Optimized analysis and reinforcement design model for RC/SCC box-section bridges using developed advanced design framework

In recent years, there has been a significant rise in the construction of reinforced concrete (RC) and steel-concrete composite (SCC) box-section bridges. However, design codes do not provide specific design methods for the RC plates of such bridges where the plates experience both intricate forces and moments. The current design approaches are primarily based on conventional one-dimensional beam element theory, which neglects the complex spatial force characteristics of the structural elements, potentially leading to unsafe design. Therefore, it is imperative to address this issue. To bridge this gap, a comprehensive analysis and reinforcement design procedure named as the developed advanced design framework (DADF) is proposed in this study. The spatial analysis of bridges was performed using a refined numerical model, called the spatial grid model (SGM), to consider the structural spatial effects with limited model scales. Subsequently, the internal force corresponding matrix (IFCM) was implemented through Python scripts to determine the most critical internal force combination for an RC plate element. Additionally, the three-layered sandwich model (T-LSM) was employed with limit analysis to automatically design reinforcement for all elements, serving as a practical tool for design. This research demonstrates that the implementation of the DADF can significantly reduce steel reinforcement in the RC plates of such bridges by up to 48 %, and 23 % in total, showcasing the efficiency of the developed framework. Overall, the findings emphasize that the proposed DADF offers a robust procedure for steel reinforcement design of RC/SCC box-section bridges. •An advanced design framework for the analysis and design of complex box bridges.•spatial response of the bridge be analyzed by Spatial Grid Model with limited-scale.•Considering transverse shear force incorporated in the Basic Sandwich Model.•Automatic design of box bridges through developed Python script linked with SGM.•23 % (up to 48 %) reduction in the reinforcement quantity by the developed method.