Acceleration of Morphodynamic Simulations Based on Local Trends in the Bed Evolution
Due to the significant mismatch in timescales associated with morphological and hydrodynamic processes in coastal environments, modellers typically resort to various techniques for speeding up the bed evolution in morphodynamic simulations. In this paper, we propose a novel method that differs from...
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Veröffentlicht in: | Journal of marine science and engineering 2023-12, Vol.11 (12), p.2314 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Due to the significant mismatch in timescales associated with morphological and hydrodynamic processes in coastal environments, modellers typically resort to various techniques for speeding up the bed evolution in morphodynamic simulations. In this paper, we propose a novel method that differs from existing ones in several aspects. For example, unlike previous approaches that apply a global measure (such as a constant acceleration factor that uniformly amplifies the bed evolution everywhere), we track and extrapolate local trends in morphological changes. The present algorithm requires the setting of four different parameters, values for which we set through an extensive calibration process. The proposed method is compared against the simple acceleration technique built into the popular software XBeach (wherein it is called morfac) for eight different beach profiles (including linear, Dean, and measured profiles). While the accuracy of both methods is generally similar, the proposed algorithm consistently shows a greater reduction in computational time relative to morfac, with our algorithm-accelerated simulations being on average 2.6 times faster than morfac. In light of these results, and considering the algorithm’s potential for easy generalisation to address arbitrary coastal morphodynamic problems, we believe that this method represents an important addition to the toolbox available to the community interested in coastal modelling. |
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ISSN: | 2077-1312 2077-1312 |
DOI: | 10.3390/jmse11122314 |