An efficient method to derive statistical mechanical properties of concrete reinforced with spiral-shaped steel fibres in dynamic tension

Steel-fibre-reinforced concrete (SFRC) has been recognised as an effective solution to resist impact loading on structures. The reliable application and efficient design of SFRC structures depends on the knowledge of its mechanical properties. Since many important factors, including the locations an...

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Main Authors: Wang, Y., Hao, Yifei, Hao, Hong, Huang, X.
Format: Journal Article
Published: Elsevier BV 2016
Online Access:http://hdl.handle.net/20.500.11937/39870
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author Wang, Y.
Hao, Yifei
Hao, Hong
Huang, X.
author_facet Wang, Y.
Hao, Yifei
Hao, Hong
Huang, X.
author_sort Wang, Y.
building Curtin Institutional Repository
collection Online Access
description Steel-fibre-reinforced concrete (SFRC) has been recognised as an effective solution to resist impact loading on structures. The reliable application and efficient design of SFRC structures depends on the knowledge of its mechanical properties. Since many important factors, including the locations and orientations of fibres and aggregates in concrete and the material properties of concrete matrix, are intrinsically random, the mechanical properties of SFRC present a high level of randomness. To accurately quantify them, effective statistical techniques are indispensable. Using traditional statistical techniques, a large quantity of data, from either experiments or numerical simulations, are needed to derive the correlation between the mechanical properties and the random factors. However, both ways are time-consuming and costly. Therefore, very little information regarding the statistical mechanical properties of SFRC can be found in the current literature. In this study, a kernel-based nonparametric statistical method is proposed to derive the statistical mechanical properties of SFRC with limited number of data. The behaviours of SFRC with randomly distributed spiral-shaped fibres and aggregates under impact loading are simulated using commercial software LS-DYNA. The simulation accuracy is validated by the experimental results. The influences of various volume fractions of fibres on dynamic increase factor (DIF) of the tensile strength of SFRC specimens under dynamic loadings at different strain rates are quantified through a prediction model obtained from kernel regression. The results demonstrate that the proposed method is able to estimate the DIF value of SFRC based on the tensile strength and strain rate, and to derive the statistical mechanical properties of SFRC.
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institution Curtin University Malaysia
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publishDate 2016
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spelling curtin-20.500.11937-398702019-09-02T07:22:15Z An efficient method to derive statistical mechanical properties of concrete reinforced with spiral-shaped steel fibres in dynamic tension Wang, Y. Hao, Yifei Hao, Hong Huang, X. Steel-fibre-reinforced concrete (SFRC) has been recognised as an effective solution to resist impact loading on structures. The reliable application and efficient design of SFRC structures depends on the knowledge of its mechanical properties. Since many important factors, including the locations and orientations of fibres and aggregates in concrete and the material properties of concrete matrix, are intrinsically random, the mechanical properties of SFRC present a high level of randomness. To accurately quantify them, effective statistical techniques are indispensable. Using traditional statistical techniques, a large quantity of data, from either experiments or numerical simulations, are needed to derive the correlation between the mechanical properties and the random factors. However, both ways are time-consuming and costly. Therefore, very little information regarding the statistical mechanical properties of SFRC can be found in the current literature. In this study, a kernel-based nonparametric statistical method is proposed to derive the statistical mechanical properties of SFRC with limited number of data. The behaviours of SFRC with randomly distributed spiral-shaped fibres and aggregates under impact loading are simulated using commercial software LS-DYNA. The simulation accuracy is validated by the experimental results. The influences of various volume fractions of fibres on dynamic increase factor (DIF) of the tensile strength of SFRC specimens under dynamic loadings at different strain rates are quantified through a prediction model obtained from kernel regression. The results demonstrate that the proposed method is able to estimate the DIF value of SFRC based on the tensile strength and strain rate, and to derive the statistical mechanical properties of SFRC. 2016 Journal Article http://hdl.handle.net/20.500.11937/39870 10.1016/j.conbuildmat.2016.07.140 Elsevier BV fulltext
spellingShingle Wang, Y.
Hao, Yifei
Hao, Hong
Huang, X.
An efficient method to derive statistical mechanical properties of concrete reinforced with spiral-shaped steel fibres in dynamic tension
title An efficient method to derive statistical mechanical properties of concrete reinforced with spiral-shaped steel fibres in dynamic tension
title_full An efficient method to derive statistical mechanical properties of concrete reinforced with spiral-shaped steel fibres in dynamic tension
title_fullStr An efficient method to derive statistical mechanical properties of concrete reinforced with spiral-shaped steel fibres in dynamic tension
title_full_unstemmed An efficient method to derive statistical mechanical properties of concrete reinforced with spiral-shaped steel fibres in dynamic tension
title_short An efficient method to derive statistical mechanical properties of concrete reinforced with spiral-shaped steel fibres in dynamic tension
title_sort efficient method to derive statistical mechanical properties of concrete reinforced with spiral-shaped steel fibres in dynamic tension
url http://hdl.handle.net/20.500.11937/39870