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Forecasting of excavation problems for high-rise building in Vietnam using planet optimization algorithm
In this paper, a new method in forecasting the horizontal displacement of diaphragm wall (D.W.) for high-rise buildings is introduced. A new stochastic optimizer, called Planet Optimization Algorithm (P.O.A.), is employed to assess how proper finite element (F.E.) simulation is against field data. T...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8664942/ https://www.ncbi.nlm.nih.gov/pubmed/34893674 http://dx.doi.org/10.1038/s41598-021-03097-y |
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author | Sang-To, Thanh Hoang-Le, Minh Khatir, Samir Mirjalili, Seyedali Wahab, Magd Abdel Cuong-Le, Thanh |
author_facet | Sang-To, Thanh Hoang-Le, Minh Khatir, Samir Mirjalili, Seyedali Wahab, Magd Abdel Cuong-Le, Thanh |
author_sort | Sang-To, Thanh |
collection | PubMed |
description | In this paper, a new method in forecasting the horizontal displacement of diaphragm wall (D.W.) for high-rise buildings is introduced. A new stochastic optimizer, called Planet Optimization Algorithm (P.O.A.), is employed to assess how proper finite element (F.E.) simulation is against field data. The process is adopted for a real phased excavation measured at the field. To automatically run the iterative optimization tasks, a source code is constructed directly in the Geotechnical Engineering Software (PLAXIS) by using Python to ensure that the operation between optimization algorithm and F.E. simulations are smooth to guarantee the accuracy of the complex calculation for the soil problem. The proposed process consists of two steps. (1) The parameters will be optimized at the early phases of the excavation. (2) The responses of D.W. displacements are forecasted at the subsequent phases. The aim of the process is to predict the displacements of D.W. of the building from the result of the nearby excavation or to provide early warning about the risks of excavation that may happen under vital phases. The proposed procedure also provides an effective method for optimization-based soil parameters updating in real engineering practice. |
format | Online Article Text |
id | pubmed-8664942 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-86649422021-12-15 Forecasting of excavation problems for high-rise building in Vietnam using planet optimization algorithm Sang-To, Thanh Hoang-Le, Minh Khatir, Samir Mirjalili, Seyedali Wahab, Magd Abdel Cuong-Le, Thanh Sci Rep Article In this paper, a new method in forecasting the horizontal displacement of diaphragm wall (D.W.) for high-rise buildings is introduced. A new stochastic optimizer, called Planet Optimization Algorithm (P.O.A.), is employed to assess how proper finite element (F.E.) simulation is against field data. The process is adopted for a real phased excavation measured at the field. To automatically run the iterative optimization tasks, a source code is constructed directly in the Geotechnical Engineering Software (PLAXIS) by using Python to ensure that the operation between optimization algorithm and F.E. simulations are smooth to guarantee the accuracy of the complex calculation for the soil problem. The proposed process consists of two steps. (1) The parameters will be optimized at the early phases of the excavation. (2) The responses of D.W. displacements are forecasted at the subsequent phases. The aim of the process is to predict the displacements of D.W. of the building from the result of the nearby excavation or to provide early warning about the risks of excavation that may happen under vital phases. The proposed procedure also provides an effective method for optimization-based soil parameters updating in real engineering practice. Nature Publishing Group UK 2021-12-10 /pmc/articles/PMC8664942/ /pubmed/34893674 http://dx.doi.org/10.1038/s41598-021-03097-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Sang-To, Thanh Hoang-Le, Minh Khatir, Samir Mirjalili, Seyedali Wahab, Magd Abdel Cuong-Le, Thanh Forecasting of excavation problems for high-rise building in Vietnam using planet optimization algorithm |
title | Forecasting of excavation problems for high-rise building in Vietnam using planet optimization algorithm |
title_full | Forecasting of excavation problems for high-rise building in Vietnam using planet optimization algorithm |
title_fullStr | Forecasting of excavation problems for high-rise building in Vietnam using planet optimization algorithm |
title_full_unstemmed | Forecasting of excavation problems for high-rise building in Vietnam using planet optimization algorithm |
title_short | Forecasting of excavation problems for high-rise building in Vietnam using planet optimization algorithm |
title_sort | forecasting of excavation problems for high-rise building in vietnam using planet optimization algorithm |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8664942/ https://www.ncbi.nlm.nih.gov/pubmed/34893674 http://dx.doi.org/10.1038/s41598-021-03097-y |
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