Prediction of the Load-Bearing Behavior of SPSW with Rectangular Opening by RBF Network
dc.contributor.author | Mohammad Javad, Moradi | |
dc.contributor.author | Roshani, Mohammad Mahdi | |
dc.contributor.author | Shabani, Amirhosein | |
dc.contributor.author | Kioumarsi, Mahdi | |
dc.date.accessioned | 2020-07-14T16:15:08Z | |
dc.date.accessioned | 2020-08-07T09:07:34Z | |
dc.date.available | 2020-07-14T16:15:08Z | |
dc.date.available | 2020-08-07T09:07:34Z | |
dc.date.issued | 2020-02-10 | |
dc.identifier.citation | Mohammad Javad, Roshani, Shabani A, Kioumarsi M. Prediction of the Load-Bearing Behavior of SPSW with Rectangular Opening by RBF Network. Applied Sciences. 2020 | en |
dc.identifier.issn | 2076-3417 | |
dc.identifier.issn | 2076-3417 | |
dc.identifier.uri | https://hdl.handle.net/10642/8820 | |
dc.description.abstract | As a lateral load-bearing system, the steel plate shear wall (SPSW) is utilized in different structural systems that are susceptible to seismic risk and because of functional reasons SPSWs may need openings. In this research, the effects of rectangular openings on the lateral load-bearing behavior of the steel shear walls by the finite element method (FEM) is investigated. The results of the FEM are used for the prediction of SPSW behavior using the artificial neural network (ANN). The radial basis function (RBF) network is used to model the effects of the rectangular opening in the SPSW with different plate thicknesses. The results showed that the opening leads to reduced load-bearing capacity, stiffness and absorbed energy, which can be precisely predicted by employing RBF network model. Besides, the suitable relative area of the opening is determined. | en |
dc.language.iso | en | en |
dc.publisher | MDPI | en |
dc.relation.ispartofseries | Applied Sciences;Volume 10 / Issue 3: Special Issue - Soft Computing Techniques in Structural Engineering and Materials | |
dc.rights | © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). | en |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.subject | Artificial neural networks | en |
dc.subject | Steel shear walls | en |
dc.subject | Finite element methods | en |
dc.subject | Openings | en |
dc.subject | Radial basis functions | en |
dc.title | Prediction of the Load-Bearing Behavior of SPSW with Rectangular Opening by RBF Network | en |
dc.type | Journal article | en |
dc.type | Peer reviewed | en |
dc.date.updated | 2020-07-14T16:15:08Z | |
dc.description.version | publishedVersion | en |
dc.identifier.doi | https://dx.doi.org/10.3390/app10031185 | |
dc.identifier.cristin | 1819430 | |
dc.source.journal | Applied Sciences |
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Med mindre annet er angitt, så er denne innførselen lisensiert som © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).