AI-based shear capacity of FRP-reinforced concrete deep beams without stirrups
| dc.contributor.author | AlHamaydeh, Mohammad | |
| dc.contributor.author | Markou, George | |
| dc.contributor.author | Bakas, Nikos | |
| dc.contributor.author | Papadrakakis, Manolis | |
| dc.contributor.email | george.markou@up.ac.za | en_US |
| dc.date.accessioned | 2023-06-14T11:56:08Z | |
| dc.date.issued | 2022-08 | |
| dc.description | DATA AVAILABILY : All models that support the findings of this study are available from the corresponding author upon reasonable request. | en_US |
| dc.description.abstract | The presented work utilizes Artificial Intelligence (AI) algorithms, to model and interpret the behavior of the fiber reinforced polymer (FRP)-reinforced concrete deep beams without stirrups. This is done by first running an extensive nonlinear finite element analysis (NLFEA) investigation, spanning across the practical ranges of the different input parameters. The FEA modeling is meticulously validated against published experimental results. A total of 93 different models representing a multitude of possible FRP-reinforced deep beam designs are rigorously analyzed. The results are then utilized in building an AI-model that describes the shear capacity for FRP-reinforced deep beams. The study investigates the effect of several factors on the shear capacity and identifies the vital parameters to be used for further model development. Additionally, the developed AI-model is benchmarked against several design standards for blind predictions on new unseen data and design codes, namely: the EC, ACI 440.1R-15, and the modified ACI 440.1R-15 (for size effect). The AI-model demonstrated superior generalization on the blind prediction dataset in comparison to the design codes. | en_US |
| dc.description.department | Civil Engineering | en_US |
| dc.description.embargo | 2024-05-30 | |
| dc.description.librarian | hj2023 | en_US |
| dc.description.sponsorship | The EuroHPC-JU project EuroCC of the European Commission. | en_US |
| dc.description.uri | https://www.elsevier.com/locate/engstruct | en_US |
| dc.identifier.citation | AlHamaydeh, M., Markou, G., Bakas, N. et al. 2022, 'AI-based shear capacity of FRP-reinforced concrete deep beams without stirrups', Engineering Structures, vol. 264, art. 114441, pp. 1-17, doi : 10.1016/j.engstruct.2022.114441. | en_US |
| dc.identifier.issn | 0141-0296 (print) | |
| dc.identifier.issn | 1873-7323 (online) | |
| dc.identifier.other | 10.1016/j.engstruct.2022.114441 | |
| dc.identifier.uri | http://hdl.handle.net/2263/91128 | |
| dc.language.iso | en | en_US |
| dc.publisher | Elsevier | en_US |
| dc.rights | © 2022 Elsevier Ltd. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in Engineering structures. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was subsequently published in Engineering structures, vol. 264, art. 114441, pp. 1-17, doi : 10.1016/j.engstruct.2022.114441. | en_US |
| dc.subject | Nonlinear FEA | en_US |
| dc.subject | Artificial intelligence (AI) | en_US |
| dc.subject | Fiber reinforced polymer (FRP) | en_US |
| dc.subject | Deep beams without stirrups | en_US |
| dc.subject | Finite element analysis (FEA) | en_US |
| dc.subject | SDG-09: Industry, innovation and infrastructure | en_US |
| dc.title | AI-based shear capacity of FRP-reinforced concrete deep beams without stirrups | en_US |
| dc.type | Postprint Article | en_US |