@inproceedings {INPROC-2017-73,
   author = {Nehzat Emamy and Maria Luk{\'a}\&\#269;ov{\'a}-Medvid’ov{\'a} and Stefanie Stalter and Peter Virnau and Leonid Yelash},
   title = {{Reduced-order hybrid multiscale method combining the Molecular Dynamics and the Discontinuous-Galerkin method}},
   booktitle = {Proceedings of VII International Conference on Computational Methods for Coupled Problems in Science and Engineering (Coupled Problems 2017)},
   address = {Rhodes Island, Greece},
   publisher = {ECCOMAS},
   institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany},
   pages = {62--76},
   type = {Conference Paper},
   month = {June},
   year = {2017},
   language = {English},
   cr-category = {I.6.0 Simulation and Modeling General},
   department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Simulation of Large Systems},
   abstract = {},
   url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2017-73&engl=1}
}

@inproceedings {INPROC-2017-71,
   author = {Carolin Schober and David Keerl and Martin Lehmann and Miriam Mehl},
   title = {{Simulating the Interaction of Electrostatically Charged Particles in the Inflow Area of Cabin Air Filters Using a Fully Coupled System}},
   booktitle = {Proceedings of the VII International Conference on Coupled Problems in Science and Engineering},
   address = {Barcelona, Spain},
   publisher = {CIMNE},
   institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany},
   pages = {77--88},
   type = {Conference Paper},
   month = {May},
   year = {2017},
   language = {English},
   cr-category = {J.2 Physical Sciences and Engineering},
   ee = {ftp://ftp.informatik.uni-stuttgart.de/pub/library/ncstrl.ustuttgart_fi/INPROC-2017-71/INPROC-2017-71.pdf},
   department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Simulation of Large Systems},
   abstract = {Cabin air filters are applied to prevent small particles such as pollen, fine
      dust and soot amongst others from being transferred into the interior (cabin)
      of a vehicle. The filter media often make use of the so called electret effect
      as means for achieving high filtration efficiency at low pressure drop.
      Thereby, electrostatic filtration effects are supplemented to the well-known
      mechanical collection mechanisms (such as inertia, diffusion,...). Besides the
      interference of several fiber-particle interactions (Coulombic
      attraction/repulsion, induced dipolar forces, image charge effects)
      particle-particle interactions potentially play an important role. However,
      this effect is completely neglected in previous research studies due to the
      high degree of complexity [1]. In this work, we present a detailed
      investigation of the particle behaviour in the inflow area and transition area
      to the filter media. For a precise description of the underlying physical
      procedures the simulation is based on a four-way coupling. This approach takes
      into account the reciprocal influence between the fluid flow and the particle
      motion as well as the interactions between single electrostatically charged
      particles. The software package ESPResSo [2] used in this work is based on a
      molecular dynamic approach and provides the advantage of efficient algorithms
      for the modelling of electrostatic interactions. In order to emulate the air
      flow, the molecular dynamic simulation is coupled with a Lattice-Boltzmann
      fluid. The presented talk focuses on the influence of the particle-particle
      interactions on the filtration performance. It is elaborated whether the fully
      coupled system is necessary in order to reflect reality more closely or the
      simulation can be simplified to reduce the degree of complexity and thus the
      computational costs.
      
      REFERENCES [1] S. Rief, A. Latz, A. Wiegmann, {\^a}€śComputer simulation of Air
      Filtration including electric surface charges in three-dimensional fibrous
      micro structures{\^a}€ť, Filtration 6.2, (2006). [2] A. Arnold, O. Lenz, S.
      Kesselheim, R. Weeber, F. Fahrenberger, D. Roehm, P. Ko{\AA}ˇovan and C. Holm,
      {\^a}€śESPResSo 3.1: Molecular Dynamic Software for Coarse-Grained Models{\^a}€ť,
      Lecture Notes in Computational Science and Engineering, (2013).},
   url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2017-71&engl=1}
}

@inproceedings {INPROC-2017-62,
   author = {Andreas Mang and Sameer Tarakan and Amir Gholami and Naveen Himthani and Subramanian and Shanshank and James Levitt and Muneeza Azmat and Klaudius Scheufele and Miriam Mehl and Christos Davatzikos and Bill Bart and George Biros},
   title = {{SIBIA-GlS: Scalable Biophysics-Based Image Analysis for Glioma Segmentation}},
   booktitle = {The multimodal brain tumor image segmentation benchmark (BRATS), MICCAI},
   publisher = {-},
   institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany},
   pages = {202--209},
   type = {Conference Paper},
   month = {July},
   year = {2017},
   language = {English},
   cr-category = {G.1.6 Numerical Analysis Optimization,
                   G.1.8 Partial Differential Equations,
                   J.3 Life and Medical Sciences},
   ee = {https://www.cbica.upenn.edu/sbia/Spyridon.Bakas/MICCAI_BraTS/MICCAI_BraTS_2017_proceedings_shortPapers.pdf},
   department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Simulation of Large Systems},
   abstract = {},
   url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2017-62&engl=1}
}

@inproceedings {INPROC-2017-61,
   author = {Amir Gholami and Andreas Mang and Klaudius Scheufele and Christos Davatzikos and Miriam Mehl and George Biros},
   title = {{A Framework for Scalable Biophysics-based Image Analysis}},
   booktitle = {Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC17},
   address = {New York, NY, USA},
   publisher = {ACM},
   institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany},
   pages = {1--13},
   type = {Conference Paper},
   month = {November},
   year = {2017},
   doi = {10.1145/3126908.3126930},
   isbn = {978-1-4503-5114-0},
   keywords = {bio-physics based image analysis; scalable image registration},
   language = {English},
   cr-category = {G.1.6 Numerical Analysis Optimization,
                   G.1.8 Partial Differential Equations,
                   J.3 Life and Medical Sciences},
   ee = {ftp://ftp.informatik.uni-stuttgart.de/pub/library/ncstrl.ustuttgart_fi/INPROC-2017-61/INPROC-2017-61.pdf,
      https://dl.acm.org/citation.cfm?doid=3126908.3126930},
   department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Simulation of Large Systems},
   abstract = {},
   url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2017-61&engl=1}
}

@inproceedings {INPROC-2017-37,
   author = {Benjamin Peherstorfer and Dirk Pfl{\"u}ger and Hans-Joachim Bungartz},
   title = {{Density Estimation with Adaptive Sparse Grids for Large Data Sets}},
   booktitle = {Proceedings of the 2014 SIAM International Conference on Data Mining},
   publisher = {SIAM},
   institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany},
   pages = {443--451},
   type = {Conference Paper},
   month = {January},
   year = {2017},
   doi = {10.1137/1.9781611973440.51},
   keywords = {sparse grids; density estimation; big data},
   language = {English},
   cr-category = {I.2 Artificial Intelligence,
                   I.6 Simulation and Modeling},
   department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Simulation of Large Systems},
   abstract = {Nonparametric density estimation is a fundamental problem of statistics and
      data mining. Even though kernel density estimation is the most widely used
      method, its performance highly depends on the choice of the kernel bandwidth,
      and it can become computationally expensive for large data sets. We present an
      adaptive sparse-grid-based density estimation method which discretizes the
      estimated density function on basis functions centered at grid points rather
      than on kernels centered at the data points. Thus, the costs of evaluating the
      estimated density function are independent from the number of data points. We
      give details on how to estimate density functions on sparse grids and develop a
      cross validation technique for the parameter selection. We show numerical
      results to confirm that our sparse-grid-based method is well-suited for large
      data sets, and, finally, employ our method for the classification of
      astronomical objects to demonstrate that it is competitive to current
      kernel-based density estimation approaches with respect to classification
      accuracy and runtime.},
   url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2017-37&engl=1}
}

@inproceedings {INPROC-2017-35,
   author = {Florian Lindner and Miriam Mehl and Benjamin Uekermann},
   title = {{Radial Basis Function Interpolation for Black-Box Multi-Physics Simulations}},
   booktitle = {Proceedings of the VII International Conference on Coupled Problems in Science and Engineering},
   editor = {International Center for Numerical Methods in Engineering (CIMNE)},
   address = {Barcelona, Spain},
   publisher = {CIMNE},
   institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany},
   pages = {50--61},
   type = {Conference Paper},
   month = {May},
   year = {2017},
   isbn = {978-84-946909-2-1},
   language = {English},
   cr-category = {G.1.1 Numerical Analysis Interpolation},
   ee = {ftp://ftp.informatik.uni-stuttgart.de/pub/library/ncstrl.ustuttgart_fi/INPROC-2017-35/INPROC-2017-35.pdf},
   contact = {florian.lindner@ipvs.uni-stuttgart.de},
   department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Simulation of Large Systems},
   abstract = {},
   url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2017-35&engl=1}
}

@inproceedings {INPROC-2017-31,
   author = {Mario Heene and Alfredo Parra Hinojosa and Hans-Joachim Bungartz and Dirk Pfl{\"u}ger},
   title = {{A Massively-Parallel, Fault-Tolerant Solver for High-Dimensional PDEs}},
   booktitle = {Euro-Par 2016: Parallel Processing Workshops},
   editor = {F. Desprez and Et al.},
   address = {Cham},
   publisher = {Springer},
   institution = {University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany},
   series = {Lecture Notes in Computer Science (LNCS)},
   volume = {10104},
   pages = {635--647},
   type = {Conference Paper},
   month = {May},
   year = {2017},
   doi = {10.1007/978-3-319-58943-5_51},
   language = {English},
   cr-category = {G.4 Mathematical Software},
   department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Simulation of Large Systems},
   abstract = {We investigate the effect of hard faults on a massively-parallel implementation
      of the Sparse Grid Combination Technique (SGCT), an efficient numerical
      approach for the solution of high-dimensional time-dependent PDEs. The SGCT
      allows us to increase the spatial resolution of a solver to a level that is out
      of scope with classical discretization schemes due to the curse of
      dimensionality. We exploit the inherent data redundancy of this algorithm to
      obtain a scalable and fault-tolerant implementation without the need of
      checkpointing or process replication. It is a lossy approach that can guarantee
      convergence for a large number of faults and a wide range of applications. We
      present first results using our fault simulation framework {\^a}€“ and the first
      convergence and scalability results with simulated faults and algorithm-based
      fault tolerance for PDEs in more than three dimensions.},
   url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2017-31&engl=1}
}

@article {ART-2017-18,
   author = {Zahra Niroobakhsh and Nehzat Emamy and Roozbeh Mousavi and Florian Kummer and Martin Oberlack},
   title = {{Numerical investigation of laminar vortex shedding applying a discontinuous Galerkin Finite Element method}},
   journal = {Progress in Computational Fluid Dynamics, An International Journal (PCFD)},
   publisher = {Inderscience Publishers},
   volume = {17},
   number = {3},
   pages = {131--140},
   type = {Article in Journal},
   month = {March},
   year = {2017},
   language = {English},
   cr-category = {I.6.0 Simulation and Modeling General},
   department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Simulation of Large Systems},
   abstract = {},
   url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2017-18&engl=1}
}

@article {ART-2017-17,
   author = {Nehzat Emamy and Florian Kummer and Markus Mrosek and Martin Karcher and Martin Oberlack},
   title = {{Implicit-explicit and explicit projection schemes for the unsteady incompressible Navier-Stokes equations using a high-order dG method}},
   journal = {Computers \& Fluids},
   publisher = {Elsevier},
   volume = {154},
   pages = {285--295},
   type = {Article in Journal},
   month = {September},
   year = {2017},
   language = {English},
   cr-category = {I.6.0 Simulation and Modeling General},
   department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Simulation of Large Systems},
   abstract = {},
   url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2017-17&engl=1}
}

@article {ART-2017-11,
   author = {Klaudius Scheufele and Miriam Mehl},
   title = {{ROBUST MULTI-SECANT QUASI-NEWTON VARIANTS FOR PARALLEL FLUID-STRUCTURE SIMULATIONS—AND OTHER MULTIPHYSICS APPLICATIONS}},
   journal = {Siam Journal on Scientific Computing, Volume 39, Issue 5},
   editor = {SIAM},
   publisher = {SIAM},
   volume = {39},
   number = {5},
   pages = {404--433},
   type = {Article in Journal},
   month = {January},
   year = {2017},
   isbn = {10.1137/16M1082020},
   keywords = {partitioned multiphysics; nonlinear fixed-point solver; quasi-Newton, fluid-structure interaction},
   language = {English},
   cr-category = {G.4 Mathematical Software,
                   G.1.6 Numerical Analysis Optimization},
   ee = {ftp://ftp.informatik.uni-stuttgart.de/pub/library/ncstrl.ustuttgart_fi/ART-2017-11/ART-2017-11.pdf},
   contact = {klaudius.scheufele@ipvs.uni-stuttgart.de},
   department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Simulation of Large Systems},
   abstract = {},
   url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2017-11&engl=1}
}

@article {ART-2017-03,
   author = {Gizem Inci and Andreas Kronenburg and Rudolf Weeber and Dirk Pfl{\"u}ger},
   title = {{Langevin Dynamics Simulation of Transport and Aggregation of Soot Nano-particles in Turbulent Flows}},
   journal = {Flow, Turbulence and Combustion},
   publisher = {Springer},
   pages = {1--21},
   type = {Article in Journal},
   month = {January},
   year = {2017},
   issn = {1573-1987},
   doi = {10.1007/s10494-016-9797-3},
   keywords = {Aggregation; Dissipation rate; Langevin dynamics; Soot particles; Turbulence},
   language = {English},
   cr-category = {J.2 Physical Sciences and Engineering},
   department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Simulation of Large Systems},
   abstract = {The present paper uses Langevin dynamics (LD) to investigate the aggregation of
      soot nano-particles in turbulent flows. Interparticle forces are included, and
      the computation of the individual particles by LD is retained even after
      aggregate formation such that collision events and locations can be based on
      center-to-center particle distances without invoking any modelling assumptions
      of aggregate shape and/or collision frequency. We focus on the interactions
      between the specific hydrodynamic conditions and the particle properties and
      their effect on the resulting agglomerates' morphologies. The morphology is
      characterized by the fractal dimension, Df. Computations of particle
      aggregation in homogeneous isotropic turbulence and in shear flows dominated by
      counter-rotating vortices with a wide range of turbulence intensities and
      particle sizes indicate that the evolution of the agglomerates' shapes can be
      adequately parameterized by the size of the agglomerates and the Knudsen and
      P{\'e}clet numbers, the latter being based on the smallest turbulence scales. The
      computations further suggest that the shapes of agglomerates of certain sizes
      are relatively independent of time and relatively insensitive to larger
      turbulence structures. The fractal dimensions are modelled as functions of
      radius of gyration, Kn and Pe. The fitted expressions show good agreement with
      the LD simulations and represent the entire growth process of the agglomerates.
      A direct comparison of selected aggregates with experimental data shows very
      good qualitative agreement. A thorough quantitative validation of the evolution
      of the computed aggregate characteristics is, however, presently hindered by
      the challenges for and therefore lack of suitable experiments under
      appropriately controlled conditions.},
   url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2017-03&engl=1}
}

@inbook {INBOOK-2017-06,
   author = {Steffen Hirschmann and Malte Brunn and Michael Lahnert and Colin W. Glass and Miriam Mehl and Dirk Pfl{\"u}ger},
   title = {{Load balancing with p4est for Short-Range Molecular Dynamics with ESPResSo}},
   series = {Advances in Parallel Computing},
   publisher = {IOS Press},
   volume = {32},
   pages = {455--464},
   type = {Article in Book},
   month = {September},
   year = {2017},
   doi = {10.3233/978-1-61499-843-3-455},
   language = {English},
   cr-category = {G.0 Mathematics of Computing General},
   ee = {ftp://ftp.informatik.uni-stuttgart.de/pub/library/ncstrl.ustuttgart_fi/INBOOK-2017-06/INBOOK-2017-06.pdf},
   department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Simulation of Large Systems},
   abstract = {},
   url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INBOOK-2017-06&engl=1}
}

@inbook {INBOOK-2017-02,
   author = {Patrick Diehl and Michael Bu{\ss}ler and Dirk Pfl{\"u}ger and Steffen Frey and Thomas Ertl and Filip Sadlo and Marc Alexander Schweitzer},
   title = {{Extraction of Fragments and Waves After Impact Damage in Particle-Based Simulations}},
   series = {Meshfree Methods for Partial Differential Equations VIII},
   publisher = {Springer International Publishing},
   pages = {17--34},
   type = {Article in Book},
   month = {January},
   year = {2017},
   isbn = {978-3-319-51954-8},
   doi = {10.1007/978-3-319-51954-8_2},
   language = {German},
   cr-category = {I.3 Computer Graphics,
                   J.2 Physical Sciences and Engineering},
   department = {University of Stuttgart, Institute of Parallel and Distributed Systems, Simulation of Large Systems},
   abstract = {The analysis of simulation results and the verification against experimental
      data is essential to develop and interpret simulation models for impact damage.
      We present two visualization techniques to post-process particle-based
      simulation data, and we highlight new aspects for the quantitative comparison
      with experimental data. As the underlying simulation model we consider the
      particle method Peridynamics, a non-local generalization of continuum
      mechanics. The first analysis technique is an extended component labeling
      algorithm to extract the fragment size and the corresponding histograms. The
      distribution of the fragment size can be obtained by real-world experiments as
      demonstrated in Schram and Meyer (Simulating the formation and evolution of
      behind armor debris fields. ARL-RP 109, U.S. Army Research Laboratory, 2005),
      Vogler et al. (Int J Impact Eng 29:735-746, 2003). The second approach focuses
      on the visualization of the stress after an impact. Here, the particle-based
      data is re-sampled and rendered with standard volume rendering techniques to
      address the interference pattern of the stress wave after reflection at the
      boundary. For the extraction and visual analysis, we used the widely-used
      Stanford bunny as a complex geometry. For a quantitative study with a simple
      geometry, the edge-on impact experiment (Schradin, Scripts German Acad Aeronaut
      Res 40:21-68, 1939; Strassburger, Int J Appl Ceram Technol 1:1:235-242, 2004;
      Kawai et al., Procedia Eng 103:287-293, 2015) can be applied. With these new
      visualization approaches, new insights for the quantitative comparison of
      fragmentation and wave propagation become intuitively accessible.},
   url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INBOOK-2017-02&engl=1}
}