N. Erdem Unal
Istanbul Technical University
19 Papers
99 Citations
N. Erdem Unal is an academic researcher from Istanbul Technical University. The author has contributed to research in topics: Series (mathematics) & Erosion. The author has an hindex of 12, co-authored 19 publications. Previous affiliations of N. Erdem Unal include Istanbul University.
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Papers
Sloshing in a three-dimensional rectangular tank: Numerical simulation and experimental validation
Hakan Akyildiz,N. Erdem Unal +1 more
TL;DR: In this article, a numerical algorithm based on the volume of fluid (VOF) technique is used to study the non-linear behavior and damping characteristics of liquid sloshing in a moving partially filled rectangular tank.
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An experimental investigation of the effects of the ring baffles on liquid sloshing in a rigid cylindrical tank
TL;DR: In this paper, a cylindrical tank with various fill levels and ring baffles under the excitations of roll motion is experimentally investigated to examine the relative effectiveness of various baffle arrangements and provide test data for the verification of numerical models and to recommend a practical baffle arrangement that would be effective over a range of frequencies.
100
Fast segmentation algorithms for long hydrometeorological time series
TL;DR: Three algorithms are presented for time series segmentation based on dynamic programming and the second and the third—the latter being an improved version of the former—are based on the branch-and-bound approach.
Discussion of “Generalized regression neural networks for evapotranspiration modelling”
TL;DR: Results presented in the study show the potential of GRNNs as an alternative to the existing methods, but the study contains some points, which, from the experience, require further discussion and clarification.
41
Segmentation algorithm for long time series analysis
TL;DR: An algorithm based on the first order statistical moment of a time series is developed and applied on five time series with length ranging from 84 items to nearly 1,300, proving the applicability and usefulness of the proposed algorithm in long hydrometeorological and geophysical time series analysis.
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