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Generalized Regression Equation to Predict CMOD of Cracked Steel Fibre Reinforced Concrete Under Flexural Fatigue Loading
https://orcid.org/http://orcid.org/0000-0001-7614-1908
https://orcid.org/http://orcid.org/0000-0003-2831-1479
https://orcid.org/http://orcid.org/0000-0002-8016-1677
The verification of the fatigue performance of concrete often involves intricate and time-consuming experimental programs. The inherent complexities arising from variations in fibre distribution and orientation within fibre-reinforced concrete is evident when interpreting residual flexural performance results. These variations are particularly pronounced under fatigue loading, given the considerable scatter associated with the phenomenon. Addressing this challenge requires either the development of models that incorporate a logical basis for analysing design uncertainties to ensure a robust evaluation of failure probability, and to calibrate material partial safety coefficients that cover the uncertainties associated to the material performance and the inaccuracies of the models. In this regard, with the aim of proposing a model capable of predicting fatigue behaviour and thereby reducing the time required for fatigue tests, a conceptual model is presented herein. This model, formulated in a generalized form equation, considers the slope of the crack mouth opening development evolution versus the number of cycles curve for a cracked section subjected to a fatigue load that mobilizes the residual flexural tensile strength for CMOD = 0.5 mm. To validate the regression equation, a database of pre-cracked 5C strength class SFRC notched beam subjected to flexural fatigue extracted from existing literature is considered. By adopting mean values of CMOD and known strength at pre-crack, the equation proves to be capable to predict CMOD for an estimated number of cycles.
Generalized Regression Equation to Predict CMOD of Cracked Steel Fibre Reinforced Concrete Under Flexural Fatigue Loading
https://orcid.org/http://orcid.org/0000-0001-7614-1908
https://orcid.org/http://orcid.org/0000-0003-2831-1479
https://orcid.org/http://orcid.org/0000-0002-8016-1677
The verification of the fatigue performance of concrete often involves intricate and time-consuming experimental programs. The inherent complexities arising from variations in fibre distribution and orientation within fibre-reinforced concrete is evident when interpreting residual flexural performance results. These variations are particularly pronounced under fatigue loading, given the considerable scatter associated with the phenomenon. Addressing this challenge requires either the development of models that incorporate a logical basis for analysing design uncertainties to ensure a robust evaluation of failure probability, and to calibrate material partial safety coefficients that cover the uncertainties associated to the material performance and the inaccuracies of the models. In this regard, with the aim of proposing a model capable of predicting fatigue behaviour and thereby reducing the time required for fatigue tests, a conceptual model is presented herein. This model, formulated in a generalized form equation, considers the slope of the crack mouth opening development evolution versus the number of cycles curve for a cracked section subjected to a fatigue load that mobilizes the residual flexural tensile strength for CMOD = 0.5 mm. To validate the regression equation, a database of pre-cracked 5C strength class SFRC notched beam subjected to flexural fatigue extracted from existing literature is considered. By adopting mean values of CMOD and known strength at pre-crack, the equation proves to be capable to predict CMOD for an estimated number of cycles.
Generalized Regression Equation to Predict CMOD of Cracked Steel Fibre Reinforced Concrete Under Flexural Fatigue Loading
https://orcid.org/http://orcid.org/0000-0001-7614-1908
https://orcid.org/http://orcid.org/0000-0003-2831-1479
https://orcid.org/http://orcid.org/0000-0002-8016-1677
The verification of the fatigue performance of concrete often involves intricate and time-consuming experimental programs. The inherent complexities arising from variations in fibre distribution and orientation within fibre-reinforced concrete is evident when interpreting residual flexural performance results. These variations are particularly pronounced under fatigue loading, given the considerable scatter associated with the phenomenon. Addressing this challenge requires either the development of models that incorporate a logical basis for analysing design uncertainties to ensure a robust evaluation of failure probability, and to calibrate material partial safety coefficients that cover the uncertainties associated to the material performance and the inaccuracies of the models. In this regard, with the aim of proposing a model capable of predicting fatigue behaviour and thereby reducing the time required for fatigue tests, a conceptual model is presented herein. This model, formulated in a generalized form equation, considers the slope of the crack mouth opening development evolution versus the number of cycles curve for a cracked section subjected to a fatigue load that mobilizes the residual flexural tensile strength for CMOD = 0.5 mm. To validate the regression equation, a database of pre-cracked 5C strength class SFRC notched beam subjected to flexural fatigue extracted from existing literature is considered. By adopting mean values of CMOD and known strength at pre-crack, the equation proves to be capable to predict CMOD for an estimated number of cycles.
Generalized Regression Equation to Predict CMOD of Cracked Steel Fibre Reinforced Concrete Under Flexural Fatigue Loading
RILEM Bookseries
Mechtcherine, Viktor (editor) / Signorini, Cesare (editor) / Junger, Dominik (editor) / Carlesso, Débora Martinello (author) / Bairán, Jesús Miguel (author) / de la Fuente Antequera, Albert (author)
RILEM-fib International Symposium on Fibre Reinforced Concrete ; 2024 ; Dresden, Germany
Transforming Construction: Advances in Fiber Reinforced Concrete ; Chapter: 64 ; 529-536
RILEM Bookseries ; 54
2024-09-12
8 pages
Article/Chapter (Book)
Electronic Resource
English
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