Calculation method of ship collision force on bridge using artificial neural network

Ship collision on bridge is a dynamic process featured by high nonlinearity and instantaneity. Calculating ship-bridge collision force typically involves either the use of design-specification-stipulated equivalent static load, or the use of finite element method (FEM) which is more time-consuming and requires supercomputing resources. In this paper, we proposed an alternative approach that combines FEM with artificial neural network (ANN). The radial basis function neural network (RBFNN) employed for calculating the impact force in consideration of ship-bridge collision mechanics. With ship velocity and mass as the input vectors and ship collision force as the output vector, the neural networks for different network parameters are trained by the learning samples obtained from finite element simulation results. The error analyses of the learning and testing samples show that the proposed RBFNN is accurate enough to calculate ship-bridge collision force. The input-output relationship obtained by the RBFNN is essentially consistent with the typical empirical formulae. Finally, a special toolbox is developed for calculation efficiency in application using MATLAB software.

Fast evaluation of ship-bridge collision force based on nonlinear numerical simulation

The max collision force of ship-bridge collision is one of the most importantreferences for bridge design. By mean linear digital simulation method, the collision forces ofthe collisions between rigid bridge pier and ship bow were calculated out for four different ships,whose tonnages are 5 000,10 000,50 000 and 60 000 DWT respectively. Curves of collisionforce-penetration and absorbed energy-penetration are obtained, and the data of the max loads arethen summarized. On the basis of these curves and data, a set of curves describing therelationships between max collision forces and tonnages of the ships are successfully presented, bywhich the max collision forces of the ships-bridge with different tonnages and in differentvelocities can be estimated easily and reliably.

Tsunami Force Reduction due to Obstacle in Front of Coastal Dike and Evaluation of Collision Force by Driftage

Tsunami caused by the Tohoku earthquake on March 11, 2011 washed away a lot of buildings and deprived many lives on unexpected scale. Seawall is one of the measures to reduce tsunami damage, but itself is also given great damages by tsunami. Study on mechanism of tsunami force acting on seawalls is also quite important and improvement of countermeasures is very important. Hydraulic experiments were conducted to estimate wave force and collision force by driftage due to tsunami on various conditions. The tsunami force reduction due to obstacles installed shoreline is examined and assessed by previous formula. Collision force by driftage due to tsunami is also investigated and assessed by previous formula.

Mode filtering based on ponderomotive force nonlinearity in a plasma filled rectangular waveguide

Here a new scheme for mode filtering is proposed. Based on the ponderomotive force effect,propagation of the microwave dual-mode through a plasma-filled metallic rectangular waveguide is investigated. To excite the TE_（20） mode in a rectangular waveguide, the existence of fundamental modes is unavoidable. To filter the destructive mode（TE_（10））, the waveguide is filled with a collisional plasma. Based on the coupling effect, the energy of this destructive TE_（10） mode is transferred to the TE_（20） mode. The proposed structure acts like a mode convertor. The TE_（10） mode become more attenuated and instead the TE_（20） mode is amplified. The plasma filled rectangular waveguide acts as a mode filtering tool.