@article{oai:kansai-u.repo.nii.ac.jp:00013083,
 author = {山本, 阿子 and 高橋, 智幸 and 原田, 賢治 and 櫻庭, 雅明 and 野島, 和也},
 journal = {社会安全学研究 = Journal of societal safety sciences},
 month = {Mar},
 note = {To improve tsunami prediction, it is important to consider paleo tsunami records. Tsunami deposits can provide many paleo tsunami records; however, the formation mechanism of tsunami deposits remains unclear. Furthermore, numerical analysis focusing on tsunami sediment in the inundation area has fewer verification examples. Therefore, in this study, we conducted hydraulic experiments to elucidate the formation mechanism of tsunami deposits. The hydraulic experiments considered the influence of grain size and reflection wave. In addition, we investigated the characteristics of sand deposits depending on sand composition and topography (i.e., natural embankment). It was confirmed that the amount of sand deposit decreased toward the top of the run-up area. However, for the case of mixed sand which has several grain sizes, it was found that the mixing ratio influenced the composition ratio of the sand deposit in the middle of the slope area. For the case of the reflection wall, it was observed that characteristic sand deposits were formed by the return flow. We evaluated existing sand transport models using the obtained data. The results of the numerical experiments confirmed the high reproducibility of the existing models for the case with the return flow (i.e., with a reflection wall). However, for the case without return flow (without a reflection wall), it was clear that reproducibility was affected by grain size. Furthermore, it was confirmed that the amount of sand deposit was overestimated near the top of the run-up area. Thus, we considered some problems of overcome this model., This study was supported by JSPS KAKENHI Grant Number 17H02060.},
 pages = {3--19},
 title = {Validation of Sediment Transport Model Using Hydraulic Experiment Data to Assess the Influence of Grain Size and Reflection Wave on Tsunami Deposit},
 volume = {9},
 year = {2019}
}