Artificial neural network based breakwater damage estimation considering tidal level variation

作者：Kim Dong Hyawn^*; Kim Young Jin; Hur Dong Soo

来源：Ocean Engineering, 2014, 87: 185-190.

DOI：10.1016/j.oceaneng.2014.06.001

• Breakwater
• Expected damage
• Reliability
• Artificial neural network
• Tide
• Wave transformation

A new approach to damage estimation of breakwater armor blocks was developed by incorporating a wave height prediction artificial neural network (ANN) into a Monte Carlo simulation (MCS). The ANN was used to predict the wave height in front of a breakwater, with both the deep water wave heights and tidal level being input to the ANN. The waves predicted by the ANN were comparable to those from a wave transform analysis. Using an ANN in wave prediction makes it possible to very simply and quickly obtain numerous waves near the breakwater. Eventually, the analysis time for the expected damage can be reduced. In addition, the effect of the tidal level on the expected damage was revealed by numerical examples. In these numerical examples, it was found that the tidal variation should be taken into account when estimating the expected breakwater damage.

• 出版日期2014-9-1