Cargando…

Determination of Prestress Losses in Existing Pre-Tensioned Structures Using Bayesian Approach

Deterioration of materials and structures is an unavoidable fact, and prestressed concrete structures are not an exception. The evaluation of load-carrying capacity and remaining service life includes collecting various information. However, one type of information is essential and the most importan...

Descripción completa

Detalles Bibliográficos
Autores principales: Moravčík, Martin, Kraľovanec, Jakub
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9145248/
https://www.ncbi.nlm.nih.gov/pubmed/35629575
http://dx.doi.org/10.3390/ma15103548
_version_ 1784716242662195200
author Moravčík, Martin
Kraľovanec, Jakub
author_facet Moravčík, Martin
Kraľovanec, Jakub
author_sort Moravčík, Martin
collection PubMed
description Deterioration of materials and structures is an unavoidable fact, and prestressed concrete structures are not an exception. The evaluation of load-carrying capacity and remaining service life includes collecting various information. However, one type of information is essential and the most important, the state of prestressing, which inevitably decreases over time. Currently, many possible methods for the evaluation of prestressing are available. These techniques are part of the structural assessment and provide residual prestressing force value which is later used in the evaluation process. Therefore, it is suitable to provide the value of prestressing force based on certain probabilistic backgrounds. This study addresses the determination of residual prestressing force in pre-tensioned railway sleepers one year after their production, using the so-called Bayesian approach. This technique is focused on the validation of results obtained from the application of the non-destructive indirect saw-cut method. The Bayesian approach considers analytic calculation as the primary method of prestressing determination. In this paper, Monte Carlo simulation was used to determine the total variability that defines all Bayesian systems of probability functions. Specifically, a total of 1000 simulations was applied, and the current random vector of prestressing force derived from the analytical calculation has been assumed as a normally distributed function. Finally, obtained results for different depths of saw-cuts are compared. The results of the experimental and statistical determination of residual prestressing force provide its value with a 95% confidence level. This study suggests that the implementation of the probability approach can be an effective tool for determining prestress losses.
format Online
Article
Text
id pubmed-9145248
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-91452482022-05-29 Determination of Prestress Losses in Existing Pre-Tensioned Structures Using Bayesian Approach Moravčík, Martin Kraľovanec, Jakub Materials (Basel) Article Deterioration of materials and structures is an unavoidable fact, and prestressed concrete structures are not an exception. The evaluation of load-carrying capacity and remaining service life includes collecting various information. However, one type of information is essential and the most important, the state of prestressing, which inevitably decreases over time. Currently, many possible methods for the evaluation of prestressing are available. These techniques are part of the structural assessment and provide residual prestressing force value which is later used in the evaluation process. Therefore, it is suitable to provide the value of prestressing force based on certain probabilistic backgrounds. This study addresses the determination of residual prestressing force in pre-tensioned railway sleepers one year after their production, using the so-called Bayesian approach. This technique is focused on the validation of results obtained from the application of the non-destructive indirect saw-cut method. The Bayesian approach considers analytic calculation as the primary method of prestressing determination. In this paper, Monte Carlo simulation was used to determine the total variability that defines all Bayesian systems of probability functions. Specifically, a total of 1000 simulations was applied, and the current random vector of prestressing force derived from the analytical calculation has been assumed as a normally distributed function. Finally, obtained results for different depths of saw-cuts are compared. The results of the experimental and statistical determination of residual prestressing force provide its value with a 95% confidence level. This study suggests that the implementation of the probability approach can be an effective tool for determining prestress losses. MDPI 2022-05-16 /pmc/articles/PMC9145248/ /pubmed/35629575 http://dx.doi.org/10.3390/ma15103548 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Moravčík, Martin
Kraľovanec, Jakub
Determination of Prestress Losses in Existing Pre-Tensioned Structures Using Bayesian Approach
title Determination of Prestress Losses in Existing Pre-Tensioned Structures Using Bayesian Approach
title_full Determination of Prestress Losses in Existing Pre-Tensioned Structures Using Bayesian Approach
title_fullStr Determination of Prestress Losses in Existing Pre-Tensioned Structures Using Bayesian Approach
title_full_unstemmed Determination of Prestress Losses in Existing Pre-Tensioned Structures Using Bayesian Approach
title_short Determination of Prestress Losses in Existing Pre-Tensioned Structures Using Bayesian Approach
title_sort determination of prestress losses in existing pre-tensioned structures using bayesian approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9145248/
https://www.ncbi.nlm.nih.gov/pubmed/35629575
http://dx.doi.org/10.3390/ma15103548
work_keys_str_mv AT moravcikmartin determinationofprestresslossesinexistingpretensionedstructuresusingbayesianapproach
AT kralovanecjakub determinationofprestresslossesinexistingpretensionedstructuresusingbayesianapproach