m (Lfvm94 moved page Draft Verduzco Martinez 745304701 to Verduzco Martinez Zaragoza 2021a) |
|||
Line 2: | Line 2: | ||
== Abstract == | == 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 | + | 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. |
== Full document == | == Full document == | ||
<pdf>Media:Draft_Verduzco Martinez_745304701-3648-document.pdf</pdf> | <pdf>Media:Draft_Verduzco Martinez_745304701-3648-document.pdf</pdf> |
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.
Published on 01/01/2021
Licence: CC BY-NC-SA license
Are you one of the authors of this document?