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Numerical simulation data on landslide generated impulse waves affected by the reservoir geometry.

ABSTRACT: The data article provided time series of water surface elevation and wave parameters of landslide generated impulse waves affected by reservoir geometry. Two types of generalized reservoir geometries were investigated by the numerical method of Tsunami Squares-converging reservoir geometries and diverging reservoir geometries. 14 numerical reservoir models with expansion angle of 0°, 5°, 10°, 15°, 20°, 25° and 30° were performed. Time series of water surface elevation at the propagation distance of 2 km for the converging and diverging reservoir models were obtained from 70 numerical wave gauges, which allows to analyse the effect of reservoir geometries on wave characteristics generated by landslide. The wave profiles of section C at different propagation distance were also investigated in order to improve the understanding of wave characteristics at different positions. Furthermore, wave parameters (wave height, wave amplitude and wave trough) of different propagation distance for all reservoir geometries were present in the article. These data were used in Zhang et al., 2019 [1].

SUBMITTER: Zhang Y

PROVIDER: S-EPMC7096667 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Numerical simulation data on landslide generated impulse waves affected by the reservoir geometry.

Zhang Yu Y Li Deying D Chen Lixia L Yin Kunlong K Xiao Lili L Fu Xiaolin X Glade Thomas T Leo Chin C

Data in brief 20191214

The data article provided time series of water surface elevation and wave parameters of landslide generated impulse waves affected by reservoir geometry. Two types of generalized reservoir geometries were investigated by the numerical method of Tsunami Squares-converging reservoir geometries and diverging reservoir geometries. 14 numerical reservoir models with expansion angle of 0°, 5°, 10°, 15°, 20°, 25° and 30° were performed. Time series of water surface elevation at the propagation distance ...[more]

PMID: 32226797

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Project description:BackgroundCortical spreading depolarization (SD) is a propagating depolarization wave of neurons and glial cells in the cerebral gray matter. SD occurs in all forms of severe acute brain injury, as documented by using invasive detection methods. Based on many experimental studies of mechanical brain deformation and concussion, the occurrence of SDs in human concussion has often been hypothesized. However, this hypothesis cannot be confirmed in humans, as SDs can only be detected with invasive detection methods that would require either a craniotomy or a burr hole to be performed on athletes. Typical electroencephalography electrodes, placed on the scalp, can help detect the possible presence of SD but have not been able to accurately and reliably identify SDs.MethodsTo explore the possibility of a noninvasive method to resolve this hurdle, we developed a finite element numerical model that simulates scalp voltage changes that are induced by a brain surface SD. We then compared our simulation results with retrospectively evaluated data in patients with aneurysmal subarachnoid hemorrhage from Drenckhahn et al. (Brain 135:853, 2012).ResultsThe ratio of peak scalp to simulated peak cortical voltage, Vscalp/Vcortex, was 0.0735, whereas the ratio from the retrospectively evaluated data was 0.0316 (0.0221, 0.0527) (median [1st quartile, 3rd quartile], n = 161, p < 0.001, one sample Wilcoxon signed-rank test). These differing values provide validation because their differences can be attributed to differences in shape between concussive SDs and aneurysmal subarachnoid hemorrhage SDs, as well as the inherent limitations in human study voltage measurements. This simulated scalp surface potential was used to design a virtual scalp detection array. Error analysis and visual reconstruction showed that 1 cm is the optimal electrode spacing to visually identify the propagating scalp voltage from a cortical SD. Electrode spacings of 2 cm and above produce distorted images and high errors in the reconstructed image.ConclusionsOur analysis suggests that concussive (and other) SDs can be detected from the scalp, which could confirm SD occurrence in human concussion, provide concussion diagnosis on the basis of an underlying physiological mechanism, and lead to noninvasive SD detection in the setting of severe acute brain injury.

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Numerical simulation data on landslide generated impulse waves affected by the reservoir geometry.

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Numerical simulation data on landslide generated impulse waves affected by the reservoir geometry.

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