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Derivation of dynamic material properties of steel-fibre-reinforced concrete using kernel regression

Wang, Ying, Hao, Hong and Hao, Yifei 2015, Derivation of dynamic material properties of steel-fibre-reinforced concrete using kernel regression, in ICPS3 2015 : Design and Analysis of Protective Structures : Proceedings of the 3rd International Conference on Protective Structures, Centre for Infrastructure Performance and Reliability, The University of Newcastle, Callaghan, N.S.W., pp. 679-685.

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Title Derivation of dynamic material properties of steel-fibre-reinforced concrete using kernel regression
Author(s) Wang, Ying
Hao, Hong
Hao, Yifei
Conference name Protective Structures. Conference (3rd : 2015 : Newcastle, N.S.W.)
Conference location Newcastle, N.S.W.
Conference dates 3-6 Feb. 2015
Title of proceedings ICPS3 2015 : Design and Analysis of Protective Structures : Proceedings of the 3rd International Conference on Protective Structures
Editor(s) Stewart, Mark
Netherton, Michael
Publication date 2015
Start page 679
End page 685
Total pages 7
Publisher Centre for Infrastructure Performance and Reliability, The University of Newcastle
Place of publication Callaghan, N.S.W.
Keyword(s) steel-fibre-reinforced concrete
kernel regression
impact tests
split Hopkinson pressure bar
Summary The reliable and efficient design of steel-fibre-reinforced concrete (SFRC) structures requires clear knowledge of material properties. Since the locations and orientations of aggregates and fibres in concrete are intrinsically random, testing results from different specimens vary, and it needs hundreds or even thousands of specimens and tests to derive the unbiased statistical distributions of material properties by using traditional statistical techniques. Therefore, few statistical studies on the SFRC material properties can be found in literature. In this study, high-rate impact test results on SFRC using split Hopkinson pressure bar are further analysed. The influences of different strain rates and various volume fractions of fibres on compressive strength of SFRC specimens under dynamic loadings will be quantified, by using kernel regression, a kernel-based nonparametric statistical method. Several kernel estimators and functions will be compared. This technique allows one to derive an unbiased statistical estimation from limited testing data. Therefore it is especially useful when the testing data is limited.
ISBN 9780987114372
Language eng
Field of Research 090506 Structural Engineering
Socio Economic Objective 870501 Civil Building Management and Services
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2015, University of Newcastle
Persistent URL http://hdl.handle.net/10536/DRO/DU:30083638

Document type: Conference Paper
Collection: School of Engineering
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