Parallel processing based on ship maneuvering in identification of interaction force coefficients

Abstract

The parallel processing based on the free running model test was adopted to predict the interaction force coefficients (flow straightening coefficient and wake fraction) of ship maneuvering. And the multi-population genetic algorithm (MPGA) based on real coding that can contemporarily process the data of free running model and simulation of ship maneuvering was applied to solve the problem. Accordingly the optimal individual was obtained using the method of genetic algorithm. The parallel processing of multi-population solved the prematurity in the identification for single population, meanwhile, the parallel processing of the data of ship maneuvering (turning motion and zigzag motion) is an attempt to solve the coefficient drift problem. In order to validate the method, the interaction force coefficients were verified by the procedure and these coefficients measured were compared with those ones identified. The maximum error is less than 5%, and the identification is an effective method.