The design of conceptual schemes for ship hull forms often faces challenges in managing the complex coupling relationships among various design parameters. Traditionally, conceptual schemes for different ship hull forms and corresponding requirements rely heavily on the domain knowledge and engineering experience of ship experts. This approach leads to long design cycles and high costs. Therefore, this study proposes a fuzzy reasoning strategy based on a stack-like structure, aimed at rapidly generating initial solutions for ship conceptual scheme.

This strategy employs fuzzy reasoning based on the user's requirements to derive the performance parameter values of the ship hull that meet the user's requirements. These values are then matched with the design scheme library of the parent ship to obtain the conceptual scheme of the ship hull that meets the user's requirements. Drawing upon the principle of stacked generalization, the method introduces a stack-like structure to systematically combine the initially inferred valid information with the input user requirements in a hierarchical manner. This approach reduces reasoning bias by applying multi-stage verification. Finally, a clustering algorithm is designed to optimize the fusion of the performance parameter library and the parent ship design scheme library. This optimization enhances the rationality of the ship conceptual scheme by establishing quantitative relationships between new designs and proven reference solutions.

The numerical examples demonstrate that both the performance parameters of the ship hull derived through reasoning and the corresponding conceptual schemes effectively address the real needs of users.

To address the significant inference bias in performance parameters observed in existing methods, this study proposes a rapid fuzzy inference system based on a stack-like structure for ship conceptual design. This system enhances computational efficiency while effectively reducing reasoning deviations during the inference process. By leveraging hierarchical reasoning layers, it improves decision-making accuracy in the early stages of ship design. Existing methods for ship conceptual schemes design often result in unreasonable coupling relationships among the solutions generated through reasoning technology. This study thoroughly explores the commonalities between the fuzzy reasoning results and the parent ship, ensuring that the user's requirements are met while eliminating the imbalance in the design parameter coupling of the ship conceptual schemes. As a result, the efficiency and rationality of generating ship conceptual scheme solutions are significantly improved.

This study investigates the dynamic motion and structural response characteristics of ships with large openings in the middle under wave conditions.

Referring to the characteristics of cargo loading and large openings in the middle of container ships, a stiffened plate ship model is designed and manufactured. A series of linear and nonlinear operating condition tests are then conducted in a wave-making tank to measure the elastoplastic deformation of the ship model under the combined action of ballast and waves, as well as stress changes in the deck area.

The results indicate that the appearance of structural plasticity slightly reduces the growth amplitude of the overall pitch motion and prolongs the occurrence time of sagging deformation; the larger the wave amplitude, the more significant the high-frequency vibration of the structure it causes.

For ships with large openings in the middle, the high-frequency stress generated during sagging is greater than that during hogging, and the superposition of low-frequency stress poses a greater threat to ship safety, which needs to be considered in ship design. The proposed ship model can provide valuable references for the study of the plastic collapse of ships in waves.

The structural response and dynamic structural collapse mode of a container ship in waves are studied by fully considering the effects of load nonlinearity and surface nonlinearity.

First, a hydrodynamic model of a container ship is established based on the CFD platform, and the overset grid method is used to realize matching between the dynamic boundary grid of the hull hydrodynamic model and the Euler grid in the far-field fluid domain. The volume of fluid method is used to simulate the nonlinearity of the free surface in the whole fluid domain, and the N–S equations in three directions are solved in the whole flow field domain so as to solve the nonlinear wave load of the ship in real time. A nonlinear finite element model of the ship that can simulate its collapse behavior is then established, and the time-domain collapse response of the ship including plasticity and buckling is calculated based on the explicit dynamic nonlinear finite element method (FEM). Finally, the transmission of fluid pressure and node displacement between the hydrodynamic model and structural finite element model on the wet surface are realized, and two-way iterative coupling between the CFD solver and nonlinear finite element solver is carried out to calculate the nonlinear wave load and structural collapse response during the structural collapse of a 4600 TEU container ship in real time.

Under extreme waves, the upper to middle structures of the container ship are widely plastic, the main deck, side plate, deck longitudinal, side longitudinal and other components have typical yield instability under the action of wave loads, the deck longitudinal, side longitudinal and other structural members have serious lateral instability, and the hull structure loses its bearing capacity.

The proposed CFD nonlinear FEM can accurately solve the structural response and dynamic collapse mode, making it viable as a new approach to studying the collapse response of ship structures.

The method of rewriting the element node information file to realize parametric modeling is commonly employed in existing structural optimization based on finite element (FE) strength calculation, but it remains difficult to consider variations of the profile number in hull section structure optimization. To this end, a container ship structure optimization method based on FE strength calculation is proposed using an artificial bee colony (ABC) algorithm and parametric FE modeling method.

First, the bee colony algorithm is written on the Matlab platform, and a script file which can generate the geometric model in its CAE module is established based on the ABAQUS kernel in the Python language. A Python script file which can submit the FE calculation and read the results is established. The geometric model is updated by rewriting the solution generated by the algorithm to the corresponding position in the script, then ABAQUS is called in the background and the script files are run in turn. Finally, the calculation results are returned to Matlab for verification, and the parametric geometric modeling and FE analysis are completed.

The feasibility of this method is verified by taking the section structure optimization of a 4600 TEU container ship as an example. It is found that the weight reduction of the container ship cabin structure reaches 18.7%.

When the results of the FE strength optimization and code optimization are compared and analyzed, under the set conditions, the FE optimization method is more sufficient than that based on code.