**Published at : ** 19 Jul 2021

**Volume :** **IJtech**
Vol 12, No 3 (2021)

**DOI :** https://doi.org/10.14716/ijtech.v12i3.3355

Ulhaq, N.D., Andayani, R. 2021. Normal Concrete Mix Design based on the Isoresponse of Slump as a Function of Specific Surface Area of Aggregate and Cement Paste-Aggregate Ratio.

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Nabil Dhiya Ulhaq | Department of Civil Engineering, Faculty of Civil Engineering and Planning, Gunadarma University, Depok 16424, Indonesia |

Relly Andayani | Department of Civil Engineering, Faculty of Civil Engineering and Planning, Gunadarma University, Depok 16424, Indonesia |

Abstract

Many methods of normal concrete mix design produce
the same proportion of cement and water content of concrete for different
specific surface area of aggregate. Therefore, they often produce inappropriate
workability of fresh concrete in the first batch. In the end, several trial
batch adjustments are required by increasing or decreasing cement paste for
reaching the required slump. This research aims to find out the correlation
between specific surface area of aggregate and cement paste-aggregate ratio
(C/A) to slump in a constant water-cement ratio (W/C) in normal concrete. This
correlation will be used as an alternative method of normal concrete mix
design. First, the new fine aggregate was established by modifying natural fine
aggregate gradation. Then, two reference mixtures with these natural and
modified fine aggregates were designed based on SNI 03-2834-2000. From each of
these mixtures, the water content was added and reduced at multiple of 10 kg/m^{3}
in a constant water-cement ratio until the measured slumps of samples had
approached or reached 6 and 18 cm. Thus, different specific surface area of
aggregate, cement paste-aggregate ratio, and slump could be known. Then, an
isoresponse is developed to present the correlation between these variables.
Finally, other mixtures are designed based on this isoresponse to validate it.
The isoresponse is considered satisfactory if the measured slump of the
validation mixtures does not deviate more than 2 cm of the required slump. The
result shows that the measured slumps of validation mixtures had maximum
deviations of 1 cm only. It means that the isoresponse of slump as a function
of specific surface area of aggregate and cement paste-aggregate ratio can be
used to predict the slump of a mixture and also as an alternative method of
normal concrete mix design.

Cement paste-aggregate ratio; Isoresponse; Normal concrete mix design; Slump; Specific surface area of aggregate

Introduction

Concrete is a favoured building material due to its ease of production and use (Han et al., 2016). Along with the increasing use of concrete as a building material, concrete improvement was also carried out by researchers in the past few years. One way to improve concrete mixtures is to do experimental research about the possibility of using other concrete constituents as additives or substitutions. For example, Yadav et al. (2018) that have conducted research on high range replacement of normal aggregates with recycled aggregates. Likewise, Eddhie (2017) developed mathematical equations that account for the relationship between the content of nanosilica and the mechanical properties of concrete so it
can be applied to any concrete mixture. The
improvement of concrete mixtures can also be done
by finding the influence of various variables and their correlation that affect
the properties of fresh and hardened concrete.

Amini et al. (2019) have investigated the relationship
between paste ingredients for achieving an optimum paste-to-void volume ratio
to meet given performance requirements. Curing as a variable that affects the
properties of concrete has also been taken to the next level, Nie et al. (2016) explored the internal curing as
a way of overcoming the disadvantages associated with heat curing and for
improving the performance of heat-cured concrete. Another way to improve
concrete mixtures is by developing optimum proportioning of concrete. In this
case, the new method of concrete mixtures design can also be developed. Yeh (2007) applied analytical methods by using
Computer-Aided Design system to search for the optimum mixture of concrete
composition. Moreover, Yong et al. (2018)
have developed a new method of high-performance concrete mixture design based
on the 4-parameters compressible packing model of Packing Density Theory. Ahmad and Alghamdi (2014) also conducted a
statistical analysis of experimental data and developed mathematical
polynomials regression to obtain an approach in the optimum proportioning of
concrete mixtures. Actually, there is a possibility that there are other ways
to improve the concrete mixtures besides those already mentioned. The point is
how this concrete mixtures improvement produces concrete that is more
satisfying. One factor that shows concrete satisfaction is workability and it
can be influenced by many variables such as the specific surface area of
aggregate.

ACI (2008) 238.1R-08 explains that the specific surface area of
aggregate is a derivative of the factors that affect the workability of
concrete. Hughes (1973) explained that the
specific surface area of aggregate can represent the gradation of an aggregate as
a single numerical value or commonly known as grading modulus. It can be
calculated by simplifying the specific surface area of aggregate as the surface
area per unit volume of spheres which pass the same sieve sizes as the actual
aggregate. Moreover, other methods for quantifying the specific surface area of
aggregate have developed in recent studies, such as using imaging techniques,
developed mathematical models, Brunauer-Emmett-Teller model, etc. (Rabbani et al., 2014; Panda et al., 2016; Zhang and Luo,
2018). Tattersall (1991) explains
that specific surface area of aggregate is the ratio of the total surface area
to the total mass or volume, and is measured in m^{2}/kg or m^{2}/m^{3}.
In concrete, this means that the area of surface to be coated and lubricated by
finer particles and by cement paste is greater and thus, other things being
equal, it would be expected that the finer the fine aggregate, the less
workable the concrete.

However,
there are many mix design standard methods that do not accommodate specific
surface area of aggregate as a variable that influence concrete. SNI
03-2834-2000 and IS 10262:2009 as standard methods in concrete mix design in
Indonesia and India classify fine aggregate gradations into four grading zones.
Moreover, the results of mix design will produce the same proportion of water
and cement content for specific grading zone and required slump. However
actually, all fine aggregates classified into the same grading zone can have
specific surface areas of aggregate that are very different from each other. In
British method which was presented by Teychenné et
al. (1997), the proportion of fine aggregate is determined based on the
percentage of fine aggregate that passes 600 µm sieve. In fact, even though
there are two fine aggregates with the same percentage of 600 µm of sieve
passing, they likely have very different specific surface areas of aggregate.
In ACI (2002) 211.1-91, the fineness modulus
of fine aggregate determines the proportion of coarse and fine aggregates in a
mixture. However, the fineness modulus actually cannot describe the specific
surface area of aggregate. In this case, it is possible for two fine aggregates
to have the same fineness modulus but actually, they have different specific
surface areas of aggregate. Likewise, for SNI 7656:2012 which is an adoption of
ACI (2002) 211.1-91 and is the most recent
standard method in concrete mix design in Indonesia. In the end, concrete
mixtures that were designed using those standard methods require several trial
batch adjustments by increasing or decreasing cement paste for reaching the
required slump.

In the
present study, the effort has been made by changing the value of cement
paste-aggregate ratio (C/A) of concrete mixtures. These changes will affect the
value of the specific surface area of aggregate and slump of concrete mixtures.
Thus, the correlation between specific surface area of aggregate, cement
paste-aggregate ratio, and slump can be presented in the form of an
isoresponse, or what can be known as a contour plot. Sonebi (2004) has
also used isoresponse to present the relationship of several variables in
concrete, such as W/C, cement content, slump flow, fluidity loss, compressive
strength, et cetera. This is because isoresponse is very easy to present
relationships between three or more variables in one form. Finally, from the
isoresponse developed in this study, it is expected that the measured slump of
a concrete mixture can be predicted. Furthermore, this isoresponse is also
expected to be used as a new method of normal concrete mix design.

Conclusion

Based
on the experimental results in this study, the following conclusions have been
drawn: (1) Indeed there is a correlation between specific surface area of
aggregate and cement paste-aggregate ratio to slump which can be presented in
an isoresponse. The greater the specific surface area of aggregate, the slump
value will be smaller. Otherwise, the greater the cement paste-aggregate ratio,
the slump value will be even greater; (2) From that correlation, a new alternative method of mix design has been
developed. The advantage of this new alternative method is that a mixture of
concrete with specific slump values can be designed. In contrast to the British
Standard and Indonesian Standard methods which classify required slump in four
ranges, which will complicate when designing concrete mixtures with slump
values that are more specific; (3) In
addition, a new method for predicting slump values of a concrete mixture also
has been developed using that correlation. This method is a new thing because
only by looking at the proportion of concrete materials and aggregate
gradations, the slump value of the concrete mixture can be predicted without
mixing the concrete and testing the slump before; (4) Improvements are still
needed on these methods, it is recommended to examine variations in W/C or
other variables that can affect slump or other variables that can affect slump.

Supplementary Material

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