Post-buckling Strength of Welded Steel I-Girders with Corrugated Webs

Lin, Xuqun; Far, Harry

doi:10.1007/s13296-021-00477-y

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…Because the SGA can only deal directly with unconstrained optimization problems, it requires the transformation of the constraint problem into an unconstrained problem via the penalty function [10], as shown in Equation (8).…”

Section: Penalty Functionmentioning

confidence: 99%

“…As a new type of structure with two face sheets and a cell core, corrugated sandwich panels have often been used to replace traditional metal components to reduce weight. Corrugated sandwich panels offer many advantages, such as lightness, low construction cost, high specific strength, effective sound insulation, high energy absorption efficiency, and strong impact resistance [4][5][6][7][8][9]. Hence, corrugated steel sandwich panels are being used in ship construction, for example, in the Visby class corvettes built by the Swedish Navy [10], in the European research project SANDWICH [11], and in the smooth components of ships [12].…”

Section: Introductionmentioning

confidence: 99%

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Multi-Objective Optimization Design of Corrugated Steel Sandwich Panel for Impact Resistance

Liu

Guang-ming

et al. 2021

Metals

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The application of corrugated steel sandwich panels on ships requires excellent structural performance in impact resistance, which is often achieved by increasing the weight without giving full play to the characteristics of the structure. Considering the mechanical properties of sandwich panels under static and impact loading, a multi-objective optimal method based on a back-propagation (BP) neural network and a genetic algorithm developed in MATLAB is proposed herein. The evaluation criteria for this method included structural mass, static and dynamic stress, static and dynamic deformation, and energy absorption. Before optimization, representative sample points were obtained through numerical simulation calculations. Then, the functional relationship between the design and output variables was generated using the BP neural network. Finally, a standard genetic algorithm (SGA) and an adaptive genetic algorithm (AGA) were used for multi-objective optimization analysis with the established function to obtain the best result. Through this study, a new design concept with high efficiency and reliability was developed to determine the structural parameters that provide the best impact resistance using limited sample points.

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Section: Penalty Functionmentioning

confidence: 99%