A Study On The Multi-objective Optimization Of The Whole-ship Structure With Considerations For Dynamic Response Characteristics

By far, ship structural optimization problems are mainly limited to the midship cross-section and local structures, such as the hatch cover, frame, grillage and bulkhead, and are always solved as single-objective optimization problem of minimizing the structural weight with static strength constraint (and frequency constraint). However, with the power of the main engine becoming more powerful and the extensive use of the high-strength steel in ship constructions, it is more prone for ship structures to have harmful vibrations, so it's necessary to take its dynamic response characteristics into account when optimizing the ship structure. Taking a self-propelled cutter suction dredger as the study object, we studied the multi-objective optimization problem of optimizing dynamic response characteristics and the whole-ship structural weight in this paper. To be detailed, we mainly explored the following problems:(1)The choice of the analysis model. The frequency response analysis required by the whole-ship structural dynamic response characteristics analysis is quite time-consuming, so choosing an appropriate analysis model to improve the optimizing efficiency is the principal task.In this paper, we proposed the method of converting the 3D FE model into the mixed FE model within the database seamlessly to solve the problem.(2)The prediction of the vibration response of aft structures. Based on summarizing empirical formulae of calculating the forces induced by propellers briefly, we choosed the Holden method as the way to estimate the pressure pulse induced by propellers, and focused on how to apply the pressure pulse to the ship hull surface as a spatial field.(3)Constructing the optimization platform in the Isight 5.0 software. We explored the way of modifying the member sizes, extracting the structural weight and acceleration response adequately, and diged deep into the measures of improving the optimizing efficiency.(4)Solving the multi-objective optimizing model, analyzing and comparing optimizing results, choosing the optimum structure. We solved the multi-objective optimizing model using the NSGA-II, AMGA and NCGA belong to the direct method and the main objective method and the linear weighted sum method belong to the indirect method, and compared the optimizing effect of each optimizing method.