Ching-Piao Tsai

Neural network for wave forecasting among multi-stations

Unlike in the open sea, the use of wind information for forecasting waves may encounter more ambiguous uncertainties in the coastal or harbor area due to the influence of complicated geometric configurations. Thus this paper attempts to forecast the waves based on learning the characteristics of observed waves, rather than the use of the wind information. This is reported in this paper by the application of the artificial neural network (ANN), in which the back-propagation algorithm is employed in the learning process for obtaining the desired results. This model evaluated the interconnection weights among multi-stations based on the previous short-term data, from which a time series of waves at a station can be generated for forecasting or data supplement based on using the neighbor stations data. Field data are used for testing the applicability of the ANN model. The results show that the ANN model performs well for both wave forecasting and data supplement when using a short-term observed wave data.

STANDING WAVE INDUCED PORE PRESSURES IN A POROUS SEABED

Incident waves reflecting normally from a breakwater produce standing waves; they are more conducive in terms of scouring of the seabed than the action of progressive waves. Employing Biots theory of consolidation, the pore pressure response within a porous seabed induced by the standing wave is analytically presented. Experiments for the response are also conducted in a wave flume. Unlike the progressive wave, the variation of standing-wave induced soil response is temporal and spatial. The theories compare well with the experiments.

Calculations of wave transformation across the surf zone

The accuracy of predicting wave transformation in the nearshore is very important to wave hydrodynamics, sediment transport and design of coastal structures. An efficient numerical model based on the time-dependent mild-slope equation is presented in this paper for the estimation of wave deformation across the surf zone. This model incorporates an approximate nonlinear shoaling formula and an energy dissipation factor due to wave breaking to improve the accuracy of the calculation of wave height deformation prior to wave breaking and also in the surf zone. The model also computes the location of first wave breaking, wave recovery and second wave breaking, if physical condition permits. Good agreement is found upon comparison with experimental data over several one-dimensional beach profiles, including uniform slope, bar and step profiles.

Prediction of Storm-Built Beach Profile Parameters Using Neural Network

This study presents the applicability of an artificial neural network for predicting some major parameters of a storm-built beach profile. The prediction model is derived based upon learning the bar profiles obtained from previous large wave tank tests. Back-propagation neural network a supervised learning model, is used in which the interconnection weights in the network are repeatedly adjusted in the learning process in order to achieve the best performance. Base on the proposed neural network model, five major geometric parameters for a storm-built bar profile are predicted for a given wave condition. The results from the neural network model are found to be much accurate than the empirical relationships given by Silvester and Hsu (1993) and Hsu and Wang (1997).

Velocity Fields in Near-Bottom and Boundary Layer Flows in Prebreaking Zone of a Solitary Wave Propagating over a 1:10 Slope

AbstractThe velocity characteristics of a solitary wave shoaling in the prebreaking zone and near the breaking point are investigated experimentally. The study focuses on the near-bottom and boundary layer flows on a 1:10 slope, with the incident wave steepness varying from 0.133 to 0.384. Both a flow visualization technique (FVT) with thin-layered dye as well as particle image velocimetry (PIV) with a high-speed camera were used. Results from FVT reveal that laminar boundary layer flow occurs not only in the prebreaking zone during the shoaling phases, but also in the postbreaking zone during the run-up and run-down phases. However, the laminar boundary layer disappears soon after breaking but before the run-up motion, and immediately after the flow separation followed by hydraulic jump during the later stage of the run-down motion. Results from the PIV measurement show that the maximum horizontal velocity appears under the wave crest and increases during the shoaling process. Flow reversal is observed a...

Downrush flow from waves on sloping seawalls

This paper investigates the characteristics of downrush flow from breaking waves on sloping seawalls, which cause toe scour. Flow visualization techniques were employed in these experiments. The velocity and pressure of the downrush flow at the toe were analyzed. It was found that the intensity of the flow is reduced as the structure slope decreases. The empirical formula for normalized flow intensity at the structure toe is presented as a function of the relative wave run-up height.

Characteristics of Boundary Layer Flow Induced by Solitary Wave Propagating over Horizontal Bottom

Experimental results on the flow characteristics of bottom boundary layer induced by a solitary wave propagating over a horizontal bottom are presented. Particle-trajectory flow visualization technique and high-speed particle image velocimetry (HSPIV) were used to elucidate detailed velocity fields underneath solitary waves with the ratios of wave height to water depth from 0.130 to 0.386. The results show that the velocity profiles can be classified into two classes with respect to the passage of the solitary wave-crest at the measuring section: ＂the pre-passing＂ and ＂post-passing phases＂. For the pre-passing phase, the velocity distributions can be deduced to a unique similarity profile with the use of unsteady free stream velocity and time-dependent boundary layer thickness as the characteristic velocity and length scales. On the other hand, the similarity profile for the flow reversal, acting like an unsteady wall jet, is obtained from the velocity distributions during the post-passing phase. The velocity deficit between the unsteady free stream velocity and the maximum negative velocity as well as the (time-dependent) thickness of reversal flow were identified as the characteristic velocity and length scales, respectively.

A new approach to analyze nonlinear standing waves

Abstract An accurate and simple analysis for nonlinear gravity standing waves is suggested in this paper. The nonlinearity of wave profile is introduced to maintain the implicit function, and the interaction terms are worked out by using the Lagranges expansion method. For the convenience of applications, the relationships between the standing waves and their corresponding source of incident progressing waves are formulated in this study. The results are in good agreement with both the higher order solution and the experimental data performed by predecessors.