Parametric modeling for automated intelligent design of concrete beam bridges: A global and local optimization approach

Abstract The structural design of prestressed concrete girders in beam bridges is performed by coupling 3D parametric modeling, optimization, and statistical techniques, structural analysis, and design. The objective is to explore the potential and advantages of advanced design methodologies based on intelligent design. The full 3D parametric beam bridge is modeled in the software Rhinoceros (computer‐aided design)/Grasshooper (algorithm‐aided design). An optimization procedure using a genetic algorithm is adopted to find the minimum number of supports. With the 3D bridge configuration, static and modal finite element analyses are performed using the Karamba3D plugin to extract the internal forces of the prestressed girders. After that, the Ultimate and Serviceability Limit States are checked by plugging the non‐linear design equilibrium equations in a Python script directly into Grasshopper. The Simplex method is used to determine the feasible domain (space of solutions) allowing the choice of the most appropriate pair of girder height and prestressing force.