Analysis of Empirical Models for Predicting the Rupture Force in Four-Pile Caps
Technical literature provides experimental campaign results for four-pile caps with significant value in structural engineering. However, failure modes and measurement of these specimens are particularly challenging due to their volumetric nature. These experimental records are frequently utilized t...
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2025-01-01
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author | Raphael Saverio Spozito André Luis Christoforo Fernando Menezes de Almeida Filho Rodrigo Gustavo Delalibera Elvys Dias Reis André Luís Lima Velame Branco |
author_facet | Raphael Saverio Spozito André Luis Christoforo Fernando Menezes de Almeida Filho Rodrigo Gustavo Delalibera Elvys Dias Reis André Luís Lima Velame Branco |
author_sort | Raphael Saverio Spozito |
collection | DOAJ |
description | Technical literature provides experimental campaign results for four-pile caps with significant value in structural engineering. However, failure modes and measurement of these specimens are particularly challenging due to their volumetric nature. These experimental records are frequently utilized to evaluate analytical models focusing on less conservative than normative models to predict rupture force. Moreover, recent studies emphasize the necessity of developing simplified predictive models. In this context, the objective of this study was to evaluate the feasibility of regression models for estimating the rupture force associated with strut failure. The evaluation was based on a commonly used database and employed analysis of variance (ANOVA) at a 5% significance level to identify critical variables. The regression models were developed with variable interactions incorporated into the equations in three forms: (i) without interaction, (ii) with linear interaction, and (iii) with quadratic interaction. An analysis of the developed regression models identified a model with satisfactory accuracy. This model achieved an average predicted force ratio of 1.00 (COV = 14%) for the database and 1.03 (COV = 16.68%) for extrapolated numeric models in finite elements with the concrete damaged and plasticity (CDP) constitutive model, initially calibrated with experimental tests. A methodology was proposed to assist in the initial design of four-pile caps. |
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id | doaj-art-694b416ad50c43c6bad657b8ce5b48cb |
institution | Kabale University |
issn | 2079-3197 |
language | English |
publishDate | 2025-01-01 |
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series | Computation |
spelling | doaj-art-694b416ad50c43c6bad657b8ce5b48cb2025-01-24T13:27:49ZengMDPI AGComputation2079-31972025-01-011311810.3390/computation13010018Analysis of Empirical Models for Predicting the Rupture Force in Four-Pile CapsRaphael Saverio Spozito0André Luis Christoforo1Fernando Menezes de Almeida Filho2Rodrigo Gustavo Delalibera3Elvys Dias Reis4André Luís Lima Velame Branco5Department of Civil Engineering, Federal Institute of São Paulo, Votuporanga 15503-110, São Paulo, BrazilDepartment of Civil Engineering, Federal University of São Carlos, São Carlos 13565-905, São Paulo, BrazilDepartment of Civil Engineering, Federal University of São Carlos, São Carlos 13565-905, São Paulo, BrazilDepartment of Civil Engineering, Federal University of Uberlândia, Uberlândia 38400-902, Minas Gerais, BrazilDepartment of Civil Engineering, Federal Center for Technological Education of Minas Gerais, Belo Horizonte 30421-169, Minas Gerais, BrazilCivil Engineering, ALL Velame–Structural Desing, São Carlos 13560-250, São Paulo, BrazilTechnical literature provides experimental campaign results for four-pile caps with significant value in structural engineering. However, failure modes and measurement of these specimens are particularly challenging due to their volumetric nature. These experimental records are frequently utilized to evaluate analytical models focusing on less conservative than normative models to predict rupture force. Moreover, recent studies emphasize the necessity of developing simplified predictive models. In this context, the objective of this study was to evaluate the feasibility of regression models for estimating the rupture force associated with strut failure. The evaluation was based on a commonly used database and employed analysis of variance (ANOVA) at a 5% significance level to identify critical variables. The regression models were developed with variable interactions incorporated into the equations in three forms: (i) without interaction, (ii) with linear interaction, and (iii) with quadratic interaction. An analysis of the developed regression models identified a model with satisfactory accuracy. This model achieved an average predicted force ratio of 1.00 (COV = 14%) for the database and 1.03 (COV = 16.68%) for extrapolated numeric models in finite elements with the concrete damaged and plasticity (CDP) constitutive model, initially calibrated with experimental tests. A methodology was proposed to assist in the initial design of four-pile caps.https://www.mdpi.com/2079-3197/13/1/18finite elementsfour-pile capsnumerical modellingregression modelsreinforced concretestatistical analysis |
spellingShingle | Raphael Saverio Spozito André Luis Christoforo Fernando Menezes de Almeida Filho Rodrigo Gustavo Delalibera Elvys Dias Reis André Luís Lima Velame Branco Analysis of Empirical Models for Predicting the Rupture Force in Four-Pile Caps Computation finite elements four-pile caps numerical modelling regression models reinforced concrete statistical analysis |
title | Analysis of Empirical Models for Predicting the Rupture Force in Four-Pile Caps |
title_full | Analysis of Empirical Models for Predicting the Rupture Force in Four-Pile Caps |
title_fullStr | Analysis of Empirical Models for Predicting the Rupture Force in Four-Pile Caps |
title_full_unstemmed | Analysis of Empirical Models for Predicting the Rupture Force in Four-Pile Caps |
title_short | Analysis of Empirical Models for Predicting the Rupture Force in Four-Pile Caps |
title_sort | analysis of empirical models for predicting the rupture force in four pile caps |
topic | finite elements four-pile caps numerical modelling regression models reinforced concrete statistical analysis |
url | https://www.mdpi.com/2079-3197/13/1/18 |
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