12
1 Static Mechanical Properties of UHPCC
Fig. 1.10 Failure patterns of
UHPCC specimens with
a no mixing fiber
b micro-straight fiber
c hooked fiber, Ren et al.
(2018), copyright 2020, with
permission from Elsevier
of silica fume which could make UHPCC more brittle. Compared with the plain
UHPCC specimens, the interaction (i.e., bonding and slipping) between steel fiber
and matrix makes the ductile failure of the UHPCC specimens, which remain nearly
unseparated after the axial compression, as shown in Fig. 1.10.
Table 1.5 lists the test results of the axial compressive strength, compressive
elastic modulus and Poisson’s ratio from the axial compressive test. “—” denotes
that the data is not collected due to the brittle characteristics of UHPCC, which
makes the specimen collapse before reaching the peak stress. Figure 1.11 further
illustrates the effects of steel fiber content and type. It can be derived that, (i) the
steel fiber type has little influence on the axial compressive strength, compressive
elastic modulus and Poisson’s ratio of UHPCC; (ii) the axial compressive strengths
of UHPCC obviously increase with rising the steel fiber content from 0% (~100 MPa)
up to 1.0% (~120 MPa), while the values of that almost keep unchanged with the
volumetric ratio further increasing. The reason may lie in that, increasing the steel
fiber content could increase the bonding strength at fiber-matrix interface, which can
restraint the lateral cracking of specimens to some extent. When the axial stress of
the specimen reaches a certain value, i.e., nearly 120 MPa at present, the bonding
strength is lower than the lateral stress, which leads to the formation of cracks and the
specimens are broken. Thus the axial compressive strength could not further increase
by increasing the steel fiber content; (iii) the steel fiber content has little effect on
the compressive elastic modulus and Poisson’s ratio of UHPCC, and the averaged
values of which are 43.8GPa and 0.23. As we know, the compressive elastic modulus
E is dominated by the matrix and could be predicted as a first approximation by Ref.
(Wille et al. 2014).
E = (1 − V f )E m + V f E s
(1.1)
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