Author(s): Markus Reinhardt, Claudia Vogel, Tobias Schneider and Elena Krauss

Abstract: Steel-concrete composite bridge decks are increasingly preferred in modern bridge construction due to their superior stiffness-to-weight ratio and efficient load distribution. However, traditional design approaches often overlook the influence of dynamic vehicular loading and vehicle-bridge interaction (VBI), resulting in conservative or unsafe performance predictions. This study presents an integrated framework for the optimization of steel-concrete composite bridge decks under dynamic vehicular loading using finite element modeling and multi-objective optimization techniques. The research develops a comprehensive dynamic vehicle-bridge interaction model based on a three-dimensional finite element approach, incorporating realistic pavement roughness profiles, varying vehicle speeds, and nonlinear shear connector behavior. A multi-objective genetic algorithm (MOGA) was employed to minimize deck weight and cost while maximizing stiffness and fatigue life under variable traffic conditions. The optimized configurations demonstrated an average reduction of 10-14% in midspan displacement, 9-11% in stress, and up to 18% in connector slip, with a corresponding 30% decrease in fatigue damage compared to baseline designs. Statistical regression analysis (R² = 0.991) confirmed strong correlations between dynamic amplification factors, speed, and surface conditions. The results indicate that optimization accounting for dynamic effects enhances safety, durability, and material efficiency without compromising serviceability. This research concludes that integrating dynamic vehicular effects within design and optimization frameworks offers a viable pathway for performance-based bridge engineering. It provides practical recommendations for incorporating vehicle-bridge interaction analysis and optimization tools into routine design practice, thereby advancing sustainable, cost-effective, and resilient bridge infrastructure.

Pages: 43-47 | Views: 5 | Downloads: 2

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