimation for time-dependent PDEs: Application to linear and nonlinear parabolic equations Computer Methods in Applied Mechanics and Engineering. 288, 83-109
M. LAFOREST, S. PRUDHOMME and K.G. VAN DER ZEE, 2015. Preface to the special issue on error estimation and adaptivity for nonlinear and time-dependent problems Computer Methods in Applied Mechanics and Engineering. 288, 1
WU, X., VAN ZWIETEN, G. J. and VAN DER ZEE, K. G., 2014. Stabilized second-order convex splitting schemes for Cahn–Hilliard models with application to diffuse-interface tumor-growth models INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING. 30(2), 180-203
G. KURU, C.V. VERHOOSEL, K.G. VAN DER ZEE and E.H. VAN BRUMMELEN, 2014. Goal-adaptive Isogeometric Analysis with hierarchical splines Computer Methods in Applied Mechanics and Engineering. 270, 270-292
G.J. VAN ZWIETEN, E.H. VAN BRUMMELEN, K.G. VAN DER ZEE, M.A. GUTIÉRREZ and R.F. HANSSEN, 2014. Discontinuities without discontinuity: The Weakly-enforced Slip Method Computer Methods in Applied Mechanics and Engineering. 271, 144-166
GARG, V.V., PRUDHOMME,. S., VAN DER ZEE, K.G. and CAREY, G.F., 2014. Adjoint-consistent formulations of slip models for coupled electroosmotic flow systems Advanced Modeling and Simulation in Engineering Sciences. 2, 15
A. HAWKINS-DAARUD, J.T. ODEN, S. PRUDHOMME and K.G. VAN DER ZEE, 2014. A four-species diffuse-interface tumor-growth model of gradient-flow type: in Reactive Flows in Deformable, Complex Media, M. Gerritsen, J. Nordbotten, I. Pop, B. Wohlmuth, eds. Oberwolfach Reports. 11(3), 2424-2426
HAWKINS-DAARUD, A., PRUDHOMME, S., VAN DER ZEE, K. G. and ODEN, J.T., 2013. Bayesian calibration, validation, and uncertainty quantification of diffuse interface models of tumor growth JOURNAL OF MATHEMATICAL BIOLOGY. 67(6-7), 1457-1485
VAN DER ZEE, K. G., VAN ZWIETEN, G. J., VERHOOSEL, C. V. and VAN BRUMMELEN, E. H., 2013. Shape-Newton method for isogeometric discretizations of free-boundary problems. In: ECA, L., ONATE, E., GARCIA-ESPINOSA, J. and KVAMSDAL, T., eds., MARINE 2011, IV International Conference on Computational Methods in Marine Engineering: Selected Papers 29. Springer Netherlands. 85-102
VAN BRUMMELEN, E. H., VAN DER ZEE, K. G., GARG, V. V. and PRUDHOMME, S., 2012. Flux evaluation in primal and dual boundary-coupled problems JOURNAL OF APPLIED MECHANICS-TRANSACTIONS OF THE ASME. 79(1),
HAWKINS-DAARUD, A., VAN DER ZEE, K. G. and ODEN, J. T., 2012. Numerical simulation of a thermodynamically consistent four-species tumor growth model INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING. 28(1), 3-24
VAN DER ZEE, K. G. and VERHOOSEL, C. V., 2011. Isogeometric analysis-based goal-oriented error estimation for free-boundary problems FINITE ELEMENTS IN ANALYSIS AND DESIGN. 47(6), 600-609
VAN DER ZEE, K.G., VAN BRUMMELEN, E.H., AKKERMAN, I. and DE BORST, R., 2011. Goal-oriented error estimation and adaptivity for fluid-structure interaction using exact linearized adjoints Computer Methods in Applied Mechanics and Engineering. 200(37-40), 2738-2757
VAN DER ZEE, K.G., ODEN, J.T., PRUDHOMME, S. and HAWKINS-DAARUD, A., 2011. Goal-oriented error estimation for Cahn-Hilliard models of binary phase transition Numerical Methods for Partial Differential Equations. 27(1), 160-196
AKKERMAN, I., HULSHOFF, S. J., VAN DER ZEE, K. G. and DE BORST, R., 2011. Variational Germano approach for multiscale formulations. In: DE BORST, R. and RAMM, R., eds., Multiscale Methods in Computational Mechanics: Progress and Accomplishments 55. Springer Netherlands. 53-73
VAN DER ZEE, K.G., VAN BRUMMELEN, E.H. and DE BORST, R., 2010. Goal-oriented error estimation and adaptivity for free-boundary problems: the domain-map linearization approach SIAM Journal on Scientific Computing. 32(2), 1064-1092
AKKERMAN, I., VAN DER ZEE, K. G. and HULSHOFF, S. J., 2010. A variational Germano approach for stabilized finite element methods COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING. 199(9-12), 502-513
VAN DER ZEE, K. G., VAN BRUMMELEN, E. H. and DE BORST, R., 2010. Goal-oriented error estimation and adaptivity for free-boundary problems: The shape-linearization approach SIAM JOURNAL ON SCIENTIFIC COMPUTING. 32(2), 1093-1118
FICK, P. W., VAN BRUMMELEN, E. H. and VAN DER ZEE, K. G., 2010. On the adjoint-consistent formulation of interface conditions in goal-oriented error estimation and adaptivity for fluid-structure interaction COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING. 199(49-52), 3369-3385
VAN DER ZEE, K. G., VAN BRUMMELEN, E. H. and DE BORST, R., 2008. Goal-oriented error estimation for Stokes flow interacting with a flexible channel INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS. 56(8), 1551-1557
VAN BRUMMELEN, E.H., VAN DER ZEE, K.G. and DE BORST, R., 2008. Space/time multigrid for a fluid-structure-interaction problem Applied Numerical Mathematics. 58(12), 1951-1971
VAN DER ZEE, K. G., VAN BRUMMELEN, E. H. and DE BORST, R., 2006. An H-1(rho(h))-coercive discontinuous Galerkin formulation for the poisson problem: 1d analysis SIAM JOURNAL ON NUMERICAL ANALYSIS. 44(6), 2671-2698
FARHAT, C., VAN DER ZEE, K. G. and GEUZAINE, P., 2006. Provably second-order time-accurate loosely-coupled solution algorithms for transient nonlinear computational aeroelasticity COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING. 195(17-18), 1973-2001

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