EU Regional School - Kalidindi Seminar
Prof. Dr.Surya Kalidindi - Rigorous Quantification of the Hierarchical Material Structure in a Statistical Framework
Georg W. Woodruff School of Mechanical Engineering
Georgia Institute of Technology, USA
A versatile framework for the rigorous quantification of the hierarchical material internal structure will be presented in this lecture along with demonstrations to applications on a broad variety of heterogeneous material structures at different length scales and different materials classes. This new framework is based on the established concepts of n-point spatial correlations that provide a systematic statistical description of the highly complex material structure. The framework takes advantage of toolsets established in digital signal processing, Fourier representations, and principal component analyses to develop high performance computational toolsets needed for performing the computations involved. The versatility of the framework will be demonstrated through the application of a single consistent framework at both atomistic and continuum length scales as well as different materials classes (e.g., multiphase composites, polycrystals, porous membranes).
I³MS - Möller Seminar
Dr. Matthias Möller - Isogeometric Analysis for Compressible Flow Problems in Industrial Applications
Department of Applied Mathematics, Delft University of Technology, Netherlands
In this talk, we will present an isogeometric analysis (IgA) approach for the simulation of compressible flows that arise in industrial applications, in particular, in twin-screw rotary compressors.
In the first part of the talk, we present a positivity-preserving high-resolution scheme for compressible flows building upon the generalization of the algebraic flux correction paradigm  to isogeometric analysis. Our approach adopts Fletcher's group formulation  together with an efficient edge-based formation of system matrices and vectors from pre-computed coefficients to overcome the high computational costs that are typically observed in quadrature-based IgA-assembly algorithms.
Next to this algorithmic approach to achieving high computational efficiency, our implementation in the open-source library G+Smo (https://www.gs.jku.at/gismo) makes use of meta-programming techniques to combine the computational performance of several hardware-optimized linear algebra back-ends like Blaze, Eigen, and VexCL, with ease of implementation offered by the fluid dynamics expression-template library FDBB (https://mmoelle1.gitlab.io/FDBB). Just-in time compilation techniques are used to run the solver in heterogeneous computing environments.
In the second part of the talk, we describe an isogeometric approach for the creation of analysis-suitable multi-patch parameterizations for complex industrial applications and, in particular, for (parts of) twin-screw rotary compressors. Our approach builds on well-established elliptic grid generation techniques, which have been generalized to the IgA framework.
 C.A.J. Fletcher, The group finite element formulation, Computer Methods in Applied Mechanics and Engineering, 37, 225–244, 1983.
 D. Kuzmin, M. Möller, M. Gurris, Algebraic flux correction II. Compressible flow problems. In: Kuzmin et al. (editors) Flux-Corrected Transport: Principles, Algorithms, and Applications, 193–238. Springer, 2nd edition, 2012.
EU Regional School - Persson Seminar
Prof. Dr. Per-Olof Persson - High-Order Discontinuous Galerkin Methods for Fluid and Solid Mechanics
Department of Mathematics
University of California at Berkeley, USA
It is widely believed that high-order accurate numerical methods, for example discontinuous Galerkin (DG) methods, will eventually replace the traditional low-order methods in the solution of many problems, including fluid flow, solid dynamics, and wave propagation. The lecture will give an overview of this field, including the theoretical background of the numerical schemes, the efficient implementation of the methods, and examples of real-world applications. Topics include high-order compact and sparse numerical schemes, high-quality unstructured curved mesh generation, scalable preconditioners for parallel iterative solvers, fully discrete adjoint methods for PDE-constrained optimization, and implicit-explicit schemes for the partitioning of coupled fluid-structure interaction problems. The methods will be demonstrated on some important practical problems, including the inverse design of energetically optimal flapping wings and large eddy simulation (LES) of wind turbines.
EU Regional School - Kirkland Seminar
Prof. Dr. Angus Kirkland - Advanced Methods in High Resolution Transmission Electron Microscopy: Instrumentation, Simulation and Exit Wavefunction Reconstruction
Department of Materials
University of Oxford, United Kingdom
I³MS - Mortensen Seminar
Prof. Dr. Mikael Mortensen - Automating the Spectral Galerkin Method - High Performance Computing in Python
Department of Mathematics, University of Oslo, Norway
The spectral Galerkin method employs globally supported spectral basis functions (e.g., Fourier, Chebyshev, Legendre) in the Galerkin approximation. Due to its accuracy, the method is often favored in the study of fundamental physical phenomena in Cartesian domains, like turbulence and transitional flows. Until now there have been few tools available for solving PDEs with this method, at least not if one is aiming at high performance supercomputers. With the shenfun Python module (https://github.com/spectralDNS/shenfun) an effort is made towards automating the implementation of the spectral Galerkin method for simple (yet large in scale) tensor product domains. The user interface to shenfun is intentionally made very similar to FEniCS (https://fenicsproject.org). PDEs are represented through weak variational forms and solved using efficient, order optimal direct solvers, that are made possible by exploiting the structure of the operators (e.g., tri-/penta-diagonality and upper Hessenberg), that arise from clever choices of modified Chebyshev or Legendre bases. MPI decomposition is achieved through the recently released mpi4py-fft module (https://bitbucket.org/mpi4py/mpi4py-fft), and all developed solver may, with no additional effort, be run on supercomputers using thousands of processors. The shenfun package has, for example, been used to create Navier Stokes solvers for triply periodic domains as well as channels. This talk will give a demonstration of current capabilities and highlight Python as the powerful language it is for high performance scientific computing.