S
Schalk Kok
Researcher at University of Pretoria
Publications - 111
Citations - 1601
Schalk Kok is an academic researcher from University of Pretoria. The author has contributed to research in topics: Finite element method & Creep. The author has an hindex of 19, co-authored 107 publications receiving 1311 citations. Previous affiliations of Schalk Kok include University of Illinois at Urbana–Champaign & Council of Scientific and Industrial Research.
Papers
More filters
Journal ArticleDOI
A polycrystal plasticity model based on the mechanical threshold
TL;DR: In this article, a temperature and rate-dependent viscoplastic polycrystal model is presented, which uses a single crystal constitutive response that is based on the isotropic Mechanical Threshold Stress continuum model.
Journal ArticleDOI
Spatial coupling in jerky flow using polycrystal plasticity
Schalk Kok,M. S. Bharathi,Armand Joseph Beaudoin,Claude Fressengeas,G. Ananthakrishna,L.P. Kubin,Mikhail Lebyodkin +6 more
TL;DR: In this paper, a multiscale approach including a finite element framework for polycrystal plasticity is used to model jerky flow, also known as the Portevin-Le Chatelier effect.
Journal ArticleDOI
Development of a convex polyhedral discrete element simulation framework for NVIDIA Kepler based GPUs
TL;DR: A novel DEM based particle simulation code (BLAZE-DEM) that is capable of simulating millions of particles on a desktop computer utilizing a NVIDIA Kepler Graphical Processor Unit (GPU) via the CUDA programming model is introduced.
Journal ArticleDOI
A comparative assessment of the uncertainties of global surface ocean CO 2 estimates using a machine-learning ensemble (CSIR-ML6 version 2019a) – have we hit the wall?
Luke Gregor,Luke Gregor,Luke Gregor,Alice Lebehot,Alice Lebehot,Schalk Kok,Pedro M. S. Monteiro +6 more
TL;DR: In this paper, an ensemble average of six machine learning models (CSIR-ML6 version 2019a, Council for Scientific and Industrial Research -Machine Learning ensemble with Six members) is proposed to fill the gaps in sparse surface ocean CO2 measurements.
Journal ArticleDOI
Comparison of linear and classical velocity update rules in particle swarm optimization : Notes on diversity
TL;DR: The significance of diversity in the particle swarm optimization (PSO) algorithm is investigated and two different implementations of the PSO are studied, being the so‐called linear and classical PSO formulations.