Titlebook: High Performance Computing in Science and Engineering ‘ 18; Transactions of the Wolfgang E. Nagel,Dietmar H. Kr?ner,Michael M. Res Confere

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DNS of Compressible Turbulent Boundary Layers with Adverse Pressure Gradients boundary-layer profiles in their streamwise evolution, which represents the most general canonical form of the adverse pressure gradient case. Only few results are available in literature for this problem even in the incompressible regime, since the achievement of such canonical flows requires very

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Towards a Direct Numerical Simulation of Primary Jet Breakup with Evaporatione liquid also evaporates during breakup. Direct Numerical Simulations (DNS) are well suited for the analysis of this phenomena. As a first step towards an understanding of this problem, a DNS of an evaporating jet is carried out and a comparison with a non evaporating jet is presented. We use the in

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Accurate and Efficient Spin-Spin Zero-Field Splitting Calculations for Extended Periodic Systemsn of experimental data. Here we address the negatively charged nitrogen-vacancy center (NV.) in diamond. It is used as a test system to explore the accuracy and efficiency of spin-spin zero-field splitting calculations on massively parallel computing systems.

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Enhanced Acid Dissociation at the Solid/Liquid Interfaceace, as well as the role of the silanols in stabliziing the deprotonated form of the acid. The enhanced acidity at the hydrophilic quartz/water interface is at odd with what typically found at the water/air interface where acidity is normally reduced, and the associated form of the acidity stabilized.

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B. M. McLaughlin,C. P. Ballance,M. S. Pindzola,P. C. Stancil,J. F. Babb,S. Schippers,A. Mülleron an example..Secondly, we are developing a conceptual hierarchy building method based on the similarity between events or event sets using the notion of Similarity vectors. The algorithm outputs several equally sensible hierarchies.

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ithms and methods used in the applications in the spectrum of time-dependent electricity consumption to smart grid planning and operations are investigated extensively. Moreover, the properties of time series data, fundamental concepts of machine learning, and techniques of hyperparameter tuning are described in detail.

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