The Simulation and Data Lab computational fluid dynamics (SimDataLab CFD) is leading parallel computing in Computational fluid dynamics in Iceland at the University of Iceland. The SimDataLab is Iceland’s representative in the international projects in CFD and parallel computing. SimDataLab CFD aims to develop parallel code applications in CFD and support users who have already developed parallel application codes. SimDataLab CFD participates in the European project network in parallel computing and has an infrastructure and access to powerful parallel systems in-memory optimization, processing system architecture, high scalability, and have performance optimization computer nodes.
The Simulation and Data Lab CFD performs fundamental and applied research in the CFD engineering sciences who have already developed or exploit parallel codes but need support for the use of massively parallel systems regarding high scalability, memory optimization, programming of hierarchic computer architectures, and performance optimization on computer nodes.
Part of the National Competence Center IRHPC
Dr. Ásdís Helgadóttir
Associate Professor- Faculty of Industrial Engineering, Mechanical Engineering and Computer Science
Development and implementation of numerical methods for partial differential equations with applications in Fluid Dynamics, Heat Transfer and Bio Engineering is my main research focus. Those applications call for governing equations that are often nonlinear and may have an irregular interface. The location of the interface needs to be accurately known to correctly enforce the boundary conditions at it. This may be a challenge, especially if the interface is moving. These problems generally have multiple scales, meaning that the difference between the smallest scale that needs to be resolved and the largest scale is vast. This calls for immense computational power where HPC comes to the rescue.
Dr. Pedro Costa
Post-doc – Faculty of Industrial Engineering, Mechanical Engineering and Computer Science
Turbulent multiphase flows abound in the environment and industry. These flows are three-dimensional, chaotic and multiscale by nature, giving rise to remarkable and at times dramatic phenomena. Direct Numerical Simulations of turbulent flows are first-principles simulations that resolve all spatial and temporal scales of the system. Simulating turbulent multiphase flows poses the additional challenge of imposing appropriate kinematic/dynamic compatibility conditions at fluid-fluid or particle-fluid interfaces, while the interface itself moves and deforms with the flow. These challenges make these first-principles simulations difficult, resulting in an unbalance between the limited fundamental knowledge of the physics of these flows, and their prevalent nature. Our research revolves precisely around the development of numerical methods to tackle these flows with high-fidelity, and their exploitation using HPC to unveil the underlying physics of these complex systems.
- CaNS — A code for fast, massively-parallel direct numerical simulations (DNS) of canonical flows (https://github.com/p-costa/CaNS)
- SNaC — An FFT-enhanced multi-block Navier-Stokes solver (https://github.com/p-costa/SNaC)
- InteRPartS — A numerical tool for massively-parallel, interface-resolved simulations of particle-laden flows
- CaNS-VoF — A numerical code for interface-resolved simulations of complex two-fluid flows (e.g. including phase change)
- PRACE Project DEBRIS – Microscopic Insights on the Physics of Debris Flow Through Interface-Resolved Simulations
- University of Iceland Recruitment Fund Grant TURBBLY – Numerical Investigation of heat transport in wall-bounded turbulent flows
Ph.D. Student S. Reza Hassanian. M
Ph.D. Student – Faculty of Industrial Engineering, Mechanical Engineering and Computer Science
Reza Hassanian received the B.Sc. and M.Sc. degrees in mechanical engineering from the Chamran University and the Technical University, Iran, in 2009 and 2012, respectively. He participated in Lagrangian particle tracking (LPT) application in straining turbulence studies performed in Experimental technique at the Laboratory for Fundamental Turbulence Research (LFTR) funded by the Icelandic Center for Research (Rannís) at Reykjavik University. As well He was a member of the research team in wind turbine blade erosion studies and Constant Temperature Anemometry (CTA) application at the wind tunnel in wind energy research at Reykjavik University. He is a member of the ‘‘Simulation and Data Lab Computational Fluid Dynamics’’ (SimDataLab CFD) research group at the University of Iceland, Iceland. He is leading SimDataLab CFD on RAISE and EuroCC projects at European projects Horizon 2020. He is currently pursuing a Ph.D. degree in computational engineering at the University of Iceland, Iceland. His research interest is mainly in turbulence flow, computational fluid dynamics applications, and machine learning methods. His particular focus on Machine Learning and High-Performance Computing (HPC) for computational fluid dynamics applications.
Dr. -Ing. Andreas Lintermann
Advisory Board Member
Computational Science Division, Jülich Supercomputing Centre, Forschungszentrum Jülich GmbH, Jülich, Germany
Dr.-Ing. Andreas Lintermann is a postdoctoral researcher at Forschungszentrum Jülich, a member of the Helmholtz Association, Germany. At the Jülich Supercomputing Centre (JSC), he is heading the Simulation and Data Laboratory ‘‘Highly Scalable Fluids & Solids Engineering’’, which is also part of the Jülich Aachen Research Alliance Center for Simulation and Data Science (JARA-CSD). His research focuses, amongst others, on lattice-Boltzmann methods, artificial intelligence, high-performance computing, heterogeneous computing on modular supercomputing architectures, high-scaling meshing methods, efficient multi-physics coupling strategies, and bio-fluidmechanical analyses of respiratory diseases. He is the coordinator of the European Center of Excellence in Exascale Computing “Research on AI- and Simulation-Based Engineering at Exascale” (CoE RAISE).
- -B. Indurain, D. Uystepruyst, F. Beaubert, S. Lalot, Á. Helgadóttir. Numerical investigation of several twisted tubes with non-conventional tube cross sections on heat transfer and pressure drop. Journal of Thermal Analysis and Calorimetry. 140: 1555-1568 (2020). https://doi.org/10.1007/s10973-019-08965-4
- – Á. Helgadóttir, S. Lalot, F. Beaubert, H. Pálsson. Mesh Twisting Technique for Swirl Induced Laminar Flow Used to Determine a Desired Blade Shape. Applied Sciences. 8 (10): 1865 (2018). https://doi.org/10.3390/app8101865
- – Á. Helgadóttir, A. Guittet, F. Gibou. On Solving the Poisson Equation with Discontinuities on Irregular Interfaces: GFM and VIM. International Journal of Differential Equations. 2018: Article ID 9216703 (2018). https://doi.org/10.1155/2018/9216703
- – Á. Helgadóttir, Y.-T. Ng, C. Min, F. Gibou. Imposing Mixed Dirichlet-Neumann-Robin Boundary Conditions in a Level-Set Framework. Computers and Fluids. 121: 68-80 (2015). https://doi.org/10.1016/j.compfluid.2015.08.007
- – J. Papac. Á. Helgadóttir, C. Ratsch, F. Gibou. A level set approach for diffusion and Stefan-type problems with Robin boundary conditions on quadtree/octree adaptive Cartesian grids.Journal of Computational Physics. 233: 241-261 (2013). https://doi.org/10.1016/j.jcp.2012.08.038
- – M. Mirzadeh, M. Theillard, Á. Helgadóttir, D. Boy, F. Gibou. An Adaptive, Finite Difference Solver for the Nonlinear Poisson-Boltzmann Equation with Applications to Biomolecular Computations. Communications in Computational Physics. 13 (1): 150-173 (2013). https://doi.org/10.4208/cicp.290711.181011s
- – Á. Helgadóttir, F. Gibou. A Poisson-Boltzmann solver on Irregular Domains with Neumann or Robin boundary conditions on Non-Graded Adaptive Grid. Journal of Computational Physics. 230 (10): 3830-3848 (2011). https://doi.org/10.1016/j.jcp.2011.02.010
- P. Costa, L. Brandt, and F. Picano. Interface-resolved simulations of small inertial particles in turbulent channel flow. J. Fluid Mech. 883 : A54 (2020)
- Z. Ahmed, D. Izbassarov, P. Costa, M. Muradoglu, and O. Tammisola. Turbulent bubbly channel flows: Effects of soluble surfactant and viscoelasticity. Comput. Fluids : 104717 (2020)
- N. Scapin, P. Costa, and L. Brandt. A volume-of-fluid method for interface-resolved simulations of phase-changing two-fluid flows J. Comput. Phys. 407 : 109251 (2020).
- P. Costa. A FFT-based finite-difference solver for massively-parallel direct numerical simulations of turbulent flows. Comput. Math. Appl. 76 : 1853 – 1862 (2018)
- P. Costa, F. Picano, L. Brandt, and W.-P. Breugem. Universal Scaling Laws for Dense Particle Suspensions in Turbulent Wall-Bounded Flows. Phys. Rev. Lett. 117 (13) : 134501 (2016)