Abstract
In the mathematical model with multiple input variables, the sensitivity analysis of the input variables is an important step to ensure the reliability of the mathematical model. In order to optimize the ship manoeuvring simulation, in particular the optimization of the trajectory ship, the sensitivity analysis should be performed in the mathematical model to select the group of the most sensitive hydrodynamic coefficients. In this paper, the author applied the sensitivity analysis method in mathematics model of ship manoeuvring programming in order to optimize the ship trajectory of Esso Bernicia 193000DWT tanker model.
Highlights
According to the achieved result of K.T Tran et al [1], to optimise the ship trajectory by minimizing the deviation of ship position and manoeuvring parameters, ship trajectories optimization problem turned into the problem of ship hydrodynamics coefficients optimization because of in such case the hydrodynamics coefficient become the variables of deviation functions.Since the very large number of variables and the influences of these on the objective functions are not the same, it is necessary to analyse the variable sensitivity to identify the most sensitivity variables
The author has written a sensitivity analysis program using Matlab to evaluate the influence of input variables on the variation of objective function Fobj in each test: Turning Circle and Zigzag [1,2,3]
The important input factors consist of: The number of hydrodynamic parameters taken into analysing sensitivity: The total number of hydrodynamic parameters is 35 (Table 1)
Summary
According to the achieved result of K.T Tran et al [1], to optimise the ship trajectory by minimizing the deviation of ship position and manoeuvring parameters, ship trajectories optimization problem turned into the problem of ship hydrodynamics coefficients optimization because of in such case the hydrodynamics coefficient become the variables of deviation functions (objective function). Since the very large number of variables and the influences of these on the objective functions are not the same, it is necessary to analyse the variable sensitivity to identify the most sensitivity variables (corresponding the Step 2 in the flowchart of the ship trajectory optimization procedure, Fig.). Due to the complexity of the mathematic model in the computational program, reducing number of variables may increases the convergence of defining the variables’ optimal values, and simultaneously reduces the amount of iteration steps to quickly reach the minimum values of objective functions, decreases the calculation time of that programme
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