Orientation Correlation in Simplified Models of Polymer Melts

We investigate mutual local chain order in systems of fully flexible polymer melts in a simple generic bead-spring model. The excluded-volume interaction together with the connectivity leads to local ordering effects which are independent of chain length between 25 and 700 monomers, i.e. in the Rouse as well as in the reptation regime. These ordering phenomena extend to a distance of about 3 to 4 monomer sizes and decay to zero afterwards.Comment: 5 pages, 3 figure

Stress Relaxation of Entangled Polymer Networks

The non-linear stress-strain relation for crosslinked polymer networks is studied using molecular dynamics simulations. Previously we demonstrated the importance of trapped entanglements in determining the elastic and relaxational properties of networks. Here we present new results for the stress versus strain for both dry and swollen networks. Models which limit the fluctuations of the network strands like the tube model are shown to describe the stress for both elongation and compression. For swollen networks, the total modulus is found to decrease like (V_0/V)^{2/3} and goes to the phantom model result only for short strand networks.Comment: 9 pages, 3 figures, RevTe

Deriving effective mesoscale potentials from atomistic simulations

We demonstrate how an iterative method for potential inversion from distribution functions developed for simple liquid systems can be generalized to polymer systems. It uses the differences in the potentials of mean force between the distribution functions generated from a guessed potential and the true (simulated) distribution functions to improve the effective potential successively. The optimization algorithm is very powerful: convergence is reached for every trial function in few iterations. As an extensive test case we coarse-grained an atomistic all-atom model of poly (isoprene) (PI) using a 13:1 reduction of the degrees of freedom. This procedure was performed for PI solutions as well as for a PI melt. Comparisons of the obtained force fields are drawn. They prove that it is not possible to use a single force field for different concentration regimes.Comment: 32 pages including 12 figure

HICFD – Highly Efficient Implementation of CFD Codes for HPC Many-Core Architectures

The objective of the German BMBF research project Highly Efficient Implementation of CFD Codes for HPC Many-Core Architectures (HICFD) is to develop new methods and tools for the analysis and optimization of the performance of parallel computational fluid dynamics (CFD) codes on high performance computer systems with many-core processors. In the work packages of the project it is investigated how the performance of parallel CFD codes written in C can be increased by the optimal use of all parallelism levels. On the highest level MPI is utilized. Furthermore, on the level of the many-core architecture, highly scaling, hybrid OpenMP/MPI methods are implemented. On the level of the processor cores the parallel SIMD units provided by modern CPUs are exploited

HICFD – Hocheffiziente Implementierung von CFD-Codes für HPC-Many-Core-Architekturen

Bei dem Forschungsprojekt HICFD handelt es sich um ein Verbundprojekt des vom Bundesministerium für Bildung und Forschung geförderten Programms „IKT 2020 – Forschung und Innovation“. Das Forschungsprojekt hat zum Ziel, neue Methoden und Werkzeuge zur Analyse und Optimierung des Leistungsvermögens strömungsmechanischer, paralleler Programme auf Hochleistungsrechnern mit Prozessoren mit einer Vielzahl von Kernen zu entwickeln und diese exemplarisch auf die strömungsmechanischen Codes TAU und TRACE des Projektpartners DLR anzuwenden. Die wesentlichen Ziele des Projektes werden in dieser Arbeit vorgestellt. Das Leistungsvermögen strömungsmechanischer, paralleler Programme soll in diesem Projekt durch eine optimale Ausnutzung aller Parallelitätsebenen verbessert werden. Auf der obersten Ebene (MPI) soll eine intelligente Gitteraufteilung den Lastausgleich zwischen den MPI-Prozessen verbessern. Für blockstrukturierte Gitter soll hier ein Multi-Core-kompatibles Partitionierungswerkzeug entwickelt werden. Auf der Ebene der Multi-Core-Architektur sollen exemplarisch für die beiden Strömungslöser TAU und TRACE hochskalierende hybride OpenMP/MPI-Verfahren implementiert werden. Auf Prozessorkern- Ebene soll ein Präprozessor entwickelt werden, der die komfortable Nutzung paralleler SIMD-Einheiten („Single Instruction Multiple Data“) auch für komplexe Anwendungen ermöglicht. Um zu überprüfen, in welchem Umfang die Anwendung des Präprozessors das Leistungsvermögen paralleler Programme beeinflusst, soll die Leistungsanalyse-Software Vampir in Richtung SIMD erweitert werden

Automatically annotated motion tracking identifies a distinct social behavioral profile following chronic social defeat stress

Severe stress exposure increases the risk of stress-related disorders such as major depressive disorder (MDD). An essential characteristic of MDD is the impairment of social functioning and lack of social motivation. Chronic social defeat stress is an established animal model for MDD research, which induces a cascade of physiological and behavioral changes. Current markerless pose estimation tools allow for more complex and naturalistic behavioral tests. Here, we introduce the open-source tool DeepOF to investigate the individual and social behavioral profile in mice by providing supervised and unsupervised pipelines using DeepLabCut-annotated pose estimation data. Applying this tool to chronic social defeat in male mice, the DeepOF supervised and unsupervised pipelines detect a distinct stress-induced social behavioral pattern, which was particularly observed at the beginning of a novel social encounter and fades with time due to habituation. In addition, while the classical social avoidance task does identify the stress-induced social behavioral differences, both DeepOF behavioral pipelines provide a clearer and more detailed profile. Moreover, DeepOF aims to facilitate reproducibility and unification of behavioral classification by providing an open-source tool, which can advance the study of rodent individual and social behavior, thereby enabling biological insights and, for example, subsequent drug development for psychiatric disorders