Optimization of local stiffener for controlling natural frequency of steel plates

Natural frequency constitutes a critical parameter influencing the dynamic characteristics of structural systems. This study presents a genetic algorithm (GA)-based optimization framework for achieving target vibration frequencies through strategic stiffener layout design in steel plate structures. A parameterized numerical model capable of generating randomly distributed stiffener configurations is developed, incorporating two key design variables: stiffener position coordinates and cross-sectional heights. The proposed methodology integrates finite element analysis with GA to establish optimal stiffener distribution patterns under various boundary conditions. Numerical experiments demonstrate the method's effectiveness in simultaneously satisfying multiple target frequencies beyond the fundamental mode, while maintaining structural feasibility. Particularly noteworthy is the algorithm's capability to handle complex frequency constraints across different support conditions. This research provides practical insights for vibration control design in aging steel structures, offering a systematic approach for performance enhancement through intelligent stiffener configuration.