Optimum design of reinforced concrete space frame systems by metaheuristic algorithms

The primary objective of a design engineer in the field of civil engineering is to ensure the structural safety of a structure under applied loads in accordance with regulations and standards while also achieving the most cost-effective design. In the design of complex structures such as reinforced concrete frame systems optimization algorithms are utilized in the field of civil engineering to achieve optimal cost efficiency. This thesis aims to enable the faster and more accurate determination of the optimal cost design for reinforced concrete frame systems. Within the scope of this thesis, a total of five optimization algorithms have been used, including three different metaheuristic optimization algorithms and two hybrid optimization algorithms derived from these metaheuristics. To determine the displacements and section forces of reinforced concrete frame systems, the matrix displacement method has been used and the design guidelines provided by the ACI 318-19 (Building Code Requirements for Structural Concrete and Commentary) code have been considered. In this study, a total of five different reinforced concrete structures, both symmetric and asymmetric, with varying numbers of elements and different building sizes, have been modeled. The internal forces and displacement values of the structures solved using the matrix displacement method in the MATLAB program are verified with the SAP2000 structural analysis software, confirming the accuracy of the solutions. Teaching-Learning-Based Optimization (TLBO), among the five different optimization algorithms used for optimal design is found to be suitable for reinforced concrete frame systems. The design method and Teaching-Learning-Based Optimization (TLBO) algorithm utilized in this thesis provide civil engineers with the opportunity to obtain designs that are both cost-optimal and structurally safe in a fast and efficient approach. The developed method assists engineers in solving complex design problems efficiently while simultaneously providing the optimal structural solution in terms of both cost and structural safety.