Abstract

In the present work the development and application of an optimal design process for reinforced concrete frames is exposed, taking on account optimal distributions of reinforcing bars in the structural elements under free-clash and slap reinforcement criteria, aside of other restriction by code specifications (ACI-318 and NTC-17) such as minimum separation and maximum reinforcement area, through visual programming in ANSYS Space-Claim using Python language for the automatic generation of detail CAD drawings. Artificial Intelligence is employed with the meta-heuristic Particle Swarm Optimization algorithm (PSO) given its rapid convergence to find optimal dimensions of the elements for a structural frame, and the Steepest Gradient Descent Method (SGD) was used along with the Idealized Smeared Reinforcement analogy (ISR) to find optimal distributions of rebar in such elements through simple search, considering symmetric reinforcement in columns. Only one numerical structural model was built for experimentation under two different design approaches for comparison: one under free-clash and slap reinforcement criteria and another without considering such criteria. Results show a great influence in the optima convergence of dimensions by considering such reinforcement criteria, Besides, great final visual detailing results of such reinforcement are obtained, demonstrating thus, that it is possible to generate with the technology nowadays available more accurate models for civil infrastructure that may represent better construction conditions under which structures are subject to.

Abstract

The present work exposes the design of optimization procedures both with the “Particle Swarm Optimization” (PSO) algorithm and the “Genetic Algorithm” (GA) for the design of reinforced concrete frames, making comparisons in cost, weight of the structure and predicted damage. The optimization procedures are built up using the “Idealized Smeared Reinforcement” (ISR) analogy for each element of the structural model frames considered for this work. Two different numerical structural plane-frame models were created for the application and comparison of the performance of the optimization design procedures hereby proposed. The optimization procedures were mono-objective with a cost-objective function, taking on account steel reinforcement and concrete for the cost computation. Two different design approaches were carried on for this work, one proposing asymmetrical reinforcement for columns and the other with symmetrical reinforcement. In order to compute the damage indices considered for this study a non-linear Pushover structural analysis is performed. Results show that asymmetrical reinforcement in columns may reduce concrete volumes, although such reduction in material might not be quite proportional with construction cost, given that asymmetric reinforcement in columns is more expensive than symmetrical, per unit-cost. The bigger the structure, the more likely is to obtain lighter structures by using asymmetrical reinforcement. Regarding damage of the structure, results show that when using asymmetrical reinforcement in columns, it is more likely to obtain smaller values for the expected damage with no great difference on the estimated collapse Safety Factors for the seismic loads. In general, the proposed methodology hereby proposed enhances quite good optima results, requiring only a few adjustments of clash-free and slap reinforcement after the optimization procedure terminates. When designing reinforced concrete frames with asymmetric reinforcement in columns, an increase in construction costs of as much as $25\%$ as that obtained for symmetric reinforcement could be enhanced. In general, with the proposed methodology to optimally design reinforced concrete frames, savings of as much as $20\%$ in construction costs from an initial structural proposal can be reached.