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RISS 인기검색어
- 검색키워드
- 저자 : Jacek Katzer (검색결과 2 건)
- 무료
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Mechanical behaviour of steel fibre reinforced SCC after being exposed to fire
Ponikiewski, Tomasz,Katzer, Jacek,Kilijanek, Adrian,Kuzminska, Elzbieta Techno-Press 2018 Advances in concrete construction Vol.6 No.6
The focus of this paper is given to the investigation of mechanical properties of steel fibre reinforced self-compacting concrete after being exposed to fire. The research programme covered tests of two sets of beams: specimens subjected to fire and specimens not subjected to fire. The fire test was conducted in an environment mirroring one of possible real fire situations where concrete surface for an extended period of time is directly exposed to flames. Micro-cracking of concrete surface after tests was digitally catalogued. Compressive strength was tested on cube specimens. Flexural strength and equivalent flexural strength were tested according to RILEM specifications. Damages of specimens caused by spalling were assessed on a volumetric basis. A comparison of results of both sets of specimens was performed. Significant differences of all tested properties between two sets of specimens were noted and analysed. It was proved that the limit of proportionality method should not be used for testing fire damaged beams. Flexural characteristics of steel fibre reinforced self-compacting concrete were significantly influenced by fire. The influence of fire on properties of steel fibre reinforced self-compacting concrete was discussed.
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Fast classification of fibres for concrete based on multivariate statistics
Paweł K. Zarzycki,Jacek Katzer,Jacek Domski 사단법인 한국계산역학회 2017 Computers and Concrete, An International Journal Vol.20 No.1
In this study engineered steel fibres used as reinforcement for concrete were characterized by number of key mechanical and spatial parameters, which are easy to measure and quantify. Such commonly used parameters as length, diameter, fibre intrinsic efficiency ratio (FIER), hook geometry, tensile strength and ductility were considered. Effective classification of various fibres was demonstrated using simple multivariate computations involving principal component analysis (PCA). Contrary to univariate data mining approach, the proposed analysis can be efficiently adapted for fast, robust and direct classification of engineered steel fibres. The results have revealed that in case of particular spatial/geometrical conditions of steel fibres investigated the FIER parameter can be efficiently replaced by a simple aspect ratio. There is also a need of finding new parameters describing properties of steel fibre more precisely.
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