To enhance the application effectiveness of the decomposition-based optimization method in the large-scale optimization design of ship cabin structures, a constraint progressive relaxation adjustment strategy and a computational resource allocation strategy are proposed that consider both the contribution of the sub-problem to the objective and the margin of constraints of the sub-problem.

Constraint progressive relaxation adjustment strategy: initially, a tightened constraint boundary is given and then gradually relaxed until it recovers to the original constraint boundary, enabling all sub-problems to be more fully optimized. Computational resource allocation strategy: optimization computing resources are comprehensively allocated based on the contribution of the sub-problem to the objective and the margin of constraints of the sub-problem. The two strategies are then combined and their coupling effects analyzed.

Compared with the original algorithm, under the same computational resources, the cabin weight is reduced by 10.3% and 7.0% when using the constraint progressive relaxation adjustment strategy and computational resource allocation strategy respectively, and the weight is reduced by 22.2% when both strategies are applied simultaneously, relative to the weight obtained by the original optimization method.

The proposed strategies are effective and possess value for the decomposition-based large-scale optimization of ship structures.

This paper proposes a domain knowledge-driven large-scale optimization algorithm for ship cabin structures based on a decomposition optimization framework.

The proposed algorithm combines domain mechanical knowledge with a general black box optimization algorithm, groups the design variables into location variables and size variables, and decomposes the original problem into a series of low-dimensional subproblems. Due to the monotonicity and locality of each bending stress, shear stress, and deformation constraint, subproblems with larger constraint margins are prioritized for optimization. All of the location variables are grouped into one subproblem, and the corresponding subproblem's objective function is to maximize the minimum constraint margin. Each girder size variable is separately grouped, and the corresponding subproblem's objective function is the weight of the cabin structure. Additionally, a surrogate model is introduced to quickly predict the constraints of each subproblem, and the sample infill criterion is adopted only in the constraint surrogate model.

The experimental results show that the algorithm can reduce the overall weight of the cabin structure by 43.5% compared to the upper bound.

The proposed algorithm has higher optimization efficiency and can obtain a better optimization solution compared to both the differential evolution algorithm directly using the using finite element method and the general black box optimization algorithm.

In order to explore the characteristics of optimization design schemes of titanium alloy double layer stiffened cylindrical shell structures under different length-to-diameter ratios and calculation pressures, a mathematical model for the lightweight optimization of such structures is established.

The main control program of the genetic algorithm is established in MATLAB, and the ultimate bearing capacity is calculated and checked by finite element software ANSYS. The differences of optimization schemes between titanium alloy single layer stiffened cylindrical shells and titanium alloy double layer stiffened cylindrical shells under different length-to-diameter ratios and different calculation pressures are then compared and analyzed.

There are two critical calculation pressures in the optimization design of titanium alloy stiffened cylindrical shells, and the optimization design is divided into three types: the stability constraint type of ultimate bearing capacity constraint control optimization design, the strength constraint type of strength constraint control optimization design, and the joint constraint type of strength and ultimate bearing capacity constraint joint control optimization design. The larger the length-to-diameter ratio, the greater the critical calculation pressure. Under the same calculation pressure and length-to-diameter ratio, the weight of the double layer shell optimization scheme is lighter than that of the single layer shell, and the critical calculation pressure of the double layer shell optimization design is smaller than that of the single layer shell under the same length-to-diameter ratio.

The results of this study can provide useful references for the optimization design of titanium alloy double layer stiffened cylindrical shell structures.

In order to explore the effects of different stiffening configurations on the bearing capacity and anti-blast performance of double stiffened cylindrical shells, a numerical study is made of the responses of four kinds of double stiffened cylindrical shells under hydrostatic pressure and underwater explosion load.

First, finite element models of stiffened cylindrical shells with different structural forms are established. Next, finite element software ANSYS is used to calculate and analyze the influence of each structural form on the strength, stability and ultimate bearing capacity of the cylindrical shell. Finally, finite element software Abaqus/Explicit is used to calculate and analyze the influence of each structural form on the deformation deflection and plastic strain of the cylindrical shell under explosion load.

Compared with a traditional single stiffened cylindrical shell with the same mass, the I-shaped double stiffened cylindrical shell has a great advantage in carrying capacity. When the explosion load level is low, the anti-blast performance of a double cylindrical shell with small rib spacing is similar, but decreases when the explosion load level is high.

The reasonable design of double stiffened cylindrical shells can yield better design schemes for bearing capacity and anti-blast performance.

This paper aims to discuss the relationship between the ultimate bearing capacity of a pressure hull and pressure tank under the same strength margin, and obtain a matching design with the equivalent ultimate bearing capacity and strength margins accordingly.

To this end, a typical external pressure tank is taken as the research object. On the basis of evaluating the stability and ultimate bearing capacity of the initial structural scheme, the influences of the thicknesses of the pressure tank shell, solid floor and transverse bulkhead on the ultimate bearing capacity are studied. The initial scheme is then adjusted to obtain a scheme with the equivalent strength margins of the pressure hull and pressure tank. In this context, the relationship between the ultimate bearing capacity of the pressure hull and pressure tank is discussed. By strengthening the pressure hull to match the ultimate bearing capacities of the pressure tank and pressure hull, the corresponding strength margins are obtained.

The results show that thinning the pressure tank shell by 30%, solid floor shell by 33.3% and transverse bulkhead shell by 30% reduces the ultimate bearing capacity of the tank by 16.5%, 36.4% and 0.17% respectively.

As further analyses show, under the condition of the same strength margin, the ultimate bearing capacity of the pressure hull is much lower than that of the pressure tank. When the strength margin of the pressure tank is about 25% and that of the pressure hull is about 40%, the ultimate bearing capacities of the pressure hull and pressure tank are roughly the same.

The effects of the thickness of the face plate, angle of the wall plate and height of the core layer on the anti-explosion performance of carbon fiber reinforced composite trapezoidal corrugated sandwich structures were investigated.

First, based on the 3D Hashin failure criterion, a subroutine module of the damage evolution of fiber reinforced composites is developed using the VUMAT user subroutine interface in ABAQUS. Second, through comparison with experiments in the public literature, the effectiveness of the dynamic response simulation method of carbon fiber reinforced composites based on a development subroutine under explosion impact loading is verified. Finally, a parametric study on the explosion resistance of carbon fiber reinforced composite trapezoidal corrugated plates is carried out based on the numerical method.

The results show that, compared with increasing the thickness of the blast face panel, increasing the thickness of the back blast face panel can improve the explosion resistance of the sandwich plate more obviously; when the folding angle of the core wall plate decreases from 45° to 30°, the explosion resistance increases by 1.3%; when it decreases from 60° to 45°, the explosion resistance increases by 6.3%; and when the core height increases from 8 mm to 20 mm, the explosion resistance increases by 27.7%.

The results of this study can provide references for the explosion-proof design of carbon fiber reinforced composite sandwich structures.

A spherical bulkhead with openings has many structural parameters, and it is time-consuming and laborious to directly use the finite element method to carry out parameter research. Therefore, a combined surrogate model method for predicting characteristic stresses is proposed.

The geometric characteristic parameters of an opening spherical bulkhead are extracted and used as design variables to construct a surrogate model for the characteristic stresses of a spherical bulkhead with a single opening. After analyzing the correlation between the characteristic stresses and structural parameters using the surrogate model, a combined surrogate model method with lower dimensions of design variables is proposed. The combined surrogate model consists of a surrogate model of characteristic stresses based on the parameters of a cylindrical-toroidal-spherical shell and a surrogate model of characteristic stress correction coefficients based on the opening fence parameters and thickness of the spherical shell.

The results show that the accuracy of the combined surrogate model is significantly improved due to the lower dimensions of design variables. Compared with the results of the directly constructed surrogate model, the maximum error and average error of the characteristic stresses are reduced by 4.96%–22.95% and 0.59%–5.43% respectively. The single-opening combination surrogate model is used to predict the characteristic stresses of a typical spherical bulkhead with multiple openings, and the prediction errors of the characteristic stresses are 0.12%–11.42%.

The proposed combined surrogate model for the strength of a spherical bulkhead with a single opening can be used for the rapid prediction of the characteristic stresses of spherical bulkheads with multiple openings.

As solving the robust optimization (RO) problem with interval uncertainty is unduly time-consuming when the nested differential evolution algorithm is directly used, a new RO design method is proposed.

In the proposed method, individuals' response values that have been accurately calculated within the critical distance are used to approximately predict the response values of other individuals and evaluate the robustness indexes accordingly. The accurate information of individuals' response values, which is gradually expanded in the evolutionary procedure, is also used to selectively re-evaluate the past robustness of individuals, and the critical distance is adaptively reduced on the basis of the robustness misjudgment rate.

Two numerical and one engineering examples are tested to demonstrate the applicability of the proposed algorithm. The results show that the proposed algorithm saves more than 94% of computational resources, while the estimated error is less than 2.5%.

The proposed method can greatly reduce the calculation time of individuals' response values in the evolution process and maintain the adaptive balance between the accuracy and cost of robustness evaluation by using previous optimization knowledge, providing a new idea and method for RO design with interval uncertainty.