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Prediction and forewarning of axial force of steel bracing in foundation pit based on verhulst model

The axial force of steel bracing is one of the essential indexes to measure the stability of the bracing system of a foundation pit. The steel bracing system of a foundation pit in Ningbo City, China was taken as the research object to guarantee the stability of the steel bracing system of the found...

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Autores principales: Chen, Huan, Zhang, Ke, Jiang, Yibo, Shi, Zheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8956196/
https://www.ncbi.nlm.nih.gov/pubmed/35333895
http://dx.doi.org/10.1371/journal.pone.0265845
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author Chen, Huan
Zhang, Ke
Jiang, Yibo
Shi, Zheng
author_facet Chen, Huan
Zhang, Ke
Jiang, Yibo
Shi, Zheng
author_sort Chen, Huan
collection PubMed
description The axial force of steel bracing is one of the essential indexes to measure the stability of the bracing system of a foundation pit. The steel bracing system of a foundation pit in Ningbo City, China was taken as the research object to guarantee the stability of the steel bracing system of the foundation pit. Besides, the change of axial force between the two steel bracing structures was analyzed to predict the axial force data of the steel bracing and perform the safety forewarning of the steel bracing system. Firstly, GM (1,1) and Verhulst models in the gray model were selected for prediction based on the characteristics of poor information and the small sample size of original monitoring data of the steel bracing. Secondly, the precision of the GM (1,1) model and Verhulst model was compared to determine a more accurate prediction method. Finally, the safety forewarning model of the confidence interval estimation method was established based on the data obtained from the prediction model and the deformation characteristics and indexes of the steel bracing. With the significance levels α = 5% and α = 2% as the demarcating points, the forewarning grades of the steel bracing system of the deep foundation pit were divided, and then the operating state of the current steel bracing system was determined. The results demonstrated that the Verhulst model had better prediction precision compared with the ordinary GM (1, 1) model. Besides, the steel bracing system was in the safe operation range, and the judgment results of the model were consistent with the actual situation of the foundation pit of the steel bracing system. Thus, the Verhulst prediction model and the confidence interval security early forewarning model could be used to judge the stability of the steel bracing system.
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spelling pubmed-89561962022-03-26 Prediction and forewarning of axial force of steel bracing in foundation pit based on verhulst model Chen, Huan Zhang, Ke Jiang, Yibo Shi, Zheng PLoS One Research Article The axial force of steel bracing is one of the essential indexes to measure the stability of the bracing system of a foundation pit. The steel bracing system of a foundation pit in Ningbo City, China was taken as the research object to guarantee the stability of the steel bracing system of the foundation pit. Besides, the change of axial force between the two steel bracing structures was analyzed to predict the axial force data of the steel bracing and perform the safety forewarning of the steel bracing system. Firstly, GM (1,1) and Verhulst models in the gray model were selected for prediction based on the characteristics of poor information and the small sample size of original monitoring data of the steel bracing. Secondly, the precision of the GM (1,1) model and Verhulst model was compared to determine a more accurate prediction method. Finally, the safety forewarning model of the confidence interval estimation method was established based on the data obtained from the prediction model and the deformation characteristics and indexes of the steel bracing. With the significance levels α = 5% and α = 2% as the demarcating points, the forewarning grades of the steel bracing system of the deep foundation pit were divided, and then the operating state of the current steel bracing system was determined. The results demonstrated that the Verhulst model had better prediction precision compared with the ordinary GM (1, 1) model. Besides, the steel bracing system was in the safe operation range, and the judgment results of the model were consistent with the actual situation of the foundation pit of the steel bracing system. Thus, the Verhulst prediction model and the confidence interval security early forewarning model could be used to judge the stability of the steel bracing system. Public Library of Science 2022-03-25 /pmc/articles/PMC8956196/ /pubmed/35333895 http://dx.doi.org/10.1371/journal.pone.0265845 Text en © 2022 Chen et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Chen, Huan
Zhang, Ke
Jiang, Yibo
Shi, Zheng
Prediction and forewarning of axial force of steel bracing in foundation pit based on verhulst model
title Prediction and forewarning of axial force of steel bracing in foundation pit based on verhulst model
title_full Prediction and forewarning of axial force of steel bracing in foundation pit based on verhulst model
title_fullStr Prediction and forewarning of axial force of steel bracing in foundation pit based on verhulst model
title_full_unstemmed Prediction and forewarning of axial force of steel bracing in foundation pit based on verhulst model
title_short Prediction and forewarning of axial force of steel bracing in foundation pit based on verhulst model
title_sort prediction and forewarning of axial force of steel bracing in foundation pit based on verhulst model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8956196/
https://www.ncbi.nlm.nih.gov/pubmed/35333895
http://dx.doi.org/10.1371/journal.pone.0265845
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