K
Kristoffer G. van der Zee
Researcher at University of Nottingham
Publications - 40
Citations - 1085
Kristoffer G. van der Zee is an academic researcher from University of Nottingham. The author has contributed to research in topics: Finite element method & Discretization. The author has an hindex of 11, co-authored 35 publications receiving 882 citations. Previous affiliations of Kristoffer G. van der Zee include University of Texas at Austin & Eindhoven University of Technology.
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Provably second-order time-accurate loosely-coupled solution algorithms for transient nonlinear computational aeroelasticity
TL;DR: In this paper, a second-order time-accurate and yet loosely-coupled partitioned procedure for the solution of nonlinear fluid-structure interaction (FSI) problems on moving grids is presented.
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Numerical simulation of a thermodynamically consistent four-species tumor growth model
TL;DR: A thermodynamically consistent four-species model of tumor growth on the basis of the continuum theory of mixtures, unique to this model is the incorporation of nutrient within the mixture as opposed to being modeled with an auxiliary reaction-diffusion equation.
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Bayesian calibration, validation, and uncertainty quantification of diffuse interface models of tumor growth
TL;DR: This work attempts to lay out a framework, based on Bayesian probability, for systematically addressing the questions of Validation, the process of investigating the accuracy with which a mathematical model is able to reproduce particular physical events, and Uncertainty quantification, developing measures of the degree of confidence withWhich a computer model predicts particular quantities of interest.
Reference EntryDOI
Computational Phase-Field Modeling
TL;DR: The phase-field model as discussed by the authors is a methodology to reformulate interface problems as equations posed on fixed domains, and it is shown to converge to the moving-boundary problem as a regularization parameter tends to zero, which shows the mathematical soundness of the approach.
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Goal-oriented error estimation for Cahn-Hilliard models of binary phase transition
TL;DR: In this article, a posteriori estimates of errors in quantities of interest are developed for the nonlinear system of evolution equations embodied in the Cahn-Hilliard model of binary phase transition.