is an Assistant Professor
Disaster Prevention and Coastal Engineering Lab.,
Department of Social Systems and Civil Engineering,
Graduate School of Engineering,
Tottori University.
4-101, Koyama Minami, Tottori, Japan, 680-8552
日本語ページはこちら
Research papers published in peer reviewed journals, international conferences and national conferences in English, Japanese, Korean and Vietnam.
Welcome to a glimpse of my research life in 365 days.
Publication
Research papers published in peer reviewed journals, international conferences and national conferences in English, Japanese, Korean and Vietnam.
Research
My research is mainly involved with modelling of storm surge, wave, tide and sediment transport on coastal and ocean environment using a coupled model of surge, wave and tide (SuWAT) since PhD candidate.
The assessment of future storm surge risk using synthetic typhoons projected by an atmospheric circulation model (Japan Meteorological Agency).
Sediment transport modeling using a coupled model of surge, wave, tide and sediment transport (SuWATsed).
Wave-surge-current interaction in the sea surface and bottom boundaries in the extreme condition of typhoon/hurricane.
Forecast modeling of time-dependent surge and wave levels has been recently carried out using a machine learning method of an artificial neural network.
See in detail for publication.
Model
A coupled model of surge, wave and tide (SuWAT) that has been developed with collaboration of Professor H. Mase at DPRI, Kyoto University and T. Yasuda at Kansai University. The SuWAT model on structured C grids has been rewritten based on Message Passing Interface to nest inner domains and to robust calculation speeds. The SuWAT model consists of modules of storm surge, wave (SWAN), tide and sediment transport (in developing). Wind and pressure force can be chosen by a parametric model and an external model of atmospheric circulation model. The source code of SuWAT is basically opened to the public and commercial sectors.
The SuWAT model supports following modes.
- Only surge mode
- Only wave mode
- a coupled mode of surge and wave
- a coupled model of surge, wave and tide
A machine learning method of Artificial Neural Network (ANN) has been used to model time-dependent surge and wave levels. We are now trying to forecast surge levels with the 32 h lead time and wave information of height, period and direction with 7 weeks in advance.
A coupled model of surge, wave, tide and sediment transport (SuWATsed) that has been developed with collaboration of P. Shunqi at Cardiff University, UK.
Further information, please contact me.